Stormwater-Retaining Ground Surface Depressions of Solar Photovoltaic Farms
Publication: Journal of Sustainable Water in the Built Environment
Volume 10, Issue 1
Abstract
Solar photovoltaic (PV) farms are commonly used for harnessing renewable solar energy, but they will change the natural landscape. Surface depression storage refers to the maximum empty volume that precipitation can fill on a surface before runoff occurs. This study aimed to determine the surface depression storage depths and volumes of a solar PV farm and assess the impact of solar PV panels on them. A solar PV farm with a grassy land surface was chosen and divided into six subwatersheds with varying topographic characteristics. Terrestrial laser scanning (TLS) point cloud and its triangulated irregular network (TIN) were utilized to identify and quantify surface depressions. The results showed that the microtopography of the grassy land surface between and under solar PVPs and the components commonly found in solar PV farms were accurately captured compared with field observations. The rainfall-retaining depression depths at solar PV farms were found to span 0.91–12.63 mm, which, among other applications, would provide new reference values for watershed models. The study also found a positive correlation between the surface depression storage depth and the area ratio of solar PVPs. Moreover, this study isolated the impact of solar PV farms on surface depressions from the underlying grassy surfaces and revealed that a deviation in the area ratio of solar PVP from one-third will result in a deviation of depression depths from the underlying grassy land surfaces. This study provides reference data on rainfall-retaining ground surface depression depths of solar PV farms as well as offers direction for future solar PV farm installations, considering various solar PVP area ratios.
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Data Availability Statement
Some of all data, models or code that support the findings of this research are available from the corresponding author upon reasonable request, including but not limited to: Point cloud data set obtained from TLS.
Acknowledgments
This research was partially supported by the National Fish and Wildlife Foundation through the Community Resiliency Grant 43931. The graduate study of the first author (DMM) was also financially supported by Rutgers University. The City of Linden, New Jersey, kindly provided logistic support to the study including access to the solar photovoltaic farm.
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Published In
Journal of Sustainable Water in the Built Environment
Volume 10 • Issue 1 • February 2024
Copyright
© 2023 American Society of Civil Engineers.
History
Received: Apr 17, 2023
Accepted: Aug 31, 2023
Published online: Sep 28, 2023
Published in print: Feb 1, 2024
Discussion open until: Feb 28, 2024
ASCE Technical Topics:
- Agriculture
- Climates
- Energy engineering
- Energy sources (by type)
- Environmental engineering
- Geomatic surveys
- Geomatics
- Infrastructure
- Irrigation engineering
- Land surveys
- Landscaping
- Meteorology
- Precipitation
- Renewable energy
- River engineering
- River systems
- Solar power
- Topographic surveys
- Urban and regional development
- Urban areas
- Waste management
- Waste sites
- Waste storage
- Water and water resources
- Water management
- Water storage
- Water supply
- Water supply systems
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