Infiltration–runoff–slope instability mechanism of macropore slope under heavy rainfall is unclear.This paper studied its instability mechanism with an improved Green–Ampt(GA)model considering the dual-porosity(i.e...Infiltration–runoff–slope instability mechanism of macropore slope under heavy rainfall is unclear.This paper studied its instability mechanism with an improved Green–Ampt(GA)model considering the dual-porosity(i.e.,matrix and macropore)and ponding condition,and proposed the infiltration equations,infiltration–runoff coupled model,and safety factor calculation method.Results show that the infiltration processes of macropore slope can be divided into three stages,and the proposed model is rational by a comparative analysis.The wetting front depth of the traditional unsaturated slope is 17.2%larger than that of the macropore slope in the early rainfall stage and 27%smaller than that of the macropore slope in the late rainfall stage.Then,macropores benefit the slope stability in the early rainfall but not in the latter.Macropore flow does not occur initially but becomes pronounced with increasing rainfall duration.The equal depth of the wetting front in the two domains is regarded as the onset criteria of macropore flow.Parameter analysis shows that macropore flow is delayed by increasing proportion of macropore domain(ω_(f)),whereas promoted by increasing ratio of saturated permeability coefficients between the two domains(μ).The increasing trend of ponding depth is sharp at first and then grows slowly.Finally,when rainfall duration is less than 3 h,ωf andμhave no significant effect on the safety factor,whereas it decreases with increasingωf and increases with increasingμunder longer duration(≥3 h).With the increase ofω_(f),the slope maximum instability time advances by 10.5 h,and with the increase ofμ,the slope maximum instability time delays by 3.1 h.展开更多
The traditional Green-Ampt model does not accurately represent the infiltration behavior of clay soils.Infiltration in clay is influenced by low hydraulic conductivity,strong capillary forces,and a gradual transition ...The traditional Green-Ampt model does not accurately represent the infiltration behavior of clay soils.Infiltration in clay is influenced by low hydraulic conductivity,strong capillary forces,and a gradual transition zone between saturated and unsaturated zones.These factors often lead to overestimated infiltration rates and underestimated infiltration durations.Therefore,it is necessary to improve the model to better reflect the characteristics of clay infiltration and enhance its predictive accuracy and practical applicability.This study conducts hydraulic characterization tests,one-dimensional soil column rainfall infiltration experiments,and numerical analysis on a representative clay sampled from Wuhan,China,to investigate infiltration behaviors under varying rainfall intensities and initial moisture conditions.The study reveals that the proportion of the transition layer within the wetting layer decreases with increasing wetting front depth,following a power-law function.Under the same initial moisture content,this proportion tends to converge to a stable value regardless of rainfall intensity.In contrast,under the same rainfall intensity,a higher initial moisture content leads to a larger proportion of the transition layer at a given wetting front depth.Based on the NMR curve,the unsaturated permeability coefficients corresponding to different volumetric water contents of clay can be obtained quickly,accurately,and at low cost.By utilizing the unsaturated permeability coefficient prediction model based on the nuclear magnetic resonance(NMR)curve,the study refines the computational method for the equivalent permeability coefficient in the wetting layer during clay rainfall infiltration,and proposes an improved clay Green-Ampt infiltration model that considers the saturated-unsaturated differentiation layer and the dynamic variation of its equivalent permeability coefficient under continuous rainfall conditions.The computational results of the improved model were compared with measured infiltration data,numerical simulations,and predictions from the traditional GA model.The results indicate that the improved model effectively captures the dynamic variation between the transition layer and wetting layer and provides more accurate predictions of wetting front depth in clay,with an accuracy approximately 68.36%higher than that of the traditional GA model.展开更多
Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous f...Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous factors. Accurate estimation of soil infiltration is required for future irrigation, and many other purposes. To estimate the infiltration process, there are numerous models. The majority of them have some presumptions, a unique calculation method, and some limitations. The purpose of the paper was to assess the model’s performance for a similar hypothetical scenario involving soil infiltration. It compared the infiltration rate, runoff rate, and incremental infiltration versus time for three different infiltration models: the Green-Ampt model (GA), the Horton model and the Modified Green-Ampt (MGA) model. A spreadsheet was used to calculate the Horton model, and HYDROL-INF (V 5.03) was used to simulate the other two models. Among those three models, the MGA model outperformed those three models, while the GA model produced greater infiltration rate than rainfall, which was insensible. The study showed that the MGA model, which provides useful infiltration predictions, outperformed the other two infiltration models. Since the Horton model does not consider ponding conditions, it is only applicable when the effective rainfall intensity exceeds the final infiltration capacity. Moreover, the GA model’s initial infiltration rate is irrational because it disregards the intensity of the rainfall. The results of this study will assist in selecting the most accurate method for estimating soil infiltration for agricultural purposes.展开更多
Determination of the infiltration rate in a watershed is not easy and in empirical and theoretical point of view, it is important to access average value of infiltration. Infiltration models has main role in managing ...Determination of the infiltration rate in a watershed is not easy and in empirical and theoretical point of view, it is important to access average value of infiltration. Infiltration models has main role in managing water sources. Therefore different types of models with various degrees of complexity were developed to reach this aim. Most of the estimating methods of soil infiltration are expensive and time consuming and these methods estimate infiltration with hypothesis of zero slope. One of the conceptual and physical models for estimating soil infiltration is Green-Ampt model which is similar to Richard model. This model uses slope factor in estimating infiltration and this is the power point of Green-Ampt model. In this research the empirical model of Green-Ampt was optimized with integrating artificial neural network model (ANN) and a model of geographical information system WMS to estimate the infiltration in Kakasharaf watershed. Results of the comparison between the output of this method and real value of infiltration in region (through multiple cylinders) showed that this method can estimate the infiltration rate of Kakasharaf watershed with low error and acceptable accuracy (Nash-Sutcliff performance coefficient 0.821, square error 0.216, correlation coefficient 0.905 and model error 0.024).展开更多
基金funded by the Natural Science Foundation of Fujian Province(Grant No.2023J011133)。
文摘Infiltration–runoff–slope instability mechanism of macropore slope under heavy rainfall is unclear.This paper studied its instability mechanism with an improved Green–Ampt(GA)model considering the dual-porosity(i.e.,matrix and macropore)and ponding condition,and proposed the infiltration equations,infiltration–runoff coupled model,and safety factor calculation method.Results show that the infiltration processes of macropore slope can be divided into three stages,and the proposed model is rational by a comparative analysis.The wetting front depth of the traditional unsaturated slope is 17.2%larger than that of the macropore slope in the early rainfall stage and 27%smaller than that of the macropore slope in the late rainfall stage.Then,macropores benefit the slope stability in the early rainfall but not in the latter.Macropore flow does not occur initially but becomes pronounced with increasing rainfall duration.The equal depth of the wetting front in the two domains is regarded as the onset criteria of macropore flow.Parameter analysis shows that macropore flow is delayed by increasing proportion of macropore domain(ω_(f)),whereas promoted by increasing ratio of saturated permeability coefficients between the two domains(μ).The increasing trend of ponding depth is sharp at first and then grows slowly.Finally,when rainfall duration is less than 3 h,ωf andμhave no significant effect on the safety factor,whereas it decreases with increasingωf and increases with increasingμunder longer duration(≥3 h).With the increase ofω_(f),the slope maximum instability time advances by 10.5 h,and with the increase ofμ,the slope maximum instability time delays by 3.1 h.
基金financial support from the Joint Funds of the National Nature Science Foundation of China(No.U22A20232)Supported by Open Project Funding of Key Laboratory of Intelligent Health Perception and Ecological Restoration of Rivers and Lakes,Ministry of Education(HGKFZ07)+2 种基金the National Natural Science Foundation of China(No.51978249)Innovation Research Team Project of the Hubei Provincial Department of Science and Technology(2025AFA020)the International Collaborative Research Fund for Young Scholars in the Innovation Demonstration Base of Ecological Environment Geotechnical and Ecological Restoration of Rivers and Lakes.
文摘The traditional Green-Ampt model does not accurately represent the infiltration behavior of clay soils.Infiltration in clay is influenced by low hydraulic conductivity,strong capillary forces,and a gradual transition zone between saturated and unsaturated zones.These factors often lead to overestimated infiltration rates and underestimated infiltration durations.Therefore,it is necessary to improve the model to better reflect the characteristics of clay infiltration and enhance its predictive accuracy and practical applicability.This study conducts hydraulic characterization tests,one-dimensional soil column rainfall infiltration experiments,and numerical analysis on a representative clay sampled from Wuhan,China,to investigate infiltration behaviors under varying rainfall intensities and initial moisture conditions.The study reveals that the proportion of the transition layer within the wetting layer decreases with increasing wetting front depth,following a power-law function.Under the same initial moisture content,this proportion tends to converge to a stable value regardless of rainfall intensity.In contrast,under the same rainfall intensity,a higher initial moisture content leads to a larger proportion of the transition layer at a given wetting front depth.Based on the NMR curve,the unsaturated permeability coefficients corresponding to different volumetric water contents of clay can be obtained quickly,accurately,and at low cost.By utilizing the unsaturated permeability coefficient prediction model based on the nuclear magnetic resonance(NMR)curve,the study refines the computational method for the equivalent permeability coefficient in the wetting layer during clay rainfall infiltration,and proposes an improved clay Green-Ampt infiltration model that considers the saturated-unsaturated differentiation layer and the dynamic variation of its equivalent permeability coefficient under continuous rainfall conditions.The computational results of the improved model were compared with measured infiltration data,numerical simulations,and predictions from the traditional GA model.The results indicate that the improved model effectively captures the dynamic variation between the transition layer and wetting layer and provides more accurate predictions of wetting front depth in clay,with an accuracy approximately 68.36%higher than that of the traditional GA model.
文摘Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous factors. Accurate estimation of soil infiltration is required for future irrigation, and many other purposes. To estimate the infiltration process, there are numerous models. The majority of them have some presumptions, a unique calculation method, and some limitations. The purpose of the paper was to assess the model’s performance for a similar hypothetical scenario involving soil infiltration. It compared the infiltration rate, runoff rate, and incremental infiltration versus time for three different infiltration models: the Green-Ampt model (GA), the Horton model and the Modified Green-Ampt (MGA) model. A spreadsheet was used to calculate the Horton model, and HYDROL-INF (V 5.03) was used to simulate the other two models. Among those three models, the MGA model outperformed those three models, while the GA model produced greater infiltration rate than rainfall, which was insensible. The study showed that the MGA model, which provides useful infiltration predictions, outperformed the other two infiltration models. Since the Horton model does not consider ponding conditions, it is only applicable when the effective rainfall intensity exceeds the final infiltration capacity. Moreover, the GA model’s initial infiltration rate is irrational because it disregards the intensity of the rainfall. The results of this study will assist in selecting the most accurate method for estimating soil infiltration for agricultural purposes.
文摘Determination of the infiltration rate in a watershed is not easy and in empirical and theoretical point of view, it is important to access average value of infiltration. Infiltration models has main role in managing water sources. Therefore different types of models with various degrees of complexity were developed to reach this aim. Most of the estimating methods of soil infiltration are expensive and time consuming and these methods estimate infiltration with hypothesis of zero slope. One of the conceptual and physical models for estimating soil infiltration is Green-Ampt model which is similar to Richard model. This model uses slope factor in estimating infiltration and this is the power point of Green-Ampt model. In this research the empirical model of Green-Ampt was optimized with integrating artificial neural network model (ANN) and a model of geographical information system WMS to estimate the infiltration in Kakasharaf watershed. Results of the comparison between the output of this method and real value of infiltration in region (through multiple cylinders) showed that this method can estimate the infiltration rate of Kakasharaf watershed with low error and acceptable accuracy (Nash-Sutcliff performance coefficient 0.821, square error 0.216, correlation coefficient 0.905 and model error 0.024).
