The next-generation weather radar(NEXRAD) can generally capture the spatial variability of rainfall fields,but fails to provide accurate depth measurements.A systematic strategy to evaluate the accuracy of radar data ...The next-generation weather radar(NEXRAD) can generally capture the spatial variability of rainfall fields,but fails to provide accurate depth measurements.A systematic strategy to evaluate the accuracy of radar data in depth measurement and its performance in hydrologic model is outlined.Statistical evaluation coefficients are calculated by comparing NEXRAD data with individual raingauges as well as subbasin-averaged interpolations,and point-and surface-average factors are introduced to revise radar data successively.Hydrologic simulations are then performed with a distributed hydrologic model,called basin pollution calculation center(BPCC) with both raingauge observations and revised NEXRAD estimates inputs.The BPCC model is applied to Clear Creek Watershed,IA,USA,on an hourly scale,and the calibration and validation parameters are semi-automatically optimized to improve manual calibration shortcomings.Results show that hydrographs generated from both gauge and NEXRAD are in good agreement with observed flow hydrographs.Coefficient statistics reveal that NEXRAD contributes to model performance,indicating that NEXRAD data has the potential to be used as an alternative source of precipitation data and improve the accuracy of hydrologic simulations.展开更多
The hydrologic cycle and understanding the relationship between rainfall and runoff is an important component of earth system science,sustainable development,and natural disasters caused by floods.With this in mind,th...The hydrologic cycle and understanding the relationship between rainfall and runoff is an important component of earth system science,sustainable development,and natural disasters caused by floods.With this in mind,the integration of digital earth data for hydrologic sciences is an important area of research.Currently,it takes a tremendous amount of effort to perform hydrologic analysis at a large scale because the data to support such analyses are not available on a single system in an integrated format that can be easily manipulated.Furthermore,the state-of-the-art in hydrologic data integration typically uses a rigid relational database making it difficult to redesign the data model to incorporate new data types.The HydroCloud system incorporates a flexible document data model to integrate precipitation and stream flow data across spatial and temporal dimensions for large-scale hydrologic analyses.In this paper,a document database schema is presented to store the integrated data-set along with analysis tools such as web services for data access and a web interface for exploratory data analysis.The utility of the system is demonstrated based on a scientific workflow that uses the system for both exploratory data analysis and statistical hypothesis testing.展开更多
基金supported by the National Basic Research Program of China ("973" Project) (Grant No. 2007CB407202)
文摘The next-generation weather radar(NEXRAD) can generally capture the spatial variability of rainfall fields,but fails to provide accurate depth measurements.A systematic strategy to evaluate the accuracy of radar data in depth measurement and its performance in hydrologic model is outlined.Statistical evaluation coefficients are calculated by comparing NEXRAD data with individual raingauges as well as subbasin-averaged interpolations,and point-and surface-average factors are introduced to revise radar data successively.Hydrologic simulations are then performed with a distributed hydrologic model,called basin pollution calculation center(BPCC) with both raingauge observations and revised NEXRAD estimates inputs.The BPCC model is applied to Clear Creek Watershed,IA,USA,on an hourly scale,and the calibration and validation parameters are semi-automatically optimized to improve manual calibration shortcomings.Results show that hydrographs generated from both gauge and NEXRAD are in good agreement with observed flow hydrographs.Coefficient statistics reveal that NEXRAD contributes to model performance,indicating that NEXRAD data has the potential to be used as an alternative source of precipitation data and improve the accuracy of hydrologic simulations.
基金the Towson University School of Emerging Technologies.
文摘The hydrologic cycle and understanding the relationship between rainfall and runoff is an important component of earth system science,sustainable development,and natural disasters caused by floods.With this in mind,the integration of digital earth data for hydrologic sciences is an important area of research.Currently,it takes a tremendous amount of effort to perform hydrologic analysis at a large scale because the data to support such analyses are not available on a single system in an integrated format that can be easily manipulated.Furthermore,the state-of-the-art in hydrologic data integration typically uses a rigid relational database making it difficult to redesign the data model to incorporate new data types.The HydroCloud system incorporates a flexible document data model to integrate precipitation and stream flow data across spatial and temporal dimensions for large-scale hydrologic analyses.In this paper,a document database schema is presented to store the integrated data-set along with analysis tools such as web services for data access and a web interface for exploratory data analysis.The utility of the system is demonstrated based on a scientific workflow that uses the system for both exploratory data analysis and statistical hypothesis testing.
