ALBERT

Description: A Lagrangian advection scheme with shape matrix (LASM) for solving advection problems Geoscientific Model Development, 7, 2951-2968, 2014 Author(s): L. Dong, B. Wang, and L. Liu A new Lagrangian advection scheme with shape matrix (LASM) is proposed to take advantage of the extreme low numerical diffusion of the Lagrangian methods. The tracer is discretized into finite parcels, which move along the downstream trajectories. Different from other Lagrangian schemes, the parcel shape is simulated explicitly by a linear transformation matrix. By doing so, the aliasing error in the Lagrangian schemes is largely reduced without introducing substantial interparcel mixing in the pure advection stage, because the flow information will be respected when remapping tracer density onto the fixed model grids. An adaptive interparcel mixing algorithm is constructed to ensure the validity of the linear approximation of the parcel shape, where the mixing is only triggered when it is necessary and resembles the physical mixing. The total tracer mass on the parcels is conserved exactly. The new scheme is validated by using several test cases.

Description: Technical Note: Reducing the spin-up time of integrated surface water–groundwater models Hydrology and Earth System Sciences, 18, 5169-5179, 2014 Author(s): H. Ajami, J. P. Evans, M. F. McCabe, and S. Stisen One of the main challenges in the application of coupled or integrated hydrologic models is specifying a catchment's initial conditions in terms of soil moisture and depth-to-water table (DTWT) distributions. One approach to reducing uncertainty in model initialization is to run the model recursively using either a single year or multiple years of forcing data until the system equilibrates with respect to state and diagnostic variables. However, such "spin-up" approaches often require many years of simulations, making them computationally intensive. In this study, a new hybrid approach was developed to reduce the computational burden of the spin-up procedure by using a combination of model simulations and an empirical DTWT function. The methodology is examined across two distinct catchments located in a temperate region of Denmark and a semi-arid region of Australia. Our results illustrate that the hybrid approach reduced the spin-up period required for an integrated groundwater–surface water–land surface model (ParFlow.CLM) by up to 50%. To generalize results to different climate and catchment conditions, we outline a methodology that is applicable to other coupled or integrated modeling frameworks when initialization from an equilibrium state is required.

Description: Extending periodic eddy covariance latent heat fluxes through tree sapflow measurements to estimate long-term total evaporation in a peat swamp forest Hydrology and Earth System Sciences Discussions, 11, 13607-13661, 2014 Author(s): A. D. Clulow, C. S. Everson, M. G. Mengistu, J. S. Price, A. Nickless, and G. P. W. Jewitt A combination of measurement and modelling was used to find a pragmatic solution to estimate the annual total evaporation (ET) from the rare and indigenous Nkazana Peat Swamp Forest (PSF) on the east coast of Southern Africa to improve the water balance estimates within the area. Total evaporation was measured during three window periods (between seven and nine days each) using an eddy covariance (EC) system on a telescopic mast above the forest canopy. Sapflow of an understory and an emergent tree was measured using a low maintenance heat pulse velocity system for an entire hydrological year (October 2009 to September 2010). An empirical model was derived, describing the relationship between the observed ET of the Nkazana PSF measured during two of the window periods ( R 2 = 0.92 and 0.90) which, overlapped with sapflow measurements, thereby providing hourly estimates of predicted ET of the Nkazana PSF for a year, totalling 1125 mm (while rainfall was 650 mm). In building the empirical model, it was found that including the understory tree sapflow provided no benefit to the model performance. In addition, the observed emergent tree sapflow relationship with observed ET between the two field campaigns was consistent and could be represented by a single empirical model ( R 2 = 0.90; RMSE = 0.08 mm). During the window periods of EC measurement, no single meteorological variable was found to describe the Nkazana PSF ET satisfactorily. However, in terms of evaporation models, the hourly FAO56 Penman–Monteith equation best described the observed ET from EC during the August 2009 ( R 2 = 0.75), November 2009 ( R 2 = 0.85) and March 2010 ( R 2 = 0.76) field campaigns, compared to the Priestley–Taylor model ( R 2 = 0.54, 0.74 and 0.62 during the respective field campaigns). From the empirical model of ET and the FAO56 Penman–Monteith equation, a monthly crop factor ( K c ) was derived for the Nkazana PSF providing a method of estimating long-term swamp forest ET from meteorological data. The monthly crop factor indicated two distinct periods. From February to May, it was between 1.2 and 1.4 compared with June to January, when the crop factor was 0.8 to 1.0. The derived monthly K c values were verified as accurate (to one significant digit) using historical data measured at the same site, also using EC, from a~previous study. The measurements provided insights into the microclimate within a subtropical peat swamp forest and the contrasting sapflow of emergent and understory trees. They showed that expensive, high maintenance equipment can be used during manageable window periods in conjunction with low maintenance systems, dedicated to individual trees, to derive a model to estimate long-term ET over remote heterogeneous forests. In addition, the contrast in ET and rainfall emphasises the reliance of the Nkazana PSF on groundwater.

Description: Publication date: 2014 Source: Procedia Environmental Sciences, Volume 22 Author(s): Herman van Os , Rien Herber , Bert Scholtens The decision-making process for subsurface activities in the Netherlands has been unable to cope with the driving forces related to social acceptance in several recently proposed subsurface activities. We therefore investigated the possibility to include the triangle of social acceptance in the decision-making process. Our conceptual model relates the stakeholders, their goals and the driving forces to each other. We developed a framework, which describes the interaction between eleven design criteria for a Decision Support System (DSS). This framework will enable us to design a better, from a social acceptance perspective, DSS for subsurface activities in the Netherlands. Since the goals addressed in the decision-making process are very broad and the stakeholders are quite diverse, a single uniform DSS is not able to provide a satisfactory solution. We therefore suggest to design a DSS that is matched with each class of social acceptance.

Description: Publication date: 2014 Source: Procedia Environmental Sciences, Volume 22 Author(s): Yoshie Inada , Shinobu Izumi , Motoya Koga , Shigehito Matsubara We are developing a planning support system for welfare urban design. If we quantify the optimal route (the route that is the easiest to pass through) for challenged people, we will be able to select the areas that require adjustment in terms of accessibility with greater efficiency. In this paper we report on our development of the prototype system to present an optimal route for wheelchair users, and also, the two workshops we had for evaluating the accuracy of the resulted optimal route.

Description: Publication date: 2014 Source: Procedia Environmental Sciences, Volume 22 Author(s): Erfaneh Allameh , Mohammadali Heidari , Bauke De Vries , Harry Timmermans , Mohammad Masoud , Farhang Mozaffar Almost everyone would agree that teleworking is increasingly growing; but beyond this broad statement, we know little about how people behave when they work at home and how they balance their work and life. User comfort and productivity cannot be addressed properly, without a deep understanding of usersʼ working behavior. This gap is even deeper when it comes to the domain of smart homes as new types of housing which aim to enhance working at home. Hence, more user-centered studies are needed to comprehend the interrelationships among housing, technology, daily life and the work activities. In this paper, we use the outputs of an experiment to model usersʼ work activities in a smart home. The experiment was conducted among 254 respondents, who were asked to explore a smart home in a virtual environment and then to arrange their daily activities including work related activities in the virtual smart home. A choice modeling approach, based on the Multinomial Logit Model (MNL), is applied to model how an individual works at a smart home given influential factors such as the individualsʼ socio-demographic profile and their current lifestyle. Two features of working in a smart home are covered in this paper, namely, “the integration of work activities with other daily activities” and “the location of work activities in the house”. The results give better insight into the future trends of working at home and the effects of smart homes on working behavior of people. The results can be used in further developments of both smart homes and teleworking.

Description: Publication date: 2014 Source: Procedia Environmental Sciences, Volume 22 Author(s): Jinhee Kim , Soora Rasouli , Harry Timmermans Hybrid choice models have been developed as an extension of discrete choice models, particularly multinomial logit models, in an attempt to include attitudinal variables. The quintessence of hybrid choice models is that a model of attitude formation is estimated and the estimated attitudes are added to the commonly used set of attributes in discrete choice models: attributes of the choice alternatives and socio-demographic variables. The most commonly applied model is based on linear specifications, both for the attitude model and the utility function. In this review paper, we discuss the principles underlying the hybrid choice model, summarize the specifications used in previous applications of the model and then continue discussing recent progress that added social influence to the model specification and replaced the linear specification of the utility function with a nonlinear function.

Description: Publication date: 2014 Source: Procedia Environmental Sciences, Volume 22 Author(s): Yountaik Leem , Sang Ho Lee , Jungho Yoon To overcome many difficulties in sustaining the satisfying quality of life for a large population 1 , urban spaces are evolving toward more efficient spaces by combination with ICTs (information and communication technologies) and raising the possibility to provide improved urban services which can enrich the quality of life of the citizen. In many cities over the world, a good number of public and private services in transportation, environment, urban safety from crime or disaster, health and other fields are designed and implemented with IT infrastructure. In spite of the expectation of cost-effective urban services based on the linkage between data and systems, obstructions in administrative and technical domains have made it difficult to be implemented. In this study, two advanced ICTs based urban services, which were developed by linkage and convergence of urban information and systems of Korea were introduced and analysed. The structural design of system convergence and data sharing scheme of Carbon Emission Monitoring System (CEMS) in Sejong City uses UIS (Urban Information System for local authorities), GIS data and other data provided by the public agencies, such as Korea Meteorological Administration for the monitoring and analysing the characteristics of the energy consumption of household 2 . Another system, Urban Integrated CCTV Control System (ICCS) in Anyang City, shows integrated CCTV networks for crime prevention, traffic control and public facility management to provide extended urban services, such as disaster prevention, police investigation and others. Qualitative and Quantitative effects analyses with technical and policy directions were suggested for the development and improvement of future urban services for a liveable city.

Description: Publication date: Available online 12 November 2014 Source: Geoscience Frontiers Author(s): Wengang Zhang , Anthony T.C. Goh Piles are long, slender structural elements used to transfer the loads from the superstructure through weak strata onto stiffer soils or rocks. For driven piles, the impact of the piling hammer induces compression and tension stresses in the piles. Hence, an important design consideration is to check that the strength of the pile is sufficient to resist the stresses caused by the impact of the pile hammer. Due to its complexity, pile drivability lacks a precise analytical solution with regard to the phenomena involved. In situations where measured data or numerical hypothetical results are available, neural networks stand out in mapping the nonlinear interactions and relationships between the system's predictors and dependent responses. In addition, unlike most computational tools, no mathematical relationship assumption between the dependent and independent variables has to be made. Nevertheless, neural networks have been criticized for their long trial-and-error training process since the optimal configuration is not known a priori. This paper investigates the use of a fairly simple nonparametric regression algorithm known as multivariate adaptive regression splines (MARS), as an alternative to neural networks, to approximate the relationship between the inputs and dependent response, and to mathematically interpret the relationship between the various parameters. In this paper, the Back propagation neural network (BPNN) and MARS models are developed for assessing pile drivability in relation to the prediction of the Maximum compressive stresses (MCS), Maximum tensile stresses (MTS), and Blow per foot (BPF). A database of more than four thousand piles is utilized for model development and comparative performance between BPNN and MARS predictions. Graphical abstract

Description: Publication date: Available online 18 November 2014 Source: Geoscience Frontiers Author(s): Fei Gao , Lily Wang , Mudan Yin