基于多源遥感数据的艾比湖流域盐土SWAT模型参数修正

在SWAT（soil and water assessment tool）模型模拟地表分量过程中，常默认土壤剖面电导率（electrical conductivity，EC）值为0或0.1，将其应用于土壤盐渍化程度较高的流域时，不符合下垫面实际情况。为确保水文模拟逼近真实地表模拟过程，进一步提高模拟精度，该文利用GF-1号卫星16m分辨率多光谱遥感影像结合分类回归树法反演艾比湖流域区域尺度0～100cm土壤剖面电导率，模拟值与实测值均方根最大值误差为4.81dS/m，相对误差最大值为15.17%。模拟值用于修正EC值，结果表明：EC值修正后的SWAT模型土壤水分模拟值，较修正前模拟值精度提高2...

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Bibliographic Details
Published in农业工程学报 Vol. 33; no. 23; pp. 139 - 144
Main Author 王瑾杰;丁建丽;张喆;陈文倩
Format Journal Article
LanguageChinese
Published 新疆交通职业技术学院,乌鲁木齐 831401 2017
新疆大学绿洲生态教育部重点实验室,乌鲁木齐 830046%新疆大学资源与环境科学学院智慧城市与环境建模自治区普通高校重点实验室,乌鲁木齐 830046
新疆大学生态学科博士后科研流动站,乌鲁木齐 830046
新疆大学绿洲生态教育部重点实验室,乌鲁木齐 830046%新疆大学生态学科博士后科研流动站,乌鲁木齐 830046
新疆大学资源与环境科学学院智慧城市与环境建模自治区普通高校重点实验室,乌鲁木齐 830046
新疆大学绿洲生态教育部重点实验室,乌鲁木齐 830046
Subjects
土壤;电导率;遥感;盐渍化;SWAT模型;GF-1
盐渍化
GF-1
电导率
SWAT model
SWAT模型
remote sensing
遥感
soils
electrical conductivity
土壤
salinization
Online AccessGet full text
ISSN1002-6819
DOI10.11975/j.issn.1002-6819.2017.23.018

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Summary:在SWAT（soil and water assessment tool）模型模拟地表分量过程中，常默认土壤剖面电导率（electrical conductivity，EC）值为0或0.1，将其应用于土壤盐渍化程度较高的流域时，不符合下垫面实际情况。为确保水文模拟逼近真实地表模拟过程，进一步提高模拟精度，该文利用GF-1号卫星16m分辨率多光谱遥感影像结合分类回归树法反演艾比湖流域区域尺度0～100cm土壤剖面电导率，模拟值与实测值均方根最大值误差为4.81dS/m，相对误差最大值为15.17%。模拟值用于修正EC值，结果表明：EC值修正后的SWAT模型土壤水分模拟值，较修正前模拟值精度提高23.84个百分点。该方法在实现SWAT模型参数本地化的同时，有效提高了土壤水分模拟精度，可为土壤盐渍化区域水文模拟提供参考。
Bibliography:11-2047/S
soils; electrical conductivity; remote sensing; salinization; SWAT model; GF-1
SWAT model is one of the most widely used hydrological models in the world.The electrical conductivity(EC)is defaulted as0or0.1,which might be not suitable for the soils with high salinity.In this study,we tested the feasibility of SWAT model with default EC values in simulating soil moisture and proposed a method to modify model parameters.The study area was Ebinur Lake Watershed.The watershed was located in Xinjiang with little rainfall and full sunshine.The evaporation was high.In the recent10years,the environment around the watershed was deteriorated,threatening sustainable development.The soil EC inversion was obtained by GF-116m WFV hyperspectral remote sensing images.Different bands were used for calculation of vegetation index,soil index,salinity index and saturation.Then,these were used to build EC inversion model by the classification and regression tree method.The inversion values were compared with measured valu
ISSN:1002-6819
DOI:10.11975/j.issn.1002-6819.2017.23.018