基于SWAT模型的清江流域中上游旱灾监测  

Drought monitoring of upper and middle reaches of Qingjiang Basin based on SWAT model

作　　者：孙丽[1] 陈曦炜[1] 裴志远[1] 

机构地区：[1]农业部规划设计研究院,北京100125

出　　处：《农业工程学报》2014年第21期129-137,共9页Transactions of the Chinese Society of Agricultural Engineering

基　　金：国家科技支撑资助项目(2012BAH33B02)

摘　　要：为解决地形复杂区域因无法及时获取数据而影响旱灾监测的问题,该研究以湖北省清江流域中上游为例,基于具有较强物理机制的分布式水文模型(soil and water assessment tool,SWAT),建立作物水分亏缺指数进行农业旱情监测,其中,利用该流域的土地覆被、土壤、地形、气象以及2003-2005年和2007-2010年水文观测数据构建了流域SWAT模型,模拟作物水分亏缺指数的有关参量,包括潜在蒸散量和降水量。研究结果表明:1)SWAT模型模拟的潜在蒸散量与气象数据计算得到的潜在蒸散量拟合相关度达到97%以上;2)与标准化降水指数监测结果进行对比,基于SWAT模型建立的作物水分亏缺指数能够从机理方面客观反映监测区域作物生长期的受旱程度,有效实现了流域尺度的旱灾监测,克服了复杂地形区利用少数气象站点建立气象干旱指标评价旱情的局限性。该研究可为复杂地形区旱灾评估提供可行途径。In recent years droughts occurred frequently in western, southwestern remote mountainous areas of China, affecting the local agricultural production and farmers＆#39; life. Drought monitoring and prediction is one of the main tasks of crop condition monitoring. Remote sensing data and ground survey data are used to monitor drought in current crop condition monitoring system, while high-resolution Remote sensing data and enough ground survey data for effective monitoring are often unable to access timely in those remote mountainous areas due to complex topography and broken plots. The aim of the study was to develop drought monitoring method to meet the complex terrain area and then to provide reliable scientific information to guide agricultural production. Crop water deficit index （CWDI） as an index characterizing agricultural drought has been widely used, which includes parameters of potential evapotranspiration （PET） and precipitation. Soil and water assessment tool （SWAT） as a distributed hydrological model with strong mechanism has been used to simulate crop’s potential evapotranspiration in those areas with complex topography. Those tools provide a feasible way of this study. The upper and middle reaches of Qingjiang River Basin, as the study area, from which drought conditions were monitored by the combination of CWDI and SWAT. Land use/cover data, soil data, topography data, meteorology data and hydrological data from 2003 to 2005 and 2007 to 2010 were used for calibration and validation of SWAT model. The PET simulated by SWAT had a high correlation fit with the PET calculated with meteorological data. Comparison of the statistical indexes included relative bias, root mean square error and multiple correlation coefficients. Standard precipitation index （SPI） was used for two times of drought monitoring tests to compare with the crop water deficit index （CWDI） based on the SWAT model. In July 2009, heavy drought happened in upper and middle reaches of Qingjiang River Basin. From the

关 键 词：干旱 监测 灾害 SWAT模型 作物水分亏缺指数 

分 类 号：S423[农业科学—植物保护]