Analyses of potential evapotranspiration of two major towns in Enugu State, Nigeria

Evapotranspiration (ET) may account for up to 70% of the annual precipitation even in humid region. Understanding ET is essential for management of water resource, crop water requirement as well as irrigation designs/scheduling etc. Therefore, this study tries to analyze potential ET over Enugu State using meteorological data from weather stations and compared the results obtained with that from satellite remote sensed techniques. The meteorological data from 1999 to 2014 were collected from Nigerian Meteorological agency (NIMET) for two stations in Enugu State (Enugu town and Nsukka). The data were processed and ET calculated using CROPWAT software. Also, necessary data for ET were downloaded from global atmospheric reanalysis product by European Centre for Medium-Range Weather Forecast (ERA-Interim) and National Aeronautics and Space Administration (NASA). Daily and monthly potential ET results were estimated for Enugu and Nsukka. The potential ET obtained for both stations varies with month and seasons with higher values in dry season than rainy season. The potential ET obtained from NIMET, NASA and ERA-Interim have similar trend but varied in magnitude. Statistically, ETNIMET was the most accurate followed by ETNASA

A comparison of three models used to determine water fluxes over the Albany Thicket, Eastern Cape, South Africa:

The Albany Thicket (AT) biome contains outstanding global biodiversity as well as the potential to achieve carbon credits associated with water-efficient Crasslucean acid metabolism (CAM). Understanding the water fluxes in the AT is crucial to determining carbon (C) sequestration rates and water-use efficiency. Despite large variation in water fluxes across the AT, only a few studies have been conducted in this region with their results validated against short periods of observed data. This study aims to evaluate three models of water fluxes over AT against data from an eddy covariance (EC) system active from October 2015 to May 2018. ET was modelled using the BioGeoChemistry Management (BGC-MAN) model, a biophysical model (Penman-Monteith-Leuning (PML)) and a remotely-sensed product (MOD16), and their results compared with that from the EC system