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《水文科学杂志》2013,58(4):685-695
Abstract Employing 1-, 2-, 4-, 6-, 12- and 24-hourly data sets for two catchments (10.6 and 298 km2) in Wales, the calibrated parameters of a unit hydrograph-based model are shown to change substantially over that range of data time steps. For the smaller basin, each model parameter reaches, or approaches, a stable value as the data time step decreases, providing a straightforward method of estimating time-step independent model parameter values. For the larger basin, the model parameters also reach, or approach, stable values using hourly data, but, for reasons given in the paper, interpretation of the results is more difficult. Model parameter sensitivity analyses are presented that give insights into the relative precision on the parameters for both catchments. The paper discusses the importance of accounting for model parameter data time-step dependency in pursuit of a reduction in the uncertainty associated with estimates of flow in ungauged basins, and suggests that further work along these lines be undertaken using different catchments and models. 相似文献
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由于冰雪的存在及缺乏地面观测站点资料,高寒地区的水文模拟研究一直面临很大的困难。遥感数据能够提供大范围时空尺度上的地面信息对无资料地区有很大帮助。MODIS数据具有较高的时空分辨率深受人们关注。本文以长江上游泥曲流域为例,探求将MODIS遥感数据与地面气温数据相结合对新安江模型径流模拟的帮助,方法步骤如下:(1)建立MODIS雪覆盖面积与流域周围站气温关系,获取气温阈值;(2)依据气温阈值判别降水形式并计算融雪水当量;(3)将雨雪分离后的降水信息输入新安江模型模拟径流,并与新安江模拟结果(未考虑雨雪分离)和实测径流进行比较。研究结果显示改进方案(考虑雨雪分离)模拟效果更好,将有助于提高新安江模型在高寒无资料地区的径流模拟精度,为高寒无资料地区水资源管理及生态需水研究提供帮助。 相似文献
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Knowledge of the effective impervious area (EIA) or the degree to which impervious surfaces are hydraulically connected to the drainage system is useful for improving hydrological and environmental models and assessing the effectiveness of green stormwater infrastructure in urban watersheds. The goal of this research is to develop a method to estimate EIA fraction in urban watersheds using readily available data. Since EIA is dependent on rainfall–runoff response and cannot be solely determined based on the physical characteristics of a watershed, the EIA is linked with the asymptotic curve number (CN), a watershed index that represents runoff characteristics. In order for the method to be applicable to ungauged watersheds, the asymptotic CN is predicted using land cover and soil data from 35 urban catchments in Minnesota and Texas, USA. Similar data from 11 other urban catchments in Wisconsin and Texas, USA, are used to validate the results. A set of runoff depth versus EIA fraction curves is also developed to assess the impact of EIA reduction on discharge from an urban watershed in land-use planning studies. 相似文献
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Streamflow prediction in ungauged basins is necessary to support water resources management decisions. Herein we refine and evaluate the Streamflow Prediction under Extreme Data-scarcity (SPED) model, a framework designed for streamflow prediction within regions of sparse hydrometeorological observation. With the SPED framework, inclusion of soft data directs optimization to balance runoff efficiency with the selection of hydrologically representative parameters. Here SPED is tested in catchments around the world, including four well-gauged catchments, by mimicking data-scarcity and comparing against data-intensive approaches. By differentiating equifinal models, SPED succeeds where traditional approaches are likely to fail: partially dissimilar reference/target catchments. For instance, in a pair of reference/target catchments with different base flow regimes, SPED outperforms a model calibrated only to maximize efficiency (NSE of 0.54 versus 0.08). SPED performs consistently (NSE range: 0.54–0.74) across the diverse climatological and physiographic settings tested and proves comparable to state-of-the-science methods that use robust data networks. 相似文献
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近年来,无资料或资料缺乏地区汇流计算成为水文研究热点。基于地形参数的地貌瞬时单位线(GIUH)方法凭借其对历史降雨径流实测资料的不依赖性,已然成为径流模拟研究中被普遍采用且效果较好的方法之一。为探讨江苏省无资料山丘区的径流模拟方法,选取具有典型地形地貌特征的镇江通胜洛阳河小流域展开研究。根据地貌特征值等数据提取出该流域的地貌单位线,采用地貌单位线计算径流过程,利用2016、2017年汛期实测的4场洪水进行方法验证,将计算径流与实测数据进行对比分析,结果表明:基于地貌特征的地貌单位线法在该流域洪水模拟中具有较高精度,又因该流域于江苏省乃代表性区域,初步判定可将该方法推广至其他无资料山丘区流域。 相似文献
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Use of a parsimonious rainfall–run‐off model for predicting hydrological response in ungauged basins 
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下载免费PDF全文 A new parameter parsimonious rainfall–run‐off model, the Distance Distribution Dynamics (DDD) model, is used to simulate hydrological time series at ungauged sites in the Lygne basin in Norway. The model parameters were estimated as functions of catchment characteristics determined by geographical information system. The multiple regression equations relating catchment characteristics and model parameters were trained from 84 calibrated catchments located all over Norway, and all model parameters showed significant correlations with catchment characteristics. The significant correlation coefficients (with p‐value < 0.05) ranged from 0.22 to 0.55. The suitability of DDD for predictions in ungauged basins was tested for 17 catchments not used to estimate the multiple regression equations. For ten of the 17 catchments, deviations in Nash–Sutcliffe efficiency (NSE) criteria between the calibrated and regionalised model were less than 0.1, and for two calibrated catchments within the Lygne basin, the deviations were less than 0.08. The median NSE for the regionalized DDD for the 17 catchments for two time series was 0.66 and 0.72. Deviations in NSE between calibrated and regionalised models are well explained by the deviations between calibrated and regressed parameters describing spatial snow distribution and snowmelt respectively. The quality of the simulated run‐off series for the ungauged sites in the Lygne basin was assessed by comparing flow indices describing high, medium and low flow estimated from observed run‐off at the 17 catchments and for the simulated run‐off series. The indices estimated for the simulated series were generally well within the ranges defined by the 17 observed series. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
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A design hyetograph which represents the time distribution of design rainfall depth corresponding to a duration and a return period is essential in hydrologic design. However, for locations without observed data (ungauged sites), construction of design hyetographs is a difficult task because of the lack of data. Hence, an approach based on self‐organizing map (SOM) is proposed in this paper to construct design hyetographs at ungauged sites. SOM, which is a special kind of artificial neural networks (ANNs), is a powerful technique for extracting and visualizing salient features of data and for solving classification problems. The proposed approach is composed of three steps: classification, assignment and construction. First, the SOM‐based classification is performed to analyse gauged sites' design hyetographs. Second, based on the concept of indicator kriging, a method is developed to assign an ungauged site of interest to a certain cluster. Third, based on the spatial information, the clustering results, and the design hyetographs of gauged sites, the design hyetograph at the site of interest is constructed using the reciprocal‐distance‐squared method. An application is conducted to assess the advantages of the proposed approach over the conventional approaches. Moreover, cross‐validation tests are applied to evaluate the performance of the accuracy and the robustness of the proposed approach. The results confirm the improvement in performance by using the proposed approach instead of conventional approaches. The proposed approach is useful for constructing design hyetographs at ungauged sites. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
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Application of distributed hydrological models for predictions in ungauged basins: a method to quantify predictive uncertainty 下载免费PDF全文
下载免费PDF全文 Stream flow predictions in ungauged basins are one of the most challenging tasks in surface water hydrology because of nonavailability of data and system heterogeneity. This study proposes a method to quantify stream flow predictive uncertainty of distributed hydrologic models for ungauged basins. The method is based on the concepts of deriving probability distribution of model's sensitive parameters by using measured data from a gauged basin and transferring the distribution to hydrologically similar ungauged basins for stream flow predictions. A Monte Carlo simulation of the hydrologic model using sampled parameter sets with assumed probability distribution is conducted. The posterior probability distributions of the sensitive parameters are then computed using a Bayesian approach. In addition, preselected threshold values of likelihood measure of simulations are employed for sizing the parameter range, which helps reduce the predictive uncertainty. The proposed method is illustrated through two case studies using two hydrologically independent sub‐basins in the Cedar Creek watershed located in Texas, USA, using the Soil and Water Assessment Tool (SWAT) model. The probability distribution of the SWAT parameters is derived from the data from one of the sub‐basins and is applied for simulation in the other sub‐basin considered as pseudo‐ungauged. In order to assess the robustness of the method, the numerical exercise is repeated by reversing the gauged and pseudo‐ungauged basins. The results are subsequently compared with the measured stream flow from the sub‐basins. It is observed that the measured stream flow in the pseudo‐ungauged basin lies well within the estimated confidence band of predicted stream flow. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献