Combining an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate
Combining an ecological model with remote sensing and GIS techniques to monitor soil water content of croplands with a monsoon climate
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DOI：
10.1016/j.agwat.2009.12.007
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发表时间：
2010-08
影响因子：
6.7
通讯作者：
W. Ju;P. Gao;Jun Wang;Yanlian Zhou;Xuehui Zhang
中科院分区：
文献类型：
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作者：
W. Ju;P. Gao;Jun Wang;Yanlian Zhou;Xuehui Zhang
土壤水分是影响作物光合作用、蒸腾作用、生长发育和产量的重要因素。准确的土壤含水量（SWC）信息对于各种尺度的农业用水管理至关重要。在这项研究中，遥感参数（叶面积指数，土地覆被类型，和植被）和空间数据处理，使用地理信息系统（GIS）技术同化到北方生态系统生产力模拟器（BEPS）模型监测农田土壤水资源动态在江苏省，中国。这里的季风气候的特点是大的年际和季节性变化的降雨造成的高和低SWC的时期。模型验证进行了比较模拟SWC与测量重力法在2005年和2006年在9个农业气象站。模型-测量R2值范围为0.40 - 0.82。Nash-Sutcliffe效率值在0.10至0.80的范围内。均方根误差（RMSE）值范围为0.028至0.056m3m−3。模拟的蒸散量（ET）与蒸发皿蒸发测量的ET估计值一致。BEPS模型成功地跟踪了2006年9月至11月期间发生的严重土壤水分亏缺的动态和程度。这些结果表明，基于过程的模型与遥感和GIS技术相结合的适用性，在监测农田SWC和改善农业用水管理在区域尺度上的季风气候。
Soil water is an important factor affecting photosynthesis, transpiration, growth, and yield of crops. Accurate information on soil water content (SWC) is crucial for practical agricultural water management at various scales. In this study, remotely sensed parameters (leaf area index, land cover type, and albedo) and spatial data manipulated using the geographic information system (GIS) technique were assimilated into the boreal ecosystem productivity simulator (BEPS) model to monitor SWC dynamics of croplands in Jiangsu Province, China. The monsoon climate here is characterized by large interannual and seasonal variability of rainfall causing periods of high and low SWC. Model validation was conducted by comparing simulated SWC with measurements by a gravimetric method in the years 2005 and 2006 at nine agro-meteorological stations. The model-to-measurement R2values ranged from 0.40 to 0.82. Nash-Sutcliffe efficiency values were in the range from 0.10 to 0.80. Root mean square error (RMSE) values ranged from 0.028 to 0.056m3m−3. Simulated evapotranspiration (ET) was consistent with ET estimated from pan evaporation measurements. The BEPS model successfully tracked the dynamics and extent of the serious soil water deficit that occurred during September–November 2006. These results demonstrate the applicability of combining process-based models with remote sensing and GIS techniques in monitoring SWC of croplands and improving agricultural water management at regional scales in a monsoon climate.