Understanding rainfall distribution in space and time is crucial for sustainable water resource management and agricultural productivity. This study investigated the spatial distribution and temporal trends of rainfall in Amhara region using time series rainfall data of Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) for the period 1981–2017. Coefficient of variation, standardized anomaly index (SAI), precipitation concentration index (PCI) and seasonality index (SI) were used to evaluate rainfall variability and seasonality. Mann–Kendall's test was also employed for rainfall trend analysis. Results showed that the region has been experiencing variable rainfall events that cause droughts and floods over different years. SAI also witnessed the presence of inter-annual variability of rainfall with negative and positive anomalies in 59.46% and 40.54% of the analyzed years, respectively. PCI and SI results implied that the area had irregular and strong irregular rainfall distribution. Trend analysis results showed an overall increase in the annual and seasonal rainfall (except winter) during the study period. The information obtained from this study could serve as a proxy for rainfall variability and trend in the study area which might be used as input for decision-makers to take appropriate adaptive measures in various agricultural and water resources sectors.
Ever increase in population growth and drastic climatic changes augment the demand and exploration of groundwater from time to time. An integrated approach of remote sensing (RS), geographic information system (GIS) and multicriteria decision analysis (MCDA) of analytical hierarchical process (AHP) were applied to delineate groundwater potential (GWP) zones in Andasa-Tul watershed, Upper Blue Nile Basin, Ethiopia. For this purpose, nine GWP influencing thematic layers comprising lithology, lineament density, geomorphology, slope, soil, drainage density, land use/land cover, rainfall and depth to groundwater level were used. The thematic layers and classes within them were given scale values based on literature and experts' decision and calculated using Satty's AHP. The thematic layers have been integrated via their weights/rates using weighted overlay spatial function tool of ArcGIS to provide GWP map. The result shows that GWP map comprises very good (13.4%), good (7%), moderate (23.6 %), poor (35.4%) and very poor (20.5%) zones. Validation of the GWP map with existing water point yields shows 84.21 % agreement indicating good accuracy of the method. The map removal sensitivity analysis result reveals that GWP is more sensitive to lithology (mean variation index, 1.92 %) and less sensitive to geomorphology (mean variation index, 0.59 %). Similarly, from the single layer sensitivity analysis, lithology and slope are found to be more effective parameters, whereas rainfall and depth to groundwater level are less effective variables.
Detecting the potential region of the groundwater resource is a difficult issue all over the world. Know a day, advanced geospatial technologies are excellent tools for efficient planning, managing, and assessing groundwater resources, particularly in data-scarce developing nations. Remote sensing (RS) and GIS-based multi-criteria decision analysis (MCDA) methods were applied to delineate the groundwater potential (GWP) in the Fetam-Yisir catchment, Blue Nile Basin, Ethiopia. Nine thematic layers: slope, geomorphology, normalized difference vegetation index (NDVI), topographic elevation, geology, land use/land cover (LULC), soil, rainfall, and drainage density from satellite and conventional data were used. The analytical hierarchy process (AHP) of an MCDA was employed to compute the corresponding normalized weight for the class in a layer and weights for the thematic layers on the base of their relative significance to the GWP. Integration of all thematic maps has been done using the ‘‘Weighted overlay’’ tool to obtain a GWP map. The GWP map is then validated using observed boreholes, and springs yield data. The verification of the final GWP zone map against yield data confirms 81.82% agreement indicating the authenticity of the method. The final GWP output confirmed that 43.2% area of the Fetam-Yisir catchment falls in a ‘‘good’’ GWP zone; 41.8%, 7.44%, 7.4%, and 0.02% of the area falls in ‘‘moderate’’, ‘‘Very good’’, “Poor” and ‘‘very poor’’ GWP zones, respectively. The sensitivity analysis divulges that the GWP map is highly sensitive to slope with a mean variation index of 1.45%. Thus, this study can be used for effective groundwater exploration, development, and sustainable abstraction, as well as it guides the researchers in locating the GWP zone.
The study analyzed the daily extreme rainfall indices and its consequences on Meher (summer) season cereal crop calendar in the agro - climatic zones (ACZs) of a watershed. Long-term (1981–2019) rainfall data for 50 sample grid points with a spatial resolution of 5 5 km from Climate Hazards Group Infrared Precipitation (CHIRPS) was considered. Focus group discussions were employed to identifying the local crop calendars and consequences of extreme rainfall events. Mann Kendall’s (MK) and Sen’s slop statistics were used to define the trends, statistical significance, and magnitude of the changes in extreme rainfall indices. The upward and downward signals were found for different crop calendars of the ACZs. Most of the increasing trends were observed for the land preparation period (LPP), sowing and management period (SaMP), and harvesting and threshing period (HaTP) field operations in the highland zone, midland zone, and all ACZs, respectively. In contrast, some of the downward trends in extreme rainfall indices were observed for LPP and SaMP in the cold-highland zone and highland zone, and HaTP was observed to be the same in all ACZs. The upward and downward signals of the indices could have negative consequences for existing cereal crop production in the watershed.
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