Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia
Abstract Climate change is one of the worst environmental issues, with a negative impact on most developing countries across the globe and in some regions, including Ethiopia. This study seeks to establish the temporal and spatial changes in rainfall for the period 1987–2021. In this study, ordinary...
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2024-12-01
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| author | Elias Bojago |
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| description | Abstract Climate change is one of the worst environmental issues, with a negative impact on most developing countries across the globe and in some regions, including Ethiopia. This study seeks to establish the temporal and spatial changes in rainfall for the period 1987–2021. In this study, ordinary statistical measures, such as the mean and coefficient of variation, precipitation concentration index (PCI), and standardized anomaly index (SAI), were applied to investigate the rainfall variation. Concerning the estimation of the spatiotemporal distribution and magnitude of changes in, non-parametric Mann-Kendall (MK) tests, Sen’s slope estimator, and innovative trend analysis (ITA) were also conducted in ArcGIS 10.8 environment and XLSTAT/R. The study showed significant fluctuations in rainfall in the Wolaita zone, with minimum mean annual rainfall in 1997 and maximum rainfall in 2003. All but the Belg season had more negative seasonal anomalies than positive ones. The annual rainfall for each of the AEZs in different parts of the country ranged from one another; it was 969.03 mm in a southeast lowland AEZ and 1648.75 mm in the northwest highland AEZ. Rainfall was not uniformly distributed throughout the year and study area; the highland AEZs received more rainfall in the Belg and Kermit seasons than in the lowland seasons. In the ordinary kriging results, the extent of variability in the CV of the mean annual rainfall for each zone was identifiable. The southwest lowland AEZ produced a CV of 24.22% with a decrease in rainfall amounts, and the northeast highland AEZ produced a CV of 31.63% of the rainfall distribution amounts. This area includes lowland and highland AEZs of the northeastern part of the study area’s rainfall, which is moderately distributed by PCI. This information is helpful when attempting to associate development and cropping systems with temporal and spatial climatic patterns with respect to rainfall for agro-climatological activities and projects or flood regulatory measures. |
| format | Article |
| id | doaj-art-30e8c71e261d4ba7aa7b9a34078f7a10 |
| institution | Kabale University |
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| language | English |
| publishDate | 2024-12-01 |
| publisher | Springer |
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| series | Discover Sustainability |
| spelling | doaj-art-30e8c71e261d4ba7aa7b9a34078f7a102025-01-26T12:10:28ZengSpringerDiscover Sustainability2662-99842024-12-015112910.1007/s43621-024-00685-6Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south EthiopiaElias Bojago0Department of Environmental Science, College of Natural and Computational Sciences, Wolaita Sodo UniversityAbstract Climate change is one of the worst environmental issues, with a negative impact on most developing countries across the globe and in some regions, including Ethiopia. This study seeks to establish the temporal and spatial changes in rainfall for the period 1987–2021. In this study, ordinary statistical measures, such as the mean and coefficient of variation, precipitation concentration index (PCI), and standardized anomaly index (SAI), were applied to investigate the rainfall variation. Concerning the estimation of the spatiotemporal distribution and magnitude of changes in, non-parametric Mann-Kendall (MK) tests, Sen’s slope estimator, and innovative trend analysis (ITA) were also conducted in ArcGIS 10.8 environment and XLSTAT/R. The study showed significant fluctuations in rainfall in the Wolaita zone, with minimum mean annual rainfall in 1997 and maximum rainfall in 2003. All but the Belg season had more negative seasonal anomalies than positive ones. The annual rainfall for each of the AEZs in different parts of the country ranged from one another; it was 969.03 mm in a southeast lowland AEZ and 1648.75 mm in the northwest highland AEZ. Rainfall was not uniformly distributed throughout the year and study area; the highland AEZs received more rainfall in the Belg and Kermit seasons than in the lowland seasons. In the ordinary kriging results, the extent of variability in the CV of the mean annual rainfall for each zone was identifiable. The southwest lowland AEZ produced a CV of 24.22% with a decrease in rainfall amounts, and the northeast highland AEZ produced a CV of 31.63% of the rainfall distribution amounts. This area includes lowland and highland AEZs of the northeastern part of the study area’s rainfall, which is moderately distributed by PCI. This information is helpful when attempting to associate development and cropping systems with temporal and spatial climatic patterns with respect to rainfall for agro-climatological activities and projects or flood regulatory measures.https://doi.org/10.1007/s43621-024-00685-6Climate changeInnovative trend analysisKriging-interpolationRainfall variabilitySpatial analysis |
| spellingShingle | Elias Bojago Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia Discover Sustainability Climate change Innovative trend analysis Kriging-interpolation Rainfall variability Spatial analysis |
| title | Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia |
| title_full | Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia |
| title_fullStr | Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia |
| title_full_unstemmed | Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia |
| title_short | Spatio-temporal rainfall variability and trends using a Kriging-interpolation and Innovative trend analysis approach: the case of Wolaita zone, south Ethiopia |
| title_sort | spatio temporal rainfall variability and trends using a kriging interpolation and innovative trend analysis approach the case of wolaita zone south ethiopia |
| topic | Climate change Innovative trend analysis Kriging-interpolation Rainfall variability Spatial analysis |
| url | https://doi.org/10.1007/s43621-024-00685-6 |
| work_keys_str_mv | AT eliasbojago spatiotemporalrainfallvariabilityandtrendsusingakriginginterpolationandinnovativetrendanalysisapproachthecaseofwolaitazonesouthethiopia |