Integrated framework for hydrologic modelling in data-sparse watersheds and climate change impact on projected green and blue water sustainability

Lawal, I. M. and Bertram, D. and White, C. J. and Jagaba, A. H. (2023) Integrated framework for hydrologic modelling in data-sparse watersheds and climate change impact on projected green and blue water sustainability. Frontiers in Environmental Sciences, 11. 1233216. ISSN 2296-665X (https://doi.org/10.3389/fenvs.2023.1233216)

[thumbnail of Lawal-etal-FES-2023-Integrated-framework-for-hydrologic-modelling-in-data-sparse-watersheds-and-climate-change-impact]
Preview
 Text. Filename: Lawal-etal-FES-2023-Integrated-framework-for-hydrologic-modelling-in-data-sparse-watersheds-and-climate-change-impact.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo
Download (6MB)| Preview

Abstract

Climate and hydrologic hazards threaten the distribution of watersheds’ water resources in time and space, necessitating planning for sustainable resilience and adaptation. Hydrologic modelling has emerged as a potential solution for understanding watershed responses to projected climate change and a prediction model that can deliver actionable information is necessary, although it requires basin-scale observations to calibrate the model to reliably predict basin-scale water resources hazards. Such luxury is not always tenable in watersheds with inadequate ground-based observation. However, the availability of satellite-based data of hydrologic fluxes and states, coupled with a machine learning feature selection and data refinement process has made integrated water balance modelling widely regarded as a viable alternative for improving the performance and capability of watershed modelling processes in data-sparse regions. This study develops a convincing framework by integrating machine learning-based feature selection and a process-based hydrologic model to calibrate sufficiently, accurate behavioural solutions for all model responses using satellite evapotranspiration data. The framework was applied to four subbasins that form the larger Lake Chad basin with distinct morphological features. The model results were used to assess the dynamic changes in projected blue and green water resource sustainability in response to climate change in one of the subbasins. Study findings indicate that hydrologic fluxes can be simulated accurately with varying degrees of acceptability, irrespective of the watershed morphological properties although there are significant trade-offs in parameter sensitivity. While green water is the dominant freshwater component across the basin relative to blue water, climate change may be a significant factor in the spatial and temporal changes of projected green water sustainability status. However, the combination of socioeconomic drivers and climate change may significantly impact the projected blue water sustainability status across the basin. Projected changes in green and blue water sustainability status have shown that more than 50% of the watershed will be ecologically fragile and identified freshwater geographic sustainability hotspots may be beyond restoration without adequate long-term river basin water resources plans.

ORCID iDs

Lawal, I. M. ORCID logoORCID: https://orcid.org/0000-0002-4130-9739, Bertram, D. ORCID logoORCID: https://orcid.org/0000-0003-4291-5842, White, C. J. and Jagaba, A. H.;
CORE (COnnecting REpositories)