A Rain Duration and Modified AMC-dependent SCS-CN Procedure for Long Duration Rainfall-runoff Events

This paper presents a rain duration-dependent procedure based on the popular Soil Conservation Service Curve Number (SCS-CN) methodology for computation of direct surface runoff from long duration rains. Curve numbers are derived from long-term daily rainfall-runoff data, and antecedent moisture condition (AMC) related with antecedent duration. Analysis of data from five Indian (large, in terms of area) watersheds reveals the calculated curve numbers to decrease with the considered duration, showing the existence of a characteristic value of minimum CN or maximum initial abstraction to occur in a watershed for a pre-selected AMC. The testing of the proposed procedure on the separate (measured) rainfall-runoff event data sets from the same watersheds suggests satisfactory workability of the method.     

SCS-CN模型中CN值的空间移用效果研究

SCS-CN模型因其曲线数CN值可以根据下垫面(土壤和植被)确定,近年来在分布式水文模拟和无/缺资料地区得到较为广泛的应用。美国土壤保持局提供的CN查算表在中国地区并不完全适用,如果直接采用,可能会带来较大的径流计算误差。选择资料数据较好的北京柏崖厂站作为假定的无实测径流资料的目标站,通过相似流域特性分析确定北山下站为参证站,利用参证站资料计算出CN值校正系数,并将该系数引用到目标站,利用校正前后的CN值分别模拟多场次洪水。结果表明,SCS-CN模型的参数CN值修正后,在空间上具备一定的外推能力;无论在确定性系数、径流总量精度和洪峰流量精度上,CN值修正后的洪水预报精度都要比修正前要高。     

A modified NRCS-CN method for eliminating abrupt runoff changes induced by the categorical antecedent moisture conditions

The popular Natural Resources Conservation Service Curve Number (NRCS-CN) (earlier known as Soil Conservation Service Curve Number (SCS-CN) method of rainfall-runoff modeling has often faced the criticism of exhibiting quantum jumps in runoff computations because of the sudden jumps appearing in CN-values derived from NEH-4 tables for three antecedent moisture conditions (AMC), viz., AMC-I, AMC-II, and AMC-III valid for dry, normal, and wet conditions, respectively. The variability of antecedent soil moisture within an AMC category is responsible for the abrupt jump and other deficiencies in the CN method for runoff estimation. This paper suggests a novel procedure to account for the antecedent moisture (M), preventing quantum jumps and eliminating deficiencies in determination of CN and, in turn, estimation of direct runoff. Its validity was verified utilizing the observed rainfall (P)-runoff (Q) events from 36 US watersheds, four sub-catchments of the Godavari basin, and small agricultural plots at Roorkee, India. The performance of the proposed model (M5) for runoff prediction was compared with the existing NRCS-CN (M1), Mishra and Singh (2002) (M2), Singh et al. (2015) (M3), and Verma et al. (2021) (M4) model using various performance indices. Using the CNs derived from observed events, model M5 was seen to have performed better than M1-M4 in terms of Nash Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and Percent Bias (PBIAS) for the data of US watersheds, and CN-P correlation improved as the coefficient of determination (R²) enhanced. Similarly, using the RS & GIS-based CNs on natural watersheds of the Godavari basin and considering AMC-I, the performance of M5 was again better than M1-M4 in terms of RMSE, Mean Bias Error (mBIAS), Mean Absolute Error (MAE), and Normalized-Nash Sutcliffe Efficiency (NNSE). Interestingly, there existed a significant (p < 0.05) relationship between the in-situ water content (w) measured for the experimental plots of Roorkee and the model input variable antecedent moisture (M), offering a physical touch to the conceptual model.     

On relationship between curve numbers and phi indices

The curve number and phi (φ)-index models each provide a simple one-parameter relationship between storm-event rainfall and runoff. It is shown that the curve number and φ-index models can both be used to segregate the rainfall hyetograph into initial abstraction, retention, and runoff amounts. However, the principal advantages of the φ-index model are that both rainfall distribution and duration can be explicitly taken into account in calculating runoff, and the φ index is more physically based than the curve number. The quantitative relationship between the curve number and the φ index is presented and validated with field measurements. Knowing the relationship between the curve number and the φ index is useful in that it facilitates using the extensive database of curve numbers in the more realistic φ-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.     

径流曲线数模型在湖南省山区小流域的优化与应用

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R²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。     

Field Applicability of the SCS-CN-Based Mishra–Singh General Model and its Variants

The general soil conservation service curve number (SCS-CN)-based Mishra and Singh (Mishra and Singh, 1999, J. Hydrologic. Eng. ASCE, 4(3), 257–264) model and its eight variants were investigated for their field applicability using a large set of rainfall-runoff events, derived from a number of U.S. watersheds varying in size from 0.3 to 30351.5 ha, grouped into five classes based on the rainfall magnitude. The analysis based on the goodness of fit criteria of root mean square error (RMSE) and error in computed and observed mean runoff revealed that the performance of the existing version of the SCS-CN method was significantly poorer than that of all the model variants on all the five data sets with rainfall 38.1 mm. The existing version showed a consistently improved performance on the data with increasing rainfall amount, but greater than 38.1 mm. The one-parameter modified SCS-CN method (a = 0.5 and = a median value) performed significantly better than the existing one on all the data sets, but far better on rainfall data less than 2 inches. Finally, the former with = 0 was recommended for routine field applications to any data set.     

Development of a GIS Interface for Estimation of Runoff from Watersheds

Development of accurate surface runoff estimation techniques from ungauged watersheds is relevant in Indian condition due to the non-availability of hydrologic gauging stations in majority of watersheds. Besides this, the high budgetary requirements for installation of gauging stations are another limiting factor in India, which leads to the use of surface runoff estimation techniques for ungauged watersheds. Natural Resources Conservation Services Curve Number (NRCS-CN) method is one of the most widely used methods for quick and accurate estimation of surface runoff from ungauged watershed. Also, the coupling of NRCS-CN techniques with the advanced Geographic Information System (GIS) capabilities automates the process of runoff prediction in timely and efficient manner. Keeping view of this, a GIS interface was developed using the in-built macro programming language, Visual Basic for Applications (VBA) of ArcGIS® tool to estimate the surface runoff by adopting NRCS-CN technique and its three modifications. The developed interface named as Interface for Surface Runoff Estimation using Curve Number techniques (ISRE-CN), was validated using the recorded data for the periods from 1993 to 2001 of a gauged watershed, Banha in the Upper Damodar Valley in Jharkhand, India. The observed runoff depths for different rainfall events in this study watershed was compared with the predicted values of NRCS-CN methods and its three modifications using statistical significance tests. It was revealed that using all the rainfall data for different AMC conditions, the modified CN I performed the best [R ² (coefficient of determination)?=?0.92; E (model efficiency)?=?0.89) followed by modified CN III method (R ²?=?0.88; E?=?0.87), while the modified CN II (R ²?=?0.42; E?=?0.36) failed to predict accurately the surface runoff from Banha watershed. Moreover, under AMC based estimations, the modified CN I method also performed best ( R ²?=?0.95; E?=?0.95) for AMC II condition, while the modified CN II performed the worst in all the AMC conditions. However, the developed Interface in ArcGIS® needs to be tested in other watershed systems for wider applicability of the modified CN methods.     

Modeling runoff from an agricultural watershed of western catchment of Chilika lake through ArcSWAT

Chilika lake is the biggest lagoon in the Indian Eastern coast and is a source of livelihood for peoples of the coastal region surrounding it mainly through fisheries. However, the deposition of sediments in the lake carried through runoff water from its drainage basins may alter this wetland ecosystem in future. Implementation of appropriate soil water conservation measures may reduce the sediment load in runoff water and thus may protect this lagoon ecosystem. Keeping in view these concerns, runoff water from a selected watershed of western catchment of Chilika lagoon was modeled through ArcSWAT with a purpose to estimate future runoff potential from western catchment. Effective hydraulic conductivity of main channel, base flow alpha factor, curve number corresponding to antecedent moisture content II, and roughness coefficient of main channel were found most sensitive parameters in decreasing order. Nash–Sutcliffe coefficient of predicted monthly runoff was 0.72 and 0.88 during calibration and validation period, respectively whereas root mean squared error of predicted monthly runoff was 54.5 and 66.1 mm, respectively. Modeling results indicated that about 60% of rainfall is partitioned to runoff water, which carry significant amount of sediment load and contributes to Chilika lake.     

Estimation of Width and Depth of the Wetted Soil Volume Under a Surface Emitter,Considering Root Water-Uptake and Evaporation

A cylindrical flow model that describes local infiltration from a surface point source, by incorporating evaporation and water extraction by roots, was used to obtain numerical results that were the base for the development and testing of an empirical method for determining the surface and vertical components of the wetting front. The implementation of the mathematical model took place against two of the twelve USDA soil classes, using three water application rates for each one. The empirical methodology consisted of two simple, time dependent empirical relationships: a power law for the stage of the infiltration, which was applied in both directions and a polynomial for the stage after the end of the irrigation, applied only for the vertical component, to account for percolation losses. The statistical criteria used for the evaluation of the method showed good agreement between the numerical results and the values calculated by the empirical relationships. Based on the limited availability of necessary experimental data for detailed analysis of multidimensional transient infiltration, the introduction of such an empirical model, as a design tool for trickle irrigation systems, may contribute to the selection of the optimum application rate and lateral spacing.     

Application of GIS-based SCS-CN method in West Bank catchments,Palestine

Among the most basic challenges of hydrology are the prediction and quantification of catchment surface runoff.The runoff curve number(CN)is a key factor in determining runoff in the SCS(Soil Conservation Service)based hydrologic modeling method.The traditional SCS-CN method for calculating the composite curve number is very tedious and consumes a major portion of the hydrologic modeling time.Therefore,geographic information systems(GIS)are now being used in combination with the SCS-CN method.This paper assesses the modeling of flow in West Bank catchments using the GIS-based SCS-CN method.The West Bank,Palestine,is characterized as an arid to semi-arid region with annual rainfall depths ranging between 100 mm in the vicinity of the Jordan River to 700 mm in the mountains extending across the central parts of the region.The estimated composite curve number for the entire West Bank is about 50 assuming dry conditions.This paper clearly demonstrates that the integration of GIS with the SCS-CN method provides a powerful tool for estimating runoff volumes in West Bank catchments,representing arid to semi-arid catchments of Palestine.     

西林县雨水情防汛服务平台设计概述

介绍了西林县河流及雨、水情遥测站的分布情况,分析了雨水情防汛服务平台建设的背景,论述了平台的结构、通信组网方式、后台数据库及服务平台的主要功能。     

雨水花园设计方法探析

雨水花园是一种有效的雨水自然净化与生物滞留处置技术。对目前国外雨水花园常用的三种设计方法进行了对比和分析,包括:基于达西定律的渗滤法、蓄水层有效容积法和基于汇水面积的比例估算法。根据我国多数城市雨水花园的建造特点,提出了一种基于水量平衡分析的设计方法,为雨水花园的设计提供参考。     

Comparison of potential water supply and demand in Taiwan

The authors estimated the potential water supply in Taiwan based on hydrologic and water resource data sets pertaining to 233 rainfall stations, 145 stage stations and 109 reservoirs. The comparison between potential water supply estimates and predicted water demand indicated a slight water shortage, even though Taiwan normally receives a large amount of rainfall. This predicted water shortage likely occurred due to the uneven distribution of rainfall in Taiwan. Taken together, the results of this study demonstrate the importance of conservation of forests and paddy fields for the maintenance of base flow and effective management of reservoirs in Taiwan.     

城市雨水径流量计算方法--修正RRL法

阐述了一种城市雨水径流量的计算方法--修正RRL法的原理和方法,并模拟实际的降雨过程,预测结果与实际观测值接近,从而验证了该计算方法的准确性,为预测城市雨水径流量提供了一种有效的计算方法.     

Improvement of LCM model and determination of model parameters at watershed scale for flood events in Hongde Basin of China

Considering the fact that the original two-parameter LCM model can only be used to investigate rainfall losses during the runoff period because the initial abstraction is not included, the LCM model was redefined as a three-parameter model, including the initial abstraction coefficient λ, the initial abstraction I_a, and the rainfall loss coefficient R. The improved LCM model is superior to the original two-parameter model, which only includes r and R, where r is the initial rainfall loss index and can be calculated with λ using the Soil Conservation Service curve number(SCS-CN) method, with r=(1+λ). The trial method was used to determine the parameter values of the improved LCM model at the watershed scale for 15 flood events in the Hongde Basin in China. The results show that larger r values are associated with smaller R values, and the parameter R ranges widely from 0.5 to 2.0. In order to improve the practicability of the LCM model, r = 0.833 with λ= 0.2 is reasonable for simplifying calculation. When the LCM model is applied to arid and semi-arid regions, rainfall without yielding runoff should be deducted from the total rainfall for more accurate estimation of rainfall-runoff.     

宝鸡市雨水径流岸边渗滤系统设计与应用

城市雨水径流污染对城市河湖水体污染的贡献越来越受到关注.针对城市雨水径流,采用岸边砂渗滤系统处理,进行了工程设计和建设,建成"宝鸡市金渭湖雨水岸边渗滤系统示范工程".运行结果表明,渗滤池对水中有机物和悬浮物的去除率达80%以上.该工程将城市雨水管网、集蓄、处理及排放连为有机整体,为解决雨水径流污染城市河湖水体提供示范.     

城市雨水径流生态处理研究现状与进展

从城市雨水径流产生的问题出发,分析对城市雨水径流进行生态处理的必要性。对包括植被缓冲带、植被浅沟、生物滞留系统、滞留塘和人工湿地等在内的多项雨水径流管理与利用生态技术的优缺点、净化机理、适用条件等进行了综合比较。并对我国城市雨水径流生态处理技术的应用前景进行了展望,为生态城市建设和城市水环境改善提供借鉴。     

水击波数值模拟中高分辨率TVD格式优选

TVD方法特别适合数值模拟双曲型偏微分方程间断波问题,选用4种典型的TVD格式应用于水击方程的数值模拟。通过水击实例计算,将数值结果与理论解比较,揭示4种不同构造形式的TVD格式在捕捉水击波方面耗散性和压制性数值性能的差异,且TVD格式均优于常规的差分方法;改变计算库朗数条件下的计算结果表明:Harten修正通量TVD格式、TVD-MC格式以及全离散TVD格式在大范围库朗数条件下计算稳定性较差,优选Sweby反扩散TVD格式模拟水击,其计算稳定性良好,精度较高。     

面向EMD分解的径流分量重构方法对比研究

水文序列非平稳与非线性的复杂变化导致水文序列中长期预测的准确性备受质疑。"分解-预测-重构"模式作为一种新的有效的预测思路近年来备受业界和学者关注。但受到高频分量预测误差大、趋势走向不确定等问题困扰,这种模式在发展过程中仍有诸多需要改进的地方。其中,径流分量的重构方法是控制高频分量误差,提高整体预测精度的关键性措施,其优劣对预测效果实现有着重要的意义。基于经验模态分解(EMD)和自回归模型(AR)建立"分解-预测"耦合模型,结合粒子群优化(PSO)算法,提出PSO重构系数优化法和高频分量剔除+重构系数优化法两种重构方法,结合前人提出的高频分量剔除法,以陕北丁家沟站、关中华县站、陕南白河站为算例,对不同重构方法的效果进行对比研究。研究结果表明:基于高频分量剔除法、PSO重构系数优化法、高频分量剔除+重构系数优化法三种重构方法的预测效果均较好,五项误差评价指标均优于标准重构法,三种重构方法均可不同程度地提高预测精度。对比研究发现:高频分量剔除法在重构过程中剔除了最不稳定且最难预测的高频分量,提高了预测精度,但提升效果有限;PSO重构系数优化法对所有径流分量赋予优化重构系数并重构,可最大程度地实现分量间的平差,有效提高了预测精度;高频分量剔除+重构系数优化法综合上述两种方法的优势,取得了比其他方法更好的预测效果。