Sustainable development and anthropogenic induced geomorphic hazards in subsiding areas
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Bibliographic record
Abstract
Abstract In many areas of the world, subsidence related to the lowering of the water table is modifying the landscape and provoking costly environmental hazards. We consider the Dead Sea (the Earth's lowest lake) as a model. Its water level was 395 m bMSL in the 1960s. Due to water diversions in the catchment area, as of 2016, the level has dropped to about 430 m bMSL. Here, as in other parts of the Anthropocene world, from China, to Iran, to Turkey, to Canada and the United States, consequences of human interventions are rapidly modifying the environment. Aggressive geomorphic processes leading to accelerated degradations are taking place and affecting landforms and infrastructures. In Tectonic terms, the lake is a pull‐apart basin resulting from the motion of the Dead Sea Transform fault. Since the 1960s, a slice of brine of about 35 km 3 has been lost. The water table is dropping more rapidly in the lake than in the coastal zone creating an ever‐increasing head difference. Consequently, groundwater moves towards the sea to compensate for the imbalance, provoking the reactivation of the area's paleo‐channels with subsidence, sinkholes, and landslides. Since the 1980s, industrial‐touristic infrastructure has covered newly emerging lands in geomorphic hazards‐prone areas of the coastal zone. Time series analysis of high to very high resolution visible/radar satellite images acquired from the 1970s to present, revealed major landscape evolution. Such dynamic systems prevailing in recent decades permitted the study of human/environment interactions to help minimize their effects. Major deformations of an industrial dike were analysed and quantified. The results underline the necessity in the Anthropocene of careful analysis of relevant data sources acquired before and during subsidence, particularly in karst topography zones and prior to the development of major human activities in economically appealing environments around the world. Copyright © 2016 John Wiley & Sons, Ltd.
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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 | 0.000 | 0.000 |
| 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 it