Preprints
https://doi.org/10.5194/hess-2020-486
https://doi.org/10.5194/hess-2020-486

  02 Nov 2020

02 Nov 2020

Review status: a revised version of this preprint is currently under review for the journal HESS.

Simulating the Dry Chaco Hydrology under Deforestation Pressure

Michiel Maertens1, Gabriëlle J. M. De Lannoy1, Sebastian Apers1, Sujay V. Kumar2, and Sarith P. P. Mahanama2 Michiel Maertens et al.
  • 1KU Leuven, Department of Earth and Environmental Sciences, Belgium
  • 2NASA Goddard Space Flight Center, Maryland, USA

Abstract. Various regions in the world experience land cover and land use changes. One such a region is the Dry Chaco ecoregion in South America, characterized by deforestation and forest degradation since the 1980s. In this study, we simulated the water balance over the Dry Chaco and assessed the impact of land cover changes thereon, using three different state-of-the-art land surface models (LSMs) within the NASA Land Information System (LIS) with updated parameters. The default LIS parameters were revised with (i) improved soil parameters, (ii) satellite-based dynamic vegetation parameters instead of default climatological vegetation parameters, and (iii) yearly land cover information instead of static land cover. A relative comparison in terms of water budget components and ‘efficiency space’ for various baseline and revised experiments showed that large regional and long-term differences relate to different LSM structures, whereas smaller local differences resulted from updated soil, vegetation and land cover parameters. Furthermore, different LSM structures redistributed water differently in response to these parameter updates. A time series comparison of the simulations to independent satellite-based estimates of evapotranspiration and brightness temperature showed that no LSM setup significantly outperformed another for the entire region, and that not all LSM simulations improved with updated parameter values. However, the revised soil parameters generally reduced the simulated surface soil moisture bias relative to pixel-scale in situ observations, and the simulated Tb bias relative to regional Soil Moisture Ocean Salinity (SMOS) observations.

Michiel Maertens et al.

 
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Michiel Maertens et al.

Michiel Maertens et al.

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Short summary
In this study, we simulated the water balance over the South American Dry Chaco and assessed the impact of land cover changes thereon, using three different land surface models. Our simulations indicated that different models result in a different partitioning of the total water budget, but all showed an increase in soil moisture and percolation over the deforested areas. We also found that, relative to independent data, no specific land surface model is significantly better than another.