Drainage Timescale Estimates and Storage Change Analysis on A Basin Scale

Abstract

The groundwater travel time depicts the characteristic timescale of the catchment drainage process and is therefore also known as drainage timescale (K). Catchment drainage timescale can be estimated empirically from recession flow analysis as well as from hydraulic theory. Applicability of is critical in groundwater hydrology, such as, estimation to groundwater storage change. The groundwater storage change estimation allows to assess risks for potential flood and droughts and to provide action guidelines for water managers to adjust water needs under increasingly intense population pressure. On account of the importance of in catchment hydrology, it brings the necessity for the research on K. This thesis conducts two analyses for for 17 HUC-8 watersheds in central Minnesota. First, the unknown agreement between empirically obtained drainage timescales and the groundwater theory is confirmed statistically. From theoretical analysis, is dependent on geomorphic features and hydrological conditions from the contributing unconfined aquifer, such as watershed area, stream length, saturated thickness, aquifer slope, hydrologic conductivity. A satisfactory statistical result and the interpretation are obtained showing the general agreement of the obtained from the recession analysis and the groundwater theory expression. Although the aquifer thickness’ contribution to regression results are inexplicit, the relationship strength of stream length, watershed drainage area, aquifer slope and aquifer transmissivity against is characterized by statistical coefficients and signs. Second, applicability of in annual groundwater storage change estimate is validated with a unique approach, which computes groundwater storage change by interpolating water tables’ temporal deviations (WT method). An overall agreement regarding the magnitude of order and the trend confirms the applicability of in annual groundwater storage change analysis. We identify 3 watersheds where the groundwater storage change estimated from does not conform to the storage change prediction from the WT method. An attempt to explain this observed discrepancy is based on the quality and seasonal completeness of discharge data, which impacts the recession analysis. But the comparison consistency is observed for the remaining watersheds in the study area. Among them, for 4 watersheds, the storage change estimated from correlates very well with that calculated from WT method, which is indicated by the correlation coefficient over 0.7.