Use of Groundwater, Baseflow and SPEI to Evaluate Water Resources in Michigan, USA

Precipitation and evaporation are commonly used to assess and forecast droughts. However, surface and groundwater respond to both land surface processes, land use, and climatic variables, and should be integrated into water management decisions. Water trend analysis near the Great Lakes is limited due to fluctuating cycles and data scarcity. In this study, we examine daily discharge data from 46 surface water gauges with high baseflow contributions and groundwater elevation from 28 observation wells in Michigan. Using established hydrograph separation techniques, we determined baseflow and standardized both annual average baseflow levels (SDBF) and groundwater levels (SDGW) from 1960 to 2022. These results are compared to the widely used Standardized Precipitation-Evapotranspiration Index (SPEI). SPEI is a widely used drought indicator that integrates both precipitation and potential evapotranspiration, offering a more comprehensive measure of water balance. While the SPEI suggests that Michigan is becoming wetter, the SDBF shows a mix of both wet and dry conditions. Interpreting SDGW is more challenging due to incomplete records, but it indicates varying groundwater stability across the state. In some areas, SDGW mirrors the trends seen in SDBF, while in others, it takes 3 to 4 years for groundwater levels to reflect the same changes observed in baseflow. Overall, SDBF provides a better understanding of surface processes and responses to changing climatic variables.

Tools to Estimate Groundwater Levels in the Presence of Changes of Precipitation and Pumping

Central Wisconsin has the greatest density of high capacity wells in the state, most of which are used for agricultural irrigation. Irrigated agriculture has been growing steadily in the region since the 1950’s, when irrigation systems and high capacity wells became inexpensive and easy to install. Recent low lake and river levels have increased concerns that unregulated groundwater pumping for irrigation will undermine the availability of groundwater to support surface waters and domestic uses. Some research has quantified the magnitude of groundwater level declines due to irrigation pumping, but no studies have identified its relation to climatic precipitation changes. Changes in precipitation can appear to exacerbate or mask the effect of groundwater pumping. In this study, four groundwater monitoring wells and five climate stations were examined for shifts in groundwater levels and precipitation changes. Through statistical analysis, significant precipitation increases were identified in the southern part of the study area which averaged 2.7 mm per year, but no significant change was determined for the northern portion. Bivariate analysis identified water level declines within the region in the years 1974, 1992 and 1999 for irrigated land covers. Multiple regression analysis explained, predicted and quantified the interaction between precipitation and pumping. Wells located in areas with many high capacity wells showed a decline in water levels of up to 1.28 meters. In the southern portion of the study area where increases in precipitation occurred, this decline was thought to be masked. Results for one region (Plover) agreed with a previously published calibrated groundwater model, which demonstrates that this statistical method may be used to separate the impact of groundwater pumping from changing precipitation, even where observation well data are not widely available.

Comparison of Three Delineation Methods Using the Curve Number Method to Model Runoff

Digital Elevation Models (DEMs) are spatial grids which are used to automate watershed boundary determination. Sinks are present within most DEMs. In order to easily process the watershed boundary, the sinks are reassigned to elevation equivalent to an adjacent cell. The derived DEM is called a “filled” DEM. Due to its relative simplicity, the use of the “filled” DEM is one of the most widely used methods to delineate watershed boundaries and works well in about 70 percent of the watersheds in the US. In landscapes with internal drainage, sinks may accurately represent these depressions. In this study, we compare two delineation methods that do not fill in sinks to another method that does fill in sinks. We examined ten gaged watersheds in Wisconsin and Minnesota. We found the spatial extent of the watersheds from the three methods were significantly different. To evaluate the delineation methods, we modeled ten runoff events using the Curve Number (CN) method and compared them to USGS gage discharge for each watershed. For small storms we found that there were no significant differences in the modeled runoff for three delineation methods. For large storms, we found the no-fill methods had a smaller error, but overall the difference was insignificant. This research suggests that capturing internal drainage by the delineation does not have much of an impact on the widely used CN model.

Characterizing Clustering in Boulder Bed Channels and the Impact on Shear Stress Equations

Boulders and cobbles are often used in stream restoration projects to increase flow resistance and enhance channel stability and habitat diversity. Particle size metrics determined from the particle distribution are often used as a proxy for shear stress in field equations. Clustering of large particles has been thought to contribute to shear stress, but the effect of clustering is not accounted for in equations that use a representative particle size, such as the D84. In this paper, clustering is defined using the upper tail (≥84%) in a variable called Topsum. The number of clusters, average size of clusters, and shear stress are evaluated using the proposed definition of cluster. Findings suggest that the upper tail represents the roughness height better than the commonly used proxy of D84 for boulder bed streams (streams which have a D84 particle 0.05 - 0.15 meters).

Evaluating the Effect of Land Cover, Seasonality and Delineation Method on Runoff at the Watershed Scale

The aim of this study was to determine if runoff estimates from the curve number model were affected by seasons for different land covers. Eighteen watersheds with varying land covers were delineated using three methods. The delineation methods differ in how internal drainage is evaluated. Runoff estimates from storms for spring, summer, and fall were compared to observed runoff from USGS gaging station data. Errors (difference between estimate runoff and observed runoff) were found to be highest for fall by 3% for all the two delineation methods which do not consider internal drainage. Watersheds were categorized by their dominant land cover (agriculture, forest, or urban). Seasonal differences were found to be significant for certain land covers. The greatest differences between observed and estimated data were found in agriculture and urban especially spring versus fall for all delineations. Forest land cover was found to have no seasonal difference for all three delineation methods. The research suggests that this work contributes to the growing body of research suggesting that vegetative seasonal differences have a greater impact on runoff than is accounted for in the runoff model.

Linking Watershed Scales through Altered Waterways

Nested hierarchy theory advances the idea that rivers have a fractal dimension where processes at the catchment scale (>1 km) control processes at the reach or mesoscale (100 m) and microscale (1 - 10 m). Largely absent from this work is a mesoscale link to the larger and smaller scales. We used stream alteration classifications to provide this link. We used orthophotographs, land cover, and LiDAR derived terrain models to classify stream alterations within four watersheds. We compared phosphorus point data with watershed, sub-watershed, and 100-meter buffers around the point data. In the predominately urban watershed, the 100 m buffer scale correlated better with phosphorus levels. In the predominately agricultural watershed, the sub-watershed scale correlated with phosphorus levels better. We found adding the classification of the stream alteration type clarified anomalously low phosphorus levels.