Runoff models such as the Curve Number (CN) model are dependent upon land use and soil type within the watershed or contributing area. In regions with internal drainage (e.g. wetlands) watershed delineation methods th...Runoff models such as the Curve Number (CN) model are dependent upon land use and soil type within the watershed or contributing area. In regions with internal drainage (e.g. wetlands) watershed delineation methods that fill sinks can result in inaccurate contributing areas and estimations of runoff from models such as the CN model. Two methods to account for this inaccuracy have been 1) to adjust the initial abstraction value within the CN model;or 2) to improve the watershed delineation in order to better account for internal drainage. We used a combined approach of examining the watershed delineation, and refining the CN model by the incorporating of dual hydrologic soil classifications. For eighteen watersheds within Wisconsin, we compared the CN model results of three watershed delineation methods to USGS gaged values. We found that for large precipitation events (>100 mm) the CN model estimations are closer to observed values for watershed delineations that identify the directly connected watershed and use the undrained hydrologic soil classification.展开更多
Digital Elevation Models (DEMs) are spatial grids which are used to automate watershed boundary determination. Sinks are present within most DEMs. In order to easily process the watershed boundary, the sinks are reass...Digital Elevation Models (DEMs) are spatial grids which are used to automate watershed boundary determination. Sinks are present within most DEMs. In order to easily process the watershed boundary, the sinks are reassigned to elevation equivalent to an adjacent cell. The derived DEM is called a “filled” DEM. Due to its relative simplicity, the use of the “filled” DEM is one of the most widely used methods to delineate watershed boundaries and works well in about 70 percent of the watersheds in the US. In landscapes with internal drainage, sinks may accurately represent these depressions. In this study, we compare two delineation methods that do not fill in sinks to another method that does fill in sinks. We examined ten gaged watersheds in Wisconsin and Minnesota. We found the spatial extent of the watersheds from the three methods were significantly different. To evaluate the delineation methods, we modeled ten runoff events using the Curve Number (CN) method and compared them to USGS gage discharge for each watershed. For small storms we found that there were no significant differences in the modeled runoff for three delineation methods. For large storms, we found the no-fill methods had a smaller error, but overall the difference was insignificant. This research suggests that capturing internal drainage by the delineation does not have much of an impact on the widely used CN model.展开更多
径流曲线数模型(Soil Conservation Service Curve Number Model,简称SCS-CN模型)可以利用降雨资料估算径流,对水资源合理配置和山洪灾害预警具有重要意义,因为其方便计算、参数简单,而被广泛应用。目前标准SCS-CN模型在山区小流域的适...径流曲线数模型(Soil Conservation Service Curve Number Model,简称SCS-CN模型)可以利用降雨资料估算径流,对水资源合理配置和山洪灾害预警具有重要意义,因为其方便计算、参数简单,而被广泛应用。目前标准SCS-CN模型在山区小流域的适用性欠佳,因此需要对模型参数进行优化以提高预测精度。本文以湖南省螺岭桥流域为例,根据实测降雨径流资料优化径流曲线数CN(Curve Number)查算表,并利用步长优化参数算法研究初损率对模型精度的影响,将优化模型的方法应用于湖南省凤凰小流域,验证该优化方法的可靠性。结果分析表明:与标准SCS-CN模型相比,优化后的SCS-CN模型效率系数NSE从0.576提升至0.813,决定系数R^(2)为0.858。将模型优化方法验证于气候地形条件相似的凤凰流域,模型NSE值提高117%。通过预测径流深与实测径流深比较,优化模型模拟精度较为理想,对湖南省山区小流域场次降雨产流预报有一定的参考意义。展开更多
The curve number and phi(4)-index models each provide a simple one-parameter relationship between storm-event rainfall and runoff. It is shown that the curve number and 4-index models can both be used to segregate the...The curve number and phi(4)-index models each provide a simple one-parameter relationship between storm-event rainfall and runoff. It is shown that the curve number and 4-index models can both be used to segregate the rainfall hyetograph into initial abstraction, retention, and runoff amounts. However, the principal advantages of the 4-index model are that both rainfall distribution and duration can be explicitly taken into account in calculating runoff, and the 4 index is more physically based than the curve number. The quantitative relationship between the curve number and the 4 index is presented and validated with field measurements. Knowing the relationship between the curve number and the 4 index is useful in that it facilitates using the extensive database of curve numbers in the more realistic 4-index model in calculating a runoff hydrograph from a given rainfall hyetograph. It is demonstrated that conventional adjustments to curve numbers can be largely explained by variations in storm duration, which suggests that variable rainfall duration can possibly be an essential factor in accounting for deviations from the median curve number of a catchment.展开更多
The proper determination of the curve number(CN) in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and 5 Polish Carpathian catchments. Empiri...The proper determination of the curve number(CN) in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and 5 Polish Carpathian catchments. Empirical curve numbers were applied to the distribution fitting. Next, theoretical characteristics of CN were estimated. For 100-CN the Generalized Extreme Value(GEV) distribution was identified as the best fit in most of the catchments. An assessment of the differences between the characteristics estimated from theoretical distributions and the tabulated values of CN was performed. The comparison between the antecedent runoff conditions(ARC) of Hawkins and Hjelmfelt was also completed. The analysis was done for various magnitudes of rainfall. Confidence intervals(CI) were helpful in this evaluation. The studies revealed discordances between the tabulated and estimated CNs. The tabulated CNs were usually lower than estimated values; therefore, an application of the median value and the probabilistic ARC of Hjelmfelt for wet runoff conditions is advisable. For dry conditions the ARC of Hjelmfelt usually better estimated CN than ARC of Hawkins did, but in several catchments neither the ARC of Hawkins nor Hjelmfelt sufficiently depicted the variability in CN.展开更多
The aim of this study was to determine if runoff estimates from the curve number model were affected by seasons for different land covers. Eighteen watersheds with varying land covers were delineated using three metho...The aim of this study was to determine if runoff estimates from the curve number model were affected by seasons for different land covers. Eighteen watersheds with varying land covers were delineated using three methods. The delineation methods differ in how internal drainage is evaluated. Runoff estimates from storms for spring, summer, and fall were compared to observed runoff from USGS gaging station data. Errors (difference between estimate runoff and observed runoff) were found to be highest for fall by 3% for all the two delineation methods which do not consider internal drainage. Watersheds were categorized by their dominant land cover (agriculture, forest, or urban). Seasonal differences were found to be significant for certain land covers. The greatest differences between observed and estimated data were found in agriculture and urban especially spring versus fall for all delineations. Forest land cover was found to have no seasonal difference for all three delineation methods. The research suggests that this work contributes to the growing body of research suggesting that vegetative seasonal differences have a greater impact on runoff than is accounted for in the runoff model.展开更多
文摘Runoff models such as the Curve Number (CN) model are dependent upon land use and soil type within the watershed or contributing area. In regions with internal drainage (e.g. wetlands) watershed delineation methods that fill sinks can result in inaccurate contributing areas and estimations of runoff from models such as the CN model. Two methods to account for this inaccuracy have been 1) to adjust the initial abstraction value within the CN model;or 2) to improve the watershed delineation in order to better account for internal drainage. We used a combined approach of examining the watershed delineation, and refining the CN model by the incorporating of dual hydrologic soil classifications. For eighteen watersheds within Wisconsin, we compared the CN model results of three watershed delineation methods to USGS gaged values. We found that for large precipitation events (>100 mm) the CN model estimations are closer to observed values for watershed delineations that identify the directly connected watershed and use the undrained hydrologic soil classification.
文摘Digital Elevation Models (DEMs) are spatial grids which are used to automate watershed boundary determination. Sinks are present within most DEMs. In order to easily process the watershed boundary, the sinks are reassigned to elevation equivalent to an adjacent cell. The derived DEM is called a “filled” DEM. Due to its relative simplicity, the use of the “filled” DEM is one of the most widely used methods to delineate watershed boundaries and works well in about 70 percent of the watersheds in the US. In landscapes with internal drainage, sinks may accurately represent these depressions. In this study, we compare two delineation methods that do not fill in sinks to another method that does fill in sinks. We examined ten gaged watersheds in Wisconsin and Minnesota. We found the spatial extent of the watersheds from the three methods were significantly different. To evaluate the delineation methods, we modeled ten runoff events using the Curve Number (CN) method and compared them to USGS gage discharge for each watershed. For small storms we found that there were no significant differences in the modeled runoff for three delineation methods. For large storms, we found the no-fill methods had a smaller error, but overall the difference was insignificant. This research suggests that capturing internal drainage by the delineation does not have much of an impact on the widely used CN model.
文摘径流曲线数模型(Soil Conservation Service Curve Number Model,简称SCS-CN模型)可以利用降雨资料估算径流,对水资源合理配置和山洪灾害预警具有重要意义,因为其方便计算、参数简单,而被广泛应用。目前标准SCS-CN模型在山区小流域的适用性欠佳,因此需要对模型参数进行优化以提高预测精度。本文以湖南省螺岭桥流域为例,根据实测降雨径流资料优化径流曲线数CN(Curve Number)查算表,并利用步长优化参数算法研究初损率对模型精度的影响,将优化模型的方法应用于湖南省凤凰小流域,验证该优化方法的可靠性。结果分析表明:与标准SCS-CN模型相比,优化后的SCS-CN模型效率系数NSE从0.576提升至0.813,决定系数R^(2)为0.858。将模型优化方法验证于气候地形条件相似的凤凰流域,模型NSE值提高117%。通过预测径流深与实测径流深比较,优化模型模拟精度较为理想,对湖南省山区小流域场次降雨产流预报有一定的参考意义。
文摘The curve number and phi(4)-index models each provide a simple one-parameter relationship between storm-event rainfall and runoff. It is shown that the curve number and 4-index models can both be used to segregate the rainfall hyetograph into initial abstraction, retention, and runoff amounts. However, the principal advantages of the 4-index model are that both rainfall distribution and duration can be explicitly taken into account in calculating runoff, and the 4 index is more physically based than the curve number. The quantitative relationship between the curve number and the 4 index is presented and validated with field measurements. Knowing the relationship between the curve number and the 4 index is useful in that it facilitates using the extensive database of curve numbers in the more realistic 4-index model in calculating a runoff hydrograph from a given rainfall hyetograph. It is demonstrated that conventional adjustments to curve numbers can be largely explained by variations in storm duration, which suggests that variable rainfall duration can possibly be an essential factor in accounting for deviations from the median curve number of a catchment.
基金supported by the Slovak Grant Agency VEGA under Project No.1/0776/13 and Project No.1/0710/15Research Project No.N N305 396238 founded by the Polish Ministry of Science and Higher Education
文摘The proper determination of the curve number(CN) in the SCS-CN method reduces errors in predicting runoff volume. In this paper the variability of CN was studied for 5 Slovak and 5 Polish Carpathian catchments. Empirical curve numbers were applied to the distribution fitting. Next, theoretical characteristics of CN were estimated. For 100-CN the Generalized Extreme Value(GEV) distribution was identified as the best fit in most of the catchments. An assessment of the differences between the characteristics estimated from theoretical distributions and the tabulated values of CN was performed. The comparison between the antecedent runoff conditions(ARC) of Hawkins and Hjelmfelt was also completed. The analysis was done for various magnitudes of rainfall. Confidence intervals(CI) were helpful in this evaluation. The studies revealed discordances between the tabulated and estimated CNs. The tabulated CNs were usually lower than estimated values; therefore, an application of the median value and the probabilistic ARC of Hjelmfelt for wet runoff conditions is advisable. For dry conditions the ARC of Hjelmfelt usually better estimated CN than ARC of Hawkins did, but in several catchments neither the ARC of Hawkins nor Hjelmfelt sufficiently depicted the variability in CN.
文摘The aim of this study was to determine if runoff estimates from the curve number model were affected by seasons for different land covers. Eighteen watersheds with varying land covers were delineated using three methods. The delineation methods differ in how internal drainage is evaluated. Runoff estimates from storms for spring, summer, and fall were compared to observed runoff from USGS gaging station data. Errors (difference between estimate runoff and observed runoff) were found to be highest for fall by 3% for all the two delineation methods which do not consider internal drainage. Watersheds were categorized by their dominant land cover (agriculture, forest, or urban). Seasonal differences were found to be significant for certain land covers. The greatest differences between observed and estimated data were found in agriculture and urban especially spring versus fall for all delineations. Forest land cover was found to have no seasonal difference for all three delineation methods. The research suggests that this work contributes to the growing body of research suggesting that vegetative seasonal differences have a greater impact on runoff than is accounted for in the runoff model.
