Research explainer
Debris does not move through a community by logistics alone.
After a hurricane, every pile of debris sits at the end of a chain of human decisions: what residents know, how they prepare, what help they can find, and which disposal options they can actually reach.
đ° In press
Please note that the paper has been accepted and is currently in press.
Post-disaster debris management is often treated as an engineering problem: estimate the volume, locate temporary sites, schedule collection, and route trucks. Yet cleanup outcomes also depend on thousands of household-level decisions made under urgency, uncertainty, and uneven access to services.
Our research, âUncovering Community Debris Disposal Behaviors During Post-Disaster Recovery: A Case Study of Illegal Dumping After Hurricane Ian,â reframes those decisions as a staged behavioral process. It combines a KnowledgeâAttitudesâPractices (KAP) framework, survey evidence from communities affected by Hurricane Ian, and a county-level Illegal Debris Disposal Tendency Index (IDDTI) for planning and screening.
The behavioral journey
One outcome, three decision environments
Select a stage to see how behavior develops before debris reaches its final destination.
Figure 1. Preparedness, on-property handling, and final disposal are analytically distinct but behaviorally connected. Some roadside or curbside placements remain context-dependent because emergency authorization can vary locally.
From survey response to behavioral evidence
The survey mapped nine constructs across the three stages: knowledge, attitudes or constraints, and practices. Outcome-specific models were then matched to the data: Poisson models for counts and logistic models for binary legality, placement, and material-handling outcomes. False-discovery-rate correction was applied within each outcome family.
This design matters because âillegal dumpingâ is not one undifferentiated act. The study distinguishes designated sites and authorized collection, locally contingent roadside placements, and clearly unauthorized locations such as highways, parks, and other cities.
The central result
Knowledge changes compliance. Access still shapes possibility.
Switch the outcome to compare standardized total associations at the final disposal stage.
Figure 2. Standardized total associations from the staged path models. Bootstrap 95% intervals excluded zero for Stage-C knowledge and access, but not for Stage-B preparation. These cross-sectional relationships are associations, not causal effects.
At the count level, a one-unit increase in standardized Stage-C knowledge was associated with a 24% increase in expected reported legal behaviors (IRR = 1.24) and an 11% decrease in expected reported illegal behaviors (IRR = 0.89). Knowledge was more strongly associated with expanding legal practice than eliminating illegal placementâa signal that information alone cannot remove physical and institutional barriers.
Evidence explorer
The answer changes with the question
Explore the reported associations for behavior counts, placement locations, and correct material handling.
Figure 3. IRRs are shown for count models and odds ratios for binary outcomes. Values above 1 indicate a positive association and values below 1 a negative association, holding other modeled constructs constant.
The material-specific results make the knowledge signal especially visible. Higher Stage-C knowledge was associated with correct handling of white goods (OR = 3.67), wrecked vehicles (3.34), hazardous debris (3.24), construction and demolition waste (2.58), soil (1.99), and vegetative debris (1.61).
Placement tells a different story. Concern and help-seeking were positively associated with both ambiguous and illegal off-site locations, while correct Stage-B preparation was associated with designated-site use. More knowledgeable respondents were not consistently less likely to place debris off-site. The practical interpretation is not that knowledge fails, but that knowing the right action and being able to take it are different problems.
From households to counties
What changes when hazard exposure enters the index?
Choose a validation target to compare the socioeconomic-only IDDTI-A with IDDTI-B, which adds Hurricane Ian wind exposure.
Figure 4. IDDTI values rank relative screening priority; they do not predict individual behavior. Validation was internal, county samples were uneven, and performance depends on the chosen target.
Against the survey-derived county ranking, adding hazard exposure improved Spearman correlation from 0.15 to 0.26 and pairwise accuracy from 0.54 to 0.60. Against the observed illegal-disposal ratio, however, IDDTI-A and IDDTI-B were close, and the hazard-enhanced version did not lead on every metric. That target dependence is a feature worth seeing, not hiding: the indices are screening tools for prioritization, not deterministic risk scores.
Translating evidence into action
Barrier
Intervention
Evaluate with
The evidence argues for a paired strategy. Use clear, debris-specific education where correct handling is technically demanding. At the same time, reduce the friction of compliance through closer temporary debris-management sites, mobile hazardous-waste drop-offs, real-time wait information, and coordinated collection support. Enforcement messaging is most credible when residents also have a practical legal option.
The broader contribution
This research shows why post-disaster disposal should not be reduced to a single cleanup choice. Earlier preparedness and handling conditions matter, but their associations with final behavior are largely mediated. At the moment of disposal, knowledge is linked to compliance quality, while access, convenience, concern, and available support shape where debris can end up.
That distinction gives emergency managers a more useful question than âWhy did residents dump debris illegally?â It asks: At which stage did the path toward compliant disposal break downâand was the missing piece knowledge, access, support, or credible alternatives?
Behavior sandbox
Watch a neighborhood respond
Change the conditions and watch the residents redistribute among authorized disposal, curbside or locally contingent placement, and clearly unauthorized off-site placement.
Figure 5. This is a qualitative teaching game, not a fitted agent-based model or forecast. It translates the studyâs supported directional relationships into an illustrative neighborhood scene; the character counts are not estimated population shares.
Research manuscript
Mohammad Movahedi, Navid Nickdoost, and Juyeong Choi. âUncovering Community Debris Disposal Behaviors During Post-Disaster Recovery: A Case Study of Illegal Dumping After Hurricane Ian.â manuscript has been accepted and is currently in press.
@article{Movahedi2026NHR,
author = {Movahedi, Mohammad and Nickdoost, Navid and Choi, Juyeong},
journal = {Natural Hazards Review},
publisher = {American Society of Civil Engineers},
title = {{Uncovering Community Debris Disposal Behaviors During Post-Disaster Recovery: A Case Study of Illegal Dumping After Hurricane Ian}},
year = {2026}
}