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

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.

[1]  Martin Volk,et al.  Using precipitation data ensemble for uncertainty analysis in SWAT streamflow simulation , 2012 .

[2]  H. G. Baker,et al.  SOIL AND STEM WATER STORAGE DETERMINE PHENOLOGY AND DISTRIBUTION OF TROPICAL DRY FOREST TREES ' , 2007 .

[3]  D. Diner,et al.  Estimation of vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from atmosphere‐corrected MISR data , 1998 .

[4]  John R. Williams,et al.  The EPIC crop growth model , 1989 .

[5]  Robert J. Marquis,et al.  6. Vegetation Physiognomies and Woody Flora of the Cerrado Biome , 2002 .

[6]  Jeffrey G. Arnold,et al.  Soil and Water Assessment Tool Theoretical Documentation Version 2009 , 2011 .

[7]  A. Belward,et al.  The Best Index Slope Extraction ( BISE): A method for reducing noise in NDVI time-series , 1992 .

[8]  F. Reinstorf,et al.  Measuring methods for groundwater, surface water and their interactions: a review , 2006 .

[9]  S. G. Thampi,et al.  Influence of Scale on SWAT Model Calibration for Streamflow in a River Basin in the Humid Tropics , 2010 .

[10]  F. H. Frimmel,et al.  Challenges of an integrated water resource management for the Distrito Federal, Western Central Brazil: climate, land-use and water resources , 2012, Environmental Earth Sciences.

[11]  B. Bache,et al.  Soil and Water , 1971, Nature.

[12]  Osmar Abílio de Carvalho Júnior,et al.  Mapa pedológico digital - SIG atualizado do Distrito Federal Escala 1:100.000 e uma síntese do texto explicativo , 2004 .

[13]  Steven W. Running,et al.  Effects of precipitation and soil water potential on drought deciduous phenology in the Kalahari , 2004 .

[14]  B. Poulter,et al.  Satellite remote sensing of tropical forest canopies and their seasonal dynamics , 2009 .

[15]  H. Sansom,et al.  Tropical climatology — An introduction to the climates of the low latitudes , 1977 .

[16]  R. J. Baker,et al.  Grain filling in three spring wheat genotypes: statistical analysis , 1990 .

[17]  Martin Volk,et al.  The impact of Best Management Practices on simulated streamflow and sediment load in a Central Brazilian catchment. , 2013, Journal of environmental management.

[18]  S. Nieuwolt,et al.  Tropical climatology: An introduction to the climates of the low latitudes , 1978 .

[19]  A. Young,et al.  Tropical Soils and Soil Survey. , 1978 .

[20]  T. Vangpaisal,et al.  Suitability of SWAT Model for Simulating of Monthly Streamflow in Lam Sonthi Watershed , 2012 .

[21]  Christian Floret,et al.  Plant phenology in relation to water availability: herbaceous and woody species in the savannas of northern Cameroon , 1995, Journal of Tropical Ecology.

[22]  Elaine Cristina Cardoso Fidalgo,et al.  PEDOTRANSFER FUNCTIONS FOR ESTIMATING SOIL BULK DENSITY FROM EXISTING SOIL SURVEY REPORTS IN BRAZIL , 2007 .

[23]  Tammo S. Steenhuis,et al.  A multi basin SWAT model analysis of runoff and sedimentation in the Blue Nile, Ethiopia , 2010 .

[24]  S. Childes,et al.  Phenology of nine common woody species in semi-arid, deciduous Kalahari Sand vegetation , 2004, Vegetatio.

[25]  V. T. Chow Open-channel hydraulics , 1959 .

[26]  J. Thornley,et al.  An open-ended logistic-based growth function , 2005 .

[27]  O. A. Santana,et al.  Contribuição da vegetação rasteira na evapotranspiração total em diferentes ecossistemas do bioma cerrado, Distrito Federal. , 2010 .

[28]  Frederick C. Meinzer,et al.  Seasonal leaf dynamics across a tree density gradient in a Brazilian savanna , 2005, Oecologia.

[29]  Kellie B. Vaché,et al.  Model intercomparison to explore catchment functioning: Results from a remote montane tropical rainforest , 2012 .

[30]  Carlos Alberto da Silva Oliveira,et al.  Comparação da evapotranspiração real simulada e observada em uma bacia hidrográfica em condições naturais de cerrado , 2001 .

[31]  John R. Williams,et al.  LARGE AREA HYDROLOGIC MODELING AND ASSESSMENT PART I: MODEL DEVELOPMENT 1 , 1998 .

[32]  Jeffrey G. Arnold,et al.  Model Evaluation Guidelines for Systematic Quantification of Accuracy in Watershed Simulations , 2007 .

[33]  Guillermo Sarmiento,et al.  Phenological Strategies of Plant Species in the Tropical Savanna and the Semi-Deciduous Forest of the Venezuelan Llanos , 1976 .

[34]  Bernd Diekkrüger,et al.  Analyzing the effects of different soil databases on modeling of hydrological processes and sediment yield in Benin (West Africa) , 2012 .

[35]  S. H. Bullock,et al.  Phenology of canopy trees of a tropical deciduous forest in México. , 1990 .

[36]  Yu Zhang,et al.  Prototyping of MODIS LAI and FPAR algorithm with LASUR and LANDSAT data , 2000, IEEE Trans. Geosci. Remote. Sens..

[37]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[38]  D. Roy,et al.  An overview of MODIS Land data processing and product status , 2002 .

[39]  J. Tomasella,et al.  Pedotransfer functions for tropical soils , 2004 .

[40]  J. Kirchner Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology , 2006 .

[41]  T. Giambelluca,et al.  Controls on stand transpiration and soil water utilization along a tree density gradient in a Neotropical savanna , 2008 .

[42]  S. Running,et al.  Regional evaporation estimates from flux tower and MODIS satellite data , 2007 .

[43]  Maosheng Zhao,et al.  Development of a global evapotranspiration algorithm based on MODIS and global meteorology data , 2007 .

[44]  P. Beck,et al.  Improved monitoring of vegetation dynamics at very high latitudes: A new method using MODIS NDVI , 2006 .

[45]  G. Goldstein,et al.  Plant- and stand-level variation in biophysical and physiological traits along tree density gradients in the Cerrado , 2008 .

[46]  T. Giambelluca,et al.  Evapotranspiration and energy balance of Brazilian savannas with contrasting tree density , 2009 .

[47]  Karl Schneider,et al.  Technical Note: Hydrological Modeling with SWAT in a Monsoon-Driven Environment: Experience from the Western Ghats, India , 2011 .

[48]  Raghavan Srinivasan,et al.  SWAT: Model Use, Calibration, and Validation , 2012 .

[49]  Jeffrey G. Arnold,et al.  The Soil and Water Assessment Tool: Historical Development, Applications, and Future Research Directions , 2007 .

[50]  R. Machado,et al.  Conservation of the Brazilian Cerrado , 2005 .

[51]  Damien Arvor,et al.  Convective activity in Mato Grosso state (Brazil) from microwave satellite observations: Comparisons between AMSU and TRMM datasets , 2012 .

[52]  John R. Williams,et al.  A modeling approach to determining the relationship between erosion and soil productivity [EPIC, Erosion-Productivity Impact Calculator, mathematical models] , 1984 .

[53]  M. Schaap,et al.  ROSETTA: a computer program for estimating soil hydraulic parameters with hierarchical pedotransfer functions , 2001 .

[54]  Bernardo Friedrich Theodor Rudorff,et al.  Assessment of MODIS LAI retrievals over soybean crop in Southern Brazil , 2006 .

[55]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[56]  W. P. Lima,et al.  Comparative evapotranspiration of eucalyptus , pine and natural cerrado vegetation measure by the soil water balance method , 1990 .

[57]  E. Davidson,et al.  Deep root function in soil water dynamics in cerrado savannas of central Brazil , 2005 .

[58]  P. Atkinson,et al.  Inter-comparison of four models for smoothing satellite sensor time-series data to estimate vegetation phenology , 2012 .

[59]  J. Monteith Climate and the efficiency of crop production in Britain , 1977 .

[60]  R. C. Izaurralde,et al.  Historical Development and Applications of the EPIC and APEX Models , 2004 .

[61]  W. Hoffmann,et al.  Specific leaf area explains differences in leaf traits between congeneric savanna and forest trees , 2005 .

[62]  S. Running,et al.  Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data , 2002 .

[63]  K. Abbaspour,et al.  Estimation of freshwater availability in the West African sub-continent using the SWAT hydrologic model , 2008 .

[64]  Keith Beven,et al.  Prophecy, reality and uncertainty in distributed hydrological modelling , 1993 .

[65]  F. Reinstorf,et al.  Measuring methods for groundwater – surface water interactions: a review , 2006 .

[66]  J. Monteith Evaporation and environment. , 1965, Symposia of the Society for Experimental Biology.

[67]  R. Colwell Remote sensing of the environment , 1980, Nature.

[68]  C. Bernhofer,et al.  Spatiotemporal variability of grassland vegetation cover in a catchment in Inner Mongolia, China, derived from MODIS data products , 2011, Plant and Soil.