Environmental Science
N. Robertson; B. Oinam
Abstract
BACKGROUND AND OBJECTIVES: Land suitability analysis is a technique of attaining optimum utilization of natural available land resource. This study is the first attempt to map the potential rice suitability zone besides the existing rice cultivation zone in Imphal-Iril River catchment. The overriding ...
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BACKGROUND AND OBJECTIVES: Land suitability analysis is a technique of attaining optimum utilization of natural available land resource. This study is the first attempt to map the potential rice suitability zone besides the existing rice cultivation zone in Imphal-Iril River catchment. The overriding objective of this study is to identify the land suitability potential zones for rice crop cultivation. The study was carried-out in Imphal-Iril River catchment, Manipur, India.METHODS: The suitability analysis was carried-out based on soil, climate and topographic parameters as the input variable using integrated geographical information system and analytic hierarchy process, a multi criteria decision based approach. To compute criteria weight for various suitability classes, pairwise comparison matrix was applied using analytical hierarchy process and the resulting weights were used for assigning criteria ranking.FINDINGS: The study result indicates that the major section of high and moderate potential suitability zones of rice is concentrated in the flatter valley regions of the catchment. The result also indicates that there is 79.15 km2 of the area which can be potentially cultivated other than the existing agriculture cover. The major patches of such zones are found in the north-western portion of the valley region in the catchment.CONCLUSION: This study clearly indicates, the potential zones lying in the foothills in the north-western which are still not under the agriculture cover have the potential to be cultivated as per the model result. The model result clearly indicates the potential of geographical information system integrated with analytical hierarchy process technique can be utilized to decide the weights of each individual parameter using experts’ opinions which can serve as a versatile tool to carry-out such kind of analysis which can aid policy makers.
Environmental Management
C. Loukrakpam; B. Oinam
Abstract
BACKGROUND AND OBJECTIVE: Soil erosion is considered one of the major indicators of soil degradation in our environment. Extensive soil erosion process leads to erosion of nutrients in the topsoil and decreases in fertility and hence productivity. Moreover, creeping erosion leads to landslides in the ...
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BACKGROUND AND OBJECTIVE: Soil erosion is considered one of the major indicators of soil degradation in our environment. Extensive soil erosion process leads to erosion of nutrients in the topsoil and decreases in fertility and hence productivity. Moreover, creeping erosion leads to landslides in the hilly regions of the study area that affects the socio-economics of the inhabitants. The current study focuses on the estimation of soil erosion rate for the year 2011 to 2019 and projection for the years 2021, 2023 and 2025.METHODS: In this study, the Revised Universal Soil Loss Equation is used for estimation of soil erosion in the study area for the year 2011 to 2019. Using Artificial Neural Network-based Cellular Automata simulation, the Land Use Land Cover is projected for the future years 2021, 2023 and 2025. Using the projected layer as one of the spatial variables and applying the same model, Soil Erosion based on Revised Universal soil loss equation is projected for a corresponding years.FINDINGS: For both cases of projection, simulated layers of 2019 (land use land cover and soil erosion) are correlated with the estimated layer of 2019 using actual variables and validated. The agreement and accuracy of the model used in the case land use are 0.92 and 96.21% for the year 2019. The coefficient of determination of the model for both simulations is also observed to be 0.875 and 0.838. The simulated future soil erosion rate ranges from minimum of 0 t/ha/y to maximum of 524.271 t/ha/y, 1160.212 t/ha/y and 783.135 t/ha/y in the year 2021, 2023 and 2025, respectively.CONCLUSION: The study has emphasized the use of artificial neural network-based Cellular automata model for simulation of land use and land cover and subsequently estimation of soil erosion rate. With the simulation of future soil erosion rate, the study describes the trend in the erosion rate from past to future, passing through present scenario. With the scarcity of data, the methodology is found to be accurate and reliable for the region under study.
V. Anand; B. Oinam
Abstract
Hydrological components in a river basin can get adversely affected by climate change in coming future. Manipur River basin lies in the extreme northeast region of India nestled in the lesser Himalayan ranges and it is under severe pressure from anthropogenic and natural factors. Basin is un-gauged as ...
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Hydrological components in a river basin can get adversely affected by climate change in coming future. Manipur River basin lies in the extreme northeast region of India nestled in the lesser Himalayan ranges and it is under severe pressure from anthropogenic and natural factors. Basin is un-gauged as it lies in remote location and suffering from large data scarcity. This paper explores the impact of climate change towards understanding the inter-relationships between various complex hydrological factors in the river basin. An integrated approach is applied by coupling Soil and Water Assessment Hydrological Model and Hadley Center Coupled Model based on temperature, rainfall and geospatial data. Future representative concentration pathways 2.6, 4.5 and 8.5 scenarios for 2050s and 2090s decades were used to evaluate the effects of climatic changes on hydrological parameters. Both annual mean temperature and annual precipitation is predicted to be increased by 2.07oC and 62% under RCP 8.5 by the end of 21st century. This study highlights that change in meteorological parameters will lead to significant change in the hydrological regime of the basin. Runoff, actual evapotranspiration and water yield are expected to be increased by 40.96 m3/s, 52.2% and 86.8% respectively under RCP 8.5. This study shows that water yield and evapotranspiration will be most affected by increase in precipitation and temperature in the upper and middle sub-basins. Different region within the basin is likely to be affected by frequent landslides and flood in coming decades.
