Journal of Irrigation and Drainage Engineering

Permeable pavements underlain by infiltration beds have been used as storm-water control measures (SCMs) for several decades. As a design practice, runoff volume reduction in those systems is attributed exclusively to subsurface infiltration. Neglecting evaporation in the hydrologic cycle of permeable pavement systems is based on the perceived insignificance of this factor rather than on scientific evidence. This paper presents research designed to fill the knowledge gap in the evaporation behavior of pervious concrete SCMs. A laboratory simulation was conducted to identify parameters affecting evaporation from pervious concrete systems and to obtain the evaporation rates typical for summer months in the Philadelphia area. Considerations used in the experiment design, methodology, the experimental program, and the results are presented here. The depth to water surface and the time since rainfall event were both found to be significant terms in predicting the evaporation rate. The concept of influence depth was established and characterized as approximately 250 mm. A predictive empirical equation describing 24-h evaporation rates as a function of the initial depth and the time since the last rainstorm event was developed. Generalizing the experimental results to field conditions, the percentage of the water budget accounted for by evaporation from a single rain event was found to be highly variable, ranging from negligible to moderate depending on the watershed configuration and the size of the rain event. The paper includes a discussion of evaporation behavior and optimization of the design parameters to promote evaporation from pervious pavement systems.

Clogging of pore space is the leading cause of failure of permeable pavements. A study conducted at Villanova University on two permeable pavements, porous asphalt and pervious concrete, endeavored to answer the question of what materials were depositing in the pore spaces. In 2007, an existing parking lot at Villanova University was retrofitted with a 30 by 9 m section of permeable pavement. Half of the section (15 by 9 m) consisted of pervious concrete, whereas the other half was porous asphalt. The $270{\mathrm{m}}^2$ porous pavement area had a drainage area of $730{\mathrm{m}}^2$, which was 100% traditional dense-graded (impermeable) asphalt. A stone infiltration bed underlaid the permeable pavements. Intensive vacuuming was performed using an industrial strength vacuum cleaner to extract the material contained in the pore spaces of the pavement surface layer. The material collected was analyzed to determine the grain size distribution, percentage of organic matter, and concentration of metals (copper, lead, and zinc). Most of the material removed during vacuuming was pieces of the pavements that had raveled. This analysis revealed that very little fines or organics were found in the pore spaces of the pavements, which is attributable to the measures taken on-site to reduce the influx of foreign materials into the pavement surfaces. Metals had sorbed onto the materials removed from the pore spaces; over 20.1 g of copper, 1.8 g of lead, and 18.7 g of zinc were retained because of trapping of sediments in the pores of the permeable pavements. These results indicate that permeable pavement infiltration systems not only reduce the volume of runoff by providing a means of infiltration, but that they improve water quality by removing pollutants at several steps along the water’s path. Pollutants can sorb to the sediments in the pore spaces, the rocks in the infiltration bed, and the natural soils beneath the infiltration bed.

The ASCE-EWRI Penman-Monteith (ASCE PM) combination equation was recommended by the American Society of Civil Engineers–Environmental and Water Resources Institute as the standard equation for estimating reference evapotranspiration (${\mathrm{ET}}_o$). The standardized model was intended to simplify and clarify the presentation and application of the method; however, it requires numerous inputs that frequently are not available at most weather stations. In this study, comparisons were made between daily ${\mathrm{ET}}_o$ estimates from five different ${\mathrm{ET}}_o$ approaches using limited data to those computed with the full-form ASCE PM equation during the growing season in northeast Louisiana. Procedures to estimate missing data were followed when limited weather inputs were available. The results revealed that the differences between ${\mathrm{ET}}_o$ obtained with complete and limited data were influenced by the underlying surface, the weather conditions during the study, and the application of empirical methods to determine missing inputs. The mean absolute error (MAE) and root mean square error (RMSE) were less than 0.83 and $0.99\mathrm{mm}·{\mathrm{d}}^{-1}$, respectively, whereras low correlation was found through the coefficient of determination $R^2$. Overall, the reduced data set ${\mathrm{ASCE}\mathrm{PM}}_{SP}$ using wind speed data from a nearby station provided better results ($\mathrm{MAE}:0.56\mathrm{mm}·{\mathrm{d}}^{-1}$, $R^2:0.64$, $\mathrm{Mean}\mathrm{ratio}:0.98$) when compared with the ${\mathrm{ASCE}\mathrm{PM}}_{W2}$, Hargreaves-Samani, Turc, and Priestley-Taylor methods. The radiation-based equations tended to underestimate ${\mathrm{ET}}_o$ by as much as 10%, whereas the temperature-based Hargreaves model overestimated ${\mathrm{ET}}_o$ by 8% during the growing season.

It is important to calibrate the potential evapotranspiration measured by the Hargreaves method (${\mathrm{ET}}_{0,\mathrm{HG}}$) using the Penman-Monteith method (${\mathrm{ET}}_{0,\mathrm{PM}}$). However, the substantial temporal variations in the calibration coefficients (${\mathrm{ET}}_0$ ratio measured by the two methods) have not been considered in the spatial analysis of the calibration coefficients. The objectives of this study were to investigate the spatiotemporal distribution of the calibration coefficient on the scale of Mainland China and to compare the accuracy of the calibrated ${\mathrm{ET}}_{0,\mathrm{HG}}$ by this spatiotemporal calibration method with three alternative methods including the calibration coefficients over space or time. One year was divided into 72 five-day periods in this study. For each five-day period, quantitative models were used to describe the spatial dependence of the calibration coefficients, and the maps of the calibration coefficients were produced by the Kriging method. The accuracies of the calibrated ${\mathrm{ET}}_0$ by this spatiotemporal calibration method and the other three methods were evaluated by criteria such as absolute bias, relative bias, root mean square error, and mean bias error. The results showed spatiotemporal changes in the parameters of the geostatistical models and the maps of the calibration coefficients of Mainland China. The maps were characterized by their divisions into two regions along a calibration coefficient contour of 1.0, and the directions of these contours showed obvious seasonal changes. The accuracy of the calibrated ${\mathrm{ET}}_{0,\mathrm{HG}}$ was highest when both the spatial and temporal variations of the calibration coefficients were considered simultaneously.

Estimating the response time of a canal is essential for the open-loop control of an irrigation canal since upstream flow releases must be anticipated to satisfy scheduled demands at irrigation outlets. The authors consider a flow release at the upstream end of a pool to satisfy a side withdrawal at its downstream end. When the flow is released, wave travel time causes the flow change to arrive sometime later downstream, and attenuation causes the flow to arrive gradually downstream such that the peak discharge is further delayed. A clear definition of this response time is proposed based on volume compensation. A linear approach is used to calculate the canal response to a flow release and a withdrawal and then the volume passing at the downstream end of the canal. The approach provides an analytical determination of the time of opening that ensures volume compensation. A practical method to derive this response time is proposed. It is illustrated for a canal for which different downstream boundary conditions are imposed.

A tension-saturated capillary fringe above the water table in drained lands gives rise to lower water tables than would occur in its absence. Results of a conformal mapping solution for the flow from uniform steady rainfall rates on the soil surface to deep drains installed above an impermeable bed when the soil above the drains is wholly tension-saturated show that the effect on the water table is greater the nearer the drain is to the impermeable floor. The effect becomes less with increasing rainfall rate. For the very deep tension-saturated soils assumed in the analysis (that implies a very large negative value for the air-entry pressure for the soil), the results obtained give lower bounds for the water-table heights in real soils with finite air-entry values that lie between the calculated ones and those obtained by theory neglecting a capillary fringe.

Information on soil hydraulic properties is a prerequisite in irrigation management decisions and crop planning. Such information on soils of the black soil region (BSR) occupying $7.7\times {10}^7\mathrm{ha}$ of India is sparse. Soil profile information for 49 representative sites (244 samples) was collected and used for analysis. Ten different functions were evaluated for their efficacy to describe soil water retention characteristics (SWRC) of the BSR soils. Campbell model fitted to measured SWRC data with relatively lower root mean square error ($\mathrm{RMSE}=0.0214{\mathrm{m}}^3·{\mathrm{m}}^{-3}$), higher degree of agreement $d=0.9653$), and lower absolute error on average ($\mathrm{MAE}=0.0165{\mathrm{m}}^3·{\mathrm{m}}^{-3}$). The next best description was by van Genuchten (VG) function with RMSE ($0.0249{\mathrm{m}}^3·{\mathrm{m}}^{-3}$), $d(0.9489)$, and MAE ($0.0868{\mathrm{m}}^3·{\mathrm{m}}^{-3}$). Pedotransfer functions (PTF) were developed to predict field capacity (FC) and permanent wilting point (PWP) using nearest neighbor (kNN) algorithm and artificial neural networks (ANN). Four levels of input information used for point PTF development include (1) textural data (data on sand, silt, and clay fraction-SSC), (2) level 1+bulk density data (SSCBD), (3) level 2+organic matter (SSCBDOM), and (4) level 1+organic matter (SSCOM). The RMSE of predictions by kNN PTFs ranged from 0.0346 to $0.0611{\mathrm{m}}^3·{\mathrm{m}}^{-3}$ with an average of $0.0483{\mathrm{m}}^3·{\mathrm{m}}^{-3}$. The ANN PTFs performed with an average RMSE of $0.0550{\mathrm{m}}^3·{\mathrm{m}}^{-3}$ and a range of 0.0367 to $0.0905{\mathrm{m}}^3·{\mathrm{m}}^{-3}$. Relatively better estimates of $\mathrm{FC}/\mathrm{PWP}$ were obtained using SSCBD-based PTF. Accuracy of FC and PWP estimates obtained by using analytical functions was relatively greater than the estimates by kNN and ANN PTFs. Campbell and VG functions were relatively more accurate. The study demonstrated the efficacy of kNN technique vis-a-vis neural regression with the additional benefit of appending the development data as and when desired. The proposed PTFs could be useful in making irrigation management decisions for BSR soils of India. Identification of the most suitable SWRC function for the study soils will help in crop modeling/water balance studies of the region.

Submerged sluice gates may be used as discharge measuring structures in irrigation channels. One commonly used model to predict discharge under submerged gates is based on the simultaneous solution of the energy and momentum equations (EM method). The conventional assumption for the solution is that the roller forming downstream of the gate is a static bubble of water with zero net flux of both momentum and kinetic energy. Energy losses along the submerged gate flow are commonly neglected. In this study, rational analysis of the EM method shows that the roller momentum flux and the energy loss may be considerable. A novel formulation of the EM method accounting for these two phenomena is proposed. Although it yields results similar to those of the conventional method, the new method introduces rationality in the application of the EM equations for submerged gate flow and helped to critically revise the assumptions in which the conventional EM method is based.

In this work, the discharge coefficients of four well-defined operation stages of baffle-sluice gates are presented and modeled using the individual contributions of weir and sluice flow components. Existing empirical relationships proved effective to model the discharge. The presence of submerged baffles has an insignificant effect on the module discharge. One of the most important differences, compared with the constant value recommended in the literature, was found in the case of the submerged discharge coefficient, which grew linearly with the bottom opening. Other differences in the discharge coefficient were also found for the sluice gate flow; however, they did not significantly affect the magnitude of the discharge coefficients. The study is useful for refining the design of baffle-sluice irrigation module.