Utilizing a gridded meteorological dataset for the estimation of required storage in water balance cover systems in Nevada

Abstract

Water balance cover systems (WBCs) are an effective alternative to conventional compacted clay/composite covers for landfills, mine remediation, or other waste containment applications. WBCs operate on the principle of soil-water storage and release, meaning an engineered WBC acts as a temporary storage reservoir for precipitation until the water is removed, or released via evapotranspiration (PET). To effectively engineer a WBC for any given location required storage (Sr) must be estimated for the WBC soil. Required storage refers to the amount of soil-water storage that must be available to prevent percolation. Meteorological data are necessary for the calculation of any required storage estimate. Precipitation and PET, components of required storage, are commonly measured and/or estimated using local, on-site meteorological monitoring stations (MET stations). MET station data are an accurate means for obtaining meteorological data, however large gaps in data can occur if the MET station is not kept up or the station is located in a spot with extreme weather conditions (high snowfall or gusty winds). Additionally, in remote places, such as Nevada, there is a sparse station network, making on-site storage estimates more difficult, and/or expensive. Thus, it is worth investigating other potential means for meteorological inputs for required storage calculations. In this case, a gridded meteorological dataset (gridMET) is used to estimate required storage using the interface, ClimateEngine, as well as MET station data. A statistical comparison of the two datasets at multiple sites throughout Nevada will provide a context for the variation in required storage estimates, and thus help determine the statistical similarity between the two and efficacy of using a gridded meteorological model to estimate required storage.