A Modeling Framework to Investigate the Impact of Climate and Land-Use/Cover Change on Hydrological Processes in the Elbow River Watershed in Southern Alberta
Bibliographic record
Abstract
Complex dynamical and physical interactions exist between climate, land use/cover (LULC), and hydrology. In fact, each of these systems is considered complex because they possess the following characteristics. They consist of a large number of components that interact in a non-linear way. They interchange information with their surroundings and constantly modify their self-organized structure. They are far-from-equilibrium and display instability, sensitivity to initial conditions, sudden changes, and a behavior that cannot be captured by simple models. Understanding how hydrological processes respond to climate and LULC change requires knowledge about how these complex systems interact in the present and how they might in the future. The objective of this research is to understand the responses of hydrological processes to climate and LULC change in the Elbow River watershed using an integrated modeling framework that can address the complexity of these interrelated systems. To achieve this goal, the physically-based, distributed MIKE SHE/MIKE 11 model was coupled with a LULC cellular automata to simulate hydrological processes up to the year 2070 under five GCM-scenarios (NCARPCM-A1B, CGCM2-B2(3), HadCM3-A2(a), CCSRNIES-A1FI, and HadCM3-B2(b)). Results reveal that most scenarios generate an increase in overland flow, baseflow, and evapotranspiration in the winter/spring, and a decrease in the summer/fall. The highest increase in streamflow occurs in mid-late spring due to an increase in snowmelt and rain-on-snow events that may enhance the risk of flooding. In addition, LULC change substantially modifies the river regime in the east sub-catchment, where urbanization occurs. The separated impacts of climate and LULC change on streamflow are positively correlated in winter and spring, which intensifies their influence and leads to a rise in streamflow, which in turn increases the vulnerability of the watershed to floods, particularly in spring. Flow duration curves indicate that LULC change has a greater contribution to peak flows than climate change in both the 2020s and 2050s. The integrated modeling framework used in this research is a powerful analytical tool that can help scientists and decision makers for the planning of sustainable water resources and infrastructure management.
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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 | 0.000 | 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 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".