کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6409535 1629912 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Event-based stormwater management pond runoff temperature model
ترجمه فارسی عنوان
مدل دمای رواناب حوضچه مدیریت رویدادها
کلمات کلیدی
رویداد، طوفان آب حوضچه، رواناب درجه حرارت، مدل،
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات فرآیندهای سطح زمین
چکیده انگلیسی


- Investigated effect of pond design parameters on stormwater runoff temperature.
- Four stormwater wet ponds were monitored for three summers 2009-2011.
- Novel ANN and GEP models developed to predict pond outflow EMT.
- Uncertainties of the ANN & GEP models are 1.3% and 0.4% of the median Y value.
- The GEP produced a simple & accurate relationship between various parameters.

Stormwater management wet ponds are generally very shallow and hence can significantly increase (about 5.4 °C on average in this study) runoff temperatures in summer months, which adversely affects receiving urban stream ecosystems. This study uses gene expression programming (GEP) and artificial neural networks (ANN) modeling techniques to advance our knowledge of the key factors governing thermal enrichment effects of stormwater ponds. The models developed in this study build upon and compliment the ANN model developed by Sabouri et al. (2013) that predicts the catchment event mean runoff temperature entering the pond as a function of event climatic and catchment characteristic parameters. The key factors that control pond outlet runoff temperature, include: (1) Upland Catchment Parameters (catchment drainage area and event mean runoff temperature inflow to the pond); (2) Climatic Parameters (rainfall depth, event mean air temperature, and pond initial water temperature); and (3) Pond Design Parameters (pond length-to-width ratio, pond surface area, pond average depth, and pond outlet depth). We used monitoring data for three summers from 2009 to 2011 in four stormwater management ponds, located in the cities of Guelph and Kitchener, Ontario, Canada to develop the models. The prediction uncertainties of the developed ANN and GEP models for the case study sites are around 0.4% and 1.7% of the median value. Sensitivity analysis of the trained models indicates that the thermal enrichment of the pond outlet runoff is inversely proportional to pond length-to-width ratio, pond outlet depth, and directly proportional to event runoff volume, event mean pond inflow runoff temperature, and pond initial water temperature.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Hydrology - Volume 540, September 2016, Pages 306-316
نویسندگان
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