Forest Road/Stream Crossings Structure Vulnerability Determination Using Hydro-Geomorphologic Analysis-Supported Geospatial Modeling Approach
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Major consequences on road/stream crossing drainage structures are siltation and scouring, particularly after extreme precipitation events. The risk of forest structure failures is high with high-gradient topography that causes increased soil erosion, higher discharge, enhanced streambank erosion probability, and heightened chance of debris flow to the structure mouth. The goal of this study is to develop a Morphological Vulnerability Assessment Decision Support System (MVADSS) to identify road/stream crossing drainage structures failure vulnerability risks combining four geospatial vulnerability risks assessment models – i) Design Discharge with Modified CN (DDM-CN), ii) Modified-Revised Universal Soil Loss Equation (M-RUSLE), iii) streambank erosion spatial vulnerability assessment (SBEVA), and iv) Hydro-geomorphologic characteristics supported Watershed Debris-Flow Assessment (WDFA). The study is completed in a high-gradient EFR system at Hubbard Brook (Northern Research Station (NRS)). The DDM-CN automated geospatial model uses the recently developed modified CN algorithm to calculate pixel-based runoff from individual watersheds that exited at each culvert. The M-RUSLE geospatial model amounts the eroded soil coming to each structure, which applies a newly developed R-Factor using NOAA published Precipitation-Intensity-Duration-Frequency (PIDF-I30) raster and a NDVI-based C-Factor. The SBEVA model is developed using spatial data like landuses across the streambanks (100 feet), Lidar-based 1m DEM, 10 m gSSURGO data, and design flood discharges calculated using 100-yr 24-hr partial duration series PIDF (NOAA). The WDFA model is developed through an innovative approach of using pixel-based tree/shrub speciation, rock type and rock depth spatial variation information obtained from Geology vector, spatial soil depth (gSSURGO) data, slope data (LiDAR-based DEM), and the designed runoff (DDM-CN model). Spatial environmental rasters used in models were reclassified with their vulnerability probability scale/weight, developed through Delphi method of weighted scale determination. Each model explained the structure failure risk in a scale of 1(High), 2(Moderate), and 3(Low). These four Risk-scaled models were combined to provide the qualitative scale vulnerability results of each structure in the EFR system. The results were field verified to confirm with our automated geospatial modeling approach for stream/road crossing structures’ vulnerability assessment. This study would provide proactive decision support to USDA Forest Service or any other agencies responsible for safeguarding these structures.