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SWAT plant growth modification for improved modeling of perennial vegetation in the tropics

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  • Strauch, Michael
  • Volk, Martin

Abstract

The Soil and Water Assessment Tool (SWAT) has been used for assessing the impact of land cover and land management changes on water resources for a wide range of scales and environmental conditions across the globe. However, originally designed for temperate regions, SWAT must be critically examined for its appropriate use in tropical watersheds. One major concern is the simulation of perennial tropical vegetation due to the absence of dormancy. While for temperate regions SWAT uses dormancy to terminate growing seasons of trees and perennials, seasonality in the tropics (wet and dry season) can only be represented by defining date or heat unit specific “plant” and “kill” operations which are fixed for every year of simulation. In this paper, we discuss these shortcomings and present an alternative approach to automatically initiate annual growing cycles based on changes in soil moisture. Furthermore, we propose a logistic leaf area index (LAI) decline function which approaches a user-defined minimum LAI instead of using the default function, which is not considering the minimum LAI. The modified SWAT model was tested based on MODIS LAI and evapotranspiration data for the Santa Maria/Torto watershed in Central Brazil, covered mostly by Cerrado (savanna) vegetation. Our model results show that the modified model can reasonably represent seasonal dynamics of the Cerrado biome. However, since the proposed changes are process-based but also allow flexible model settings (e.g. the beginning of growing cycles based on a soil moisture threshold adjustable for plant/land cover types), the modified plant growth module should be useful for large parts of the model community.

Suggested Citation

  • Strauch, Michael & Volk, Martin, 2013. "SWAT plant growth modification for improved modeling of perennial vegetation in the tropics," Ecological Modelling, Elsevier, vol. 269(C), pages 98-112.
    • Handle: RePEc:eee:ecomod:v:269:y:2013:i:c:p:98-112
    DOI: 10.1016/j.ecolmodel.2013.08.013
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    References listed on IDEAS

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    1. Gassman, Philip W. & Reyes, Manuel R. & Green, Colleen H. & Arnold, Jeffrey G., 2007. "The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions," ISU General Staff Papers 200701010800001027, Iowa State University, Department of Economics.
    2. Santosh Thampi & Kolladi Raneesh & T. Surya, 2010. "Influence of Scale on SWAT Model Calibration for Streamflow in a River Basin in the Humid Tropics," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4567-4578, December.
    3. Philip W. Gassman & Jimmy R. Williams & Verel W. Benson & R. César Izaurralde & Larry M. Hauck & C. Allan Jones & Jay D. Atwood & James Kiniry & Joan D. Flowers, 2005. "Historical Development and Applications of the EPIC and APEX Models," Center for Agricultural and Rural Development (CARD) Publications 05-wp397, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    4. Plesca, I. & Timbe, E. & Exbrayat, J.-F. & Windhorst, D. & Kraft, P. & Crespo, P. & Vaché, K.B. & Frede, H.-G. & Breuer, L., 2012. "Model intercomparison to explore catchment functioning: Results from a remote montane tropical rainforest," Ecological Modelling, Elsevier, vol. 239(C), pages 3-13.
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    Cited by:

    1. Lei Sun & Lizhe Yang & Lu Hao & Di Fang & Kailun Jin & Xiaolin Huang, 2017. "Hydrological Effects of Vegetation Cover Degradation and Environmental Implications in a Semiarid Temperate Steppe, China," Sustainability, MDPI, vol. 9(2), pages 1-20, February.
    2. Lee, Sangchul & Qi, Junyu & McCarty, Gregory W. & Anderson, Martha & Yang, Yun & Zhang, Xuesong & Moglen, Glenn E. & Kwak, Dooahn & Kim, Hyunglok & Lakshmi, Venkataraman & Kim, Seongyun, 2022. "Combined use of crop yield statistics and remotely sensed products for enhanced simulations of evapotranspiration within an agricultural watershed," Agricultural Water Management, Elsevier, vol. 264(C).
    3. Čerkasova, Natalja & White, Michael & Arnold, Jeffrey & Bieger, Katrin & Allen, Peter & Gao, Jungang & Gambone, Marilyn & Meki, Manyowa & Kiniry, James & Gassman, Philip W., 2023. "Field scale SWAT+ modeling of corn and soybean yields for the contiguous United States: National Agroecosystem Model Development," Agricultural Systems, Elsevier, vol. 210(C).
    4. Guanghui Li & Lei Chang & Haoye Li & Yuefen Li, 2023. "Modeling the Impact of Land Use Optimization on Non-Point Source Pollution: Evidence from Chinese Reservoir Watershed," Land, MDPI, vol. 13(1), pages 1-17, December.
    5. Michael Strauch & Rohini Kumar & Stephanie Eisner & Mark Mulligan & Julia Reinhardt & William Santini & Tobias Vetter & Jan Friesen, 2017. "Adjustment of global precipitation data for enhanced hydrologic modeling of tropical Andean watersheds," Climatic Change, Springer, vol. 141(3), pages 547-560, April.
    6. Lan Thanh Ha & Wim G. M. Bastiaanssen, 2023. "Determination of Spatially-Distributed Hydrological Ecosystem Services (HESS) in the Red River Delta Using a Calibrated SWAT Model," Sustainability, MDPI, vol. 15(7), pages 1-24, April.
    7. Strehmel, Alexander & Jewett, Amy & Schuldt, Ronja & Schmalz, Britta & Fohrer, Nicola, 2016. "Field data-based implementation of land management and terraces on the catchment scale for an eco-hydrological modelling approach in the Three Gorges Region, China," Agricultural Water Management, Elsevier, vol. 175(C), pages 43-60.

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