| Summary: | The Prairie Pothole Region (PPR) of North American contains millions of wetlands in shallow depressions that provide important hydrological and ecological functions. To assess and model these functions it is important to have accurate methods to quantify wetland water volume storage. Hayashi and van der Kamp (2000) developed equations suitable for calculating water volume in natural, regularly shaped wetlands when two coefficients are known. This thesis tested the robustness of their full and simplified volume (V) area (A) depth (h) methods to accurately estimate volume for the range of wetland shapes occurring across the PPR. Further, a digital elevation model (DEM) derived from light detection and ranging (LiDAR) data was used to extract the necessary data for applying the simplified V-A-h method at a broad spatial scale. Detailed topographic data were collected for 27 wetlands in the Smith Creek Research Basin and St. Denis National Wildlife Area, Saskatchewan that ranged in surface area shape. The full V-A-h method was found to accurately estimate volume (errors <5%) across wetlands of various shapes and is therefore suitable for calculating water storage in the variety of wetland shapes found in the PPR. Analysis of the simplified V-A-h method showed that the depression (p) and size (s) coefficients are sensitive to the timing of area and depth measurements and the accuracy of area measurements. Surface area and depth should be measured concurrently at two points in time to achieve volume errors <10%. For most wetlands this means measuring area and depth in spring when water levels are approximately 70% of hmax, and also in late summer prior to water depths dropping below 0.1 m. The wetted perimeter of the deepest water level must also be measured accurately to have volume errors less than 10%. Applying the simplified V-A-h method to a LiDAR DEM required GIS analysis to extract elevation contours that represent potential water surfaces. From these data the total wetland depth and s coefficient were estimated. Volume estimates through this LiDAR V-A-h method outperformed estimates from two volume-area equations commonly used in the PPR. Furthermore, the process to extract the wetland coefficients from the LiDAR DEM was automated such that storage could be estimated for the entire St. Denis National Wildlife Area. Applying the simplified V-A-h method according to the guidelines and data sources recommended here will allow for more accurate, time-effective water storage estimates at multiple spatial scales, thereby facilitating evaluation and modelling of hydrological and ecological functions.
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