伽玛分布地貌瞬时单位线

本文以概念性元素“特征河长河段”的响应函数作为水质点传播时间的概率密度函数，建立了具有水动力学基础和伽玛分布地貌瞬时单位线模型，推导出了三级，四级和五级流域的地貌瞬时单位线，并对其性质作了分析，详细讨论了参数的约束条件和求解参数的方法，实例检验表明，模型结构合理，内罚函数法求解比较有效，模型拟合精度较高。     

逆高斯分布地貌瞬时单位线

本文假设水质点在河道状态传播时间的概率密度函数服从逆高斯分布，并根据地貌瞬时单位线理论建立了逆高斯分布地貌瞬时单位线模型。推导了三级流域的瞬时单位线，并对其性质作了分析。     

基于误差原理的瞬时单位线法参数敏感性研究

计算暴雨洪水的瞬时单位线法在我国应用较广,瞬时单位线法的地理参数、产汇流参数和暴雨参数等原始参数往往存在一定的误差,会通过误差传播使地面径流过程产生相应的误差.采用多元函数一阶泰勒公式展开瞬时单位线法基本方程,可得到各参数一阶代数精度的误差传播方程.结果表明:暴雨的相对误差传播具有一定的放大效应;流域面积的相对误差会导致地面径流过程等量的相对误差;下渗量的相对误差传播敏感性总体相对较小,局部仍有可能较大;线型参数n、K的加大,会导致地面径流峰值减小,上涨段更平瘦、回落段更丰满,并存在不显著的峰值发生时间后移趋势.     

基于Nash瞬时单位线法的渗透坡面汇流模拟

基于Nash瞬时单位线法,结合Horton土壤入渗经验模型,并考虑植被对降雨的截流作用,建立了渗透坡面汇流计算的数学模型。以矩形坡面为研究对象,基于其汇流时间-面积特性,推导建立了Nash瞬时单位线参数n、K的确定方法。其中参数n的值与坡面汇流时间-面积曲线指数相等,K的值与坡面汇流时间相等。应用本文建立的模型,对林地渗透坡面降雨径流进行计算,并与实测值进行比较。结果表明,计算值与实测值的变化趋势基本吻合,初步验证了本文方法的合理性。     

基于Nash 瞬时单位线法的渗透坡面汇流模拟

基于Nash瞬时单位线法,结合Horton土壤入渗经验模型,并考虑植被对降雨的截流作用,建立了渗透坡面汇流计算的数学模型。以矩形坡面为研究对象,基于其汇流时间-面积特性,结合等流时线法,推导建立了Nash瞬时单位线参数n、K的确定方法。其中,参数n的值为1.0,K的值与坡面汇流时间相等,相当于单一线性水库。应用本文建立的模型,对林地渗透坡面降雨径流进行计算,并与实测值进行比较。结果表明,计算值与实测值的变化趋势基本吻合,初步验证了本文方法的合理性。     

Evaluation of three unit hydrograph models to predict the surface runoff from a Canadian watershed

The predictability of unit hydrograph (UH) models that are based on the concepts of land morphology and isochrones to generate direct runoff hydrograph (DRH) were evaluated in this paper. The intention of this study was to evaluate the models for accurate runoff prediction from ungauged watershed using the ArcGIS^® tool. Three models such as exponential distributed geomorphologic instantaneous unit hydrograph (ED-GIUH) model, GIUH based Clark model, and spatially distributed unit hydrograph (SDUH) model, were used to generate the DRHs for the St. Esprit watershed, Quebec, Canada. Predictability of these models was evaluated by comparing the generated DRHs versus the observed DRH at the watershed outlet. The model input data, including natural drainage network and Horton's morphological parameters (e.g. isochrone and instantaneous unit hydrograph), were prepared using a watershed morphological estimation tool (WMET) on ArcGIS^® platform. The isochrone feature class was generated in ArcGIS^® using the time of concentration concepts for overland and channel flow and the instantaneous unit hydrograph was generated using the Clark's reservoir routing and S-hydrograph methods. An accounting procedure was used to estimate UH and DRHs from rainfall events of the watershed. The variable slope method and phi-index method were used for base flow separation and rainfall excess estimation, respectively. It was revealed that the ED-GIUH models performed better for prediction of DRHs for short duration (≤6 h) storm events more accurately (prediction error as low as 4.6–22.8%) for the study watershed, than the GIUH and SDUH models. Thus, facilitated by using ArcGIS^®, the ED-GIUH model could be used as a potential tool to predict DRHs for ungauged watersheds that have similar geomorphology as that of the St. Esprit watershed.     

Investigation of stage-discharge model performance for streamflow estimating: A case study of the Gono River,Japan

In water resource studies, long-term measurements of river streamflow are essential. They allow us to observe trends and natural cycles and are prerequisites for hydraulic and hydrology models. This paper presents a new application of the stage-discharge rating curve model introduced by Maghrebi et al. (2016) to estimate continuous streamflow along the Gono River, Japan. The proposed method, named single stage-discharge (SSD) method, needs only one observed data to estimate the continuous streamflow. However, other similar methods require more than one observational data to fit the curve. The results of the discharge estimation by the SSD are compared with the improved fluvial acoustic tomography system (FATS), conventional rating curve (RC), and flow-area rating curve (FARC). Some statistical indicators, such as the coefficient of determination (R²), root mean square error (RMSE), percent bias (PBAIS), mean absolute error (MAE), and Kling-Gupta efficiency (KGE), are used to assess the performance of the proposed model. ADCP data are used as a benchmark for comparing four studied models. As a result of the comparison, the SSD method outperformed of FATS method. Also, the three studied RC methods were highly accurate at estimating streamflow if all observed data were used in calibration. However, if the observed data in calibration was reduced, the SSD method by R² = 0.99, RMSE = 2.83 (m³/s), PBIAS = 0.715(%), MAE = 2.30 (m³/s), and KGE = 0.972 showed the best performance compared to other methods. It can be summarized that the SSD method is the feasible method in the data-scarce region and delivers a strong potential for streamflow estimation.