Trend and Sensitivity Analysis of Reference Evapotranspiration in the Senegal River Basin Using NASA Meteorological Data

Abstract

<jats:p>Understanding evapotranspiration and its long-term trends is essential for water cycle studies, modeling and for water uses. Spatial and temporal analysis of evapotranspiration is therefore important for the management of water resources, particularly in the context of climate change. The objective of this study is to analyze the trend of reference evapotranspiration (ET0) as well as its sensitivity to climatic variables in the Senegal River basin. Mann-Kendall’s test and Sen’s slope were used to detect trends and amplitude changes in ET0 and climatic variables that most influence ET0. Results show a significant increase in annual ET0 for 32% of the watershed area over the 1984–2017 period. A significant decrease in annual ET0 is observed for less than 1% of the basin area, mainly in the Sahelian zone. On a seasonal scale, ET0 increases significantly for 32% of the basin area during the dry season and decreases significantly for 4% of the basin during the rainy season. Annual maximum, minimum temperatures and relative humidity increase significantly for 68%, 81% and 37% of the basin, respectively. However, a significant decrease in wind speed is noted in the Sahelian part of the basin. The wind speed decrease and relative humidity increase lead to the decrease in ET0 and highlight a “paradox of evaporation” in the Sahelian part of the Senegal River basin. Sensitivity analysis reveals that, in the Senegal River basin, ET0 is more sensitive to relative humidity, maximum temperature and solar radiation.</jats:p>

Assessment of spatiotemporal variability and trend analysis of reference crop evapotranspiration for the southern region of Peninsular India

“…The inclining trends of ET 0 was explained by the signi cantly increasing trend of sunshine hours in growing season of 18 stations in Poland (Łabędzki et al 2014). The results obtained by (Ndiaye et al 2020) showed that the increased solar radiation had a positive in uence on annual ET 0 values. The sunshine duration (solar radiation) was the key climate variable in governing the trend of annual ET 0 of the 19 stations in the Guizhou Province of south west China during 1959-2011 (Gao et al 2016).…”

“…The climatic variables such as air temperature and relative humidity exhibited a positive trend while the wind speed showed negative trends in monthly, seasonal and annual timescales. The trends of seasonal and annual ET 0 over the period 1984-2017 were analysed in the Senegal river basin using the Mann-Kendall test and Sen's slope methods (Ndiaye et al 2020). An increasing annual and seasonal (dry season) ET 0 trend were found in majority of the stations for the study period.…”

Reliable Evapotranspiration Predictions with a Probabilistic Machine Learning Framework

“…ET o accounts for climate-driven watershed-scale ET from a surface covered by a hypothetical grass reference crop with uniform height, fully shading the saturated soil, and hence, reflects evaporation power of the atmosphere. The FAO56 Penman-Monteith equation (FAO56 PME) is commonly used to calculate the ET o [7][8][9][10][11]. FAO56 PME-based ET o calculations depend on the climate data, involving time series of shortwave solar radiation (R s ), air temperature (T a ), atmospheric pressure (P), relative humidity (RH), and wind speed (u 2 ).…”

Estimation of Daily Reference Evapotranspiration from NASA POWER Reanalysis Products in a Hot Summer Mediterranean Climate

“…In order to improve its accuracy, reanalysis data may require corrections using observation-based datasets in order to amend for anomalies that arise from land sur-face modeling [41]. Recent studies aimed to evaluate the performance of NASA POWER data [32,[41][42][43][44][45][46][47]. Those studies showed that there is a significant agreement between NASA POWER reanalysis and observed data for most weather parameters (mostly air temperature and solar radiation).…”

“…Despite the high importance of ETo in the field of irrigated agriculture, there are only a few studies available that demonstrate the accuracy and goodness of fit of ETo estimations derived from NASA POWER datasets [45,47], especially for the Mediterranean regions [43]. Monteiro et al [45], for Brazilian conditions, found that estimation ETo PM when using NASA POWER data led to an RMSE averaging 3.5 mm d −1 , while Negm et al [44], for Sicily, estimated an RMSE varying from 0.68 to 1.27 mm d −1 and a mean bias error (MBE) that varied between −0.39 and 0.73 mm d −1 .…”