Dynamic Simulation Model to Monitor Flow Growth Rivers in Rapid-Response Catchments Using Humanitarian Logistic Strategies
Climate change, driven by natural factors and human activity, produces significant environmental changes worldwide. One consequence is increased rainfall, which leads to intense and increasingly frequent storms, sudden increases in river flows, and increased likelihood of emergencies linked to natur...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-05-01
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| Series: | Technologies |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2227-7080/13/6/213 |
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| Summary: | Climate change, driven by natural factors and human activity, produces significant environmental changes worldwide. One consequence is increased rainfall, which leads to intense and increasingly frequent storms, sudden increases in river flows, and increased likelihood of emergencies linked to natural disasters. This framework proposes a model based on the System Dynamics (SD) approach that aims to monitor the increase in flow in rapid-response catchments (RRCs). The model evaluates humanitarian logistics strategies to manage supplies during emergency situations and it is based on dynamic simulation, whose advantages are the analysis of causal relationships between variables and their behavior over time, mathematical support during the creation of the simulation model, and the creation of a graphical interface that allows the user to carry out a visual analysis of the variables involved in the model. The results show, through a case study, the implementation of a containment plan based on early decision-making from rapid-response catchment monitoring to generate humanitarian logistics strategies preventing material and human damage. Therefore, the main contribution of this framework is the creation of a simulation model that involves the synergy between two different systems: the analysis of RRC behavior and the humanitarian logistics plan to establish provision policies (food, water and medicine) based on the number of people at risk. |
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| ISSN: | 2227-7080 |