水土与地表过程

土壤数据空间分辨率对水文过程模拟的影响

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  • 1. 中国科学院南京地理与湖泊研究所 湖泊与环境国家重点实验室|南京 210008;
    2. 中国科学院研究生院|北京 100049
叶许春(1982-)|男|安徽潜山人|博士研究生|主要研究方向为流域水文模型的应用。E-mail:yxch2500@163.com

网络出版日期: 2009-07-25

基金资助

中国科学院知识创新工程重大项目(KZCX2-YW-337,KZCX1-YW-08-01);国家自然科学基金项目(40871026)

Effects of Spatial Resolution of Soil Data on Hydrological Processes Modeling

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  • 1. Nanjing Institute of Geography and Limnology, State Key Laboratory of Lake Science and Environment|Nanjing 210008, China; 2. Graduate University of Chinese Academy of Sciences|Beijing 100049, China

Online published: 2009-07-25

摘要

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。

本文引用格式

叶许春1,2|张奇1|刘健1,2|李丽娇1,2|左海军1,2 . 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 , 28(4) : 575 -583 . DOI: 10.11820/dlkxjz.2009.04.013

Abstract

The prediction accuracy of a distributed hydrological model depends on how well the model input spatial data describe the characteristics of the watershed. Especially, in a large scale catchment, could a higher resolution of input data contribute to a more accurate result? As an important component of input data, soil information directly impacts the accuracy of the simulation of hydrologic model. In this study, surveyed soil data with two different spatial resolutions were used as input data for a SWAT model simulation in a large scale catchment of Xinjiang River basin (15535km2) in China. Simulations of stream flow, soil water storage and evapotranspiration using the two soil datasets were compared, and the applicability of fine resolution of soil data was analysed. The results indicate that the different resolutions of soil data have a great impact on the distribution of hydrological response units in the SWAT model, but show no obvious differences in stream flow simulation and evapotranspiration (ET). Our observations also show that the lower resolution data improved slightly in average monthly stream flow simulation before and after calibration, but there is no substantial difference. The finer resolution data produced a higher monthly soil water storage (SW) simulation than the lower resolution data across the whole watershed during the simulating period. Results also show that the evapotranspiration calculation method in the SWAT model is insensitive to soil resolution. The implications of this study are that improvement of the resolution of soil data does not necessarily contribute to a more accurate prediction of streamflow in large scale catchments. In practical studies, modellers need to select an appropriate resolution of soil data depending on the scale of watershed and the level of accuracy required, and also need to consider the principle of the model and the physical meanings of some key parameters to explain the simulation result.

参考文献


[1]  Helge Bormann. Sensitivity of a soil-vegetation-atmosphere-transfer scheme to input data resolution and data classification. Journal of Hydrology, 2008, 351∶ 154-169.

[2]  Romanowicz A A, Vanclooster M, Rounsevell M, et al. Sensitivity of the SWAT model to the soil and land use data parameterization: A case study in the Thyle catchment, Belgium. Ecological Modeling, 2005,187:27-39.

[3]  Chaplot V. Impact of DEM mesh size and soil map precision for the prediction of water, sediment and NO3 loads in a watershed. Journal of Hydrology, 2005, 312: 207-222.

[4]  Band L E, Moore I D. Scale: landscape attributes and geographical information systems. Hydrological Processes, 1995, 9: 401-422.

[5]  Seyfried M. Spatial variability constructions to modeling soil water at different scales. Geoderma, 1998, 85:231-254.

[6]  Muttiah R S, Wurbs R A. Scale-dependent soil and climate variability effects on watershed water balance of the SWAT mode1.Journal of Hydrology, 2003, 256(3-4):264-285.

[7]  Zhu A X, Mackay D S. Effects of spatial detail of soil information on watershed modeling. Journal of Hydrology, 2001, 248(1-4): 54-77.

[8]  Peck A J, Luxmoore R J, Stolzy J L. Effects of spatial variability of soil hydraulic properties in water modeling. Water Resoure, 1997, 13(2): 348-354.

[9]  Peschel J M, Haan K P, Lacey R E. A SSURGO preprocessing extension for the ArcView Soil and Water Assessment too1. ASAE Meeting Presentation, Paper No.032123, Las Vegas, NV, 2003, July: 27-30.

[10] Wang X, Melesse A M. Effects of STATSGO and SSURGO as inputs on SWAT model’s snowmelt simulation. Journal of American Water Resources Association, 2006, 42 (5): 1217-1236.

[11] Geza Mengistu, McCray J E. Effects of soil data resolution on SWAT model stream flow and water quality predictions. Journal of Environmental Management, 2008, 88:393-406

[12] Guo H, Hu Q, Jiang T. Annual and seasonal stream flow responses to climate and land-cover changes in the Poyang Lake basin, China. Journal of Hydrology, 2008, 355: 106-122.

[13]史学正, 于东升, 高鹏, 等. 中国土壤信息系统(SISChin)及其应用基础研究. 土壤, 2007, 39(3):329-333.

[14] Shi X Z, Yu D S, Warner E D, et al. Cross-Reference System for translating between genetic soil classification of China and soil taxonomy. Soil Sci. Soc. Am.J. 2006, 70(1):78-83.

[15] Shi X Z, Yu D S, Warner E D, et al. Soil Database of 1∶1,000,000 digital soil survey and reference system of the Chinese genetic soil classification system. Soil Survey Horizons, 2004, 45(4):129-136.

[16] Levick L R, Semmens D J, Guertin D P, et al. Adding global soils data to the automated geospatial watershed assessment tool (AGWA)
[C/CD]. Second International Symposium on Transboundary Waters Management, Tucson, AZ, 2004, November 16-19: 8.

[17] 李润奎, 朱阿兴, Peter, 等. SWAT模型对高精度土壤信息的敏感性研究. 地球信息科学, 2007, 9(3):72-90.

[18] Zhang W, Montgomery D R. Digital elevation model grid size, landscape representation, and hydrologic simulations. Water Resources Research, 1994, 30: 1019-1028.

[19] 吴军, 张万昌. DEM分辨率对AVSWAT2000径流模拟的敏感性分析. 遥感信息, 2007, 3: 8-13.

[20] 郝芳华, 程红光, 杨胜天. 非点源污染模型: 理论方法与应用. 北京: 中国环境科学出版社, 2006:62-118.

[21] 王中根, 刘昌明, 黄友波. SWAT模型的原理、结果及应用研究. 地理科学进展, 2003,22(1):79-86.

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