Estimating runoff and erosion on forest roads under various climate projections in Florida Panhandle region, USA
| Authors: | Jingqiu Chen, Shuyuan Wang, William J. Elliot, Zhihan Chen, Feng Pan, Yaoze Liu, Johnny M. Grace |
| Year: | 2026 |
| Type: | Scientific Journal |
| Station: | Rocky Mountain Research Station |
| DOI: | https://doi.org/10.1016/j.jenvman.2025.128207 |
| Source: | Journal of Environmental Management |
Abstract
Forest roads directly influence storm runoff, soil erosion, and sediment transport, making soil and water conservation essential. This study estimated runoff and erosion using the Water Erosion Prediction Project (WEPP) model for a typical unimproved forest road in the Chipola Experimental Forest, considering two alternative designs: a compacted “graded aggregate base” and a gravel surface. Both historical and future performance were evaluated using five widely used climate models in their Coupled Model Intercomparison Project (CMIP) fifth phase (CMIP5) and sixth phase (CMIP6) versions under emission scenarios 4.5 and 8.5. Model reliability during the historical period (2015–2023) was assessed using the ADF test for stationarity and ARMA modeling of precipitation biases. Extreme events were extracted to evaluate model performance under high-impact conditions. For 2024–2099, uncertainty was quantified using bootstrapped confidence intervals for projected precipitation, and estimated runoff and erosion. Results indicate that all selected models were stationary and provided reasonable annual and monthly precipitation estimates. CMIP6 models outperformed CMIP5, exhibiting lower ARMA intercepts for precipitation differences and more consistent projections of precipitation, runoff, and erosion across all road designs. CMIP5 models showed a tendency toward more extreme events. CMIP6 bootstrapped confidence intervals were more precise while maintaining comparable accuracy. The fractions of acceptable monthly precipitation, runoff, and erosion estimates exceeded 79 %, 64 %, and 45 %, respectively, with better performance for compacted and gravel roads than unimproved roads. These findings establish a robust framework for estimating runoff and erosion using climate models, underscore the benefits of improved road designs, and elucidate the differences between CMIP5 and CMIP6 models. The results can inform the design and maintenance of forest road networks under changing climate conditions and support long-term infrastructure resilience planning.