Scenario-Based Hydrological Modeling for Designing Climate-Resilient CoastalWater Resource Management Measures: Lessons from Brahmani River, Odisha, Eastern India

In Sustainability
Peer-reviewed Article

Widespread urban expansion around the world, combined with rapid demographic and
climatic changes, has resulted in serious pollution issues in many coastal water bodies. To help
formulate coastal management strategies to mitigate the impacts of these extreme changes (e.g.,
local land-use or climate change adaptation policies), research methodologies that incorporate
participatory approaches alongside with computer simulation modeling tools have potential to be
particularly effective. One such research methodology, called the “Participatory Coastal Land-Use
Management” (PCLM) approach, consists of three major steps: (a) participatory approach to find
key drivers responsible for the water quality deterioration, (b) scenario analysis using different
computer simulation modeling tools for impact assessment, and (c) using these scientific evidences
for developing adaptation and mitigation measures. In this study, we have applied PCLM approach
in the Kendrapara district of India (focusing on the Brahmani River basin), a rapidly urbanizing
area on the country’s east coast to evaluate current status and predict its future conditions. The
participatory approach involved key informant interviews to determine key drivers of water quality
degradation, which served as an input for scenario analysis and hydrological simulation in the next
step. Future river water quality (BOD and Total coliform (Tot. coli) as important parameters) was
simulated using the Water Evaluation and Planning (WEAP) tool, considering a different plausible
future scenario (to 2050) incorporating diverse drivers and pressures (i.e., population growth, landuse
change, and climate change). Water samples (collected in 2018) indicated that the Brahmani
River in this district was already moderately-to-extremely polluted in comparison to the desirable
water quality (Class B), and modeling results indicated that the river water quality is likely to further
deteriorate by 2050 under all of the considered scenarios. Demographic changes emerged as the
major driver affecting the future water quality deterioration (68% and 69% for BOD and Tot. coli
respectively), whereas climate change had the lowest impact on river water quality (12% and 13%
for BOD and Tot. coli respectively), although the impact was not negligible. Scientific evidence to
understand the impacts of future changes can help in developing diverse plausible coastal zone
management approaches for ensuring sustainable management of water resources in the region.
The PCLM approach, by having active stakeholder involvement, can help in co-generation of the
coastal management options followed by open access free software, and models can play a relevant
cost-effective approach to enhance science-policy interface for conservation of natural resources.

Binaya Kumar