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Correct estimation of soil loss at catchment level helps the land and water resources planners to identify priority areas for soil conservation measures
. Soil erosion is one of the major hazards affected by the climate change, particularly the increasing intensity of rainfall resulted in increasing erosion, apart from other factors like landuse change. Changes in climate have an adverse effect with increasing rainfall. It has caused increasing concern for modeling the future rainfall and projecting future soil erosion. In the present study, future rainfall has been generated with the downscaling of GCM (Global Circulation Model) data of Mandakini river basin, a hilly catchment in the state of Uttarakhand, India, to obtain future impact on soil erosion within the basin. The USLE is an erosion prediction model designed to predict the long-term average annual soil loss from specific field slopes in specified landuse and management systems (i.e., crops, rangeland, and recreational areas) using remote sensing and GIS technologies. Future soil erosion has shown increasing trend due to increasing rainfall which has been generated from the statistical-based downscaling method
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Conservation agriculture (CA) is considered as a suitable technique for soil erosion control, productivity enhancement, and improved economic benefits
. To investigate these issues, an experiment was conducted under rainfed conditions using grass vegetation strip (VS) with minimum tillage, organic amendments and weed mulch during June 2007–October 2011 at Dehradun, Uttarakhand in the Indian Himalayan region. Results showed that the mean wheat equivalent yield was ~47% higher in the plots under with CA compared with conventional agriculture in a maize–wheat crop rotation. Mean runoff coefficients and soil loss with CA plots were ~45% less and ~54% less than conventional agriculture plots. On average, after the harvest of maize, soil moisture conservation up to 90cm soil depth for wheat crop was 108% higher under CA than conventional agriculture plots. The net return from the plots with CA was 85% higher, and when expressed net return per tonne of soil loss, it was four and half times higher than conventional practice. Results demonstrate that the suitable CA practice (a grass strip of Palmarosa with applied organic amendments (farmyard manure, vermicompost and poultry manure) along with weed mulching under conservation tillage) enhances system productivity, reduces runoff, soil loss and conserve soil moisture
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Soil and water conservation (SWC) measures are needed to control erosion and sustain agricultural production in mountain regions
. This study assessed the costs and benefits of indigenous SWC measures in a predominantly rural watershed in Sikkim Himalaya, India, from 2009 to 2010. Physical data were obtained through field measurements of soil erosion and runoff in plots with and without SWC measures; further information was collected through a structured questionnaire survey of 150 farm households. Major costs and benefits of various measures implemented in the study area were quantified using net present value, internal rate of return, time horizon, discount rate, payback period, and sensitivity analysis. For a 10-year period and with a 6% discount rate, all the practices were found to have a positive net present value and to help ensure economic and environmental sustainability. The sensitivity analysis showed that the most widespread SWC practices are worth implementing. Some practices not only prevented nutrient loss and retained soil moisture but also provided additional income and increased crop yield. Our findings suggest that agroforestry and vegetative barriers are the most favorable practices
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A state-of-art regional climate modelling system, known as PRECIS (Providing Regional Climates for Impacts Studies) developed by the Hadley Centre for Climate Prediction and Research, is applied for India to develop high-resolution climate change scenarios
. The present day simulation (1961-1990) with PRECIS is evaluated, including an examination of the impact of enhanced resolution and an identification of biases. The RCM is able to resolve features on finer scales than those resolved by the GCM, particularly those related to improved resolution of the topography. The most notable advantage of using the RCM is a more realistic representation of the spatial patterns of summer monsoon rainfall such as the maximum along the windward side of the Western Ghats. There are notable quantitative biases in precipitation over some regions, mainly due to similar biases in the driving GCM. PRECIS simulations under scenarios of increasing greenhouse gas concentrations and sulphate aerosols indicate marked increase in both rainfall and temperature towards the end of the 21st century. Surface air temperature and rainfall show similar patterns of projected changes under A2 and B2 scenarios, but the B2 scenario shows slightly lower magnitudes of the projected change. The warming is monotonously widespread over the country, but there are substantial spatial differences in the projected rainfall changes. West central India shows maximum expected increase in rainfall. Extremes in maximum and minimum temperatures are also expected to increase into the future, but the night temperatures are increasing faster than the day temperatures. Extreme precipitation shows substantial increases over a large area, and particularly over the west coast of India and west central India
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