A STATISTICAL COMPARISON BETWEEN MET STATION DATA AND REMOTELY-SENSED DATA FOR CALCULATING REQUIRED STORAGE IN WATER BALANCE COVER SYSTEMS

Water balance cover (WBC) systems provide an economical alternative to traditional geotechnical composite soil caps for closed mining process components and landfills. The objective of this research is to assess the impacts of utilizing remotely-sensed data versus site-specific micro-meteorological (MET) data for estimating required water storage capacity in a water balance cover system. Required storage refers to the total amount of water that must be stored in a WBC system annually; or, alternatively, the net infiltration when precipitation exceeds evapotranspiration. Data from the Alternative Cover Assessment Program (ACAP) indicate that required storage is primarily influenced by the monthly balance of evaporation and precipitation. Two different monthly precipitation and evapotranspiration data sources were considered: On-site, or site-proximate micro-meteorological (MET) stations and ClimateEngine, a cloud-based tool that utilizes public-domain remote-sensing data to perform environmental calculations. Both data sets were used to calculate the required storage for two different mine sites over a twenty year period to compare the efficacy and reliability of each data source. Several statistical analyses comparing overall precipitation, winter precipitation, potential evapotranspiration (PET), and required storage were conducted to determine the statistical significance in the differences in required storage between the remotely-sensed and site-specific MET data. The difference in required storage calculated from each data set is statistically insignificant. Thus, utilization of remotely-sensed data, such as ClimateEngine, is as mathematically reliable for estimating required water storage capacity, as site-dependent MET data.