Abstract

The rise in greenhouse gases, carbon dioxide concentrations in the atmosphere, along with the warmer climate and Land Use/Land Cover (LULC) changes may have a significant impact on water resources of the local hydrological regime. Hence, it is essential to assess the river basin response to corresponding changes to providing a reliable, resilient, sustainable management system in future. So, the present study focuses on providing a robust framework to evaluate sustainability of river Krishna under future climate scenarios. A novel framework was developed with the help of Bayesian Networks (BNs) known as the River Sustainability Bayesian Network (RSBN) model. It contains twenty-one parameters, which covers socio-economic and environmental dimensions of sustainability. In these twenty-one parameters, ten parameters are root (independent) nodes, and the other eleven parameters were child nodes of these root nodes. The proposed RSBN model offers a unique combination of parameters, which includes various aspects of river basin such as water quality, quantity, climatic conditions, and LULC changes along with ecological management in the basin. The parameters used are flexible enough to modify based on user requirements. Under the Representative Concentration Pathway (RCP) 8.5 scenario, the model shows basin progress towards medium sustainability from mid-century onwards, whereas there is no significant change in river sustainability under the RCP 4.5 scenario. The sustainability of the basin is expected to be highly sensitive to extreme events followed by changes to water stress, environmental flow. The present model framework may help policymakers and water managers for sustainable planning and management of water resources of the basin.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.