Background: Northern Ethiopian Highlands, including Guna-Tana watershed, have experienced profound natural resources degradation which are resulted from coupled natural and anthropogenic factors. To mitigate this problem, Ethiopian government has launched various soil and water conservation programs at different watersheds. Overall objective of this study was to analyze impacts of soil and water conservation programs on vegetation regeneration and ecosystem productivity at in Guna-Tana watershed. As prime data source, the study has utilized Moderate Imaging Spectrometer satellite bi-monthly Enhanced Vegetation Index, 8-day land surface temperature and annual Net Primary Productivity products of the past 17 years starting from 2000. Imagery was processed by using various image preprocessing and analytical techniques. Long-term trend was tested by using Sens slope estimator and Mann-Kendall's monotonic trend test. Analyzed trend was also segregated into slope and agroecology classes. More importantly, to supplement trend analysis, Vegetation Disturbance Index was developed.
Results:Results have showed that despite of long-term soil and water conservation programs, except small patches, vast expanses of the watershed have showed decrease in vegetation regeneration and primary productivity trend. This observed trend has also spatial variability across slope gradient and agroecological classes of the watershed.
Conclusion:Though there is tendency of increasing vegetation regeneration and productivity, its observed that significant positive change as a result of watershed conservation programs was very little. This indicates that for better regeneration of vegetation and maintenance of ecosystem health in a watershed, intervention programs should be revised and constraints should be assessed. Taking these into consideration, the study calls further implementation strategies which have accounted agroecology and livelihoods production system.
The prime objective of this study was evaluating six satellite precipitation products by using standard statistical techniques to assess its capability to provide reliable rain rate (amount) and detect rainfall event correctly. High‐resolution precipitation products, Climate Hazards Group InfraRed Precipitation with Station (CHIRPS), Tropical Applications of Meteorology using Satellite data and ground‐based observations (TAMSAT), Tropical Rainfall Measuring Mission (TRMM 3B42RT v7), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIAN CDR), African Rainfall Climatology (ARC v2) and Climate Prediction Center Morphing technique (CMORPH v1.0) were utilized. Evaluation includes both numerical and categorial metrices. Results indicated that in terms of rainfall amount estimation, TAMSAT has relatively better capability whilst for detecting rain event, ARC v2 was found capable in Eastern Ethiopian landscape. All precipitation products underestimate precipitation amount with profound bias level. These needs a thorough bias correction before utilization of these satellite precipitation products.
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