Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and...Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and rainfall will result in different surface runoff generation mechanisms. For a large area (e.g., a model grid size of a regional climate model or a general circulation model), these runoff generation mechanisms are commonly present at different portions of a grid cell simultaneously. Missing one of the two major runoff generation mechanisms and failing to consider spatial soil variability can result in significant under/over estimation of surface runoff which can directly introduce large errors in soil moisture states over each model grid cell. Therefore, proper modeling of surface runoff is essential to a reasonable representation of feedbacks in a land-atmosphere system. This paper presents a new surface runoff parameterization with the Philip infiltration formulation that dynamically represents both the Horton and Dunne runoff generation mechanisms within a model grid cell. The parameterization takes into account the effects of soil heterogeneity on Horton and Dunne runoff. The new parameterization is implemented into the current version of the hydrologically based Variable Infiltration Capacity (VIC) land surface model and tested over one watershed in Pennsylvania, USA and over the Shiguanhe Basin in the Huaihe Watershed in China. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere-land coupling system, and has potential applications on large hydrological simulations and land-atmospheric interactions. It is further found that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation.展开更多
论文对比分析了1980—2016年基于站点插值降水数据CMA(China Meteorological Administration)和APHRODITE(Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation)、卫星遥感降水数据PERSIANN-CDR(Pr...论文对比分析了1980—2016年基于站点插值降水数据CMA(China Meteorological Administration)和APHRODITE(Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation)、卫星遥感降水数据PERSIANN-CDR(Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record)和GPM(Global Precipitation Measurement)、大气再分析数据GLDAS(Global Land Data Assimilation System)以及区域气候模式输出数据HAR(High Asia Refined analysis)在雅鲁藏布江7个子流域的降水时空描述,利用国家气象站点数据对各套降水数据进行单点验证,并以这6套降水数据驱动VIC(Variable Infiltration Capacity)大尺度陆面水文模型反向评估了各套降水产品在雅鲁藏布江各子流域径流模拟中的应用潜力。结果表明:①PERSIANN-CDR和GLDAS年均降水量最高(770~790 mm),其次是HAR和GPM(650~660 mm),CMA和APHRODITE年均降水量最低(460~500 mm)。除GPM外,其他降水产品在各子流域都能表现季风流域的降水特征,约70%~90%的年降水量集中在6—9月份。②除PERSIANN-CDR和GLDAS外,其他降水产品皆捕捉到流域降水自东南向西北递减的空间分布特征。其中,HAR数据空间分辨率最高,表现出更详细的流域内部降水空间分布特征。③与对应网格内的国家气象站降水数据对比显示,APHRODITE、GPM和HAR降水整体低估(低估10%~30%),且严重低估的站点主要集中在下游(低估40%~120%)。PERSIANN-CDR和GLDAS整体表现为高估上游流域站点降水(高估28%~60%),但低估下游流域站点降水(低估11%~21%)。④在流域径流模拟上,当前的6套降水产品在精度或时段上仍无法满足水文模型模拟的需求。⑤通过水文模型反向评估,6套降水产品中区域气候模式输出的HAR在流域平均降水量和季节分配上更合理。展开更多
The Xin'anjiang Model is used as the basic model to develop a monthly grid-based macroscale hydrological model for the assessment of the effects of climate change on water resources.The monthly discharge from 1953...The Xin'anjiang Model is used as the basic model to develop a monthly grid-based macroscale hydrological model for the assessment of the effects of climate change on water resources.The monthly discharge from 1953 through 1985 in the Huaihe River Basin is simulated.The sensitivity analysis on runoff is made under assumed climatic scenarios.There is a good agreement between the observed and simulated runoff.Due to the increase of time interval and decrease of precipitation intensity on monthly time scale,there is no monthly runoff in some model girds as the momhly hydrological model is applied to the Huaihe River Basin.Two methods of downscaling monthly precipitation to daily resolution are validated by running the Xin'anjiang model with monthly data at a daily time step.and the model outputs are more realistic than the monthly hydrological model.The metbods of downscaling of monthly precipitation to daily resolution may provide an idea in solving the problem of the shortage of daily data.In the research of the climate change on water resources,the daily hydrological model can be used instead of the monthly one.展开更多
基金The research reported herein was jointly supported by the National Natural Science Foundation of China under Grant Nos. 40145020, 40275023, 49794030, the National Key Program for Developing Basic Sciences under Grant Nos. G1998040905 and 2001CB309404,
文摘Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and rainfall will result in different surface runoff generation mechanisms. For a large area (e.g., a model grid size of a regional climate model or a general circulation model), these runoff generation mechanisms are commonly present at different portions of a grid cell simultaneously. Missing one of the two major runoff generation mechanisms and failing to consider spatial soil variability can result in significant under/over estimation of surface runoff which can directly introduce large errors in soil moisture states over each model grid cell. Therefore, proper modeling of surface runoff is essential to a reasonable representation of feedbacks in a land-atmosphere system. This paper presents a new surface runoff parameterization with the Philip infiltration formulation that dynamically represents both the Horton and Dunne runoff generation mechanisms within a model grid cell. The parameterization takes into account the effects of soil heterogeneity on Horton and Dunne runoff. The new parameterization is implemented into the current version of the hydrologically based Variable Infiltration Capacity (VIC) land surface model and tested over one watershed in Pennsylvania, USA and over the Shiguanhe Basin in the Huaihe Watershed in China. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere-land coupling system, and has potential applications on large hydrological simulations and land-atmospheric interactions. It is further found that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation.
文摘论文对比分析了1980—2016年基于站点插值降水数据CMA(China Meteorological Administration)和APHRODITE(Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation)、卫星遥感降水数据PERSIANN-CDR(Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record)和GPM(Global Precipitation Measurement)、大气再分析数据GLDAS(Global Land Data Assimilation System)以及区域气候模式输出数据HAR(High Asia Refined analysis)在雅鲁藏布江7个子流域的降水时空描述,利用国家气象站点数据对各套降水数据进行单点验证,并以这6套降水数据驱动VIC(Variable Infiltration Capacity)大尺度陆面水文模型反向评估了各套降水产品在雅鲁藏布江各子流域径流模拟中的应用潜力。结果表明:①PERSIANN-CDR和GLDAS年均降水量最高(770~790 mm),其次是HAR和GPM(650~660 mm),CMA和APHRODITE年均降水量最低(460~500 mm)。除GPM外,其他降水产品在各子流域都能表现季风流域的降水特征,约70%~90%的年降水量集中在6—9月份。②除PERSIANN-CDR和GLDAS外,其他降水产品皆捕捉到流域降水自东南向西北递减的空间分布特征。其中,HAR数据空间分辨率最高,表现出更详细的流域内部降水空间分布特征。③与对应网格内的国家气象站降水数据对比显示,APHRODITE、GPM和HAR降水整体低估(低估10%~30%),且严重低估的站点主要集中在下游(低估40%~120%)。PERSIANN-CDR和GLDAS整体表现为高估上游流域站点降水(高估28%~60%),但低估下游流域站点降水(低估11%~21%)。④在流域径流模拟上,当前的6套降水产品在精度或时段上仍无法满足水文模型模拟的需求。⑤通过水文模型反向评估,6套降水产品中区域气候模式输出的HAR在流域平均降水量和季节分配上更合理。
文摘The Xin'anjiang Model is used as the basic model to develop a monthly grid-based macroscale hydrological model for the assessment of the effects of climate change on water resources.The monthly discharge from 1953 through 1985 in the Huaihe River Basin is simulated.The sensitivity analysis on runoff is made under assumed climatic scenarios.There is a good agreement between the observed and simulated runoff.Due to the increase of time interval and decrease of precipitation intensity on monthly time scale,there is no monthly runoff in some model girds as the momhly hydrological model is applied to the Huaihe River Basin.Two methods of downscaling monthly precipitation to daily resolution are validated by running the Xin'anjiang model with monthly data at a daily time step.and the model outputs are more realistic than the monthly hydrological model.The metbods of downscaling of monthly precipitation to daily resolution may provide an idea in solving the problem of the shortage of daily data.In the research of the climate change on water resources,the daily hydrological model can be used instead of the monthly one.
