Loss of street trees predicted to cause 6000 L/tree increase in leaf-on stormwater runoff for Great Lakes urban sewershed

《Loss of street trees predicted to cause 6000 L/tree increase in leaf-on stormwater runoff for Great Lakes urban sewershed》

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作者: Robert C. Coville;James Kruegler;William R. Selbig;Satoshi Hirabayashi;Steven P. Loheide;William Avery;William Shuster;Ralph Haefner;Bryant C. Scharenbroch;Theodore A. Endreny;David J. Nowak

来源: URBAN FORESTRY & URBAN GREENING,Vol.74,Issue1,Article 127649

语言: 英文

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作者单位: USDA Forest Service/Davey Institute, Davey Tree Expert Company, 5 Moon Library, SUNY-ESF, Syracuse, NY 13210, USA;US Geological Survey, Upper Midwest Water Science Center, 8505 Research Way, Middleton, WI 53562, USA;Department of Civil and Environmental Engineering, University of Wisconsin – Madison, Engineering Hall, 1415 Engineering Drive, Madison, WI 53716, USA;Wayne State University, College of Engineering, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA;US Geological Survey, Upper Midwest Water Science Center, 5840 Enterprise Drive, Lansing, MI 48911, USA;University of Wisconsin – Stevens Point, College of Natural Resources, Room 278 Trainer Natural Resources Building, Stevens Point, WI 54481, USA;Department of Environmental Resources Engineering, SUNY ESF, Syracuse, NY 13210, USA;USDA Forest Service, Forest Inventory and Analysis, 5 Moon Library, SUNY-ESF, Syracuse, NY 13210, USA;USDA Forest Service/Davey Institute, Davey Tree Expert Company, 5 Moon Library, SUNY-ESF, Syracuse, NY 13210, USA;US Geological Survey, Upper Midwest Water Science Center, 8505 Research Way, Middleton, WI 53562, USA;Department of Civil and Environmental Engineering, University of Wisconsin – Madison, Engineering Hall, 1415 Engineering Drive, Madison, WI 53716, USA;Wayne State University, College of Engineering, 5050 Anthony Wayne Drive, Detroit, MI 48202, USA;US Geological Survey, Upper Midwest Water Science Center, 5840 Enterprise Drive, Lansing, MI 48911, USA;University of Wisconsin – Stevens Point, College of Natural Resources, Room 278 Trainer Natural Resources Building, Stevens Point, WI 54481, USA;Department of Environmental Resources Engineering, SUNY ESF, Syracuse, NY 13210, USA;USDA Forest Service, Forest Inventory and Analysis, 5 Moon Library, SUNY-ESF, Syracuse, NY 13210, USA;Department of Systems Engineering, Czech University of Life Sciences Prague, Kamýcká 129, 165 21 Prague 6-Suchdol, Czech Republic;Nature Conservation Agency of the Czech Republic, Kaplanova 1931/1, 148 00 Prague 11-Chodov, Czech Republic;University of Minnesota, College of Food, Agricultural and Natural Resource Sciences, 1420 Eckles Ave #190, St. Paul 55108, MN, United States;The Martin Centre for Architecture, Department of Architecture, University of Cambridge, Cambridge CB2 1PX, UK;Geospatial Sciences, School of Science, STEM College, RMIT University, GPO Box 2476V, Victoria 3001, Australia;School of Tourism and Geography Science, Qingdao University, Qingdao 266071, China;Department of Plant and Soil Sciences, University of Delaware, Newark, DE, USA;USDA Forest Service, Northern Research Station, NRS-08, Newark, DE, USA;USDA Forest Service, Northern Research Station, NRS-08, Baltimore, MD, USA;USDA Forest Service, Northern Research Station, NRS-08, Delaware, OH, USA;USDA Forest Service, Northern Research Station, NRS-08, Philadelphia, PA, USA;Ironwood Urban Forestry Consulting Inc., 570 Wardlaw Ave., Winnipeg R3L 0M2, Manitoba, Canada;School for Resource and Environmental Studies, 6100 University Ave, Halifax B3H 4R2, Nova Scotia, Canada

摘要: Urban forests are recognized as a nature-based solution for stormwater management. This study assessed the underlying processes and extent of runoff reduction due to street trees with a paired-catchment experiment conducted in two sewersheds of Fond du Lac, Wisconsin. Computer models are flexible, fast, and low-cost options to generalize and assess the hydrologic processes determined in field studies. A state-of-the-art, public-domain model, which explicitly simulates urban tree hydrology, i-Tree Hydro, was used to simulate the paired-catchment experiment, and results from field observations and simulation predictions were compared to assess model validity and suitability as per conditions in the broader Great Lakes basin. Model parameters were aligned with observed conditions using automatic and manual calibration. Model performance metrics were used to quantify the weekly performance of calibration and to validate predictions. Those calibration metrics differed substantially between the two periods simulated, but most calibration metrics remained positive, indicating the model was not fitting only the period used for calibration. Predicted avoided runoff for a five-month leaf-on period was 64 L/m2 of canopy, 4 % lower than the field-estimated avoided runoff of 66 L/m2 of canopy. Interception was the most directly comparable process between the model and field observations. Based on 5 storms sampled, field estimation of precipitation intercepted and retained on trees averaged 63 % and ranged from 22 % to 81 %, while model estimation averaged 61 % and ranged from 36 % to 99 %. This model was able to fit predictions to observed catchment discharge but required extensive manual calibration to do so. The i-Tree Hydro model predicted avoided runoff comparable with the field study and earlier assessments. Additional field studies in similar settings are needed to confirm findings and improve transferability to other tree species and environmental settings.