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土壤空间分辨率对BTOPMC模型径流模拟的影响 被引量:2
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作者 文小平 万育安 敖天其 《人民黄河》 CAS 北大核心 2010年第11期45-46,48,共3页
以湄公河为例,给出了3种不同分辨率的网格土壤类型,分析了不同的土壤空间分辨率对BTOPMC模型参数的影响。结果表明:不同分辨率下,用1980年优化得到的BTOPMC模型参数模拟1982年径流时,都能体现湄公河流域的水文过程,且峰现时差几乎不受... 以湄公河为例,给出了3种不同分辨率的网格土壤类型,分析了不同的土壤空间分辨率对BTOPMC模型参数的影响。结果表明:不同分辨率下,用1980年优化得到的BTOPMC模型参数模拟1982年径流时,都能体现湄公河流域的水文过程,且峰现时差几乎不受土壤空间分辨率的影响;使用不同土壤分辨率的数据进行优化得到的Nash效率相近;BTOPMC模型对土壤信息的敏感性较弱。 展开更多
关键词 BTOPMC模型 土壤类型 土壤空间分辨率 湄公河
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土壤数据空间分辨率对水文过程模拟的影响 被引量:10
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作者 叶许春 张奇 +2 位作者 刘健 李丽娇 左海军 《地理科学进展》 CSCD 北大核心 2009年第4期575-583,共9页
分布式水文模型的应用,其准确性有赖于输入数据对流域特征的描述,尤其在大尺度流域,输入数据分辨率的增加是否必然改善模型的模拟效果是值得深入研究的问题。本文以鄱阳湖信江流域为研究区,运用SWAT模型为模拟工具,分析了土壤数据空间... 分布式水文模型的应用,其准确性有赖于输入数据对流域特征的描述,尤其在大尺度流域,输入数据分辨率的增加是否必然改善模型的模拟效果是值得深入研究的问题。本文以鄱阳湖信江流域为研究区,运用SWAT模型为模拟工具,分析了土壤数据空间分辨率对径流、蒸发及土壤含水量等水文要素模拟的影响以及高精度土壤数据在大流域尺度的适应性。结果表明:不同分辨率的土壤数据对SWAT模型中水文响应单元的划分结果差异显著,但在径流模拟和蒸发计算结果中并没有表现出显著的差别;模型率定前后,低分辨率土壤数据的径流模拟结果略好于高分辨率土壤数据,但两者之间的差别不明显;模型模拟的土壤含水量差异显著,高分辨率土壤模拟的月平均土壤含水量整体大于低分辨率土壤模拟结果;研究还发现,模型的蒸发计算对土壤分辨率信息不敏感。本文研究意味着,大尺度SWAT模型的应用中,土壤数据分辨率的提高不一定会改善模型的模拟效果。在具体应用中,应考虑流域本身的尺度以及模拟精度的要求,选择合适分辨率的土壤数据,同时应结合模型原理和关键参数的物理含义来解释模拟结果。 展开更多
关键词 SWAT模型 水文过程 土壤数据空间分辨率 信江流域
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Improved spatial resolution in soil moisture retrieval at arid mining area using apparent thermal inertia 被引量:4
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作者 雷少刚 卞正富 +1 位作者 John L.DANIELS 刘东烈 《Transactions of Nonferrous Metals Society of China》 SCIE EI CAS CSCD 2014年第6期1866-1873,共8页
A surface soil moisture model with improved spatial resolution was developed using remotely sensed apparent thermal inertia(ATI).The model integrates the surface temperature derived from TM/ETM+ image and the mean ... A surface soil moisture model with improved spatial resolution was developed using remotely sensed apparent thermal inertia(ATI).The model integrates the surface temperature derived from TM/ETM+ image and the mean surface temperature from MODIS images to improve the spatial resolution of soil temperature difference based on the heat conduction equation,which is necessary to calculate the ATI.Consequently,the spatial resolution of ATI and SMC can be enhanced from 1 km to 120 m(TM) or 60m(ETM+).Moreover,the enhanced ATI has a much stronger correlation coefficient(R^2) with SMC(0.789) than the surface reflectance(0.108) or the ATI derived only from MODIS images(0.264).Based on the regression statistics of the field SMC measurement and enhanced ATI,a linear regression model with an RMS error of 1.90%was found. 展开更多
关键词 soil water content soil temperature difference thermal inertia remote sensing spatial resolution
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Modeling Carbon Dynamics in Paddy Soils in Jiangsu Province of China with Soil Databases Differing in Spatial Resolution 被引量:9
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作者 XU Sheng-Xiang SHI Xue-Zheng +5 位作者 ZHAO Yong-Cun YU Dong-Sheng WANG Shi-Hang ZHANG Li-Ming C. S. LI TAN Man-Zhi 《Pedosphere》 SCIE CAS CSCD 2011年第6期696-705,共10页
A number of process-based models have been developed for quantifying carbon(C)sequestration in agro-ecosystems.The DeNitrification-DeComposition(DNDC)model was used to simulate and quantify long-term(1980-2008)soil or... A number of process-based models have been developed for quantifying carbon(C)sequestration in agro-ecosystems.The DeNitrification-DeComposition(DNDC)model was used to simulate and quantify long-term(1980-2008)soil organic carbon(SOC)dynamics in the important rice-producing province,Jiangsu,China.Changes in SOC storages were estimated from two soil databases differing in spatial resolution:a county database consisting of 68 polygons and a soil patch-based database of 701 polygons for all 3.7 Mha of rice fields in Jiangsu.The simulated SOC storage with the coarse resolution county database ranged between 131.0-320.6 Tg C in 1980 and 170.3-305.1 Tg C in 2008,respectively,while that estimated with the fine resolution database was 201.6 and 216.2 Tg C in 1980 and 2008,respectively.The results modeled with the soil databases differing in spatial resolution indicated that using the soil input data with higher resolution substantially increased the accuracy of the modeled results;and when lacking detailed soil datasets,the DNDC model,parameterized with the most sensitive factor(MSF) method to cope with attribute uncertainty,could still produce acceptable results although with deviations of up to 60% for the case study reported in this paper. 展开更多
关键词 1:1 000000 soil map C sequestration rate DeNitrification-DeComposition (DNDC) greenhouse gas soil organic carbon (SOC)
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