Modeling rainfall infiltration on hillslopes using Flux-concentration relation and time compression approximation

Wang, Jie; Chen, Li; Yu, Zhongbo

doi:10.1016/j.jhydrol.2017.12.031

Cited by 26 publications

(12 citation statements)

References 27 publications

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“…Because the soil is susceptible to surface sealing during rainfall (Assouline, ), the two‐layer infiltration model presented in Smith et al (, ) and Corradini et al (, , ) was applied in this study. To extend the model to sloping surfaces, the governing equations can be modified by changing the terms depicting the gravity effect (Chen & Young, ; Wang et al, ), which can be expressed as

C_{1} ((), ψ_{0}) \frac{d ψ_{0}}{dt} = \frac{1}{a_{s} Z_{c}} ([], i_{0} - K_{0} cos γ - \frac{K_{1 s} G_{1} ((),, ψ_{c}, ψ_{0})}{Z_{c}}),

\frac{d ψ_{c}}{dt} = \frac{({}, K_{0} cos γ + \frac{K_{1 s} G_{1} ((),, ψ_{c}, ψ_{0})}{Z_{c}} - K_{2 c} cos γ - \frac{β_{2} ((), θ_{2 c}) b_{2} ((), θ_{2 c} - θ_{2 i}) K_{2 s} G_{2} ((),, ψ_{i}, ψ_{c})}{I - Z_{c} ([], θ_{1 c} - θ_{1 i} + ((), θ_{0} - θ_{1 c}) α_{s}) - K_{2 i} t cos γ})}{P ((),,, ψ_{0}, ψ_{c}, t)},

in which the function P ( ψ 0 , ψ c , t ) is defined as

\begin{matrix} lefttrue \\ P (ψ_{0}, ψ_{c}, t) = [β_{2}] \end{matrix}

…”

Section: Modeling Approachmentioning

confidence: 99%

Modeling Rainfall‐Runoff and Soil Erosion Processes on Hillslopes With Complex Rill Network Planform

Chen

Wang

et al. 2018

Water Resources Research

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The effect of rill network planforms on hillslope rainfall-runoff and soil erosion processes is usually neglected in modeling practices, although they can markedly alter the hydrologic and geomorphic processes. Based on the CeRIRM model and WEPP erosion theory, a simple approach is developed to account for these effects. In the framework, several characteristic parameters including the average rill width, rill orientation angle, the number of rills, and number of discontinuous rills and their variations along the hillslope are introduced to represent the planar characteristics of the rill network. The model is tested against experimental erosion data from a hillslope subjected to three successive rainfall events, resulting in continuous rill network evolution. The results show that rill network planforms alter the partitioning of interrill and rill flows, thereby modifying the hydraulics, erosion, and sedimentation in the rills. Rill characteristics are found to significantly affect the amount of rill erosion. The new approach is compared to WEPP, which ignores rill network features. The WEPP approach of simulating rill erosion on hillslopes using one set of model parameters leads to errors that are up to 30% larger than the new approach that is able to account for spatially and temporally varying rill characteristics. The differences in cumulative rill erosion amounts between the two models vary significantly with slope length, slope angle, rill orientation angle, number of rills, and discontinuous rills. The results are valuable for the development of general rainfall-runoff and soil erosion models on hillslopes with complex geomorphic features. Plain Language Summary Rill erosion is one of the main forms of soil erosion and is associatedwith fast flowing water in networks of small channels, that is, rills. Modeling rill erosion is an important yet challenging task informing soil conservation. Although actual rill networks are usually composed of irregular, tortuous, and even discontinuous rills, using parallel and straight rills to simplify the actual rill network is still the prevailing method in current models. This study demonstrates the impact of the irregular planform of rill network on soil erosion and proposes a simple and effective conceptualization to represent complex rill networks using only a few parameters, including rill orientation angle, number of rills, and number of discontinuous rills. The approach can better represent the spatially intricate partitioning of interrill and rill flow and improve the modeling of rill hydraulics, erosion, and sedimentation prediction. Owing to its improved physical basis, the proposed approach simulates both the total amount and the spatial distribution of erosion with improved accuracy. The results of this study are expected to help improve general rainfall-runoff and soil erosion models for hillslopes with complex geomorphic features, and benefit other scientific fields involving transport through complex rill networks.

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C_{1} ((), ψ_{0}) \frac{d ψ_{0}}{dt} = \frac{1}{a_{s} Z_{c}} ([], i_{0} - K_{0} cos γ - \frac{K_{1 s} G_{1} ((),, ψ_{c}, ψ_{0})}{Z_{c}}),

\frac{d ψ_{c}}{dt} = \frac{({}, K_{0} cos γ + \frac{K_{1 s} G_{1} ((),, ψ_{c}, ψ_{0})}{Z_{c}} - K_{2 c} cos γ - \frac{β_{2} ((), θ_{2 c}) b_{2} ((), θ_{2 c} - θ_{2 i}) K_{2 s} G_{2} ((),, ψ_{i}, ψ_{c})}{I - Z_{c} ([], θ_{1 c} - θ_{1 i} + ((), θ_{0} - θ_{1 c}) α_{s}) - K_{2 i} t cos γ})}{P ((),,, ψ_{0}, ψ_{c}, t)},

in which the function P ( ψ 0 , ψ c , t ) is defined as

\begin{matrix} lefttrue \\ P (ψ_{0}, ψ_{c}, t) = [β_{2}] \end{matrix}

…”

Section: Modeling Approachmentioning

confidence: 99%

Modeling Rainfall‐Runoff and Soil Erosion Processes on Hillslopes With Complex Rill Network Planform

Chen

Wang

et al. 2018

Water Resources Research

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“…Many of these models are based on a conceptual representation of the system, which inherently involves a number of important assumptions [6]. Some of the models used are approximations (numerical models) [17][18][19], while others are analytical solutions [16,20,21]. These models cannot, however, provide the profile of water content without large simplifications of the soil description.…”

Section: Introductionmentioning

confidence: 99%

Modelling Projected Changes in Soil Water Budget in Coastal Kenya under Different Long-Term Climate Change Scenarios

Okello

Greggio

Giambastiani

et al. 2020

Water

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The possible impacts that climate change will have on soil water budget and specifically on deep percolation, runoff and soil water content have been investigated using HYDRUS, a methodology based on numerical modelling simulations of vertical water movement in a homogenous soil column on a flat surface. This study was carried out on four typical soil types occurring on the Kenyan coast and the adjacent hinterlands of up to an elevation of 200 m above sea level (m a.s.l.) covered by five weather stations (two dry and three wet stations). Results show that deep percolation and runoff are expected to be higher in 2100 for both Relative Concentration Pathways (RCPs) 2.6 and 8.5 scenarios than they were for the reference period (1986–2005). The average deep percolation is expected to increase by 14% for RCP 2.6 and 10% for the RCP 8.5, while the average runoff is expected to increase by 188% and 284% for the same scenarios. Soil water content is expected to either increase marginally or reduce depend in the same scenarios. The average soil water content is also expected to increase by 1% in the RCP 2.6 scenario and to decrease by 2% in the RCP 8.5 scenario. Increase in deep percolation through clay soil is expected to be the largest (29% in both scenarios), while sandy and sandy clay soil are expected to be the least influenced with an average increase of only 2%. Climate change is expected to impact runoff mostly in sandy soils, whereas the least affected would be clay loam soils. These results further support the assertion that the change in climate is expected to impact the recharge of aquifers by triggering an increase in infiltration under both scenarios.

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“…However, in most real situations, infiltration occurs over surfaces characterized by different gradients [76,77] and the role of surface slope on infiltration is not clear. In fact, the results obtained by some theoretical and experimental investigations [78][79][80][81][82][83][84][85][86][87][88][89][90][91][92][93][94][95][96][97] lead to contrasting conclusions, suggesting that an improved understanding and modeling of infiltration on sloping surfaces is required.…”

Section: Introductionmentioning

confidence: 99%

Rainfall Infiltration Modeling: A Review

Morbidelli

Corradini

Saltalippi

et al. 2018

Water

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Infiltration of water into soil is a key process in various fields, including hydrology, hydraulic works, agriculture, and transport of pollutants. Depending upon rainfall and soil characteristics as well as from initial and very complex boundary conditions, an exhaustive understanding of infiltration and its mathematical representation can be challenging. During the last decades, significant research effort has been expended to enhance the seminal contributions of Green, Ampt, Horton, Philip, Brutsaert, Parlange and many other scientists. This review paper retraces some important milestones that led to the definition of basic mathematical models, both at the local and field scales. Some open problems, especially those involving the vertical and horizontal inhomogeneity of the soils, are explored. Finally, rainfall infiltration modeling over surfaces with significant slopes is also discussed.

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Modeling rainfall infiltration on hillslopes using Flux-concentration relation and time compression approximation

Cited by 26 publications

References 27 publications

Modeling Rainfall‐Runoff and Soil Erosion Processes on Hillslopes With Complex Rill Network Planform

Modeling Rainfall‐Runoff and Soil Erosion Processes on Hillslopes With Complex Rill Network Planform

Modelling Projected Changes in Soil Water Budget in Coastal Kenya under Different Long-Term Climate Change Scenarios

Rainfall Infiltration Modeling: A Review

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