GIS-based flood hazard exposure assessment of schools in the West Bank, Palestine: a decision support framework
- 1Civil & Architectural Engineering Department, An-Najah National University, Nablus, Palestine
Abstract
School flooding poses a significant threat to educational continuity in developing countries. This study develops a GIS-based decision-support framework to assess and prioritize flood exposure across 2220 schools in the West Bank, Palestine, by integrating a previously developed flood hazard map with school locations and student enrollment data. The results show that fewer than 8% of schools are located in low or very low flood hazard classes, indicating limited low-hazard educational alternatives for emergency planning. Exposure scoring identified 111 critical-priority schools (top 5%), 66% of which are located in Hebron, Jerusalem, and Nablus. High flood exposure combined with larger student populations may amplify educational disruption. The Getis-Ord Gi* analysis identified significant high-exposure clusters in Nablus, Ramallah-Jerusalem, and Hebron. Based on these findings, a decision support framework was developed that translates spatial analysis into three operational decision pathways: policy and planning, school-level, and area-level. The framework was supported by quantitative and empirical validation evidence. The framework contributes to the objectives of the Sendai Framework Target D and SDG 4 on quality education. It offers educational decision-makers and emergency planners a systematic, spatially explicit basis for proactive flood preparedness, supporting student protection and educational continuity during extreme flood events.
Related
- Chemical Alternatives Assessment: Progress and Perspectives in Hazard Characterization, Exposure Assessment, and Life Cycle Assessment
- Analytical Replication Improves Precision but Does Not Create Environmental Replication: Hierarchical Uncertainty and Decision Stability in Metal(loid) Soil Exposure Screening.
- Dynamic life cycle assessment in environmental assessment of processes and products: A scoping review of sectoral applications, digitalization, decision support, and policy relevance
- An Artificial Intelligence Integrated Geospatial Decision-Support Framework for Scenario-Based Climate-Adaptive Land-Use Optimization and Environmental Risk Reduction
- Optimization of UV-C irradiation time for biologically treated saline wastewater using artificial neural networks and a hybrid multi-criteria decision-making framework
BibTeX
@article{shadeed2026gisbased,
title = {{GIS-based flood hazard exposure assessment of schools in the West Bank, Palestine: a decision support framework}},
author = {Sameer Shadeed},
journal = {Progress in Disaster Science},
year = {2026},
month = nov,
doi = {10.1016/j.pdisas.2026.100787},
url = {https://doi.org/10.1016/j.pdisas.2026.100787},
note = {CC BY},
}
RIS
TY - JOUR
TI - GIS-based flood hazard exposure assessment of schools in the West Bank, Palestine: a decision support framework
AU - Sameer Shadeed
PY - 2026
DA - 2026/11/05
JO - Progress in Disaster Science
DO - 10.1016/j.pdisas.2026.100787
UR - https://doi.org/10.1016/j.pdisas.2026.100787
AB - School flooding poses a significant threat to educational continuity in developing countries. This study develops a GIS-based decision-support framework to assess and prioritize flood exposure across 2220 schools in the West Bank, Palestine, by integrating a previously developed flood hazard map with school locations and student enrollment data. The results show that fewer than 8% of schools are located in low or very low flood hazard classes, indicating limited low-hazard educational alternatives for emergency planning. Exposure scoring identified 111 critical-priority schools (top 5%), 66% of which are located in Hebron, Jerusalem, and Nablus. High flood exposure combined with larger student populations may amplify educational disruption. The Getis-Ord Gi* analysis identified significant high-exposure clusters in Nablus, Ramallah-Jerusalem, and Hebron. Based on these findings, a decision support framework was developed that translates spatial analysis into three operational decision pathways: policy and planning, school-level, and area-level. The framework was supported by quantitative and empirical validation evidence. The framework contributes to the objectives of the Sendai Framework Target D and SDG 4 on quality education. It offers educational decision-makers and emergency planners a systematic, spatially explicit basis for proactive flood preparedness, supporting student protection and educational continuity during extreme flood events.
SN - 2590-0617
ER -