Search Results (20)

The Green–Ampt (GA) model is a widely used analytical method to calculate the depth of the wetting front during intense rainfall. However, it neglects the existence of the transition layer and the seepage parallel to the slope surface. Therefore, a modified stratified Green–Ampt (MSGA) model is proposed. A process to assess the stability of the finite slope during a rainfall event is demonstrated by combining the MSGA model and the limit equilibrium method. In the case of the Liangshuijing landslide, the factor of safety presents a negative correlation with the depth of the wetting front. The factor of safety obtained by the stratified Green–Ampt (SGA) model is smaller than that calculated by the MSGA model, and the gap between the factor of safety based on the two methods widens with time. The moving speed of the wetting front accelerates with the increase in the length of the slope surface, and the size effect becomes apparent when the length is short. In the initial stage of infiltration, the effect of the seepage parallel to the slope surface is small. The effect of the seepage cannot be neglected at the latter stage. The result calculated by the MSGA model agrees well with the measured result in the test. Full article

A thorough understanding of the hydrologic mechanisms that control the movement of water through the soil is essential for developing effective stormwater management strategies. Infiltration is critical for determining the amount of water entering the soil and controlling surface runoff. Spatial and temporal variations in soil properties strongly affect infiltration rates, which underscores the importance of evaluating field-specific values for hydraulic conductivity, which are also highly dependent on the chosen measurement and evaluation methods. The objective of this study is to determine and compare soil hydraulic conductivity under dry conditions using two field measurement techniques, namely the double-ring infiltrometer (DRI) and the mini-disk infiltrometer (MDI). The results demonstrate the importance of performing multiple replicates of infiltration tests, especially during the dry season, as the initial dry surface caused deviations in hydraulic conductivity estimates for both methods used (DRI and MDI). Significant spatial variability was observed within the radius of the test replicates over short distances (<1 m). In addition, experimental infiltration curves for a selected site were used to evaluate and compare soil hydraulic parameters through infiltration modeling. In general, the Philip, Green-Ampt, and Smith-Parlange theoretical models showed a better fit to the experimental DRI data than the semi-empirical Horton model. Full article

The SCS curve number (SCS-CN) method has gained widespread popularity for simulating rainfall excess in various rainfall events due to its simplicity and practicality. However, it possesses inherent structural issues that limit its performance in accurately simulating rainfall excess and infiltration over time. The objective of this study was to develop a modified CN method with temporally varying rainfall intensity (MCN-TVR) by combining a soil moisture accounting (SMA) based SCS-CN method with the SMA method in the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS). In the MCN-TVR, the SMA-based SCS-CN method is utilized to simulate the cumulative rainfall excess and infiltration, while the SMA method in the HEC-HMS serves as an infiltration control function. A key advantage of the MCN-TVR is that it eliminates the need for additional input parameters by inherently linking the parameters in the two SMA-based methods. Sixteen hypothetical 24 h SCS Type II rainfall events with different soil types and five real rainfall events for the Rush River Watershed in North Dakota were used to assess the performances of the MCN-TVR method and the SMA-based SCS-CN method. In the hypothetical simulations, the rainfall excess simulated by the SMA-based SCS-CN and MCN-TVR models was compared to that simulated by a Green–Ampt model. Discrepancies were observed between the rainfall excess simulated by the SMA-based SCS-CN and Green–Ampt models, especially for coarse soils under relatively light rainfall. However, the MCN-TVR model, incorporating an infiltration control function, demonstrated its improved performance closer to the Green–Ampt model. For all the hypothetical events, the Nash–Sutcliffe efficiency (NSE) coefficient of the rainfall excess simulated by the MCN-TVR method compared to the Green–Ampt model was greater than 0.99, while the root mean standard deviation ratio (RSR) was less than 0.03. In the real applications, the SMA-based SCS-CN model failed to provide acceptable simulation of the direct runoff for rainfall events with durations of less than the time of concentration. In contrast, the MCN-TVR model successfully simulated the direct runoff for all the events with NSE values ranging from 0.65 to 0.91 and RSR values from 0.31 to 0.56. Full article

The application of the low impact development (LID) in a cold climate such as northeastern China is constrained by two unresolved research questions with regards to its infiltration potential through the winter and its varied runoff regimes between winters and summers. This study picked a typical residential district under construction in Changchun, China, and modeled the storm drainage system with and without LID facilities based on the Storm Water Management Model. The hydrological performance of LID was evaluated through various design storms and historic rain events in dry, average, and wet years. The influence of the Horton and the Green–Ampt infiltration methods on the seasonal water budgets was particularly compared since the former is universally adopted in China while the latter is more widely used in the U.S. and other countries. The results indicate that the Horton method tended to generate a higher infiltration volume than the Green–Ampt method. Consequently, when driven by the 100-year design storm, the Horton method led to a 17.4% higher outflow than the Green–Ampt method; when driven by the measured 3-year precipitation in the study area, the yearly runoff coefficients, with regards to the Horton method, were at least 1.3 times higher than those modeled by the Green–Ampt method. This finding challenged the interchangeable use of the Horton and Green–Ampt methods without tests. Furthermore, the formation of snow covers in winter also reduced the permeability of LID and its capacity of managing runoff compared to summer. However, LID still exhibited a decent potential of regulating the winter runoff in the cold region compared to the baseline, possibly owing to the presence of frequent freezing-thawing cycles. Full article

Plain farmland areas without significant topographic slope exhibit microtopographic features of different scales. Quantitative assessment of the effects of microtopography at different scales on runoff generation in typical farmland areas is of great significance for regional water resources management and flood disaster forecasting. The main objective of the study was to develop an event-based rainfall–runoff model based on the layered Green–Ampt model (LGAM) with the consideration of plot-scale microtopographic features in plain farmland areas. Our experimental field, located in Taihu Lake Basin, was classified into three types of topographic subunits (i.e., main field, rill, and ditch) according to the average elevation. To simplify the concentration process for three topographic subunits, the average concentration time method was employed. Here, various experimental scenarios were simulated, including two classical unsteady rainfall events in homogeneous soil, one ponding infiltration experiment, and two typical rainfall–runoff events in the experimental field. We found that the multilayered setting showed higher accuracy than the homogeneous setting for simulating infiltration in the ponding infiltration experiment in the field. The RMSE of simulated ponding water depth reduced from 0.166 cm to 0.035 cm and NSE rose from 0.988 to 0.999. The simulated hydrograph considering microtopography effects proved higher accuracy than that under unified topography assumption. After classifying topography, the RMSE and NSE of simulated hydrographs decreased and increased, respectively. The lower the topographic subunit, the earlier the outflow occurred. At the early stage, the runoff mostly originated from the relatively low topographic subunits. Infiltration-excess regime under saturated condition may initially dominate in the low-lying ditch under intense rainfall, with extremely high runoff coefficient. Concentration process in the plain farmland area was affected by both rainfall intensity and microtopography. The greater the rainfall intensity, the shorter the average concentration time. The concentration velocity under heavy rainfall was four times faster than that under light rainfall. The lower topographic subunit was characterized by shorter concentration pathway and average concentration time. Ditches reduced the peak flow and advanced the time to peak. This quantitative study provides new insights into effects of microtopography on runoff generation in plain farmland area as well as an effective alternative for plot-scale rainfall–runoff modeling. Full article

Capillary barrier covers consist of fine-grained soil layer overlying coarse-grained soil layer, which are widely used as surface covers for mine tailings, solid waste landfills, and low-level radioactive waste repositories. On one hand, the capillary barrier covers can effectively prevent the rainfall water infiltrating into the toxic and hazardous materials below. On the other hand, the infiltrated water stores and diverts in the fine-grained soil layer, leading to a reduction in the stability of the capillary barrier covers. In this study, a stability analysis method for the capillary barrier covers was established based on the Green-Ampt model and the Janbu method. Firstly, the infiltration process of capillary barrier covers was analyzed and divided into four stages. The variation of the wetting front profile during infiltration, caused by the capillary barrier effect, was depicted based on the law of mass conservation. Next, the wetting front is assumed to be the potential sliding surface. As the infiltration goes on, the stability of capillary barrier covers in different stages was analyzed through the limit equilibrium method. Both the water redistribution and the influence of seepage force in the capillary barrier covers were considered in the proposed method. Finally, using the examples in the published articles, the availability and superiority of the proposed method was verified. Full article

Ascertaining the spatiotemporal accuracy of precipitation is a challenge for hydrologists and planners for flood protection measures. The objective of this study was to compare streamflow simulations using rain gauge and radar data from a watershed in Southern Ontario, Canada, using the Hydrologic Engineering Center’s event-based distributed Hydrologic Modeling System (HEC-HMS). The model was run using the curve number (CN) and the Green and Ampt infiltration methods. The results show that the streamflow simulated with rain gauge data compared better with the observed streamflow than the streamflow simulated using radar data. However, when the Mean Field Bias (MFB) corrections were applied, the quality of the streamflow results obtained from radar rainfall data improved. The results showed no significant difference between the simulated streamflow using the SCS and the Green and Ampt infiltration approach. However, the SCS method is reasonably more appropriate for modeling the runoff at the sub-basin-scale than the Green and Ampt infiltration approach. With the SCS method, the simulated and observed runoff amount obtained using rain gauge rainfall showed an R² value of 0.88 and 0.78 for MFB-corrected radar and 0.75 for radar only. For the Green and Ampt modeling option, the R² value for the simulated and observed runoff amounts were 0.87 with rain gauge, 0.66 with radar only, and 0.68 with MFB-corrected radar rainfall inputs. The NSE values for rain gauge input ranged from 0.65 to 0.35. Overall, three values were less than 0.5 for streamflow for both the methods. For seven radar rainfall events, the NSE was greater than 0.5, with a range of very good to satisfactory. The analysis of RSR showed a very good comparison of stream flow using the SCS curve number method and Green and Ampt method using different rainfall inputs. Only one value, the 2 November 2003 event, was above 0.7 for rain gauge-based streamflow. The other RSR values were in the range of “very good”. Overall, the study showed better results for the simulated runoff with the MFB-corrected radar rainfall when compared with the simulations obtained using radar rainfall only. Therefore, MFB-corrected radar could be explored as a substitute rainfall source. Full article

The variation in moisture content between subsequent irrigations determines the use of infiltration equations that contain representative physical parameters of the soil when irrigation begins. This study analyzes the reliability of the hydrodynamic model to simulate the advanced phase in border irrigation. For the solution of the hydrodynamic model, a Lagrangian scheme in implicit finite differences is used, while for infiltration, the Kostiakov equation and the Green and Ampt equation are used and compared. The latter was solved using the Newton–Raphson method due to its implicit nature. The models were validated, and unknown parameters were optimized using experimental data available in the literature and the Levenberg–Marquardt method. The results show that it is necessary to use infiltration equations based on soil parameters, because in subsequent irrigations, the initial conditions change, modifying the advance curve in border irrigation. From the coupling of both equations, it is shown that the empirical Kostiakov equation is only representative for a specific irrigation event, while with the Green and Ampt equations, the subsequent irrigations can be modeled, and the advance/infiltration process can be observed in detail. Full article

In the present study, the determination of soil saturated hydraulic conductivity (K_s) and soil sorptivity (S) from one-dimensional vertical infiltration data of eight different soils were investigated using three methodologies. Specifically, the nonlinear optimization procedure with the help of the Excel Solver application using six different two-parameter infiltration equations, as described by Valiantzas, Haverkamp et al. (complete, two and three approximate expansions), Talsma and Parlange and Green and Ampt; the linearization method of cumulative infiltration data by Valiantzas and the method of Latorre et al. were used. The results showed that, in almost all cases, the relative errors in the prediction of S were smaller than those of K_s. The nonlinear optimization procedure using the Valiantzas equation gave the best prediction of S and K_s, with relative errors up to −12.49% and 13.61%, respectively. The two-term approximate expansion of Haverkamp gave the highest relative errors in both S and K_s. The various forms of the Haverkamp equation (complete and three approximate expansion), as well as the Latorre method, gave good predictions of S and K_s in fine-textured soils. In all forms of the Haverkamp equation, when parameter β was considered as an additional adjustment parameter, no improvement in the prediction of the S and K_s values was achieved, so the constant value β = 0.6 was proposed. The relative errors in the prediction of S and K_s resulting from the linearization method of the cumulative infiltration data were similar to those of the Valiantzas equation by the nonlinear optimization procedure. The accuracy in estimating the S and K_s parameters from each equation depends on its infiltration time validity and the soil type. Full article

Groundwater recharge is strongly influenced by the infiltration process. In this research, the Philip, Horton, Kostiakov, and Green–Ampt infiltration models were tested for the ability to describe the infiltration process in the ephemeral stream beds located in Al Madinah Al Munawarah Province in Saudi Arabia. Infiltration data were obtained from double-ring infiltrometer tests in 14 locations distributed over the province. The method of least squares through an objective function optimization formalism is utilized to estimate the parameters of each model. The results show high variability in the parameters of each model over the tests. Individual tests showed that some models were better for representing specific tests than other models. On average, the Kostiakov empirical model was the best at describing the 14 infiltration tests with only 2 empirical parameters, since it had the minimum root mean square error (RMSE) for the cumulative infiltration depth F (1.13 cm), and it also had the same RMSE for the infiltration rates f (0.1 cm/min), similar to other models. Moreover, the Kostiakov model had an acceptable correlation coefficient R = 0.61 for f, and R = 0.99 for F. The results imply significant variability in the groundwater recharge rates from flash floods in the region. Full article

Stormwater control is an urgent concern in cities where the increased impervious surface has disrupted natural hydrology, particularly causing a reduction in groundwater recharge which is the source of potable water supply for many communities. Water managers are increasingly turning towards infiltration-based stormwater management options (ISMOs) to help minimize flooding and mitigate the impact of urbanization on the local hydrologic systems. This paper offers a unique hydrologic and hydraulic (H&H) modeling approach using the Geographic Information System (GIS) and Interconnected Pond and Channel Routing (ICPR) software to help quantify the associated flood stage and groundwater recharge benefits of using ISMOs. The proposed approach incorporated ICPR percolation links and utilization of the curve number and Green-Ampt infiltration methods into the case study design, as well as an analysis of the effectiveness of including low-impact development practices. This analysis shows a 13–36% reduction in stormwater volume leaving the proposed site when percolation links were utilized to account for percolation from the proposed ISMOs. These reduction provides an indirect estimate of groundwater recharge benefits. The conversion from impervious parking to a pervious one and inclusion of rainwater harvesting from the roof area resulted in a further reduction in peak stages ranging from 1.20 to 7.62 cm. Full article

In gravity irrigation, how water is distributed in the soil profile makes it necessary to study and develop methodologies to model the process of water infiltration and redistribution. In this work, a model is shown to simulate the advancing front in border irrigation based on the one dimensional equations of Barré de Saint-Venant for the surface flow and the equation of Green and Ampt for the flow in a porous medium. The solutions were obtained numerically using a finite difference Lagrangian scheme for the surface flow and the Raphson method for the subsurface flow. The model was validated with data obtained from the literature from an irrigation test and its predictive capacity was compared with another model and showed excellent results. The hydrodynamic parameters of the soil, necessary to obtain the optimal irrigation discharge, were obtained through the solution of the inverse problem using the Levenberg–Marquardt optimization algorithm. Finally, the results found here allow us to recommend that this model be used to design and model border irrigation, since the infiltration equation uses characteristic parameters of the physical soil. Full article

Rainfall-runoff transformation on urban catchments involves physical processes governing runoff production in urban areas (e.g., interception, evaporation, depression, infiltration). Some previous 1D/2D coupled models do not include these processes. Adequate representation of rainfall–runoff–infiltration within a dual drainage model is still needed for practical applications. In this paper we propose a new modelling setup which includes the rainfall–runoff–infiltration process on overland flow and its interaction with a sewer network. We first investigated the performance of an outflow hydrograph generator in a 2D model domain. The effect of infiltration losses on the overland flow was evaluated through an infiltration algorithm added in a so-called Surf-2D model. Then, the surface flow from a surcharge sewer was also investigated by coupling the Surf-2D model with the SWMM 5.1 (Storm Water Management Model). An evaluation of two approaches for representing urban floods was carried out based on two 1D/2D model interactions. Two test cases were implemented to validate the model. In general, similar results in terms of peak discharge, water depths and infiltration losses against other 1D/2D models were observed. The results from two 1D/2D model interactions show significant differences in terms of flood extent, maximum flood depths and inundation volume. Full article

This study examined how different nonhomogeneous soil characteristics affected hydrologic responses in rainfall-runoff models. The cell-based FLO-2D and lumped Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) were setup. Then, water loss parameters of both the Green-Ampt infiltration approach and curve number method were prescribed and applied in three different ways: (i) a separate value for each cell (mosaic; (ii) a representative as a most frequent occurring value for a large area (predominant); (iii) and a representative as an arithmetic mean value for a watershed (arithmetic mean). The spatial variability of nonhomogeneous catchment parameters was disregarded in lumped models, while each cell had distinct surface parameters in the distributed models. This study shows that the hydrologic response was meaningfully different in different representations. For the study site, the mosaic method was recommended for distributed models, and arithmetic mean was recommended for lumped models. Full article

The increase in frequency and intensity of extreme precipitation events caused by the changing climate (e.g., cloudbursts, rainstorms, heavy rainfall, hail, heavy snow), combined with the high population density and concentration of assets, makes urban areas particularly vulnerable to pluvial flooding. Hence, assessing their vulnerability under current and future climate scenarios is of paramount importance. Detailed hydrologic-hydraulic numerical modeling is resource intensive and therefore scarcely suitable for performing consistent hazard assessments across large urban settlements. Given the steadily increasing availability of LiDAR (Light Detection And Ranging) high-resolution DEMs (Digital Elevation Models), several studies highlighted the potential of fast-processing DEM-based methods, such as the Hierarchical Filling-&-Spilling or Puddle-to-Puddle Dynamic Filling-&-Spilling Algorithms (abbreviated herein as HFSAs). We develop a fast-processing HFSA, named Safer_RAIN, that enables mapping of pluvial flooding in large urban areas by accounting for spatially distributed rainfall input and infiltration processes through a pixel-based Green-Ampt model. We present the first applications of the algorithm to two case studies in Northern Italy. Safer_RAIN output is compared against ground evidence and detailed output from a two-dimensional (2D) hydrologic and hydraulic numerical model (overall index of agreement between Safer_RAIN and 2D benchmark model: sensitivity and specificity up to 71% and 99%, respectively), highlighting potential and limitations of the proposed algorithm for identifying pluvial flood-hazard hotspots across large urban environments. Full article