ALBERT

Description: The operation of pumps imposes significant costs on a water distribution system for energy supply and pumps maintenance. To derive an optimum pumps scheduling program, this study presents a multiobjective optimization problem with the objective functions of 1- energy cost and 2- the number of pump switches. The optimization of both objective functions together leads to a multiobjective constrained optimization problem. To solve the problem, the Non-Dominated Sorting Genetic Algorithm, version II, (NSGA-II) is coupled to the EPANET hydraulic simulation model. For constraint handling, some modifications are introduced to the standard NSGA-II to make it self-adaptive through which all constraints of the problem are automatically satisfied. Application of the model to a test example and a real pipe network verifies that the proposed scheme is computationally efficient and reliable. Also, optimization of the real pipe network reveals that by a careful pump scheduling program the total number of pump switches even in optimum operations could be decreased by 69% while the energy cost increases at most by 10%.

Description: A nested optimization approach is proposed to solve capacity expansion problems of multiquality water supply systems. The problem to be solved consists of determining the infrastructure that should be built and/or rehabilitated at a specific time. This decision should be taken in a long-term planning perspective. It should consider how the operation will be performed to satisfy demand and water quality requirements by using multiple sources with different water quality at the source, take into account the temporal and spatial distribution of the water resources available and remain aware of the environmental impacts. In addition, decision processes which do not appropriately consider inherent uncertainties (e.g., hydrological, demographic, and technological uncertainties) can lead to suboptimal solutions. Here, uncertainty is handled using scenario planning with the aim of finding expansion solutions that can be expected to perform well under a set of possible future situations (or scenarios). The solution method combines simulated annealing with nonlinear programming to determine the solution to the nested optimization problem.

Description: Conflict-resolution models can be used as practical approaches to consider the contradictions and trade-offs between the involved stakeholders in integrated water resource management. These models are utilized to reach an optimal solution considering agents interactions. In this paper, a new methodology is developed based on multi-objective optimization model (NSGA-II), groundwater simulation model, M5P model tree, fallback bargaining procedures and social choice rules to determine the optimal groundwater management policies with an emphasis on resolving conflicts between stakeholders. By incorporating the multi-objective simulation-optimization model and bargaining methods, the optimal groundwater allocation policies are determined and the preferences of the stakeholders as well as social criteria such as justice are also considered. The obtained data set, based on Monte Carlo analysis of calibrated MODFLOW model, is used for training and validating the M5P meta-models. The validated M5P meta-models are linked with NSGA-II to determine the trade-off curve (Pareto front) for the objectives. Social choice rule and fallback bargaining methods, as conflict-resolution models, are applied to determine the best socio-optimal solution among stakeholders, and their results are compared. The effectiveness of the proposed methodology is verified in a case study of Darian aquifer, Fars province, Iran. Results indicated that the solutions obtained by the proposed conflict-resolution approaches have an appropriate applicability. Total groundwater withdrawal, after applying the optimal groundwater allocations, reduced to 20.85 MCM, resulting in a 4.62 m increase in the mean groundwater level throughout the aquifer.

Description: An integrated approach of system dynamics (SD), orthogonal experimental design (OED) and inexact optimization modeling was proposed for water resources management under uncertainty. The developed method adopted a combination of SD and OED to identify key scenarios within multiple factors, through which interval solutions for water demands could be obtained as input data for consequential optimization modeling. Also, optimal schemes could be obtained in the combination of inexact two-stage stochastic programming and credibility constrained programming. The developed method was applied to a real-world case study for supporting allocation of multiple-source water resources to multiple users in Dalian city within a multi-year context. The results indicated that a lower credibility-satisfaction level would generate higher allocation efficiency, a higher system benefit and a lower system violation risk. The developed model could successfully reflect and address the variety of uncertainties through provision of credibility levels, which corresponds to the decision makers’ preference regarding the tradeoffs between system benefits and violation risks.

Description: In one of the widely used methods to estimate surface runoff - Soil Conservation Service Curve Number (SCS-CN), the antecedent moisture condition (AMC) is categorized into three AMC levels causing irrational abrupt jumps in estimated runoff. A few improved SCS-CN methods have been developed to overcome several in-built inconsistencies in the soil moisture accounting (SMA) procedure that lies behind the SCS-CN method. However, these methods still inherit the structural inconsistency in the SMA procedure. In this study, a modified SCS-CN method was proposed based on the revised SMA procedure incorporating storm duration and a physical formulation for estimating antecedent soil moisture ( V 0 ). The proposed formulation for V 0 estimation has shown a high degree of applicability in simulating the temporal pattern of soil moisture in the experimental plot. The modified method was calibrated and validated using a dataset of 189 storm-runoff events from two experimental watersheds in the Chinese Loess Plateau. The results indicated that the proposed method, which boosted the model efficiencies to 88% in both calibration and validation cases, performed better than the original SCS-CN and the Singh et al. ( 2015 ) method, a modified SCS-CN method based on SMA. The proposed method was then applied to a third watershed using the tabulated CN value and the parameters of the minimum infiltration rate ( f c ) and coefficient ( β ) derived for the first two watersheds. The root mean square error between the measured and predicted runoff values was improved from 6 mm to 1 mm. Moreover, the parameter sensitivity analysis indicated that the potential maximum retention ( S ) parameter is the most sensitive, followed by f c . It can be concluded that the modified SCS-CN method, may predict surface runoff more accurately in the Chinese Loess Plateau.

Description: The sustainability index ( SI ) is a relatively new concept for measuring the performance of water resource systems over long time periods. Its definition is aimed at providing an indication of the integral behaviour of the system with regards to possible undesired consequences if misbalance of available and required waters occurs. SI is initially defined as a product and later reformulated as a geometric mean of performance indicators: reliability, resilience and vulnerability. As an extension of a recently published methodology to compute and use SI , in this paper we propose introducing two more indicators of system performance: (1) reliability of annual firm (safe) water as a system yield and (2) deviation of reservoir levels from corresponding rule curves. The last indicator is of particular importance if there are multi-purpose reservoirs in the system because reservoirs are the most important and sensitive regulators of the water regime within the system. We also propose a framework for assessing system performance in a systematic manner to compute SI at various locations within the system if different operating strategies are applied and, finally, how to evaluate strategies according to the resulting SI by using multi-criteria methods. A case study example from Serbia is used to illustrate the results of measuring sustainability under alternative operating scenarios for a system with three reservoirs and two diversion structures.

Description: Water distribution systems with complex configurations are important urban facilities and the hydraulic analysis is essential for system design, optimization and management. Hydraulic analysis involves the procedure of calculating the hydraulic parameters of nodal pressure heads and pipe flow rates under steady-state condition. The equations governing the heads and flows are nonlinear and the most popular method for solving the equations is the Newton-Raphson method, which is the basis of existing hydraulic simulator (EPANET 2). In this paper, fixed point iteration method is proposed for hydraulic analysis after transformation of the original nonlinear equations. Compared to EPANET 2, the proposed method can analyze a water distribution system without differentiation for the convergence for some problems which cannot be solved by EPANET 2. Three test networks were analyzed by the proposed method and EPANET 2. It is proved that the proposed method could get the convergence after a series of iterations, even in cases that EPANET 2 fail. And the initial values of nodal pressure heads and the specified calculation accuracy are considered to have influences on the calculation procedure.

Description: Reservoirs often play an important role in mitigating water supply problems. However, the implications of climate change are not always considered in reservoir planning and management. This study aimed to address this challenge in the Alto Sabor watershed, northeast Portugal. The study analysed whether or not the shortage of water supply can be effectively addressed through the construction of a new reservoir (two-reservoir system) by considering future climate projections. The hydrological model Soil and Water Assessment Tool (SWAT) was calibrated and validated against daily-observed discharge and reservoir volume, with a good agreement between model predictions and observations. Outputs from four General Circulation Models (GCM) for two scenarios (RCP 4.5 and 8.5) were statistically downscaled and bias-corrected with ground observations. A general increase in temperature is expected in the future while the change in precipitation is more uncertain as per the differences among climatic models. In general, annual precipitation would slightly decrease while seasonal changes would be more significant, with more precipitation in winter and much less in spring and summer. SWAT simulations suggest that the existence of two-reservoir will better solve the water supply problems under current climate conditions compared to a single-reservoir system. However in the future, the reliability of this solution will decrease, especially due to the variability of projections from the different climatic models. The solution to water supply problems in this region, adopted taking only present-day climate into account, will likely be inefficient for water supply management under future climate conditions.

Description: Water quality monitoring networks are usually designed according to statistical approaches and general criteria without a consistent or logical deterministic design strategy. In this research, a deterministic approach for allocating the most sensitive water quality monitoring stations was proposed. This approach was applied on the western part of the Al-Hammar Marsh. Two-dimensional hydrodynamic and water quality simulation models were used to estimate the distribution of total dissolved solids (TDS) within the marsh for all of the expected conditions. Subsequently, the spatial distribution of the variance of TDS was computed based on the results of these models and performed in a Geographic Information System (GIS) database layer. The standard acceptable TDS variation limits of ±5%, land-use map, land-cover map and other main selection criteria of the monitoring stations were set as constraints via GIS database layers. These layers were integrally applied to the variance layer to obtain the locations of the most sensitive monitoring stations. It was concluded that, the most representative monitoring network consists of 46 stations. This number can be reduced to 37 and 29 stations by increasing the acceptable TDS variation limits to ±10% and 15%, respectively. The developed approach can be used with limited data. Moreover, it can be applied to rivers, lakes or wetlands, considering all of the related constraints. In addition, the GIS database can be easily updated and analysed. These features are not available in other methods such as the Sanders method, multiple criteria decision making and dynamic programming approach.

Description: Leak detection and localization in water pipeline networks is of paramount importance to industry, especially in regions where water is scarce. In this paper, we present a novel multi-modal and multi-scale approach for leak detection and localization in water pipeline networks, in which pressure measurements at various points on the network are used to localize the pipe segment in which the leak is occurring, and then the vibration sensors are used to localize the leak within this segment. In some situations where the complete pipeline model is not available, pressure data alone may not be effective in localizing the leak. However, in such a situation, by supplementing pressure data with vibration data, the leak can be localized, as these additional data are easier to acquire at arbitrary points, since vibration sensors are non-invasive. In order to validate the effectiveness of the approach that needs both pressure and vibration data, we simulate the pipeline model using EPANET that includes models for flow and pressure at various points on the pipeline, then integrate the vibration model with it in MATLAB, since EPNAET does not include models for vibration measurements. A case study of a pipeline network is considered, and the proposed scheme is used to detect and localize the leak. Extensive simulation results show the effectiveness of the proposed scheme in providing accurate leak detection and localization.

Description: Mathematical (analytical, numerical and optimization) models are employed in many disciplines including the water resources planning, engineering and management. These models can vary from a simple black-box model to a sophisticated distributed physics-based model. Recently, development and employment of modern optimization methods (MOMs) have become popular in the area of mathematical modeling. This paper overviews the MOMs based on the evolutionary search which were developed over mostly the last 30 years. These methods have wide application in practice from finance to engineering and this paper focuses mostly on the applications in the area of water resources planning, engineering and management. Although there are numerous optimization algorithms, the paper outlines the ones that have been widely employed especially in the last three decades; such as the Genetic Algorithm (GA), Ant Colony (AC), Differential Evolution (DE), Particle Swarm (PS), Harmony Search (HS), Genetic Programming (GP), and Gene Expression Programming (GEP). The paper briefly introduces theoretical background of each algorithm and its applications and discusses the merits and, if any, shortcomings. The wide spectrum of applications include, but not limited to, flood control and mitigation, reservoir operation, irrigation, flood routing, river training, flow velocity, rainfall-runoff processes, sediment transport, groundwater management, water quality, hydropower, dispersion, and aquifers.

Description: The global climate is changing and altering the hydrologic cycle that results in (i) reduction of water supply; (ii) increase in frequency and magnitude of flood and drought events; (iii) damage to the shoreline areas; (iv) increase in irrigation water use; (v) decrease in quality of all freshwater sources; and (vi) increase in functional and operational requirements for the existing water infrastructure. The paper provides the review of water resources management challenges posed by the climate change. In order to provide guidance for including climate change impacts into water management studies, a generic approach is detailed for potential implementation in practice. Methods for selecting global climate models and emission scenarios, followed by bias correction and downscaling are discussed. The paper ends with the description of one practical example, IDF_CC , a web based tool for updating intensity duration frequency curves under changing climate. The tool is designed in response to real needs of water engineering practice and has been in use in Canada since early 2015.

Description: To support sustainable long-term developments and minimize urban sprawl, Low Impact Development (LID) practices have been highlighted for a long time. They are useful, but understanding on LID practices and broadening the LID applications among practitioners is another important task. The main purpose of this study is to understand local professionals’ perceptions on different LID techniques and awareness on their benefits, while also gathering opinions on barriers and incentives. An online survey was delivered to 91 recipients, a diverse pool of stakeholders involved in the Energy Corridor District (ECD) area in Houston, Texas. The majority of the respondents answered that they were familiar with LID. The techniques that have been applied to a larger extent are Detention Ponds and Bioswales. When asked about applying techniques in the future, Retention Ponds, Rain Gardens, Bioswales, and Detention Ponds are highly probable items. Decision-makers identified the major barriers as being the lack of incentives for their application, lack of knowledge of the client, and lack of knowledge of the development team. Education programs would be the most successful incentive, followed by financial incentives and innovations in policy systems. Urban planners have the most expertise in LID practices, followed by architects/landscape architects, while developers were found not to be very familiar with the concepts. This study understands the current and practical opinions about LID from the decision-makers. Different groups understand the importance of education and identified a major barrier as the lack of policy instruments. Some innovation in regulations may elevate proper LID practices.

Description: The assessment of productivity change across companies and over time is of great importance for water utilities managers and regulators. In this paper, for the first time, we apply the Färe-Primont productivity index (FPI) to evaluate the productivity change for the 10 water and sewerage companies (WaSCs) and 12 water only companies (WoCs) in England and Wales during the years 2001–2008. The FPI is the only index that without price data allows making comparisons involving many firms and many periods. The results indicate that during the years 2001–2004 productivity improved which was mainly attributed to gains in efficiency whereas technical change remained constant, the exception being the year 2004. During the years 2005–2008 productivity showed a declining trend and any gains in efficiency were lost to the highly negative technical change on productivity growth. From a policy perspective, it has been illustrated the importance of using a reliable index to compute the productivity change of water companies when the performance of companies is used to set water tariffs. Finally, the decomposition of productivity change into several drivers allows water utilities and managers to identify the main factors on which they should act to improve productivity of the company.

Description: Accurate estimation of flow resistance restricts the quality of the hydraulic model performance. In this study, we try to investigate the seasonal dynamic of the Manning’s roughness coefficient ( n ) based on the one-dimensional hydraulic model HEC-RAS in a German lowland area. We set up four river section models based on the 1 m digital elevation model and field measurements, in which the seasonal roughness factors were calibrated and validated with the gauge record. The results revealed that: 1) the Manning’s n varied from 46% to 135% from the base value in autumn; 2) adopting the seasonal roughness factor improved the quality of the model output; 3) the vegetation condition and water elevation dominated the Manning’s n in summer (April–September) and winter (October–March) half year respectively. Water temperature increased the flow resistence in winter half year; 4) the peak value of Manning’s n appeared in late summer due to the highest biomass, while the minimum roughness occurred in early-spring because of the combined influence of low biomass, high water level and relatively higher temperature. The involvement of seasonal roughness factor improved the model performance and the results are comparable to the previous research of the same area.

Description: In the field of water management, the evaluation of sustainability has no universal methodological approach nor any consensus regarding the definitions of sustainability or sustainable development. There is an essential need therefore for a precise definition of sustainability in different water management fields. This paper deals with the sustainability of one part of urban water management, namely a water supply. A precise definition of a sustainable water supply system is given, together with a methodological framework that quantifies the degree of water supply sustainability. The proposed framework relies on the proposed quasi-strong sustainability concept, its components (dimensions), their particular relationships and corresponding indicators representing individual processes in the water supply system and utility. The processing of indicators is performed through a joint fuzzy logic/neural network (ANFIS) model. In order to evaluate each sustainability component, separate ANFIS models were created whose results were aggregated into a single result (sustainability index). According to the presented framework, sustainability is evaluated for 17 public water supply systems/utilities in Croatia.

Description: The main objective of the present study was to identify the periodic behavior of monthly droughts in Iran. For this purpose, monthly precipitation data obtained from 41 synoptic stations for a period of 22 years (1992–2013) were used. To identify the frequency of different severities of drought, effective drought index (EDI) was calculated at monthly scale and then spectral analysis of time series of EDI was conducted for each station. Temporal stability of these periods was also estimated using the wavelet transform. The results of spectral analysis of monthly droughts in Iran showed that periodicities in time series of Iran’s droughts are very diverse and involve periods of 2 to 22 years. Assessment of temporal stability of periodicities using the wavelet transform also indicated that there is a dominant periodic interval (significant at a level of α = 0.1) only in 8 stations of Ardebil, Iranshahr, Zahedan, Bandar Lengeh, Shahroud, Khorramabad, Oroomieh, and Shahre Kord. Studying the variability of time series of EDI in 41 stations showed that the severity of wet years is declining and the severity of droughts is increasing. It was also observed that periodic intervals were shorter at the beginning but longer at the end of time series. This suggests that the probability of incidence of drought in Iran is increasing. Additionally, a reduction can be observed in interval between incidences of droughts in Iran. This means that the interval between occurrence of droughts were longer at the beginning and then shorter at the end of times series.

Description: Growing water demands as well as inconsistency between water demand and water supply pose new challenges for water resources managers in arid regions. This study examines the strategies to tackle water shortage for a sustainable development in Shahrood, Iran. A contentious plan has been proposed to transfer water from the Caspian Sea in north of Iran to this region. Ensuring sustainable development, however, necessitates a strategic planning for water resources. The study develops all viable strategies for the region using Strengths, Weaknesses, Opportunities, and Threats (SWOT) analysis. Due to inability of the SWOT model to rank the alternatives, the developed strategies are ranked using Multi Criteria Decision Making (MCDM) models based on specified sustainable development criteria. The ranking is implemented using the compensatory models of Simple Additive Weighting (SAW) and Analytical Hierarchy Process (AHP), and the non-compensatory model of ELimination and Choice Translating REality (ELECTRE III). The results of all MCDM models introduce water transfer as the worst strategy for the region. Because of the uncertainty in the relative importance of specified criteria, sensitivity analysis is done for MCDM models by altering the criteria weights. The results show that the ELECTRE III method has lower sensitivity than the SAW and AHP methods to changes in the weights. Also, the compensatory methods exhibits a high dependency to the weights of some dominant criteria. Therefore, this research reveals that the rankings obtained from the ELECTRE III method are more reliable for decision makers to ensure a sustainable development in the region.

Description: A simulation-optimization framework is presented for reliability-based optimal sizing, operation, and water allocation in the Bashar-to-Zohreh inter-basin water transfer project. The problem was formulated as a mixed integer nonlinear program (MINLP), for which two solution approaches were tested, including gradient-based nonlinear programming and simulation-optimization (SO). The SO framework linked the water evaluation and planning system (WEAP) simulation module, benefiting from fast, single-period linear programming, to the multi-objective particle swarm optimization (MOPSO) for multiperiod optimization. The objective functions were minimizing the sizes of the project’s infrastructures and maximizing the reliability of supplying water to agricultural lands. The combination of nonlinear programming and the branch-and-bound algorithm was not able to solve the resulting MINLP. The results of the MOPSO-WEAP framework indicated that the project can supply water for land development in the Dehdasht and Choram agricultural plains, located in the less developed Kohgiluye and Boyer-Ahmad Province of Iran at an acceptable reliability level. For example, for one of the Pareto solutions found corresponding to maximum land development (30,000 ha), an average volume of 237 million cubic meter (MCM) is transferred annually at a 73.2% reliability level with average sizes of water transfer and storage elements. Further, design-operation and hydropower scenarios were also evaluated, and the Pareto solutions were obtained.

Description: Evolutionary algorithms are used widely in optimization studies on water distribution networks. The optimization algorithms use simulation models that analyse the networks under various operating conditions. The solution process typically involves cost minimization along with reliability constraints that ensure reasonably satisfactory performance under abnormal operating conditions also. Flow entropy has been employed previously as a surrogate reliability measure. While a body of work exists for a single operating condition under steady state conditions, the effectiveness of flow entropy for systems with multiple operating conditions has received very little attention. This paper describes a multi-objective genetic algorithm that maximizes the flow entropy under multiple operating conditions for any given network. The new methodology proposed is consistent with the maximum entropy formalism that requires active consideration of all the relevant information. Furthermore, an alternative but equivalent flow entropy model that emphasizes the relative uniformity of the nodal demands is described. The flow entropy of water distribution networks under multiple operating conditions is discussed with reference to the joint entropy of multiple probability spaces, which provides the theoretical foundation for the optimization methodology proposed. Besides the rationale, results are included that show that the most robust or failure-tolerant solutions are achieved by maximizing the sum of the entropies.

Description: It once seemed that all water managers had to do was to develop and manage infrastructure necessary to convert the natural spatial and temporal distributions of water and its quality to that desired by we humans at acceptable levels of reliability and cost. We are increasingly learning there are limits to achieving such goals, and the consequences can impact just about every component in our economy and society. We’re having to conserve, treat, reuse, find alternatives for and generally get smarter about how we develop and manage our natural resources. Furthermore, we must do it in a political environment of conflicting stakeholder expectations and in ways that minimize the damage to our natural environment as well. No one wants their behavior or life style to contribute to an environment of climatic extremes and regional conflicts that are outside the ranges we and our ecosystems can thrive, or even survive. If we who are in the business of developing and applying models for identifying and evaluating ways of improving how we plan, design, and operate water resources infrastructure systems do not address these broader global environmental and social issues, even partially, and in ways that lead to beneficial impacts, and reduced risks to health and economic security risks, what’s our value? Our literature, including this journal, is full of novel and often useful modeling approaches for identifying and evaluating alternative environmental resource systems designs, plans and policies. Is this enough? This paper addresses ways we might, and in my opinion should, as a discipline, extend our planning and management modeling expertise to address a wider range of societal concerns that stem from the impact water has on almost all human activities. How can we better provide and manage water to better serve society? In short how can we water systems analysts, planners and managers better serve humankind as we manage a critical resource everyone and every economy needs?

Description: Transverse mixing coefficient (TMC) is one of the key factors in the modelling of lateral dispersion of pollutants. Several researchers have attempted to estimate this coefficient using various models. However, robust equations that can accurately estimate lateral mixing in both straight and meandering streams are still required. In this study, novel formulae were developed using the hydraulic and geometric parameters of rivers. The multiple linear regression (MLR), genetic programming based symbolic regression (GPSR) and dimensionless parameters were used for this purpose. Two extensive data sets including data from straight channels/streams and meandering ones were employed to develop the formulae. The main advantage of the developed formula for meandering streams is proper consideration of the effects of aspect ratio, friction, and sinuosity. The formulae performances were then compared quantitatively with those of existing ones using accuracy metrics such as RMSE (Root Mean Square Error). The results illustrated that the proposed formulae outperform others in terms of accuracy and can be used for estimating TMC in straight and meandering streams. In addition, the comparison of MLR and GPSR models showed that the latter is marginally more accurate than MLR specially in meandering streams. However, the MLR models presented a more justifiable relationship between the TMC and governing dimensionless parameters. The main advantages of the presented formulae are that they are more accurate than previous models, can be used in both meandering and straight streams; and can be easily implemented in numerical models to estimate the pollutant concentration and mixing length.

Description: The timely repair of City Water Distribution System, a basic guarantee for the life of city residents, requires a reasonable supervision area partition of the City Water Distribution Network (CWDN). In this paper, a graph-theoretic and multi-objective approach for the partition of CWDN is presented. The proposed framework is mainly based on rescue distance and extreme workload of the same area. The rescue distance is expressed by effective distance, which is calculated by the adjustment of straight line distance and seeking smallest value. Extreme workload refers to the average importance of failure nodes belonging to a same crew and needing to be placed in balance. The node importance is coupled with node function importance and node structure importance, and they are calculated using knowledge of Graph Theory. This approach can finish the emergency repair scope partition quickly and easily since it does not rely on precise hydraulic simulation which requires complex calibration processes and computation, while remaining meaningful from a physical and topological point of view. The method is also applied to the analysis of a CWDN and successfully tested, with the result that there emerged a 7.83% decrease of the rescue distance. In addition, the balance of extreme workload was found to be three times higher than the previous.

Description: Drought is considered as a major natural hazard/ disaster, affecting several sectors of the economy and the environment worldwide. Drought, a complex phenomenon can be characterised by its severity, duration, and areal extent. Drought indices for the characterization and the monitoring of drought simplify the complex climatic functions and can quantify climatic anomalies for their severity, duration, and frequency. With this as background drought indices were worked out for Madurai district of Tamil Nadu using DrinC (Drought Indices Calculator) software. DrinC calculates the drought indices viz., deciles, Standard Precipitation Index (SPI), Reconnaissance Drought Index (RDI), Streamflow Drought Index (SDI) by providing a simple, though flexible interface by considering all the factors. The drought of 3, 6 and 9 months as time series can also be estimated. The results showed that drought index of Madurai region by decile method revealed that among the 100 years, 20 years were affected by drought and it is cyclic in nature and occurring almost every 3 to 7 years once repeatedly, except for some continuous period, i.e. , 1923, 1924 and 1985, 1986, etc. During the last five decades, the incidence is higher with 13 events, whereas in the first five decades it was only 7. The SPI and RDI index also followed the similar trend of deciles. However, under SPI and RDI, the severely dry and extremely dry category was only seven years and all other drought years of deciles were moderately dry. Our study indicated that SPI is a better indicator than deciles since here severity can be understood. SDI did not follow the trend similar to SPI or RDI. Regression analysis showed that the SPI and RDI are significantly correlated and if 1st 3 months rainfall data is available one can predict yearly RDI drought index. The results demonstrated that these approaches could be useful for developing preparedness plan to combat the consequences of drought. Findings from such studies are useful tools for devising strategic preparedness plans to combat droughts and mitigate their effects on the activities in the various sectors of the economy.

Description: Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared hydrologic/water quality models including Spreadsheet Tool for the Estimation of Pollutant Load (STEPL)-Purdue, Soil and Water Assessment Tool (SWAT), High Impact Targeting (HIT), Long-Term Hydrologic Impact Assessment (L-THIA), Pollutant Load (PLOAD), Spatially and Temporally Distributed Model for Phosphorus Management (STEM-P), Region 5, and ensemble modeling (using STEPL-Purdue, SWAT, L-THIA, PLOAD, and STEM-P). Model capabilities, inputs, and underlying methods to estimate streamflow, surface runoff, baseflow, nutrients, and sediment were examined. Uncalibrated, calibrated, and validated outputs of these models and uncalibrated ensemble modeling in estimating water quantity and quality for a 41.5 km 2 agricultural watershed in Northeastern Indiana were explored, and suggestions were provided on the selection and use of models. Models need to be selected carefully based on the simulation objectives, data availability, model characteristics, time constraints, and project budgets.

Description: Meshfree methods are often tested in literature for the rectangular domain with uniform aquifer properties (e.g. transmissivity or hydraulic conductivity) and constant groundwater head boundary conditions. In this paper, a multiquadric meshfree (Mfree) groundwater model is developed for a real field irregular domain aquifer system which is capable of incorporating variability like heterogeneity, temporally and spatially varied groundwater head and flow boundary conditions. The developed model is free from the inadequacy of meshing which eventually saves the time on computing resources by calculating the groundwater head-derivatives at different nodes sprinkled over the entire flow domain. Initially, two synthetic problems with pre- existing analytical and grid based results are tested against the presented model. Sensitivity analysis of different parameters like time step size, nodal density and support size of basis function are also investigated. Subsequently Mfree solutions are obtained for a large Mahi Right Bank Canal (MRBC) unconfined aquifer located in Gujarat India. The Mfree solution performance on two synthetic and one real field large aquifer problem revealed that the projected method is advantageous over other grid based simulator in terms of computational time consideration. Such a simulation is preferable in groundwater management models where flow models are coupled with the optimization problem.

Description: Integrated Water Resource Management (IWRM) requires simultaneous consideration of the multiple benefits that attend water. IWRM can also be more challenging in regulatory environments where the resource manager must justify choices and elements of each intervention. This is particularly challenging in the context of urban waterways that have many uses including an ecological function and a source of human amenity. To justify expenditure on maintaining and improving urban waterways for ecological and/or amenity changes regulated utilities must be able to articulate and measure these types of values with at least some degree of precision. This paper presents a generic and systematic framework for understanding the ecological and amenity values of urban waterways. We illustrate deployment of the framework in the case of Melbourne, one of Australia’s fastest growing cities and a location ranked as amongst the most liveable since 2011. We also explore how the results could improve the way we measure benefits in dollar terms.

Description: Public and stakeholder participation in water management is a crucial element in the EU Water Framework Directive (WFD). Theoretically, the WFD identifies several advantages of public participation, such as the better use of knowledge and experiences from different stakeholders, increases in public acceptance and reduced litigation, delays, and inefficiencies in implementation. However, few studies have gone as deep, in practical terms, as the existing difficulty to introduce public participation in water management. The aim of this study was to cover this issue. It aims to conduct a literature review on public participation looking for successful social innovation experiences by the EU member states and also for the main limitations and difficulties of implementation detailing the study of the Spanish case.

Description: Over the last few years water scarcity and pollution have been rapidly growing at both regional and global level. This has generated in many cases increasing intersectoral competition over the use of a limited amount of water resources. To examine the dynamics that such competition may generate in the economy, the present paper proposes a simple dynamic evolutionary model in which two sectors ( A and B ) compete for the use of water and studies the impact of water pricing on the dynamics of the two sectors in the presence of a population of interacting economic agents characterized by imitative behaviors. As it emerges from the model, when water is underpriced a self-enforcing process may be observed driving the economy towards a Pareto-dominated equilibrium. In such equilibrium the economy fully specializes in sector A , characterized by the highest negative impact on the water resource, at the expenses of sector B . The paper shows that a policy of fine tuning that increases water price through the endogenous water pricing mechanism examined in the model can inhibit the convergence of the economy to such an equilibrium point and can progressively shift the system towards the less water-consuming sector. Finally, assuming a Leontief production function and performing numerical simulations, it is shown how a change in water price can affect the dynamics of the model, and that the same results hold also in a more general, three-sector context.

Description: This study extends the PSO-MODSIM model, integrating particle swarm optimization (PSO) algorithm and MODISM river basin decision support system (DSS) to determine optimal basin-scale water allocation, in two aspects. The first is deriving hydrologic state-dependent (conditional) operating rules to better account for drought and high-flow periods, and the second is direct, explicit consideration of sustainability criteria in the model’s formulation to have a better efficiency in basin-scale water allocation. Under conditional operating rules, the operational parameters of reservoir target storage levels and their priority rankings were conditioned on the hydrologic state of the system in a priority-based water allocation scheme. The role of conditional operating rules and policies were evaluated by comparing water shortages associated with objective function values under unconditional and conditional operating rules. Optimal basin-scale water allocation was then evaluated by incorporating reliability, vulnerability, reversibility and equity sustainability indices into the PSO objective function. The extended model was applied for water allocation in the Atrak River Basin, Iran. Results indicated improved distribution of water shortages by about 7.5% using conditional operating rules distinguishing dry, normal and wet hydrologic states. Alternative solutions with nearly identical objective function values were found with sustainability indices included in the model.

Description: Assessing productivity change over time and identifying its determinants is a valuable tool for water regulators when setting water tariffs. However, in a price cap regulatory framework such as in England and Wales policy makers should give attention to quality of service issues. Previous studies that assessed the productivity change of the English and Welsh water industry did not include the lack of quality of service to customers as undesirable outputs. To overcome this limitation, and as a pioneering approach, we estimated the Malmquist-Luenberger Productivity Indicator and its components, efficiency and technical change, for the 10 water and sewerage companies and the 12 water only companies over the period 2001–2008. To explore the role of quality of service to customers on the productivity change over time, we contrasted our results with a conventional measure of productivity change namely the Luenberger productivity indicator. The findings suggest that from 2001 to 2004 water companies made significant efforts to improve the quality of the service provided to customers, whereas after 2005 companies’ performance regarding customer services was considered as poor. Results excluding quality of service variables illustrated that productivity declined during all years evaluated. However, when the quality of service was introduced in the assessment, productivity improved by 4.13 % from 2000 to 2004 whereas it declined by 16.96 % in the following years. From a policy perspective, water utility regulators need to pay attention to quality of service issues when assessing companies’ performance and setting water tariffs under comparative yardstick regimes.

Description: The water footprint has been established as an indicator to assess water use by a product. However, the grey component of the water footprint (GWF) has received the least focus compared to the green and blue components. In developing countries, the GWF estimation is restricted by the availability of data concerning crop practices. The various biophysical and socioeconomic settings configure a system difficult to standardize even for small areas. The objective of this study was to assess the GWF uncertainty due to primary data for the main greenhouse tomato production from Colombia. The GWF for N and P fertilizers and pesticides were estimated based on detailed crop information collected from 2010 to 2013. The uncertainty was evaluated by fitting univariate theoretical distributions to the empirical distributions of the pollutants’ GWFs. Growers applied on average 419.2 and 201.9 kg ha −1 of N and P fertilizers per cycle, respectively. The average rates of application for fungicides and insecticides were 11.8 and 3.5 kg ha −1 , respectively. The average GWF for N and P fertilizers and pesticides were 79, 6182.1 and 223.2 m 3  t −1 , respectively. The empirical distributions of the GWF for N fertilizer and pesticides were fitted to a lognormal distribution while for P fertilizer the Weibull distribution showed the best fit. The pesticides GWF showed the highest coefficient of variation (615.3%), however the results for N and P fertilizers were also high with values of 79.8 and 74.1%, respectively. Additional to the methodological choices involved in the GWF estimation, the primary data is a relevant uncertainty source, which should be considered for systems operating under unstandardized practices. The decision making process to regulate the pollutants losses from the agroecosystem, based on environmental assessments such as the GWF, should consider all sources of uncertainty and address its implications in a quantitatively form.

Description: Urbanization can significantly increase the load on aging, inefficient and already strained sewer infrastructure, resulting in catastrophic pipe failure, unwanted spillage, property damage, and serious threat to public health. Urbanization can also dramatically alter the natural water cycle, resulting in diminished water quality, increased frequency and severity of flooding, channel erosion and destruction of aquatic habitat. Recent advances in smart water network (SWN) modeling technology have played a crucial and growing role in addressing these challenges. SWN technology has equipped practicing engineers with a comprehensive set of analytical decision making tools designed to help them preserve structural integrity, manage and reduce the risks of sewer overflow and urban runoff, improve resiliency and keep their urban drainage networks operating well into the future. These advances propel routine conveyance system analysis from basic planning and design to two-dimensional surface/subsurface flow modeling, real-time operation and control, analytical risk-based asset integrity and condition assessment, and optimal selection and placement of green infrastructure based on cost and effectiveness. SWN is providing critically needed support to federal, state, and local agencies and watershed practitioners — not only in optimizing their integrated water management and adaptation strategies, but in ensuring sustainable drainage, addressing environmental quality restoration and protection needs in urban and developing areas, and improving communities’ resiliency. It is also within the grasp of utilities of all sizes, but they need to seize the opportunity.

Description: The purpose of this study is to evaluate Gharanghu multi-purpose reservoir system (East Azerbaijan, Iran) using efficiency indexes (EIs) affected by climate change. At first, the effects of climate change on inflow to the reservoir, as well as changes in the demand volume over a time interval of 30 years (2040–2069) are reviewed. Simulation results show that inflow to the reservoir is decreased in climate change interval compared to the baseline interval (1971–2000), so that comparison of long-term average monthly inflow to the reservoir in climate change interval is reduced about 25% compared to the baseline. Also, water demand in climate change interval will increase, namely volume of water demand for agricultural, drinking and industrial, and environmental in climate change interval is expected to increase by 20%. The simulation results of the water evaluation and planning (WEAP) model is used to determine EIs of multi-purpose reservoir system. Next, three scenarios of water supply for climate change interval are introduced to WEAP model, keeping variable of parameter related to water demand volume (based on different percentages of supply) and keeping constant of the parameter related to the volume of inflow to the reservoir. Results show that system EIs in climate change interval will have a disadvantage compared to the baseline. So that, reliability, vulnerability, resiliency and flexibility indexes in climate change interval based on 100% of water supply compared to the baseline will decrease 18%, increase 150%, decrease 33%, and decrease 47%, respectively. These indexes based on 85% of supply compared to the baseline will decrease 12%, increase 75%, decrease 30%, and decrease 39%, respectively. Also, those based on 70% of supply compared to the baseline will decrease 1%, will be without change, decrease 18%, and decrease 18%, respectively. Changes in indexes in future interval indicate the need to manage water resource development projects in the basin.

Description: Water companies traditionally deal with the problem of rehabilitation and redesign of municipal water supply system due to the either of aging the existed water supply network and housing development. However, such problems are hemmed in by uncertainty due to their long planning horizons and the fact that the exact prediction of future is impossible. Uncertain data and parameters which are likely to undermine the effectiveness of our decisions in this area, are exacerbated if they are be correlated. Unfortunately, correlated uncertain parameters are the things typically such problems are entangled with. Thus, along with considering all of decision objectives, it is incumbent upon water supply system redesign and rehabilitation decision model to develop methods able to appropriately confront with the correlated uncertainty. This paper introduces a bi-objective robust optimization model capable of handling correlated uncertain parameters in municipal water supply system redesign and rehabilitation problem. This robust optimization framework is able to adjust the level of conservatism, a factor which contributes to the reliability of the system. The proposed mathematical framework is applied for a water supply system inspired from Tehran potable water supply system and then various levels of conservatism and reliability are compared. Numerical results show neglecting uncertainty can lead to significant increase in the total cost and amount of unsatisfied demand.

Description: This paper reviews the development of real time flood forecasting systems from the early 1970 approaches to the recent probabilistic ones. A preliminary discussion on the motivations for developing real time flood forecasting systems is introduced to explain their evolution in the last four to five decades. It will be shown how recent probabilistic flood forecasts are more robust and effective than the traditional deterministic ones. In particular, when combined with Bayesian decision approaches, probabilistic forecasts are the most appropriate tools for rational decision making in flood warning and flood management. Moreover, they allow taking into account the information from several models to be taken into account by combining into a unique predictive density the deterministic predictions of several hydrological or hydraulic models of a different nature, while in the multi-temporal forecasting extensions, they provide to answers questions such as: Which is the probability of overtopping a dyke in the next 24 h? When will this event be more likely to occur during the next 24 h? The work concludes with a discussion on the still unresolved problems, namely how decisions makers can fully take advantage of the probabilistic forecasts and how these forecasts must be communicated to them in order to meet this objective.

Description: The EU Water Framework Directive (WFD) explicitly requires the full cost recovery of water services, including the environmental costs incurred from the damage that water uses inflict on the environment. Although flow regulation by river damming is one of the most prominent human impact on fresh water ecosystems its environmental costs are not properly included in water pricing. This paper presents a novel approach to assessing the environmental costs of flow regulation based on the polluter-pays principle. The methodology includes three steps: ( i ) assessing the admissible range of regulated flow variability, derived from the natural flow regime variability, ( ii ) estimating the daily environmental impact of regulated flows according to deviations from the admissible range of flow variability, and ( iii ) calculating the environmental costs of flow regulation. The procedure is applied to four river case studies in Spain, UK and Norway. The advantages over other water cost valuation methods are discussed. The methodology enlarges the current recognition of environmental costs of water use and represents a practical management tool within the WFD context, encouraging transparency and stakeholder communication.

Description: To alleviate the water resources shortage in arid or semi-arid area, various water transfer projects have been constructed and put into operation over the last few decades. Apart from the available water, the allocation scheme also determines whether the water demands alongside can be satisfied well. Different from traditional evaluation without considering how often the failure occurs and how severe magnitude the failure may be when operating a scheme, this study proposes three indexes to evaluate scheme performance comprehensively, which are: (1) the satisfaction degree of a selected scheme (reliability); (2) the ability of the system to recover from a failure to satisfactory state (stability); and (3) the maximum damage of operating a scheme (severity). To illustrate the application of these evaluation indexes, an optimization model and an exponent describing differences among schemes are established, and then applied to the east route South-to-North Water Transfer project in China. The result shows that there exist tradeoffs among scheme’s benefits, which is described by reliability, stability, and severity. And with the increase of the exponent, the optimal scheme would consider deficit distribution more. In order to make the water transfer system with high reliability, high stability, and low severity, the exponent should be in the range of 1.0–2.0. These findings can be taken as the references to the operation of the water transfer projects.

Description: Kinematic wave (KW) theory is widely applied for modeling overland flow. The theory is comprised of (1) continuous waves, (2) formation of shocks, and (3) propagation of shocks. This paper revisits the KW concept for overland flow from fluid mechanical and mathematical points of view. Then, it develops mathematical formulations of overland flow, based on the classification of overland flow problems and the influence of storm movement and areal coverage. Depending on the class of overland flow problems, the mathematical formulation involves free boundary problems that are not known beforehand and must be solved for along with the solution of the problem. Finally, the validity of the KW concept is revisited and the accuracy of the KW approximation can be expressed by Riccati equation that describes the error for the whole hydrograph.

Description: Practical and optimal reduction of watershed loads under deep uncertainty requires sufficient search alternatives and direct evaluation of robustness. These requirements contribute to the understanding of the tradeoff between cost and robustness; while they are not well addressed in previous studies. This study thereby (a) uses preconditioning technique in Evolutionary Algorithm to reduce unnecessary search space, which enables a sufficient search; and (b) derives Robustness Index (RI) as a second-tier optimization objective function to achieve refined solutions (solved by GA) that address both robustness and optimality. Uncertainty-based Refined Risk Explicit Linear Interval Programming is used to generate alternatives (solved by Controlled elitist NSGA-II). The robustness calculation error is also quantified. Proposed approach is applied to Lake Dianchi, China. Results demonstrate obvious improvement in robustness after conducting sufficient search and negative robustness-optimality trade-offs, and provides a detailed characteristic of robustness that can serve as references for decision-making.

Description: Runoff, erosion and pollutant transport are influenced by spatial and temporal variation in soil hydraulic properties. Hydrologic models contain parameters that are related to these properties. Model parameters can be anticipated to exhibit similar variation which, when characterized, can improve runoff estimates. This study used plot-scale data from a 0.07 ha grassed study area in the southeastern US to characterize spatio-temporal variation in the NRCS curve number (CN) parameter. Based on over 200 rainfall-runoff data pairs collected over a 19-year period, CN exhibited highly variable (coefficient of variation up to 0.54) spatial behavior. Within-plot variation also demonstrated discernible spatial structure, with high variation associated with low CN. While preserving some similarities, spatial structure of CN and connectedness of regions of similar CN varied with runoff event date. Temporal trends were detected, with some regions demonstrating increasing trends and others decreasing. Rainfall-runoff plot characteristics and experimental protocols were consistent during the period of data collection; based on spatial distribution of CN values and trends as well as observation, traffic patterns and mammalian bioturbation are hypothesized as major sources of observed spatio-temporal CN variation.

Description: The short-term hydrothermal scheduling (SHS), typically a complicated nonlinear, nonconvex and non-smooth optimization problem, is very important for the economic operation of power systems. Instead of heuristic algorithms popularly used in previous studies, this paper employs a mathematical approach, where a two-stage linear programming with special ordered sets (TLPSOS) is proposed to solve the SHS problem. The nonlinear thermal cost functions and hydropower output functions are approximated by using the special ordered sets. The TLPSOS involves two stages: solve the linearized model in the first stage, and eliminate the linearization errors in the second. Superior to heuristic algorithms, the TLPSOS does not rely on parameters, and can always give stable results. Applied to a widely used hydrothermal system which consists of four hydroplants and three thermal plants, the present method shows its efficiency and strength in obtaining results better than those of previous studies.

Description: Inter-basin water transfer projects are usually considered as one of the most effective facilities to balance the non-uniform temporal and spatial distribution of water resources and water demands by diverting water from surplus to deficient area. However, the operation of these projects are always daunting, especially for projects with multi-donor reservoirs but only one recipient reservoir. In this study, a set of water transfer rule curves are firstly proposed to determine when, where and how much water should be diverted from each donor reservoir. In addition, a simulation-optimization model with the objective to minimize both water shortage risk and vulnerability is established to derive the optimal operation rule curves. Following that, the new transfer rules are applied to provide guidelines for the operation of a water transfer-supply project with two donor reservoirs in central China. The effects of water diversion on each reservoir are evaluated under different scenarios including no diversion, diversion from the donor reservoir with relatively sufficient water, diversion from the donor reservoir with relatively limited water, and diversion from both donor reservoirs. The results show the advantages of improving the performance of whole water diversion system and demonstrate the feasibility of the proposed approach.

Description: The lack of information to manage groundwater for irrigation is one of the biggest concerns for farmers and stakeholders in agricultural areas of Mississippi. In this study, we present a novel implementation of a nonlinear autoregressive with exogenous inputs (NARX) network to simulate daily groundwater levels at a local scale in the Mississippi River Valley Alluvial (MRVA) aquifer, located in the southeastern United States. The NARX network was trained using the Levenberg-Marquardt (LM) and Bayesian Regularization (BR) algorithms, and the results were compared to identify an optimal architecture for the forecasting of daily groundwater levels over time. The training algorithms were implemented using different hidden node combinations and delays (5, 25, 50, 75, and 100) until the optimal network was found. Eight years of daily historical input time series including precipitation and groundwater levels were used to forecast groundwater levels up to three months ahead. The comparison between LM and BR showed that NARX-BR is superior in forecasting daily levels based on the Mean Squared Error (MSE), coefficient of determination (R 2 ), and Nash-Sutcliffe coefficient of efficiency. The results showed that BR with two hidden nodes and 100 time delays provided the most accurate prediction of groundwater levels with an error of ± 0.00119 m. This innovative study is the first of its kind and will provide significant contributions for the implementation of data-based models (DBMs) in the prediction and management of groundwater for agricultural use.

Description: This study aims to test the appropriateness of multivariate skew- t copula and checkerboard copula of maximum entropy in generating monthly rainfall total data. The generation of synthetic data is important, as it provides hypothetical data in areas for which data availability remains limited. Three selected meteorological stations in Kelantan, Malaysia, Stesen Pertanian Melor, Rumah Pam Salor, and Ladang Lepan Kabu, are considered in this study. Monthly rainfall total data for the driest and wettest months in the year are tested in this study. For these three stations, the identified month with the least total of rainfall received (driest) is May, while the month with the highest total of rainfall received (wettest) is November. The data is fitted to gamma distribution with the corresponding parameters estimated. The observed data will be transformed to be in unit uniform using the gamma marginal. The resulting data is compared to simulated uniform data generated using multivariate skew- t copula and checkerboard copula of maximum entropy models based on the correlation values of the observed and simulated data. Next, the Kolmogorov-Smirnov test is used to assess the fit between the observed and generated data. The results show that the values of simulated correlation coefficients do not differ much for gamma distribution, multivariate skew- t , and maximum entropy approaches. This implies that the multivariate skew- t and maximum entropy may be used to generate monthly rainfall total for cases in which actual data is unavailable.

Description: The spatial characteristics and the high-duty water regions of the Water Usage Patterns (WUP) are very important for the allocation and management of water resources. Taken Hubei province, China as an example, we adopted the exploratory spatial data analysis (ESDA) method to investigate the spatial dependence and local patterns of the WUP from 2003 to 2012. Subsequently, the spatial variation mechanisms were analyzed through the gravity center model. The results indicated that the overall spatial dependence of the agricultural WUP was detected (more significant after 2008). Moreover, the global spatial autocorrelation analysis results on the domestic WUP showed statistical significance (Moran’s I 〉 0.1, P  〈 0.05). These indicated that the local patterns were presented. The high values clustering areas of the agricultural and domestic WUP were mainly distributed in the central province and in the western province respectively. However, the approximate random distribution was identified for the industrial WUP because the industrial development had been conducted widely in the whole province during these years. Furthermore, the governmental policies and natural environment contributed to the spatial evolution tendency of the WUP. An increasing trend of the spatial association of the agricultural WUP and a significant decreasing trend of that of the domestic WUP, which suggested that the natural circumstance superiority and the industrial structure adjustment related to water utilization has been utilized and implemented effectively. This study can provide a useful reference and guidance for scientific planning of water resource systems.

Description: Impact of spatial data availability on the temperature and precipitation prediction characteristics of Weyib River basin in Ethiopia has been investigated using CMIP5-CanESM2 model for the RCP8.5, RCP4.5 and RCP2.6 scenarios. The objective of the present study is to characterize how future temperatures and precipitation prediction under CMIP5-CanESM2 model output varies against diverse averaged arbitrary spatial weather stations found in the basin. The statistical downscaling model tested and verified using the observed daily data for twelve, six and three averaged arbitrary spatial weather stations as well as for a single weather station was used to predict the future climate scenarios. The results revealed that the mean annual daily maximum and minimum temperature and precipitation for twelve, six and three arbitrary spatial stations have revealed an increasing trend in the upcoming periods until the end of the century. In single station analysis, the trend itself has changed from increasing trend to decreasing trend in case of maximum and minimum temperature. In case of precipitation, no visible trend has been observed in case of single station analysis. Therefore, the variation in amount and distribution of precipitation and temperature among the four averaged spatial stations in the same study area might affect the water resources and agriculture of the basin and also instead of using a single weather station to predict future climate variables for a particular study basin, it is more reliable using averages of numerous spatial weather stations data.

Description: Runoff plots are important for soil loss measurements, and increasing numbers of plots use automatic equipment. To choose equipment with appropriate capacities, the peak flow rate must be known. The peak flow rate is also an important parameter in the modified universal soil loss equation (MUSLE) which calculate the soil loss from upland slope. The available peak flow rate equations are primarily for the watershed scale, not for small drainage areas like runoff plot. This study’s purpose was to derive an equation suitable for the small drainage areas. A total of 149 runoff events on 5 runoff plots were used to develop a peak flow rate equation for the hillslope scale. All plots are located in the Tuanshangou catchment, Zizhou county, Shaanxi province, China. Dimensionless analyses were used to determine the equation form of linear regression analyses. The results revealed that the peak flow rate was significantly correlated with plot area, slope steepness, runoff depth, rainfall depth and the maximum 30-min rainfall intensity. Two equations were developed to estimate peak flow. The model efficiencies of both equations exceeded 0.9. The equations developed in this study represent an important complement to existing peak flow rate equations. These new equations will facilitate the design of soil conservation practices and/or the selection of flow-observation equipment for small drainage areas.

Description: This paper highlights key trends and projections in water scarcity, reviews the ways that water security and water scarcity are most commonly understood, and explores possible responses. Based on a selected review of the literature, an explanation is provided of ways that water pricing can be applied to respond to water insecurity from both a demand and supply perspective. ‘Hard’ and also ‘soft’ approaches that include stakeholder, policy and decision processes are briefly reviewed as ways to promote water security. Collectively, the paper provides a guide about how decision makers might efficiently and equitably respond to the ‘wicked problem’ of water insecurity.

Description: Safe, trusted drinking water is fundamental to society. Discolouration is a key aesthetic indicator visible to customers. Investigations to understand discolouration and iron failures in water supply systems require assessment of large quantities of disparate, inconsistent, multidimensional data from multiple corporate systems. A comprehensive data matrix was assembled for a seven year period across the whole of a UK water company (serving three million people). From this a novel data driven tool for assessment of iron risk was developed based on a yearly update and ranking procedure, for a subset of the best quality data. To avoid a ‘black box’ output, and provide an element of explanatory (human readable) interpretation, classification decision trees were utilised. Due to the very limited number of iron failures, results from many weak learners were melded into one high-quality ensemble predictor using the RUSBoost algorithm which is designed for class imbalance. Results, exploring simplicity vs predictive power, indicate enough discrimination between variable relationships in the matrix to produce ensemble decision tree classification models with good accuracy for iron failure estimation at District Management Area (DMA) scale. Two model variants were explored: ‘Nowcast’ (situation at end of calendar year) and ‘Futurecast’ (predict end of next year situation from this year’s data). The Nowcast 2014 model achieved 100% True Positive Rate (TPR) and 95.3% True Negative Rate (TNR), with 3.3% of DMAs classified High Risk for un-sampled instances. The Futurecast 2014 achieved 60.5% TPR and 75.9% TNR, with 25.7% of DMAs classified High Risk for un-sampled instances. The output can be used to focus preventive measures to improve iron compliance.

Description: As much as transboundary river basins can be niches for regional cooperation, they could also be causes for interstate water disputes. The risk of water conflict in these river basins is much higher during water scarcity. As a result, establishing a fair and efficient water allocation mechanism is key for the sustainable sharing of these river basins’ water. In this paper, the authors propose a monotonic water allocation mechanism for transboundary river basins under water scarcity by coupling the bankruptcy theory with the Asymmetric Kalai-Smorodinsky bargaining solution concept. The allocation framework takes into account the aspiration water claims of the sharing countries. Additionally, as a case study, the allocation solution was used to allot the contested water of the Nile among the basin countries. For the medium term water demands the framework allocated 61.67%, 89.80%,91.82% and 61.67% of their water claims to Ethiopia, Sudan, Egypt and to the assumed coalition countries on the White Nile referred in this paper as equatorial states (Uganda, Kenya, Tanzania, Burundi, Rwanda, and Democratic Republic of Congo) respectively. On the other hand, for the long term demands, the allocation scheme allocated 63.65%, 69.36%, 71.42% and 60.41% of their water demands to the riparian countries in the same order. In general, the authors hope that the water allocation scheme applied in this article can contribute to the ongoing efforts to design river sharing solutions to river sharing problems in transboundary river basins by understanding the strategic interaction among riparian countries.

Description: This paper proposes a random fuzzy optimization (RFO) model for short-term hydropower scheduling, in order to avoid frequent unit switches owing to uncertainty of the power load. The cascade hydropower stations of Qing River in China are firstly introduced for research, and the power load error of the cascade is described. Defined as a random fuzzy variable, the error is analyzed and its distribution is derived to signify the uncertainty. Then random fuzzy programming is integrated into short-term hydropower scheduling to develop the RFO model, with more attention payed to unit spare capacity, while satisfying the demand of power grids. Meanwhile, an applicable solution searching strategy is proposed to solve the model. Simulation results of random fuzzy optimization of the cascade prove that the strategy is practical and the developed model is effective to avoid frequent unit switches. The method also can provide available references for other cascade dispatching center and hydropower stations with the same plight.

Description: Supplying agricultural water has recently become more challenging due to increase in drought frequency in semi-arid regions. Unreliable supply water resources lead to inflow fluctuations in irrigation districts locating at the downstream part of the rivers. The conventional operation cannot handle the fluctuations effectively; therefore, water delivery to the off-takes is seriously compromised. In this study, the capability of decentralized Proportional-Integral (PI) and centralized Linear Quadratic Regulators (LQR) controllers were investigated to alleviate the effects of severe inflow fluctuations in the main irrigation canals operation. In this regard, the Roodasht North Branch (RNB) main canal, located in the central Iran, consisting of 24 reaches was selected as a test case. Mathematical operational model of the canal was coupled with the designed PI and LQR controllers. The performance of the controllers were evaluated under the normal and severe unpredictable inflow fluctuations scenarios. The results showed that the PI configuration was able to successfully deal with and handle the normal inflow fluctuations. Water delivery to the upstream and middle canal reaches was regulated reasonably well, while the downstream canal reaches were still slightly suffering from the inflow fluctuation. The LQR controller showed an outstanding performance in dealing with both normal and severe inflow fluctuation test scenarios. The controller optimally adjusted the gates accordingly to manage even the sever inflow fluctuation. The results of this study demonstrate capabilities of the control configurations in managing the inflow fluctuations in main canals which can help moving towards the urgent needs for improving the current canal operational performance.

Description: Next to the traditional analysis of trends in time series of hydro-climatological variables, analysis of decadal oscillations in these variables is of particular importance for the risk assessment of hydro-climatological disasters and risk-based decision-making. Conventional parametric and nonparametric tests, however, need implementing a set of background assumptions related to serial structure and statistical distribution of data. They neither focus on the extreme events and their probability of occurrence. In order to get rid of these limitations, we suggest a modified version of the Sen Method (SM), combined with the Quantile Perturbation Method (QPM) for examining temporal variation of extreme hydrological events. The developed method is tested for decadal analysis of monthly and annual river flows at 10 hydrometric stations in the Qazvin plain in Iran. The results show oscillatory patterns in extreme river flow quantiles, with a positive anomaly during the 1990s and a negative one during the 2000s. It is also shown that the concurrent use of the two methods allows to set a complete picture on the temporal changes in high and low extremes in historical river flow observations in different seasons.

Description: Watershed management is defined as a comprehensive management planning that leads to good ecological, economic and social conditions in a watershed. Due to financial limitation and human resources, it is vital to prioritize watersheds for implementation of development strategies. It is a challenging problem to select watershed because of existence of multiple conflicting criteria and complex relations and influences among them. This paper is aimed to treat this problem by introducing a novel hybrid fuzzy decision making technique based on fuzzy DEMATEL, fuzzy ANP and fuzzy VIKOR for evaluating watersheds with respect to different development strategies. Five watersheds in Iran are considered as alternatives and different development strategies are defined in social, economic, environmental, managerial and technical sectors as criteria. The fuzzy DEMATEL method is used to establish interdependencies among the groups of strategies and their intensities. Then the weights of strategies are calculated by fuzzy ANP method. Finally, the watersheds are ranked by fuzzy VIKOR method. Also, the sensitivity analysis was performed.

Description: It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four forecasting models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.

Description: A multi-core parallel Particle Swarm Optimization (MPPSO) algorithm is developed to improve computational efficiency for long-term optimal hydropower system operation, in response to rapidly increasing size and complexity of hydropower systems, especially in China. The MPPSO can be implemented in three steps with easily accessible multi-core hardware platforms. First, a multi-group parallel computing strategy is introduced to maintain the diversity of population for finding the global optima. Second, the fork/join framework based on divide-and-conquer strategy is adopted to distribute multiple populations to different CPU cores for parallel calculations to take full advantage of CPU performance. Third, the results generated in different CPUs are merged to achieve an improved acceleration effect on computational time cost and more accurate optimal scheduling solution. Results for a system of twelve hydropower stations in the Guizhou Power Grid in China demonstrate that the proposed algorithm makes full use of multi-core resources, and significantly improves the computational efficiency and accuracy of the optimal solution, in addition to its low parallelization cost and low implementation cost. These suggest that the proposed algorithm has great potential for future optimal operation of hydropower systems.

Description: Medium-Term Hydro Generation Scheduling (MTHGS) plays an important role in the operation of hydropower systems. In the first place, this paper presents a Chance Constrained Model for solving the optimal MTHGS problem. The model recognizes the impact of inflow uncertainty and the constraints involving hydrologic parameters subjected to uncertainty are described as probabilistic statements. It aims at providing a more practical technique compared to the traditional deterministic approaches used for MTHGS. The stochastic inflow is expressed as a simple discrete-time Markov chain and Stochastic Dynamic Programming is adopted to solve the model. Then in order to use the information of long-term inflow forecast to improve dispatching decisions, a Dynamic Control Model is developed. Short-term forecast results of the current period and long-term forecast results of the remaining period are treated as inputs of the model. Finally, the two methods are applied to MTHGS of Xiluodu hydro plant in China. The results are compared to those obtained from Deterministic Dynamic Programming with hindsight and advantages and disadvantages of the two methods are analyzed.

Description: This study evaluated the correlation between the western U.S. snow water equivalent (SWE) and two major oceanic-atmospheric indices of the Pacific Ocean, namely, the El Niño Southern Oscillation (ENSO) and the Pacific Decadal Oscillation (PDO), using continuous wavelet transformation and its derivatives. Snow Telemetry (SNOTEL) data for 1 April SWE from 323 sites (out of which 258 are in six hydrologic regions) were obtained for a study period of 56 years (1961–2016). The results showed that ENSO had a much higher influence than PDO throughout the western U.S. SWE across the study period. Both ENSO and PDO showed a higher correlation with SWE at multiple timescale bands across different time intervals, although significant intervals in the higher timescales were of longer duration. ENSO showed a higher correlation in the 10-to-16-years band across the entire study period as well as in the lower timescales. PDO showed a higher correlation below the 4-years band. The relative phase relationship suggested that ENSO led SWE, with certain lags, while both were moving in the same direction in many instances. The lag-response behavior of SWE and PDO was not found to be uniform. The regional analyses, based on the western U.S. hydrologic regions, suggested significant variation across the adjacent regions in terms of their correlation with ENSO/PDO. Association with ENSO was also observed to be higher compared to PDO among the regions. Regions close to the ocean and at lower elevation showed higher correlation compared to the inland regions with higher elevation.

Description: This study established a hydrological drought forecasting system based on the Bayesian method and evaluated its utilization for South Korea. The regression result between Historical Runoff (HR) and Ensemble Streamflow Prediction Runoff (ESP_R) was used as prior information in the Bayesian method. Additionally Global seasonal forecast System 5 Runoff (GS5_R) produced using a dynamic prediction method was used in a likelihood function. Bayesian Runoff (BAY_R), as posterior information, was generated and compared with the ESP_R and GS5_R results for predictive ability evaluation. The Standardized Runoff Index (SRI) was selected for the drought prediction, and the BAY_SRI, GS5_SRI and ESP_SRI were computed using BAY_R, GS5_R and ESP_R, respectively. The Correlation Coefficient (CC), Nash-Sutcliffe Efficiency (NSE) and Receiver Operating Characteristic (ROC) score of BAY_SRI were the highest, and the Root Mean Square Error (RMSE) of BAY_SRI was the lowest among the methods. The Bayesian method improved the behavioral and quantitative error of drought prediction and the predictive ability of the occurrence of drought. In particular, the simulation accuracy was significantly improved during the flood season. Additionally, BAY_SRI represented past drought scenarios better than did the other two methods. Overall, we found that the Bayesian method could be applied for hydrological drought predictions for based on 1- and 2-month lead times.

Description: Reconciling simultaneous water quantity and quality aspects in drawing optimal reservoir operational strategy involves extensive computational burdens. Surrogate based optimization techniques (SBOTs) are common approaches to overcome computational bottlenecks of numerical hydrodynamic simulation models coupling evolutionary algorithm in simulation-optimization approaches. In this study, the reservoir high resolution CE-QUAL-W2 model is replaced by the lower resolution CE-QUAL-W2 and/or static ANN to speed up the optimization process. These surrogate models could consider the complex relationships to emulate the main dynamics of HR CE-QUAL-W2 model due to various reservoir operational strategies. The performance of various SBOTs, based on adaptive and sequential surrogate models coupled with particle swarm optimization algorithm, are evaluated in deriving optimal reservoir operational strategies. Then adaptive surrogate model, as the more efficient and accurate one, is applied to derive long term optimal reservoir operational strategy in the selective withdrawal scheme. The results show application of the proposed approach could enhance downstream water temperature, water demand satisfactions, and hydropower peak energy generation compared with the standard operation policy (SOP) in Karkheh reservoir during 15-year-time horizon.

Description: Recently water supply alternative sources, recognized as sustainable and ecofriendly have become popular. This is consequent on the scarcity and increasing demand for water, especially by developing nations characterized by industrialization and increasing population growth. However, the intricacies and overwhelming nature of factors to be considered in reaching a decision on a best alternative has further prompted the emergence of several decision support tools, some of which arouse discrepancies with setbacks. We employ here, the uniqueness of fuzzy TOPSIS (technique for order preference by similarity to ideal solution), a multi-criteria decision approach (MCDA), to aid in deciding the most preferred alternative water supply among, desalination, water borehole, rain water harvesting, reclaimed water, black water, grey water and water importation. This method is reckoned for its ease in handling both quantitative and qualitative data. Moreover it also overcomes the uncertainties in expert opinions usually encountered in the decision process due to the numerous variables, criteria and attributes that interplay in achieving sustainability. Results from analysis on data aggregation, normalization and performance ratings, coupled with the weighted distance from the positive and negative ideal solutions indicated that borehole ranked topmost followed by rain water harvesting (RWH). These revelations are apt to all stakeholders in the water delivery sector and in deliberations on the paradigm shift to water conservation and management measure.

Description: Groundwater provides close to 40% of California’s overall water supply under average hydrologic conditions. It is a critical source of backup during drought when increased pumping occurs to compensate for reduced surface supplies and decreased soil moisture. The conundrum is that in regions of the state where groundwater dependence is already high and rates of recharge are low, over the long term the volume withdrawn, particularly during droughts, generally exceeds replenishment in many regions. The result is overdraft - ongoing declines in groundwater levels over the long-term. To facilitate the reduction or cessation of long-term groundwater overdraft, this paper proposes that sustainable groundwater management must include the development of a drought reserve. The reserve, ideally sourced, sited and used locally, would encompass sufficient water for use during a drought such that the increased withdrawals during a drought do not result in unrecoverable groundwater declines and concomitant negative impacts. The objective is to reduce vulnerability to the state’s periodic droughts, as opposed to mitigating seasonal variations in precipitation. This paper first summarizes the issues associated with developing drought reserves, and then examines in detail how two California groundwater management agencies approach establishing and implementing a drought reserve.

Description: The aim of this paper is to compare the supply-side and demand-side approaches for assessing the scarcity rents of irrigation water. The results obtained from the case study confirm the expectation that the demand-side rationale provides the lower bound estimate of water scarcity rents. Specifically, a hypothetical elimination of water scarcity brings extra benefits to the local farmers, but these benefits cannot compensate the costs of the backstop technology which provide such extra water. Therefore, the lost opportunities, in terms of income forgone due to water scarcity, cannot legitimize supply-side approaches alone. A “soft” sensitivity analysis was included to examine the robustness of such a cost-effective property, while the policy implications of the results are also examined.

Description: Nutrient loading from agricultural drainage systems into downstream aquatic ecosystems, like Lake Winnipeg in the prairie province of Manitoba, Canada, represents a major challenge for water quality management. In order to improve water quality in downstream waterbodies, the Manitoba government is currently investigating the relationship between hydrological standard of agricultural drainage network and nutrient retention in the drainage systems. Briefly, oversized drains have more capacity to transport nutrients, which can increase nutrient loading to downstream waterbodies, especially during rainfall events. Currently, the hydrological standards of agricultural drainage design in Manitoba were mainly developed according to cost-benefit analysis without considering nutrient retention. The purpose of this study was to use computer modelling techniques to simulate the impact of drain size (based on different hydrological standards) on nutrient retention within an agricultural drainage network. The site chosen was the Tobacco Creek Watershed, an agricultural area which drains into the Red River, and thence into Lake Winnipeg. Suspended sediment, nutrient and flow data, from several locations along the Brown drain within this watershed, were used to calibrate a water quality model. Scenarios were then simulated with the model to estimate how different drain sizes affect nutrient transport and retention. Sampling took place during the spring and summer of 2013 starting with freshet and ending when the drains dried up near mid-summer. Study results indicated that the amount of nutrients transported was generally greater during freshet and summer rain storms. Occasionally, however, nutrients in summer discharge exceeded those transported during freshet. The water quality model was applied to the Brown drain to investigate the effects of different drain sizes for rainfall amounts under 2, 5, 10, 15, and 20 year return periods. Generally the results indicate that as the return periods became larger (in larger channels) lower nutrients concentrations were predicted downstream (higher decay rates). On average, the model predicted a 15%–20% decline in nutrient concentration with a 20-year return channel design compared to a 2-year return. The research from this study may provide an impetus to the policy-making process of drainage design.

Description: Rainfall rates and soil moisture content have been recognized as the most critical parameters in flood forecasts; the former known as forcing and the latter as the state variable. The main objective of this article is the incorporation of antecedent soil moisture information to reduce false flood warnings over Riyadh City, Saudi Arabia. The forcing variable was obtained from the Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) Real Time (RT) data (3B42RT). Soil moisture (SM) information was obtained from Advanced Microwave Scanning Radiometer (AMSR-E) as the state variable. Long time series SM information (2002–2011) provided Cumulative Distribution Function (CDF) of SM. CDF with 90% was taken as the SM threshold value. Flooding is indicated for rainy dates exceeding the rain thresholds with the previous satellite overpass SM being greater than 90% CDF of the respective month. The methodology removed the false flood warnings substantially when compared to the flood warnings where SM information was absent. The method is robust and simple, and it can be applied on TRMM and AMSR-E follow on missions; like Global Precipitation Measurement (GPM) and Soil Moisture Active Passive (SMAP).

Description: The aim of this paper is to characterize the relationship between system characteristics of topography, peak demand, and topology and the energy dynamics of four small to medium-sized water distribution systems in Ontario, Canada. First, previously developed energy indicators were used to evaluate and compare the energy efficiency, energy lost to friction, energy lost to leakage, and the surplus energy of the four systems. The systems had a high energy efficiency ranging from 75 to 94% (leak-free) and 58–70% (leaky). Friction losses comprised 3–22% of the total energy input to the systems. Energy lost to leakage comprised 23–26% of total energy input to the systems. Second, hypothesis testing was used to identify statistically significant correlations between system characteristics and energy use patterns in the system. No statistically significant correlation was found between the standard deviation of node elevation and energy use in the four systems. Hydraulic redundancy and energy use did not have a statistically significant correlation. This is because during a ‘typical’ day of service, the most efficient flow paths are concentrated through the trunk mains rather than in the smaller distribution mains that account for most of the looping and hydraulic redundancy of a system. Correlations between peak hour factor and the energy indicators were near the cut-off p -value level ( p  〈 0.05) so it was not clear if the correlations are statistically significant. Despite this, moderate to high Spearman rank correlation coefficients (−0.6 to +0.8) were calculated for the leaky and leak-free systems.

Description: There are over 260 transboundary river and lake basins in the world that many of them are facing great challenges of water sharing between riparian countries concerned. The 1997 UN Watercourses Convention, entered into force in 2014, includes articles and factors on water sharing which have not been completely used for modelling of the basins yet. In this paper, legal aspects (i.e. Articles 5, 6, 7 and 10 of the Convention) are integrated with a technical approach for water allocation in transboundary rivers. For this purpose, a new conceptual model is developed for quantification of the Convention provisions concerning equitable and reasonable water sharing. The method is applied to the Sirwan-Diyala transboundary river shared by Iran and Iraq. Some indicators are developed and quantified for determination of water shares of the riparian countries and different scenarios considering extreme and equal weights of the factors are defined. The basin is simulated by WEAP model to evaluate effects of the scenarios on up- and downstream of the basin. Five demand management alternatives comprising increasing of irrigation efficiency and eliminating second cultivation are proposed as appropriate measures for elimination or mitigation of possible significant harm. The proposed technical-legal approach paves the way for enhancing bargaining potentials of the riparian countries and increasing their cooperation to achieve a win-win solution in using waters of transboundary rivers.

Description: A sustainable drinking-water supply requires durable securing of the resource. With an increase in spatial pressure, the need is increasing to prioritize measures based on the vulnerability of the resources and the impact of surrounding land use functions. This is especially challenging in the Province of Overijssel with groundwater abstraction sites in vulnerable Pleistocene sandy soils and increasing spatial pressure from both agricultural and urban areas. The governance of the groundwater abstractions in the Province of Overijssel is based on a combination of precaution and a risk-based approach. The Province has adopted REFLECT to assess the risks of spatial developments. REFLECT is a negotiation support system that gives an overview of the vulnerability of the groundwater abstractions and risks of several land use functions on the groundwater quality. REFLECT has been used to obtain the current risk scores of all drinking water abstractions in the Province and following the EU Water Framework Directive. Spatial insight of risks was used to identify and target measures reducing these risks. Moreover, REFLECT has been applied to decide on a local spatial development near an abstraction. Knowledge of the impact of land use changes on groundwater quality helped the municipality harmonizing the spatial plan with the interest of the drinking water abstraction and creating a step-forward in the protection level of the abstraction site. These applications illustrate that REFLECT is an instrument that fits well within risk-based groundwater governance which aims at safeguarding of the public water supply by harmonizing land use functions.

Description: The authors propose a new approach for trend assessment that takes into account long-term periodicity of annual flows. In particular, analysis is performed of annual flows recorded at the locations of 30 operating and designed hydropower plants (HPPs) in Serbia, in order to assess the current and future water availability for hydropower generation. The composite annual trend is determined by sliding a fixed time window of 30 years along the observed time series with a one-year time step. Such a linear moving window (LMW) approach enables the identification of the flow trend as a median of all values for each time step. Significant trend harmonics are determined using discrete spectral analysis. The results show an alternation of upward and downward trend phases of different durations, namely: 67–87, 33–43 and 21–29 years. On the other hand, the results of the Mann-Kendall test indicate a monotonic downward trend at the studied sites in the Drina River Basin, while statistically insignificant trends are noted at other river basins. The Mann-Kendall test with the Theil-Sen estimator also implies a downward and statistically insignificant flow trend after the observed period, whereas the LMW approach indicates a probable trend increase at all the examined sites. The proposed approach can be used to predict annual flows in order to establish long-term water management plans at hydropower plants.

Description: This study attempts to perform a global analysis of the trend in drought propensity in the twenty-first century using bias corrected soil moisture simulations from two General Circulation Model (GCMs) outputs based on the Representative Concentration Pathway-8.5 (RCP8.5) scenario. Drought propensity is characterized in terms of the probabilistic index – Drought Management Index (DMI), which is suitable for the assessment of slowly varying changes in soil moisture drought on a multi-year time scale. A global gridded analysis is performed to assess the future trend in drought propensity at each location on the globe over the twenty-first century. Regional analysis is also carried out to investigate the trends, if any, at the continental scale. A significant increasing trend in drought propensity is observed in large parts of Africa, South America and Asia, whereas a significant decreasing trend is observed in the northern parts of Europe and North America. This study helps to assess the spatio-temporal propagation of global drought propensity in future and aids in identifying the regions that would be relatively more/less prone to droughts towards the end of the century.

Description: Sediment transport in streams and rivers takes two forms as suspended load and bed load. Suspended load comprises sand + silt + clay-sized particles that are held in suspension due to the turbulence and will only settle when the stream velocity decreases, such as when the streambed becomes flatter, or the streamflow into a pond or lake. The sources of the suspended sediments are the sediments transported from the river basin by runoff or wind and the eroded sediments of the river bed and banks. Suspended-sediment load is a key indicator for assessing the effect of land use changes, water quality studies and engineering practices in watercourses. Measuring suspended sediment in streams is real sampling and the collection process is both complex and expensive. In recent years, artificial intelligence methods have been used as a predictor for hydrological phenomenon namely to estimate the amount of suspended sediment. In this paper the abilities of Support Vector Machine (SVM), Artificial Neural Networks (ANNs) and Adaptive Network Based Fuzzy Inference System (ANFIS) models among the artificial intelligence methods have been investigated to estimate the suspended sediment load (SSL) in Ispir Bridge gauging station on Coruh River (station number: 2316). Coruh River is located in the northern east part of Turkey and it is one of the world”s the fastest, the deepest and the largest rivers of the Coruh Basin. In this study, in order to estimate the suspended sediment load, different combinations of the streamflow and the SSL were used as the model inputs. Its results accuracy was compared with the results of conventional correlation coefficient analysis between input and output variables and the best combination was identified. Finally, in order to predict SSL, the SVM, ANFIS and various ANNs models were used. The reliability of SVM, ANFIS and ANN models were determined based on performance criteria such as Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Efficiency Coefficient (EC) and Determination Coefficient (R 2 ).

Description: A regional water management system always contains long-term and short-term actions in practice. The uncertainty of short-term actions increases great complexity for evaluating the performance of action portfolio comprised with long-term and short-term actions. Developing an efficient methodology to define a cost-effective action portfolio is an important task. Hence, this study develops a novel decision model, the Stochastic Programming with Recourse Decision Model (SPRDM), to compute a cost-effective action portfolio. The effectiveness of SPRDM is verified by address a problem of water shortage and financial cost in Taoyuan City, Northern Taiwan. The results shown adding Kaotai Reservoir alone can fulfill the Taoyuan demand most of the time, and the remaining extreme water shortage events can be addressed by short-term and irrigation management actions additionally. When drought duration of water shortage event is longer than 200 days, using irrigation management action to address water deficit has lower expected costs than other short-term actions do. Although the study focuses on Northern Taiwan, the proposed model is applicable to other areas with an integrated water resources management framework.

Description: In this paper, the application of two data mining techniques (decision tree and association rules) was offered to discover affiliation between several thresholds of monthly precipitation (MP) values of Tabriz and Kermanshah synoptic stations (located in Iran) and de-trend sea surface temperature (SST) of the Black, Mediterranean and Red Seas. Two major steps of the modeling in this study were the classification of de-trend SST data and selecting the most effective groups and extracting hidden predictive information involved in the data. The decision tree techniques which can identify the good traits from a data set for the classification purpose were used for classification and selecting the most effective groups and association rules were employed to extract the hidden predictive information from the large observed data. To examine the accuracy of the rules, confidence and lift measures were calculated and compared for different thresholds of precipitation at different lag times. The computed measures confirm reliable performance of the proposed hybrid data mining method to forecast extreme precipitation events considering higher threshold values and the results show a relative correlation between the Mediterranean, Black and Red Sea de-trend SSTs and maximum MP of Tabriz and Kermanshah synoptic stations so that the confidence between the threshold of 35% of MP values and the de-trend SST of seas is higher than 70 for Tabriz and 60% for Kermanshah. It was also shown that the geographical location of stations and the distribution of precipitation data affect the measures of the rules and forecasting outcomes.

Description: Leakage is responsible for pressure reduction and water loss in water distribution systems. Approaches for detection of leaks, based on the pressure variation impact from the boundary condition of a leakage point, have been explored to calibrate location and leakage quantity. Even through expression in the frequency domain allows precise description of abnormalities along pipeline systems, existing leakage formulations suffer from complexity in the analytical derivation for multiple leakage conditions. This study proposes an alternative method, the multiple leakage function (MLF), for an efficient multiple leakage representation of a reservoir pipeline valve system in the frequency domain. To address unsteady friction impact on a multiple leakage situation, the MLF was used with one-dimensional and two − dimensional unsteady friction models. Model validation was achieved by comparing impedance frequency responses with those of existing approaches. Strengths associated with the MLF were discussed in terms of model parsimony, computational accuracy, and leak detection capability. Feasibility of the MLF was confirmed for robustness in the leakage implementation sequence and for identification of any single leakage, which is useful in detecting multiple leakages in real systems.

Description: Best Management Practices (BMPs) have become the most effective way to mitigate non-point source pollution (NPS) issues. Much attention has been paid to NPS in rural areas, where agricultural activities increase nutrients, toxics, and sediments in surface water. Stormwater from urban areas is also a major contributor to NPS pollution. For watersheds bearing various soil types and land uses, a single type of BMP cannot be the panacea to all stormwater problems. To solve these problems, a Diagnostic Decision Support System (DDSS) was developed in this research. The DDSS can identify and locate the most critical NPS areas (hotspots) within a watershed in high spatial resolution. The DDSS can provide a series of spatially distributed small-scale BMPs which are effective in treating the NPS and are suitable for the physical environment. The BMPs, varying in types and locations, are recommended at HRU (Hydrologic Response Unit) level. The DDSS was tested in Watts Branch, a small urban watershed of the Anacostia River in metropolitan Washington D.C., USA. The process-based hydrologic model, Soil and Water Assessment Tool (SWAT), was used to simulate watershed responses. The simulation results were then used by the DDSS for BMP recommendation. Hotspots of different NPS were successfully located and prescribed with spatially distributed BMPs. The DDSS serves as a useful tool to better understand urban watersheds and to make proper stormwater management plans.

Description: This paper reviews the evolvement of water footprint assessment (WFA) as a new research field over the past fifteen years. The research is rooted in four basic thoughts: (1) there is a global dimension to water management because water-intensive commodities are internationally traded, so we must study virtual water trade and the effects of countries externalizing their water footprint; (2) freshwater renewal rates are limited, so we must study the development of consumption, production and trade patterns in relation to these limitations; (3) supply-chain thinking, previously uncommon in water management, can help to address sustainable water use from the perspective of companies and final consumers; and (4) a comprehensive approach requires the consideration of green in addition to blue water consumption, the traditional focus in water management, and the analysis of water pollution in the same analytical framework as well. The quick emergence of the new field and wide uptake of the water footprint concept in society has generated substantial discussion about what the concept in narrow sense and the research field in broader sense can offer and what not. The paper reflects on the main issues of debate.

Description: This article presents experimental and numerical study of an under-ground water reservoir (cistern) during six months operation in a semi-arid region. The cistern with one dome, four windcatchers and a water reservoir is located in Lar, a hot arid city at south of Iran. Outdoor and indoor air temperature and humidity, water temperature in three depths and dome surface temperature were measured using a data logging system. The results show that the average air humidity inside the cistern was almost constant during the experiments but its slight variation during a day follows inside air temperature changes. The inside air temperature was always lower than the ambient temperature and inside and outside average air temperature difference was about 6 °C. The difference was slightly higher in the hot seasons. The water reservoir was also modeled in 2D, axisymmetric and quasi steady numerical simulation for six months of operation. Highly stratified water temperature distribution was observed in the numerical results as well as the experimental measurements.

Description: The Zayandeh-Rud River basin, Iran, is projected to face spatiotemporally heterogeneous temperature increase and precipitation reduction that will decrease water supply by mid-century. With projected increase (0.70–1.03 °C) in spring temperature and reduction (6–55%) in winter precipitation, the upper Zayandeh-Rud sub-basin, the main source of renewable water supply, will likely become warmer and drier. In the lower sub-basin, 1.1–1.5 °C increase in temperature and 11–31% decrease in annual precipitation are likely. A system dynamics model was used to analyze adaptation strategies taking into account feedbacks between water resources development and biophysical and socioeconomic sub-systems. Results suggest that infrastructural improvements, rigorous water demand management (e.g., replacing high water demand crops such as rice, corn, and alfalfa), and ecosystem-based regulatory prioritization, complemented by supply augmentation can temporarily alleviate water stress in a basin that is essentially governed by the Limits to Growth archetype.

Description: In the field of water quality management, it is vital to determine the main precursory anomalies from the precursor of intricate water bloom in the context of a given area. In this paper, a water bloom precursor analysis method, based on two direction singular rough set, was proposed. This approach was produced on the basis of the different sections and pre-water bloom of water bloom precursor anomalies and characteristic of elements transferred in singular rough set. For testing the validity of two direction singular rough set application in water bloom precursor analysis, Xiangxi River, which is one of the typical tributaries of Three Gorges Reservoir in China, was selected as study area. The result showed that compared with other indexes, pH and dissolved oxygen (DO) are the most valuable indicators of water bloom in the precursory anomalies. Furthermore, regarding with water bloom precursory anomalies in Xiangxi River, most of the nutrient loading and biological community are the key indicators. Hence, this method can determine the main precursory anomaly for water bloom in the study area, which provides powerful knowledge support to water quality specialists for them to comprehensively analyze precursory anomaly so as to find out its relationship with occurrence law of water bloom.

Description: The rainfall Intensity-Duration-Frequency (IDF) relationship is the primary input for storm water management and other engineering design applications across the world and it is developed by fitting an appropriate theoretical probability distribution to annual maximum (AM) series or partial duration series (PDS) of rainfall. The existing IDF relationship developing methods consider the extreme rainfall series as a stationary series. There exist few studies that compared AM and PDS datasets for developing rainfall IDF relationship in a stationary condition. However, during the last few decades, the intensity and frequency of extreme rainfall events are increasing due to global climate change and creating a non-stationary component in the extreme rainfall series. Therefore, the rainfall IDF relationship developed with the stationary assumption is no longer tenable in a changing climate. Hence, it is inevitable to develop non-stationary rainfall IDF relationship and to understand the differences in non-stationary rainfall IDF relationships derived using AM and PDS datasets. Consequently, the objectives of this study are: (1) to develop non-stationary rainfall IDF relationships using both AM and PDS datasets; (2) to compare them in terms of return level estimation. In particular, the non-linear trend in different durations’ PDS and AM datasets of Hyderabad city (India) rainfall is modeled using Multi-objective Genetic Algorithm (MGA) generated Time based covariate. In this study, the PDS datasets are modeled by the Generalized Pareto Distribution (GPD) while the AM datasets are modeled by the Generalized Extreme Value Distribution (GEVD). The time-varying component is introduced in the scale parameter of the GPD and the location parameter of the GEVD by linking the MGA generated covariate. In addition, the complexity of each non-stationary model is identified using the corrected Akaike Information Criteria (AICc) and the statistical significance of trend parameter in the non-stationary models is estimated using the Likelihood Ratio (LR) test. Upon detecting significant superiority of non-stationary models, the return levels of extreme rainfall event for 2-, 5-, 10- and 25-year return periods are calculated using non-stationary models. From the results, it is observed that the non-stationary return levels estimated with PDS datasets are higher than those estimated with AM datasets for short durations and smaller return periods while the non-stationary return levels estimated with AM datasets are higher than those estimated with PDS datasets for long durations and higher return periods.

Description: Freshwater reservoirs are under threat because of huge amounts of sediments deposited annually. Sediment flushing seems to be effective to preserve reservoir storage, but it may have negative environmental impacts on downstream ecosystems such as fish mortality. Therefore, providing a suitable flushing strategy that could be compatible with the river ecosystem downstream is of great importance. Two numerical models were developed in this paper to predict the suspended sediment concentration (SSC) on the reservoir-river system and effects of different flushing scenarios on aquatic life. Developed models were applied to the Dez Resevoir system in the southwest of Iran which has suffered from the sediment problems in two last decades. The suitable values for flushing time, concentration limits, and flushing discharge have been recommended in this research by use of the existing information and previous flushing records, as well as field measurement and modeling. Based on social, environmental and technical limitations, March is the appropriate time for flushing. After hydraulic simulation of different flushing scenarios and sediment routing along the river, flushing with 1275 and 800 cubic meter per second with 30 and 20 g per lit concentration in dry and wet season respectively are feasible and have minimum environmental impacts.

Description: Vegetative filter strips (VFS) are an effective methodology for runoff management and control of sediment flow and soil erosion, particularly for large urban parking lots, and for irrigation water management. An optimization model for the design of vegetative filter strips for runoff management, that minimizes the amount of land required for the strips, is developed herein. The resulting optimization model is based upon the kinematic wave equation for overland sheet flow along with equations defining the cumulative infiltration and infiltration rate. The nonlinear programming (NLP) optimization model has been applied using the General Algebraic Modeling System (GAMS). The runoff management model is extended for the control of sediment. These new models provide flexibility for site-specific conditions and are a step forward in the development of new design methodologies for stormwater and irrigation flow management. The optimization models have been applied using a sensitivity analysis of parameters such as different soil types, rainfall characteristics etc., performed to validate the model. Results of the example model applications indicate the usefulness of the models for practical applications in the field. To our knowledge this is the first optimization model developed for the design of vegetative filter strips for runoff and sediment control.

Description: We investigated the potential impacts of climate changes on hydrological drought of the Zayandehrud basin in Iran. The meteorological data was simulated using the LARS-WG model by output downscaling of HADCM3, INCM3 and NCCCSM from 2011 to 2040 under A1B, A2 and B1 scenarios. In order to estimate the runoff of the basin, the IHACRES model was calibrated and validated by data obtained from the Koohrang station during 1987–2007. The runoff was calculated for 2011–2040 period based on the mean of downscaling values in the IHACRES model. Then, the impact of climate changes on hydrological drought was studied by a probabilistic approach and MSUI index. The results revealed a drastic reduction in normal levels and also a significant increase in moderate, severe, and very severe drought levels in the future compared to the base period. The MSUI index represents a 42.32% reduction in the normal level based on the HADCM3 model under A1B scenario as well as an 86.8%increasein the severe drought. Furthermore, the HADCM3 model using the probabilistic approach showed a 73% reduction under the A2 scenario for normal condition and an increase of 20% for severe drought.

Description: In order to improve the efficiency of emergency management of the Middle Route of the South-to-North Water Diversion Project (SNWDP), and to guarantee the water supply function of the project, the intergovernmental cooperation system of emergency management for emergent events in the Middle Route of the South-to-North Water Diversion Project was established. The cooperation models of emergent events were built using Evolutionary Game Theory. The evolutionary influence of system parameters on respective governmental behaviour was analysed. The payment functions of the emergency agents involved were constructed, the corresponding replicator dynamic equations were established and evolutionary stable strategies were discussed. Theoretical and numerical analysis results show that: In order to let local government show strong willingness to implement emergency policies, the profit caused by local government i increases its implement policy willingness to more than the increased cost. Only MWR increases the penalty on local government when it shows weak willingness and let the penalty be more than the cost increased by weak willingness, can avoid all local government select weak cooperative willingness.

Description: Regarding the ever increasing issue of water scarcity in different countries, the current study plans to apply support vector machine (SVM), random forest (RF), and genetic algorithm optimized random forest (RFGA) methods to assess groundwater potential by spring locations. To this end, 14 effective variables including DEM-derived, river-based, fault-based, land use, and lithology factors were provided. Of 842 spring locations found, 70% (589) were implemented for model training, and the rest of them were used to evaluate the models. The mentioned models were run and groundwater potential maps (GPMs) were produced. At last, receiver operating characteristics (ROC) curve was plotted to evaluate the efficiency of the methods. The results of the current study denoted that RFGA, and RF methods had better efficacy than different kernels of SVM model. Area under curve (AUC) of ROC value for RF and RFGA was estimated as 84.6, and 85.6%, respectively. AUC of ROC was computed as SVM- linear (78.6%), SVM-polynomial (76.8%), SVM-sigmoid (77.1%), and SVM- radial based function (77%). Furthermore, the results represented higher importance of altitude, TWI, and slope angle in groundwater assessment. The methodology created in the current study could be transferred to other places with water scarcity issues for groundwater potential assessment and management.

Description: This paper presents management of groundwater resource using a Bayesian Decision Network (BDN). The Kordkooy region in North East of Iran has been selected as study area. The region has been sub-divided into three zones based on transmissivity (T) and electrical conductivity (EC) values. The BDN parameters: prior probabilities and Conditional Probability Tables - CPTs) have been identified for each of the three zones. Three groups of management scenarios have been developed based on the two decision variables including “Crop pattern” and “Domestic water demand” across the three zones of the study area: 1) status quo management for all three zones represent current conditions; 2) the effect of change in cropping pattern on management endpoints and 3) the effect of future increased domestic water demand on management endpoints. The outcomes arising from implementing each scenario have been predicted by use of the constructed BDN for each of the zones. Results reveal that probability of drawdown in groundwater levels of southern areas is relatively high compared with other zones. Groundwater withdrawal from northern and northwestern areas of the study area should be limited due to the groundwater quality problems associated with shallow groundwater of these two zones. The ability of the Bayesian Decision Network to take into account key uncertainties in natural resources and perform meaningful analysis in cases where there is not a vast amount of information and observed data available – and opportunities for enabling inputs for the analysis based partly on expert elicitation,emphasizes key advantages of this approach for groundwater management and addressing the groundwater related problems in a data-scarce area.

Description: The quantification of soil variability is one of the most important aspects in the geo-engineering context. The uncertainty analysis is the main part of the reliability assessment for which a quantitative evaluation was performed in this study. The Reliability Index and the Probability of Failure using the First-Order Reliability Method (FORM) represents both, an effective method which is easy to implement at the same time. This work analyzes possible effects of compaction induced into the aquifer of the Scarlino Plain, caused by the extension of the hydraulic barrier for groundwater remediation. The currently implemented vertical barrier is composed of 12 wells which reach the depth of 10 m. The improvement of the project involves the construction of a further 40 clusters, each consisting of a doublet which intercepts different depths (10 and 18 m). The models of the subsoil stratigraphy and of the groundwater were built using a numerical model. The groundwater flow and the piezometric surface in the current configuration of the barrier were studied and the project configuration was evaluated. Using the Aquitard drainage model, the land subsidence was estimated to calculate the maximum admissible displacement related to exhibited goods , the so called territorial vulnerability. The evaluation analysis was performed using a traditional deterministic approach, followed by a reliability method based on probabilistic models. Finally, the respective results were reported in a soil mapping with overlapping layers.

Description: This paper investigates positively skewed shape of instantaneous unit hydrograph (IUH), one of the universal features of hydrologic response function. An analytical expression of statistical moments for IUH is derived in the framework of width function based geomorphologic IUH (GIUH) theory being interpreted by the concept of hydrodynamic, geomorphologic and kinematic dispersion. Within the extent of a river basin there is a significant scale difference between hillslope and channel flow path length. Even though the former has much smaller length scale its variation coefficient tends to be higher and skewness coefficient has a different trend than the latter. Kinematic heterogeneity has larger influence on the shape of IUH rather than hydrodynamic heterogeneity. Furthermore, its combined effect with geomorphologic heterogeneity can be a major cause of skewing hydrologic response function. Through transformation of width function into GIUH statistical properties of hillslope and channel flow path length can be imprinted on the shape of hydrologic response function in the form of dimensionless statistics.

Description: Eutrophication is a serious water pollution problem in many lakes and reservoirs. One method of understanding the causes of eutrophication and devising strategies to address this phenomenon is watershed modeling. An integrated model is developed in this paper for simulating and evaluating the water quality protection strategies of reservoirs based on controlling the upstream point and non-point sources of pollution and also reservoir operation. To achieve this, Soil and Water Assessment Tool (SWAT) model is used for modeling of the surface runoff and transportation of pollutant load over the watershed area and then, the numerical model CE-Qual-W2 is used for simulating the reservoir water quality. These models are linked to simulate the transmission and distribution of water quality variables in the Seimare watershed-reservoir system, west part of Iran. After calibration of the models, different strategies for reduction of pollution over the watershed are simulated and ranked based on their efficiency in reducing the pollution load entering into the reservoir. Results show that completion and modernization of the sewage network and wastewater treatment plant of Kermanshah city as long as adopting some measures against the direct release of municipal wastewater into the Gharehsou River can reduce the pollution load by 40–50% as the best short term strategy. It is also found that in the long-term period, watershed management and decreasing local animal husbandry activities are the most effective measure for reducing the nutrient load entering Seimare reservoir, and thus need to be considered in the future watershed management policies and programs.

Description: Studies evaluating the determinants of water demand typically use household-scale data or aggregated data. The household-scale data basically is preferred since it can reveal the heterogeneity in responses to the demand drivers across different consumer groups. However, the scarcity of household-scale data and its high data collection cost generally have limited the studies to rely on small samples of household data. Thus, they failed to show the spatial variation of water demand. In contrast, the aggregated studies have assessed the spatial variation of water use however they overlooked the variations across households. Using a rich source of GIS-based urban databases in Auckland, New Zealand, this study overcame this challenge by developing a large sample of 31000 single-unit housing through integration of household-level water consumption and property data with micro-scale household demographics information. This large dataset enabled this study to evaluate the water consumption both at the household scale and the census area unit scale. Panel data models were used for the water demand analysis in both scales. The proposed multi-scale analysis approach provided detailed knowledge about water consumption and its major determinants across different consumer groups and urban areas. This information may help water planners to more reliably plan water supply systems and manage consumption in the complex urban environments.

Description: Rapid increases in demand for food and energy as a result of population growth and economic development is placing ever increasing demands on limited water resources in South Asia, and climate change is expected further complicate water resource management. In spite of important reductions in poverty levels in recent decades the region is still home to a very large number of poor whose quality of life is directly affected by the availability and quality of water and water services. A significant fraction of the water resources of the region and a significant fraction of the poor are associated with major Himalayan transboundary rivers, and given growing water demand it is likely that the already significant sensitivity around water cooperation amongst co-riparians will increase. Understanding the risks and opportunities for transboundary cooperation in the river systems in South Asia is thus important for guiding sustainable transboundary basin management in the region. This study refines a novel method for a rapid assessment of these cooperation risks and opportunities and applies it to the Brahmaputra, Ganges and Indus river basins to test its utility. The method employs a fuzzy synthetic evaluation technique that combines fuzzy logic and an analytical hierarchy process to assess cooperation risk and opportunity in terms of a Risk-Opportunity Index (ROI). The ROI is a function of four composite development variables and three hegemony variables that indicate the various pressures on the basin water resource and the different control strategies riparians could adopt given existing power asymmetries. In the absence of a clear rationale for differential weighting, equal weights were assigned to all seven variables for this application. A “defuzzification” scoring method is used to define compromising , risk-averse and risk-taking variants of ROI for riparian pairs within each basin. Overall, the results for the compromising ROI suggest that the opportunities for bilateral cooperation are highest (and risks the lowest) in the Brahmaputra Basin and the opportunities are lowest (and the risks highest) in the Indus Basin. This overall assessment is consistent with current common perception. Within the basins the compromising ROI values suggest a few instances of high risk and/or low opportunity, as well as an approximately equal number of instances of medium risk/opportunity and low risk/high opportunity. The study demonstrates that the fuzzy synthetic evaluation technique has utility for rapidly identifying potential opportunities for riparian cooperation in transboundary basins, in order to guide dialogue processes and more detailed analyzes. The study also however, reveals some aspects of the method where further refinement would likely yield more reliable assessments of cooperation risks and opportunities. Specifically, further refinements could consider the relative geographic position of co-riparians within a basin, and the relative resource access of different riparians. The method only considers bilateral riparian interactions and not more complex multi-lateral interactions. The results of study may contribute to various ongoing regional and basin dialogues on water cooperation in South Asia.

Description: Sustainable water management is crucial in the reduction of water pollution and floods. New techniques should be investigated in order to avoid present and future problems such as flood, drought, and water contamination. For this purpose, Low Impact Development-Best Management Practice (LID-BMP) has recently come into the stage in storm water management. Vegetative swales, green roofs, bioretentions, storm water wetlands, rain barrels, permeable asphalts and pavements are among LID-BMPs. Bioretention type of LID is implemented to diminish adverse effects of urbanization such as flood by reducing peak flows on surface and thus managing storm water runoff. The aim of this study is to investigate the hydrological performance of bioretentions by developing a hydrological model based on the data obtained using experimental setup called Rainfall-Watershed-Bioretention (RWB). The hydrological model of RWB (HM-RWB) consists of two main components: (i) rainfall-runoff model in which kinematic wave theory is used for simulation of surface runoff generated over the drainage area that reaches the bioretention as inflow; (ii) runoff-bioretention flow model in which Green-Ampt method under unsteady rainfall is employed and further improved by incorporating the effect of ponding depth on bioretention for the simulation of outflow at the exit of the bioretention. It is observed that the results of the hydrological model developed herein are in good agreement with the measured data obtained in the RWB experimental setup.

Description: Adaptation to increasing irrigation cost due to declination of groundwater level is a major challenge in groundwater dependent irrigated region. The objective of this study is to estimate the optimum abstraction of groundwater for irrigation for sustainable management of groundwater resources in Northwest Bangladesh. A data-driven model using a support vector machine (SVM) has been developed to estimate the optimum abstraction of groundwater for irrigation and a multiple-linear regression (MLR)-based model has been developed to estimate the reduction of the irrigation cost due to the elevation of the groundwater level. The application of the SVM model revealed that the groundwater level in the area can be kept within the suction lift of a shallow tube-well by reducing pre-monsoon groundwater-dependent irrigated agriculture by 40%. Adaptive measures, such as reducing the overuse of water for irrigation and rescheduling harvesting, can keep the minimum level of groundwater within the reach of shallow tube-wells by reducing only 10% of groundwater-based irrigated agriculture. The elevation of the groundwater level through those adaptive measures can reduce the irrigation cost by 2.07 × 10 3 Bangladesh Taka (BDT) per hectare in Northwest Bangladesh, where the crop production cost is increasing due to the decline of the groundwater level. It is expected that the study would help in policy planning for the sustainable management of groundwater resources in the region.

Description: This study was aimed at developing an optimization approach to rainwater harvesting (RWH) considering three (3) water consumption scenarios (WCS). These scenarios which include basic water need (BWN), pour flush (PF) and full plumbing connection (FPC) corresponding to 50 litres per capita per day (lpcd), 75(lpcd) and 150(lpcd) respectively were simulated for different categories of buildings. Reliability of supply was determined by first obtaining composite surplus/deficit of rainwater followed by optimizing the redistribution of surplus rainwater harvested to deficient buildings. Results showed that when total annual rainfall intercepted by roof exceeded total demand, 100% reliability of water supply was guaranteed. Reliability was found to be a linear function of storage. When reliability of supply is possible, the optimized storage bears an inverse exponential relationship to the roof plan area per capita. The relationship between surplus/deficit and roof plan area per capita follows a one-phase decay pattern. An optimal redistribution of surplus water from self-sufficient buildings to deficient ones gave an improvement in supply reliability from 64 to 87% for basic water need, 47 to 58% for pour flush and 28 to 29% for full plumbing connection.

Description: In previous studies we have ascertained that inflows and seawater intrusion in the Shatt al-Arab River (SAR) are two key physical factors behind fluctuating and sharply escalating salinities observed in recent years. Such levels require a series of countermeasures and investigative studies to translate physical factors into a salinity dynamics model to understand the problem and its impact as these factors vary in location, time and quantity. A one-dimensional hydrodynamic and salt intrusion numerical model was applied to simulate the complex salinity regime in the SAR based on hourly time-series data for the year 2014. The model was used to analyse the impact of different management scenarios on salinity under different conditions. The results show a high correlation between seawater intrusion and river discharge. Increased use of water upstream and local water withdrawals along the SAR will increase seawater intrusion and salinity concentrations. Improving the quantity and quality of the upstream freshwater sources could reduce salinity levels. Discharging the drainage water into the river could be used to counteract the salt intrusion, considering that its location affects both the salinity distribution and extent. A scenario analysis based on a numerical model constructed for the longitudinal salinity variation associated with different sources in a tidal regime, can efficiently screen alternative water management strategies.

Description: In flood control operation, the maximum release from a reservoir is minimized to lessen flood risks. Two properties of the minimax problem are derived by formulating the multi-period decision process as a recursive two-stage model. First, the cost-to-go function, which represents the maximum release in the remaining periods, is a non-decreasing function of the carryover storage. Second, monotonic relationships exist between the initial storage of the two-stage model and the optimal decisions of release and carryover storage. The two properties hold not only in the deterministic case with a given streamflow scenario, but also in the stochastic case with an ensemble of streamflow scenarios. The monotonic relationships are incorporated into the dynamic programming (DP) and sampling stochastic DP (SSDP). Two novel algorithms—improved DP (IDP) and improved SSDP (ISSDP)—are developed. The algorithms are applied to a case study of the Danjiangkou Reservoir in Central China. IDP and ISSDP respectively obtain the same decisions as DP and SSDP, and they are more computationally efficient. The execution times of IDP and ISSDP increase linearly with the number of storage discretizations, while those of DP and SSDP increase quadratically. With 1000 discretizations of reservoir storage, IDP and ISSDP derive optimal decisions at 0.939 and 97.453 s, respectively, whereas DP and SSDP finish at 115.931 and 6372.915 s, respectively. These results suggest that IDP and ISSDP can be useful tools for flood control operation – testing different flood scenarios and determining the optimal decisions.

Description: Application of an optimization/simulation model for the simulated real-time flood control for river-reservoir systems to the catastrophic May 2010 flood on the Cumberland River at Nashville, Tennessee is described. The optimization/simulation model includes five major components, including a hydrologic rainfall-runoff model, a hydraulic unsteady flow model, a short-term rainfall forecasting model, a reservoir operation model, and a genetic algorithm optimization model. The model application revealed that the reservoir upstream of Nashville was more contained and that an optimal gate release schedule could have decreased the floodwater levels in downtown Nashville below the 100-year flood stage. The application is for demonstrative purposes only, but does reflect the suitability of the optimization/simulation model for real-world application.