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Many of the existing stream–aquifer interaction models available in the literature are very complex with limited applicability in semi‐gauged and ungauged catchments. In this study, to estimate the influent and effluent subsurface water fluxes under limited geo‐hydrometeorological data availability conditions, a simple stream–aquifer interaction model, namely, the variable parameter McCarthy–Muskingum (VPMM) hillslope‐storage Boussinesq (hsB) model, has been developed. This novel model couples the VPMM streamflow transport with the hsB groundwater flow transport modules in online mode. In this integrated model, the surface water–groundwater flux exchange process is modelled by the Darcian approach with the variable hydraulic heads between the river stage and groundwater table accounting for the rainfall forcing. Considering the exchange fluxes in the hyporheic zone and lateral overland flow contribution, this approach is field tested in a typical 48‐km stretch of the Brahmani River in eastern India to simulate the streamflow and its depth with the minimum Nash–Sutcliffe efficiency of 94% and 88%; the maximum root mean square error of 134 m3/s and 0.35 m; and the minimum index of agreement of 98% and 97%, respectively. This modelling approach could be very well utilized in data‐scarce world‐river basins to estimate the stream–aquifer exchange flux due to rainfall forcings. 相似文献
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GRAPES NOAH-LSM陆面模式水文过程的改进及试验研究 总被引:3,自引:1,他引:2
土壤含水量的计算影响着陆面过程的能量平衡和水量平衡,是陆面模式的核心计算要素之一。目前,GRAPES_Meso模式采用的NOAH-LSM(Noah-Land Surface Model)陆面模式既不能有效地表达径流产源面积的变动情况,也不能完整描述水文循环过程。本次试验针对以上问题对其进行了改进:(1)加入蓄水容量曲线,考虑网格内产流面积的变化及土壤含水量的不均匀性;(2)加入汇流模式,以考虑水平二维水分再分配,提高模式对径流和流量模拟能力。选取2008年8月至9月降水进行模拟试验,研究陆面水循环过程对近地面气象要素的影响。结果表明:改进后的模式模拟土壤湿度、2 m温度等近地面气象要素更接近观测值,并最终对降水量以及降水落区也产生了一定的影响。 相似文献
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基于栅格数据的流域降雨径流模型 总被引:30,自引:0,他引:30
本文在研究降雨时空分布不均匀与下垫面自然地理参数空间分布不均匀,对降雨径流过程影响的基础上,提出了一种在地理信息系统支持下的动态分布式降雨径流流域模型,实现了基于栅格的坡面产汇流与河道汇流的数值模拟,能够获得流域上任意模拟时刻任意栅格的径流量。模型视栅格为水文一致性单元,水文参数在栅格内一致,在相邻栅格间变化,采用Holtan模型计算下渗率,水量平衡方程和线性水库的马斯京根法进行栅格产汇流演算,模 相似文献
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Confidence interval of real‐time forecast stages provided by the STAFOM‐RCM model: the case study of the Tiber River (Italy) 下载免费PDF全文
Silvia Barbetta Tommaso Moramarco Luca Brocca Marco Franchini Florisa Melone 《水文研究》2014,28(3):729-743
This study proposes a statistically based procedure to quantify the confidence interval (CI) to be associated to the stages forecast by a simple model called STAge FOrecasting Model‐Rating Curve Model (STAFOM‐RCM). This model can be used for single river reaches characterized by different intermediate drainage areas and mean wave travel times when real‐time stage records, cross section surveys and rating curves are available at both ends. The model requires, at each time of forecast, an estimate of the lateral contribution qfor between the two sections delimiting the reach. The CI of the stage is provided by analyzing the statistical properties of model output in terms of lateral flow, and it is derived from the CI of the lateral contribution qfor which, in turn, is set up by associating to each qfor the qopt which allows STAFOM‐RCM to reproduce the exact observed stage. From an operative point of view, the qfor values are ranked in order of magnitude and subdivided in classes where the qopt values can be represented through normal distributions of proper mean and variance from which an interval of selected confidence level for qfor is computed and transferred to the stage. Three river reaches of the Tiber river, in central Italy, are used as case study. A sensitivity analysis is also performed in order to identify the minimum calibration set of flood events. The CIs obtained are consistent with the level of confidence selected and have practical utility. An interesting aspect is that different CI widths can be produced for the same forecast stage since they depend on the estimate of qfor made at the time of forecast. Overall, the proposed procedure for CI estimate is simple and can be conveniently adapted for other forecasting models provided that they have physically based parameters which need to be updated during the forecast. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
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Two models, one linear and one non‐linear, were employed for the prediction of flow discharge hydrographs at sites receiving significant lateral inflow. The linear model is based on a rating curve and permits a quick estimation of flow at a downstream site. The non‐linear model is based on a multilayer feed‐forward back propagation (FFBP) artificial neural network (ANN) and uses flow‐stage data measured at the upstream and downstream stations. ANN predicted the real‐time storm hydrographs satisfactorily and better than did the linear model. The results of sensitivity analysis indicated that when the lateral inflow contribution to the channel reach was insignificant, ANN, using only the flow‐stage data at the upstream station, satisfactorily predicted the hydrograph at the downstream station. The prediction error of ANN increases exponentially with the difference between the peak discharge used in training and that used in testing. ANN was also employed for flood forecasting and was compared with the modified Muskingum model (MMM). For a 4‐h lead time, MMM forecasts the floods reliably but could not be applied to reaches for lead times greater than the wave travel time. Although ANN and MMM had comparable performances for an 8‐h lead time, ANN is capable of forecasting floods with lead times longer than the wave travel time. Copyright © 2007 John Wiley & Sons, Ltd. 相似文献
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《国际泥沙研究》2016,(2):139-148
Applications of sediment transport and water flow characteristics based sediment transport simulation models for a river system are presented in this study. An existing water–sediment model and a new sediment–water model are used to formulate the simulation models representing water and sediment movement in a river system. The sediment–water model parameters account for water flow characteristics embodying sediment transport properties of a section. The models are revised formulations of the multiple water inflows model describing water movement through a river system as given by the Muskingum principle. The models are applied to a river system in Mississippi River basin to estimate downstream sediment concentration, sediment discharge, and water discharge. River system and the river section parameters are estimated using a revised and the original multiple water inflows models by applying the genetic algorithm. The models estimate downstream sediment transport rates on the basis of upstream sediment/water flow rates to a system. Model performance is evaluated by using standard statistical criteria;downstream water discharge resulting from the original multiple water inflows model using the estimated river system parameters indicate that the revised models satisfactorily describe water movement through a river system. Results obtained in the study demonstrate the applicability of the sediment transport and water flow characteristics-based simulation models in predicting downstream sediment transport and water flow rates in a river system. 相似文献
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根据水力学原理和洪水波运动理论,通过对Muskingum法的关键参数X与特征河长、扩散波动力方程和运动波数值扩散之间关系的分析,给出了X更为全面的物理解释;证明了Muskin gum法槽蓄方程是扩散波动力方程近似的表达;指出了Muskingum法演算公式在一定条件下是扩散波方程的二阶精度解。讨论了Muskingum法的使用条件和分段连续演算的必要性;应用Z 变换方法导出了Muskingum法的分段连续演算的汇流系数公式。 相似文献