INTEGRATED WATER RESOURCES MANAGEMENT IN A TRANSBOUNDARY RIVER BASIN: MODEL DEVELOPMENT AND SENSITIVITY ANALYSIS
Bibliographic record
Abstract
Traditional water resources management in transboundary river basins is often fragmented by political boundaries. This fragmentation can not effectively address the challenges induced by increasing anthropogenic activities and climate change, which follow the river basin boundary rather than the political borders. The basin-scale water management model in such cases is a useful tool to investigate the impacts of these challenges over the social, economic, and environmental dimensions of water resources management. The Saskatchewan River Basin (SaskRB) is a sizeable transboundary river system in Canada, facing several water security challenges. Climate change and growing hydrological variability further accentuate these challenges by increasing uncertainty in supply and demand. The fragmentation of water resources management by provincial administrations, in principle, can hinder the process of basin-level water resources planning and management. An integrated basin-scale water management model can help to manage water resources both at the sub-basin and basin-scale effectively. \nThe present study first developed seven water management models for different regions of the SaskRB within the MODSIM system, which is a well-established modelling platform for river basin management and decision support. Next, these models (called “sub-models” hereafter), which simulate local water management and allocation rules in their respective regions, were integrated into one unified platform to develop an integrated water management model for the SaskRB (IWMSask). IWMSask was validated based on observed data and previous modeling work in the basin. IWMSask was then applied under changing conditions of demand and supply to assess the sensitivities of the water resources system. Three different scenarios of change were considered, which include a 10% decrease in streamflow (C1), a 10% increase in irrigation demand (C2), and a combination of C1 and C2 (C3). The results showed that the IWMSask can represent the entire system under the current and future water management infrastructure and climate conditions, thereby providing a platform for the stakeholders and decision-makers to understand the interconnected complexities of the entire system, vulnerabilities, and implications of policy change in one point for the rest of the system. IWMSask provides a helpful tool to investigate basin-level issues, e.g., the impact of natural and anthropogenic changes on the economy, society, and environment. It further enables the users to examine alternative policy options and discover trade-offs in the mitigation of the impacts of climate change.
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".