Abstract
The occurrence frequency of drought has intensified with the unprecedented effect of global warming. Knowledge about the spatiotemporal distributions of droughts and their trends is crucial for risk management and developing mitigation strategies. In this study, we developed seven artificial neural network (ANN) predictive models incorporating hydro-meteorological, climate, sea surface temperatures, and topographic attributes to forecast the standardized precipitation evapotranspiration index (SPEI) for seven stations in the Upper Blue Nile basin (UBN) of Ethiopia from 1986 to 2015. The main aim was to analyze the sensitivity of drought-trigger input parameters and to measure their predictive ability by comparing the predicted values with the observed values. Statistical comparisons of the different models showed that accurate results in predicting SPEI values could be achieved by including large-scale climate indices. Furthermore, it was found that the coefficient of determination and the root-mean-square error of the best architecture ranged from 0.820 to 0.949 and 0.263 to 0.428, respectively. In terms of statistical achievement, we concluded that ANNs offer an alternative framework for forecasting the SPEI drought index.
Highlights
Drought is a weather-related phenomenon that occurs in more or less all climatic regions
The model was trained by utilizing large-scale climate indices (SOI, IOD, Pacific decadal oscillation (PDO)) and SST (Nino 3.0, 3.4, 4.0), which are linked to changes of atmospheric and ocean circulation, and hydro-metrological variables (RF, Max T, Min T, potential evapotranspiration (PET),) as the input variables for the artificial neural network (ANN) model, and the output variables were the standardized precipitation evapotranspiration index (SPEI) values calculated at a 12 months timescale
We concluded that the best ANN forecasting model built using large-scale climate indices and SST made better predictions, which was verified by analysis of the prediction errors
Summary
Drought is a weather-related phenomenon that occurs in more or less all climatic regions. Drought is a complicated and little-understood phenomenon due to its multiple causes [1]. It usually originates from a reduction in the amount of precipitation received over an extended period [2,3], while a few instances have resulted from anomalies of temperature and evapotranspiration [4]. Once a region has been in drought conditions for two or more months, the plants and trees will dry out. The recent bush fires in Australia have been fueled by an extreme temperature change in the Indian Ocean, record high temperatures, and prolonged dry spells
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