Welcome to Journal of University of Chinese Academy of Sciences，Today is
RSS 中文

Journal of University of Chinese Academy of Sciences >

2021 , Vol. 38 >Issue 5: 590 - 600

DOI: https://doi.org/10.7523/j.issn.2095-6134.2021.05.003

Research Articles

Multi-objective calibration and evaluation of SWAT modela case study in Meichuan River basin

  • LI Jing ,
  • MA Tianxiao ,
  • LU Yanru ,
  • SONG Xianfeng ,
  • LI Runkui ,
  • LIU Junzhi ,
  • DUAN Zheng
Expand
  • 1. College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China;
    2. State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;
    3. Key Laboratory of Quantitative Remote Sensing Information Technology of CAS, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China;
    4. Key Laboratory of Virtual Geographic Environment of Ministry of Education, Nanjing Normal University, Nanjing 210023, China;
    5. Department of Physical Geography and Ecosystem Science, Lund University, Lund 22362, Sweden

Received date: 2019-12-16

  Revised date: 2020-03-19

  Online published: 2021-09-13

Fold

Abstract

SWAT model calibrated by streamflow data from gauging stations often provides a relatively high accuracy of hydrologic simulation, nevertheless those calibrated model parameters are still with uncertainty, particularly in the area with sparse gauging stations where the compensation between parameters would make SWAT model deeply disturbed by the phenomenon of equifinality. In this paper, a multi-objective calibration method is proposed to calibrate SWAT model and improve modeling quality by using leaf area index (LAI) from remote sensing data. Generally, vegetation has a crucial impact on eco-hydrological process that is also the core component of hydrological process. Therefore, the calibration of vegetation module facilitates to increase the precision of hydrologic model output. In-situ measured streamflow data is usually collected at gauging points, while remote sensed data is a snapshot over a large space. So LAI data may presents much more spatial details in the model other than streamflow data. The test was carried out with streamflow, crop yield yearbook, and MODIS LAI datasets in the Meichuan River basin, and the results showed that the multi-objective method significantly reduced the impact of equifinality on model parameters and improved the simulation accuracy as well as the robustness of the SWAT model because it took full advantages of vegetation remote sensing and concerned the great role of vegetation in hydrological process.

Key words： SWAT model; equifinality; multi-objective optimization; leaf area index; crop yield

Cite this article

LI Jing , MA Tianxiao , LU Yanru , SONG Xianfeng , LI Runkui , LIU Junzhi , DUAN Zheng . Multi-objective calibration and evaluation of SWAT modela case study in Meichuan River basin[J]. Journal of University of Chinese Academy of Sciences, 2021 , 38(5) : 590 -600 . DOI: 10.7523/j.issn.2095-6134.2021.05.003

References

[1] 罗开盛, 陶福禄. 黑河流域1995-2014年县域水资源压力评价[J]. 中国科学院大学学报, 2018, 35(2):172-179.
[2] 吕乐婷, 彭秋志, 郭媛媛, 等. 基于SWAT模型的东江流域径流模拟[J]. 自然资源学报, 2014, 29(10):1746-1757.
[3] 张蕾, 卢文喜, 安永磊, 等. SWAT模型在国内外非点源污染研究中的应用进展[J]. 生态环境学报, 2009, 18(6):2387-2392.
[4] 郭军庭, 张志强, 王盛萍, 等. 应用SWAT模型研究潮河流域土地利用和气候变化对径流的影响[J]. 生态学报, 2014, 34(6):1559-1567.
[5] Khelifa W B, Hermassi T, Strohmeier S, et al. Parameterization of the effect of bench terraces on runoff and sediment yield by SWAT modeling in a small semi-arid watershed in Northern Tunisia[J]. Land Degradation & Development, 2017, 28(5):1568-1578.
[6] 周建中, 卢韦伟, 孙娜, 等. 水文模型参数多目标率定及最优非劣解优选[J]. 水文, 2017, 37(2):1-7.
[7] Abbaspour K C, Yang J, Maximov I, et al. Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT[J]. Journal of Hydrology, 2007, 333(2-4):413-430.
[8] Park G A, Park J Y, Joh H K, et al. Evaluation of mixed forest evapotranspiration and soil moisture using measured and swat simulated results in a hillslope watershed[J]. KSCE Journal of Civil Engineering, 2014, 18(1):315-322.
[9] Beven K. Prophecy, reality and uncertainty in distributed hydrological modelling[J]. Advances in Water Resources, 1993, 16(1):41-51.
[10] 杨凯杰, 吕昌河. SWAT模型应用与不确定性综述[J]. 水土保持学报, 2018, 32(1):17-24,31.
[11] Bai J W, Shen Z Y, Yan T Z. A comparison of single-and multi-site calibration and validation:a case study of SWAT in the Miyun Reservoir watershed, China[J]. Frontiers of Earth Science, 2017, 11(3):592-600.
[12] Nkiaka E, Nawaz N R, Lovett J C. Effect of single and multi-site calibration techniques on hydrological model performance, parameter estimation and predictive uncertainty:a case study in the Logone catchment, Lake Chad basin[J]. Stochastic Environmental Research and Risk Assessment, 2018, 32(6):1665-1682.
[13] Shrestha M K, Recknagel F, Frizenschaf J, et al. Assessing SWAT models based on single and multi-site calibration for the simulation of flow and nutrient loads in the semi-arid Onkaparinga catchment in South Australia[J]. Agricultural Water Management, 2016, 175:61-71.
[14] Odusanya A E, Mehdi B, Schürz C, et al. Multi-site calibration and validation of SWAT with satellite-based evapotranspiration in a data-sparse catchment in southwestern Nigeria[J]. Hydrology and Earth System Sciences, 2019, 23(2):1113-1144.
[15] Gong Y W, Shen Z Y, Liu R W, et al. A comparison of single and multi-gauge based calibrations for hydrological modeling of the Upper Daning River Watershed in China's Three Gorges Reservoir Region[J]. Hydrology Research, 2012, 43(6):822-832.
[16] Molina-Navarro E, Andersen H E, Nielsen A, et al. The impact of the objective function in multi-site and multi-variable calibration of the SWAT model[J]. Environmental Modelling & Software, 2017, 93:255-267.
[17] Wanders N, Bierkens M F P, de Jong S M, et al. The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models[J]. Water Resources Research, 2014, 50(8):6874-6891.
[18] Zhang J, Li Q N, Guo B B, et al. The comparative study of multi-site uncertainty evaluation method based on SWAT model[J]. Hydrological Processes, 2015, 29(13):2994-3009.
[19] 芮孝芳.论流域水文模型[J]. 水利水电科技进展, 2017, 37(4):1-7,58.
[20] Li Y, Grimaldi S, Pauwels V R N, et al. Hydrologic model calibration using remotely sensed soil moisture and discharge measurements:The impact on predictions at gauged and ungauged locations[J]. Journal of Hydrology, 2018, 557:897-909.
[21] Tuo Y, Marcolini G, Disse M, et al. A multi-objective approach to improve SWAT model calibration in alpine catchments[J]. Journal of Hydrology, 2018, 559:347-360.
[22] 何柯琪, 高超, 谢京凯, 等. 基于径流和积雪资料的水文模型多目标率定[J]. 水力发电学报, 2019, 38(3):65-74.
[23] Kunnath-Poovakka A, Ryu D, Renzullo L J, et al. The efficacy of calibrating hydrologic model using remotely sensed evapotranspiration and soil moisture for streamflow prediction[J]. Journal of Hydrology, 2016, 535:509-524.
[24] 杨大文, 雷慧闽, 丛振涛. 流域水文过程与植被相互作用研究现状评述[J]. 水利学报, 2010, 41(10):1142-1149.
[25] 陈喜,宋琪峰,高满, 等.植被-土壤-水文相互作用及生态水文模型参数的动态表述[J]. 北京师范大学学报(自然科学版), 2016, 52(3):362-368.
[26] 赖格英, 仇霖, 张智勇, 等. 基于多植物生长模式的SWAT模型的修正与有效性初探[J]. 湖泊科学, 2018, 30(2):472-487.
[27] Zhou X V, Clark C D, Nair S S, et al. Environmental and economic analysis of using SWAT to simulate the effects of switchgrass production on water quality in an impaired watershed[J]. Agricultural Water Management, 2015, 160:1-13.
[28] Abbaspour K C, Vejdani M, Haghighat S, et al. SWAT-CUP calibration and uncertainty programs for SWAT[C]//MODSIM 2007 International Congress on Modelling and Simulation, Modelling and Simulation Society of Australia and New Zealand. 2007:1596-1602.
[29] Abbaspour K C, Rouholahnejad E, Vaghefi S, et al. A continental-scale hydrology and water quality model for Europe:calibration and uncertainty of a high-resolution large-scale SWAT model[J]. Journal of Hydrology, 2015, 524:733-752.
[30] Rajib M A, Merwade V, Yu Z Q. Multi-objective calibration of a hydrologic model using spatially distributed remotely sensed/in-situ soil moisture[J]. Journal of Hydrology, 2016, 536:192-207.
[31] Emelyanova I V, McVicar T R, van Niel T G, et al. Assessing the accuracy of blending Landsat-MODIS surface reflectances in two landscapes with contrasting spatial and temporal dynamics:a framework for algorithm selection[J]. Remote Sensing of Environment, 2013, 133:193-209.
[32] Ma T, Duan Z, Li R, et al. Enhancing SWAT with remotely sensed LAI for improved modelling of ecohydrological process in subtropics[J]. Journal of Hydrology, 2019, 570:802-815.
[33] Cai X L, Sharma B R. Integrating remote sensing, census and weather data for an assessment of rice yield, water consumption and water productivity in the Indo-Gangetic river basin[J]. Agricultural Water Management, 2010, 97(2):309-316.
[34] 杨建莹, 霍治国, 邬定荣, 等. 基于MODIS和SEBAL模型的黄淮海平原冬小麦水分生产力研究[J]. 中国农业气象, 2017, 38(7):435-446.
[35] Duan Z, Bastiaanssen W G M. First results from Version 7 TRMM 3B43 precipitation product in combination with a new downscaling-calibration procedure[J]. Remote Sensing of Environment, 2013, 131:1-13.
[36] 左德鹏, 徐宗学. 基于SWAT模型和SUFI-2算法的渭河流域月径流分布式模拟[J]. 北京师范大学学报(自然科学版), 2012, 48(5):490-496.
[37] Qiu L J, Zheng F L, Yin R S. SWAT-based runoff and sediment simulation in a small watershed, the loessial hilly-gullied region of China:capabilities and challenges[J]. International Journal of Sediment Research, 2012, 27(2):226-234.
[38] Zhang X S, Srinivasan R, Bosch D. Calibration and uncertainty analysis of the SWAT model using Genetic Algorithms and Bayesian Model Averaging[J]. Journal of Hydrology, 2009, 374(3/4):307-317.
[39] Narsimlu B, Gosain A K, Chahar B R, et al. SWAT model calibration and uncertainty analysis for streamflow prediction in the Kunwari River basin, India, using sequential uncertainty fitting[J]. Environmental Processes, 2015, 2(1):79-95.
[40] 梁珂, 阚光远, 李致家. 新型耦合数据驱动模型在降雨径流模拟中的应用研究[J]. 水文, 2016, 36(4):1-7.
[41] Bosznay M. Generalization of SCS curve number method[J]. Journal of Irrigation and Drainage Engineering, 1989, 115(1):139-144.
[42] 林炳青, 陈莹, 陈兴伟.SWAT模型水文过程参数区域差异研究[J]. 自然资源学报, 2013, 28(11):1988-1999.
Options
Outlines

/

〈 〉

Copyright © Journal of University of Chinese Academy of Sciences

Support by Beijing Magtech Co.ltd support@magtech.com.cn