Assessment of the Impacts of Climate Change on Groundwater Evapotranspiration in Mid-to-High Latitude Regions
Bibliographic record
Abstract
In arid and semi-arid regions of mid-to-high latitude zones, actual evapotranspiration (AET) often exceeds annual precipitation or substantially dominates over other water balance components, posing risks to the hydrologic budget and groundwater depletion under future conditions. Despite numerous studies on AET, the contributions of various water sources to AET remain poorly understood at a regional scale. In the hydrologic cycle, AET represents the total amount of water lost through three main processes: surface water evaporation (SWE), subsurface evaporation (SSE), and subsurface transpiration (SST). These processes draw water from surface water (SW) and groundwater (GW). As a result, AET is categorized into two types: SW evapotranspiration (SWET) and GW evapotranspiration (GWET), based on the water source. This study developed, calibrated, and validated a process-based three-dimensional model to study variations in AET, the physical processes involved, and the contributions from different water sources in the North Saskatchewan River Basin (NSRB) in central Alberta. The study utilized the physically-based distributed HydroGeoSphere (HGS) model to simulate the hydrologic processes connecting surface water, groundwater, and AET for historical (1983-2013) and mid-future (2043-2073) periods. The NSRB, situated between latitudes 51.63°N and 54.56°N, is characterized by heterogeneous climate, soil, land use-land cover types, diverse landforms, and hydrogeological settings. These variations divide the watershed into three Ecohydro(geo)logical (EHG) regions: Mountains, Foothills, and Plains. Results demonstrate that across all EHG regions, more than 80% of the annual AET occurs during the spring/summer season (April-August), aligning with increased temperatures, potential evapotranspiration, and the active plant growing season. SST represents the largest contribution of water to supply annual AET, followed by SSE, with SWE making the smallest contribution in all regions. Regarding the source of water, SWET has the greatest contribution to annual AET in most areas across all EHG regions. On the other hand, GWET accounts for the majority of the annual AET in riparian areas and the northeast Plains. These areas are influenced by high atmospheric evapotranspiration demand, consistent GW discharge, and forest land cover with a large Leaf Area Index and deep plant roots that can reach shallow GW. Mean annual AET under mid-future (2043-2073) climate change scenarios shows an overall increase across the NSRB, with the greatest increase expected in the Mountains, compared to the historical period. In areas affected by GW discharge, such as riparian areas and the northeast Plains, a steady flow of GW is anticipated to support future increases in AET. Consequently, the share of GWET contribution to AET is expected to increase compared to the historical period in these regions. Study results reveal varied impacts of climate change on the saturated zone (SZ) across the EHG regions. In the Mountains, there is a predominant increase in water storage in the SZ, leading to a rise in the GW table. However, the proportion of SWET and GWET contribution to total AET remains relatively constant because of a deep GWT in this region. Conversely, projected drier conditions in the Foothills and Plains, compared to Mountains, result in the depletion of GW, reduction of GWET and increase of SWET. The most significant impacts on GW and its contribution to AET are expected in the Plains for the mid-future period. This study lays a strong basis for understanding the physical processes driving the spatiotemporal variation of AET and its contributing water sources, including groundwater and surface water, under historical and future climate change scenarios. The findings demonstrate the delicate hydrological balance of a large semi-arid and snow-dominated watershed in a mid-to-high latitude region and the potential alteration in the source of water for AET in the future, which can inform surface and groundwater management and land use planning.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".