Congrats to Rosangela for MS thesis!
I'm very happy to report that LCB M.S. student Rosangela Carreon has successfully defended her thesis and filed it in time for Dec 2020 completion. Rosangela's work involved collaboration with Universidad Nacional Agraria and the Centro Humboldt (both located in Managua, Nicaragua). I’ll let Rosangela tell you about it, as she wrote in her abstract below:
This thesis integrated remote sensing and gridded data products with a small network of precipitation data with the intended goal of conducting a hydrologic assessment in the tropical country of Nicaragua. The objective of chapter 1 was to find a representative gridded precipitation product that could be distributed across the tropical country of Nicaragua for further hydrological assessment. Using a small network of stations along the north-northwest region of Nicaragua as reference, I evaluated two gridded precipitation datasets: the Tropical Rainfall Measuring Mission (TRMM) and the Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS). Based on stronger correlation and agreement between observation data from station and estimated data from CHIRPS at the monthly and seasonal temporal scales, I determined that CHIRPS provided a better characterization of the variability in precipitation collected at the meteorological stations.
The objective of chapter 2 was to evaluate water flux from sources (e.g. rainfall) to sinks (e.g. evapotranspiration, ET) and basin-system response from perturbed forest cover. I used three gridded datasets: precipitation from Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), evapotranspiration from the Operational Simplified Surface Energy Balance model (SSEBop), and Global Forest Watch forest fraction. Four pairs of basins were evaluated along the north and east of Nicaragua between 2003-2019. Findings determined basins on the east and north experienced increasingly dry conditions over time, whereas basins in the south were getting wetter. Across all basins, forest cover was variable, with decreasing forest cover largely observed on the Caribbean east. With a negative relationship, precipitation was the most important influence on the evaporative index (the ratio of ET to precipitation). However, the addition of the covariate of forest fraction improved the model and indicated forest loss reduced evapotranspiration.
