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Ensemble data-driven rainfall-runoff modeling using multi-source satellite and gauge rainfall data input fusion
Earth Science Informatics ( IF 2.8 ) Pub Date : 2021-04-29 , DOI: 10.1007/s12145-021-00615-4
Vahid Nourani , Hüseyin Gökçekuş , Tagesse Gichamo

Feed Forward Neural Network (FFNN), Adaptive Neuro-fuzzy Inference System (ANFIS), and Support Vector Regression (SVR) were applied for rainfall-runoff modeling of the Gilgel Abay catchment, Blue Nile basin, Ethiopia. Daily precipitations from satellite sources and rain gauge stations and outlet discharge were used. The dominant inputs were selected by non-linear sensitivity analysis. The study was conducted in two stages. First, single models for each data source with input fusion were trained. Second, ensemble runoff modeling using rainfall data fusion from only satellite products (strategy 1) and satellite and gauge (strategy 2) was conducted by Simple Average (SA), Weighted Average (WA), and Neural Network Ensemble (NNE) methods. NNE method using input fusion of strategy 2 improved performance of the best single satellite model up to 14.5% and a single gauge model up to 8% in the validation. Strategy 2 input data fusion ensemble rainfall-runoff modeling indicated substantial improvement over satellite data-based runoff modeling. This could be due to the bias correction ability of gauge rainfall over satellite rainfall products. Overall, results showed that ensemble modeling of input fusion from multiple source satellite rainfall products is a promising option for accurate modeling of the rainfall-runoff process for ungagged or sparsely gauged catchments.



中文翻译:

使用多源卫星和标量降雨数据输入融合,进行数据驱动的降雨径流建模的综合

前馈神经网络(FFNN),自适应神经模糊推理系统(ANFIS)和支持向量回归(SVR)用于埃塞俄比亚青尼罗河盆地吉尔吉尔阿贝集水区的降雨径流模拟。使用了来自卫星源和雨量计站的日降水量以及出口流量。通过非线性灵敏度分析选择主要输入。该研究分两个阶段进行。首先,对具有输入融合的每个数据源的单个模型进行了训练。其次,通过简单平均(SA),加权平均(WA)和神经网络集成(NNE)方法,仅使用卫星产品(策略1)和卫星及轨距(策略2)的降雨数据融合进行整体径流建模。使用策略2的输入融合的NNE方法将最佳单颗卫星模型的性能提高了14个。验证中使用了5%的单轨距模型,最高可达8%。策略2的输入数据融合集合降雨径流模型表明,与基于卫星数据的径流模型相比,有了很大的改进。这可能是由于标准降水量对卫星降水量产品的偏差校正能力所致。总体而言,结果表明,对无源或稀疏集水区的降雨径流过程进行精确建模,来自多源卫星降雨产品的输入融合的集成建模是一个有前途的选择。

更新日期:2021-04-29
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