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首页> 外文期刊>Journal of Agrometeorology >Rainfall estimation using multiple linear regression based statistical downscaling for Piperiya watershed in Chhattisgarh
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Rainfall estimation using multiple linear regression based statistical downscaling for Piperiya watershed in Chhattisgarh

机译：贾蒂斯加尔邦基于Piperiya流域的基于多元线性回归的统计缩减的降雨估算

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摘要

Climatic variability and its behavior is a complex phenomenon that is directly associated with uncertainties. In the climate change study, particularly in hydrological aspects, it is necessary to identify the parameters (predictors) that are directly or indirectly associated with predictands. The forecasted results are directly associated with the selection of predictors. In the present study, the statistical downscaling model (SDSM) has been advocated to downscale the daily rainfall in Piperiya watershed of Chhattisgarh state. SDSM is based on multiple linear regression (MLR) technique. The daily rainfall data (1961-2001) of the Piperiya watershed in Chhattisgarh is considered as input (predictand) to the model. The model has been calibrated and validated on the basis of rainfall period of 1961-1990 and 1991-2001 respectively with large scale predictors of National Centre for Environmental Prediction (NCEP) reanalysis data. Finally, monthly rainfall is predicted on the basis of forecasted future daily rainfall for the periods of 2020s, 2050s and 2080s under the consideration of HadCM3 A2 and B2 emission scenarios.
机译：气候变异及其行为是一个复杂的现象，与不确定性直接相关。在气候变化研究中，特别是在水文方面，有必要确定与预测值直接或间接相关的参数（预测值）。预测结果与预测变量的选择直接相关。在本研究中，提倡使用统计缩减模型（SDSM）来缩减恰蒂斯加尔邦Piperiya流域的每日降雨量。 SDSM基于多重线性回归（MLR）技术。恰蒂斯加尔邦Piperiya流域的每日降雨数据（1961-2001年）被视为该模型的输入（预测）。该模型已分别在1961-1990年和1991-2001年的降雨期的基础上进行了校准和验证，并使用了国家环境预测中心（NCEP）再分析数据的大规模预测因子。最后，在考虑到HadCM3 A2和B2排放情景的情况下，根据2020s，2050s和2080s期间的未来未来每日降雨量预测月降雨量。

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