Application of Remote Sensing and Hydrologic Modeling to Reduce Highway Flooding in the Nebraska Sandhills

Hydrologic calculations for the Nebraska Sandhills (NSH) generally assume high infiltration, no runoff, and ignore subsurface runoff (groundwater and interflow). While these assumptions allow for the solution to a complex problem, they are not accurate representations of the complex movement of water in the region. Highways in the Sandhills region are a scarce and vital link that facilitate the movement of people and goods throughout the region. Roadway closures often lead to significant detours or make communities inaccessible to goods and emergency services. Inundation of highways in the Sandhills began in April 2019, a short time after snowmelt and rainfall events. Portions of N-97 were overtopped for more than five months and continued to be an issue during 2020. Up to seven locations were obstructed by rising groundwater. Understanding the Sandhills hydrology and highway flooding is extremely difficult because stream gages and monitoring wells are sparse. In areas, where groundwater and surface water are strongly connected, such as the NSH, surface water bodies are often representative of the groundwater level. In these cases, satellite altimetry may be suitable for remote estimates of groundwater level. Studies have used satellite altimetry to estimate the surface water elevation level, especially lake level, with sufficient accuracy to characterize the lake water level variation. Hofton et al. (2000) used the airborne scanning laser altimetry to estimate the lake surface elevation and found the accuracy was within 3 cm. Höfle et al. (2009) assessed the accuracy of LIDAR-derived water surface level and found the accuracy within 0.45 m. Hopkinson et al. (2011) measured water levels with a mean deviation of -0.22 to + 0.04 m in the Mackenzie Delta using Light Detection and Ranging (LIDAR) data. The thousands of lakes in the NSH provides an opportunity to develop a detailed monitoring system of surface and ground water. Shrestha et al (2021) has shown that the lakes in the NSH can be used to accurately estimate the water table elevation. Combined with available climate information (snow melt, precipitation) the higher density of groundwater and surface water elevation measurements (or estimates) from this project will lead to improved estimates of lag times between hydrologic events and water level changes. Understanding the quantity of snow melt and precipitation that causes highway flooding in the NSH and the lag time is necessary to determine the frequency, duration and causes. Gosselin et al. (2000) assessed the response of 130 lakes in the western part of the NSH and suggested the area variation could be due to the lake position relative to the regional groundwater system and hydrologic complexity. Schmieder et al. (2011) found that the frequency of lake-level variation is related to droughts of varying intensity using paleohydrological reconstruction from the last four thousand years. Rossman et al. (2019) simulated lake and wetland areas under different climate scenarios using a groundwater flow model and found that areas of lakes and wetlands change by 35 and 18% respectively. In a recent study, Shrestha et al. (2021) used satellite imagery and Palmer Drought Severity Index (PDSI) to determine the lake areas in three regions of the NSH and their response to climatic conditions. They were able to estimate lake area and identified cyclic trends.