土地利用数据精度对泾河上游区径流模拟影响研究
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摘要
作为SWAT模型基础数据之一的土地利用数据的空间精度的不同会对模型模拟产生一定的影响。为了更好地了解土地利用数据空间精度对模型模拟的具体影响,以泾川三站以上的泾河流域为研究区域。选用3种常见的不同空间分辨率、分类系统的土地利用数据集(Land 1、Land 2、Land 3)构建SWAT模型,选用模型评价指标ENS、R2,模拟泾川三站1980-1990年共11年的月径流量。其中,率定期为1980-1988年,验证期为1989-1990年,分析比较各数据集对应的模型模拟结果。研究结果表明:①3种土地利用/覆被数据集均在泾河上游区的适用性良好,就模拟结果来说,Land 2数据集的模拟效果最好,率定期(1980-1988年)的ENS、R2分别为0.73、0.74;验证期(1989-1990年)分别为0.55、0.73;②水文响应单元HRUs划分的个数可能跟输入模型的土地利用/覆被数据集的空间精度有关,且输入数据空间精度越高,划分的HRUs数量越多;③输入土地利用数据的分类精度对模型敏感性参数的影响高于空间分辨率对模型敏感性参数的影响;④输入土地利用数据的精度与模拟结果之间的关系并不是随数据精度高低而变化的简单线性关系;水文响应单元HRUs的划分数量对于模型模拟结果的影响大于土地利用分类精度对模型模拟结果的影响。研究成果对于研究区土地利用数据的选用有较高的研究意义。
As one of the basic data of the SWAT model,the spatial precision of land use data will have a certain impact on the model simulation. In order to better understand the effect of spatial precision of land use data on model simulation,this paper takes the Jinghe River Basin above the third of Jingchuan Station as the research area. Three common land use datasets(Land 1,Land 2,Land 3) with different spatial resolution and classification systems were used to build SWAT models and two model evaluation indexes,ENSand R2,were selected to simulate the 11-year monthly runoff of the third of the Jingchuan station from 1980 to 1990. Among them,the calibration period was 1980-1988 and the validation period was 1989-1990,and the simulation results of each data set were analyzed and compared. The results show that: ① The values of the two indexes of SWAT models that build by three different land use date sets are greater than 0.7. Among them,the simulation results of Land 2 corresponding SWAT model are the best,ENSand R2 are 0.73 and 0.74 during the calibration period(1980-1988),0.55 and 0.73 during the validation period,respectively. ② Changes in spatial precision of land use data will affect the division of hydrological response unit hrus,and the higher the precision of the input data space,the more HRUs. ③The effect of classification accuracy of input land use data on model sensitivity parameters is higher than that of spatial resolution. ④ The relationship between the precision of the input land use data and the simulation results is not a simple linear relationship; the number of division of the hydrological response unit(HRUs) has more influence on the model simulation result than the accuracy of land use classification on the model simulation result.
As one of the basic data of the SWAT model,the spatial precision of land use data will have a certain impact on the model simulation. In order to better understand the effect of spatial precision of land use data on model simulation,this paper takes the Jinghe River Basin above the third of Jingchuan Station as the research area. Three common land use datasets(Land 1,Land 2,Land 3) with different spatial resolution and classification systems were used to build SWAT models and two model evaluation indexes,ENSand R2,were selected to simulate the 11-year monthly runoff of the third of the Jingchuan station from 1980 to 1990. Among them,the calibration period was 1980-1988 and the validation period was 1989-1990,and the simulation results of each data set were analyzed and compared. The results show that: ① The values of the two indexes of SWAT models that build by three different land use date sets are greater than 0.7. Among them,the simulation results of Land 2 corresponding SWAT model are the best,ENSand R2 are 0.73 and 0.74 during the calibration period(1980-1988),0.55 and 0.73 during the validation period,respectively. ② Changes in spatial precision of land use data will affect the division of hydrological response unit hrus,and the higher the precision of the input data space,the more HRUs. ③The effect of classification accuracy of input land use data on model sensitivity parameters is higher than that of spatial resolution. ④ The relationship between the precision of the input land use data and the simulation results is not a simple linear relationship; the number of division of the hydrological response unit(HRUs) has more influence on the model simulation result than the accuracy of land use classification on the model simulation result.
引文
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[11]金鑫,陈琼,金彦香.土地利用/覆被数据精度对流域水文过程模拟的影响研究[J].灌溉排水学报,2018,37(2):108-115.
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[14]叶许春,张奇,刘健,等.土壤数据空间分辨率对水文过程模拟的影响[J].地理科学进展,2009,(4):575-583.
[15] Zheng Shen,Qian Hong,Hong Yu,et al. Parameter uncertaintyanalysis of the non-point source pollution in the Daning River water-shed of the Three Gorges Reservoir Region,China[J].Science of theTotal Environment,2008,(405):195-205.
[16] Tan M L,Darren Ficklin,Barnali Dixon,et al. Impacts of DEM res-olution,source,and resampling technique on SWAT-simulated stre-amflow[J]. Applied Geography,2015,(63):357-368.
[17] Geza M,J E Mccray. Effects of soil data resolution on SWAT modelstream flow and water quality predictions[J]. Journal of Environmen-tal Management,2008,88(3):393-406.
[2]刘春雨,陈星,向龙.伊逊河流域土地不同利用方式的水文效应模拟[J].人民长江,2016,47(10):31-36.
[3]李鸿儒,卢远,何文.钦江流域土地利用/覆被变化对径流产沙的影响[J].中国水土保持,2016,(4):40-43.
[4]王潺,杨国范,林茂森.土地利用变化对牤牛河流域径流的影响[J].人民长江,2017,48(8):32-37.
[5]黄沛然,汤玲英.基于SWAT模型的金华江上游土地利用变化对径流影响的研究[J].水资源开发与管理,2017,(4):64-69.
[6]冉有华,李新,卢玲.四种常用的全球1km土地覆盖数据中国区域的精度评价[J].冰川冻土,2009,31(3):490-500.
[7]樊琨,泾河上游区SWAT模型径流模拟与参数移植方法研究[D].陕西杨凌:西北农林科技大学,2015.
[8]郑倩,史海滨,李仙岳,等. SWAT水文模型在灌区水文和物质模拟中的研究进展[J].节水灌溉,2015,(9):70-73.
[9] Murty P S A Pandey,S Suryavanshi. Application of semi-distributedhydrological model for basin level water balance of the Ken basin ofCentral India[J]. Hydrological Processes,2014,28(13):4 119-4 129.
[10]钱坤,叶水根,朱琴.基于SWAT模型的房山区不同情景方案下的蒸腾蒸发模拟[J].农业工程学报,2011,27(1):99-105.
[11]金鑫,陈琼,金彦香.土地利用/覆被数据精度对流域水文过程模拟的影响研究[J].灌溉排水学报,2018,37(2):108-115.
[12] Moriasi D N,J G Arnold,M W Van Liew,et al. Model EvaluationGuidelines for Systematic Quantification of Accuracy in WatershedSimulations[J]. Transactions of the ASABE,2007,50(3):885-900.
[13]宁吉才,刘高焕,刘庆生,等.水文响应单元空间离散化及SWAT模型改进[J].水科学进展,2012,23(1):14-20.
[14]叶许春,张奇,刘健,等.土壤数据空间分辨率对水文过程模拟的影响[J].地理科学进展,2009,(4):575-583.
[15] Zheng Shen,Qian Hong,Hong Yu,et al. Parameter uncertaintyanalysis of the non-point source pollution in the Daning River water-shed of the Three Gorges Reservoir Region,China[J].Science of theTotal Environment,2008,(405):195-205.
[16] Tan M L,Darren Ficklin,Barnali Dixon,et al. Impacts of DEM res-olution,source,and resampling technique on SWAT-simulated stre-amflow[J]. Applied Geography,2015,(63):357-368.
[17] Geza M,J E Mccray. Effects of soil data resolution on SWAT modelstream flow and water quality predictions[J]. Journal of Environmen-tal Management,2008,88(3):393-406.