Unraveling the causes and impacts of increasing flood disasters in the kathmandu valley: Lessons from the unprecedented September 2024 floods
Bibliographic record
Abstract
Understanding the underlying causes of flood disasters is essential not only for developing effective flood management strategies but also for evaluating past policies and mitigation efforts. This study investigates the multi-dimensional causes and impacts of the increasing flood disasters in the Kathmandu Valley and the surrounding Roshi catchment, with a specific focus on the unprecedented September 2024 floods. Using a diverse range of data sources-including field observations, open-ended interviews, published studies and reports, remote sensing, socio-economic and hydro-meteorological data, as well as institutional, legal, and policy frameworks-we identify key factors contributing to the rising flood risk in and around the valley. The causes of flooding were broadly categorized into four main areas: catchment characteristics, anthropogenic activities, hydro-meteorological factors, and policy and institutional frameworks. The extreme rainfall events of September 2024 and the resulting floods further exposed the Kathmandu Valley's vulnerability, causing over three dozen fatalities and millions in economic losses. Unlike previous years, the flood impacts were exacerbated by debris flows and landslides from surrounding hillslopes, along with sediment contributions from mining sites and encroached riverbanks, intensifying the severity of inundation. Despite early warnings of heavy rainfall from concerned agencies, inadequate preparedness and response significantly amplified the disaster's impact, revealing critical gaps in Nepal's disaster management framework. Instead of a one-size-fits-all approach, effective flood management in the Kathmandu Valley requires a collaborative, multi-dimensional strategy tailored to its unique challenges. The September 2024 floods underscore the urgent need for systemic reforms in urban planning, policy reforms and enforcement, inter-agency collaboration, strengthened local government, and disaster risk management. Our analysis provide critical insights for enhancing flood resilience and improving future flood risk management strategies in a holistic manner.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".