Modeling Hydrology of a Solar Farm Using a Flexible Open-Source Hydrological Model

Abstract Ground-mounted solar arrays, or solar farms, are being implemented for renewable energy generation. Solar panels can alter local hydrology, making accurate modeling essential for optimal site selection and management. We developed a modeling framework leveraging open-access software OpenHydroQual, since this model can represent the unique way that solar panels redistribute water on solar farms, and has explicit representation of unsaturated zone hydrologic processes. This study focuses on a solar farm with a steep (20%) slope within central Pennsylvania, USA. The model was calibrated and validated using one year of soil moisture data collected in prior research by the study authors; Nash–Sutcliffe efficiencies varied from 0.74 to 0.79 for different zones of the solar farm. Comparison of the solar farm model with a model of pre-development conditions indicates redistribution of soil moisture, with concentration of water at the dripline and reduced moisture under panels. The hydrologic changes increased runoff, with annual runoff generation changing from 2 cm to 3.5 cm. Additional scenarios performed to explore implications of management options indicated that increasing space between solar panel rows from 3 m to 4 m led to a decrease in runoff depth by 28.6%. Reduction of Manning’s n (representing reduction in grass height) from 0.06 to 0.03 led to a 2.9% increase in runoff depth. The comparison of different scenarios for 2- and 100-year return period storm events also indicated that solar panel implementation led to an increase in runoff volume and peak flow rate. Over the entire solar farm area, the implementation of solar panels resulted in a 21.5% decrease in annual evapotranspiration. Though this work demonstrated increases in runoff due to solar panel implementation, it also showed how certain management practices can counter these increases. Though these specific results apply to one site, this modeling framework can be customized for other solar farm sites. Resulting insights on anticipated runoff changes are critical for appropriate selection and sizing of stormwater management practices on solar farms.