Mapping Flood-Prone Areas Using GIS and Morphometric Analysis in the Mantaro Watershed, Peru: Approach to Susceptibility Assessment and Management

Del Piero R. Arana-Ruedas (), Edwin Pino-Vargas, Sandra del Águila-Ríos and German Huayna
Additional contact information
Del Piero R. Arana-Ruedas: Doctorate in Environmental Engineering and Sciences, Universidad Nacional Agraria La Molina, Av. La Molina s/n, Lima 15024, Peru
Edwin Pino-Vargas: Doctorate in Environmental Engineering and Sciences, Universidad Nacional Agraria La Molina, Av. La Molina s/n, Lima 15024, Peru
Sandra del Águila-Ríos: Doctorate in Environmental Engineering and Sciences, Universidad Nacional Agraria La Molina, Av. La Molina s/n, Lima 15024, Peru
German Huayna: Department of Civil Engineering, Universidad Nacional Jorge Basadre Grohmann, Av. Miraflores S/N, Tacna 23000, Peru

Sustainability, 2025, vol. 17, issue 17, 1-17

Abstract: Floods represent one of the most significant climate-related hazards, particularly in regions with complex topographies and variable precipitation patterns. This study assesses flood-prone areas within the Mantaro watershed, Peru, using Geographic Information Systems (GISs) and morphometric analysis. The methodology integrates digital elevation models (DEMs) with hydrological parameters, applying weighted sum analysis to classify 18 sub-watersheds into different flood priority levels. Morphometric parameters, including basin relief, drainage density, and slope, were analyzed to establish correlations between watershed morphology and flood susceptibility. The results indicate that approximately 74.38% of the watershed exhibits high to very high flood risk, with the most vulnerable sub-watersheds characterized by steep slopes, high drainage densities, and compact morphometric configurations. The correlation matrix confirms that watershed topography significantly influences surface runoff behavior, underscoring the necessity of incorporating geospatial analysis into flood risk assessment frameworks. The classification of sub-watersheds into priority levels provides a scientific basis for optimizing resource allocation in flood mitigation strategies. This study highlights the importance of integrating advanced geospatial technologies, such as GISs and remote sensing, into hydrological risk assessments. The findings emphasize the need for proactive watershed management, including the use of real-time monitoring and digital tools for climate adaptation. Future research should explore the influence of land-use changes and climate variability on flood dynamics to enhance predictive modeling. These insights contribute to evidence-based decision-making for disaster risk reduction, reinforcing resilience in climate-sensitive regions.

Keywords: flood susceptibility; GIS analysis; morphometric parameters; Mantaro watershed; Peru (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/17/17/7809/pdf (application/pdf)
https://www.mdpi.com/2071-1050/17/17/7809/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:17:y:2025:i:17:p:7809-:d:1737750

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().