Impacts of stormwater infiltration on downslope soil moisture and tree water use
Bibliographic record
Abstract
Abstract Infiltration of stormwater is a widely used strategy to mitigate the flooding and environmental risks that come from urban runoff and conventional urban drainage. An understanding of the fate of this infiltrated water is required for rigorous design. Principal design objectives are typically to restore more natural hydrology in order to protect receiving waters from pollution and hydrologic change. Without such understanding there is also a risk of unforeseen impacts on nearby infrastructure and urban vegetation. We sought to understand the pathways and fate of water from a stormwater infiltration basin. To trace water, we used a combination of water table monitoring and isotopic composition analysis in the infiltration basin, as well as in rainfall, soil water, the shallow groundwater, and in vegetation upslope and downslope of the basin. We also measured tree water use directly using sap flow sensors. The infiltration basin was shown to increase the availability of water downslope, allowing trees to maintain elevated levels of water use during dry periods with high energy demand. In contrast, water limitation upslope saw substantial seasonal reductions in tree water use. The soil water isotopic composition demonstrated significant differences from upslope to downslope, with downslope water being more reflective of rainfall, while the upslope water used by the trees was more depleted. The results paint a picture of stormwater infiltration being a significant source of lateral flow, while trees are a significant sink of lateral flow emanating from the basin. This finding suggests that stormwater infiltration could be used as a strategy to support the health and growth of urban trees. Urban trees have demonstrated benefits for human health and comfort, particularly in a warming climate. It also suggests that stormwater infiltration may not always recharge groundwater and provide baseflow in receiving waters, being instead taken up by vegetation. These findings should be considered in the siting of stormwater infiltration systems, to ensure that the objectives they were designed for are actually met.
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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) | 0.002 | 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".