Uttarakhand state comes under special category state where approximately 69.45% population lived in rural area under the population density with varied range of 37 to 607 persons per sq.km. Although Uttarakhand is hav...Uttarakhand state comes under special category state where approximately 69.45% population lived in rural area under the population density with varied range of 37 to 607 persons per sq.km. Although Uttarakhand is having per capita consumption of 1112.29 kWh which is higher than national average per capita consumption of 779 kWh as till date, but remote communities, villages are not able to access clean, cheep and good quality of energy due to uneven terrain, lack of proper transmission & distribution lines [1]. 100% villages are electrified under the RGGVY scheme as per the Ministry of Power Government of India, but due to poor loading of transformer, lack of grid infrastructure and natural calamities, remote house owners are not able to get good quality of power thus affect the livelihood and source of income generation in various means [2]. As Uttarakhand state having future plans to be make state energy sufficient and energy access to all by year 2016-2017, so major ground level initiative have been taken by Government of Uttarakhand. The government of Uttarakhand has incorporated innovative business model to provide good quality of power with non-conventional energy source. Under the initiative invlovement of local people and village level, panchayats have ownership and responsibility to operate these clean energy business model to improve livelihood in remote hilly places of Uttarakhand. Under this analysis, five different type of community models are categorized as Community 1, Community 2, Community 3, Standalone 1 & Standalone 2 for rural &remote communities based on number of unclustered households with the distance covered between 200 m to 20 km, and electrical loads i.e. lighting, fan, mobile chargers, television along with time of day energy consumption patterns. These community models are for remote hilly location where grid integration and distribution lines are not feasible to built due to hilly terrain, low soil strength and huge expenses for expanding power cables for supplying good quality powe展开更多
Runoff is a major component of the water cycle, and its multi-scale fluctuations are important to water resources management across arid and semi-arid regions. This paper coupled the Distributed Time Variant Gain Mod...Runoff is a major component of the water cycle, and its multi-scale fluctuations are important to water resources management across arid and semi-arid regions. This paper coupled the Distributed Time Variant Gain Model （DTVGM） into the Community Land Model （CLM 3.5）, replacing the TOPMODEL-based method to simulate runoff in the arid and semi-arid regions of China. The coupled model was calibrated at five gauging stations for the period 1980-2005 and validated for the period 2006-2010. Then, future runoff （2010-2100） was simulated for different Representative Concentration Pathways （RCP） emission scenarios. After that, the spatial distributions of the future runoff for these scenarios were discussed, and the multi-scale fluctuation characteristics of the future annual runoff for the RCP scenarios were explored using the Ensemble Empirical Mode Decomposition （EEMD） analysis method. Finally, the decadal variabilities of the future annual runoff for the entire study area and the five catchments in it were investigated. The results showed that the future annual runoff had slowly decreasing trends for scenarios RCP 2.6 and RCP 8.5 during the period 2010-2100, whereas it had a non-monotonic trend for the RCP 4.5 scenario, with a slow increase after the 2050s. Additionally, the future annual runoff clearly varied over a decadal time scale, indicating that it had clear divisions between dry and wet periods. The longest dry period was approximately 15 years （2040-2055） for the RCP 2.6 scenario and 25 years （2045-2070） for the RCP 4.5 scenario. However, the RCP 8.5 scenario was predicted to have a long dry period starting from 2045. Under these scenarios, the water resources situation of the study area will be extremely severe. Therefore, adaptive water management measures addressing climate change should be adopted to proactively confront the risks of water resources.展开更多
文摘Uttarakhand state comes under special category state where approximately 69.45% population lived in rural area under the population density with varied range of 37 to 607 persons per sq.km. Although Uttarakhand is having per capita consumption of 1112.29 kWh which is higher than national average per capita consumption of 779 kWh as till date, but remote communities, villages are not able to access clean, cheep and good quality of energy due to uneven terrain, lack of proper transmission & distribution lines [1]. 100% villages are electrified under the RGGVY scheme as per the Ministry of Power Government of India, but due to poor loading of transformer, lack of grid infrastructure and natural calamities, remote house owners are not able to get good quality of power thus affect the livelihood and source of income generation in various means [2]. As Uttarakhand state having future plans to be make state energy sufficient and energy access to all by year 2016-2017, so major ground level initiative have been taken by Government of Uttarakhand. The government of Uttarakhand has incorporated innovative business model to provide good quality of power with non-conventional energy source. Under the initiative invlovement of local people and village level, panchayats have ownership and responsibility to operate these clean energy business model to improve livelihood in remote hilly places of Uttarakhand. Under this analysis, five different type of community models are categorized as Community 1, Community 2, Community 3, Standalone 1 & Standalone 2 for rural &remote communities based on number of unclustered households with the distance covered between 200 m to 20 km, and electrical loads i.e. lighting, fan, mobile chargers, television along with time of day energy consumption patterns. These community models are for remote hilly location where grid integration and distribution lines are not feasible to built due to hilly terrain, low soil strength and huge expenses for expanding power cables for supplying good quality powe
基金supported by the National Basic Research Program of China(2012CB956204)We acknowledge the modeling groups for providing the data for analysis,the Program for Climate Model Diagnosis and Intercomparison(PCMDI)the World Climate Research Programme’s(WCRP’s)Coupled Model Intercomparison Project for collecting and archiving the model output and organizing the data analysis
文摘Runoff is a major component of the water cycle, and its multi-scale fluctuations are important to water resources management across arid and semi-arid regions. This paper coupled the Distributed Time Variant Gain Model （DTVGM） into the Community Land Model （CLM 3.5）, replacing the TOPMODEL-based method to simulate runoff in the arid and semi-arid regions of China. The coupled model was calibrated at five gauging stations for the period 1980-2005 and validated for the period 2006-2010. Then, future runoff （2010-2100） was simulated for different Representative Concentration Pathways （RCP） emission scenarios. After that, the spatial distributions of the future runoff for these scenarios were discussed, and the multi-scale fluctuation characteristics of the future annual runoff for the RCP scenarios were explored using the Ensemble Empirical Mode Decomposition （EEMD） analysis method. Finally, the decadal variabilities of the future annual runoff for the entire study area and the five catchments in it were investigated. The results showed that the future annual runoff had slowly decreasing trends for scenarios RCP 2.6 and RCP 8.5 during the period 2010-2100, whereas it had a non-monotonic trend for the RCP 4.5 scenario, with a slow increase after the 2050s. Additionally, the future annual runoff clearly varied over a decadal time scale, indicating that it had clear divisions between dry and wet periods. The longest dry period was approximately 15 years （2040-2055） for the RCP 2.6 scenario and 25 years （2045-2070） for the RCP 4.5 scenario. However, the RCP 8.5 scenario was predicted to have a long dry period starting from 2045. Under these scenarios, the water resources situation of the study area will be extremely severe. Therefore, adaptive water management measures addressing climate change should be adopted to proactively confront the risks of water resources.
