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Abstract: With the development of global changes, researchers from all over the world increasingly pay attention to drought detection, and severe droughts that may have resulted from climate change. In this paper, spatial and temporal variability of drought is evaluated based on precipitation data and remotely sensed images. The standard precipitation index (SPI) and vegetation condition index (VCI) are used to evaluate the spatial and temporal characteristics of meteorological and vegetative drought in Tigray, Northern Ethiopia. Based on the drought critical values of SPI and VCI defining drought, the spatial and temporal extent of droughts in the study area is established. We processed 396 decadal images in order to produce the multi-temporal VCI drought maps. The results of the SPI and VCI analysis reveal that the eastern and southern zones of the study region suffered a recurrent cycle of drought over the last decade. Results further show that there is a time lag between the period of the peak VCI and precipitation values obtained from the meteorological stations across the study area. A significant agreement was observed between VCI values with the current plus last two-months of precipitation. The study demonstrates the utility of the vegetation condition index in semi-arid and arid regions. [Copyright &y& Elsevier]

The results of metrological, hydrological, and environmental data analyses are mainly dependent on the reliable estimation of missing data. In this study, 21 classical methods were evaluated to determine the best method for infilling the missing precipitation data in Ethiopia. The monthly data collected from 15 different stations over 34 years from 1980 to 2013 were considered. Homogeneity and trend tests were performed to check the data. The results of the different methods were compared using the mean absolute error (MAE), root-mean-square error (RMSE), coefficient of efficiency (CE), similarity index (S-index), skill score (SS), and Pearson correlation coefficient (rPearson). The results of this paper confirmed that the normal ratio (NR), multiple linear regression (MLR), inverse distance weighting (IDW), correlation coefficient weighting (CCW), and arithmetic average (AA) methods are the most reliable methods of those studied. The NR method provides the most accurate estimations with rPearson of 0.945, mean absolute error of 22.90 mm, RMSE of 33.695 mm, similarity index of 0.999, CE index of 0.998, and skill score of 0.998. When comparing the observed results and the estimated results from the NR, MLR, IDW, CCW, and AA methods, the MAE and RMSE were found to be low, and high values of CE, S-index, SS, and rPearson were achieved. On the other hand, using the closet station (CS), UK traditional, linear regression (LR), expectation maximization (EM), and multiple imputations (MI) methods gave the lowest accuracy, with MAE and RMSE values varying from 30.424 to 47.641 mm and from 49.564 to 58.765 mm, respectively. The results of this study suggest that the recommended methods are applicable for different types of climatic data in Ethiopia and arid regions in other countries around the world. [ABSTRACT FROM AUTHOR]

Upper Blue Nile basin (UBNB) is the water tower of Ethiopia and downstream countries. It contributes significant moisture to the surrounding atmosphere. However, the contribution of the moisture from the basin to the precipitation in the UBNB is not well documented. Therefore, this paper is aimed to estimate the role of UBNB moisture budget and recycling ratio for spatiotemporal precipitation distributions. To this end, we used the European Center for Medium-range Weather Forecast (ECMWF) data from 1979 to 2017. The derived ECMWF results are correlated with in-situ observations with the correlation coefficient of 0.82. During summer season most of the UBNB moisture is converted to precipitation around the central parts of the study area, while in spring it contributes to the southern parts of the study area. Furthermore, the northwest part of the study area is affected by the basins moisture during the autumn season. The calculated recycling ratios for four seasons (summer, autumn, spring, and winter) are 9.70%, 16.33%, 19.01%, and 35.30% respectively with the annual average value of 20.11%. It is evident that the maximum amount of precipitation is captured from the local moisture during the winter season. Generally, UBNB moisture budget had a lesser contribution of precipitation over the study area. It rather contributed significant precipitation to the neighboring countries. Hence, further studies on moisture budget are required to explain this phenomenon in the context of Ethiopia. Image 1 • The precipitation pattern over upper Blue Nile basin exhibits a decreasing trend from east to northwest (1979–2017). • Recycling ratio for four seasons (summer, autumn, spring and winter) were 9.70%, 16.33%, 19.01% and 35.30% respectively. • The maximum amount of precipitation is extracted from the locale moistures during the winter season. • Egypt and Sudan have got significance precipitation from the upper Blue Nile basin moisture budgets. [ABSTRACT FROM AUTHOR]