Adaptation to climate change induced water stress in major glacierized mountain regions
Bibliographic record
Abstract
Mountains are a critical source of water and home to a large proportion of the world’s population. Cryospheric and hydrological changes combined with increasing water demand are impacting water availability, livelihoods and cultural values, threatening long-term water security of downstream populations. Here, we present a global systematic review in which 83 peer-reviewed articles were critically evaluated to unravel and assess different types of adaptation measures that have been undertaken to manage water stress. We observe that changes in glacier extent and snowfall amount are the main cryospheric changes motivating adaptations. However, changes in precipitation patterns, such as increasing extremes or alterations of the rain-snow line, which lead to both increasing water stress and seasonal flooding or glacier lake outburst floods (GLOFs), and are also observed to be important motivators of adaptive actions. The main sectors affected by hydrological and cryospheric changes are agriculture, tourism, hydropower generation and health and safety. To reduce risks of water scarcity and water-related disasters, and to enhance the resilience of human and natural systems, a broad set of adaptation measures have been implemented in the world’s mountain regions. Such adaptations include crop diversification, new irrigation practices, dams and water storage infrastructure, training programs and the establishment of Early Warning Systems, artificial snow making, shifts to non-snow-based tourism, and changes to cultural practices. We find that globally the most commonly used adaptation practices correspond to the improvement of water storage infrastructure, agricultural and irrigation practices, economic diversification and water governance and laws. However, our systematic review reveals these and other adaptation actions have strong regional variation. For example, adaptation in the agricultural sector is most prevalent in Africa, Asia and South America; while in Europe, Australia and New Zealand responses in the tourism sector are more common. Socio-ecological trade-offs associated with adaptations are often reported. For example, the promotion of snow-making reduces socio-economic vulnerability but adds pressure on water resources and environment. However, successful implementation of adaptation measures are limited by a diverse set of factors. This includes reduced capacities and resources in infrastructure maintenance, mismanagement, conflicts and mistrust in government together with lack of funding and insufficient collaboration between stakeholders as well as delayed implementation of laws and mountain development programs. Moreover, extreme events and climate change impacts together with discontinuities and errors in climate data need to be considered. In order to address or overcome these limitations, it is important to raise awareness of local communities about climate change and to demonstrate the positive effects of adaptation measures and environmental laws; increase funding for mountain programs and motivate combined activities of governments and stakeholders to build their trust on each other.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".