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Advances in Geospatial Modeling for Flood Risk Assessment in Changing Climate
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Author(s): Hafsa Muzammal (Agricultural Remote Sensing Lab, University of Agriculture, Faisalabad, Pakistan), Muhammad Zaman (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan), Muhammad Safdar (Agricultural Remote Sensing Lab, University of Agriculture, Faisalabad, Pakistan), Muhammad Adnan Shahid (Agricultural Remote Sensing Lab, University of Agriculture, Faisalabad, Pakistan), Zuhaib Nishtar (College of Electrical Engineering and New Energy, China Three Gorges University, Yichang City, China), Muhammad Bilal (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan), Muntaha Munir (Institute of Botany, University of the Punjab, Lahore, Pakistan), Mehar Muhammad Haseeb (Department of Space Science, University of the Punjab, Lahore, Pakistan), Aamir Raza (Precision Agriculture Center, Department of Soil, Water, and Climate, University of Minnesota, USA), Syed Intsar Hussain Shah (Agricultural Remote Sensing Lab, University of Agriculture, Faisalabad, Pakistan), Usman Zafar (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan), Nalain E. Muhammad (Department of Irrigation and Drainage, University of Agriculture, Faisalabad, Pakistan)and Hafiz Muhammad Bilawal Akram (Department of Agronomy, University of Agriculture, Faisalabad, Pakistan)
Copyright: 2026
Pages: 30
Source title:
Advances in Computational Intelligence for Climate Change Security and Sustainability
Source Author(s)/Editor(s): Imdad Ali Shah (School of Computing Science, Taylor’s University, Malaysia)and N.Z. Jhanjhi (School of Computing Science, Taylor’s University, Malaysia)
DOI: 10.4018/979-8-3693-9132-7.ch003
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Abstract
The chapter discusses advances in geospatial modeling for flood risk assessment in the context of climate change. It integrates Global Climate Models (GCMs) with geospatial techniques to explore the impact of changing climatic trends on flood frequency and intensity. By compiling historical climate data from 2000 to 2050, the study creates a baseline understanding of regional temperature fluctuations and precipitation changes. GCM results are downscaled to local levels, ensuring compatibility with hydrological models. The research provides a comprehensive framework for addressing the evolving flood landscape, accounting for risks related to GCM estimates and model assumptions. It highlights proactive adaptation strategies such as sustainable land use, flood-resistant infrastructure, and informed policymaking, especially for the Indus River Basin. This interdisciplinary approach offers an advanced analytical framework for understanding and mitigating flood-related vulnerabilities amid climatic uncertainty.
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