The nexus between land use, land cover dynamics, and soil erosion: a case study of the Temecha watershed, upper Blue Nile basin, Ethiopia

Prediction of soil erosion and sediment yield in an ungauged basin based on land use land cover changes

Soil erosion is a significant problem in the agriculture sector and the environment globally. Susceptible soil erosion zones must be identified and erosion rates evaluated to decrease land degradation problems and increase crop productivity by protecting soil fertility. Therefore, a research study has been carried out in the Ponnaniyar River basin, an ungauged tributary of the Cauvery basin in India, primarily used for agriculture. The main purpose of this study is to assess soil erosion (SE) and sediment yield (SY) for the future in an ungauged basin by utilizing the projected land use/land cover (LULC) map of the study area. Additionally, Landsat 8 satellite dataset was only used for the classification and prediction of LULC to eliminate the variation between the resolution, bands and its wavelength of different satellites datasets. To achieve the goals of this study, three phases were followed. First, the LULC of the study area was classified using a Random Trees Classifier (RTC), a machine learning technique, followed by the projection of land cover using a Cellular Automata-based Artificial Neural Network (CA-ANN) model. The driving factors for this model include digital elevation model (DEM), slope, distance to roads, settlements, and water bodies. The accuracy level of the projected LULC map was determined by comparing it with the classified LULC map of the study area, and the results showed an overall accuracy (OA) of 85.35 percentage and a kappa coefficient (K) of 0.74, respectively. Second, the projected LULC map was used in the land management factor (C) and conversation practice factor (P) of the Revised Universal Soil Loss Equation (RUSLE) model to assess soil erosion. The model was integrated with the sediment delivery ratio (SDR) to estimate sediment yield within the study area. The accuracy of the generated erosion map based on the classified and projected LULC for the year 2022 was determined using the receiver operating characteristic curve (ROC) curve, and it was found to be in satisfactory agreement. Finally, for effective soil and water conservation measures, the basin was divided into 13 sub-watersheds (SWs) using terrain analysis in geographical information system (GIS). The SWs were prioritized based on the mean soil loss in the 4-year interval from 2014 to 2030 and integrated using the weighted average method to determine the final prioritization. From these findings, SW 11, SW 9, SW 12, and SW 1 are extremely affected by soil erosion, and immediate implementation of water harvesting structures is required for soil conservation. Also, this research might be useful for decision-makers and policymakers in land management.

Assessment of soil erosion hazard and its relation to land use land cover changes: Case study from alage watershed, central Rift Valley of Ethiopia

Soil erosion by water and wind is among the most crucial land degradation processes in Ethiopia. This is also the case for Alage watershed located in the cental Rift Valley system. This study aimed at assessment of soil erosion hazard and its relation to land use land cover change in the watershed during the period from 1984 to 2016 for a better land management. The study is based on application of Remote Sensing (RS) and Geographical Information System (GIS) to extract inputs factor values for the Revised Universal Soil Loss Equation (RUSLE). Time-series satellite imageries of Landsat TM 1984, ETM+ 2000 and OLI 2016 were used for land use land cover change detection and determination of cover management (C) factor of the RUSLE. Biophysical data such as rainfall, soil properties, land management practices including soil and water conservation measures within the watershed were collected using field survey and secondary data sources. Slope steepness and slope length factors were derived using Digital Elevaition Model (DEM). Long-term average annual soil loss rates were estimated by the RUSLE integrated with GIS for 1984, 2000 and 2016. Using satellite imageries, the land use land cover and changes within the watershed during the three periods were obtained through a supervised classification with maximum likelihood algorithim. The results of land use land cover change indicated that the proportion of rain-fed cropland, bare land and built up areas increased by 17.4%, 5.9% and 2.9% respectively over the three study period. In contrast the proportion of bush/shrub land, irrigated cropland, grass land, forested areas and waterbodies decresaed by 15.5%, 4.7%, 3.4%, 2.3% and 0.3% respectively during the same period. Estimated average annual soil loss rates showed an increasing trend from 24.3 ton ha-1 yr-1 in 1984 to 38 ton ha-1 yr-1 in 2016. Increasing trends of average annual soil loss rate is attributed to increased proportion of cropland, bare land and built up areas during those periods leading to decreased protective vegetation cover. Hotspot areas within the watershed require implementation of land management practices to prevent further degradation and expansion of gullies. This study is relevant to demonstrate environmental implication of land use land cover change for future land management practices and land use policy in the Rift Valley of central Ethiopia.

Impacts of watershed management on land use/cover changes and landscape greenness in Yezat Watershed, North West, Ethiopia

In Ethiopia, watershed management interventions have been implemented since the 1980s to curve land degradation and improve the agricultural productivity of smallholder farmers. However, little effort has been made to investigate the impacts of watershed management on land use/cover changes and landscape greenness. Thus, this study was conducted to assess the long-term impacts of watershed management on land use/cover changes and landscape greenness in the Yezat watershed. Landsat images for 1990, 2000, 2010, and 2021 were employed and analyzed to produce maps of the respective years using GIS and remote sensing techniques. Data from satellite images, coupled with field observation and the socio-economic survey, revealed an effective approach for analyzing the extent, rate, and spatial patterns of land use/cover changes. Normalized difference vegetation index (NDVI) was also employed to detect vegetation greenness. The results of the study show that between 1990 and 2021, the built-up area, plantation, natural forest, shrubland, and grasslands were increased by + 254 ha, + 712.3 ha, 196.3 ha, + 1070.8, and + 425.3 ha respectively due to watershed management interventions. Conversely, cultivated land was decreased with a rate of - 2658.7 ha_, in the study area. However, the reverse is true between 1990 and 2000 due to large-scale land degradation. Besides, the result of the study also shows that a low landscape greenness value (- 0.11) was observed between 1990 and 2000, and a high landscape greenness value (+ 0.2) was observed between 1990 and 2021. The observed change in landscape greenness in the watershed was due to the change in shrubland (+ 1070.8 ha), grassland (+ 425.3 ha), plantation (+ 712.3 ha), and forestland (+ 196.3 ha) covers between 1990 and 2021 years. Such observed changes in land use land covers, landscape greenness, and cultivated land in the study watershed have important implications for the improvement of soil moisture, soil fertility, biodiversity, groundwater recharge, carbon sequestration, soil erosion land, crop yield, and ecosystem services.

Modeling Eragrostis tef Zucc and Hordeum vulgare L cropland in response to food insecurity in the Southwestern parts of Ethiopia

On a global scale, there is consensus to double food production as a means to address food and nutrition insecurity, yet the capacity of available resources and technologies to gratify the demands of this growing population and the price of agricultural commodities remains uncertain in Sub-Saharan Africa, particularly in Ethiopia. Despite the availability of fertile agricultural land, inappropriate use of that resource leads to reduced agricultural productivity, yet little is known about food insecurity and impacts on commodities in southwestern Ethiopia. This study was aimed at spatial modeling of land suitability evaluation for Eragrostis tef Zucc and Hordeum Vulgare L crops in the Misha district. About 11 variables related to topography, climate, and soil have been considered and resampled to 10 m resolution. The spatial analysis result indicated that, about 33.4% and 21.8% of the total area is found to be highly suitable, about 54% and 63% of the total study area is categorized into moderately suitable for Eragrostis tef Zucc and Hordeum Vulgare L crop cultivation, respectively, whereas 12.7% and 15.3% of the study area is not suitable for the above mentioned crops. The spatial decision support system reflects that Misha has mammoth potential productive lands, which are most likely promised to satisfy the demand for food and raw materials. Therefore, the stakeholders should make hard-nosed efforts on sage land use and adopt exactly the optimum land suitability plans to advance the current cropland resources for maximize yield in a sensational way for the healthier development of the region.