The Assessment of Climate Change on Rainfall-Runoff Erosivity in the Chirchik–Akhangaran Basin, Uzbekistan

Curbing land degradation and mitigating climate change in mountainous regions: a systemic review

Human population is envisaged to continue to grow, with a tremendous contribution to land degradation and climate change. Climate change and land degradation are intertwined, thus tackling climate change means mitigating land degradation. Climate change is a worldwide problem that affects lives and livelihoods; henceforth, mitigating measures are urgently required. With their unique, rich biodiversity, mountain areas are severely sensitive to climate change and land degradation; therefore, a speedy need to curb land degradation in mountain areas is needed. The aim of this systematic review was to appraise different strategic methods used globally to minimise land degradation and sustain mountainous areas in a frequently changing climate. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was utilised in this systematic review. The Scopus data base was utilised for document search, with a selection of articles limited between the years 2012 and 2021. Only articles written in English were considered. After assessing the abstracts, 703 articles were retained for a full review, leading to the final selection of 84 articles. The results show that soil erosion, overgrazing and construction of infrastructure are major causes of land degradation. The human population increase is also an enormous contributing factor to activities leading to land degradation and climate change. A conspicuous intensification of agricultural activities is expected to continue due to rising food demand. Curbing land degradation and climate change in mountain areas can be enforced by the government through stricter regulations. However, regulations and policies must be locally initiated, instead of globally initiated, with local communities being the main stakeholders. Hence, bottom-up rather than top-down policies would encourage local communities to embrace mitigation policy initiatives.

Predicting soil erosion potential under CMIP6 climate change scenarios in the Chini Lake Basin, Malaysia

Climate change and soil erosion are very associated with environmental defiance which affects the life sustainability of humans. However, the potency effects of both events in tropical regions are arduous to be estimated due to atmospheric conditions and unsustainable land use management. Therefore, several models can be used to predict the impacts of distinct climate scenarios on human and environmental relationships. In this study, we aimed to predict current and future soil erosion potential in the Chini Lake Basin, Malaysia under different Climate Model Intercomparison Project-6 (CMIP6) scenarios (e.g., SSP2.6, SSP4.5, and SSP8.5). Our results found the predicted mean soil erosion values for the baseline scenario (2019-2021) was around 50.42 t/ha year. The mining areas recorded the highest soil erosion values located in the southeastern part. The high future soil erosion values (36.15 t/ha year) were obtained for SSP4.5 during 2060-2080. Whilst, the lowest values (33.30 t/ha year) were obtained for SSP2.6 during 2040-2060. According to CMIP6, the future soil erosion potential in the study area would reduce by approximately 33.9% compared to the baseline year (2019-2021). The rainfall erosivity factor majorly affected soil erosion potential in the study area. The output of the study will contribute to achieving the United Nations' 2030 Agenda for Sustainable Development.

Effect of climate and ecological restoration on vegetation changes in the "Three-River Headwaters" region based on remote sensing technology

Surface temperature and precipitation are factors effecting vegetation growth. Vegetation coverage change is one of the important factors influencing global and regional climate change. Dynamic monitoring of vegetation change can reflect the trend of climate change to a certain extent. Three-River Headwaters are located in the hinterland of the Qinghai-Tibet Plateau. It has the characteristics of "high, cold, and dry" (higher altitude, cold and dry weather) and its ecosystem is fragile. In recent years, with the global climate change, a series of eco-environmental problems such as river flow cutoff, permafrost degradation, and vegetation destruction has occurred in the headwaters area, which are closely related to climate and vegetation changes. At the same time, in order to solve the problem of ecological environment degradation in the region, various ecological restoration policies have implemented. Several uncertainties in the relationship between vegetation and climate change in the Three-River Headwaters region. This study aims to find out the uncertainties. In this study, the spatial distribution of vegetation coverage was calculated by using NDVI (normalized difference vegetation index) from the first-level product of MODIS (moderate resolution imaging spectroradiometer) remote sensing data. Combining policy factors, the relationship between rainfall, surface temperature, and vegetation growth status were analyzed. The results show that during the study period (1948-2019), the temperature rose significantly and the rainfall increased especially after the implementation of ecological restoration policy (after 2000). Vegetation coverage increased year-by-year (2000-2015). The rainfall effect on surface temperature and vegetation growth, when the summer rainfall increased, the temperature decreased, leads to vegetation coverage decreased (for example, 2001, 2003, 2008 and 2011); the dependence of vegetation on rainfall has obvious lag in Three-River Headwaters in summer. In the years with suitable rainfall and higher temperature in summer, the vegetation grows better and the vegetation coverage increases. This is mainly because the Three-River Headwaters is located in the alpine zone, and vegetation growth is more dependent on temperature. The implementation of ecological restoration policy promotes vegetation coverage. Studying the impact of climate and policy factors on vegetation cover is of great scientific significance and practical value for understanding the ecological restoration mechanism in high cold and arid regions.

Global Challenges and Responses: Agriculture, Economic Globalization, and Environmental Sustainability in Central Asia

Economic globalization (EG) accelerates very fast in Central Asia. This could cause environmental degradation, according to the environmental Kuznets curve (EKC) hypothesis. The study aims to determine how the EG of agriculture impacts environmental sustainability, and to test the EKC hypothesis on the agricultural sector in six Central Asian countries. Particularly, some main hypotheses were proposed using secondary data from Kazakhstan, Kyrgyzstan, Mongolia, Tajikistan, Turkmenistan, and Uzbekistan from 1994 to 2019. This study uses five explanatory variables: agricultural exports value (EXP), agriculture forestry and fishing value-added (AVA), the exchange rate (EXR), total natural resource rents (RENT), and external debt stocks (DEBT), while the dependent variable in this study is the CO2 emissions from on-farm energy use (EMS), temperature changes (TEMP), and forest fires (FIRE). These data are analyzed using panel data regression. As a result, AVA and RENT raise EMS; EXC raises TEMP but lowers EMS; DEBT raises TEMP but can lower FIRE. Hence, we propose recommendations to improve this condition, including a clear roadmap, enhanced partnerships, and regional and international support.

Detailed Analysis of Spatial–Temporal Variability of Rainfall Erosivity and Erosivity Density in the Central and Southern Pannonian Basin

Estimation of rainfall erosivity (RE) and erosivity density (ED) is essential for understanding the complex relationships between hydrological and soil erosion processes. The main objective of this study is to assess the spatial–temporal trends and variability of the RE and ED in the central and southern Pannonian Basin by using station observations and gridded datasets. To assess RE and ED, precipitation data for 14 meteorological stations, 225 grid points. and an erosion model consisting of daily, monthly, seasonal, and annual rainfall for the period of 1961–2014 were used. Annual RE and ED based on station data match spatially variable patterns of precipitation, with higher values in the southwest (2100 MJ·mm·ha−1·h−1) and southeast (1650 MJ·mm·ha−1·h−1) of the study area, but minimal values in the northern part (700 MJ·mm·ha−1·h−1). On the other hand, gridded datasets display more detailed RE and ED spatial–temporal variability, with the values ranging from 250 to 2800 MJ·mm·ha−1·h−1. The identified trends are showing increasing values of RE (ranging between 0.20 and 21.17 MJ·mm·ha−1·h−1) and ED (ranging between 0.01 and 0.03 MJ·ha−1·h−1) at the annual level. This tendency is also observed for autumn RE (from 5.55 to 0.37 MJ·mm·ha−1·h−1) and ED (from 0.05 to 0.01 MJ·ha−1·h−1), as for spring RE (from 1.00 to 0.01 MJ·mm·ha−1·h−1) and ED (from 0.04 to 0.01 MJ·ha−1·h−1), due to the influence of the large-scale processes of climate variability, with North Atlantic Oscillation (NAO) being the most prominent. These increases may cause a transition to a higher erosive class in the future, thus raising concerns about this type of hydro-meteorological hazard in this part of the Pannonian Basin. The present analysis identifies seasons and places of greatest erosion risk, which is the starting point for implementing suitable mitigation measures at local to regional scales.

Spatial-Temporal Variability of Future Rainfall Erosivity and Its Impact on Soil Loss Risk in Kenya

Ongoing climate change poses a major threat to the soil resources of many African countries that mainly rely on an agricultural economy. While arid and semi-arid lands (ASALs) take up most of Kenya’s land mass, approximately 64% of its total croplands lie within mountainous areas with high rainfall, hence, areas highly vulnerable to water erosion. Flooding of the Great Lakes and increasing desertification of the ASALs are illustrative cases of the implications of recent precipitation dynamics in Kenya. This study applied the Revised Universal Soil Loss Equation (RUSLE) to estimate future soil erosion rates at the national level based on four Coupled Model Intercomparison Project v5 (CMIP5) models under two Representative Concentration Pathway (RCP) scenarios. Results showed the current soil loss rate to be at 4.76 t ha−1 yr−1 and projected an increase in average rainfall erosivity under the two scenarios, except for RCP-2.6 (2030s) and (2080s) for the MIROC-5 model. Future projections revealed an incremental change in rainfall erosivity from the baseline climate by a cumulative average of 39.9% and 61.1% for all scenarios by the 2030s and 2080s, respectively, while soil loss is likely to increase concomitantly by 29% and 60%, respectively. The CCCMA_CANESM2 model under the RCP 8.5 (2080s) scenario projected the highest erosion rate of 15 t ha−1 yr−1 over Kenya, which is a maximum increase of above 200%, with the Rift Valley region recording an increase of up to 100% from 7.05 to 14.66 t ha−1 yr−1. As a first countrywide future soil erosion study, this assessment provides a useful reference for preventing water erosion and improving ecosystem service security.

Impact of Climate Factors and Human Activities on Water Resources in the Aral Sea Basin

The Aral Sea in Central Asia plays an essential role in the socio-economic development of the region. During the last six decades, there has been remarkable changes observed in the water level and areal extent of the Aral Sea Basin; however, the causes behind these changes are unclear. This study quantifies the impacts of climatic and anthropogenic drivers on Aral Sea and the contributions made by these drivers to the variations observed in the Aral Sea Basin. The spatial and temporal seasonal variations in groundwater budget have been analyzed using the total water storage (TWS) of the basin from 2002 to 2015. The results from this study revealed significant increases in the the mean air temperature, precipitation, and potential evapotranspiration rate from 1960 to 2015 in the Aral Sea Basin. The TWS time-series shows a statistically significant declining trend of about 2 to 4 cm per year presented by the surface water storage. Based on the average monthly values of TWS, March 2005 presented the highest anomaly ~7.85 cm, while October 2008 showed the lowest anomaly ~8.22 cm between 2002 to 2015. The groundwater level indicates a small increasing trend of approximately 0.05 cm/year during the study period. Furthermore, the negative relationship between water level, climatic, and anthropogenic factors showed that these factors projected critical impact on the water level fluctuations within the Aral Sea Basin.