Your search found 5 records
1 Singh, J. P.; Soni, M. L.; Beniwal, R. K. 2004. Woody perennials: Potential resource for rehabilitation of degraded lands in Western Rajasthan. Wastelands News, 19(4):22-24.
(Location: IWMI-HQ Call no: P 7514 Record No: H038511)
2 Tadesse, L.; Suryabhagavan, K. V.; Sridhar, G.; Legesse, G. 2017. Land use and land cover changes and soil erosion in Yezat Watershed, North western Ethiopia. International Soil and Water Conservation Research, 5(2):85-94. [doi: https://doi.org/10.1016/j.iswcr.2017.05.004]
Land use ; Land cover change ; Watersheds ; Soil erosion models ; GIS ; Remote sensing ; Satellite imagery ; Landsat ; Vegetation ; Grasslands ; Farmland ; Woodlands ; Shrubs ; Biomass ; Spatial distribution / Ethiopia / Yezat Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H048161)
http://www.sciencedirect.com/science/article/pii/S2095633916301393/pdfft?md5=db1a36ec40258ace455dc8bd1f7f2b25&pid=1-s2.0-S2095633916301393-main.pdf
https://vlibrary.iwmi.org/pdf/H048161.pdf
https://vlibrary.iwmi.org/pdf/H048161.pdf
(4.19 MB) (4.19 MB)
Soil erosion affects land qualities and water resources. This problem is severe in Ethiopia due to its topographic features. The present research was aimed to estimate spatiotemporal changes in land-use/land-cover pattern and soil erosion in the Yezat watershed in Ethiopia. This study was carried out by using landsat imageries of 2001, 2010 and 2015. Images were classified into categories using supervised classification by maximum likelihood algorithm. They were also classified into different biomass levels by using Normalized Difference Vegetation Index (NDVI) analysis. Revised Universal Soil Loss Equation modeling was applied in a GIS environment to quantify the potential soil erosion risk. The area under grassland, woodland and homesteads have increased by 610.69 (4%), 101.69 (0.67%) and 126.6 ha (0.83%) during 2001–2015. The extent of cultivated land and shrub/bushland was reduced by 323.43(0.02%) and 515.44 ha (3.41%), respectively, during the same period. The vegetation cover in the watershed decreased by 91% during 2001–2010, and increased by 88% during 2010–2015. Increase of NDVI values indicates better ground cover due to implementation of integrated watershed development program in the region. The estimated annual soil losses were 7.2 t ha-1 yr-1 in 2001, 7.7 t ha-1 yr-1 in 2010 and 4.8 t ha-1 yr-1 in 2015. Management interventions are necessary to improve the status and utilization of watershed resources in response to sustainable land management practices for sustainable livelihood of the local people.
3 Mul, Marloes; Pettinotti, L.; Amonoo, Naana Adwoa; Bekoe-Obeng, E.; Obuobie, E. 2017. Dependence of riparian communities on ecosystem services in northern Ghana. Colombo, Sri Lanka: International Water Management Institute (IWMI). 43p. (IWMI Working Paper 179) [doi: https://doi.org/10.5337/2018.201]
Ecosystem services ; Riparian zones ; Communities ; Participatory rural appraisal ; Socioeconomic environment ; Living standards ; Mapping ; Seasonality ; Natural resources ; Infrastructure ; Forest reserves ; Shrubs ; Woodlands ; Water storage ; Ponds ; Dams ; River basins ; Stream flow ; Floodplains ; Household consumption ; Domestic consumption ; Gender ; Climate change ; Rain ; Dry season ; Food security ; Income ; Agriculture / Ghana
(Location: IWMI HQ Call no: IWMI Record No: H048466)
(1 MB)
This study investigated the dependence of three riparian communities on ecosystem services in northern Ghana. Participatory mapping and ranking exercises in gender-segregated groups were used to elicit information on the communities’ livelihoods. The most important ecosystem-based activities (EBA) are farming, fishing, livestock watering and grazing, collection of wild fruits and vegetables, and provision of water for domestic use. The major EBA are dependent on the seasonal flows of the White Volta River, which are under pressure due to climatic and other anthropogenic changes. For example, observed delays in the start of the rainy season are affecting rainfed agricultural activities on the floodplains. Delayed planting on the floodplains results in damage to, or loss of, crops as floods arrive before the harvest. Moreover, the Bagré Dam in Burkina Faso, built upstream of the communities, has impacted the natural river flow. The planned Pwalugu Dam may, depending on the final operations, support or affect EBA. We, therefore, recommend that operations of the Pwalugu Dam should take into consideration the flow requirements of EBA downstream of the dam.
4 Wang, X.; Nuppenau, E.-A. 2021. Modelling payments for ecosystem services for solving future water conflicts at spatial scales: the Okavango River Basin example. Ecological Economics, 184:106982. (Online first) [doi: https://doi.org/10.1016/j.ecolecon.2021.106982]
Payments for ecosystem services ; Modelling ; International waters ; Conflicts ; River basin management ; Integrated management ; Water use ; Forest conservation ; Land use change ; Farmland ; Grasslands ; Shrubs ; Deltas ; Hydrology ; Farmers / Botswana / Angola / Okavango River Basin / Cubango River / Cuito River
(Location: IWMI HQ Call no: e-copy only Record No: H050296)
(3.89 MB)
This study aims to resolve a potential water conflict between the upper catchment communities of the Okavango River Basin and the downward communities in the Okavango Delta. A model to payment for ecosystem services is developed at the basin level, recognizing spatial diversity and water flows. It addresses four objectives: (1) To assess relationships between water consumption and land use from a spatial perspective. (2) To estimate water availability under current land use as a reference without any water policy intervention. (3) To optimize water flow generation as intended for getting ecosystem services. This is based on the mechanism of payments for ecosystem services, specifically in terms of land use change as stewardship. (4) To compensate farmers for economic losses due to upstream land use changes. Our study suggests that an integrated basin management should consider payments for ecosystem services to incentivize forest conservation. The annual payments of US$28.7 million could encourage farmers upstream to change their land uses from deforestation to forest conservation. With compensation, approximately 8.7 million hectares of Miombo forests would be maintained in the basin, which would secure 3656 million m3 of water during the rainy season and subsequently benefit the Delta in the dry season.
5 Yimer, A. K.; Haile, Alemseged Tamiru; Hatiye, S. D.; Azeref, A. G. 2020. Seasonal effect on the accuracy of land use/land cover classification in the Bilate Sub-basin, Abaya-Chamo Basin, Rift Valley Lakes Basin of Ethiopia. Ethiopian Journal of Water Science and Technology, 3:23-50.
Land use ; Land cover ; Classification systems ; Seasonal variation ; Wet season ; Dry season ; Cultivated land ; Agriculture ; Water resources ; Forests ; Shrubs ; Settlement ; Remote sensing ; Landsat ; Satellite imagery / Ethiopia / Rift Valley Lakes Basin / Abaya-Chamo Basin / Bilate Sub-Basin
(Location: IWMI HQ Call no: e-copy only Record No: H050723)
https://survey.amu.edu.et/ojs/index.php/EJWST/issue/view/87/Seasonal%20effect%20on%20the%20accuracy%20of%20Land%20use%20Land%20cover%20classification%20in%20the%20Bilate%20Sub-basin%2C%20Abaya-Chamo%20Basin%2C%20Rift%20valley%20Lakes%20Basin%20of%20Ethiopia
https://vlibrary.iwmi.org/pdf/H050723.pdf
https://vlibrary.iwmi.org/pdf/H050723.pdf
(0.95 MB) (970 KB)
A correct and timely land use/land cover (LULC) classification provides indispensable information for the effective management of environmental and natural resources. However, earlier studies mapped the LULC map of Bilate Sub-basin using remote sensing images that were acquired for a single season. Hence, these studies did not consider the seasonal effects on the accuracy of LULC classification. Therefore, the objective of this study was to evaluate changes in classification accuracy for images acquired during wet and dry seasons in the Bilate Sub-basin. LULC of the study area was classified using the Landsat 8 satellite imageries. Based on field observations, we classified the LULC of the study area into 9 dominant classes. The classification for the two seasons resulted in a noticeable difference between the LULC composition of the study area because of seasonal differences in the classification accuracy. The overall accuracy of the LULC maps was 80%for the wet season and 90% for the dry season with Kappa coefficient values of 0.8 and 0.9 respectively. Therefore, the two seasons showed a significant difference in the overall accuracy of the classification. However, we discovered that when the classification accuracy was tested locally, that is for individual pixels, the results were not the same. In Bilate Sub-basin, several pixels (14.71%) were assigned to different LULC classes on the two seasons maps while 85.29% of the LULC classes remained unaltered in the two maps. According to the classification results, the season had a noticeable effect on the accuracy of LULC classification. This suggests that for LULC classification, multitemporal images should be used rather than a single remote sensing image.
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