One crucial metric for estimating a reservoirs and dam’s lifespan is sedimentation. It is dependent upon sediment output, which in turn is dependent upon soil erosion. The study area, the Aguat Wuha Dam, was located in Simada woreda, of northwestern parts of Ethiopia. And the study's goal was to use Arc GIS and RUSLE adjusted to Ethiopian conditions to assess potential soil erosion and sediment output from the watershed and identify hotspot locations for appropriate planning for erosion and sedimentation problem management techniques to make the outputs of the dam project more productive and effective for the proposed and suggested purpose of the dam. To predict the geographical patterns of soil erosion in the watershed, the Geographic Information System (GIS) was combined with the revised universal soil loss equation (RUSLE). A soil erosion map was produced using ArcGIS by utilizing all of the model's parameters, including Erosivity, erodibility, steepness, land use, land cover, and supportive practice factors. The watershed's yearly soil loss varies from 0 to 413.86 tons/ha. In order to determine the erosion hotspot area, the average annual soil loss value was discovered to be 9.24 tons/ha/year and was categorized into six erosion severity classes: low, moderate, high, very high, severe, and very severe. These findings indicated that 162.57 ha and 699.17 ha of the watershed were considered to be extremely and severely vulnerable to soil erosion, respectively. It was discovered that the anticipated sediment yield supplied to the outlet varied from 0 to 104.94 tons/ha/year. By standing from the implications of the assessments of the geological, geotechnical, topographical, and socioenvironmental considerations Watershed management is the most effective way to reduce the amount of sediment produced and the amount that enters the reservoir among the several reservoir sedimentation control options that are available.

Climate change is one of the most critical global challenges, driven primarily by the rapid increase in greenhouse gas concentrations. Carbon sequestration, the process by which ecosystems capture and store carbon, plays a key role in mitigating climate change. This study investigates the factors influencing carbon sequestration in subtropical planted forest ecosystems. Field data were collected from 100 randomly sampled plots of varying sizes (20 m² × 20 m² for trees, 5 m² × 5 m² for shrubs, and 1 m² × 1 m² for herbs) between February and April 2022. A total of 3,440 plants representing 36 species were recorded, with Prosopis juliflora and Prosopis cineraria as the dominant tree species and Desmostachya bipinnata as the dominant herb. Regression analysis, Pearson correlation, and structural equation modeling were performed using R software to explore relationships between carbon sequestration and various biotic and abiotic factors. Biotic factors such as diameter at breast height (DBH; R=0.94), tree height (R=0.83), and crown area (R=0.98) showed strong positive correlations with carbon sequestration. Abiotic factors like litter (R=0.37), humus depth (R=0.43), and electrical conductivity (E.C; R=0.11) also positively influenced carbon storage. Conversely, pH (R=-0.058), total dissolved solids (TDS; R=-0.067), organic matter (R=-0.1), and nitrogen (R=-0.096) negatively impacted carbon sequestration. The findings highlight that both biotic and abiotic factors significantly influence carbon sequestration in planted forests. To enhance carbon storage and mitigate climate change, efforts such as afforestation, reforestation, and conservation of subtropical forest ecosystems are essential.

Soil erosion is characterized by the wearing away or loss of the uppermost layer of soil, driven by water, wind, and human activities. This process constitutes a significant environmental issue, with adverse effects on water quality, soil health, and the overall stability of ecosystems across the globe. This study focuses on the Anuppur district of Madhya Pradesh, India, employing the Revised Universal Soil Loss Equation (RUSLE) integrated with Geographic Information System (GIS) tools to estimate and spatially analyze soil erosion and fertility risk. The various factors of the model, like rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), conservation practices (P), and cover management factor (C), have been computed to measure annual soil loss in the district. Each factor was derived using geospatial datasets, including rainfall records, soil characteristics, a Digital Elevation Model (DEM), land use/land cover (LULC) data, and information on conservation practices. GIS methods are used to map the geographical variation of soil erosion, providing important information on the area's most susceptible to erosion. The outcome of the study reveals that 3371.23 km2, which constitutes 91% of the district's total area, is identified as having mild soil erosion; in contrast, 154 km2, or 4%, is classified as moderate soil erosion, while 92 km2, representing 2.5%, falls under the high soil erosion category. Additionally, 50 km2, or 1.35%, is categorized as very high soil erosion and around 30 km2 of the study area is classified as experiencing severe soil erosion. The analysis further discovers that the annual soil loss in the district varies between 0 and 151 tons per hectare per year. This study indicates that most of the district is classified under low soil erosion; only a tiny fraction of the area is categorized as experiencing high and very high soil erosion. The study provides significant insights into soil erosion for policymakers and human society to bring their attention to the need for sustainable soil conservation practices in the undulating terrain/topography and agriculturally dominated district of Anuppur.

The purpose of this study is to look at the negative environmental impacts and social problems, which require a government response to maintain the sustainability of the palm oil industry. This research uses Online Research Methods (ORMs) to collect data and information through the internet and other digital technologies. The collected data was then coded using Nvivo 12 Plus. The purpose of this study is to fill the research void left by previous researchers by analyzing investment strategies and services in supporting the sustainability of the palm oil industry in Riau Province. This study shows that to support the potential of the palm oil industry to remain optimal, the central and local governments coordinate to provide investment services and pay attention to the sustainability issues of the palm oil industry. Some important aspects to consider are strengthening regulations, an integrated plantation licensing system, improving access to markets, RSPO certification, realization of foreign investment, downstream industry, replanting programme, plantation revitalisation programme, and sustainable plantation partnerships. However, there are still some crucial challenges, particularly land conflicts, climate change, environmental issues, limited technology and innovation, and export market dependence. These challenges may hamper future investment opportunities.

One of the core problems in soil erosion research is the estimation of soil erosion. It is a feasible method and technical approach to estimate soil erosion in Loess Plateau region by using USLE model, GIS and RS technology and using DEM data, meteorological data and land-use type data. With the support of GIS and RS technology, the USLE factors and soil erosion in Loess Plateau region were estimated, and the soil erosion intensity was classified according to the Chinese soil erosion intensity classification standard. The results can provide reference for the development of soil erosion control measures in the Loess Plateau.