Assessment of climate and land use changes impact including extreme events on the sediment yield is vital for water and power stressed countries. Mangla Reservoir is the second-largest reservoir in Pakistan, and its c...Assessment of climate and land use changes impact including extreme events on the sediment yield is vital for water and power stressed countries. Mangla Reservoir is the second-largest reservoir in Pakistan, and its capacity is being reduced due to rapid sedimentation and will be threatened under climate and land use changes. This paper discusses the consequences of climate and land use change on sediment yield at Mangla Dam using General Circulation Models(GCMs), Land Change Modeler(LCM), Soil and Water Assessment Tool(SWAT) model after calibration and validation.Results show that over the historical period temperature is observed to increase by 0.10 o C/decade and forest cover is observed to reduce to the level of only 16% in 2007. Nevertheless, owing to the forest conservation policy, the forest cover raised back to 27% in 2012. Anticipated land use maps by using LCM of 2025, 2050 and 2100 showed that the forest cover will be 33%, 39.2%, and, 53.7%, respectively. All seven GCMs projected the increase in temperature and five GCMs projected an increase in precipitation,however, two GCMs projected a decrease in precipitation. Owing to climate change, land use change and combined impact of climate and land use change on annual sediment yield(2011-2100) may vary from-42.9% to 39.4%, 0% to-27.3% and,-73%to 39.4%, respectively. Under climate change scenarios projected sediment yield is mainly linked with extreme events and is expected to increase with the increase in extreme events. Under land use change scenarios projected sediment yield is mainly linked with the forest cover and is expected to decrease with the increase in forest cover. The results of this study are beneficial for planners, watershed managers and policymakers to mitigate the impacts of climate and land use changes to enhance reservoir life by reducing the sediment yield.展开更多
Satellite-based Precipitation Estimates(SPEs)have gained importance due to enhanced spatial and temporal resolution,particularly in Indus basin,where raingauge network has fewer observation stations and drainage area ...Satellite-based Precipitation Estimates(SPEs)have gained importance due to enhanced spatial and temporal resolution,particularly in Indus basin,where raingauge network has fewer observation stations and drainage area is laying in many countries.Formulation of SPEs is based on indirect mechanism,therefore,assessment and correction of associated uncertainties is required.In the present study,disintegration of uncertainties associated with four prominent real time SPEs,IMERG,TMPA,CMORPH and PERSIANN has been conducted at grid level,regional scale,and summarized in terms of regions as well as whole study area basis.The bias has been disintegrated into hit,missed,false biases,and Root Mean Square Error(RMSE)into systematic and random errors.A comparison among gauge-and satellite-based precipitation estimates at annual scale,showed promising result,encouraging use of real time SPEs in the study area.On grid basis,at daily scale,from box plots,the median values of total bias(-0.5 to 0.5 mm)of the used SPEs were also encouraging although some under/over estimations were noted in terms of hit bias(-0.15 to 0.05 mm/day).Relatively higher values of missed(0.3 to 0.5 mm/day)and false(0.5 to 0.7 mm/day)biases were observed.The detected average daily RMSE,systematic errors,and random errors were also comparatively higher.Regional-scale spatial distribution of uncertainties revealed lower values of uncertainties in plain areas,depicting the better performance of satellite-based products in these areas.However,in areas of high altitude(>4000 m),due to complex topography and climatic conditions(orographic precipitation and glaciated peaks)higher values of biases and errors were observed.Topographic barriers and point scale gauge data could also be a cause of poor performance of SPEs in these areas,where precipitation is more on ridges and less in valleys where gauge stations are usually located.Precipitation system’s size and intensity can also be a reason of higher biases,because Microwave Imager underestimate precipitation in small systems(<200 km^(2))and overestimate in large systems(>2000 km^(2)).At present,use of bias correction techniques at daily time scale is compulsory to utilize real time SPEs in estimation of floods in the study area.Inter comparison of satellite products indicated that IMERG gave better results than the others with the lowest values of systematic errors,missed and false biases.展开更多
文摘Assessment of climate and land use changes impact including extreme events on the sediment yield is vital for water and power stressed countries. Mangla Reservoir is the second-largest reservoir in Pakistan, and its capacity is being reduced due to rapid sedimentation and will be threatened under climate and land use changes. This paper discusses the consequences of climate and land use change on sediment yield at Mangla Dam using General Circulation Models(GCMs), Land Change Modeler(LCM), Soil and Water Assessment Tool(SWAT) model after calibration and validation.Results show that over the historical period temperature is observed to increase by 0.10 o C/decade and forest cover is observed to reduce to the level of only 16% in 2007. Nevertheless, owing to the forest conservation policy, the forest cover raised back to 27% in 2012. Anticipated land use maps by using LCM of 2025, 2050 and 2100 showed that the forest cover will be 33%, 39.2%, and, 53.7%, respectively. All seven GCMs projected the increase in temperature and five GCMs projected an increase in precipitation,however, two GCMs projected a decrease in precipitation. Owing to climate change, land use change and combined impact of climate and land use change on annual sediment yield(2011-2100) may vary from-42.9% to 39.4%, 0% to-27.3% and,-73%to 39.4%, respectively. Under climate change scenarios projected sediment yield is mainly linked with extreme events and is expected to increase with the increase in extreme events. Under land use change scenarios projected sediment yield is mainly linked with the forest cover and is expected to decrease with the increase in forest cover. The results of this study are beneficial for planners, watershed managers and policymakers to mitigate the impacts of climate and land use changes to enhance reservoir life by reducing the sediment yield.
文摘Satellite-based Precipitation Estimates(SPEs)have gained importance due to enhanced spatial and temporal resolution,particularly in Indus basin,where raingauge network has fewer observation stations and drainage area is laying in many countries.Formulation of SPEs is based on indirect mechanism,therefore,assessment and correction of associated uncertainties is required.In the present study,disintegration of uncertainties associated with four prominent real time SPEs,IMERG,TMPA,CMORPH and PERSIANN has been conducted at grid level,regional scale,and summarized in terms of regions as well as whole study area basis.The bias has been disintegrated into hit,missed,false biases,and Root Mean Square Error(RMSE)into systematic and random errors.A comparison among gauge-and satellite-based precipitation estimates at annual scale,showed promising result,encouraging use of real time SPEs in the study area.On grid basis,at daily scale,from box plots,the median values of total bias(-0.5 to 0.5 mm)of the used SPEs were also encouraging although some under/over estimations were noted in terms of hit bias(-0.15 to 0.05 mm/day).Relatively higher values of missed(0.3 to 0.5 mm/day)and false(0.5 to 0.7 mm/day)biases were observed.The detected average daily RMSE,systematic errors,and random errors were also comparatively higher.Regional-scale spatial distribution of uncertainties revealed lower values of uncertainties in plain areas,depicting the better performance of satellite-based products in these areas.However,in areas of high altitude(>4000 m),due to complex topography and climatic conditions(orographic precipitation and glaciated peaks)higher values of biases and errors were observed.Topographic barriers and point scale gauge data could also be a cause of poor performance of SPEs in these areas,where precipitation is more on ridges and less in valleys where gauge stations are usually located.Precipitation system’s size and intensity can also be a reason of higher biases,because Microwave Imager underestimate precipitation in small systems(<200 km^(2))and overestimate in large systems(>2000 km^(2)).At present,use of bias correction techniques at daily time scale is compulsory to utilize real time SPEs in estimation of floods in the study area.Inter comparison of satellite products indicated that IMERG gave better results than the others with the lowest values of systematic errors,missed and false biases.
