Dataset Information

Climate change impact assessments on the water resources of India under extensive human interventions.

ABSTRACT: Climate change is a major concern in the twenty-first century and its assessments are associated with multiple uncertainties, exacerbated and confounded in the regions where human interventions are prevalent. The present study explores the challenges for climate change impact assessment on the water resources of India, one of the world's largest human-modified systems. The extensive human interventions in the Energy-Land-Water-Climate (ELWC) nexus significantly impact the water resources of the country. The direct human interventions in the landscape may surpass/amplify/mask the impacts of climate change and in the process also affect climate change itself. Uncertainties in climate and resource assessments add to the challenge. Formulating coherent resource and climate change policies in India would therefore require an integrated approach that would assess the multiple interlinkages in the ELWC nexus and distinguish the impacts of global climate change from that of regional human interventions. Concerted research efforts are also needed to incorporate the prominent linkages in the ELWC nexus in climate/earth system modelling.

SUBMITTER: Madhusoodhanan CG

PROVIDER: S-EPMC5012999 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Climate change impact assessments on the water resources of India under extensive human interventions.

Madhusoodhanan C G CG Sreeja K G KG Eldho T I TI

Ambio 20160512 6

Climate change is a major concern in the twenty-first century and its assessments are associated with multiple uncertainties, exacerbated and confounded in the regions where human interventions are prevalent. The present study explores the challenges for climate change impact assessment on the water resources of India, one of the world's largest human-modified systems. The extensive human interventions in the Energy-Land-Water-Climate (ELWC) nexus significantly impact the water resources of the ...[more]

PMID: 27170012

Similar Datasets

Project description:The uncertainty in climate change and high water demand pose pressure on the natural water resources supply. Not only does this require better understanding but also a call for immediate interventions, mitigation and adaptive measures. This study evaluates catchment water resources in the Luwombwa sub-catchment in Zambia through statistical analysis in the downscaling of past, present and future climatic variables from the CMIP6 climatic model. These variables are then integrated into WEAP - a semi-distributed hydrological and water evaluation model - to perform water demand and allocation scenario modelling. Mult-site calibration and validation were conducted on five selected micro-catchments within Luwombwa sub-catchment. The model performance was assessed usng the R2, NSE and PBIAS as the objective functions. Satisfactory values of 92 % for R2, 82 % for NSE and 6.9 % for PBIAS were achieved. This allowed for scenario modelling on water demand and allocation among competing users. Three future scenarios (2022-2050) were developed from the historical to baseline (1988-2022) and included state of water resources availability under climate change, expansion of irrigation area and impact of dam construction in the sub-catchment. The study reveals a decrease of 20 % in sub-catchment's water availability resulting from 9.3 % (equivalent to 4oC) rise in maximum temperature and 4.5 % reduction in rainfall within the entire sub-catchment. This is especially under the persistence of SSP370 climate variability scenario projections downscaled from four GCM models by the year 2050. The study further revealed that the change point for anticipated future climate extremes is likely to occur between 2027 and 2030. The results are indicative of downward trends in streamflow under climate change and socioeconomic development leading to increase in water value and water scarcity. The insights from the study are critical to inform formulation of effective catchment water resources management strategies such as the development of management plans and adapation measures in the face of climate change and the needs for different stakeholders involvement.

Project description:On the climate-health issue, studies have already attempted to understand the influence of climate change on the transmission of malaria. Extreme weather events such as floods, droughts, or heat waves can alter the course and distribution of malaria. This study aims to understand the impact of future climate change on malaria transmission using, for the first time in Senegal, the ICTP's community-based vector-borne disease model, TRIeste (VECTRI). This biological model is a dynamic mathematical model for the study of malaria transmission that considers the impact of climate and population variability. A new approach for VECTRI input parameters was also used. A bias correction technique, the cumulative distribution function transform (CDF-t) method, was applied to climate simulations to remove systematic biases in the Coupled Model Intercomparison Project Phase 5 (CMIP5) global climate models (GCMs) that could alter impact predictions. Beforehand, we use reference data for validation such as CPC global unified gauge-based analysis of daily precipitation (CPC for Climate Prediction Center), ERA5-land reanalysis, Climate Hazards InfraRed Precipitation with Station data (CHIRPS), and African Rainfall Climatology 2.0 (ARC2). The results were analyzed for two CMIP5 scenarios for the different time periods: assessment: 1983-2005; near future: 2006-2028; medium term: 2030-2052; and far future: 2077-2099). The validation results show that the models reproduce the annual cycle well. Except for the IPSL-CM5B model, which gives a peak in August, all the other models (ACCESS1-3, CanESM2, CSIRO, CMCC-CM, CMCC-CMS, CNRM-CM5, GFDL-CM3, GFDL-ESM2G, GFDL-ESM2M, inmcm4, and IPSL-CM5B) agree with the validation data on a maximum peak in September with a period of strong transmission in August-October. With spatial variation, the CMIP5 model simulations show more of a difference in the number of malaria cases between the south and the north. Malaria transmission is much higher in the south than in the north. However, the results predicted by the models on the occurrence of malaria by 2100 show differences between the RCP8.5 scenario, considered a high emission scenario, and the RCP4.5 scenario, considered an intermediate mitigation scenario. The CanESM2, CMCC-CM, CMCC-CMS, inmcm4, and IPSL-CM5B models predict decreases with the RCP4.5 scenario. However, ACCESS1-3, CSIRO, NRCM-CM5, GFDL-CM3, GFDL-ESM2G, and GFDL-ESM2M predict increases in malaria under all scenarios (RCP4.5 and RCP8.5). The projected decrease in malaria in the future with these models is much more visible in the RCP8.5 scenario. The results of this study are of paramount importance in the climate-health field. These results will assist in decision-making and will allow for the establishment of preventive surveillance systems for local climate-sensitive diseases, including malaria, in the targeted regions of Senegal.

Dataset Information

Climate change impact assessments on the water resources of India under extensive human interventions.

Publications

Climate change impact assessments on the water resources of India under extensive human interventions.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets