Evaluating the accuracy of gridded water resources reanalysis and evapotranspiration products for assessing water security in poorly gauged basins

Abstract

Abstract. Achieving water security in poorly gauged basins is critically hindered by a lack of in situ river discharge data to assess past, current, and future evolution of water resources. To overcome this challenge, there has been a shift toward the use of freely available satellite and reanalysis data products. However, due to inherent bias and uncertainty, these secondary sources require careful evaluation to ascertain their performance before being applied in poorly gauged basins. The objectives of this study were to evaluate river discharge and evapotranspiration estimates from eight gridded water resources reanalysis (WRR), six satellite-based evapotranspiration (ET) products, and ET estimates derived from complimentary relationship (CR–ET) across eight river basins located in Central–West Africa. Results highlight strengths and weaknesses of the different WRR in simulating discharge dynamics and ET across the basins. Likewise, satellite-based products also show some strength and weaknesses in simulating monthly ET. Our results further revealed that the performance of the different models in simulating river discharge and evapotranspiration is strongly influenced by model structure, input data, and spatial resolution. Considering all hydrological model evaluation criteria, FLDAS-Noah, Lisflood, AWRAL, and Terra were among the best performing WRR products while for ET estimates, FLDAS-Noah, Terra, GLEAM3.5a and 3.5b, and PMLV2 outperformed the rest of the products. Given the plethora of WRR and ET products available, it is imperative to evaluate their performance in representative gauged basins to identify products that can be applied in each region. However, the choice of a particular product will depend on the application and user requirements. Taking this together, results from this study suggest that gridded WRR and ET products are a useful source of data for assessing water security in poorly gauged basins.

Changes in climate, vegetation cover and vegetation composition affect runoff generation in the Gulf of Guinea Basin

“…Other sources of uncertainties in the study are from GLEAM ET data that have been reported to slightly underestimate ET in parts of Africa (Nkiaka et al, 2022). In addition, the AgERA5 data used in this study equally have its inherent biases, however it is recommended for use in water resources assessments in Africa due to its high spatial resolution (Roffe & van der Walt, 2023).…”

“…The above equation is valid under the assumption that basin storage changes can be neglected over long timescales (>10 years). A similar approach has been used to estimate annual runoff in several regions (e.g., Nkiaka et al, 2022; Wamucii et al, 2021; Zhang et al, 2023).…”

“…GLEAM v3.7a was used in the present study because it covers the longest available time period (1980–2021) at an annual timescale at a spatial resolution of 0.25°. GLEAM ET estimates have been validated in many different regions in Africa (Nkiaka et al, 2022). GLEAM ET data are used to estimate the evaporative ratio.…”

Understanding Links Between Water Scarcity and Violent Conflicts in the Sahel and Lake Chad Basin Using the Water Footprint Concept

“…WRR product used in this study is the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) with a spatial resolution of 0.1° at monthly timescale (McNally et al., 2017). Despite their numerous advantages, WRR products have generic limitations such as inherent biases and uncertainties and therefore need to be evaluated before use (Nkiaka et al., 2022). Regardless of known limitations, the use of WRR products in water scarcity assessments is growing because they can provide long‐term homogeneous water availability data for previously unmonitored areas (McNally et al., 2019; Modi et al., 2022; Veettil & Mishra, 2020).…”

“…Regardless of known limitations, the use of WRR products in water scarcity assessments is growing because they can provide long‐term homogeneous water availability data for previously unmonitored areas (McNally et al., 2019; Modi et al., 2022; Veettil & Mishra, 2020). FLDAS‐Noah used in this study has been validated extensively across West Africa (McNally et al., 2017; Nkiaka et al., 2022), and also used in a previous study to estimate annual per capita water availability in Africa (McNally et al., 2019).…”