Abstract
Soil moisture plays an important role in the predictions of precipitation and flooding forecasts. Along with precipitation, evapotranspiration and runoff can influence the conditions of the soil and how flooding can occur in a localized area. We examined an extreme flood that took place in 2018 in Ellicott City, MD to understand how well weather prediction models could forecast the precipitation and soil moisture conditions, and to understand if the relationships between soil moisture and other variables hold true. To test this, we used the Weather Research and Forecasting Model (WRF) and data from the Global Forecast System (GFS). We ran the model to produce 1-day and 2-day forecasts at both 10km and 25km resolutions for soil moisture, precipitation, latent heat, and runoff variables. The model predicted a soil moisture value of 0.3 cubic meters water per cubic meters soil and modeled average precipitation values of 4-8 mm/hr while observed average precipitation values were 10-30 mm/hr. We found that our results verified the importance of soil moisture, precipitation, evapotranspiration, and runoff in predicting flooding, but the resolutions used in this experiment could not accurately predict local precipitation rates and thus accurately forecast flooding. Future research could be done using resolutions of less than 10km to determine whether that provides a better precipitation forecast.
How to Cite:
, S. & , M.,
(2022) “Investigating Soil Moisture-Precipitation Relationships During the 2018 Ellicott City Flood Using WRF and GFS Model Results”,
Journal of Student-Scientists' Research 3.
doi: https://doi.org/10.13021/jssr2021.3197
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