Assessment of climate change impact on rainfall for studying water availability in upper Mahanadi catchment, India (original) (raw)
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Impact of climate change on water resources of upper Kharun catchment in Chhattisgarh, India
Journal of Hydrology: Regional Studies, 2017
Study region: The Upper Kharun Catchment (UKC) is one of the most important, economically sound and highly populated watersheds of Chhattisgarh state in India. The inhabitants strongly depend on monsoon and are severely prone to water stress. Study focus: This research aims to assess the impact of climate change on water balance components. New hydrological insights for the region: The station-level bias-corrected PRECIS (Providing REgional Climates for Impact Studies) projections generally show increasing trends for annual rainfall and temperature. Hydrological simulations, performed by SWAT (Soil and Water Assessment Tool), indicate over-proportional runoff-rainfall and under-proportional percolationrainfall relationships. Simulated annual discharge for 2020s will decrease by 2.9% on average (with a decrease of 25.9% for q1 to an increase by 23.6% for q14); for 2050s an average increase by 12.4% (17.6% decrease for q1 to 39.4% increase for q0); for 2080s an average increase of 39.5% (16.3% increase for q1 to an increase of 63.7% for q0). Respective ranges on percolation: for 2020s an average decrease by 0.8% (12.8% decrease for q1 to an increase of 8.7% for q14); for 2050s an average increase by 2.5% (10.3% decrease for q1 to 15.4% increase for q0); for 2080s an average increase by 7.5% (0.3% decrease for q1 to 13.7% increase for q0). These overand under-proportional relationships indicate future enhancement of floods and question sufficiency of groundwater recharge.
Study of climate change for precipitation over Tighra Dam Catchment, MP, India
— This paper describes about the effect of climate change using Statistical Downscaling Model (SDSM) on precipitation over Tighra Dam Catchment, Gwalior, Madhya Pradesh, India. Global Climate Models (GCMs), CGCM3 have been used to project future precipitation over Tighra dam catchment. The predictor variables are extracted from 1) the National Centre for Environmental Prediction (NCEP) reanalysis dataset for the period 1979-2003, 2) the simulations from the third-generation Coupled Global Climate Model (CGCM3) variability and changes in precipitation under scenarios A1B and A2 of CGCM3 model have been presented for future periods: 2020s, 2050s and 2080s. The cross-correlations are used for verifying the reliability of the simulation. Downscaled future precipitation shows increasing trends for all scenarios. This projection is further used for water resources planning and adaptation to combat the adverse impact of climate change. Index Terms—Climate change, Global Circulation Model (GCM), SDSM, CGCM3 Model, Downscaling.
Journal of The Indian Society of Remote Sensing
The effects of climate change on hydrological regimes have become a priority area for water and catchment management strategies. The terrestrial hydrology driven by monsoon rainfall plays a crucial role in shaping the agriculture, surface and ground water scenario in India. Thus, it is imperative to assess the impact of the changing climatic scenario projected under various climate change scenario towards the hydrological aspects for India. Runoff is one of the key parameters used as an indicator of hydrological process. A study was taken up to analyse the climate change impact on the runoff of river basins of India. The global circulation model output of Hadley centre (HADCM3) projected climate change data was used. Scenario for 2080 (A2 scenario indicating more industrial growth) was selected. The runoff was modeled using the curve number method in spatial domain using satellite derived current landuse/cover map. The derived runoff was compared with the runoff using normal climatic data (1951–1980). The results showed that there is a decline in the future climatic runoff in most of the river basins of India compared to normal climatic runoff. However, significant reduction was observed for the river basins in the eastern region viz: lower part of Ganga, Bahamani-Baitrani, Subarnrekha and upper parts of the Mahanadi. The mean projected runoff reduction during monsoon season (June–September) were 18 Billion Cubic Meter (BCM), 3.2 BCM, 3.5 BCM and 5.9 BCM for Brahmaputra-Barak Subarnrekha, Subarnarekha and Brahmini-Baitrani basin, respectively in comparison to normal climatic runoff. Overall reduction in seasonal runoff was high for Subarnrekha basin (54.1%). Rainfall to runoff conversion was high for Brahmaputra-Barak basin (72%), whereas coefficient of variation for runoff was more for Mahanadi basin (1.88) considering the monsoon season. Study indicates that eastern India agriculture may be affected due to shortage of surface water availability.
2019
Changing climate has significant impact on the river hydrology and water resources. An assessment of the availability of water resources in the context of future requirement and expected impact of climate change and its variability is critical for relevant national and regional long-term development strategies and sustainable development. Changes in the climate have been assessed through assessing the Metrologic parameters such as daily maximum and minimum temperature of the month, daily average temperature, annual rainfall, monthly rainfall of the monsoon season, and maximum daily rainfall of the year, number of rainy days in the year and number of rainy days in each month of monsoon season. It is observed that the 1) Maximum daily temperature shows increasing trend in summer season (March to June) and shows reducing trend in winter season (October to February) in the study area. This is indicative of extreme weather in climate change/advance scenario. 2) The monthly rainfall trend shows increasing trend for the magnitude of annual rainfall shows increasing trend in the study area. 3) The number of rainy days in the monsoon season (June to October) shows reducing trend. Rainfall-Runoff regression analysis has been carried out for base line and advance/climate change scenario to investigate the impact of climate change on Water Resources. This study will be helpful to water resources planners and decision makers regarding the strategies to be followed in view of changing climate.
IRJET- IMPACT OF CLIMATE CHANGE USING PRECIPITATION ON WATER RESOURCES IN INDIA
IRJET, 2020
Present paper analyze the impacts of climate change on hydrology and water resources such as generation technology for climate change scenario, hydrologic simulation and modelling. The Climate Change Knowledge Portal (CCKP) provides an online tool for access to regional, and country data based on climate change and development. Changes in temperature and precipitation patterns consequent to climate change are expected to affect the spatial and temporal distribution of water resource management. It is important to describe how climate has varied and changed in the past time. The monthly mean historical rainfall and temperature data can be mapped to show the baseline climate and seasonality by months, in specific years, and for rainfall and temperature. I will show the mean historical monthly rainfall and temperature for India during the time period 1990-2015 and the monthly mean precipitation and temperature data have been projected change to show the baseline climate with scenario RCP2.6, RCP4.5 in various models at Delhi for India during the period 2020-2059. Climate change is expected to exacerbate current focused on water resources resulting from population growth, economic parameters and land use changes, including urbanization.
CMIP5 climate change projections for hydrological modelling in South Asia
Weber, T., McPhee, M.J. and Anderssen, R.S. (eds) MODSIM2015, 21st International Congress on Modelling and Simulation, 2015
Climate change will impact water and related sectors. Temperature and potential evaporation will be higher. Changes in future precipitation will be amplified in the river flows. Security of water supply will be compromised due to longer and more severe droughts, more precipitation falling as rain rather than snow, increased seasonality of river flow and retreat of glaciers. Flood risk will increase due to more intense heavy precipitation events. This paper presents the analyses of all the CMIP5 global climate model (GCM) runs to derive a consistent baseline climate change projection database for the South Asia region (5.25 o-40.25 o S, 60.25 o-100.75 o E) for the Sustainable Development Investment Portfolio (SDIP) run by the Department of Foreign Affairs and Trade (DFAT). The database presents 'empirical scaling factors' for 0.5 o grids (~50 km) that reflect changes in six climate variables (precipitation, heavy precipitation, potential evaporation, daily average temperature, daily maximum temperature and daily minimum temperature) for a future (2046-2075) period relative to current. The projected changes in the climate variables are derived for each of the 12 months, four seasons and annual values for two future representative greenhouse gas concentration pathways. These are presented for each ensemble modelling run from each of the 42 CMIP5 GCMs, as well as the median and range (uncertainty) of plausible projections. These consistently derived climate change projections will be used in various hydrological modelling and integrated water management projects across South Asia to inform water management, planning and development, and their interactions with the energy and food sectors. There is strong agreement between the GCMs in the temperature projections. Averaged across the South Asia region, the median projection for RCP4.5 and RCP8.5 is an increase in daily average temperature of 2.1 o C and 2.9 o C respectively by 2046-2075 relative to current. The projected increases are slightly higher for minimum daily temperature and slightly lower for maximum daily temperature as compared to the daily average temperature. The projected temperature increase is slightly higher in winter than in summer, and greater in the high altitude areas in the north. Averaged over the South Asia region, potential evaporation is projected to increase by 4.5% and 6.2% respectively by 2046-2075 relative to current. The projected increase in potential evaporation is mainly driven by the increase in temperature. There is much greater uncertainty in the precipitation projections, with significant variations between GCMs, and in the different seasons and regions. The range of projections from multiple ensemble runs of some GCMs can also be as high as the range of projections from the different GCMs. Nevertheless, a higher proportion of GCMs project an increase in precipitation, particularly in the northeast and much more so in the summer monsoon than winter. The projections also indicate likely intensification in the high extreme precipitation. The results also indicate that weighting the projections towards the better GCMs, assessed against their ability to reproduce the observed historical annual precipitation amounts and variability, do not reduce the range of uncertainty in the projections. As such, it is probably best to use the entire set of available GCMs in climate change impact studies to represent the entire range of plausible uncertainty.
Assessment of Hydrologic Impacts of Climate Change in Tunga-Bhadra River Basin, India
Climate change would significantly affect many hydrologic systems, which in turn would affect the water availability, runoff, and the flow in rivers. This study evaluates the impacts of possible future climate change scenarios on the hydrology of the catchment area of the Tunga-Bhadra River, upstream of the Tungabhadra dam. The Hydrologic Engineering Center’s Hydrologic Modeling System version 3.4 (HEC-HMS 3.4) is used for the hydrological modeling of the study area. Linear-regression based Statistical DownScaling Model version 4.2 (SDSM 4.2) is used to downscale the daily maximum and minimum temperature, and daily precipitation in the four subbasins of the study area. The large scale climate variables for the A2 and B2 scenarios obtained from the Hadley Centre Coupled Model, version 3 (HadCM3) are used. After model calibration and testing the downscaling procedure, the hydrological model is run for the three future periods: 2011-2040, 2041-2070 and 2071-2099. The impacts of climate change on the basin hydrology are assessed by comparing the present and future streamflow and the evapotranspiration estimates. Results of the water balance study suggest increasing precipitation and runoff and decreasing actual evapotranspiration losses over the subbasins in the study area.
Effect of Climate Change on the Rainfall Trends: A case study of Pune, India
2021
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In the present study, the downscaled future climate data from the General Circulation Model (GCM), CanESM2 has been used to calculate the monthly crop water requirements of the major crops cultivated in the Jayakwadi command area, Maharashtra, India. Statistical downscaling was carried out using the statistical downscaling model and the future irrigation demands were estimated using the CROPWAT model. Statistical downscaling of the CanESM2 GCM model and prediction of the future temperature and precipitation was done for two representative concentration pathways (RCP) scenarios namely the RCP 4.5 and RCP 8.5. Further, the future irrigation demands were estimated under the RCP 4.5 and 8.5 scenarios for the period 2011-2100 with three-time spells of 30 years centered on the 2020s (2011-2040), 2050s (2041-2070), and 2080s (2071-2100). The results indicated an increase in temperature and precipitation over time spells when compared to the base period (1961-2005). The annual average temperature has been projected to increase by 0.306 °C and 0.358 °C by the 2080s when compared to the base period under the RCP 4.5 and RCP 8.5 scenarios, respectively. The annual average precipitation has been projected to increase from 856.58 mm in the base period to 1410.11 mm and 1784.06 mm under RCP 4.5 and RCP 8.5, respectively. The average reference evapotranspiration (ET o) values showed an increase from 5.41 mm/day to 5.45 mm/ day, 5.53 mm/day, and 5.57 mm/day for the periods 2020s, 2050s and 2080s respectively in the RCP 8.5 scenario. The average annual irrigation demand showed a reduction of 14.07% and 14.72% for RCP 4.5 and RCP 8.5 scenarios respectively. The estimated variations in demand values can be used for optimal irrigation planning in the culturable command area of the Jayakwadi reservoir.
Water Resources Management, 2020
Quantification of water-budget components is an essential step in the planning and management of water resources in any river basin. Recently several studies emphasized that climate change would inevitably affect terrestrial hydrology. This study applies distributed hydrological modeling using the Variable Infiltration Capacity (VIC) model to simulate the water balance components in the Sina basin, a drought-prone region in India. We analyzed the long-term spatiotemporal dynamics of precipitation, evapotranspiration, surface runoff, and baseflow components, and their alterations due to impending climate change. The study employed the Mann-Kendall test and Sen's slope estimators to analyze the spatiotemporal trends of the water balance components during the baseline (1980-2010) and for the near future (2019-2040) periods. For the baseline period, precipitation exhibited an increasing trend, particularly during the monsoon season. On the evaluation of the annual water balance components, it showed that the basin has a low annual rainfall (~718 mm) and relatively a very high annual evapotranspiration (~572 mm) during 1980-2010, which might be the main reason for frequent droughts in the study basin. Further, for analyzing the climate change impacts on the water budget in the Sina basin, the VIC model was forced with outputs from a set of global climate models for near future (2019-2040) for two emission scenarios RCP4.5 and RCP8.5. Analysis of the results revealed that the water balance components in the near future would be negatively affected by climate change despite their increasing pattern in the baseline period. In comparison to the baseline (1980-2010), the surface runoff would decrease by as much as 32% for the near future, which stresses for planning and adaptation of appropriate mitigation measures in the basin.