Evapotranspiration Mapping in a Heterogeneous Landscape Using Remote Sensing and Global Weather Datasets: Application to the Mara Basin, East Africa

Abstract

Actual evapotranspiration (ET) is a major water use flux in a basin water balance with crucial significance for water resources management and planning. Mapping ET with good accuracy has been the subject of ongoing research. Such mapping is even more challenging in heterogeneous and data-scarce regions. The main objective of our research is to estimate ET using daily Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature and Global Land Data Assimilation System (GLDAS) weather datasets based on the operational simplified surface energy balance (SSEBop) algorithm at a 1-km spatial scale and 8-day temporal resolution for the Mara Basin (Kenya/Tanzania). Unlike previous studies where the SSEBop algorithm was used, we use a seasonally-varying calibration coefficient for determining the "cold" reference temperature. Our results show that ET is highly variable, with a high inter-quartile range for wetlands and evergreen forest (24% to 29% of the median) and even up to 52% of the median for herbaceous land cover and rainfed agriculture. The basin average ET accounts for about 66% of the rainfall with minimal inter-annual variability. The basin scale validation using nine-years of monthly, gridded global flux tower-based ET (GFET) data reveals that our ET is able to explain 64% of the variance in GFET while the MOD16-NB (Nile Basin) explains 72%. We also observe a percent of bias (PBIAS) of 1.1% and 2.8%, respectively for SSEBop ET and MOD16-NB, indicating a good reliability in the ET estimates. Additionally, the SSEBop ET explains about 52% of the observed variability in the Normalized Difference Vegetation Index (NDVI) for a 16-day temporal resolution and 81% for the annual resolution, pointing to an increased reliability for longer aggregation periods. The annual SSEBop ET estimates are also consistent with the underlying primary (i.e., water and energy) and secondary (i.e., soil, topography, geology, land cover, etc.) controlling factors across the basin. This paper demonstrated how to effectively estimate and evaluate spatially-distributed and temporally-varying ET in data-scarce regions that can be applied elsewhere in the world where observed hydro-meteorological variables are limited.

An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

“…The latter mainly depends on the remotely sensed land surface temperature and the grass reference evapotranspiration (Senay et al, 2013). Alemayehu et al (2017) demonstrated that the SSEBop ET for the study area explained about 52, 63 and 81 % of the observed variability in the MODIS NDVI at 16-day, monthly and annual temporal resolution. Also, they suggested that the estimated ET can be used for hydrological model parameterization.…”

Comparing Remotely-Sensed Surface Energy Balance Evapotranspiration Estimates in Heterogeneous and Data-Limited Regions: A Case Study of Tanzania’s Kilombero Valley

“…For example, land surface ET accounts for approximately 60% of the mean annual land precipitation in the global hydrological cycle [2]. Studies of ET in irrigated agricultural areas have reported the mean annual (actual) ET to accounts for more than 60% of the mean annual precipitation [4,5].…”

Satellite Psychrometric Formulation of the Operational Simplified Surface Energy Balance (SSEBop) Model for Quantifying and Mapping Evapotranspiration

“…With a one-time calibration for bias removal, the model is capable of processing historical remote sensing data going back to 1984 (Senay et al, 2017). Similarly, Alemayehu et al (2017) demonstrated the effectiveness of the two-parameter formulation for ET mapping in the Mara Basin, a hydro-climatically complex system in East Africa.…”