ALBERT

Description: Modelling the design and implementation of urban water infrastructure (particularly decentralised systems) for strategic planning and policymaking requires detailed information of the spatial environment and quantitative knowledge of social preferences. Currently available models, however, mostly use land use, population and impervious cover data without much regard for detailed urban form or society. This study develops an algorithm for determining urban form from minimal spatial data input by incorporating local planning regulations. The interaction between urban form and implementation of lot-scale infiltration systems under different social, biophysical and climate constraints is then investigated, firstly by looking at how this varies in different residential land uses and subsequently in a case study of a typical Melbourne residential subdivision of mixed land uses. Feasibility of infiltration and its downstream impact (runoff volume, frequency and pollution) were assessed for a range of social preferences (quantified as allowable garden space) and climate scenarios (30 % increase/decrease in rainfall and evapotranspiration). Performance indicators were determined through long-term simulation with the MUSIC software. Results show how different biophysical, planning, social and climate conditions affect infiltration feasibility as well as system performance. High infiltrating soils, for example, allow smaller, well-performing and socially less-imposing systems. Low infiltrating soils lead to larger system sizes, occupy much of the allotment’s garden space, but nevertheless provide the benefit of runoff frequency reduction. Overall, climate impact was not significant except for areas with poorly infiltrating soils. Joint consideration of social, planning, climate and water management aspects potentially allows more efficient policymaking, as an array of system configurations can be tested against different multi-faceted scenarios. Such models can help facilitate better participatory planning and policymaking.

Description: Cities in developed countries have increasingly adopted rainwater tanks as an alternative water source over the last 15 years. The rapid uptake of rainwater tanks has been driven by the need to reduce demand for centralised water services that are under pressure to adapt to population growth and climate change impacts. Rainwater tanks are part of integrated urban water management approach that considers the whole water cycle to provide water services on a fit for purpose basis that minimises the impact on the local environment and receiving waters. Rainwater tanks are typically applied at the household scale for non-potable water source uses such as toilet flushing and garden irrigation. However, this paper reports on a communal approach to rainwater harvesting, where the water is treated for potable use. A communal approach to rainwater harvesting can offer benefits, such as: economies of scale for capital costs, reduced land footprint, centralised disinfection and flexibility in matching supply and demand for different households. The analysis showed that the communal approach could provide a reliable potable water source to a small urban development. However, there was an energy penalty associated with this water source compared to centralised systems that could be addressed through more appropriate pump sizing. The outputs from this monitoring and modelling study demonstrated rainwater harvesting can be expanded beyond the current mainstream practices of household systems for non-potable use in certain development contexts. The analysis contained in this paper can be used for the improved planning and design of communal approaches to rainwater harvesting.

Description: The main purpose of this paper is to evaluate the global performance and to assess the current trends in research of water resource management. The methods of informetric analysis were used to survey water resource management related articles in the Science Citation Index (SCI) and Social Science Citation Index (SSCI) during the past decades. The publication records, subjects, journals, countries, institutes, authors, citations and keywords were analyzed respectively for each paper. The number of papers related to water resource management in 2012 was approximately 8 times that of the year 2000 and hundreds of times more than early 1990s. Water resource management related papers were distributed unevenly by countries. The USA, P.R. China, Australia and UK were the top contributing countries, also present normalized by dividing with population that published most SCI papers as well as SSCI papers. The largest water resource management research center is located in the USA according to the number of publications and citations, with P.R. China becoming more proficient in water resource management according to the data from country and institute. In addition, the quality of papers produced by developed countries is more advanced than developing countries. All these efforts contributed to the indication in trends of water resource management research on a global scale. Earlier water resource management research appeared and was originally concentrated on engineering, irrigation and geography. Issues gradually transferred to management, economics and regime recently.

Description: A remote sensing-based approach to estimate actual evapotranspiration ( ET ) was tested in an area covered by olive trees and characterized by Mediterranean climate. The methodology is a modified version of the standard FAO-56 dual crop coefficient procedure, in which the crop potential transpiration, T p, is obtained by directly applying the Penman-Monteith (PM) equation with actual canopy characteristics (i.e., leaf area index, albedo and canopy height) derived from optical remote sensing data. Due to the minimum requirement of in-situ ancillary inputs, the methodology is suitable also for applications on large areas where the use of tabled crop coefficient values become problematic, due to the need of corrections for specific crop parameters, i.e., percentage of ground cover, crop height, phenological cycles, etc. The methodology was applied using seven airborne remote sensing images acquired during spring-autumn 2008. The estimates based on PM approach always outperforms the ones obtained using simple crop coefficient constant values. Additionally, the comparison of simulated daily evapotranspiration and transpiration with the values observed by eddy correlation and sap flow techniques, respectively, shows a substantial agreement during both dry and wet days with an accuracy in the order of 0.5 and 0.3 mm d −1 , respectively. The obtained results suggest the capability of the proposed approach to correctly partition evaporation and transpiration components during both the irrigation season and rainy period also under conditions of significant reduction of actual ET from the potential one.

Description: Seasonality characteristics and spatio-temporal trends of 7-day low flows were investigated for the 41,470 km 2 semi-arid Karkheh watershed (western Iran), representing 12 stations with record length of 51 years (1958–2008). Hierarchical Cluster Analysis (HCA) was used to identify low-flow seasonality (clusters of low flow seasons). Monotonic trends were detected by the Mann-Kendall test. Breaks in low flow trends were detected by the Lombard’s change point test. Breaks in short-term trends were detected by the Lepage test. According to results seasonal clusters were different in most of the stations, indicating uniqueness in station low flow behaviour. Among the 12 stations studied, four stations showed seasonal monotonic trend and change points, some with abrupt change (change point in consecutive years). Two stations near watershed outlet with no monotonic trend showed abrupt change. Most seasonal change points (dates) compared well with documented droughts, highlighting drought impacts on low flow trends at affected stations. The Lepage test detected change point in seasonal low flow trends of most stations during 5- and 10-year periods. This research has shown that in semi-arid environments low flow seasonality characteristics may vary among stations, an indication that low flow trends should be evaluated individually for each station.

Description: With the transformation of water conservancy from traditional to eco-hydraulic aiming at sustainable development, the study on eco-efficiency of the water system has attracted a great deal of attention. This study aims to develop a methodology for evaluating the eco-efficiency of water systems of 31 administrative regions in China. Considering the multiple attributes of water systems and a piecewise linear technological frontier, the Rough Set Theory (RST) and Data Envelopment Analysis model (DEA) are combined to analyze the eco-efficiency of water systems. An input-and-output index system is established based on RST. The eco-efficiency for the water system of 31 administrative regions in China is calculated by DEA, and the characteristics of its spatial differences are discussed. The results show that there is a significant difference in the eco-efficiency of water systems: (1) On the whole, the efficiency value of north China is slightly higher than the south; (2) In the eight sub-regions of China, the north coastal area gains the highest efficiency score and the middle reaches of the Yangtze River obtains the lowest value; (3) There are 11 out of 31 regions at the best practice frontier. The spatial difference in eco-efficiency of the water system is a common phenomenon, which reflects the direct or indirect influence by economical, political, legislative, historical, cultural factors and other social development. Based on the above findings, some suggestions are made to improve the eco-efficiency of the water systems in China.

Description: Drought severity and duration are usually modelled independently. However, these two characteristics are known to be related. To model this relationship, a joint distribution of drought severity and duration using a bivariate copula model is proposed and applied to daily rainfall data (1976–2007) of 30 rain gauge stations in Peninsular Malaysia. The drought characteristics are classified using the standardized precipitation index (SPI) and their univariate marginal distributions are further identified by fitting exponential, gamma, generalized extreme value, generalized gamma, generalized logistics, generalized pareto, gumbel max, gumbel min, log-logistic, log-pearson3, log-normal, normal, pearson 5, pearson 6 and weibull distributions. The three-parameter log-normal distribution is identified as the best fitting distribution for drought severity while the generalized pareto distribution is determined as the most appropriate distribution for drought duration with respect to the application of the Anderson-Darling procedure. The dependency among the drought properties is analysed using Kendall’s τ method. The maximum likelihood estimation of the univariate marginal distributions and the maximisation of the bivariate likelihood are employed to compute the Akaike Information Criterion (AIC) values in verifying the best fitting copula distribution. The Galambos distribution is recognised as the most appropriate copula distribution for describing the relationship between drought severity and duration. The conditional drought probability and drought return period are further described to explain the drought properties comprehensively. The probabilities of drought occurrences under certain circumstances with a specific seriousness or duration can be determined in order to verify the possibility of drought episodes. The return period of a recurrent drought has also been investigated to identify the time-interval for repeated drought occurrences under similar situation.

Description: Model-supported real-time flood control requires the development of effective and efficient hydraulic models. As large numbers of iterations are to be executed in optimization procedures, the hydraulic model needs to be computationally efficient. At the same time, it is also required to generate high-accuracy results. Therefore, an identification and calibration procedure was developed for the purpose of having this conceptual model built up and calibrated based on a limited number of simulations with a more detailed full hydrodynamic model. The performance of the conceptual model was evaluated for historical events under different regulation conditions. Robustness test results show close agreement, with Nash-Sutcliffe Efficiency values higher than 0.90. In addition, it is found that the conceptual model is capable of accomplishing simulation of historical flood events within few seconds. That is much faster than the detailed full hydrodynamic model, which enables the conceptual model to be applied for real-time flood control.

Description: In this study, the performance of M5 model tree and conventional method for converting pan evaporation data (E p ) to reference evapotranspiration (ET 0 ) were assessed in semi-arid regions. Conventional method uses pan coefficient (K p ) as a factor to convert E p to ET 0 . Two common K p equations for pans with dry fetch (Allen et al. 1998 ; Abdel-Wahed and Snyder in J Irrig Drain Eng 134(4):425–429, 2008 ) were considered for the comparison. The values of ET 0 derived using these three methods were compared to those estimated using the reference FAO Penmane Monteith (FAO-PM) method under semi-arid conditions of the Khuzestan plain (Southwest Iran). The results showed that the M5 model is the best one to estimate ET 0 over test sites (0.5 mm d −1 of root mean square error (RMSE) and 0.98 of coefficient of determination ( R 2 ). Conversely, the performance of the two K p equations was poor.

Description: Infiltration is the only way water enters soil on the cultivated slopes of the China’s Loess Plateau, so infiltration plays an important role in conserving soil moisture. The objective of this study was to investigate how a soil wetting front created by simulated rainfall migrated in soil with different types of surface roughness. The three types of soil surface treatments studied included surfaces of smooth, medium rough and rough soil. The results showed that, 1) compared with a smooth surface texture, medium rough and rough surface textures have a higher infiltration capacity; 2) the infiltration rate gradually decreases as the wetting front deepens and the rate tends stabilize over time. This change could be described by a logarithmic function; 3) at the early stage of rainfall, the wetting front of medium rough and rough surface textures varied greatly, while the variability of the wetting front decreases markedly after the infiltration rate stabilizes; 4) with increasing depth of the wetting front, the similarity between the wetting front and soil surface profile decreased significantly for the medium rough and rough surface textures. These results indicate that the process of infiltration on cultivated slopes on the Loess Plateau changed from a non-uniform pattern to a uniform pattern as time passed during a rainfall event. Overall, soils with rougher soil surfaces experienced a larger effect of roughness on the process of infiltration.

Description: Optimum reservoir operation is a challenging problem in water resources systems. In this paper, Intelligent Water Drops (IWD) algorithm is applied in a reservoir operation problem. IWD is a population based algorithm and is initially proposed for solving combinatorial problems. The algorithm mimics the dynamics of river system and the behavior of water drops in the rivers. For this purpose data from Dez reservoir, located in southwestern Iran, has been used to examine the performance of the model. Moreover, due to similarities between IWD and the Ant Colony Optimization (ACO) algorithms, the results are compared with those of the ACO algorithm. Comparison of the results shows that while the IWD algorithm finds relatively better solutions, it is able to overcome the computational time consumption deficiencies inherited in the ACO methods. This is very important in large models with too many decision variables where run time becomes a limiting factor for optimization model applications.

Description: Understanding temporal variability in water quality in the Three Gorges Reservoir (TGR) is crucial for evaluating environmental effects of damming and protecting China’s largest freshwater resource. This study examined water quality changes in the main channel of the Yangtze River after dam completion as well as its relationship with water level fluctuation (WLF), controlled by annual impoundment operations and conditioned by flooding. Finally, the mass balance budget and integrative water quality indexing (WQI) methods were applied to elucidate the status of overall water quality since dam completion. Results showed that TGR outlet water (Yichang) exhibited higher pH and COD Mn values and lower concentrations of dissolved oxygen (DO) and ammonia nitrogen (NH 3 -N) than inlet water (Zhutuo). Temporal variations in water quality parameters displayed similar trends for the outlet and inlet. Water quality parameters all showed negative correlations to water level, revealing the different effects of damming on water quality. It was estimated that reservoir impoundment led to a DO depletion of 1495.5 (±1482.0) × 10 3 tons/yr and a COD Mn increase of 564.0 (±405.0) × 10 3 tons/yr, likely deriving from various internal pollutant loads from the WLF zone and tributary watersheds. According to WQI, TGR water quality remained at healthy levels. However, WQI linear regression showed that water quality at the outlet significantly decreased over time, indicating that the construction of the Three Gorges Dam generally caused water quality deterioration. Further investigation is required to determine the spatial distribution of point and non-point pollution sources and to identify major factors that influence TGR water quality.

Description: Concern continues to grow over unreliable water access at the household level in many developing countries. A contingent valuation survey was designed to elicit willingness-to-pay for safe and reliable drinking water in León, Nicaragua. In addition, split-sample treatments were used to investigate preferences for two forms of service governance: the current, centralized water supplier and a decentralized service implemented at the municipal level. Results show that households are willing to pay a substantial increase in their water bills for reliable water supply. Findings also indicate that households hold greater confidence in the current, centralized provider rather than a localized service based on several characteristics such as overall service, awareness of water issues, interest in solving water problems, capacity, accountability, and potential investment.

Description: Waterlogging and secondary salinization have become a serious problem in the canal irrigated areas of arid and semi–arid regions worldwide. In this study, a unique and simple technique was evolved in which a linear programming (LP) optimization model was first developed that allocates available land and water resources in order to maximize net annual returns by mitigating the waterlogging problems. A finite–difference two–dimensional simulation model was then used to evaluate the long–term impacts of various water management strategies on the groundwater table with the optimal land and water use parameters which were obtained through the optimization model. The model was used to combat the waterlogging and salinity problem of an area located in Haryana State of India. The calibration, validation, sensitivity analysis, and error analysis of the model was performed before it was used to study the impact of various water management scenarios on the long-term groundwater level. Based on the model results a change in cropping pattern with reduced rice area is suggested. Groundwater withdrawal should be increased by 1–7 % in the various nodes. It is concluded from the analysis of various scenarios that implementing multiple approaches simultaneously are more effective in controlling waterlogging problems as compared to individual interventions.

Description: Groundwater overexploitation is threatening our ecosystems and even the life of future generations. Once happens, elimination of the bad influence will be a long-term process. It should be a feasible approach to take the environmental recovery as a whole by the way of the groundwater management. A case study of water resources management in Huaibei city, within semiarid region of north Anhui province, China, was illustrated, especially on the issues of groundwater over-extraction drawdown funnel recovery. Taking into account the water demand for satisfying the urban development in the next 15 years, three target years of water resources planning were postulated as the present (2005), the short-term (2010) and the long-term (2020), respectively. Four hydrological years: wet year, mean year, dry year and extremely dry year, were also defined by the rainfall data for many years. A groundwater management model which could deal with twelve possible scenarios (3 target years of water resources planning ×4 hydrological years) was established based on simulation and optimization. The groundwater management model could optimize the strategies of water resources development, integrate various kinds of water sources, e.g. groundwater, surface water and additive water sources, and meet the water demand for the urban development within an area of Huaibei city. Importantly, in accordance with the groundwater management model solutions, the issues of groundwater over-extraction drawdown funnel, which has formed within the Huaibei downtown area for many years and lead to some environmental and social problems, would be solved over the whole planning period.

Description: This study discusses the effects of water abstractions from two alternative sources on the available water volume around Lake Naivasha, Kenya: the lake itself and a connected aquifer. An estimation of the water abstraction pattern for the period 1999–2010 is made and its effect on the available water volume in Lake Naivasha and its connected aquifer is evaluated using a simple water balance modeling approach. This study shows that accurate estimates of annual volume changes of Lake Naivasha can be made using a simple monthly water balance approach that takes into account the exchange of water between the lake and its connected aquifer. The amount of water that is used for irrigation in the area around Lake Naivasha has a substantial adverse effect on the availability of water. Simulation results of our simple water balance model suggests that abstractions from groundwater affect the lake volume less than direct abstractions from the lake. Groundwater volumes, in contrast, are much more affected by groundwater abstractions and therefore lead to much lower groundwater levels. Moreover, when groundwater is used instead of surface water, evaporation losses from the lake are potentially higher due to a larger lake surface area. If that would be the case then the overall water availability in the area is more strongly affected by the abstraction of groundwater than by the abstraction of surface water. Therefore water managers should be cautious when using lake levels as the only indicator of water availability for restricting water abstractions.

Description: This paper considers the retail water provider’s purchasing decision of a portfolio of permanent contracts from wholesalers with multiple volatile water sources. We consider the reliability of two contract types: (1) fixed annual quantities, and (2) an inflow harvest function with storage. Our four-reservoir case in Sydney (Australia) has cross-correlated inflow data. To accommodate multi-reservoir cross-correlation we adapt Portfolio Theory from finance to lognormal reservoir inflows, re-framing traditional storage theory from the wholesaler’s optimal operating policy to the retailer’s optimal purchasing policy. We find that Reliability improves with access to a source pool (cf. fixed quantities from separate sources), demonstrating the ‘insurance effect’, and the portfolio that minimises lognormal variance also minimises harvest (and thus environmental impact). Reform direction in Australian (and other international) water markets is towards multi-provider vertical disintegration, which may reduce pool opportunities and negate the insurance effect. We consider diminishing reliability returns as reservoir harvesting increases, and conclude a retail portfolio of permanent contracts from reservoirs, plus short-term contracts from alternative sources (either independently or negatively cross-correlated) efficiently secures high reliability. The challenge in incomplete water markets remains in encouraging and sustaining supply diversification that may only be needed aperiodically during extreme droughts.

Description: The paper is the introduction to the special issue Water Engineering and Management in a Changing Environment which presents a set of the most innovative contributions at the EWRA Symposium, held in Catania, Italy on 2011.

Description: The Soil Conservation Service Curve Number (SCS-CN) method is widely used for predicting direct runoff volume for a given rainfall event. However, previous results indicated that when the CN value is determined from measured rainfall-runoff data in a natural watershed it is not possible to attribute a single CN value to the watershed, but actually the calculated CN values vary systematically with the rainfall depth. In a previous study, the authors investigated the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of the inevitable presence of soil-cover complex spatial variability along watersheds. In this study, a method to determine SCS-CN parameter values from rainfall-runoff data in heterogeneous watersheds is proposed. This method exploits the observed correlation between the calculated CN values and the rainfall depths in order to identify the spatial distribution of CN values along the watershed taking in to account the specific characteristics of the watershed. The proposed method utilizes the available rainfall-runoff data, remote sensing data and GIS techniques in order to provide information on spatial watershed characteristics that drive hydrological behavior. Furthermore, it allows the estimation of CN values for specific soil-land cover complexes in more complex watersheds. The proposed method was tested in a small experimental watershed in Greece. The watershed is equipped with a dense hydro-meteorological network, which together with a detailed land cover and soil survey using remote sensing and GIS techniques provided the detailed data required for this analysis.

Description: This paper presents a study for finding the optimal management plan of an overexploited aquifer under global climate change. The study area is the aquifer of the basin of Lake Karla, located in the eastern part of Thessaly in Greece. An optimization method has been used to evaluate the optimum volume of water that can be extracted from the aquifer and the optimum position of the wells with the objective of water table rise to a desirable sustainable level, taking into consideration the climate change forcing. The modelling system consists of a series of interlinked models: a hydrological, a lake-aquifer, a reservoir operation, a groundwater, and an optimization model. The climate change forcing on precipitation and temperature has been evaluated using the outputs of Canadian Centre for Climate Model Analysis General Circulation Model (CGCMa2) and a hybrid downscaling method which combines a multiple regression (MLR) model and a timeseries model for two socioeconomic emissions scenarios. The results of this study show that climate change plays an important role, as it affects the optimum volume of the extracted groundwater and the position of the irrigation wells.

Description: Regional frequency analysis is a useful tool for accurate estimation of precipitation quantiles than at-site frequency analysis, especially in the case of regions with a short rainfall time series. The use of meteorological information, combined with rainfall data analysis, could improve the selection of homogeneous regions. Starting from 1958, 198 meteorological configurations, related to extreme events, have been identified throughout the national territory of Italy. The reanalyzed meteorological data of the 40 Year Re-analysis Archive (ERA-40) of the European Centre for Medium-Range Weather Forecast (ECMWF) have been analyzed to identify homogeneous regions with respect to the Convective Available Potential Energy (CAPE), the Q vector Divergence (QD) and the Vertically Integrated Moisture Flux (VIMF). The latter index appears to be the better candidate for finding regional homogeneity inside areas where high frequency values of CAPE or QD are present. The paper presents an application based on the delimitation of homogeneous regions using climatic indexes for the island of Sicily. By applying the proposed methodology, seven homogeneous areas over Sicily were found. The consistency of the final results has been validated by using a coupled approach based on the Valuation of Floods in Italy procedure (VAPI) and on the heterogeneity test of Hosking and Wallis (Water Resour Res 29:271–281, 1993 , 1997 ).

Description: Each single phase of a water supply network, from water adduction to distribution to end-users, is exposed to many diverse potential sources of intentional contamination (or malicious attacks). One of the most dangerous threats is a backflow attack that occurs when a pump system, easily available on the market, is utilized to overcome the pressure gradient of network pipes. In this work, a simple backflow attack with cyanide being introduced into a real-water system is modeled and the most dangerous introduction points for a contaminant incident are defined. Moreover, the network vulnerability has been analyzed by computing the lethal dose of cyanide ingested by users and the total length of the contaminated water system. Eventually the effects of network partitioning and district isolation to protect water supply systems have been investigated. The results show how district closing - by network sectorization techniques used to improve leakage search and reduction - can significantly decrease contaminant diffusion and protect part of the users from cyanide uptake. Network sectorization can also reduce the risk of simple malicious attacks because several introduction points are necessary to have a massive negative impact on the network. Simulation results also show that in some cases water network partitioning may worsen water network protection and further studies are necessary to design water districts for network security and safety.

Description: This article examines available methods for assessing all types of drought costs, including both damage costs and costs arising from adopting policy measures to encourage mitigation of, and adaptation to, droughts. It first discusses damage costs, distinguishing between direct, indirect and non-market costs. Then it examines the suitability of existing methods for estimating drought costs in different economic sectors, their underlying theoretical assumptions, complementarity between different methods, and conditions relevant for their application. The latter include precision, ability to deal with future climate change risks, data needs and availability, and required financial and human resources. The article further considers potential policies for drought mitigation and adaptation and different cost types associated with them. It ends with providing recommendations for good practices regarding the use of methods as well as drought mitigation and adaptation policies.

Description: Dependency of reservoir operation on the climate variation occurs especially in regions, where agricultural demand has a significant share of the total water demands. The variability between demands that are based on annual climate conditions may be larger than the uncertainty associated with other explanatory variables in long-term operation of an irrigation dam. This paper proposed a rule curves to the water managers of the Zayandeh-rud reservoir in Iran in long-lead reservoir operation. A regional optimal allocation of water among different crops and irrigation units is developed. The optimal allocation model is coupled with a reservoir operating model, which is developed based on the certain hedging that deals with the available water and the water demands mutually. This coupled model is able to activate restrictions on allocating water to agricultural demands considering variation of inflow to the reservoir, variation of demands and the economic value of allocating water among different crops and irrigation units. The resulted rule curve is presented with a number of tables for more details and accuracy and a simple curve, which is more useful for operational purpose.

Description: This paper addresses the problem of the localization of contamination sources after deliberate contaminations in drinking water distribution systems (DWDS). The proposed methodology is based on the information given by successive positive readings of sensors. Thus, it is possible to estimate the localization of the contamination sources based on only the first sensor that detected a contamination, and then update the results when more information is available. From the tests performed on a real drinking water distribution system, it was possible to observe that as new sensors detect changes in contaminant concentration, other possible contaminations may be detected and the location of contamination sources may be more restricted. The results achieved for the two set of sensors considered in the study contained the correct locations and the instants of contaminations previously simulated. Two case studies were also analysed to study the effect of the occurrence of false positives. It was concluded that it is not always possible to verify the occurrence of those anomalies and when it is verified, it is not possible to distinguish between a false positive and a false negative. The occurrence of false positives did not affect also the results related with the real detections.

Description: The importance of simulation models to assess the impacts of droughts and the effects of mitigation options on water supply systems is well known. However a common procedure about the exploitation of model results is not established yet. Vulnerability is used to characterize the performance of the system, and it can be a helpful indicator in the evaluation of the most likely failures. In this paper a water allocation model is applied to the water supply system of the upper Tiber Basin (Central Italy) in which both surface waters (rivers, reservoirs) and ground waters (wells, springs) are exploited to feed mainly irrigation and civil users. Drought vulnerability indices are calculated to analyze the performance of the supply system under different climate and management conditions. Water shortage scenarios are simulated as a progressive reduction of mean precipitation, an increase in its standard deviation or a combination of both. The model shows that the safety of the water supply system mainly relies on the reservoirs and that the foreseen increased exploitation of the springs to replace contaminated wells, could be seriously limited by discharge decrease during fall. The vulnerability reduction obtained by a hypothetical augmentation of the storage capacity through additional small reservoirs was positively tested by the model. In conclusion vulnerability indices and synoptic risk maps demonstrated to be useful tools to analyze the model outputs. They provide easy-to-read scenarios to be used in a decision making framework considering negotiating among the main users.

Description: The work presented herein addresses the problem of sensor placement optimization in urban water distribution networks by use of an entropy-based approach, for the purpose of efficient and economically viable waterloss incident detection. The proposed method is applicable to longitudinal rather than spatial sensing, thus to devices such as acoustic, pressure, or flow sensors acting on pipe segments. The method utilizes the maximality, subadditivity and equivocation properties of entropy, coupled with a statistical definition of the probability of sensing within a pipe segment, to assign an entropy metric to each pipe segment and subsequently optimize the location of sensors in the network based on maximizing the total entropy in the network. The method proposed is a greedy-search heuristic.

Description: With the worldwide depletion of groundwater and the intensified use around the world, particularly in many arid and semi-arid regions for irrigation and municipal use, there is no satisfactory approach to groundwater sustainability. The lack of and miss-management of this valuable resource has not only created serious groundwater pollution problems but has created present and/or future water supply problems. This paper does not present a solution, but instead examines economic ideas such as exhaustible resource theory (over exploitation), and optimization methodologies that can incorporate new ideas of groundwater sustainability, population growth constraints, include both short term and long term consequences, and consider multi-objectives. Concepts of groundwater footprint, recharge, and safe yield are discarded as concepts for measuring groundwater sustainability. The concept of developing a sustainability index that could also be used within the context of optimization is introduced. Also the concepts of traditional knowledge are discussed with the emphasis on the use of these methodologies for both developed and developing regions of the world to achieve groundwater sustainability.

Description: Reservoir operation cannot be carried out without due heed to surface water and groundwater resources, since neglecting either will have irreversible consequences. Optimal operation of the Zayandehrood Dam which supplies water into the Zayandehrood River basin in the central plateau of Iran is a case in point which warrants due consideration paid to both dam operation and the climate conditions in the region suffering from a history of successive droughts. The main objective of the present research is to develop operation rules for the Zayandehrood reservoir through a combined perspective of both surface and ground water resources using the fuzzy inference system, and adaptive neuro-fuzzy inference system. The objective is to determine the share of the Zayandehrood reservoir in meeting downstream water demands. For this purpose, the water shortage and the dramatic groundwater drawdown in the Zayandehrood River basin faced with in recent years have been studied in an attempt to develop operation models capable of controlling groundwater drawdown. The models indicate that not only can groundwater drawdown be controlled, but that it is also possible to establish a greater sustainability. Different operation models have been compared in terms of their operation criteria. Results show that the ANFIS model composed of optimal data enjoys a higher sustainability compared to others.

Description: Genetic algorithms (GA) are optimization techniques that are widely used in the design of water distribution networks. One of the main disadvantages of GA is positional bias, which degrades the quality of the solution. In this study, a modified pseudo-genetic algorithm (PGA) is presented. In a PGA, the coding of chromosomes is performed using integer coding; in a traditional GA, binary coding is utilized. Each decision variable is represented by only one gene. This variation entails a series of special characteristics in the definition of mutation and crossover operations. Some benchmark networks have been used to test the suitability of a PGA for designing water distribution networks. More than 50,000 simulations were conducted with different sets of parameters. A statistical analysis of the obtained solutions was also performed. Through this analysis, more suitable values of mutation and crossover probabilities were discovered for each case. The results demonstrate the validity of the method. Optimum solutions are not guaranteed in any heuristic method. Hence, the concept of a “good solution” is introduced. A good solution is a design solution that does not substantially exceed the optimal solution that is obtained from the simulations. This concept may be useful when the computational cost is critical. The main conclusion derived from this study is that a proper combination of population and crossover and mutation probabilities leads to a high probability that good solutions will be obtained.

Description: Public utilities could improve their efficiency by pursuing specific strategies, such as growth, diversification of investments, or serving mainly high densely areas. For example, in the water sector, economies of scope and scale both appear possible, but extant literature does not offer clear or consensual findings. To address this lack of clarity, this article investigates the potential for efficiency improvement in the diverse Italian water sector, which comprises utilities of various sizes, operating in areas with various population densities and organized as mono- or multi-utilities. Technical and financial data from 64 different utilities were collected and then analyzed with a two-stage data envelopment analysis approach to reveal the impacts of different operational and exogenous variables on efficiency, including firm size, the degree of investment diversification, and customer density. The results obtained confirm the existence of all three types of economies (scale, scope and density), albeit with different impacts for each DEA score.

Description: Green roofs are increasingly used as sustainable urban drainage systems due to their retention and detention capacity; however, the impact of green roofs in term of water quality is still a debated issue among researchers. A monitoring programme was carried out at the University of Genoa on a full-scale experimental site to assess the quality of storm water outflows. As for rainfall, the bulk deposition (dry and wet fractions) is collected to evaluate the role of the overall atmospheric deposition in altering storm water quality. The pollutant load observed in the green roof outflow is limited; concentration values for solids and metals are lower than those generally observed in storm water runoff from impervious surfaces. Suspended solids and Chemical Oxygen Demand (COD) are below respectively 10 and 20 mg/l, on average; as for heavy metals, copper and zinc are equal to 30 μg/l on average, while iron is equal to 120 μg/l. The Event Mean Concentration (EMC) statistics of the pollutant loads associated with the rainfall and outflow have been compared and discussed. The observed green roof behaviour as a sink/source of pollutants with respect to the atmospheric deposition is also investigated based on both concentration and mass. Results demonstrate that: green roof behaves as a source with respect to solids, COD and potassium while zinc and mainly copper are retained within the green roof stratigraphy. The resulting mass delivery behaviour reveals that no significant first flush occurs for pollutant constituents irrespective of the hydrologic characteristics and pollutant sources.

Description: This paper describes a new multi-objective evolutionary optimization approach to the simultaneous layout and pipe size design of water distribution systems. Pressure-deficient and topologically infeasible solutions are fully incorporated in the genetic algorithm without recourse to constraint violation penalties or tournaments. The proposed approach is demonstrated by solving three benchmark problems taken from the literature. New optimal layouts and/or new feasible solutions that are cheaper than the best solutions in the literature were found for both branched and looped network configurations. Specifically, a new best solution was generated for each of the above-mentioned benchmark problems. In addition, the case of the looped design of a hitherto branched network in the literature was considered. Detailed results are included that show that the proposed approach achieves good solutions efficiently and consistently.

Description: There is no doubt that groundwater is an important and vital source of water supply in arid and semi-arid areas. Therefore, prediction of groundwater level fluctuations is necessary for planning conjunctive use in these areas. This research was aimed to predict groundwater levels in the Neishaboor plain using N eural N etwork – A uto R egressive e X tra input (NN-ARX) and Static-NN models. The NN-ARX model determines a nonlinear ARX model of a dynamic system by training a hidden layer neural network with the Levenberg-Marquardt algorithm. In this model the current outputs depend not only on the current inputs, but also on the inputs and outputs at the pervious time periods. The available observation wells in the study area were clustered according to their fluctuation behavior using the “Ward” method, which resulted in six areal zones. Then, for each cluster, an observation well was selected as its representative, and for each zone, values of monthly precipitation, temperature and groundwater extraction were estimated. The best input of the Static-NN model was identified using combination of Gamma Test and Genetic Algorithm. Also, Gamma Test is applied to identify the length of the training dataset. The results showed that the NN-ARX model was suitable and more practical. The performance indicators ( R 2  = 0.97, RMSE = 0.03 m, ME = --0.07 m and R 2  = 0.81, RMSE = 0.35 m, ME = 0.60 m, respectively for the best and worst performance of model) reveals the effectiveness of this model. Moreover, these results were compared with the results of a static-NN model using t-test , which showed the superiority of the NN-ARX over the static-NN.

Description: In western Victoria, Australia the water table and lake level in the Glenelg-Hopkins catchment have been declining for the last 15 years, and this is attributed to either the low rainfall over this time and/or a substantial change in land use. Stream flow modelling was carried out using monthly empirical water balance model (modified tanh function together with double mass curve analysis), on 37 stream gauges to assess whether the impact of land use change could be detected by a change in the magnitude of the resulting runoff. The empirical hydrological model was able to distinguish impact of land use change on stream flow from the climatic variables. There were substantial decreases in stream flow in the 1970s–1980s, probably related to increasing livestock densities in the region. Furthermore, the methodology can be a powerful tool to monitor and evaluate the possible impacts of future land use changes. It can be concluded that the use of such empirical hydrological modelling greatly improves the ability to analyse the impact of land use on catchment runoff. The model is a practical tool that can be readily used for identifying and quantifying the effect of landuse changes on catchment for water resource decision-making, which could be hardly possible using the time consuming, data hungry and expensive physical process models available.

Description: Based on data characteristics and nonparametric test, a new statistical temporal change analysis approach is proposed. The new approach consists of data characteristics analysis, temporal change analysis (including both change point and trend analysis), and result interpretation. Data characteristics are firstly investigated, especially with respect to the assumptions of independence and normality. Then proper nonparametric methods are chosen based on the detected characteristics of the observed data to analyze change points and monotonous linear trend for each of the segments divided by the change points. To avoid shortcoming of the traditional approach of carrying out the trend analysis before change point analysis, it is proposed in this paper that change point detection be performed before trend analysis. At last, statistical analysis results are interpreted according to the physical mechanism of observations. As a study case, the proposed approach has been carried out on three annual discharge series of the Yangtze River at the Yichang hydrological station. The investigations of data characteristics show that the observed data do not meet the assumptions of being independent and identically Gaussian-distributed. So the nonparametric Pettitt’s test was adopted to detect abrupt changes in the mean levels, followed by trend analysis using the nonparametric Mann-Kendall (MK) test. Results indicate the proposed approach is both reliable and reasonable for the temporal change analysis.

Description: The development of rainfall runoff relationship for ungauged watersheds using topography, geomorphology and other regional information remains the most active area of research in the field of hydrology. In the developing countries, some thumb rules and very old equations are in practice for designing water resources structures which sometimes provide erroneous results. In the proposed study, regional relationships have been developed for computation of peak velocity and scale parameters of Nash model using geomorphological and fluvial characteristics of 41 watersheds of varying characteristics in Central India region. The regional relationships developed to determine scale parameter ( k ) of Nash model from a morpho-fluvial factor, has facilitated derivation of at-site regional and regional only instantaneous unit hydrograph (IUH), unit hydrograph (UH) and direct surface runoff (DSRO). The performance of proposed regional model has been evaluated using spatial correlation coefficient, integral square error, relative mean absolute error, root mean square error, relative error in peak, coefficient of residual mass and model efficiency. The response of proposed regional model have been found comparable with the observed values as the Nash-Sutcliffe efficiency of proposed model during calibration varies from 69.7 % to 95.2 % for site specific approach, 60.6 % to 97.7 % for at-site regional and 67.1 % to 98.7 % for regional only approach. Similarly, the performance of proposed model have been found satisfactorily during validation as the efficiency varies from 81.3 % to 99.9 % for site specific approach, 83.5 % to 99.9 % for at-site regional and 82.7 % to 99.9 % for regional only approach. The simple regional relationships developed in the study can be used for event based rainfall-runoff modeling and estimation of design flood in ungauged catchments of central Indian region.

Description: Short-term optimization dispatching of cascaded hydroelectric system with day (or week) cycle is of great value in practical implementation, such as improving grid stability, more power benefits. This study proposes a short-term self-optimization simulation model for cascaded hydroelectric system dispatching, which balances the requirements both of the generation side and the demand side. Three conflicting objectives for the management of hydropower generation are incorporated in the cascaded hydroelectric system. And in this model, the reasonable physical factors are chosen to coordinate the contradiction. According to the characteristics of the self-optimization simulation technique, for example clear physical meaning, more perfect simulation, no dimension limitation, artificial adjustment with the accumulated experience and so on, a new solving idea for this model is set up. And the new operation model is illustrated in the middle reaches of the Chinese Jinsha River, where eight cascades are planned. Considering the different startup time and combinations, the results of the joint operation compared to the single reservoir operation has provided important demonstration for the investment entities, simultaneously the solving efficiency and quality of this model are good for implementing in practical.

Description: Microwave remote sensing and mesoscale weather models have high potential to monitor global hydrological processes. The latest satellite soil moisture dedicated mission SMOS and WRF-NOAH Land Surface Model (WRF-NOAH LSM) provide a flow of coarse resolution soil moisture data, which may be useful data sources for hydrological applications. In this study, four data fusion techniques: Linear Weighted Algorithm (LWA), Multiple Linear Regression (MLR), Kalman Filter (KF) and Artificial Neural Network (ANN) are evaluated for Soil Moisture Deficit (SMD) estimation using the SMOS and WRF-NOAH LSM derived soil moisture. The first method (and most simplest) utilizes a series of simple combinations between SMOS and WRF-NOAH LSM soil moisture products, while the second uses a predictor equation generally formed by dependent variables (Probability Distributed Model based SMD) and independent predictors (SMOS and WRF-NOAH LSM). The third and fourth techniques are based on rigorous calibration and validation and need proper optimisation for the final outputs backboned by strong non-linear statistical analysis. The performances of all the techniques are validated against the probability distributed model based soil moisture deficit as benchmark; estimated using the ground based observed datasets. The observed high Nash Sutcliffe Efficiencies between the fused datasets with Probability Distribution Model clearly demonstrate an improved performance from the individual products. However, the overall analysis indicates a higher capability of ANN and KF for data fusion than the LWA or MLR approach. These techniques serve as one of the first demonstrations that there is hydrological relevant information in the coarse resolution SMOS satellite and WRF-NOAH LSM data, which could be used for hydrological applications.

Description: The conjunctive use of surface and subsurface water is one of the most effective ways to increase water supply reliability with minimal cost and environmental impact. This study presents a novel stepwise optimization model for optimizing the conjunctive use of surface and subsurface water resource management. At each time step, the proposed model decomposes the nonlinear conjunctive use problem into a linear surface water allocation sub-problem and a nonlinear groundwater simulation sub-problem. Instead of using a nonlinear algorithm to solve the entire problem, this decomposition approach integrates a linear algorithm with greater computational efficiency. Specifically, this study proposes a hybrid approach consisting of Genetic Algorithm (GA), Artificial Neural Network (ANN), and Linear Programming (LP) to solve the decomposed two-level problem. The top level uses GA to determine the optimal pumping rates and link the lower level sub-problem, while LP determines the optimal surface water allocation, and ANN performs the groundwater simulation. Because the optimization computation requires many groundwater simulations, the ANN instead of traditional numerical simulation greatly reduces the computational burden. The high computing performance of both LP and ANN significantly increase the computational efficiency of entire model. This study examines four case studies to determine the supply efficiencies under different operation models. Unlike the high interaction between climate conditions and surface water resource, groundwater resources are more stable than the surface water resources for water supply. First, results indicate that adding an groundwater system whose supply productivity is just 8.67 % of the entire water requirement with a surface water supply first (SWSF) policy can significantly decrease the shortage index (SI) from 2.93 to 1.54. Second, the proposed model provides a more efficient conjunctive use policy than the SWSF policy, achieving further decrease from 1.54 to 1.13 or 0.79, depending on the groundwater rule curves. Finally, because of the usage of the hybrid framework, GA, LP, and ANN, the computational efficiency of proposed model is higher than other models with a purebred architecture or traditional groundwater numerical simulations. Therefore, the proposed model can be used to solve complicated large field problems. The proposed model is a valuable tool for conjunctive use operation planning.

Description: Generally, wavelets are purposefully crafted to have specific properties that make them useful for signal processing. In recent years, wavelet analysis have commonly been used instead of Fourier analysis. This is a new approach for evaluation of water quality parameters. This study determined water quality parameters and effects on water quality in Gölcük, Turkey. A 13-month data series was compared with results from laboratory analysis by using wavelet model techniques. The study investigated eight surface water sources, located in rural areas (five different villages) in the vicinity of Gölcük. Water samples were obtained during spring and analyzed for contaminants. The samples were analyzed for Cl - (chlorine), NO 3 -N (nitrate) and pH values. Wavelet analysis of extreme events showed the role of seasonal oscillations, and small-, meso- and large-scale effects on some water quality parameters. In addition, the Cl - , NO 3 -N and pH contents were determined for their suitability for irrigation, drinking and other domestic uses.

Description: This study aims to improve the accuracy of groundwater pollution source identification using concentration measurements from a heuristically designed optimal monitoring network. The designed network is constrained by the maximum number of permissible monitoring locations. The designed monitoring network improves the results of source identification by choosing monitoring locations that reduces the possibility of missing a pollution source, at the same time decreasing the degree of non uniqueness in the set of possible aquifer responses to subjected geo-chemical stresses. The proposed methodology combines the capability of Genetic Programming (GP), and linked simulation-optimization for recreating the flux history of the unknown conservative pollutant sources with limited number of spatiotemporal pollution concentration measurements. The GP models are trained using large number of simulated realizations of the pollutant plumes for varying input flux scenarios. A selected subset of GP models are used to compute the impact factor and frequency factor of pollutant source fluxes, at candidate monitoring locations, which in turn is used to find the best monitoring locations. The potential application of the developed methodology is demonstrated by evaluating its performance for an illustrative study area. These performance evaluation results show the efficiency in source identification when concentration measurements from the designed monitoring network are utilized.

Description: To implement the maintenance and management of the sea dike engineering, the qualitative factors and quantitative factors need to be combined to evaluate the sea dike safety. Firstly, the evaluation index system and evaluation grading criterions of sea dike safety are established. Secondly, a new weight structure of evaluation indexes is proposed to combine the subjective weight and objective weight. Fuzzy Analytic Hierarchy Process method is used to determine the subjective weight and implement the qualitative analysis for sea dike safety. Projection Pursuit algorithm is introduced to calculate the objective weight and implement the quantitative analysis for sea dike safety. Based on the minimum relative information entropy principle, above two weights are combined. Thirdly, an evaluation model of sea dike safety is built with the improved Set Pair Analysis method. Finally, the proposed analysis method is used to assess one sea dike safety in China. It is shown that the combined weight can describe both the subjective information of expert experience and objective variation information of samples values, the uncertainty of information can be handled by the improved Set Pair Analysis method. The evaluation model has the clear physical concepts and intuitive modeling process. The calculation result is reasonable. The proposed method can be applied to sea dike safety evaluation and other complex systems evaluation as well.

Description: The water sharing dispute in a multi-reservoir river basin forces the water resources planners to have an integrated operation of multi-reservoir system rather than considering them as a single reservoir system. Thus, optimizing the operations of a multi-reservoir system for an integrated operation is gaining importance, especially in India. Recently, evolutionary algorithms have been successfully applied for optimizing the multi-reservoir system operations. The evolutionary optimization algorithms start its search from a randomly generated initial population to attain the global optimal solution. However, simple evolutionary algorithms are slower in convergence and also results in sub-optimal solutions for complex problems with hardbound variables. Hence, in the present study, chaotic technique is introduced to generate the initial population and also in other search steps to enhance the performance of the evolutionary algorithms and applied for the optimization of a multi-reservoir system. The results are compared with that of a simple GA and DE algorithm. From the study, it is found that the chaotic algorithm with the general optimizer has produced the global optimal solution (optimal hydropower production in the present case) within lesser generations. This shows that coupling the chaotic algorithm with evolutionary algorithm will enrich the search technique by having better initial population and also converges quickly. Further, the performances of the developed policies are evaluated for longer run using a simulation model to assess the irrigation deficits. The simulation results show that the model satisfactorily meets the irrigation demand in most of the time periods and the deficit is very less.

Description: Conventionally droughts are studied in terms of their dimensions (severity, duration and areal extent), without specifying the affected system. The paper presents an innovative system-based approach for drought analysis, which can lead to rational decisions for combating drought. Concepts of water scarcity (drought, water shortage, aridity and desertification) are viewed within the perspective of this new approach. The paper focuses also on operational water management in the presence of drought. Starting from the needs for such management, the affected system is defined and the related quantities are identified. Also, sub-systems are considered which allow the establishment of the link between specific variables and drought. Some drought characterisation methods are particularly suited for the systemic approach. Finally drought is considered as a natural hazard phenomenon and its consequences are discussed. Each physical sub-system can be improved by a variety of measures aiming at decreasing its vulnerability towards drought, so that the drought risk is mitigated. It is concluded that the clear definition of the affected system on the spatial and temporal scales can significantly contribute to the rational management for combating drought.

Description: This study addressed potential areas for flood spreading by evaluating the Boolean Logic, Overlay Index and Fuzzy Clustering techniques for spatial analysis. We applied these techniques on the artificial recharge criteria of slope, infiltration rate, alluvium thickness, land use and alluvial quality. The above criteria were prepared, classified, weighted and integrated in a GIS environment. The resultant maps were organized into two classes of potentiality, suitable and unsuitable, which expressed two different levels of favorability for site selection of flood spreading in the study area. We used 32 controlling areas to compare the performance of these spatial analysis techniques. By validation of the produced maps, the most suitable areas of flood spreading for each technique were determined: Fuzzy Clustering (14.4 %) Overlay Index (10.84 %) and Boolean Logic (10 %). After land use filtering, 72 %, 70 % and 65 % of the most suitable areas were eliminated in the, Overlay Index, Boolean model and Fuzzy Clustering, respectively. According to our results, the spatial analysis techniques can be powerful tools for selecting the most suitable areas for flood spreading.

Description: This paper describes an application of linear programming (LP) methods for optimal allocation of water among competing stakeholders that would achieve the highest economic return from water use in the agricultural section of the Sefidrud Basin, northern Iran. In a network presentation of the basin, the nodes stand for the supply and demand points and arcs represent reaches. The constraints of the LP model are the network structure of the basin (flows, stream geography and channel capacity), the available surface and ground water in each node, the environmental demand in different reaches, upper and lower bands of supply in each node and water balances. Optimal policies are derived for current and future demand. The optimal policies indicate that, at present, the basin water resources satisfy the demands of all stakeholders. Although, the results show that there is no conflict for supplying stakeholders’ current demands, they indicate that the current proportion of surface water used is not optimal compared with the proportion of ground water used. The results also indicate that some future demands of provinces with lower marginal value of water are unsatisfied and that this could cause conflict between stakeholders. Since in some nodes the optimal solutions suggest using surface water even where they have available ground water, they are categorized as having a higher possibility to construct dams in the basin.

Description: Routing is a technique used to simulate and predict changes in water flow along a river or channel. There are several hydraulic flow routing methods that model channel flow with high accuracy using lots of data related to channel geometry and specifications, thus making calculations very expensive. In contrast, hydrologic methods are techniques that simplify the calculation of flow conditions in a channel reach. In this paper, a stage hydrograph is modeled in simple and compound channels by genetic programming (GP) as a hydrologic method that does not depend on channel geometry and specifications, channel shape, and modeling time step. Routed hydrographs for simple and compound channels are then compared with a river analysis system model (HEC-RAS) and a coupled characteristic-dissipative-Galerkin procedure in one-dimension (CCDG-1D) as the hydraulic methods, respectively. Results show that the sum of squared differences ( SSD ) between a stage hydrograph by GP and modeled hydrographs by HEC-RAS and CCDG-1D methods, respectively, are not considerable in simple and compound channels. Moreover, GP is a capable tool to route an acceptable stage hydrograph even by using less geometry specification and time intervals in the detected stage. Those results indicate that the proposed GP method is effective in routing a stage hydrograph.

Description: Remote sensing methods are becoming attractive to estimate crop evapotranspiration, as they cover large areas and can provide accurate and reliable estimations; intensive field monitoring is also not required, although some ground-truth measurements can be helpful in interpreting satellite images. For the purposes of this paper, modeling and remote sensing techniques were integrated for estimating actual evapotranspiration of groundnuts ( Arachishypogaea , L.) that is cultivated near Mandria Village in Paphos District of Cyprus. The Surface Energy Balance Algorithm for Land (SEBAL) was adopted for the first time in Cyprus, employing the essential adaptations for local soil and meteorological conditions. Landsat-5 TM and 7 ETM+ images were used to retrieve the needed spectral data. The SEBAL model is enhanced with empirical equations determined as part of the present study, regarding crop canopy factors, in order to increase its accuracy. Maps of ET a were created using the SEBAL modified model (CYSEBAL) for the area of interest. The results have been compared to the measurements from an evaporation pan (which was used as a reference) and those of the original SEBAL model. The statistical comparison has shown that the modified SEBAL yields results that are comparable to those of the evaporation pan. T -test application has revealed that the statistical difference between SEBAL and CYSEBAL is significant and quite crucial, especially in a place with limited surface and underground water resources.

Description: Understanding the uncertainty of climate models in space and time is necessary to help water resources managers and hydrologists in the selection of appropriate model for a specific application. In this paper, we use three separate methods to evaluate and compare the utility of 14 climate models for seven basins with area range of 2,656–26,355 km 2 on the South Korean Peninsula. On the one hand, the method of probabilistic uncertainty analysis is used to evaluate the capability of the studied General Circulation Models (GCMs) in recognizing the extreme events. On the other hand, we use two statistical tests (correlation coefficient and root mean square error) to examine the capability of the GCMs in simulating quantitatively each event. The results show that, for the first method, the performance of climate model varies depending on the number of climate model nodes used for a specific application of given basin, especially for monthly time scale. In addition, we find that, there are several GCMs showing good results for the probabilistic uncertainty test but poor results for the statistical test and conversely. Therefore, climate models should be evaluated for specific applications and specific regions. The results indicated quite clearly that, it is not easy to select an optimal climate model which can satisfy both applications using precipitation and temperature projections. However, the results of this study suggest that, there are several GCMs which are more useful than the others for general hydrological application in South Korean peninsula.

Description: The development and use of water resources in the Amu Darya Basin remain under debate in the face of increasing population and associated scarcities in water, food, and energy. The upstream riparian, the mountain nation of Tajikistan, wishes to develop its hydropower potential. Three downstream states wish to sustain or increase their economic benefits from water used for irrigation. Growing tensions among the riparian countries on the Vakhsh River, a tributary of Amu Darya, have halted development of Tajikistan’s proposed Rogun Dam. This paper examines the potential for mutually beneficial water development and allocation of water resources to sustain demands for water, food, and energy. Using long-term data on the Basin’s energy potential, water supplies, irrigated land, and crop water demands, this paper analyzes total economic welfare for a future 20-year time horizon. Two water supply scenarios for each of two policy choices are examined. Results show that a constrained economic optimization operation of the Dam has the potential to increase farm income for each riparian country, while producing considerable benefits in hydropower for Tajikistan. Political negotiation among the riparian states and much better data will be needed to discover and implement potential gains indicated by this study.

Description: The problem of the ageing infrastructure of urban water distribution networks and the loss of water associated with this has been one of the greatest infrastructure problems in urban areas. When a leakage is detected in the water supply network, problems arise when seeking to rehabilitate the network. Therefore, the decision problem is to choose which components to add or to improve and to maximize the benefits, which will result from the changes implemented. In addition, it is important to minimize costs, since water supply companies have limited budgets. Moreover, there are often several leakage points in the same water supply network and in the same period of analysis. Therefore, this paper puts forward a model for rehabilitating the greatest number of leakage points in a water network; it respects the constraints which a water company may have. Promethee V is used to assist the decision maker (DM) in selecting a set of feasible alternatives for rehabilitating the network from the criteria and the constraints set by the DM on the problem. For demonstration purposes, the proposed model was tested in a simulated network.

Description: Analyzing hydraulic risk involves simulating a high number of scenarios from which to draw statistical information about flood extent and depth in relation to variations in the defence conditions and the entity of the event. With the aim of keeping the computational times of simulations within reasonable values while maintaining a sufficient reliability of the results, rapid models enabling flooded areas to be delimited using a DEM have been introduced into the scientific literature. These models, called Rapid Flood Spreading Models (RFSMs), are based on highly simplifying hypotheses that are analyzed and discussed in this paper thus arriving to a new formulation. A comparison of the results produced by this new formulation versus those of other RFSMs in a test case largely characterized by flat land shows it to be superior and reliable, while maintaining the computational times to within a few seconds. The new formulation thus lends itself to being used to support hydraulic risk assessment and management procedures requiring a reliable simulation of numerous flood scenarios.

Description: The objective of this paper is to present an optimal model to address the water resources utilization of the Tao River basin in China. The Tao River water diversion project has been proposed to alleviate the problem of water shortages in Gansu Province in China. A multi reservoir system is under consideration with multiple objectives including water diversion, ecological water demand, irrigation, hydropower generation, industrial requirements, and domestic uses in the Tao River basin. A multi-objective model for the minimization of water shortages and the maximization of hydro-power production is proposed to manage the utilization of Tao River water resources. An adjustable PSO-GA (particle swarm optimization – genetic algorithm) hybrid algorithm is proposed that combines the strengths of PSO and GA to balance natural selection and good knowledge sharing to enable a robust and efficient search of the solution space. Two driving parameters are used in the adjustable hybrid model to optimize the performance of the PSO-GA hybrid algorithm by assigning a preference to either PSO or GA. The results show that the proposed hybrid algorithm can simultaneously obtain a promising solution and speed up the convergence.

Description: Rainfall is one of the most significant parameters in a hydrological model. Several models have been developed to analyze and predict the rainfall forecast. In recent years, wavelet techniques have been widely applied to various water resources research because of their time-frequency representation. In this paper an attempt has been made to find an alternative method for rainfall prediction by combining the wavelet technique with Artificial Neural Network (ANN). The wavelet and ANN models have been applied to monthly rainfall data of Darjeeling rain gauge station. The calibration and validation performance of the models is evaluated with appropriate statistical methods. The results of monthly rainfall series modeling indicate that the performances of wavelet neural network models are more effective than the ANN models.

Description: The traditional rainfall-runoff modelling based on the Design Event Approach has some serious limitations as this ignores the probabilistic nature of the key flood producing variables in the modelling except for rainfall depth. A more holistic approach of design flood estimation such as the Joint Probability Approach/Monte Carlo simulation can overcome some of the limitations associated with the Design Event Approach. The Monte Carlo simulation technique is based on the principle that flood producing variables are random variables instead of fixed values. This allows accounting for the inherent variability in the flood producing variables in the rainfall-runoff modelling. This paper applies the Monte Carlo simulation technique and hydrologic model URBS to a large catchment with multiple pluviograph and stream gauging stations. It has been found that it is quite feasible to apply the Monte Carlo simulation technique to large catchments. The Monte Carlo simulation technique has much greater flexibility than the Design Event approach and can provide more realistic design flood estimates with multiple scenarios, which is likely to replace the Design Event Approach. The method developed here can be applied to other catchments in Australia and other countries.

Description: In practice, the annual series of streamflow peaks is generally preferred than the partial series for flood frequency analysis. Flood selection criteria for the partial series tend to be arbitrary and are limited in making allowances for catchment scale. This aspect appears to be a constraint to greater acceptance of the partial series approach. The aim of this paper is to define a scalable selection criterion that reduces ambiguity in flood selection by defining floods that exceed the daily average. An approach based on the volume delivery time (VDT), analogous to the tip interval time in tipping bucket raingauges, is described and tested for three rural catchments of various sizes in South East Queensland, Australia. The VDT approach produced discharge quantile estimates similar to the partial series based on the commonly-used monthly maxima except for minor, high frequency discharges at the small, more perennial catchment. A simplified approach based on average daily volume gave similar results to the VDT method.

Description: Presented herein is a methodology for the seismic assessment of the reliability of urban water distribution networks (UWDN) based on general seismic assessment standards, as per the American Lifelines Alliance (ALA) guidelines, and localized historical records of critical risk-of-failure metrics pertaining to the specific UWDN under assessment. The proposed methodology is applicable to UWDN under both normal or abnormal operating conditions (such as intermittent water supply), and the assessment of reliability incorporates data of past non-seismic damage, the vulnerabilities of the network components against seismic loading, and the topology of a UWDN. Historical data obtained using records of pipe burst incidents are processed to produce clustered ‘survival curves’, depicting the pipes’ estimated survival rate over time. The survival curves are then used to localize the generalized fragility values of the network components (primarily pipes), as assessed using the approach suggested by the ALA guidelines. The network reliability is subsequently assessed using Graph Theory (Djikstra’s shortest path algorithm), while the system reliability is calculated using Monte Carlo simulation. The methodology proposed is demonstrated on a simple small-scale network and on a real-scale district metered area (DMA). The proposed approach allows the estimation of the probability that a network fails to provide the desired level of service and allows for the prioritization of retrofit interventions and of capacity-upgrade actions pertaining to existing water pipe networks.

Description: The spatial-temporal variability of groundwater in an inland basin is very sensitive to human activity. This study focused on groundwater changes in the Alagan area within the Tarim Basin, China, with the aim of analyzing the effects of land-use change and artificial recharge on the response characteristics of groundwater. The distributed hydrological model MIKE SHE was introduced for modeling the influence of land use and artificial recharge on groundwater. Based on the runoff variation of this area, we selected three periods to simulate and analyze the response of groundwater. The results of land-use change indicated that there were significant changes from 1980 to 2000. The changed region accounted for 11.93 % of the total area, and the low coverage grasslands showed the greatest reduction. The simulation of hydrological processes before artificial recharge showed that the groundwater depths differed greatly with land-use types. Response analysis of groundwater to artificial recharge showed that the regions in which groundwater decreased were mainly distributed in grassland and bare land. Moreover, spatial autocorrelation coefficients indicated positive spatial autocorrelation of groundwater depths, but these began to reverse in 2010. Overall, land use and artificial recharge have a great influence on the time and spatial distribution of groundwater. Artificial recharge has played a positive role in improving groundwater conditions, but did not change the decreasing trend in time and space. The adaptation of environment to the decrease of groundwater presents as degradation. Groundwater conditions could be improved to some extent by the artificial recharge, but its change seems to be an irreversible process. Overall, this response study provides insight into estimations for exploration of water resources in arid areas.

Description: To analyze water distribution networks under pressure-deficient conditions, most of the available hydraulic simulators, including EPANET 2, must be either modified by embedding pressure-dependent demands in the governing network equations or run repeatedly with successive adjustments made to specific parameters until a sufficient hydraulic consistency is obtained. This paper presents and discusses a simple technique that implements the square root relationship between the nodal demand and the nodal pressure using EPANET 2 tools and allows a water distribution network with pressure-dependent demands to be solved in a single run of the unmodified snapshot hydraulic analysis engine of EPANET 2. In this technique, artificial strings made up of a flow control valve, a pipe with a check valve, and a reservoir are connected to the demand nodes before running the engine, and the pressure-dependent demands are determined as the flows in the strings. The resistance of the artificial pipes is chosen such that the demands are satisfied in full at a desired nodal pressure. The proposed technique shows reasonable convergence as evidenced by its testing on example networks.

Description: The applicability of fuzzy genetic (FG) approach in modeling reference evapotranspiration (ET 0 ) is investigated in this study. Daily solar radiation, air temperature, relative humidity and wind speed data of two stations, Isparta and Antalya, in Mediterranean region of Turkey, are used as inputs to the FG models to estimate ET 0 obtained using the FAO-56 Penman–Monteith equation. The FG estimates are compared with those of the artificial neural networks (ANN). Root mean-squared error, mean absolute error and determination coefficient statistics were used as comparison criteria for the evaluation of the models’ accuracies. It was found that the FG models generally performed better than the ANN models in modeling ET 0 of Mediterranean region of Turkey.

Description: Water scarcity is a societal problem in arid and semi-arid regions in the Fertile Crescent (FC). In FC countries, water shortages threaten economic growth, social cohesion, environmental sustainability and political stability. Under drought conditions, water shortages can be mitigated by using water more efficiently and by appropriate allocation of scarce water resources. In this paper water reallocation is addressed by reallocating some agricultural water use for other higher-value uses such as municipal and industrial sectors. Reallocating water from irrigation to other uses can provide sufficient and sustainable water supplies to meet the growing domestic and industrial demands for the next two decades. Most of the literature on water reallocation suggests that shifting water use from agriculture to other sectors would be feasible, but few studies address how much water should be reallocated.. The conceptual model will suppose that there are two users (A and B) and that their economic efficiency can be achieved when MB A  = MB B, ceteris paribus . A reallocation of water away from agriculture at 1 % of average total water use per year for the next 20 years for a total reallocation of 20 % by year 20. would increase GDP, could help alleviate the water-scarcity problem in the FC and lead to more efficient use of water. Further work or modeling is less important than is action based on available analyses. All evidence suggests decision-makers would be on solid ground to began re-allocating water in the FC now.

Description: Soil moisture is an uncertain variable due to rainfall randomness. Furthermore, its density function is hybrid in nature, with spikes at maximum and minimum soil moisture (saturation and field capacity). Both of these properties are also considered for crop water stress index. The crop water stress index can be used to show the sensitivity of a crop to deficit irrigation. In this paper, a new methodology is proposed to probability analysis of water stress index using Double Bounded Density Function (DB-CDF) and moment analysis of crop water stress index. For this purpose, two equations were developed for the first and second moments of water stress index. To find out the value of the proposed moment equations, they are used as constraints in a stochastic model of crop water allocation as developed previously by Ganji and Shekarrizfard (Water Resour Manage 25:547–561, 2010 ). After verification of the model, the DB-CDF of soil moisture stress index was estimated using the value of proposed moments in the growing periods. The results show that in case of deficit irrigation, the probability of crop water stress occurrence is high and as a consequence, any unpredictable water shortage leads to yield reduction. The application of the proposed methodology is novel and has not been reported in the literature to date.

Description: To avoid the water quality deterioration that are caused by artificial recharge (AR) of groundwater, potable drinking water has been used as one of the source water for AR to control the side effects caused by the over-exploitation of groundwater. Chemical clogging problems can still be caused by certain chemical components, especially Fe and Al, and a lower concentration of these elements can cause a notable decrease in hydraulic conductivity at the top layer of the infiltration medium. Some components in AR source water can be obstructed by the clogging layer, leading to a change in water quality. The accumulation of total suspended solids (TSS) at the clogging layer can cause physical clogging and worsen the degree of chemical clogging. Although clogging and the related change in water quality were the dominant issues that affect the infiltration rate and health risks during the AR process, the dissolution of the aquifer matrix should also be taken into account. This dissolution contributed to not only the hydraulic conductivity of the infiltration medium but also the potential change in water quality during the aquifer recharge, storage and recovery processes.

Description: With global climate change, the extreme flood disasters which are characterized with low frequency but huge economic losses occur more frequently. The management of the extreme flood disasters mainly depends on the administrative means of the governments at all levels in China. When the extreme flood occurs, the government financial aid and the social donation can be used to compensate the catastrophe losses, but these compensations account for only a small part of the catastrophe losses. Therefore, it is very urgent to disperse the flood catastrophe risk by social system. The catastrophe risk securitization bridges the capital market and the insurance market and can effectively transfer the catastrophe risk to the capital market. The catastrophe bond is an effective risk dispersion mode and the pricing of catastrophe bonds is the core issue of implementing catastrophe bonds. However, the research about the design and the pricing of extreme flood catastrophe bond is scarce. In this study, a kind of one-year extreme flood catastrophe bond was designed and simulations on the pricing according to the extreme flood data in China during 1961 to 2009 with quantitative analysis method were done, combined with the non-life insurance actuarial method and Wang-double-factor model. The results show that price of catastrophe bond is increasing with the increase of the value for triggering points and reducing when the ratio that corporation confiscates the capital and the interest of catastrophe bond enlarges. Some reasons were discussed to account for the results. The results show that the method is effective and can provide some guidance for the pricing of extreme flood catastrophe bonds.

Description: This paper presents the state of the art of flood risk management in Flanders, a low-lying region in the northern part of Belgium which is vulnerable to flooding. Possible flood hazard sources are not only the many rivers which pass through the Flemish inland, but also the North Sea, which is sensitive to the predicted sea level rise and which can affect large parts of the Flemish coastal area. Due to the expected increase in flood risks in the 21st century, the Flemish government has changed its flood management strategy from a flood control approach to a risk-based approach. Instead of focusing on protection against a certain water level, the objective now is to assure protection against the consequences of a flood, while considering its probability. In the first part, attention is given to the reasoning and functioning of the risk-based approach. Recent improvements to the approach are discussed, as well as the GIS-implementation of the entire model. The functioning of the approach is subsequently demonstrated in two case studies. The second part of the paper discusses future challenges for the flood risk management in Flanders. The driving force behind these challenges is the European Directive on the assessment and management of flood risks, which entered into force in 2007. The Flemish implementation of the directive is discussed and situated in the European landscape. Finally, attention is given to the communication of flood risks to the general public, since the “availability” of flood risk management plans is among the requirements of the EU Floods Directive.

Description: Complexicity in reservoir operation poses serious challenges to water resources planners and managers. These challenges of water reservoir operation are illustrated using a simulation to aid the development of an optimal operation policy for dam and reservoir. To achieve this, a Comprehensive Stochastic Dynamic Programming with Artificial Neural Network (SDP-ANN) model were developed and tested at Sg. Langat Reservoir in Malaysia. The nonlinearity of the natural physical processes was a major problem in determining the simulation of the reservoir parameters (elevation, surface-area, storage). To overcome water shortages resulting from uncertainty, the SDP-ANN model was used to evaluate the input variable and the performance outcome of the Model were compared with the Stochastic Dynamic Programming integrated with auto-regression (SDP-AR) model. The objective function of the models was set to minimize the sum of squared deviation from the desired targeted supply. Comparison result on the performance between SDP-AR model policy with SDP-ANN model found that the SDP-ANN model is a reliable and resilience model with a lesser supply deficit. The study concludes that the SDP-ANN model performs better than the SDP-AR model in deriving an optimal operating policy for the reservoir.

Description: Watershed prioritization based on the natural resources and physical processes involves locating critical areas of erosion, which produce maximum sediment yield to take up conservation activities on priority basis. The present study was taken up with a specific objective of prioritization of micro-watersheds using Multi-Criteria Decision Approach – Analytic Hierarchy Process (AHP) based SYI model (AHPSYI) under GIS environment for a case study area of Mayurakshi watershed in India. This method basically uses information of Potential Erosion Index (PEI) and Sediment Delivery Ratio (SDR), indicative of transport capacity. In the present study, sediment delivery factors viz., topography, vegetation cover, proximity to water courses and soil were translated into GIS layers and integrated using Boolean conditions to create a data layer of spatially distributed SDIs’ across the watershed. For assessment of PEI, important watershed parameters viz., land use/land cover, soil, slope, and drainage density maps were integrated in the GIS environment using Weighted Linear Combination method (WLC) by assigning weights to themes and ranks to features of individual theme using AHP technique. A comparison between AHPSYI based sub watershed prioritization map with that of prioritization map based on the observed sediment yield data revealed that about 78 % of the area showed concurrence. Thus, it can be inferred that the watershed prioritization based on only thematic layers can be dependable to maximum extent. Subsequently, proposed approach was adopted for prioritization of the study area at micro watershed scale, where area under high and very high categories together constitutes around 33 % of the study area. Around 100 micro-watersheds out of 276 watersheds are under moderate to very high category respectively, signifying the need for watershed management.

Description: Reservoir planning and management are critical to the development of the hydrological field and necessary to Integrated Water Resources Management. The growth of forecasting models has resulted in an excellent model known as the Support Vector Machine (SVM). This model uses linearly separable patterns based on an optimal hyperplane, which are extended to non-linearly separable patterns by transforming the raw data to map into a new space. SVM can find a global optimal solution equipped with Kernel functions. These Kernel functions have high flexibility in the forecasting computation, enabling data to be mapped at a higher and infinite-dimensional space in an implicit manner. This paper presents a new solution to the expert system, using SVM to forecast the daily dam water level of the Klang gate. Four categories are identified to determine the best model: the input scenario, the type of SVM regression, the number of V-fold cross-validation and the time lag. The best input scenario employs both the rainfall R(t-i) and the dam water level L(t-i). Type 2 SVM regression is selected as the best regression type, and 5-fold cross-validation produces the most accurate results. The results are compared with those obtained using ANFIS: all the RMSE, MAE and MAPE values prove that SVM is a superior model to ANFIS. Finally, all the results are combined to determine the best time lag, resulting in R(t-2) L(t-2) for the best model with only 1.64 % error.

Description: Climate change is likely to have a profound effect on many agricultural variables, although the extent of its influence will vary over the course of the annual farm management cycle. Consequently, the effect of different and interconnected physical, technical and economic factors must be modeled in order to estimate the effects of climate change on agricultural productivity. Such modeling commonly makes use of indicators that summarize the among environmental factors that are considered when farmers plan their activities. This study uses net evapotranspiration (ET N ), estimated using EPIC, as a proxy index for the physical factors considered by farmers when managing irrigation. Recent trends suggest that the probability distribution function of ET N may continue to change in the near future due to changes in the irrigation needs of crops. Also, water availability may continue to vary due to changes in the rainfall regime. The impacts of the uncertainties related to these changes on costs are evaluated using a Discrete Stochastic Programming model representing an irrigable Mediterranean area where limited water is supplied from a reservoir. In this context, adaptation to climate change can be best supported by improvements to the collective irrigation systems, rather than by measures aimed at individual farms such as those contained within the rural development policy.

Description: This paper develops a multi-objective optimization approach for incorporating the conditional probability of fire flow failure into the design of branched water networks. To this end, a new analytical probabilistic model was developed to quantify the conditional probability of fire flow failure in branched networks and incorporated into the non-dominated sorting genetic algorithm (NSGA-II). The optimization sought to minimize capital cost through pipe diameter and pump selection and to minimize the conditional probability of fire flow failure. The NSGA-II was applied to two branched networks to generate Pareto-optimal solutions. Results indicated a strategic allocation of pipe and pump capacity with limited fiscal resources and with a reduction in uncertainty of fire flow failure. Interestingly, optimization results for a real branched network supported the industry practice of using a minimum 150 mm distribution main sizing to provide fire flow protection.

Description: Water scarcity is a common problem in many countries, especially those located in arid zones. The vulnerability of water resources due to climate change is an imperative research focus in the field of water resources management. In this study, a System Dynamics (SD) model was developed to simulate the water supply-and-demand process in Bayingolin, a prefecture in China, and to evaluate water resources vulnerability currently as well as in the future. The model was calibrated and validated using historical data. Three alternative scenarios were designed by changing parameters to test the vulnerability of water resources: i) increase the Wastewater Treatment Rate by 50 %; ii) decrease the Irrigation Water Demand per Hectare by 20 %; iii) increase Total Water Supply by 5 %. Results show that the baseline vulnerability of study region is high. The agricultural irrigation is the largest water use, and the water demand structure will change in future. Decreasing the irrigation water demand is the most suitable intervention to relatively reduce the vulnerability. Results also demonstrated that SD is a suitable method to explore management options for a complex water supply and demand system.

Description: In this paper, a new solution concept, called Fuzzy Variable Least Core (FVLC), is developed for fuzzy cooperative games. The FVLC is able to incorporate fuzzy input variables and result in fuzzy benefit shares of players participating in a coalition. This solution concept is used for water and benefit allocation to water users in inter-basin water transfer systems considering the uncertainties associated with their benefit coefficients. In the proposed water allocation methodology, an Integrated Stochastic Dynamic Programming (ISDP) model is developed to obtain the water rights of players and economic water allocation policies. In the next step, the total net fuzzy benefit of the system is reallocated to water users in an equitable and rational way using a FVLC-based model. In this model, a new algorithm is proposed for converting a multilateral cooperative game with fuzzy variables to some fuzzy bilateral cooperative games, which are solved using the FLVC solution concept. The applicability and efficiency of the proposed methodology is examined by applying it to a large scale inter-basin water transfer project in Iran.

Description: Nowadays, the efficient management of water has become the focus of vast debate, both in the academic literature and in the practical and regulatory field. Due to the growing importance and scarcity of water resources, it has become crucial to better understand how to improve the organizational efficiency of water utilities. By adopting an accounting perspective and using statistical methods, this paper analyzes whether and to what extent investment and financial strategies differ among clusters of water utilities with different ownership structures. The paper focuses on the Italian water industry, a context considered particularly appropriate due to the coexistence of utilities with different ownership structures. The main results of the paper show that ownership affects the level of investment as well as the financial structure and costs of water utilities. The evidence provided by this study should encourage national governments and regulatory authorities to select water utilities with the greatest investment potential measured in terms of financial efficiency and effectiveness.

Description: Surface water and groundwater are the most important water sources in the natural environment. Land use and seasonal factors play an important role in influencing the quality of these water sources. An in-depth understanding of the role of these two influential factors can help to implement an effective catchment management strategy for the protection of these water sources. This paper discusses the outcomes of an extensive research study which investigated the role of land use and seasonal factors on surface water and groundwater pollution in a mixed land use coastal catchment. The study confirmed that the influence exerted on the water environment by seasonal factors is secondary to that of land use. Furthermore, the influence of land use and seasonal factors on surface water and groundwater quality varies with the pollutant species. This highlights the need to specifically take into consideration the targeted pollutants and the key influential factors for the effective protection of vulnerable receiving water environments.

Description: The evolution of water distribution systems to pressurized networks has improved water use efficiency, but also significantly increased energy consumption. However, sustainable irrigated agriculture must be characterized by the reasonable and efficient use of both water and energy. Irrigation sectoring where farmers are organized in turns is one of the most effective measures to reduce energy use in irrigation water distribution networks. Previous methodologies developed for branched irrigation networks with one single source node have resulted in considerable energy savings. However, these methodologies were not suitable for networks with several water supply points. In this work, we develop an optimization methodology (WEBSOM) aimed at minimizing energy consumption and based on operational sectoring for networks with several source nodes. Using the NSGA-II multi-objective genetic algorithm, the optimal sectoring operation calendar that minimizes both energy consumption and pressure deficit is obtained. This methodology is tested in the irrigation district of Palos de la Frontera (Huelva, Spain) with three pumping stations, showing that potential annual energy savings of between 20 % and 29 % can be achieved, thus ensuring full pressure requirements in nearly all hydrants, along with the total satisfaction of irrigation requirements.

Description: In the context of integrated water resources management (IWRM), account should be taken of a wide range of factors including economic, social and environmental issues. Multi-criterion decision making (MCDM) approaches are applied to the case study in this paper to integrate different objectives into the planning, management and decision making process. A variety of criteria in terms of economic, social and environmental dimensions are identified and formulated for the purpose of MCDM analysis. A set of different management scenarios is proposed for the desired goals. They include reductions in irrigated areas, improved irrigation efficiencies, increased system loss for groundwater irrigation and changes in cropping pattern. An integrated water resources optimisation model (IWRO) is used to optimise surface and groundwater allocation, through which the identified criteria can be enumerated. Compromise programming (CP), which results in a compromise solution located as close as possible to an ideal solution, is adopted to carry out the MCDM analysis for the case study. The sensitivity of different sets of weights and different values of parameters related to CP is investigated. Results indicate that compromise programming is able to lead to satisfactory solutions. Performance of different alternatives is evaluated based on the compromise programming analysis, and potential decisional alternatives are proposed for further investigation.

Description: DIVAST is a two-dimensional hydrodynamic and water quality numerical model developed for estuarine and coastal modelling. The original model enables the simulation of problems such as pollution and flooding in surface waters. In this paper the existing model is extended to allow the modelling of 2-D groundwater as well as surface water in the same model, using an integrated approach rather than two disparate models. The changes to the original model are summarised and the method of implementation is outlined. The new extended model (DIVAST-SG) is then tested against an analytical solution to verify that the model solves the equations correctly. The model is shown to predict the analytical solution for two different scenarios to within approximately 1 % of the height of flood wave.

Description: Regional frequency approaches are frequently proposed in order to estimate runoff quantiles for non-gauged catchments. Partitioning methods such as cluster analysis are often applied in order to regionalize catchments using topography, soil and hydroclimatological characteristics. This paper aims to construct a mean regional frequency curve for annual maximum runoffs, using topographic descriptors for cluster analysis. Both trellis and hierarchical classifications partitioning methods are performed using basin area; basin perimeter; characteristic length; global slope index; compaction index; specific gradient slope and geodesic coordinates as attributes. To build the distance measures, various multidimensional spaces are considered with pairs or triplets of attributes. Resulting clusters were checked for hydrological homogeneity using the test of Hosking and Wallis based on L-moments estimates. A sample of 40 Tunisian gauged basins covering a range of areas from 56 to 16483 km 2 has been considered to achieve these purposes. The classification and the test of Hosking and Wallis concluded for separating the gauged basins in two hydrological homogeneous regions. Also, the basin global slope index is found as the main discriminating classification factor. Further, regional quantiles of the standardized maximum annual flood (index flood) were estimated using GEV distribution. The two regional curves are distinguishable for extremes events, suggesting that the second region with high slope index displays more variability in the extremes. However, comparisons of RMSE results using two regions against one single pooled region suggest that estimation of standardized quantiles is more accurate in the case of one single region for non extreme events.

Description: The FAO56 Penman–Monteith (FAO56-PM) method is known as the standard method for estimating reference evapotranspiration (ET 0 ) in a variety of climate types. Global solar radiation (R s ) is one of the essential inputs of this model, which is usually estimated from the Angstrom–Prescott (AP) method. The major drawback of the FAO56 pre-defined AP coefficients application is that the AP coefficients might need local calibration, to estimate ET 0 accurately. The aim of this study is to compare the effect of the FAO56 pre-defined AP coefficients (i.e. a and b) and the locally calibrated ones, on estimating daily ET 0 in 15 sites over Iran. Using long-term (1980–2007) experimental global solar radiation data (R s ), new locally calibrated (a) and (b) coefficients are suggested and new ET 0 values are determined accordingly. It was found that the range of the calibrated AP coefficients (a, b) are climate dependent and locally different from those of recommended by the FAO56-PM method. Estimated ET 0 at daily scale, improved up to 72.7 % when the calibrated AP coefficients were applied instead of FAO56 pre-defined AP coefficients. Based on the results, applying the FAO56 pre-defined AP coefficients (i.e. a  = 0.25 and b  = 0.50) in northern subtropical-humid and southern hot climates caused larger ET 0 errors. By contrast, the least ET 0 errors were found in cool arid and cool semi-arid inland climates, locating about 1,330 above sea level. The correlations between the calibrated AP coefficients and geographical factors are also discussed in this research.

Description: The purpose of this work is to present analytical solution for linearized Boussinesq equation in triangular-shaped aquifers in response to transient recharge from an overlaying basin. Four different configurations of hydrogeological boundary conditions (constant-head and no-flow) are considered. At first, the solutions for the rectangular-shaped aquifers are obtained through the well known image well theory. Then, the concept of expanded domain is utilized to arrive at the solution for the intended triangular domain. The resulting point-recharge solution (Green’s function) facilitates treating any arbitrary shaped recharge basin subjected to spatiotemporal varying recharge. Few examples describing the nature of transient recharge in triangular-shaped aquifers are presented. The investigation of equipotential contour lines and velocity vector fields confirms the validity of the method adopted here. The computed mound profiles are in favourably well agreement with the numerical results obtained by finite element method. Stream flow rates due to recharging are also computed for a single case. Overall, the closed form solutions provide an effective tool in order to conduct sensitivity analysis on various hydrogeological parameters that affect the formation of groundwater mound in triangular-shaped aquifers.

Description: The aim of this paper is to develop rules for optimal reservoir operation and water withdrawal from river and aquifer considering water supply and pollution control targets. The general approach is making use of an integrated water quantity-quality management (IWQM) modeling in conjunction with accurate data mining techniques. The IWQM model generates data, including; optimal releases and water withdrawal from river and aquifer for different conditions, and M5P and Support Vector Regression (SVR) data mining models utilize the results of the IWQM model for the derivation of rules. The IWQM model minimizes the deviation from water supply and water quality targets during the planning horizon. This method for derivation of operating rules is applied to a real world case study, Zayandehrood system, in Iran, with serious water supply and water pollution problems. The IWQM model is analyzed for different hydrologic and water demands scenarios with total dissolved solids (TDS) as the water quality indicator. Results show that an integrated approach to reservoir-river-aquifer operation in the study area can reduce the TDS by 43 % in the downstream river.

Description: The present study is taken up to test the suitability of SWAT (Soil and Water Assessment Tool) model for estimation of runoff and to understand sensitiveness of model input parameters in a predominantly forested watershed in Kumaun region of Himalaya. The study area Dabka is a small watershed (69.41 km 2 ) lies in North West of Nainital in Uttarakhand. The SWAT is calibrated at an upstream intermediate gauging site Bagjhala draining approximately an area of 65.78 km 2 on monthly basis due to non-availability of observed data at main outlet. A local sensitivity analysis is performed on 13 input variables in terms of model outputs such as water yield, surface runoff and baseflow to gain in depth understanding of the role of different model parameters for their proper selection. The study concluded that model performed well with Root Mean Square Error (RMSE) value 0.242 for calibration and 0.81 for validation. Nash Sutcliffe Efficiency (NSE) for calibration and validation period is obtained as 0.77 and 0.73 respectively whereas Coefficient of determination (R 2 ) for calibration and validation period is 0.86 and 0.90 indicating good model performance. The most sensitive model parameters affecting water yield are CN2, GWQMN and SOL_Z. On the basis of sensitiveness of model parameters, the ranking of most sensitive parameters from highest sensitive to relatively lesser sensitiveness on stream flow are CN2, SOL_K and SOL_AWC whereas for base flow SOL_AWC, SOL_Z and GWQMN are found to be more sensitive followed by CN2, ESCO and SOL_K.

Description: Water Distribution Systems (WDSs) are indispensable infrastructures for urban societies. Due to vitality of continuous supply of drinking water in urban areas, it is necessary to have a performance evaluation and monitoring system to provide the expected level of security in water distribution systems. A main weakness point of these systems is the physical break of pipes which results in high level of water loss, pollution risk and public unsatisfactory. In this study, a framework is developed to increase physical water supply security in urban areas. For this purpose, a physical vulnerability index (PVI) is developed for evaluation of physical statues of water mains. In quantifying PVI, pipe characteristics and bedding soil specifications are considered. The importance of these factors on PVI is determined using Analytical Hierarchy Process (AHP). In system performance evaluation, the pipe role in system performance is incorporated regarding pipe location in WDS, distance of pipe from reservoir and average pressure of pipe. Then, System Physical Performance Index (SPVI) is evaluated. An optimization algorithm is employed to determine ways to improve the system performance through enhancing the physical condition of the pipe in the system at a minimum cost. The genetic algorithm is employed for solving the optimization model. A global sensitivity analysis method named FAST, is used for sensitivity analysis to incorporate the correlation between different parameters in analysis. The proposed framework is applied to a case study located in Tehran metropolitan area. The results of this study show the significant value of the proposed algorithm in supporting decision makers to better choose vulnerable pipes for rehabilitation practices in order to decrease system vulnerability against physical failures.

Description: The combination of wavelet analysis with black-box models presently is a prevalent approach to conduct hydrologic time series forecasting, but the results are impacted by wavelet decomposition of series, and uncertainty cannot be evaluated. In this paper, the method for discrete wavelet decomposition of series was developed, and an improved wavelet modeling framework, WMF for short, was proposed for hydrologic time series forecasting. It is to first separate different deterministic components and remove noise in original series by discrete wavelet decomposition; then, forecast the former and quantitatively describe noise’s random characters; at last, add them up and obtain the final forecasting result. Forecasting of deterministic components is to obtain deterministic forecasting results, and noise analysis is to estimate uncertainty. Results of four hydrologic cases indicate the better performance of the proposed WMF compared with those black-box models without series decomposition. Because of having reliable hydrologic basis, showing high effectiveness in accuracy, eligible rate and forecasting period, and being capable of uncertainty evaluation, the proposed WMF can improve the results of hydrologic time series forecasting.

Description: Water users along the Murray River, Australia, have traditionally used climatology forecasts of river flows for intra-annual planning of water use and trading. In this paper, we develop and assess the performance of statistical models for forecasting three-month inflow totals for the Murray River. Predictors are selected to represent the influence of initial catchment conditions and future climate on streamflows. These predictors vary with season and location, but are dominated by antecedent streamflows and indices describing the El Nino–Southern Oscillation. For all seasons, the forecasts are skilful with respect to climatology forecasts, and the forecast probability distributions appear to be reliable. Forecast skill is highest for forecasts made between September and December. The forecasts appear to be robust with respect to event size and time, except for the austral autumn seasons for which none of the predictors can forecast the decline in seasonal rainfall over the most recent decade.

Description: Prediction of longitudinal dispersion coefficient (LDC) is still a novel topic for both environmental and water sciences due to its practical importance. In this study, the appraisal of LDC is considered as a spatial modelling problem and the analyses are carried out by regression kriging. Since LDC prediction includes some geometrical (spatial) parameters, the analyses have been performed such that it takes spatial variability of data into account. The modelling procedure consists of two stages. In the first stage, spatial variables are analyzed via multi-linear regression technique and deterministic relationships are identified. In the second stage, based on the spatial auto-correlations of the residuals, the regression-based kriging procedure is applied. The capacity and accuracy level of the method has been compared with former models. As a consequence, the applications revealed that analyzing hydraulic and geometrical parameters with spatially correlated errors is a convenient approach for evaluating LDC in a hydrological system.

Description: In complex socio-ecological systems, such as managing natural resources, human frames and mental models play a central role in deriving the system’s behaviour. Differences in stakeholder views and perceptions may impede the design and implementation of collective policies. Understanding stakeholder views and mental models is a pre-requisite for understanding decision making, improving communication, and eventually developing management policies that cater to the diversity of values and interests. Motivated by this premise, this research uses a cognitive mapping approach to examine the frames used by a group of water users with regard to managing available water resources. We focus on the Australian Capital Territory as a case study. Two different frames have emerged from the results: hard and soft. Differences in frames embody various perceptions about the problem definition, its causes, effective management strategies, and hence, responsibility attribution. The paper describes both frames and highlights those perceptions that may stand as barriers against sustainable management. These findings can be transferred to other arid and semi-arid areas.

Description: The paper presents a survey of several optimization techniques, mainly artificial intelligences (AIs) which have been applied to the reservoir operation modelling whether its single or multi-reservoir system. The reservoir system modeling is essential for any nations and the optimal use of it is always asked. The main objective of this review article is to discuss the potentiality of the evolutionary algorithms (EAs) and the ability to integrate with other techniques which can provide the best results. Also the formulation of these types of application has described on the ground of a well known benchmark problem regarding this field. The traditional algorithms got some drawbacks. The study provides a complete understanding to the EA users about next generation optimal search procedure and help to overcome the drawbacks. Though the background of application number of swarm intelligences is less comparatively than the genetic algorithm (GA), it provides a great scope for the researcher for further development. Also comparative results with other popular methods (such as, linear programming, stochastic dynamic programming) are discussed on the basis of past research results. Conclusions and suggestive remarks are made for the help of researchers and the reservoir decision makers as well.

Description: Cyanobacteria also known as blue-green algae can be found in almost every conceivable environment. Cyanobacteria blooms occur frequently and globally in water bodies and they are a major concern in terms of their effects on other species such as plants, fish and other microorganisms, but especially by the possible acute and chronic effects on human health due to the potential danger from cyanobacterial toxins produced by some of them in recreational or drinking waters. Consequently, anticipation of cyanotoxins presence is a matter of importance to prevent risks. The aim of this study is to build a cyanotoxin diagnostic model by using support vector machines and multilayer perceptron networks from cyanobacterial concentrations determined experimentally in the Trasona reservoir (recreational reservoir used as a high performance training centre of canoeing in the Northern Spain). The results of the present study are two-fold. In the first place, the significance of each biological and physical-chemical variables on the cyanotoxins presence in the reservoir is presented through the model. Secondly, a predictive model able to forecast the possible presence of cyanotoxins is obtained. The agreement of the model with experimental data confirmed its good performance. Finally, conclusions of this innovative research work are exposed.

Description: Rainfall is one of the most complicated effective hydrologic processes in runoff prediction and water management. The adaptive neuro-fuzzy inference system (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different kinds of problems, especially efficient in rainfall prediction. This paper after reconsidering conventional ANFIS architecture brings up a modified ANFlS (MANFlS) structure developed with attention to making ANFIS technique more efficient regarding to Root Mean Square Error (RMSE), Correlation Coefficient ( R 2 ), Root Mean Absolute Error (RMAE), Signal to Noise Ratio (SNR) and computing epoch. The modified ANFIS (MANFIS) architecture is simpler than conventional ANFIS with nearly the same performance for modeling nonlinear systems. In this study, two scenarios were introduced; in the first scenario, monthly rainfall was used solely as an input in different time delays from the time (t) to the time (t-4) to conventional ANFIS, second scenario used the modified ANFIS to improve the rainfall forecasting efficiency. The result showed that the model based Modified ANFIS performed higher rainfall forecasting accuracy; low errors and lower computational complexity (total number of fitting parameters and convergence epochs) compared with the conventional ANFIS model.

Description: A study has been conducted to assess future climate change impacts on water resources of the Upper Sind River Basin using Soil Water Assessment Tool. Sequential uncertainty fitting (SUFI-2) algorithm has been applied for model calibration and uncertainty analysis. Monthly observed stream flows matched well with simulated flows with respect to p-factor, d-factor, Correlation coefficient and Nash-Sutcliffe coefficients with values of 0.73, 0.42, 0.82, 0.80 during calibration (1992–2000) and 0.42, 0.36, 0.96, 0.93 during validation (2001–2005) respectively. PRECIS generated outputs under IPCC A1B Scenarios for Indian conditions corresponding to the baseline (1961–1990), midcentury (2021–2050) and endcentury (2071–2098); extracted by Indian Institute of Tropical Meteorology, Pune (India) have been used for the study. It has been found from the model results that the average annual streamflow could increase by 16.4 % for the midcentury and a significant increase of 93.5 % by the endcentury. The results also indicate that streamflow may rise drastically in monsoon season, but will decrease in non-monsoon season due to the projected future climate change.

Description: Spatial Monte Carlo Analysis (SMCA) is a newly developed Multi-Criteria Decision Making (MCDM) technique based on Spatial Compromise Programming (SCP) and Monte Carlo Simulation (MCS) technique. In contrast to other conventional MCDM techniques, SMCA has the ability to address uneven spatial distribution of criteria values in the evaluation and ranking of alternatives under various uncertainties. Using this technique, a new flood management tool has been developed within the framework of widely used GIS software ArcGIS. This tool has a user friendly interface which allows construction of user defined criteria, running of SCP computations under uncertain impacting factors and visualization of results. This tool has also the ability to interact with and use of classified Remote Sensing (RS) image layers, and other GIS feature layers like census block boundaries for flood damage calculation and loss of life estimation. The 100-year flood management strategy for Oconee River near the City of Milledgeville, Georgia, USA is chosen as a case study to demonstrate the capabilities of the software. The test result indicates that this new SMCA tool provides a very versatile environment for spatial comparison of various flood mitigation alternatives by taking into account various uncertainties, which will greatly enhance the quality of the decision making process. This tool can also be easily modified and implemented for solving a large variety of problems related to natural resources planning and management.

Description: This note exhibits how the implementation of the Total Loads Standard for issuing tradable water rights along a river basin can cause a significant location-induced economic disadvantage to some of the agents located along a given river site. Analysis shows, however, that this issue can be resolved by a modification of the original Total Load Standard regarding the handling of so called critical zones in which the desired water quality level is otherwise not upheld.

Description: In this study, we conducted a choice experiment for estimating the marginal willingness to pay for the different attributes of the small-scale water reservoirs, known as Tameikes, which are prevalent throughout Japan’s inhabitable rural areas. By using Internet surveys, we collected unlabeled five-way choice data from 16,000 respondents residing in the 26 Tameike-abundant prefectures out of the total 47. In this study, we report on the random parameters logit estimates with interacting terms that indicate the differences in the valuation of Tameike attributes with respect to the differences in the respondents’ socio-demographiccharacteristics.

Description: Monthly mean reference evapotranspiration ( ET 0 ) is estimated using adaptive network based fuzzy inference system (ANFIS) and artificial neural network (ANN) models. Various combinations of long-term average monthly climatic data of wind speed, air temperature, relative humidity, and solar radiation, recorded at stations in Turkey, are used as inputs to the ANFIS and ANN models so as to calculate ET 0 given by the FAO-56 PM (Penman-Monteith) equation. First, a comparison is made among the estimates provided by the ANFIS and ANN models and those by the empirical methods of Hargreaves and Ritchie. Next, the empirical models are calibrated using the ET 0 values given by FAO-56 PM, and the estimates by the ANFIS and ANN techniques are compared with those of the calibrated models. Mean square error, mean absolute error, and determination coefficient statistics are used as comparison criteria for evaluation of performances of all the models considered. Based on these evaluations, it is found that the ANFIS and ANN schemes can be employed successfully in modeling the monthly mean ET 0 , because both approaches yield better estimates than the classical methods, and yet ANFIS being slightly more successful than ANN.

Description: Pervious pavements offer a solution for rainwater runoff treatment in urban areas, combining storm-water management with water reuse purposes when the sub-bases become rainwater reservoirs. Furthermore, the thermal behaviour research into these systems has demonstrated their contribution to palliating the urban heat island effect in the hottest season and to delaying freezing during the coldest season. Recent investigations related to pervious pavements and their sub-bases have enabled the use of these structures combined with Ground Source Heat Pumps (GSHP) in addition to the other well-known applications. The aim of this field study is to investigate the temperature response observations of the water stored in the sub-bases of different pervious pavements under specific conditions, in order to evaluate the possibility of introducing GSHP technology. The base and sub-base temperatures of different types of pervious pavements were monitored during one year and the results obtained show the differences in pervious pavements temperature compared to air temperature over the period of study; and demonstrate that the sub-base is less affected by the air temperature than the base, due to the insulating capacity of pervious pavements. On the other hand, water samples were taken from the different pervious pavement sub-bases in order to assess the water quality deterioration due to the temperatures reached in the sub-base, focused on investigating the presence of Legionella in this particular aquatic environment.

Description: Eighteen radiation-based equations used to estimate reference evapotranspiration (ET ref ) were generalized into seven linear models. The general models were calibrated using the standard FAO-56 Penman-Monteith method. Model performance was evaluated under humid, sub-humid and semi-arid mediterranean climatic conditions in central Greece. Evaluation and comparison of the models was based on quantitative assessment of their ability to accurately estimate ET ref values, generated by the FAO-56 Penman-Monteith equation. All models provided relatively accurate estimates of ET ref . The Abtew model showed the best overall performance with respect to the data from all available climate stations of central Greece. The average error of the Abtew model in the monthly average daily ET ref estimates was 0.24 mm, which corresponds to a relative error of 7.7 %. The Abtew method has not yet been tested under mediterranean climatic conditions. Based on our results, it seems to be a good choice for the estimation of monthly average daily ET ref under different conditions in the mediterranean climate. An exception appears to be the mediterranean climate with relatively high humidity and low wind speed. Under these conditions the models of the Priestley-Taylor group, the Makkink group and the Jensen-Haise group performed better than the Abtew equation.

Description: Climate change affects hydropower production by modifying total annual inflow volumes and their seasonal distribution. Moreover, increasing air temperatures impact electricity consumption and, as a consequence, electricity prices. All together, these phenomena may lead to a loss in revenue. We show that an adequate management of hydropower plants mitigates these losses. These results are obtained by resorting to an interdisciplinary approach integrating hydrology, economy and hydropower management in an interdependent quantitative model.

Description: The Standardized Precipitation Index (SPI) is a well-established drought index that is based on transforming the interannual distribution of precipitation to a standard normal distribution. Because of its robust statistical basis, SPI is readily applicable to different regions making comparisons between locations and time windows possible. Nevertheless, the usability of SPI results is undermined by shortcomings that are partly resultant from data and model uncertainties. One such shortcoming is the inability of the existing SPI model to include change in variability of interannual precipitation from non-stationary normal – mostly caused by climate change. In addition, epistemic uncertainty in the form of incompleteness in station-wide precipitation records results in heterogeneity and inconsistency in SPI results. The effects of such epistemic uncertainty on the accuracy of estimations of long-term changes in drought frequency are mostly unknown. Given such deficiency, SPI’s procedure and subsequent results remain deterministic and inadequately informative. Here, we introduce modifications to the traditional SPI using Dempster-Shafer theory (DST) to enable modeling and propagation of variability and epistemic uncertainty with the regular SPI procedure. By generalizing the SPI model from a deterministic setting to an “uncertainty-driven setting” provided by DST, this work makes possible: (a) efficiently propagating data uncertainty in interpolation of station-wide precipitation and SPI, and (b) modeling the effects of shift in precipitation normals (due to e.g., climate change) on drought frequency. In addition, the significance of this shift may then be evaluated with respect to the epistemic uncertainty by measuring how much of the surrounding epistemic uncertainty this shift encloses (i.e., “probability of enclosing”). The latter is especially important due to large unknowns already associated with climate change modeling. We implement the model on summer extreme drought for the Okanagan Basin, BC, Canada. For a single general circulation model and scenario (CGCM3 A2) a maximum 7 % increase in summer extreme drought (for 2080s, as per current definition) is estimated with a maximum probability of enclosing of 36 %.