Modeling the infiltration capacity of permeable stormwater channels with a check dam system

The use of permeable stormwater channels has introduced concerns over the effects of infiltration on the hydraulic behavior of their flow and the effects of flow hydraulic conditions (e.g., the water level, channel section, flow velocity, and vegetation) on the channel infiltration capacity. A check dam system provides backwater ponding, which increases the flow water depth along a channel. In this study, a channel model was used to investigate the variation in the infiltration capacity of permeable stormwater channels under different flow hydraulic conditions. Increasing the downstream check dam height and using a grass cover increased the infiltration rate and cumulative infiltration because of the decreased velocity and increased flow depth. The presence of subsurface water did not affect the hydraulic characteristics of the channel flow but decreased the cumulative infiltration because of the fast saturation of the soil. An empirical equation was developed for predicting the infiltration capacity of grassed channels in which four hydraulic parameters (i.e., the water depth, base width, side slope, and velocity) are introduced to the modified Kostiakov model. The developed model was used to calculate the runoff reduction due to infiltration along a grassed channel with and without a check dam system. The percentage of infiltrated water increased from 8 to 14% with the check dam system. The developed model can be used to predict the infiltration capacity of permeable channels for improved stormwater management and provides a valuable decision support tool for permeable channel design

Modified models for better prediction of infiltration rates in trapezoidal permeable stormwater channels

In stormwater management, it is important to accurately quantify the infiltration rates to solve urban runoff-related problems. This study proposes a method to improve estimates of the infiltration rate in permeable stormwater channels. As part of the analysis, five infiltration models were evaluated: the Kostiakov, Horton, modified Kostiakov, Philip and SCS (Soil Conservation Service) models. Infiltration tests with various initial water levels were performed on channel models with differing base width and side slopes. The results show that the addition of three parameters that describe the trapezoidal cross-sectional area, i.e. the depth, side slope and base width, in the infiltration models yielded better estimates of the infiltration rate. A comparison of the infiltration capacity values obtained from the models after the three parameters were added with those that were experimentally obtained, shows that the improved modified Kostiakov model is the most suitable model to predict infiltration rates in trapezoidal permeable stormwater channels

Prediction of daily water level using new hybridized GS-GMDH and ANFIS-FCM models

Accurate prediction of water level (WL) is essential for the optimal management of different water resource projects. The development of a reliable model for WL prediction remains a challenging task in water resources management. In this study, novel hybrid models, namely, Generalized Structure�Group Method of Data Handling (GS-GMDH) and Adaptive Neuro-Fuzzy Inference System with Fuzzy C-Means (ANFIS-FCM) were proposed to predict the daily WL at Telom and Bertam stations located in Cameron Highlands of Malaysia. Different percentage ratio for data division i.e. 50%–50% (scenario�1), 60%–40% (scenario-2), and 70%–30% (scenario-3) were adopted for training and testing of these models. To show the efficiency of the proposed hybrid models, their results were compared with the standalone models that include the Gene Expression Programming (GEP) and Group Method of Data Handling (GMDH). The results of the investigation revealed that the hybrid GS-GMDH and ANFIS-FCM models outperformed the standalone GEP and GMDH models for the prediction of daily WL at both study sites. In addition, the results indicate the best performance for WL prediction was obtained in scenario-3 (70%–30%). In summary, the results highlight the better suitability and supremacy of the proposed hybrid GS-GMDH and ANFIS-FCM models in daily WL prediction, and can, serve as robust and reliable predictive tools for the study regio

Modeling infiltration capacity of permeable channels under static and dynamic hydraulic conditions

Increasing infiltration rate of stormwater is important for improving the control of stormwater quantity to foster sustainable urban stormwater management. In the design of stormwater channels, the effect of infiltration on the channel flow and the effects of hydraulic parameters such as water level, channel cross section, flow velocity, and vegetation, on the infiltration capacity of channels are usually ignored. The present study aimed to examine the effects of hydraulic parameters on the infiltration capacity of permeable channels through laboratory investigation on channel models under static and dynamic hydraulic conditions. The study also aimed to develop empirical models for the variations of infiltration capacity with flow hydraulic parameters, in order to improve the design of permeable stormwater channels. Different channel models were constructed for each of the above condition, and different sets of hydraulic and channel boundary conditions were used to characterise the channel flow considering the effect of infiltration and to develop empirical models for predicting infiltration capacity for permeable channels. The effect of channel cross section on the flow reduction by seepage and infiltration processes were first examined under static or standing water condition, with various initial water levels, channel base widths and side slopes. Regression analysis was used to develop an equation for predicting the rate of unsteady seepage over time, and the equation was used to examine several cases of different flow cross-sectional areas and channel dimensions, and subsequently, to determine the section that produced highest infiltration and seepage under the unsaturated soil condition. Moreover, five existing infiltration models, namely, the Kostiakov, Horton, Modified Kostiakov, Philip, and Soil Conservation Service (SCS) models were evaluated, and then they were modified by incorporating the cross-sectional flow area parameters (depth y, side slope m, and bottom width b) into them. Under the dynamic or flowing water condition, the mass-balance method was used for the estimation of infiltration rate, and the experimental tests employed five inflow rates (Qin = 5.5, 7.5, 9.5, 11.5, 13.5 l/s), with three downstream check dam heights (hw = 10, 15, 20 cm). In addition, two other sets of experiments were conducted to investigate the effects of grass cover and subsurface water on infiltration rate. The findings were used to quantify and compare the different cases in terms of the infiltration rate and cumulative infiltration, and then to develop predictive equations that include the effect of hydraulic parameters for estimating the infiltration rate in permeable channels. The results indicated that the infiltration and seepage rates increase with increasing initial water level irrespective of the base width and side slope. Moreover, an increase in the side slope increases both the infiltration and seepage rates, with the effect becoming more significant as the initial water level increases, while the effect of varying the base width is insignificant. It has also been found that increasing the wetted perimeter or top width of a channel enhances the infiltration rate if this is achieved by varying the side slope, and not by increasing the base width. In the evaluation of the five infiltration models, a comparison using the coefficients of determination R2 obtained before and after the parameters were added into the models reveals that the difference between the observed and predicted values using the modified models was significantly reduced, and R2 increased sharply from 0.14, 0.158, 0.164, 0.146 and 0.162 for the Kostiakov, Horton, Modified Kostiakov, Philip, and SCS models, respectively, to 0.732, 0.621, 0.735, 0.718 and 0.609. Two predictive equations were developed finally using the nonlinear regression analysis after introducing the four hydraulic parameters (y, m, b and v) into the Kostiakov and Modified Kostiakov models, which were chosen to be improved because they have been shown to give better performance than the other models during the previous analysis. The latter model with the new parameters was used for the analysis of a channel section to determine the best conditions to obtain the highest infiltration rates for given flow rates and then to plot graphs of the variation of cumulative infiltration F over time for a grassed channel with different check dam heights and inflow rates. Cumulative infiltration quantity after 90 min for two cases of channels, with and without check dams, were compared and the results reveal that the percentage of total infiltrated water volume increased from 8% to 14% when using check dams with 20- cm height and 10-m spacing compared to the channel without the check dams. Modeling the variations of infiltration capacity with hydraulic parameters in permeable channels using the models developed in this study therefore promises better storm water management and provides a valuable decision support tool for designing the permeable channels

Permeable channel cross section for maximizing stormwater infiltration and seepage rates

Maximization of infiltration and seepage rates is important to better control the quantity of stormwater to foster sustainable urban stormwater management. In this study, the effect of the cross-sectional flow area of a permeable channel on seepage rate was investigated to improve the efficiency of permeable stormwater channels. Physical models under ponding were used to examine seepage of earthen trapezoidal channels with various initial water levels, base widths, and side slopes. Regression analysis was used to develop an equation for predicting the rate of the unsteady seepage over time, and the equation was used to examine several cases of different flow cross-sectional areas and channel dimensions. The results showed that the channel side slope significantly affected the cumulative seepage volume. For a given top width, decreasing the base width and increasing the side slope resulted in an increase in the unsteady seepage rate

Modeling of scour depth and length of a diversion channel flow system with soft computing techniques

This study employed soft computing techniques, namely, support vector machine (SVM) and Gaussian process regression (GPR) techniques, to predict the properties of a scour hole [depth (ds) and length (Ls)] in a diversion channel flow system. The study considered different geometries of diversion channels (angles and bed widths) and different hydraulic conditions. Four kernel function models for each technique (polynomial kernel function, normalized polynomial kernel function, radial basis kernel, and the Pearson VII function kernel) were evaluated in this investigation. Root mean square error (RMSE) values are 8.3949 for training datasets and 11.6922 for testing datasets, confirming that the normalized polynomial kernel function-based GP outperformed other models in predicting Ls. Regarding predicting ds, the polynomial kernel function-based SVM outperforms other models, recording RMSE of 0.5175 for training datasets and 0.6019 for testing datasets. The sensitivity investigation of input parameters shows that the diversion angle had a major influence in predicting Ls and ds. HIGHLIGHTS Soft computing implementation for prediction of the properties of scour hole.; Benchmarking of SVM and GP-based data-intelligent models.; The diversion angle had a major influence in predicting the properties of scour hole.

Modelling infiltration rates in permeable stormwater channels using soft computing techniques

In the design of permeable stormwater channels, the ability to quantify infil-tration rates accurately is important for assessing the capability of such chan-nels to perform their required functions. Most of the available infiltrationmodels neglect the effects of water level and channel section on the infiltrationrate. In this study, physical channel models, with different channel sections,were developed in the laborator y and used to measure the infiltration rates.The performance of three soft computing techniques, including Gaussian pro-cess regression, M5P, and random forest (RF) models, were evaluated againstmeasured values. Seven independent input variables, namely, channel sideslope (m), base width (b), water level (y), sand (%), silt (%), clay (%), and time(T) and the output variable infiltration rate (f(t)), were considered in the modeldevelopment and validation. The Gaussian progression–Pearson VII universalkernel function model approach was found to perform best for the data setconsidered, followed by the RF-based model. The sensitivity investigationshowed that time, water level, and channel side slope were the most influentialinput variables in predicting infiltration rates for permeable stormwater chan-nels and should be given primary consideration in designing such channels

Estimation of Reference Evapotranspiration in Semi-Arid Region with Limited Climatic Inputs Using Metaheuristic Regression Methods

Different regression-based machine learning techniques, including support vector machine (SVM), random forest (RF), Bagged trees algorithm (BaT), and Boosting trees algorithm (BoT) were adopted for modeling daily reference evapotranspiration (ET0) in a semi-arid region (Hemren catchment basin in Iraq). An assessment of the methods with various input combinations of climatic parameters, including solar radiation (SR), wind speed (WS), relative humidity (RH), and maximum and minimum air temperatures (Tmax and Tmin), indicated that the RF method, especially with Tmax, Tmin, Tmean, and SR inputs, provided the best accuracy in estimating daily ET0 in all stations, while the SVM had the worst accuracy. This work will help water users, developers, and decision makers in water resource planning and management to achieve sustainability

Detention and Release in Stepped Gabion Weir: Case of Four Steps

The problem of water scarcity can be noticed clearly in the lined canals which provide the irrigation networks. Using porous structures like gabion weirs contributes as a part solution to this problem. In the current study, a laboratory flume was used to calculate the water depths upstream and downstream of the stepped gabion weir that is to be put inside it at a certain distance, and this flume comes with dimensions of 10 m long by 0.30 m wide and 0.50 m height. While the tested hydraulic model of the weir was built with dimensions of 0.30 m width by 0.40 m maximum height, and five lengths with different total distance of 0.88, 0.96, 1.08, 1.12, and 1.20 m respectively. The used gravel samples to fill the gabions were of monosize query gravel with diameters ranging between 0.0095-0.0140, 0.0140-0.0190, 0.0190-0.0250, 0.0250-0.0375, and 0.0375-0.0500 m in a respective way. While the values of discharge, measured during the experiments were in the range of 0.0007-0.0150 m3/s, and a total of 175 trial tests. This study achieved that the detention depth value decreases by increasing the diameter of the gravel sample used, but there is no effect of the gravel sample on the value of release depth, the different illustrated formulas for the detention and release depths maybe can be used usefully for design and scheduling actions in the field where it gave a reasonable matching between the measured and the calculated values of the studied depths, and finally, the errors percentage in an average value for both detention and release tested values were 5.278% and -0.265% respectivelyFull text license: CC BY-NC 4.0;Part of special issue: Proceedings of the 4th International Conference on Recent Innovation in Engineering ICRIE 2023, University of Duhok, College of Engineering, 13th – 14th September 2023;</p

Multi criteria decision making to optimize the best runoff control measures for the Haditha Dam Reservoir, Iraq

In Iraq, the two dominating surface water sources are Tigris and Euphrates Rivers in which some dams constructed on both of them forming reservoirs. The Haditha Dam reservoir is one of the most essential sources of drinking, irrigation, flood control and hydropower generation in Anbar State, Western Iraq. Besides, the reservoir is a unique habitat with a wide spectrum of biodiversity. The objective of this study is to investigate and monitor the water quality in Haditha Dam reservoir and introduce Multi Criteria Analysis (MCA) as a means to highlight the best runoff control measures depending on selected criteria and criteria weights. Experts were interviewed for the selection of criteria and for the assignment of the weight factor and scores. Four criteria from three categories such as technical, economic and environmental aspects were selected. Results from this study indicated that a the difference in TSS and Turbidity between the dry and wet seasons necessitates the installation of runoff control measures. It was found that the soil binders, sediment basin and diversion channel are the best alternatives for controlling erosion, sediment and drainage respectively. The sensitivity analysis showed very strong decisions made by the experts for the technical, economic and environmental criteria.Validerad;2020;Nivå 1;2020-10-19 (alebob)</p