Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impac...Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impacts of climate change and human activities on hydrological evolution and disaster risk from a holistic perspective of the basin.This study developed initiatives to clarify the mechanisms of hydrological evolution in the human-influenced Yellow River Basin.The proposed research method includes:(1)a tool to simulate multiple factors and a multi-scale water cycle using a grid-based spatiotemporal coupling approach,and(2)a new algorithm to separate the responses of the water cycle to climate change and human impacts,and de-couple the eco-environmental effects using artificial intelligence techniques.With this research framework,key breakthroughs are expected to be made in the understanding of the impacts of land cover change on the water cycle and blue/green water redirection.The outcomes of this research project are expected to provide theoretical support for ecological protection and water governance in the basin.展开更多
A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation A...A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.展开更多
The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for mul...The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt's transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required.展开更多
The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Bas...The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products(3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42 RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions,respectively, and CMORPH performs better than 3B42 RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement(GPM) data in the future.展开更多
The Palmer drought severity index(PDSI) is physically based with multivariate concepts, but requires complicated calibration and cannot easily be used for multiscale comparison. Standardized drought indices(SDIs), suc...The Palmer drought severity index(PDSI) is physically based with multivariate concepts, but requires complicated calibration and cannot easily be used for multiscale comparison. Standardized drought indices(SDIs), such as the standardized precipitation index(SPI) and standardized precipitation evapotranspiration index(SPEI), are multiscalar and convenient for spatiotemporal comparison, but they are still challenged by their lack of physical basis. In this study, a hybrid multiscalar indicator, the standardized Palmer drought index(SPDI), was used to examine drought properties of two meteorological stations(the Beijing and Guangzhou stations) in China, which have completely different drought climatologies. The results of our case study show that the SPDI is correlated with the well-established drought indices(SPI, SPEI, and PDSI) and presents generally consistent drought/wetness conditions against multiple indicators and literature records. Relative to the PDSI, the SPDI demonstrates invariable statistical characteristics and better comparable drought/wetness frequencies over time and space. Moreover,characteristics of major drought events(drought class, and onset and end times) indicated by the SPDI are generally comparable to those detected by the PDSI. As a physically-based standardized multiscalar drought indicator, the SPDI can be regarded as an effective development of the Palmer drought indices, providing additional choices and tools for practical drought monitoring and assessment.展开更多
This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process s...This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process simulation in semi-arid regions, a spatially varying storage capacity (VSC) model was developed based on the spatial distribution of water storage capacity and the vertical hybrid runoff mechanism. To verify the applicability of the VSC model, both the VSC model and a hybrid runoff model were used to simulate daily runoff processes in the catchment upstream of the Dianzi hydrological station from 1973 to 1979. The results showed that the annual average Nash-Sutcliffe coefficient was 0.80 for the VSC model, and only 0.67 for the hybrid runoff model. The higher annual average Nash-Sutcliffe coefficient of the VSC model means that this hydrological model can better simulate daily runoff processes in semi-arid regions. Furthermore, as a distributed hydrological model, the VSC model can be applied in regional water resource management.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.U2243203),the Fundamental Research Funds for the Central Universities(Grants No.B200204029 and B220201011),and the Natural Science Foundation of Jiangsu Province(Grant No.BK20210368).
文摘Significant changes in water cycle elements/processes have created serious challenges to regional sustainability and high-quality development in the Yellow River Basin in China.It is necessary to investigate the impacts of climate change and human activities on hydrological evolution and disaster risk from a holistic perspective of the basin.This study developed initiatives to clarify the mechanisms of hydrological evolution in the human-influenced Yellow River Basin.The proposed research method includes:(1)a tool to simulate multiple factors and a multi-scale water cycle using a grid-based spatiotemporal coupling approach,and(2)a new algorithm to separate the responses of the water cycle to climate change and human impacts,and de-couple the eco-environmental effects using artificial intelligence techniques.With this research framework,key breakthroughs are expected to be made in the understanding of the impacts of land cover change on the water cycle and blue/green water redirection.The outcomes of this research project are expected to provide theoretical support for ecological protection and water governance in the basin.
基金supported by the National Natural Science Foundation of China(Grant No.51979069)the Fundamental Research Funds for the Central Universities(Grant No.B200204029)the National Natural Science Foundation of Jiangsu Province,China(Grant No.BK20211202).
文摘A comprehensive assessment of representative satellite-retrieved(Integrated Multi-satellite Retrievals for Global Precipitation Measurement(IMERG)and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA)),reanalysis-based(fifth generation of atmospheric reanalysis by the European Centre for Medium Range Weather Forecasts(ERA5)),and gauge-estimated(Climate Prediction Center(CPC))precipitation products was conducted using the data from 807 meteorological stations across China's Mainland from 2001 to 2017.Error statistical metrics,precipitation distribution functions,and extreme precipitation indices were used to evaluate the quality of the four precipitation products in terms of multi-timescale accuracy and extreme precipitation estimation.When the timescale increased from daily to seasonal scales,the accuracy of the four precipitation products first increased and then decreased,and all products performed best on the monthly timescale.Their accuracy ranking in descending order was CPC,IMERG,TMPA,and ERA5 on the daily timescale and IMERG,CPC,TMPA,and ERA5 on the monthly and seasonal timescales.IMERG was generally superior to its predecessor TMPA on the three timescales.ERA5 exhibited large statistical errors.CPC provided stable estimated values.For extreme precipitation estimation,the quality of IMERG was relatively consistent with that of TMPA in terms of precipitation distribution and extreme metrics,and IMERG exhibited a significant advantage in estimating moderate and heavy precipitation.In contrast,ERA5 and CPC exhibited poor performance with large systematic underestimation biases.The findings of this study provide insight into the performance of the latest IMERG product compared with the widely used TMPA,ERA5,and CPC datasets,and points to possible directions for improvement of multi-source precipitation data fusion algorithms in order to better serve hydrological applications.
基金supported by the Program of Introducing Talents of Disciplines to Universities of the Ministry of Education and State Administration of the Foreign Experts Affairs of China (the 111 Project, Grant No.B08048)the Special Basic Research Fund for Methodology in Hydrology of the Ministry of Sciences and Technology of China (Grant No. 2011IM011000)
文摘The question of how to choose a copula model that best fits a given dataset is a predominant limitation of the copula approach, and the present study aims to investigate the techniques of goodness-of-fit tests for multi-dimensional copulas. A goodness-of-fit test based on Rosenblatt's transformation was mathematically expanded from two dimensions to three dimensions and procedures of a bootstrap version of the test were provided. Through stochastic copula simulation, an empirical application of historical drought data at the Lintong Gauge Station shows that the goodness-of-fit tests perform well, revealing that both trivariate Gaussian and Student t copulas are acceptable for modeling the dependence structures of the observed drought duration, severity, and peak. The goodness-of-fit tests for multi-dimensional copulas can provide further support and help a lot in the potential applications of a wider range of copulas to describe the associations of correlated hydrological variables. However, for the application of copulas with the number of dimensions larger than three, more complicated computational efforts as well as exploration and parameterization of corresponding copulas are required.
基金supported by the Programme of Introducing Talents of Discipline to Universities(the 111 Project,Grant No.B08048)the National Natural Science Foundation of China(Grant No.41501017)the Natural Science Foundation of Jiangsu Province(Grant No.BK20150815)
文摘The main objective of this study was to evaluate four latest global high-resolution satellite precipitation products(TMPA 3B42 RT, CMORPH,TMPA 3B42V7, and CMORPH_adj) against gauge observations of the Yellow River Basin from March 2000 to December 2012. The assessment was conducted with several commonly used statistical indices at daily and monthly scales. Results indicate that 3B42V7 and CMORPH_adj perform better than the near real-time products(3B42RT and CMORPH), particularly the 3B42V7 product. The adjustment by gauge data significantly reduces the systematic biases in the research products. Regarding the near real-time datasets, 3B42 RT overestimates rainfall over the whole basin, while CMORPH presents a mixed pattern with negative and positive values of relative bias in low- and high-latitude regions,respectively, and CMORPH performs better than 3B42 RT on the whole. According to the spatial distribution of statistical indices, these values are optimized in the southeast and decrease toward the northwest, and the trend is similar for the spatial distribution of the mean annual precipitation during the period from 2000 to 2012. This study also reveals that all the four products can effectively detect rainfall events. This study provides useful information about four mainstream satellite products in the Yellow River Basin, and the findings can facilitate the use of global precipitation measurement(GPM) data in the future.
基金supported by the National Natural Science Foundation of China(Grant No.41701022)the Open Foundation of State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering(Grant No.2017491011)the Scientific and Technical Innovation Team Foundation for Universities of Henan Province(Grant No.18IRTSTHN009)
文摘The Palmer drought severity index(PDSI) is physically based with multivariate concepts, but requires complicated calibration and cannot easily be used for multiscale comparison. Standardized drought indices(SDIs), such as the standardized precipitation index(SPI) and standardized precipitation evapotranspiration index(SPEI), are multiscalar and convenient for spatiotemporal comparison, but they are still challenged by their lack of physical basis. In this study, a hybrid multiscalar indicator, the standardized Palmer drought index(SPDI), was used to examine drought properties of two meteorological stations(the Beijing and Guangzhou stations) in China, which have completely different drought climatologies. The results of our case study show that the SPDI is correlated with the well-established drought indices(SPI, SPEI, and PDSI) and presents generally consistent drought/wetness conditions against multiple indicators and literature records. Relative to the PDSI, the SPDI demonstrates invariable statistical characteristics and better comparable drought/wetness frequencies over time and space. Moreover,characteristics of major drought events(drought class, and onset and end times) indicated by the SPDI are generally comparable to those detected by the PDSI. As a physically-based standardized multiscalar drought indicator, the SPDI can be regarded as an effective development of the Palmer drought indices, providing additional choices and tools for practical drought monitoring and assessment.
基金supported by the National Key Basic Research Program of China (Grant No. 2006CB400502)the Special Basic Research Fund for Methodology in Hydrology (Grant No. 2007FY140900)the 111 Project (Grant No. B08048)
文摘This paper introduces the method of designation of water storage capacity for each grid cell within a catchment, which considers topography, vegetation and soil synthetically. For the purpose of hydrological process simulation in semi-arid regions, a spatially varying storage capacity (VSC) model was developed based on the spatial distribution of water storage capacity and the vertical hybrid runoff mechanism. To verify the applicability of the VSC model, both the VSC model and a hybrid runoff model were used to simulate daily runoff processes in the catchment upstream of the Dianzi hydrological station from 1973 to 1979. The results showed that the annual average Nash-Sutcliffe coefficient was 0.80 for the VSC model, and only 0.67 for the hybrid runoff model. The higher annual average Nash-Sutcliffe coefficient of the VSC model means that this hydrological model can better simulate daily runoff processes in semi-arid regions. Furthermore, as a distributed hydrological model, the VSC model can be applied in regional water resource management.