Publication Date


Date of Final Oral Examination (Defense)


Type of Culminating Activity


Degree Title

Master of Science in Hydrologic Sciences



Major Advisor

Alejandro N. Flores, Ph.D.


Jodi Brandt, Ph.D.


Nancy Glenn, Ph.D.


Matthew T. Masarik, Ph.D.

Creative Commons License

Creative Commons Attribution-NonCommercial 4.0 International License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License


Land cover acts as the gatekeeper to incoming and outgoing energy and water fluxes at the land surface, partitioning energy and water in accordance with the vegetation type and in response to atmospheric forcings. As Land Surface Models become more complex and more capable of simulating the coupled dynamics of the land-atmosphere system in greater spatial detail, the need for accurate representation of spatial distribution of vegetation types and their dynamics through time grows.

As humans modify land cover, there are complex dynamics at play between the vegetation, the surface energy balance and the cycling of water. The resultant hydroclimatic impacts of land cover change is dependent on local factors such as the local atmospheric forcings and the type of vegetation and land cover in question. Central Mozambique is a particularly useful setting to explore the impacts of changing land cover on climate because, since 2000, the country’s forests have been exploited by international corporations for timber extraction and conversion to agriculture. The region is of particular interest in the context of global climate dynamics and understanding land-atmosphere exchange because the monsoonal seasonality ties the incoming oceanic moisture to the land cover. As such, Mozambique has a relatively high recycling rate, with up to 20% of the precipitation resulting from evapotranspiration from the same area. More locally, as Mozambicans rely heavily on dryland crops without the use of irrigation, the amount and distribution of local rainfall can have a much greater impact on local people than in an area where water is redistributed through mechanical means.

In order to examine the role of these vegetation changes in the redistribution of energy fluxes and resultant rainfall redistribution, we have conducted a suite of numerical experiments to investigate the impact of deforestation on regional land-atmosphere interactions. In particular, we represented deforestation in Central Mozambique by merging data gleaned from the Global Forest Cover Change dataset with the USGS land cover dataset used within the Weather Research and Forecasting (WRF) model.

In this study, we created a quasi-State and Transition model to alter the WRF model land cover input map. We used both numerical and spatial information from a regridded version of the Global Forest Cover Change Dataset. We then applied a combination of random selection and heuristic rules to these statistical information to determine how each pixel of the WRF land cover should be altered for our deforestation scenario. We then ran simulations with both the control WRF land cover and modified land cover within the WRF model to determine the difference in hydroclimatic variables. We selected the time periods of 2001 and 2015 (a wet and dry year, respectively), and the months of March – May (the dry down period after the rainy season) to show a spectrum of atmospheric conditions for forcing of the model runs.

Our results indicate that our methodology underestimates deforestation, though even these underestimates of deforestation result in impacts on the local hydroclimate within the WRF model scenarios. The overall impact is a general increase in temperature and a redistribution and decrease in rainfall due to changes in the energy and water balances. All of these outcomes are variable, though, due to spatial patterns of deforestation, topography, and weather patterns. These results demonstrate the need for better representation of deforestation within land-atmosphere modeling.



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