Regionalization approach is adopted to test the credibility of a newly developed, large‐scale, conceptual hydrological model, namely, satellite‐based hydrological model (SHM), under data‐scarce conditions. SHM has a modular structure. There are five modules: surface water module (SW), which uses natural resources conservation service‐curve number and Hargreaves equation; forest module (F), which uses water balance and subsurface dynamics; snow module (S), which uses temperature index and radiation‐temperature index algorithms; groundwater module, which considers contributions from SW, F, and S modules and uses water level variation process; and routing module, which uses modified spatial distributed direct hydrograph model. Four neighboring basins of varying size are selected to form the reference (Subarnarekha) and the test (Brahmani, Baitarani, and Kangsabati) basins. The similarity index and hierarchical agglomerative cluster analysis show that Brahmani is the most homogeneous basin with respect to the Subarnarekha basin. The model simulations are run at 1 km resolution. The values of statistical indices Nash‐Sutcliffe efficiency, coefficient of determination, and percent BIAS, are found to be 0.82%, 0.84%, and 13.99%, respectively, during calibration (1993–1999; 1993 as a warm‐up period), and 0.61%, 0.63%, and 14.13%, respectively, during validation (2000–2004) at Jenapur gauging station of the Brahmani river basin. Subsequently, the calibrated parameters are transferred in the model setup of the Subarnarekha basin for simulating streamflow over a randomly chosen period 1998–2000. The results, obtained with both Brahmani and Subarnarekha parameters, confirm that the model performs well with the regionalized parameters, and is suitable for hydrologically homogeneous ungauged basins. The results show that the newly developed model may be used for the water balance simulations in ungauged or scantily gauged basins, leading to the development of water resources plans for better utilization of this vital resource. The results from the sensitivity analysis and uncertainty analysis show that the nonsensitive parameters have a negligible impact on the model results. Further study, however, may be needed to evaluate the model performance and to establish its universal credibility.

中文翻译：

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新开发的大规模概念性水文模型在模拟水流中的应用，以在数据稀缺情况下进行可信度测试

在数据稀缺的情况下，采用区域化方法来检验新开发的大规模概念性水文模型（即卫星水文模型（SHM））的可信度。SHM具有模块化结构。共有五个模块：地表水模块（SW），它使用自然资源保护服务曲线数和Hargreaves方程；森林模块（F），它使用水平衡和地下动力；降雪模块（S），使用温度指数和辐射温度指数算法；地下水模块，考虑了SW，F和S模块的贡献，并使用水位变化过程；路由模块，使用改进的空间分布式直接水文模型。选择了四个不同大小的相邻盆地，以形成参考（Subarnarekha）和测试（Brahmani，Baitarani，和Kangsabati）盆地。相似度指数和层次聚类分析表明，布拉马马尼盆地是Subarnarekha盆地中最均匀的盆地。模型仿真以1 km的分辨率运行。在校准期间（1993年至1999年； 1993年为暖机期），统计指标Nash-Sutcliffe效率，测定系数和BIAS百分比分别为0.82％，0.84％和13.99％，在Brahmani流域的Jenapur监测站（2000-2004年）进行验证期间（分别为0.61％，0.63％和14.13％）。随后，将校准后的参数转移到Subarnarekha盆地的模型设置中，以模拟随机选择的1998-2000年期间的水流。使用Brahmani和Subarnarekha参数获得的结果，确认该模型在区域化参数下表现良好，并且适用于水文均质的非灌流盆地。结果表明，新开发的模型可用于无赋存或稀疏测量盆地的水平衡模拟，从而导致制定水资源计划以更好地利用这一重要资源。敏感性分析和不确定性分析的结果表明，非敏感性参数对模型结果的影响可忽略不计。但是，可能需要进一步研究以评估模型的性能并建立其通用信誉。结果表明，新开发的模型可用于无赋存或稀疏测量盆地的水平衡模拟，从而导致制定水资源计划以更好地利用这一重要资源。敏感性分析和不确定性分析的结果表明，非敏感性参数对模型结果的影响可忽略不计。但是，可能需要进一步研究以评估模型的性能并建立其通用信誉。结果表明，新开发的模型可用于无赋存或稀疏测量盆地的水平衡模拟，从而导致制定水资源计划以更好地利用这一重要资源。敏感性分析和不确定性分析的结果表明，非敏感性参数对模型结果的影响可忽略不计。但是，可能需要进一步研究以评估模型的性能并建立其通用信誉。