IMPACT ASSESSMENT OF CLIMATE AND LANDUSE CHANGES ON SOIL EROSION AND CARBON LOSS

Abstract

Threat of global warming is a major concern to the world. It is determined to change the future climate, which might cause an adverse impact on agriculture, water resources, environments, hydrological cycle, etc. It can affect the economy related to agricultural production or agricultural based economy leading to food shortages. However, adverse impacts can be mitigated to some extent if proper management plans can be applied. In the present study, historical data have been used for the climate trend analysis and future projection of precipitation is done for analysing climate change of the study area. Landuse change detection and future prediction has been carried out to estimate the effect of future changes of landuse on soil erosion. The soil erosion modelling is done and soil organic carbon is estimated in the laboratory to evaluate the impact of climate and landuse changes on soil erosion and soil organic carbon loss in future. Historical recorded data of rainfall and temperature have been used for trend analysis by suitable statistical techniques using data of more than 100 years. The trend analysis is illustrated in different scales (India, State and basin scale). Projection of future rainfall has been generated by LS-SVM (Least-Square Support Vector Machine) and SDSM (Statistical Downscaling Model) methods using GCM (General Circulation Model) data. Supervised Fuzzy C-Mean (FCM) was used for classification of landuse using satellite imagery. Classified images were further used for future prediction of landuse scenario for analysing the change detection. Soil erosion models of USLE (Universal Soil Loss Equation), RUSLE (Revised Universal Soil Loss Equation) and MMF (Morgan-Morgan-Finney) are applied for estimating the soil erosion and to identify the suitable model for the study area. Assessment of the impact of climate and landuse changes on soil erosion has been carried out in past, present and future time period. SOC (Soil Organic Carbon) is tested from the soil samples collected from the field. Locations of sample points are spatially interpolated by Regression Kriging (RK) method. Finally, analysis of SOC loss has been carried out using soil erosion and SOC stock. ii In India, rainfall has shown a negative trend in annual and monsoon season. The decreasing rainfall trend is observed in Madhya Pradesh (MP) and the basin area within MP, except for few locations. Maximum, minimum and mean temperatures have shown increase in different scale for the study. The future projected rainfall has shown an increasing trend in both methods (LS-SVM and SDSM), but the past trend was decreasing. The landuse detection have shown an increase of settlement and water area from 1990 to 2050 and decreased area of vegetation and fallow land. Agricultural lands have shown increase from 1990 to 2011, but in 2020 and 2050 there is a slight decrease in the agricultural land due to the encroachment of the continuously increasing settlement in these areas. Up to 2011, vegetation and fallow lands have been transformed into agricultural areas, and in 2020, there is a continuous transfer of vegetation or fallow land to the agricultural land and also to settlement. In 2050, the transfer of vegetated area to other classes has reduced, while transfer of fallow to agriculture and fallow and agriculture to settlement is more. Three soil erosion models are used to estimate the soil erosion status of the study area and have been compared. RUSLE model outputs are closer to the observed data. MMF and USLE models have estimated 39.45% and 9.60% extra load, while RUSLE has calculated 4.80% of less sediment load than the observed data. Stock of SOC estimation is observed to be more (average 12.77gm/kg) in less slope region while SOC is less (average 5.77gm/kg) in the highest degree of slopes. Natural vegetated areas and agricultural areas are showing more stock of SOC (average 15.60 and 12.24gm/kg). SOC in clay soil is highest (average 12.68gm/kg) and sandy loam is least (average 8.5gm/kg) with respect to the clay loam and sandy clay loam. The effect of climate (precipitation) change has strongly indicated increased rate of soil erosion and SOC loss in future as observed by using the generated projected precipitation by the LS-SVM and SDSM models. In contrast, the landuse change has indicated decreased erosion rate and SOC loss in future in 2050. The overall results indicate the increasing rate of soil erosion and SOC loss in the basin area due to climate and landuse change. However, there is always uncertainty as the interaction of soil, climate and landuse is complex, and it is not possible to reach any agreement without difficulty. Soil carbon is an essential factor to be considered in the assessment of soil erosion potential. The residues and vegetative covers add nutrients to the soil, reducing the impact of raindrops on bare ground causing less erosion. Therefore, if proper plans are executed such that the top soil remain covered, iii particularly during monsoon time or when there is a high intensity of rainfall, then it may help in reducing erosion. This study has highlighted the importance of climate analysis at the local and broader level, along with the impact of human intervention that may be considered in the decision making process.