Estimating effective hydraulic conductivity (Ke) for the Rangeland Hydrology and Erosion Model (RHEM)

Authors: AL-HAMDAN, O.Z. - West Texas A & M University; Williams, Christopher - Jason; Pierson Jr, Frederick; HERNANDEZ, M. - University Of Arizona; Nouwakpo, Sayjro

Submitted to: Journal of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/18/2023
Publication Date: 1/1/2024
Citation: Al-hamdan, O., Williams, C.J., Pierson Jr., F.B., Hernandez, M., Nouwakpo, S.K. 2024. Estimating effective hydraulic conductivity (Ke) for the Rangeland Hydrology and Erosion Model (RHEM). Journal of the ASABE. 67(1):141-149. https://doi.org/10.13031/ja.15652.
DOI: https://doi.org/10.13031/ja.15652

Interpretive Summary: In this study, we evaluated a suite of infiltration estimation approaches for the Rangeland Hydrology and Erosion Model (RHEM), including a new approach for sparsely vegetated rangelands conditions. The study found that all historically applied infiltration approaches with RHEM are satisfactory in terms of model performance. The new approach resulted in very good model performance. The new approach for sparse cover conditions further expands the model applicability for assessing hydrologic function of degraded rangelands and targeting of conservation practices to limit runoff and soil loss. All approaches use readily available data for estimating infiltration rates on rangelands and provide practitioners and planners a collection of methodologies for assessing hydrologic function over a wide range of vegetation, ground cover, and surface soil conditions.

Technical Abstract: Effective hydraulic conductivity (Ke) is an important parameter for the prediction of infiltration and runoff by the Rangeland Hydrology and Erosion Model (RHEM). Three sets of equations to predict Ke have previously been used in RHEM. These equations have not been evaluated for diverse rangeland conditions such as following disturbances. The goal of this research was to evaluate these equations using independent data obtained from rainfall simulations conducted at multiple rangeland sites. Additionally, we developed and evaluated a new set of Ke predictive equations applying readily measurable cover and soils data spanning a wide range of vegetation, ground cover, and soil textures. The results show that all previous methods of Ke equations in RHEM have at least a “satisfactory” performance (index of agreement (d) > 0.75). The new Ke approach resulted in “very good” performance as well, with a d > 0.9. The new set of equations enhances RHEM for applications over broader rangeland conditions including sparse vegetation cover following disturbances or community transitions.