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Validation of catchment models for predicting land-use and climate change impacts. 3. Blind validation for internal and outlet responses

机译:验证流域模型以预测土地利用和气候变化影响。 3.内部和出口响应的盲确认

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The capability of the physically based, distributed SHETRAN catchment modelling system for predictive modelling of hypothetical future catchments is validated for the 0.94 km(2) Slapton Wood catchment in southwest England. A 'blind' procedure (without sight of measured response data) is used which accounts also for uncertainty in model parameter evaluation. Internal catchment conditions as well as the outlet discharge are considered, making the test perhaps the severest to which a model can be subjected. Data collection formed an integral part of the validation procedure and was designed specifically to satisfy the needs of the modelling component. The extensive dataset which was collected included rainfall, evapotranspiration, soil property data, channel geometry, phreatic surface elevation, soil water potential and stream discharge. Following a prescribed method, blind predictions were made of ten features of the phreatic surface, soil water potential and surface runoff responses. Output uncertainty bounds were determined as a function of uncertainty in the model parameter values. Subsequent comparison of the bounds with the measured data showed that eight of the ten predictions passed the specified success criteria, constituting a successful validation. Within reasonable uncertainty bounds, and on a spatially distributed basis, SHETRAN is shown able to represent the annual catchment water balance as well as important features of the event-scale response. The results are an encouraging demonstration of the fitness of such models for predictive modelling. (C) 2004 Elsevier B.V. All rights reserved. [References: 34]
机译:基于物理的分布式SHETRAN流域建模系统对假设的未来流域进行预测建模的能力已在英格兰西南部的0.94 km(2)Slapton Wood流域得到验证。使用“盲”程序(看不到所测得的响应数据),该程序还考虑了模型参数评估中的不确定性。考虑了内部集水条件以及出口排水情况,这使得该测试可能是模型所能经受的最严格的测试。数据收集是验证程序不可或缺的一部分,专门为满足建模组件的需求而设计。收集的广泛数据集包括降雨,蒸散量,土壤性质数据,河道几何形状,潜水表面标高,土壤水势和河流流量。按照规定的方法,对潜水面,土壤水势和地表径流响应的十个特征进行了盲目预测。确定输出不确定性界限作为模型参数值不确定性的函数。随后将边界与实测数据进行比较,显示十个预测中的八个通过了指定的成功标准,构成了成功的验证。在合理的不确定性范围内,并且在空间分布的基础上,SHETRAN显示出能够代表年度集水量平衡以及事件尺度响应的重要特征。结果令人鼓舞地证明了此类模型适用于预测建模。 (C)2004 Elsevier B.V.保留所有权利。 [参考:34]

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