Hydrological processes exert enormous influences on the land surface water and energy balance, and have a close relationship with human society. We have developed a new hydrological runoff parameteriza- tion called XX...Hydrological processes exert enormous influences on the land surface water and energy balance, and have a close relationship with human society. We have developed a new hydrological runoff parameteriza- tion called XXT to improve the performance of a coupled land surface-atmosphere modeling system. The XXT parameterization, which is based upon the Xinanjiang hydrological model and TOPMODEL, includes an optimized function of runoff calculation with a new soil moisture storage capacity distribution curve （SMSCC）. We then couple XXT with the Global/RegionM Assimilation Prediction System （GRAPES） and compare it to GRAPES coupled with a simple water balance model （SWB）. For the model evaluation and comparison, we perform 72-h online simulations using GRAPES-XXT and GRAPES-SWB during two torrential events in August 2007 and July 2008, respectively. The results show that GRAPES can reproduce the rainfall distribution and intensity fairly well in both cases. Differences in the representation of feedback processes between surface hydrology and the atmosphere result in differences in the distributions and amounts of precipitation simulated by GRAPES-XXT and GRAPES-SWB. The runoff simulations are greatly improved by the use of XXT in place of SWB, particularly with respect to the distribution and amount of runoff. The average runoff depth is nearly doubled in the rainbelt area, and unreasonable runoff distributions simulated by GRAPES-SWB are made more realistic by the introduction of XXT. Differences in surface soil moisture between GRAPES-XXT and GRAPES-SWB show that the XXT model changes infiltration and increases surface runoff. We also evaluate river flood discharge in the Yishu River basin. The peak values of flood discharge calculated from the output of GRAPES-XXT agree more closely with observations than those calculated from the output of GRAPES-SWB.展开更多
There is an increasing trend to incorporate the basin hydrological model into the traditional land surface model （LSM） to improve the description of hydrological processes in them. For incorporating with the Noah LS...There is an increasing trend to incorporate the basin hydrological model into the traditional land surface model （LSM） to improve the description of hydrological processes in them. For incorporating with the Noah LSM, a new rainfall-runoff model named XXT （the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL） was developed and presented in this study, based on the soil moisture storage capacity distribution curve （SMSCC）, some essential modules of the Xinanjiang model, together with the simple model framework of the TOPMODEL （a topography based hydrological model）. The innovation of XXT is that the water table is incorporated into SMSCC and it connects the surface runoff production with base flow production. This improves the description of the dynamically varying saturated areas that produce runoff and also captures the physical underground water level. XXT was tested in a small-scale watershed Youshuijie （946 km2） and a large-scale watershed Yinglouxia （10009 km2） in China. The results show that XXT has better performance against the TOPMODEL and the Xinanjiang model for the two watersheds in both the calibration period and the validation period in terms of the Nash-Sutcliffe efficiency. Moreover, XXT captures the largest peak flow well for both the small： and large-scale watersheds during the validation period, while the TOPMODEL produces significant overestimates or underestimates, so does the Xinanjiang model.展开更多
Early and effective flood warning is essential for reducing loss of life and economic damage. Three global ensemble weather prediction systems of the China Meteorological Administration （CMA）, the European Centre fo...Early and effective flood warning is essential for reducing loss of life and economic damage. Three global ensemble weather prediction systems of the China Meteorological Administration （CMA）, the European Centre for Medium-Range Weather Forecasts （ECMWF）, and the US National Centers for Environmental Prediction （NCEP） in THORPEX （The Observing System Research and Predictability Experiment） In- teractive Grand Global Ensemble （TIGGE） archive are used in this research to drive the Global/Regional Assimilation and PrEdiction System （GRAPES） to produce 6-h lead time forecasts. The output （precipita- tion, air temperature, humidity, and pressure） in turn drives a hydrological model XXT （the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL）, the hybrid model that combines the TOPMODEL （a topography based hydrological model） and the Xinanjiang model, for a case study of a flood event that lasted from 18 to 20 July 2007 in the Linyi watershed. The results show that rainfall forecasts by GRAPES using TIGGE data from the three forecast centers all underestimate heavy rainfall rates; the rainfall forecast by GRAPES using the data from the NCEP is the closest to the obser- vation while that from the CMA performs the worst. Moreover, the ensemble is not better than individual members for rainfall forecasts. In contrast to corresponding rainfall forecasts, runoff forecasts are much better for all three forecast centers, especially for the NCEP. The results suggest that early flood warning by the GRAPES/XXT model based on TIGGE data is feasible and this provides a new approach to raise preparedness and thus to reduce the socio-economic impact of floods.展开更多
基金Supported by the National Basic Research and Development (973) Program of China (2010CB951404)National Natural Science Foundation of China (40971024)China Meteorological Administration Special Public Welfare Research Fund (GYHY200706001 and GYHY200906007)
文摘Hydrological processes exert enormous influences on the land surface water and energy balance, and have a close relationship with human society. We have developed a new hydrological runoff parameteriza- tion called XXT to improve the performance of a coupled land surface-atmosphere modeling system. The XXT parameterization, which is based upon the Xinanjiang hydrological model and TOPMODEL, includes an optimized function of runoff calculation with a new soil moisture storage capacity distribution curve （SMSCC）. We then couple XXT with the Global/RegionM Assimilation Prediction System （GRAPES） and compare it to GRAPES coupled with a simple water balance model （SWB）. For the model evaluation and comparison, we perform 72-h online simulations using GRAPES-XXT and GRAPES-SWB during two torrential events in August 2007 and July 2008, respectively. The results show that GRAPES can reproduce the rainfall distribution and intensity fairly well in both cases. Differences in the representation of feedback processes between surface hydrology and the atmosphere result in differences in the distributions and amounts of precipitation simulated by GRAPES-XXT and GRAPES-SWB. The runoff simulations are greatly improved by the use of XXT in place of SWB, particularly with respect to the distribution and amount of runoff. The average runoff depth is nearly doubled in the rainbelt area, and unreasonable runoff distributions simulated by GRAPES-SWB are made more realistic by the introduction of XXT. Differences in surface soil moisture between GRAPES-XXT and GRAPES-SWB show that the XXT model changes infiltration and increases surface runoff. We also evaluate river flood discharge in the Yishu River basin. The peak values of flood discharge calculated from the output of GRAPES-XXT agree more closely with observations than those calculated from the output of GRAPES-SWB.
基金Supported by the National Basic Research and Development (973) Program of China (2010CB951404)National Nature Science Foundation of China (40971024 and 31101073)+2 种基金Natural Science Research Fund of the Education Department of Sichuan Province (09ZA075)Open Research Fund of the Meteorological Center for Huaihe Watershed (HRM200905)China Meteorological Administration Special Public Welfare Research Fund (GYHY200906007)
文摘There is an increasing trend to incorporate the basin hydrological model into the traditional land surface model （LSM） to improve the description of hydrological processes in them. For incorporating with the Noah LSM, a new rainfall-runoff model named XXT （the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL） was developed and presented in this study, based on the soil moisture storage capacity distribution curve （SMSCC）, some essential modules of the Xinanjiang model, together with the simple model framework of the TOPMODEL （a topography based hydrological model）. The innovation of XXT is that the water table is incorporated into SMSCC and it connects the surface runoff production with base flow production. This improves the description of the dynamically varying saturated areas that produce runoff and also captures the physical underground water level. XXT was tested in a small-scale watershed Youshuijie （946 km2） and a large-scale watershed Yinglouxia （10009 km2） in China. The results show that XXT has better performance against the TOPMODEL and the Xinanjiang model for the two watersheds in both the calibration period and the validation period in terms of the Nash-Sutcliffe efficiency. Moreover, XXT captures the largest peak flow well for both the small： and large-scale watersheds during the validation period, while the TOPMODEL produces significant overestimates or underestimates, so does the Xinanjiang model.
基金Supported by the National Basic Research and Development (973) Program of China (2010CB951404)National Nature Science Foundation of China (40971024 and 31101073)+1 种基金Natural Science Research Fund of the Education Department of Sichuan Province (09ZA075)China Meteorological Administration Special Public Welfare Research Fund (GYHY200906007)
文摘Early and effective flood warning is essential for reducing loss of life and economic damage. Three global ensemble weather prediction systems of the China Meteorological Administration （CMA）, the European Centre for Medium-Range Weather Forecasts （ECMWF）, and the US National Centers for Environmental Prediction （NCEP） in THORPEX （The Observing System Research and Predictability Experiment） In- teractive Grand Global Ensemble （TIGGE） archive are used in this research to drive the Global/Regional Assimilation and PrEdiction System （GRAPES） to produce 6-h lead time forecasts. The output （precipita- tion, air temperature, humidity, and pressure） in turn drives a hydrological model XXT （the first X stands for Xinanjiang, the second X stands for hybrid, and T stands for TOPMODEL）, the hybrid model that combines the TOPMODEL （a topography based hydrological model） and the Xinanjiang model, for a case study of a flood event that lasted from 18 to 20 July 2007 in the Linyi watershed. The results show that rainfall forecasts by GRAPES using TIGGE data from the three forecast centers all underestimate heavy rainfall rates; the rainfall forecast by GRAPES using the data from the NCEP is the closest to the obser- vation while that from the CMA performs the worst. Moreover, the ensemble is not better than individual members for rainfall forecasts. In contrast to corresponding rainfall forecasts, runoff forecasts are much better for all three forecast centers, especially for the NCEP. The results suggest that early flood warning by the GRAPES/XXT model based on TIGGE data is feasible and this provides a new approach to raise preparedness and thus to reduce the socio-economic impact of floods.
