scholarly journals Application of Artificial Neural Networks in Forecasting a Standardized Precipitation Evapotranspiration Index for the Upper Blue Nile Basin

Water ◽  
2020 ◽  
Vol 12 (3) ◽  
pp. 643 ◽  
Author(s):  
Getachew Mehabie Mulualem ◽  
Yuei-An Liou

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.

2007 ◽  
Vol 8 (3) ◽  
pp. 327-343 ◽  
Author(s):  
Paul Block ◽  
Balaji Rajagopalan

Abstract Ethiopian agriculture and Nile River flows are heavily dependent upon the Kiremt season (June–September) precipitation in the upper Blue Nile basin, as a means of rain-fed irrigation and streamflow contribution, respectively. Climate diagnostics suggest that the El Niño–Southern Oscillation phenomenon is a main driver of interannual variability of seasonal precipitation in the basin. One-season (March–May) lead predictors of the seasonal precipitation are identified from the large-scale ocean–atmosphere–land system, including sea level pressures, sea surface temperatures, geopotential height, air temperature, and the Palmer Drought Severity Index. A nonparametric approach based on local polynomial regression is proposed for generating ensemble forecasts. The method is data driven, easy to implement, and provides a flexible framework able to capture any arbitrary features (linear or nonlinear) present in the data, as compared to traditional linear regression. The best subset of predictors, as determined by the generalized cross-validation (GCV) criteria, is selected from the suite of potential large-scale predictors. A simple technique for disaggregating the seasonal precipitation forecasts into monthly forecasts is also provided. Cross-validated forecasts indicate significant skill in comparison to climatological forecasts, as currently utilized by the Ethiopian National Meteorological Services Agency. This ensemble forecasting framework can serve as a useful tool for water resources planning and management within the basin.


2021 ◽  
Vol 13 (9) ◽  
pp. 1835
Author(s):  
Yared Bayissa ◽  
Semu Moges ◽  
Assefa Melesse ◽  
Tsegaye Tadesse ◽  
Anteneh Z. Abiy ◽  
...  

Drought is one of the least understood and complex natural hazards often characterized by a significant decrease in water availability for a prolonged period. It can be manifested in one or more forms as meteorological, agricultural, hydrological, and/or socio-economic drought. The overarching objective of this study is to demonstrate and characterize the different forms of droughts and to assess the multidimensional nature of drought in the Abbay/ Upper Blue Nile River (UBN) basin and its national and regional scale implications. In this study, multiple drought indices derived from in situ and earth observation-based hydro-climatic variables were used. The meteorological drought was characterized using the Standardized Precipitation Index (SPI) computed from the earth observation-based gridded CHIRPS (Climate Hazards Group InfraRed Precipitation with Station) rainfall data. Agricultural and hydrological droughts were characterized by using the Soil Moisture Deficit Index (SMDI) and Standardized Runoff-discharge Index (SRI), respectively. The monthly time series of SMDI was derived from model-based gridded soil moisture and SRI from observed streamflow data from 1982 to 2019. The preliminary result illustrates the good performance of the drought indices in capturing the historic severe drought events (e.g., 1984 and 2002) and the spatial extents across the basin. The results further indicated that all forms of droughts (i.e., meteorological, agricultural, and hydrological) occurred concurrently in Abbay/Upper Blue Nile basin with a Pearson correlation coefficient ranges from 0.5 to 0.85 both Kiremt and annual aggregate periods. The concurrent nature of drought is leading to a multi-dimensional socio-economic crisis as indicated by rainfall, and soil moisture deficits, and drying of small streams. Multi-dimensional drought mitigation necessitates regional cooperation and watershed management to protect both the common water sources of the Abbay/Upper Blue Nile basin and the socio-economic activities of the society in the basin. This study also underlines the need for multi-scale drought monitoring and management practices in the basin.


2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mulatu Liyew Berihun ◽  
Atsushi Tsunekawa ◽  
Nigussie Haregeweyn ◽  
Mitsuru Tsubo ◽  
Ayele Almaw Fenta

Abstract Background Evaluating the impacts of land-use/land-cover (LULC) changes on ecosystem service values (ESVs) is essential for sustainable use and management of ecosystems. In this study, we evaluated the impact of human activity driven LULC changes on ESVs over the period 1982–2016/17 in contrasting agro-ecological environments: Guder (highland), Aba Gerima (midland), and Debatie (lowland) watersheds of the Upper Blue Nile basin, Ethiopia. Results During the study period, the continuous expansion of cultivated land at the expense of natural vegetation (bushland, forest, and grazing land) severely reduced the total ESV by about US$ 58 thousand (35%) in Aba Gerima and US$ 31 thousand (29%) in Debatie watersheds. In contrast, the unprecedented expansion of plantations, mainly through the planting of Acacia decurrens, led, from 2006, to a ESV rebound by about US$ 71 thousand (54%) in Guder watershed, after it had decreased by about US$ 61 thousand (32%) between 1982 and 2006. The reduction in natural forest area was the major contributor to the loss of total ESV in the study watersheds, ranging from US$ 31 thousand (63%) in Debatie to US$ 96.9 thousand (70%) in Guder between 1982 and 2016/17. On an area-specific basis, LULC changes reduced the average ESV from US$ 560 ha−1 year−1 (1982) in Guder to US$ 306 ha−1 year−1 (2017) in Debatie watersheds. Specific ESVs such as provisioning (mainly as food production) and regulating services (mainly as erosion control and climate regulation) accounted for most of the total ESVs estimated for the study watersheds. Conclusions In most cases, the total and specific ESVs of the watersheds were negatively associated with the population growth, which in turn was positively associated with the expansion of cultivated land over the study period. In Guder, however, ESVs were positively associated with population growth, especially after 2012. This is mainly due to the expansion of Acacia decurrens plantations. Our results suggest, therefore, that future policy measures and directions should focus on improving vegetation cover through planting multipurpose trees such as Acacia decurrens to prevent future loss of ESV in the midland and lowland regions of the Upper Blue Nile basin and beyond. However, caution must be taken during plantation of invasive species as they may have undesirable consequences.


2021 ◽  
Author(s):  
Belay B. Bizuneh ◽  
Mamaru A. Moges ◽  
Berhanu G. Sinshaw ◽  
Mulu S. Kerebih

2016 ◽  
Vol 17 (11) ◽  
pp. 2875-2882 ◽  
Author(s):  
Dejene Sahlu ◽  
Efthymios I. Nikolopoulos ◽  
Semu A. Moges ◽  
Emmanouil N. Anagnostou ◽  
Dereje Hailu

Abstract This work presents a first evaluation of the performance of the Integrated Multisatellite Retrievals for GPM (IMERG) precipitation product over the upper Blue Nile basin of Ethiopia. One of the unique features of this study is the availability of hourly rainfall measurements from an experimental rain gauge network in the area. Both the uncalibrated and calibrated versions of IMERG are evaluated, and their performance is contrasted against another high-resolution satellite product, which is the Kalman filter (KF)-based Climate Prediction Center (CPC) morphing technique (CMORPH). The analysis is performed for hourly and daily time scales and at spatial scales that correspond to the nominal resolution of satellite products, which is 0.1° spatial resolution. The period analyzed is focused on a single wet season (May–October 2014). Evaluation is performed using several statistical and categorical error metrics, as well as spatial correlation analysis to assess the ability of satellite products to represent spatial variability of precipitation in the area. Results show that both IMERG products have a better bias ratio and correlation coefficient on both time scales as compared to CMORPH. Comparison statistics show a slight improvement in the skill of detecting rainfall events in IMERG products compared to CMORPH. Results also show a decreasing trend in the detection ability of satellite products for increasing threshold values, highlighting the need to further improve detection during heavy precipitation.


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