Abstract Understanding flow regime dynamics is important for the management and conservation of river systems and their related ecosystems under current and future pressures like climate and land use change. For this reason, the accuracy and detail with which hydrological models are able to replicate streamflow and other spatially distributed processes is critical for global and regional water management programs. One of the most critical factors for model performance is the spatial and temporal representation of precipitation data, a procedure known as regionalisation. It is therefore imperative to evaluate the sensitivity of models to data from different stations in order to identify locations that exert the strongest control on simulated streamflow. In this study, a spatially distributed rainfall/runoff model, the J2000, calibrated under near natural river flow conditions, was used to analyse the overall precipitation station impact on simulated streamflow and its flow components. For this purpose, different analysis methods including Regional Sensitivity Analysis (RSA) were used. The study was applied to the Berg River catchment, a water stressed region in the Western Cape, South Africa that was recently affected by serious drought conditions. The results show that during peak flows precipitation stations in the headwater part of the basin had the largest systematic impact, often controlling the data input for only a small proportion of the overall spatial extent of the model, but still having the largest impact on the overall modelled streamflow. In contrast, precipitation stations in lowland areas showed to be more important during low-flow periods, although they often control the data input for a larger part of the modelled catchment. The study highlights the importance of good overall data coverage for improved low-flow simulations, as well as identification of critical areas in regions responsible for peak runoff generation processes. The inclusion of systematic station weights has the potential to improve the ecohydrological representation of rainfall/runoff models in data scarce regions, as well as precipitation regionalisation approaches. The results are indicative of known microclimatic variability in semi-arid Southern Africa, highlighting the significance of catchment heterogeneity and areas of dominant sub-basins for overall runoff generation.

中文翻译：

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降水数据密度和持续时间对模拟流动动力学的影响以及对南部非洲半干旱集水区生态水文建模的影响

摘要 了解流态动态对于在气候和土地利用变化等当前和未来压力下管理和保护河流系统及其相关生态系统具有重要意义。出于这个原因，水文模型能够复制水流和其他空间分布过程的准确性和细节对于全球和区域水资源管理计划至关重要。模型性能的最关键因素之一是降水数据的空间和时间表示，这一过程称为区域化。因此，必须评估模型对来自不同站点的数据的敏感性，以确定对模拟流量施加最强控制的位置。在这项研究中，空间分布的降雨/径流模型 J2000，在接近自然河流流量条件下校准，用于分析整体降水站对模拟流量及其流量分量的影响。为此，使用了不同的分析方法，包括区域敏感性分析 (RSA)。该研究应用于贝格河集水区，这是南非西开普省的一个缺水地区，最近受到严重干旱条件的影响。结果表明，流域上游部分的高峰流量降水站系统影响最大，往往控制数据输入仅占模型整体空间范围的一小部分，但仍对整体影响最大。建模的流。相比之下，低地地区的降水站在低流量时期显得更为重要，尽管他们经常控制建模流域的大部分数据输入。该研究强调了良好的整体数据覆盖对于改进低流量模拟以及确定负责峰值径流生成过程的区域的关键区域的重要性。包含系统站权重有可能改善数据稀缺地区降雨/径流模型的生态水文表征，以及降水区域化方法。结果表明了半干旱南部非洲已知的小气候变化，突出了集水区异质性和主要子流域面积对整体径流生成的重要性。该研究强调了良好的整体数据覆盖对于改进低流量模拟以及确定负责峰值径流生成过程的区域的关键区域的重要性。包含系统站权重有可能改善数据稀缺地区降雨/径流模型的生态水文表征，以及降水区域化方法。结果表明了半干旱南部非洲已知的小气候变化，突出了集水区异质性和主要子流域面积对整体径流生成的重要性。该研究强调了良好的整体数据覆盖对于改进低流量模拟以及确定负责峰值径流生成过程的区域的关键区域的重要性。包含系统站权重有可能改善数据稀缺地区降雨/径流模型的生态水文表征，以及降水区域化方法。结果表明了半干旱南部非洲已知的小气候变化，突出了集水区异质性和主要子流域面积对整体径流生成的重要性。包含系统站权重有可能改善数据稀缺地区降雨/径流模型的生态水文表征，以及降水区域化方法。结果表明了半干旱南部非洲已知的小气候变化，突出了集水区异质性和主要子流域面积对整体径流生成的重要性。包含系统站权重有可能改善数据稀缺地区降雨/径流模型的生态水文表征，以及降水区域化方法。结果表明了半干旱南部非洲已知的小气候变化，突出了集水区异质性和主要子流域面积对整体径流生成的重要性。