A DIGITAL TERRAIN ANALYSIS TECHNIQUE FOR ASSESSING SEDIMENT EROSION AND EFFICIENTLY TARGETING BEST MANAGEMENT PRACTICES WITHIN AGRICULTURAL WATERSHEDS IN SOUTHEASTERN MINNESOTA

Digital Terrain Analysis (DTA) based on high-resolution LiDAR data was used to identify high-priority areas for implementation of agricultural best management practices (BMPs) in two southeastern Minnesota watersheds. The objective of the study was to identify highly erodible portions of the landscape that potentially contribute disproportionately large percentages of sediment to streams. The DTA-based approach provides an opportunity to more effectively allocate limited resources for BMP implementation while maximizing the potential for improving stream water quality.

Our analysis focused on the Bridge Creek and Rush-Pine Creek watersheds in southeastern Minnesota and utilized 1 m and 3 m resolution digital elevation models (DEMs), respectively. We used the DEMs to calculate the Stream Power Index (SPI) across the whole of the landscape. The SPI is a DTA technique that evaluates the potential for erosion based on the primary terrain attributes of slope and flow accumulation. Field verification of the SPI results indicates that the technique accurately predicts actual erosional features in our study watersheds.

We then delineated “microbasins” adjacent to the stream corridors based on the high-resolution DEMs, which essentially define the potential near stream contributing areas of sediments. By overlaying the SPI results on the near-stream microbasins we were able to identify and extract the catchment areas exhibiting the highest potential for erosion. We termed these areas of continuously linked, high SPI values as “Highly Connected Corridors” (HCCs). HCCs represent corridors through the landscape that are potential superhighways of erosion connecting upland areas of the watershed to the stream.

Using the HCCs we were able to determine the relationship between the width of a hypothetical riparian buffer, the number of acres taken out of production by the buffer, and the potential acres of highly erodible landscape isolated from the stream by the buffer. This approach affords the opportunity to identify critical source areas of sediments within a watershed and efficiently target BMP implementation to maximize benefit while minimizing the cost and acres removed from production.