CMIP5 Climate Projections and RUSLE-Based Soil Erosion Assessment in The Central Part of Iran [post]

Fatemeh Hateffard, Safwan Mohammed, Karam Alsafadi, Glory Enaruvbe, Ahmad Heidari, Hazem Ghassan Abdo, Jesus Rodrigo Comino
2020 unpublished
Soil erosion (SE) and climate change are closely related to environmental challenges that influence human wellbeing. However, the potential impacts of both processes in semi-arid areas are difficult to be predicted because of atmospheric variations and non-sustainable land use management. Thus, models can be employed to estimate the potential effects of different climatic scenarios on environmental and human interactions. In this research, we present a novel study where changes in soil erosion
more » ... y water in the central part of Iran under current and future climate scenarios are analyzed using the Climate Model Intercomparison Project-5 (CMIP5) under three Representative Concentration Pathway-RCP 2.6, 4.5 and 8.5 scenarios. Results showed that the estimated annual rate of SE in the study area in 2005, 2010, 2015 and 2019 averaged approximately 12.8 t ha −1 y −1 . The rangeland areas registered the highest soil erosion values, especially in RCP2.6 and RCP8.5 for 2070 with overall values of 4.25 t ha −1 y −1 and 4.1 t ha −1 y −1 , respectively. They were followed by agriculture fields with 1.31 t ha −1 y −1 and 1.33 t ha −1 y −1 . The lowest results were located in the residential areas with 0.61 t ha −1 y −1 and 0.63 t ha −1 y −1 in RCP2.6 and RCP8.5 for 2070, respectively. In contrast, RCP4.5 showed that the total soil erosion could experience a decrease in rangelands by − 0.24 t ha −1 y −1 (2050), and − 0.18 t ha −1 y −1 (2070) or a slight increase in the other land uses. We conclude that this study provides new insights for policymakers and stakeholders to develop appropriate strategies to achieve sustainable land resources planning in semi-arid areas that could be affected by future and unforeseen climate change scenarios. Changes in land uses have consistently been described because of rapid population growth and the expansion of human settlement around the world 1-7 . These changes play important roles in shaping the landscape and altering land resources, sometimes with negative impacts 8 . Numerous scholars have concluded that unregulated land-use changes lead to environmental degradation that poses a major threat to the socioeconomic and ecological sustainability of soil as a vital resource 9-11 . Increasing pressure on land resources because of unsustainable cultivation, overgrazing, deforestation, climate change and drought, urbanization and poor land management practices are worsening land degradation on a global scale 12-15 . Among them, soil erosion (SE) is one of the common forms of land degradation that is related to unsustainable environmental management. Soil erosion is particularly severe in arid and semi-arid regions 15-20 . SE is a complex process resulting from the impacts of wind, precipitation, human activities and associated runoff processes that are influenced by parent material, soil properties, relief and vegetation cover 21, 22 . Although OPEN SE may occur naturally, anthropogenic activities such as land-use change, agriculture, livestock grazing or deforestation are known to exacerbate erosion and soil degradation 23-25 . Therefore, SE is considered a natural and human-induced challenge 9,13,22 , that leads to severe adverse socioeconomic and environmental damage in many societies 26, 27 . Despite the important implications of SE on sustainable use of soil; however, there is limited information on current and future scenarios. The dearth of this information is linked to the complexity of erosion processes which makes SE estimation expensive, time-consuming and difficult 28, 29 . This difficulty has resulted in the development of various models and tools that seek to simplify SE modelling and improve our understanding of the pattern and processes of SE. The Universal Soil Loss Equation (USLE) 30,31 model is widely used for estimating SE because it integrates many of the components of the SE process 13, 26, 29, 32, 33 . Apart from the anthropogenic factors driving SE, recent studies show that other factors influencing land degradation are climate-related 32,34,35 . On the other hand, the Intergovernmental Panel on Climate Change (IPCC) has launched the four future scenarios for earth greenhouse gases (GHGs) emission, which is known as Representative Concentration Pathways (RCPs) 2.6, 4.5, 6, and 8.5 36 . These scenarios simulate different GHGs emission, the RCP2.6 refer to low GHGs emission, the RCP4.5, and RCP6 express as stabilization scenarios, while RCP8.5 denote high GHGs emission 37 . Studies have been carried out to predict the impact of future climate on soil erosion by using different CMIP5-RCP scenarios (i.e. Tibetan Plateau 38 ; Lancang-Mekong River 39 ; Minab Dam Watershed 35 ; Burkina Faso 40 ; mid-Yarlung Tsangpo River region 41 ). SE is a natural geomorphological process (erosion, transport and sedimentation) but after human disturbances can be considered as a land degradation one, which has been a recurring challenge for decades over the world for stakeholders, and especially, in countries such as Iran. Recently, scientists have examined land degradation indicators including desertification 42 , deforestation 43 , salinization 44 , alkalization of soils 45 , overgrazing 46 , intensive land-use changes 47 , and especially, water and wind erosion 48,49 . Many of these studies integrated remote sensing, Geographic Information System (GIS) and the RUSLE approach for the estimation of SE 50-55 . Other recent techniques such as Artificial Neural Networks or Machine Learning techniques are also becoming popular for erosion simulation and modelling in Iran 29,56,57 . However, despite the numerous studies on SE estimation, there is limited information on SE estimation based on future climate change (CC) scenarios in Iran and other arid and semi-arid countries. Thus, the main goals of this research are to 1) estimate the current SE in the central part of Iran, and 2) predict SE changes under future climate scenarios using Climate Model Intercomparison Project-5 (CMIP5). We hypothesize that this will provide important information for policymakers and stakeholders to develop appropriate strategies to achieve sustainable land resource planning, utilization and management.
doi:10.22541/au.158981430.00704431 fatcat:figpyhj4bjeyle537cjhswd55q