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Hydrological transit times in nested urban and agricultural watersheds in the Greater Toronto Area, Canada
Author(s) -
Parajulee Abha,
Wania Frank,
Mitchell Carl P.J.
Publication year - 2018
Publication title -
hydrological processes
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.222
H-Index - 161
eISSN - 1099-1085
pISSN - 0885-6087
DOI - 10.1002/hyp.13328
Subject(s) - environmental science , hydrology (agriculture) , watershed , streams , precipitation , streamflow , sampling (signal processing) , transit time , water quality , drainage basin , geology , geography , meteorology , ecology , biology , computer network , geotechnical engineering , cartography , filter (signal processing) , machine learning , computer science , computer vision , transport engineering , engineering
Watershed mean transit times (MTTs) are used to characterize the hydrology of watersheds. Watershed MTTs could have important implications for water quality, as relatively long MTTs imply lengthier water retention, thereby allowing more time for pollutant transformation and more moderate release of pollutants into streams. Although estimates of MTTs are common for undisturbed watersheds, only a few studies to date have applied MTT models to urbanized watersheds. In the present study, we use δ 18 O to compare estimates of MTTs for paired suburban‐industrial and agricultural watersheds in Toronto, Canada. Although differences in precipitation δ 18 O between the two watersheds were negligible, there were significant differences in stream δ 18 O, suggesting differences in water transport pathways. Less damping between input precipitation δ 18 O and output stream δ 18 O in the suburban‐industrial watershed indicated a larger streamflow contribution from quick‐flow transport pathways. We applied three transit time models to quantify MTTs. Considering overall model fit, root mean square error, and uncertainty in model parameters, the exponential model performed the best of the three models. Optimized MTTs using this distribution across the suburban‐industrial subwatersheds ranged from 2.1 to 2.9 months, whereas those in the agricultural subwatersheds ranged from 2.7 to 7.5 months. The relatively small difference between urban and agricultural MTTs coincides with observations elsewhere. Model efficiencies could potentially be improved, and MTTs estimated more reliably, with a higher sampling frequency that captures a greater volume of overall discharge. Overall, this work provides a distinct first glimpse into the separation of MTTs between paired watersheds with such a large contrast in their land use.