|PAPANICOLAOU, ATHANASIOS - University Of Tennessee
|ABBAN, BENJAMIN - University Of Tennessee
|DERMISIS, DIMITRIOS - McNeese State University
|GIANNOPOULOS, CHRISTOS - University Of Tennessee
|Frankenberger, James - Jim
|WACHA, KENNETH - Oak Ridge Institute For Science And Education (ORISE)
Submitted to: Water Resources Research
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/26/2017
Publication Date: 1/24/2018
Citation: Papanicolaou, A.N., Abban, B., Dermisis, D.C., Giannopoulos, C.P., Flanagan, D.C., Frankenberger, J.R., Wacha, K.M. 2018. Flow resistance interactions on hillslopes with heterogeneous attributes: Effects on runoff hydrograph characteristics. Water Resources Research. 54:359-380. doi: 10.1002/2017WR021109.
Interpretive Summary: Soil erosion and sediment losses are driven by rainfall and runoff processes and particularly by concentrated flow in rill channels on tilled agricultural fields. Computer simulation models are commonly used to predict the amount of runoff and erosion from croplands, and determine how use of different land management such as conservation tillage (that leaves the soil with more cover and rougher) or strip cropping (that can intersperse tilled crop areas with rougher perennial vegetation) can affect runoff and soil loss. In this study, new modeling approaches were examined that focused on the use of unique spatial elements that can have different roughness and other characteristics, as opposed to some of the existing approaches that average landscape attributes together. When these changes were tested within the existing model, we found that they could have large effects on the predicted peak runoff rates – that directly influence the power of the rill flow to detach and transport soil. The effects of changes in vegetation down a hill can cause changes up to six times in the calculated peak runoff rates, while changes due to slope curvature can be up to three times. Overall, the use of the newer approaches may predict runoff peak rates two times different from the current ones. These results impacts scientists and modelers working to better predict runoff rates and associated soil loss from agricultural landscapes, and others who are utilizing natural resource models for runoff and/or erosion estimates. Future work may involve implementation of these new approaches into updated versions of current models to allow for better hydrologic and erosion predictions.
Technical Abstract: An improved modeling framework for capturing the effects of dynamic resistance to overland flow is developed for intensively managed landscapes. The framework builds on the WEPP model but it removes the limitations of the “equivalent” plane and static roughness assumption. The enhanced model therefore accounts for hillslope dynamic roughness variability due to changes in roughness, in curvature, and downslope variability. The model is used to quantify the degree of influence – from individual soil grains to aggregates, “isolated roughness elements”, and vegetation – on overland flow characteristics under different storm magnitudes, downslope gradients, and curvatures. It was found that the net effects of land use change from vegetation to a bare surface resulted in hydrograph peaks that were up to six times higher. Changes in hillslope curvature instead resulted in runoff rate changes that were up to threefold. The flow power concept is utilized to develop a taxonomy that relates the influence of the aforementioned landscape attributes on overland flow under different storm magnitudes and hillslope gradients. A threshold was found above which different landscape attributes seized to have an effect on the peak flow power. The results also highlight weaknesses of the static resistance assumption and demonstrate that assumptions on landscape terrain characteristics exert a strong control both on the shape and magnitude of hydrographs, with deviations reaching 200% in the peak runoff when dynamic roughness effects are ignored in some cases.