为解决SWAT(soil and water assessment tool)模型在复杂情形下的参数不确定性分析问题,引入参数不确定性分析平台UQ-PyL(Uncertainty Quantification Python Laboratory),开发UQ-PyL与SWAT模型的耦合模块,使得UQ-PyL中的各种算法能够...为解决SWAT(soil and water assessment tool)模型在复杂情形下的参数不确定性分析问题,引入参数不确定性分析平台UQ-PyL(Uncertainty Quantification Python Laboratory),开发UQ-PyL与SWAT模型的耦合模块,使得UQ-PyL中的各种算法能够方便快捷地应用于SWAT模型的参数不确定性分析。为验证UQ-PyL用于SWAT模型参数不确定性分析的效果,在我国不同气候条件下的4个流域构建SWAT模型,综合对比评估UQ-PyL与SWAT-CUP对模型参数的不确定性分析结果。结果表明:UQ-PyL多种敏感性分析方法筛选出的敏感参数比SWAT-CUP单一方法筛选的结果更加合理;使用UQ-PyL率定的参数在4个流域应用中都表现良好,优化后模拟结果的纳什效率系数均在0.55以上,收敛次数在550次以内;在4个流域的模拟中,UQ-PyL能提供计算效率更高的算法ASMO,也能提供模拟结果更准确的算法SCE。综上,与SWAT模型相耦合的UQ-PyL能够支持SWAT模型用户在不同系统下对模型参数进行更高效的不确定性分析研究。展开更多
This study was undertaken to examine the applicability of the SWAT model in Gumera river basin upstream of Lake Tana, Ethiopia for simulating stream runoff and sediment load. The area of river basin was discretized in...This study was undertaken to examine the applicability of the SWAT model in Gumera river basin upstream of Lake Tana, Ethiopia for simulating stream runoff and sediment load. The area of river basin was discretized into 24 sub-catchments using ArcSWAT interface of the model. The semi automated Sequential Uncertainty Fitting (SUFI2) and fully automated Parameter Solution (ParaSol) calibration process built in SWAT calibration and uncertainty program (SWAT-CUP) were used to calibrate the model parameters using time series of flow and sediment load data of 1994 to 2002 and validated with the observed data from years 2003 to 2006. The performance of the model was evaluated using statistical and graphical methods to assess the capability of the model in simulating the runoff and sediment yield for the study area. The coefficient of determination (R2) and NSE values for the daily runoff by using [ParaSol] optimization technique was obtained as 0.72 and 0.71 respectively for the calibration period and 0.79 and 0.78 respectively for the validation period, R2 and NSE values of monthly flow calibration using SUFI2 are 0.83 and 0.78 respectively for validation it was 0.93 and 0.93. For monthly sediment yield by using SUFI2 calibration technique the model evaluation coefficients R2 and NS for calibration was computed as 0.61 and 0.60 respectively, for validation it was 0.84 and 0.83 respectively. The sensitivity analysis on 13 runoff producing parameters was also carried out and discussed.展开更多
The hydrology of the Little Ruaha River which is a major catchment of the Ihemi Cluster in the Southern Agricultural Growth Corridor of Tanzania (SA-GCOT) has been studied. The study focused on the hydrological assess...The hydrology of the Little Ruaha River which is a major catchment of the Ihemi Cluster in the Southern Agricultural Growth Corridor of Tanzania (SA-GCOT) has been studied. The study focused on the hydrological assessment through analysis of the available data and developing a model that could be used for assessing impacts of environmental change. Pressures on land and water resources in the watershed are increasing mainly as a result of human activities, and understanding the hydrological regime is deemed necessary. In this study, modeling was conducted using the Soil and Water Assessment Tool (SWAT) in which meteorological and streamflow data were used in the simulation, calibration and evaluation. Calibration and evaluation was done at three gauging stations and the results were deemed plausible with NSE ranging between 0.64 and 0.80 for the two stages. The simulated flows were used for gap filling the missing data and generation of complete daily time series of streamflow at three gauging stations of Makalala, Ihimbu and Mawande. Results of statistical trends and flow duration curves, revealed decline in magnitudes of seasonal and annual flows indicating that streamflows are changing with time and may have implications on envisioned development and the water dependent ecosystems.展开更多
Understanding watershed runoff processes is critical for planning effective soil and water management practices and efficiently utilize available water resources. The main objective of this study was to investigate th...Understanding watershed runoff processes is critical for planning effective soil and water management practices and efficiently utilize available water resources. The main objective of this study was to investigate the performance of the Soil and Water Assessment Tool (SWAT) to simulate streamflow from the Bina basin in the Madhya Pradesh state of India. The SWAT model was calibrated and validated on a daily and monthly basis using historical streamflow and weather data from the Bina basin. The Sequential Uncertainty Fitting (SUFI-2) technique in the SWAT? Calibration and Uncertainty Procedures (SWAT-CUP) program was used to assess model uncertainties. The SWAT model performed “satisfactory” and “very good” in simulating streamflow at daily and monthly time steps, respectively. Model calibration results showed that coefficients of determination (R2) values were 0.66 and 0.96;while Nash-Sutcliffe (NSE) values were 0.65 and 0.94 for daily and monthly simulations, respectively. The R2 values of daily and monthly simulations during model validation were 0.65 and 0.72, respectively while the respective NSE values were 0.58 and 0.72. This study demonstrated that the SWAT model could be effectively used to simulate streamflow in the Bina river basin.展开更多
Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model para-meters), making quantification of uncertainty in hydro- l...Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model para-meters), making quantification of uncertainty in hydro- logical modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Like-lihood Uncertainty Estimation (GLUE), Sequential Uncer-tainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and R- factor, coefficient of determination (R^2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor > 0.83, R-factor < 0.56 and R^2>0.91, NSE > 0.89, and 0.18 < PBIAS < 0.32. Hence, we would suggest to use SUFI-2 initially to set the parameter ranges, and further use PSO for final analysis. Indeed, the uncertainty analysis must be accounted when the outcomes of the model use for policy or management decisions.展开更多
文摘为解决SWAT(soil and water assessment tool)模型在复杂情形下的参数不确定性分析问题,引入参数不确定性分析平台UQ-PyL(Uncertainty Quantification Python Laboratory),开发UQ-PyL与SWAT模型的耦合模块,使得UQ-PyL中的各种算法能够方便快捷地应用于SWAT模型的参数不确定性分析。为验证UQ-PyL用于SWAT模型参数不确定性分析的效果,在我国不同气候条件下的4个流域构建SWAT模型,综合对比评估UQ-PyL与SWAT-CUP对模型参数的不确定性分析结果。结果表明:UQ-PyL多种敏感性分析方法筛选出的敏感参数比SWAT-CUP单一方法筛选的结果更加合理;使用UQ-PyL率定的参数在4个流域应用中都表现良好,优化后模拟结果的纳什效率系数均在0.55以上,收敛次数在550次以内;在4个流域的模拟中,UQ-PyL能提供计算效率更高的算法ASMO,也能提供模拟结果更准确的算法SCE。综上,与SWAT模型相耦合的UQ-PyL能够支持SWAT模型用户在不同系统下对模型参数进行更高效的不确定性分析研究。
文摘This study was undertaken to examine the applicability of the SWAT model in Gumera river basin upstream of Lake Tana, Ethiopia for simulating stream runoff and sediment load. The area of river basin was discretized into 24 sub-catchments using ArcSWAT interface of the model. The semi automated Sequential Uncertainty Fitting (SUFI2) and fully automated Parameter Solution (ParaSol) calibration process built in SWAT calibration and uncertainty program (SWAT-CUP) were used to calibrate the model parameters using time series of flow and sediment load data of 1994 to 2002 and validated with the observed data from years 2003 to 2006. The performance of the model was evaluated using statistical and graphical methods to assess the capability of the model in simulating the runoff and sediment yield for the study area. The coefficient of determination (R2) and NSE values for the daily runoff by using [ParaSol] optimization technique was obtained as 0.72 and 0.71 respectively for the calibration period and 0.79 and 0.78 respectively for the validation period, R2 and NSE values of monthly flow calibration using SUFI2 are 0.83 and 0.78 respectively for validation it was 0.93 and 0.93. For monthly sediment yield by using SUFI2 calibration technique the model evaluation coefficients R2 and NS for calibration was computed as 0.61 and 0.60 respectively, for validation it was 0.84 and 0.83 respectively. The sensitivity analysis on 13 runoff producing parameters was also carried out and discussed.
文摘The hydrology of the Little Ruaha River which is a major catchment of the Ihemi Cluster in the Southern Agricultural Growth Corridor of Tanzania (SA-GCOT) has been studied. The study focused on the hydrological assessment through analysis of the available data and developing a model that could be used for assessing impacts of environmental change. Pressures on land and water resources in the watershed are increasing mainly as a result of human activities, and understanding the hydrological regime is deemed necessary. In this study, modeling was conducted using the Soil and Water Assessment Tool (SWAT) in which meteorological and streamflow data were used in the simulation, calibration and evaluation. Calibration and evaluation was done at three gauging stations and the results were deemed plausible with NSE ranging between 0.64 and 0.80 for the two stages. The simulated flows were used for gap filling the missing data and generation of complete daily time series of streamflow at three gauging stations of Makalala, Ihimbu and Mawande. Results of statistical trends and flow duration curves, revealed decline in magnitudes of seasonal and annual flows indicating that streamflows are changing with time and may have implications on envisioned development and the water dependent ecosystems.
文摘Understanding watershed runoff processes is critical for planning effective soil and water management practices and efficiently utilize available water resources. The main objective of this study was to investigate the performance of the Soil and Water Assessment Tool (SWAT) to simulate streamflow from the Bina basin in the Madhya Pradesh state of India. The SWAT model was calibrated and validated on a daily and monthly basis using historical streamflow and weather data from the Bina basin. The Sequential Uncertainty Fitting (SUFI-2) technique in the SWAT? Calibration and Uncertainty Procedures (SWAT-CUP) program was used to assess model uncertainties. The SWAT model performed “satisfactory” and “very good” in simulating streamflow at daily and monthly time steps, respectively. Model calibration results showed that coefficients of determination (R2) values were 0.66 and 0.96;while Nash-Sutcliffe (NSE) values were 0.65 and 0.94 for daily and monthly simulations, respectively. The R2 values of daily and monthly simulations during model validation were 0.65 and 0.72, respectively while the respective NSE values were 0.58 and 0.72. This study demonstrated that the SWAT model could be effectively used to simulate streamflow in the Bina river basin.
文摘Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model para-meters), making quantification of uncertainty in hydro- logical modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Like-lihood Uncertainty Estimation (GLUE), Sequential Uncer-tainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and R- factor, coefficient of determination (R^2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor > 0.83, R-factor < 0.56 and R^2>0.91, NSE > 0.89, and 0.18 < PBIAS < 0.32. Hence, we would suggest to use SUFI-2 initially to set the parameter ranges, and further use PSO for final analysis. Indeed, the uncertainty analysis must be accounted when the outcomes of the model use for policy or management decisions.
