Multi-source weighted-ensemble precipitation(MSWEP)is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution.While various studies have acknowledged its abilit...Multi-source weighted-ensemble precipitation(MSWEP)is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution.While various studies have acknowledged its ability to accurately estimate precipitation in terms of temporal dynamics,its performance regarding spatial pattern and extreme rainfall is overlooked.To fill this knowledge gap,the daily precipitation of two versions of MSWEP(MSWEP V2.1&V2.2)are compared with that of three representative satellite-and reanalysis-based products,namely the Tropical Rainfall Measuring Mission(TRMM 3B42 V7),the climate prediction center morphing technique satellite-gauge merged product(CMORPH BLD),and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts(ERA5).The comparison is made according to the dense daily rainfall observations from 539 rain gauges over the Huaihe River Basin in China during 2006–2015.The results show that MSWEP V2.1,MSWEP V2.2 and CMORPH BLD have better performance on temporal accuracy of precipitation estimation,followed by ERA5 and TRMM 3B42V7.MSWEPs yield the most even spatial distribution across the basin since it takes full advantage of the multi datasets.As the weighted-ensemble method is independently carried out on each grid in MSWEPs,the spatial distribution of local precipitation is changed by different source data,which results in that MSWEPs perform worse than CMORPH BLD in terms of the representation of precipitation spatial pattern.In addition,the capability of MSWEPs to describe the spatial structure in the rainy season is lower than that in the dry season.Strong precipitation(≥100 mm/d)events are better represented in TRMM 3B42 V7 products than in MSWEPs.Finally,based on the comparison results,we suggest to improve the merging algorithm of MSWEP by considering the precipitation spatial self-correlation and adjusting the merging weights based on the performance of the source datasets under different precipitation intensities.展开更多
Climate change and human activity can cause remarkable hydrological variation.Traits of hydrological series such as runoff before and after the change points could be significantly different,so the calculation of inst...Climate change and human activity can cause remarkable hydrological variation.Traits of hydrological series such as runoff before and after the change points could be significantly different,so the calculation of instream ecological water requirements(EWRs)is confronted with more challenges.Taking the Xitiaoxi River(XTXR)in the upper reach of the Taihu Lake Basin as an example,this paper investigates the calculation of EWRs using the range of variability approach(RVA)under changing environment.The change point diagnosis of the natural and observed runoff series are conducted for XTXR.Then,differences in the hydrological alternation indicators and instream EWRs processes obtained from various daily runoff series are compared.It was found that the natural and observed annual runoff series in XTXR from 1957 to 2018 both show significant variations,and the change points are in 2007 and 1999 respectively.If runoff data before the change points or all runoff data are used,the instream EWRs obtained from natural runoff are significantly lower than those obtained from the observed runoff.At the monthly time step,EWRs differences within a year mainly occurred from May to August.Also,calculation results of the instream EWRs are strongly related to the selected period of runoff series.The EWRs obtained using runoff series after the change points have rather acute fluctuation within a year.Therefore,when the RVA method is used under changing environment,the instream EWRs should be prudently determined by comparing different calculation results on the basis of river runoff restoration and variability analysis.To a certain extent,this paper enriches our understanding about the hydrological method for EWRs estimation,and proposes new ideas for future research on EWRs.展开更多
论文基于2003-2014年水文资料,采用长短期记忆神经网络(Long-Short Term Memory,LSTM),构建了汉江上游安康站日径流预测模型,评价了不同输入条件下日径流预测的精度。结果表明:当预见期为1 d时,在仅以安康站前期日径流量作为输入的条件...论文基于2003-2014年水文资料,采用长短期记忆神经网络(Long-Short Term Memory,LSTM),构建了汉江上游安康站日径流预测模型,评价了不同输入条件下日径流预测的精度。结果表明:当预见期为1 d时,在仅以安康站前期日径流量作为输入的条件下,LSTM模型在训练期和检验期的效率系数分别达到0.68和0.74;如再将流域前期面雨量和上游石泉站前期日径流量加入LSTM网络作为输入变量,安康站日径流量预测效果将更好,训练期和检验期的效率系数最高可达到0.83和0.84,均方根误差也有显著削减,且对主要洪峰流量的预测能力也有一定提高。此外,LSTM可以有效避免过拟合等问题,具有较好的泛化性能。但当预见期从1 d延长至2、3 d时,LSTM的预测精度显著降低。展开更多
基金National Key R&D Program of China,No.2021YFC3000104National Natural Science Foundation of China,No.52009081,No.51479118Special Funded Project for Basic Scientific Research Operation Expenses of the Central Public Welfare Scientific Research Institutes of China,No.Y519006。
文摘Multi-source weighted-ensemble precipitation(MSWEP)is one of the most popular merged global precipitation products with long-term spanning and high spatial resolution.While various studies have acknowledged its ability to accurately estimate precipitation in terms of temporal dynamics,its performance regarding spatial pattern and extreme rainfall is overlooked.To fill this knowledge gap,the daily precipitation of two versions of MSWEP(MSWEP V2.1&V2.2)are compared with that of three representative satellite-and reanalysis-based products,namely the Tropical Rainfall Measuring Mission(TRMM 3B42 V7),the climate prediction center morphing technique satellite-gauge merged product(CMORPH BLD),and the fifth-generation reanalysis product of the European Centre for Medium Range Weather Forecasts(ERA5).The comparison is made according to the dense daily rainfall observations from 539 rain gauges over the Huaihe River Basin in China during 2006–2015.The results show that MSWEP V2.1,MSWEP V2.2 and CMORPH BLD have better performance on temporal accuracy of precipitation estimation,followed by ERA5 and TRMM 3B42V7.MSWEPs yield the most even spatial distribution across the basin since it takes full advantage of the multi datasets.As the weighted-ensemble method is independently carried out on each grid in MSWEPs,the spatial distribution of local precipitation is changed by different source data,which results in that MSWEPs perform worse than CMORPH BLD in terms of the representation of precipitation spatial pattern.In addition,the capability of MSWEPs to describe the spatial structure in the rainy season is lower than that in the dry season.Strong precipitation(≥100 mm/d)events are better represented in TRMM 3B42 V7 products than in MSWEPs.Finally,based on the comparison results,we suggest to improve the merging algorithm of MSWEP by considering the precipitation spatial self-correlation and adjusting the merging weights based on the performance of the source datasets under different precipitation intensities.
基金National Key Research and Development Program of China,No.2018YFC1508204Special Program for Public Welfare Industrial Scientific Research of the Ministry of Water Resources,No.201401015,No.201501014National Natural Science Foundation of China,No.51509157。
文摘Climate change and human activity can cause remarkable hydrological variation.Traits of hydrological series such as runoff before and after the change points could be significantly different,so the calculation of instream ecological water requirements(EWRs)is confronted with more challenges.Taking the Xitiaoxi River(XTXR)in the upper reach of the Taihu Lake Basin as an example,this paper investigates the calculation of EWRs using the range of variability approach(RVA)under changing environment.The change point diagnosis of the natural and observed runoff series are conducted for XTXR.Then,differences in the hydrological alternation indicators and instream EWRs processes obtained from various daily runoff series are compared.It was found that the natural and observed annual runoff series in XTXR from 1957 to 2018 both show significant variations,and the change points are in 2007 and 1999 respectively.If runoff data before the change points or all runoff data are used,the instream EWRs obtained from natural runoff are significantly lower than those obtained from the observed runoff.At the monthly time step,EWRs differences within a year mainly occurred from May to August.Also,calculation results of the instream EWRs are strongly related to the selected period of runoff series.The EWRs obtained using runoff series after the change points have rather acute fluctuation within a year.Therefore,when the RVA method is used under changing environment,the instream EWRs should be prudently determined by comparing different calculation results on the basis of river runoff restoration and variability analysis.To a certain extent,this paper enriches our understanding about the hydrological method for EWRs estimation,and proposes new ideas for future research on EWRs.
