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Sponge city construction (SCC) in China, as a new concept and a practical application of low-impact development (LID), is gaining wide popularity. Modelling tools are widely used to evaluate the ecological benefits of SCC in storm...
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Sponge city construction (SCC) in China, as a new concept and a practical application of low-impact development (LID), is gaining wide popularity. Modelling tools are widely used to evaluate the ecological benefits of SCC in stormwater pollution mitigation. However, the understanding of the robustness of water quality modelling with different LID design options is still limited due to the paucity of water quality data as well as the high cost of water quality data collection and model calibration. This study develops a new concept of 'robustness' measured by model calibration performances. It combines an automatic calibration technique with intensive field monitoring data to perform the robustness analysis of storm water quality modelling using the SWMM (Storm Water Management Model). One of the national pilot areas of SCC, Fenghuang Cheng, in Shenzhen, China, is selected as the study area. Five water quality variables (COD, NH3-N, TN, TP, and SS) and 13 types of LID/non-LID infrastructures are simulated using 37 rainfall events. The results show that the model performance is satisfactory for different water quality variables and LID types. Water quality modelling of greenbelts and rain gardens has the best performance, while the models of barrels and green roofs are not as robust as those of the other LID types. In urban runoff, three water quality parameters, namely, SS, TN and COD, are better captured by the SWMM models than NH_3-N and TP. The modelling performance tends to be better under heavy rain and significant pollutant concentrations, denoting a potentially more stable and reliable design of infrastructures. This study helps to improve the current understanding of the feasibility and robustness of using the SWMM model in sponge city design.
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This study attempted to use the soil and water assessment tool (SWAT), integrated with geographic information systems (GIS), for assessment of climate change impacts on hydropower generation. This methodology of climate change imp...
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This study attempted to use the soil and water assessment tool (SWAT), integrated with geographic information systems (GIS), for assessment of climate change impacts on hydropower generation. This methodology of climate change impact modeling was developed and demonstrated through application to a hydropower plant in the Rio Jubones Basin in Ecuador. ArcSWAT 2012 was used to develop a model for simulating the river flow. The model parameters were calibrated and validated on a monthly scale with respect to the hydro-meteorological inputs observed from 1985 to 1991 and from 1992 to 1998, respectively. Statistical analyses produced Nash-Sutcliffe efficiencies (NSEs) of 0.66 and 0.61 for model calibration and validation, respectively, which were considered acceptable. Numerical simulation with the model indicated that climate change could alter the seasonal flow regime of the basin, and the hydropower potential could change due to the changing climate in the future. Scenario analysis indicates that, though the hydropower generation will increase in the wet season, the plant will face a significant power shortage during the dry season, up to 13.14% from the reference scenario, as a consequence of a 17% reduction of streamflow under an assumption of a 2.9°C increase in temperature and a 15% decrease in rainfall. Overall, this study showed that hydrological processes are realistically modeled with SWAT and the model can be a useful tool for predicting the impact of climate change.
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Sustainable development of the Himalayan region is directly linked to optimal utilization of available renewable resources. There is a need to first select the zones suitable for hydropower sites, and then to focus on them only; a...
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Sustainable development of the Himalayan region is directly linked to optimal utilization of available renewable resources. There is a need to first select the zones suitable for hydropower sites, and then to focus on them only; as purely field-based surveying of rugged mountainous regions for hydropower generation requires too much of time and effort. We used geospatial tools to identify suitable sites for hydropower generation. A Geographic Information System (GIS)-based tool called Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) was used for computing annual runoff volume using watershed-wise topography and biophysical variables. The zones suitable for hydropower generation were then identified based on calculated hydropower energy using derived runoff volumes and hydraulic head. The model accuracy was checked using well established efficiency criteria: coefficient of determination (R-2 = 0.98), RMSE-observations standard deviation ratio (RSR), Percent bias (PBIAS) and Nash-Sutcliffe efficiency (NSE). For all these parameters, the model was found to be performing satisfactorily.
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Despite all the progress made over the years on developing automatic methods for analysing hydrographs and measuring the performance of rainfall-runoff models, automatic methods cannot yet match the power and flexibility of the hu...
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Despite all the progress made over the years on developing automatic methods for analysing hydrographs and measuring the performance of rainfall-runoff models, automatic methods cannot yet match the power and flexibility of the human eye and brain. Very simple approaches are therefore being developed that mimic the way hydrologists inspect and interpret hydrographs, including the way that patterns are recognised, links are made by eye, and hydrological responses and errors are studied and remembered. In this paper, a dynamic programming algorithm originally designed for use in data mining is customised for use with hydrographs. It generates sets of " rays" that are analogous to the visual links made by the hydrologist's eye when linking features or times in one hydrograph to the corresponding features or times in another hydrograph. One outcome from this work is a new family of performance measures called " visual" performance measures. These can measure differences in amplitude and timing, including the timing errors between simulated and observed hydrographs in model calibration. To demonstrate this, two visual performance measures, one based on the Nash-Sutcliffe Efficiency and the other on the mean absolute error, are used in a total of 34 split-sample calibration-validation tests for two rainfall-runoff models applied to the Hodder catchment, northwest England. The customised algorithm, called the Hydrograph Matching Algorithm, is very simple to apply; it is given in a few lines of pseudocode.
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Hydrologic modeling using precipitation estimated from satellite images considers temporal and spatial variability of the precipitation. The objective of this study was to model the rain-runoff process and calibrate some hourly hy...
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Hydrologic modeling using precipitation estimated from satellite images considers temporal and spatial variability of the precipitation. The objective of this study was to model the rain-runoff process and calibrate some hourly hydrograms from the Coahuayana River Basin in Jalisco, Mexico. IMERG version 6 satellite rainfall images during the maximum events occurred in July 2010, October 2011, September 2013, October 2015, and August 2021 were used. The basin is located in the states of Jalisco, Colima, and Michoacán, and covers an area of 7332 km 2 . The hydrologic model was developed using the program HEC-HMS and calibrated at the CONAGUA hydrometric station Callejones. The methods used for the calculations are the runoff curve number and Clark’s modified unitary hydrogram. The results obtained in three of the five events were satisfactory: the Nash-Sutcliffe coefficient (NSE) oscillated between 0.39 and 0.77, and R 2 oscillated between 0.51 and 0.86. We concluded that the integration of an hourly hydrologic model with IMERG-L satellite rainfall images is a good option in areas where hourly rainfall data measured on land is scarce or non-existent.
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Infiltration and drainage are complex hydrological considerations to determine unsaturated flow processes in case of irrigation, root growth and pollutant transport in porous media consisting of multi-layered soils. Considering sp...
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Infiltration and drainage are complex hydrological considerations to determine unsaturated flow processes in case of irrigation, root growth and pollutant transport in porous media consisting of multi-layered soils. Considering sports fields, this affects the quality of sports organization in terms of player's health, the participation of spectators and the cancellation of games. This study investigated the drainage behavior of sports fields both experimentally and numerically under simulated rainfall. To achieve this goal, a newly-developed experimental setup which consists of a rainfall simulator (RS) that is able to simulate the natural rainfall, and a drainage tank (DT) that is able to pack stratified drainage layers same as in the sports fields were used. Experimental rainfall hyetographs were designed to simulate various rainfall conditions for the relevant region in Istanbul, Turkey. Numerous experiments were conducted to investigate hydrological description of unsaturated flow by using packed drainage layers in the laboratory. Time-dependent water contents were also monitored using soil moisture sensors (10-HS, Decagon Devices) at different depths in the drainage layers. Soil water retention curve (SWRC) of each drainage layer obtained from calibration tests and empirical parameters (a, n) were optimized with HYDRUS-3D model by using water contents and suction pressure results. Observed drain outflow hydrographs were compared with simulated drain outflow hydrographs by using statistical indices of Nash-Sutcliffe Efficiency (NSE) index, Kling and Gupta Efficiency (KGE) index and determination coefficient (R-2). Experimental results and HYDRUS-3D simulations showed good compatibility with the values of NSE, KGE and R-2 varied between 0.859-0.958, 0.594-0.972 and 0.868-0.975, respectively. In the present study, experimental and numerical investigation of the drainage mechanisms for sports fields was evaluated by considering unsaturated flow characteristics through the different drainage layers.
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Streamflow records with sufficient spatial and temporal coverage at the site of interest are usually scarce in Pakistan. As an alternative, various regional methods have been frequently adopted to derive hydrological information, ...
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Streamflow records with sufficient spatial and temporal coverage at the site of interest are usually scarce in Pakistan. As an alternative, various regional methods have been frequently adopted to derive hydrological information, which in essence attempt to transfer hydrological information from gauged to ungauged catchments. In this study, a new concept of ensemble hydrological prediction (EHP) was introduced which is an improved regional method for hydrological prediction at ungauged sites. It was mainly based on the performance weights (triple-connection weights (TCW)) derived from Nash Sutcliffe efficiency (NSE) and hydrological variable (here percentiles) calculated from three traditional regional transfer methods (RTMs) with suitable modification (i.e., three-step drainage area ratio (DAR) method, inverse distance weighting (IDW) method, and three-step regional regression analysis (RRA)). The overall results indicated that the proposed EHP method was robust for estimating hydrological percentiles at ungauged sites as compared to traditional individual RTMs. The comparative study based on NSE, percent bias (PBIAS) and the relative error (RE) as performance criteria resulted that the EHP is a constructive alternative for hydrological prediction of ungauged basins. (C) 2015 Elsevier B.V. All rights reserved.
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ABSTRACT The investigation of methods to evaluate the performance of hydrological models has never stopped. This study explores an innovative application, called joint multifractal spectra (JMS) analysis. The JMS analysis, which i...
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ABSTRACT The investigation of methods to evaluate the performance of hydrological models has never stopped. This study explores an innovative application, called joint multifractal spectra (JMS) analysis. The JMS analysis, which is demonstrated in three typical basins in Zhejiang Province, China, analyses both flood and low-flow periods. JMS is applied to seasonal-decomposed observed and simulated runoff series, thus helping to analyse the rising and the recession processes of discharge, which are unique features of a hydrograph. This is achieved by using q exponents to magnify or shrink the relative magnitudes of different parts. The joint multifractal spectra revealed many details of modelling, like the evaluation of recession process modelling. Given its versatility, the JMS analysis has great potential for its applications in hydrological modelling.
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To secure accuracy in the Soil and Water Assessment Tool (SWAT) simulation for various hydrology and water quality studies, calibration and validation should be performed. When calibrating and validating the SWAT model with measur...
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To secure accuracy in the Soil and Water Assessment Tool (SWAT) simulation for various hydrology and water quality studies, calibration and validation should be performed. When calibrating and validating the SWAT model with measured data, the Nash-Sutcliffe efficiency (NSE) is widely used, and is also used as a goal function of auto-calibration in the current SWAT model (SWAT ver. 2009). However, the NSE value has been known to be influenced by high values within a given dataset, at the cost of the accuracy in estimated lower flow values. Furthermore, the NSE is unable to consider direct runoff and baseflow separately. In this study, the existing SWAT auto-calibration was modified with direct runoff separation and flow clustering calibration, and current and modified SWAT auto-calibration were applied to the Soyanggang-dam watershed in South Korea. As a result, the NSE values for total streamflow, high flow, and low flow groups in direct runoff, and baseflow estimated through modified SWAT auto-calibration were 0.84, 0.34, 0.09, and 0.90, respectively. The NSE values of current SWAT auto-calibration were 0.83, 0.47, -0.14, and 0.90, respectively. As shown in this study, the modified SWAT auto-calibration shows better calibration results than current SWAT auto-calibration. With these capabilities, the SWAT-estimated flow matched the measured flow data well for the entire flow regime. The modified SWAT auto-calibration module developed in this study will provide a very efficient tool for the accurate simulation of hydrology, sediment transport, and water quality with no additional input datasets.
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Incorporating the time variant function of the otherwise used as steady infiltration rate, this paper presents revised versions of the popular and frequently used Kostiakov and modified Kostiakov infiltration models. The proposed,...
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Incorporating the time variant function of the otherwise used as steady infiltration rate, this paper presents revised versions of the popular and frequently used Kostiakov and modified Kostiakov infiltration models. The proposed, along with the existing, versions are tested on 40 datasets of infiltration observed on five different soils in India and USA The former indicated an improved performance over their respective existing versions. Further generalization of the improved modified Kostiakov model incorporating time to ponding showed an enhanced performance on all the soils.
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