Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. ...Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends （＋0.11℃decade） reported for the entire north-west Himalaya for past century and the regional warming （＋0.7℃/decade） trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model （SRM） based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamfiow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5%-40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.展开更多
The role of forests is being actively considered under the agenda of REDD＋ （Reducing Emissions from Deforestation and Forest Degradation plus） aimed at reducing emissions related to changes in forest cover and fore...The role of forests is being actively considered under the agenda of REDD＋ （Reducing Emissions from Deforestation and Forest Degradation plus） aimed at reducing emissions related to changes in forest cover and forest quality. Forests in general have undergone negative changes in the past in the form of deforestation and degradation, while in some countries positive changes are reported in the form of conservation, sustainable management of forests and enhancement of carbon stock. The present study in the Kashmir Himalayan forests is an effort to assess historical forest cover changes that took place from 1980 to 2009 and to predict the same for 2030 on the basis of past trend using geospatial modeling approach. Landsat data （Multispectral Scanner （MSS）, Thematic Mapper （TM） and Enhanced Thematic Mapper （ETM＋）） was used for the years 1980, 199o and （2001, 2009） respectively and change detection analysis between the dates was performed. The maps generated were validated through ground truthing. The study area （3375.62 km^2） from 1980-2009 has uffered deforestation and forest degradation of about 126 km^2 and 239.02 km^2 respectively which can be claimed under negative options of REDD＋, while as the area that experienced no change （1514 km^2） can be claimed under conservation. A small area （23.31 km^2） observed as positive change can be claimed under positive options. The projected estimates of forest cover for 2030 showed increased deforestation and forest degradation on the basis of trend analysis using Cellular Automata （CA） Markov modeling. Despite the fact that country as a whole has registered a net positive change in the past few decades, but there are regions like Kashmir region of western Himalaya which have constantly undergoing deforestation as well as degradation in the past few decades.展开更多
With the growing recognition to myriad forms of current and future threats in the mountain agriculture systems,there is a pressing need to holistically understand the vulnerability of mountain agriculture communities....With the growing recognition to myriad forms of current and future threats in the mountain agriculture systems,there is a pressing need to holistically understand the vulnerability of mountain agriculture communities.The study aims to assess the biophysical and social vulnerability of agriculture communities using an indicator-based approach for the state of Uttarakhand,India.A total of 14 indicators were used to capture biophysical vulnerability and 22 for social vulnerability profiles of15285 villages.Vulnerability analysis was done at village level with weights assigned to each indicator using Analytical Hierarchical Process(AHP).The results of the study highlight the presence of very high biophysical vulnerability(0.82 ± 0.10) and high social vulnerability(0.65 ± 0.15) within the state.Based on the results,it was found that incidences of high biophysical vulnerability coincide with presence of intensified agriculture land and absence of dense forest.Higher social vulnerability scores were found in villages with an absence of local institutions(like Self Helping Groups(SHGs)),negligible infrastructure facilities and higher occupational dependence on agriculture.A contrast was observed in the vulnerability scores of villages present in the three different altitudinal zones in the study area,indicating respective vulnerability generating conditions existing in these three zones.Biophysical vulnerability was recorded to be highest in the villages falling in the lower zone and lowest in the upper zone villages;whereas,social vulnerability was found to be highest in the middle zone villages and lowest in lower zone villages.Our study aids policy makers in identifying areas for intervention to expedite agriculture adaptation planning in the state.Additionally,the adaptation programmes in the region need to be more context-specific to accommodate the differential altitudinal vulnerability profiles.展开更多
文摘Air temperature and snow cover variability are sensitive indicators of climate change. This study was undertaken to forecast and quantify the potential streamflow response to climate change in the Jhelum River basin. The implications of air temperature trends （＋0.11℃decade） reported for the entire north-west Himalaya for past century and the regional warming （＋0.7℃/decade） trends of three observatories analyzed between last two decades were used for future projection of snow cover depletion and stream flow. The streamflow was simulated and validated for the year 2007-2008 using snowmelt runoff model （SRM） based on in-situ temperature and precipitation with remotely sensed snow cover area. The simulation was repeated using higher values of temperature and modified snow cover depletion curves according to the assumed future climate. Early snow cover depletion was observed in the basin in response to warmer climate. The results show that with the increase in air temperature, streamfiow pattern of Jhelum will be severely affected. Significant redistribution of streamflow was observed in both the scenarios. Higher discharge was observed during spring-summer months due to early snowmelt contribution with water deficit during monsoon months. Discharge increased by 5%-40% during the months of March to May in 2030 and 2050. The magnitude of impact of air temperature is higher in the scenario-2 based on regional warming. The inferences pertaining to change in future streamflow pattern can facilitate long term decisions and planning concerning hydro-power potential, waterresource management and flood hazard mapping in the region.
文摘The role of forests is being actively considered under the agenda of REDD＋ （Reducing Emissions from Deforestation and Forest Degradation plus） aimed at reducing emissions related to changes in forest cover and forest quality. Forests in general have undergone negative changes in the past in the form of deforestation and degradation, while in some countries positive changes are reported in the form of conservation, sustainable management of forests and enhancement of carbon stock. The present study in the Kashmir Himalayan forests is an effort to assess historical forest cover changes that took place from 1980 to 2009 and to predict the same for 2030 on the basis of past trend using geospatial modeling approach. Landsat data （Multispectral Scanner （MSS）, Thematic Mapper （TM） and Enhanced Thematic Mapper （ETM＋）） was used for the years 1980, 199o and （2001, 2009） respectively and change detection analysis between the dates was performed. The maps generated were validated through ground truthing. The study area （3375.62 km^2） from 1980-2009 has uffered deforestation and forest degradation of about 126 km^2 and 239.02 km^2 respectively which can be claimed under negative options of REDD＋, while as the area that experienced no change （1514 km^2） can be claimed under conservation. A small area （23.31 km^2） observed as positive change can be claimed under positive options. The projected estimates of forest cover for 2030 showed increased deforestation and forest degradation on the basis of trend analysis using Cellular Automata （CA） Markov modeling. Despite the fact that country as a whole has registered a net positive change in the past few decades, but there are regions like Kashmir region of western Himalaya which have constantly undergoing deforestation as well as degradation in the past few decades.
基金the support of the Ministry of Environment & Forests(MoEF),Government of India (GoI) (Project Serial Number:R&D/NNRMS/2/2013-14)
文摘With the growing recognition to myriad forms of current and future threats in the mountain agriculture systems,there is a pressing need to holistically understand the vulnerability of mountain agriculture communities.The study aims to assess the biophysical and social vulnerability of agriculture communities using an indicator-based approach for the state of Uttarakhand,India.A total of 14 indicators were used to capture biophysical vulnerability and 22 for social vulnerability profiles of15285 villages.Vulnerability analysis was done at village level with weights assigned to each indicator using Analytical Hierarchical Process(AHP).The results of the study highlight the presence of very high biophysical vulnerability(0.82 ± 0.10) and high social vulnerability(0.65 ± 0.15) within the state.Based on the results,it was found that incidences of high biophysical vulnerability coincide with presence of intensified agriculture land and absence of dense forest.Higher social vulnerability scores were found in villages with an absence of local institutions(like Self Helping Groups(SHGs)),negligible infrastructure facilities and higher occupational dependence on agriculture.A contrast was observed in the vulnerability scores of villages present in the three different altitudinal zones in the study area,indicating respective vulnerability generating conditions existing in these three zones.Biophysical vulnerability was recorded to be highest in the villages falling in the lower zone and lowest in the upper zone villages;whereas,social vulnerability was found to be highest in the middle zone villages and lowest in lower zone villages.Our study aids policy makers in identifying areas for intervention to expedite agriculture adaptation planning in the state.Additionally,the adaptation programmes in the region need to be more context-specific to accommodate the differential altitudinal vulnerability profiles.
