Climate change affects the environment and natural resources immensely.Rainfall,temperature and evapotranspiration are major parameters of climate affecting changes in the environment.Evapotranspiration plays a key ro...Climate change affects the environment and natural resources immensely.Rainfall,temperature and evapotranspiration are major parameters of climate affecting changes in the environment.Evapotranspiration plays a key role in crop production and water balance of a region,one of the major parameters affected by climate change.The reference evapotranspiration or ETo is a calculated parameter used in this research.In the present study,changes in the future rainfall,minimum and maximum temperature,and ETo have been shown by downscaling the HadCM3(Hadley Centre Coupled Model version 3) model data.The selected study area is located in a part of the Narmada river basin area in Madhya Pradesh in central India.The downscaled outputs of projected rainfall,ET_0 and temperatures have been shown for the 21 st century with the HADCM3 data of A2 scenario by the Least Square Support Vector Machine(LS-SVM)model.The efficiency of the LS-SVM model was measured by different statistical methods.The selected predictors show considerable correlation with the rainfall and temperature and the application of this model has been done in a basin area which is an agriculture based region and is sensitive to the change of rainfall and temperature.Results showed an increase in the future rainfall,temperatures and ETo.The temperature increase is projected in the high rise of minimum temperature in winter time and the highest increase in maximum temperature is projected in the pre-monsoon season or from March to May.Highest increase is projected in the 2080 s in 2081-2091 and 2091-2099 in maximum temperature and 2091-2099 in minimum temperature in all the stations.Winter maximum temperature has been observed to have increased in the future.High rainfall is also observed with higher ETo in some decades.Two peaks of the increase are observed in ET_0 in the April-May and in the October.Variation in these parameters due to climate change might have an impact on the future water resource of the study area,which is mainly an agricultural based region,and will help in proper planning and management.展开更多
Digital Elevation Model(DEM) is one of the important parameters for soil erosion assessment.Notable uncertainties are observed in this study while using three high resolution open source DEMs.The Revised Universal Soi...Digital Elevation Model(DEM) is one of the important parameters for soil erosion assessment.Notable uncertainties are observed in this study while using three high resolution open source DEMs.The Revised Universal Soil Loss Equation(RUSLE) model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs(SRTM,ASTER and CARTOSAT) and their increasing grid space(pixel size) from the actual.The study area is a part of the Narmada river basin in Madhya Pradesh state,which is located in the central part of India and the area covered 20.558 km^2.The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90,150,210.270 and 330 m for this study.Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map(toposheet).Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL(Mean Sea Level),before the accuracy assessment and modelling.Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31,14.51,and 18.19 m in 30,150 and 330 m resolution respectively,is better than the ASTER and the CARTOSAT DEMs.When the grid space of the DEMs increases,the accuracy of the elevation and calculated soil erosion decreases.This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models.The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling.展开更多
Temporal change in rainfall erosivity varies due to the rainfall characteristic(amount,intensity,frequency,duration),which affects the conservation of soil and water.This study illustrates the variation of rainfall er...Temporal change in rainfall erosivity varies due to the rainfall characteristic(amount,intensity,frequency,duration),which affects the conservation of soil and water.This study illustrates the variation of rainfall erosivity due to changing rainfall in the past and the future.The projected rainfall is generated by SDSM(Statistical DownScaling Model)after calibration and validation using two GCMs(general circulation model)data of HadCM3(A2 and B2 scenario)and CGCM3(A1B and A2 scenario).The selected study area is mainly a cultivable area with an agricultural based economy.This economy depends on rainfall and is located in a part of the Narmada river basin in central India.Nine rainfall locations are selected that are distributed throughout the study area and surrounding.The results indicate gradually increasing projected rainfall while the past rainfall has shown a declined pattern by Mann–Kendall test with statistical 95%confidence level.Rainfall erosivity has increased due to the projected increase in the future rainfall(2080 s)in comparison to the past.Rainfall erosivity varies from32.91%to 24.12%in the 2020s,18.82 to 75.48%in 2050 s and 20.95–202.40%in 2080s.The outputs of this paper can be helpful for the decision makers to manage the soil water conservation in this study area.展开更多
Long-term droughts significantly impact surface and groundwater resources in India,however,observed changes in major river basins have not been well explored.Here we use Standardized Precipitation Index(SPI)and Standa...Long-term droughts significantly impact surface and groundwater resources in India,however,observed changes in major river basins have not been well explored.Here we use Standardized Precipitation Index(SPI)and Standardized Precipitation Evapotranspiration Index(SPEI)at three different time scales(24,48,and 60 months)to identify long-term droughts in India for the observed record of 1951-2015.Drought characteristics(extent,events,frequency,and intensity)are analyzed for different river basins in India.Increasing trend in the areal extent of droughts is observed in two methods with three time scales in the maximum area(63.66%)in India.We use the data from the Gravity Recovery and Climate Experiment(GRACE)to estimate the changes in the terrestrial water storage(TWS)during the period 2002-2015.We identify that major long-term droughts in India occurred from 1966 to 1969,1972,1986-1987,and 2002-2004.The all-India average TWS shows a negative trend from 2002 to 2015 with prominent decline in north Indian river basins and positive trend in south Indian river basins.SPI and SPEI at longer time scales are positively associated with TWS indicating the adverse impacts of droughts on surface and groundwater resources in such a populated region.展开更多
基金the University Grant Commission(UGC) for providing financial assistance in this research
文摘Climate change affects the environment and natural resources immensely.Rainfall,temperature and evapotranspiration are major parameters of climate affecting changes in the environment.Evapotranspiration plays a key role in crop production and water balance of a region,one of the major parameters affected by climate change.The reference evapotranspiration or ETo is a calculated parameter used in this research.In the present study,changes in the future rainfall,minimum and maximum temperature,and ETo have been shown by downscaling the HadCM3(Hadley Centre Coupled Model version 3) model data.The selected study area is located in a part of the Narmada river basin area in Madhya Pradesh in central India.The downscaled outputs of projected rainfall,ET_0 and temperatures have been shown for the 21 st century with the HADCM3 data of A2 scenario by the Least Square Support Vector Machine(LS-SVM)model.The efficiency of the LS-SVM model was measured by different statistical methods.The selected predictors show considerable correlation with the rainfall and temperature and the application of this model has been done in a basin area which is an agriculture based region and is sensitive to the change of rainfall and temperature.Results showed an increase in the future rainfall,temperatures and ETo.The temperature increase is projected in the high rise of minimum temperature in winter time and the highest increase in maximum temperature is projected in the pre-monsoon season or from March to May.Highest increase is projected in the 2080 s in 2081-2091 and 2091-2099 in maximum temperature and 2091-2099 in minimum temperature in all the stations.Winter maximum temperature has been observed to have increased in the future.High rainfall is also observed with higher ETo in some decades.Two peaks of the increase are observed in ET_0 in the April-May and in the October.Variation in these parameters due to climate change might have an impact on the future water resource of the study area,which is mainly an agricultural based region,and will help in proper planning and management.
基金the Council of Scientific&Industrial Research (CSIR)
文摘Digital Elevation Model(DEM) is one of the important parameters for soil erosion assessment.Notable uncertainties are observed in this study while using three high resolution open source DEMs.The Revised Universal Soil Loss Equation(RUSLE) model has been applied to analysis the assessment of soil erosion uncertainty using open source DEMs(SRTM,ASTER and CARTOSAT) and their increasing grid space(pixel size) from the actual.The study area is a part of the Narmada river basin in Madhya Pradesh state,which is located in the central part of India and the area covered 20.558 km^2.The actual resolution of DEMs is 30 m and their increasing grid spaces are taken as 90,150,210.270 and 330 m for this study.Vertical accuracy of DEMs has been assessed using actual heights of the sample points that have been taken considering planimetric survey based map(toposheet).Elevations of DEMs are converted to the same vertical datum from WGS 84 to MSL(Mean Sea Level),before the accuracy assessment and modelling.Results indicate that the accuracy of the SRTM DEM with the RMSE of 13.31,14.51,and 18.19 m in 30,150 and 330 m resolution respectively,is better than the ASTER and the CARTOSAT DEMs.When the grid space of the DEMs increases,the accuracy of the elevation and calculated soil erosion decreases.This study presents a potential uncertainty introduced by open source high resolution DEMs in the accuracy of the soil erosion assessment models.The research provides an analysis of errors in selecting DEMs using the original and increased grid space for soil erosion modelling.
基金The authors express their thanks to the Indian Meteorological Department(IMD)for the rainfall data and the Pacific Climate Impacts Consortium(PCIC)for the GCM and NCEP Data.The authors are also thankful to the Council of Scientific&Industrial Research(CSIR)(Roll no.200773,Ref.No.20-12/2009(ii)EU-IV)for financial assistance.
文摘Temporal change in rainfall erosivity varies due to the rainfall characteristic(amount,intensity,frequency,duration),which affects the conservation of soil and water.This study illustrates the variation of rainfall erosivity due to changing rainfall in the past and the future.The projected rainfall is generated by SDSM(Statistical DownScaling Model)after calibration and validation using two GCMs(general circulation model)data of HadCM3(A2 and B2 scenario)and CGCM3(A1B and A2 scenario).The selected study area is mainly a cultivable area with an agricultural based economy.This economy depends on rainfall and is located in a part of the Narmada river basin in central India.Nine rainfall locations are selected that are distributed throughout the study area and surrounding.The results indicate gradually increasing projected rainfall while the past rainfall has shown a declined pattern by Mann–Kendall test with statistical 95%confidence level.Rainfall erosivity has increased due to the projected increase in the future rainfall(2080 s)in comparison to the past.Rainfall erosivity varies from32.91%to 24.12%in the 2020s,18.82 to 75.48%in 2050 s and 20.95–202.40%in 2080s.The outputs of this paper can be helpful for the decision makers to manage the soil water conservation in this study area.
文摘Long-term droughts significantly impact surface and groundwater resources in India,however,observed changes in major river basins have not been well explored.Here we use Standardized Precipitation Index(SPI)and Standardized Precipitation Evapotranspiration Index(SPEI)at three different time scales(24,48,and 60 months)to identify long-term droughts in India for the observed record of 1951-2015.Drought characteristics(extent,events,frequency,and intensity)are analyzed for different river basins in India.Increasing trend in the areal extent of droughts is observed in two methods with three time scales in the maximum area(63.66%)in India.We use the data from the Gravity Recovery and Climate Experiment(GRACE)to estimate the changes in the terrestrial water storage(TWS)during the period 2002-2015.We identify that major long-term droughts in India occurred from 1966 to 1969,1972,1986-1987,and 2002-2004.The all-India average TWS shows a negative trend from 2002 to 2015 with prominent decline in north Indian river basins and positive trend in south Indian river basins.SPI and SPEI at longer time scales are positively associated with TWS indicating the adverse impacts of droughts on surface and groundwater resources in such a populated region.
