Interdisciplinary approach to hydrological hazard mitigation and disaster response and effects of climate change on the occurrence of flood severity in central Alaska
Bibliographic record
Abstract
Abstract. In May 2013, a massive ice jam on the Yukon River caused flooding that destroyed much of the infrastructure in the Interior Alaska village of Galena and forced the long-term evacuation of nearly 70% of its residents. This case study compares the communication efforts of the out-of-state emergency response agents with those of the Alaska River Watch program, a state-operated flood preparedness and community outreach initiative. For over 50 years, the River Watch program has been fostering long-lasting, open, and reciprocal communication with flood prone communities, as well as local emergency management and tribal officials. By taking into account cultural, ethnic, and socioeconomic features of rural Alaskan communities, the River Watch program was able to establish and maintain a sense of partnership and reliable communication patterns with communities at risk. As a result, officials and residents in these communities are open to information and guidance from the River Watch during the time of a flood, and thus are poised to take prompt actions. By informing communities of existing ice conditions and flood threats on a regular basis, the River Watch provides effective mitigation efforts in terms of ice jam flood effects reduction. Although other ice jam mitigation attempts had been made throughout US and Alaskan history, the majority proved to be futile and/or cost-ineffective. Galena, along with other rural riverine Alaskan communities, has to rely primarily on disaster response and recovery strategies to withstand the shock of disasters. Significant government funds are spent on these challenging efforts and these expenses might be reduced through an improved understanding of both the physical and climatological principals behind river ice breakup and risk mitigation. This study finds that long term dialogue is critical for effective disaster response and recovery during extreme hydrological events connected to changing climate, timing of river ice breakup, and flood occurrence in rural communities of the Far North.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".