SPATIAL VARIABILITY OF CONDUCTWITY AS APPLIED TO DISTRIBUTED PARAMETER INFILTRATION MODELS1

ABSTRACT: Two infiltration models, called VVSIM (variable variance stochastic infiltration model) and EVVSIM (enhanced variable variance stochastic infiltration model), are developed in this study. A distributed parameter infiltration model can estimate the amount of infiltration over a field area by computing the infiltration over zones of the field area. Hydraulic conductivity is the most important parameter determining infiltration in simulations by infiltration models. The performance of an infiltration model depends on how well the model accommodates the complicated spatial distribution of hydraulic conductivity. The two proposed models include the effects of spatial correlation of the conductivity distribution. Virtual conductivity fields are generated using the turning bands method. Monte Carlo simulations show that the proposed models give infiltration estimates more accurate than those obtained by the other models employed.     

APPLICATION OF INFILTRATION THEORY FOR THE DETERMINATION OF EXCESS RAINFALL HYETOGRAPH1

ABSTRACT: The purpose of this paper is to show through the use of numerical examples that modern infiltration theory can be used in everyday hydrologic practice. The actual use of four methods of calculation of infiltration rates and of excess rainfall rates is demonstrated for the case when simultaneous data of rainfall and stream flow are available for a watershed. The four methods are: (1) the well known Π-index method, (2) the traditional Horton's infiltration capacity formula, (3) the less traditional Green and Ampt infiltration capacity formula, and (4) a ponding time approach. It is recommended that hydrologists become at least familiar with the numerical procedures involved in the ponding time and postponding infiltration approach. This approach, though not flawless, should be preferred to the other three methods if use of the other three is at all considered.     

INFILTRATION EVALUATION OF FOUR MECHANICAL RAINFALL SIMULATION TECHNIQUES IN SIERRA NEVADA WATERSHEDS1

ABSTRACT: Little quantitative site-specific infiltration, runoff and sediment transport data for Tahoe Basin soils under varying storm events or stage of development are available. Modular (Ml), F-type (M2), Impact nozzle (M3), and Impact-Fan nozzle (M4) rainfall simulators were evaluated as to their practicality and ability to characterize infiltration for the Cagwin Soil Series within the Tahoe Basin. Three slope (0–15,15–30, >30%) and four plot conditions (natural with duff [P1], natural without duff [P2], disturbed without duff [P3], and disturbed with duff [P4]) were studied. The measured data were incorporated into a modified Philip's infiltration model and multiple non-linear regression analyses were used to examine relationships between method, slope, plot condition, and infiltration characteristics.^t Simulation methods Ml and M4 produced statistically similar (P=0.01) infiltration data, as did M2 and M3 which produced lower infiltration rates. All were found suitable for use in Sierra Nevada watersheds. Ml was considered most practical. Slope had negligible effect on infiltration. The plot condition was found to significantly influence infiltration, and the effect of each plot condition was significantly different. Final infiltration rates ranged from 4.7 to 6.2 cm/hr. Thus, the Cagwin soil demonstrated moderate to high infiltration rates even when exposed to extreme storm conditions (8–10 cm/hr).     

USING CURVE NUMBERS TO DETERMINE BASELINE VALUES OF GREEN-AMPT EFFECTIVE HYDRAULIC CONDUCTIVITIES1

ABSTRACT: Since the trend in infiltration modeling is currently toward process-based approaches such as the Green-Ampt equation, more emphasis is being placed on methods of determining appropriate parameters for this approach. The SCS curve number method is an accepted and commonly used empirical approach for estimating surface runoff, and is based on numerous data from a variety of sources. The time and expense of calibrating process-based infiltration parameters to measured data are often prohibitive. This study uses curve number predictions of runoff to develop equations to estimate the “baseline” hydraulic conductivities (K_b) for use in the Green-Ampt equation. Curve number predictions of runoff were made for 43 soils. K_b values in the Water Erosion Prediction Project (WEPP) model were then calibrated so that the annual runoff predicted by WEPP was equal to the curve number predictions. These calibrated values were used to derive an equation that estimated K_b based on the percent sand, percent clay, and cation exchange capacity of the soil. Estimated values of K_b from this equation compared favorably with measured values and values calibrated to measured natural runoff plot data. WEPP predictions of runoff using both optimized and estimated values of K_b were compared to curve number predictions of runoff and the measured values. The WEPP predictions using the optimized values of K_b were the best in terms of both average error and model efficiency. WEPP predictions using estimated values of K_b were shown to be superior to predictions obtained from the curve number method. The runoff predictions all tended to be biased high for small events and low for larger events when compared to the measured data. Confidence intervals for runoff predictions on both an annual and event basis were also developed for the WEPP model.     

INFILTRATION OF WASTEWATER AND SIMULATED RAINWATER AS AFFECTED BY POLYACRYLAMIDE1

ABSTRACT: Irrigation reduces infiltration rates for subsequent irrigations or rains, thus decreasing the efficiency of water use and impacting watersheds in agricultural areas. Reduced infiltration causes greater runoff with its accompanying erosion, pollution, and sedimentation. Small rates of polyacrylamide (PAM) improve infiltration and reduce erosion on irrigated fields. The effects of PAM on infiltration of rainwater, the longevity of the effects of various rates of PAM, and the effects of repeated or intermittent PAM applications are not understood. This study measured the effects of four PAM application rates (0, 10, 25, and 40 ppm) on the subsequent infiltration of wastewater or simulated rainwater for seven weeks following the initial treatments. Also, effects of repeated and intermittent PAM applications on infiltration were determined. Hydraulic conductivity was determined for each soil column using the falling head method. Two soil types from the coastal plain of south Texas were tested — a soil high in clay (Victoria) and a sandy loam (Willacy). Effects of PAM rates were significant, but effects of water type were not (P > 0.05). Benefits from single PAM applications disappeared within two weeks. Water enriched with PAM is so viscous and infiltrates so slowly that applying PAM in every irrigation event may not be feasible. However, repeating PAM applications every two weeks maintained high infiltration rates on the alternate weeks. This intermittent application of PAM may be a practical approach for improving infiltration rates on irrigated lands.     

APPLICATION OF THE GREEN-AMPT INFILTRATION EQUATION TO WATERSHED MODELING1

ABSTRACT: A computer model was developed, based on the Green-Ampt infiltration equation, to computed rainfall excess for a single precipitation event. The model requires an estimate of parameters related to hydraulic conductivity, wetting front section, and fillable porosity of the soil layers. Values of parameters were estimated from soil textural averages or regression equations based on percent sand, percent clay, and porosity. Average values of effective porosity and wetting front suction were largely acceptable due to the relatively low variability and low model sensitivity to the parameters. Hydraulic conductivity was the most erratic constituent of the loss rate computation due to the high variability and the high sensitivity of the computed infiltration to the parameter. The performance of the Green-Ampt infiltration model was tested through a comparison with the SCS curve number procedure. Seven watersheds and 23 storms with precipitation of one inch or greater were used in the comparison. For storms with less than one inch of rainfall excess, the SCS curve number procedure generally gave the best results; however, for six of the seven storms with precipitation excess greater than one inch, the Green-Ampt procedure delivered better results. In this comparison, both procedures used the same initial abstractions. The separation of rainfall losses into infiltration, interception, and surface retention is, in theory, an accurate method of estimating precipitation excess. In the second phase of the study using nine watersheds and 39 storms, interception and surface retention losses were computed by the Horton equations. Green-Ampt and interception parameters were estimated from value sin the literature, while the surface retention parameter was calibrated so that the computed runoff volumes matched observed volumes. A relationship was found between the surface retention storage capacity and the 15-day antecedent precipitation index, month of year, and precipitation amount.     

SATURATED SOIL HYDRAULIC CONDUCTWITY IN LOBLOLLY PINE PLANTATIONS ON DRAINED SITES1

ABSTRACT: Variation of in situ measured saturated hydraulic conductivity (KS) with stand age was examined in drained and intensively managed loblolly pine (Pinus taeda L.) plantations on very poorly drained Bayboro loam soils. Stand ages studied were 1-year-old and 14-years old. No differences in Ks values were found between the stand ages. In addition, no differences in core measured soil properties were found between the stand ages, indicating that there were no differences in the pore structure of the soil matrix. There was large variation of Ks within stands and between stands within ages. The mean within stand Ks values ranged from 0.66 cm/hr to 4.85 cm/hr. The frequency of tests exhibiting pipe flow through large non-capillary voids was significantly greater in the older stands; however, the continuity of the voids in the soil, and whether or not non-Darcy type flow would occur in a saturated profile, could not be determined.     

MODELING PERCOLATION LOSSES FROM A PONDED FIELD UNDER VARIABLE WATER-TABLE CONDITIONS1

ABSTRACT: A numerical simulation model was developed to predict the vertical and lateral percolation losses from a ponded agricultural field. The two-dimensional steady-state unsaturated/ saturated flow equation was solved using the finite-difference technique. A constant ponding depth was maintained at the soil surface with different water table conditions in an application of the model for rice fields bordered by bunds. Field experiments were conducted for two different water table depths to collect data on the spatial distribution of volumetric soil-moisture content for model verification. The measured soil-moisture content values were found to be in close agreement with those predicted by the model. The sensitivity analysis of the model with selected hydrologic conditions shows that the model is most sensitive to the values of saturated hydraulic conductivity, but relatively less sensitive to water table depth, ponding depth, and evaporation rate from the soil surface. It implies that, in a ponded rice field condition, the lateral and vertical percolation losses are mostly governed by the hydraulic conductivity of the soil. The vertical percolation losses were almost equal to the saturated hydraulic conductivity values and, in most cases, these losses increased with deeper water table depths. The lateral percolation losses also increased with deeper water table depths; however, these losses were relatively small in comparison to the vertical percolation losses. The vertical and lateral percolation losses increased with the increase in ponding depths. The lateral percolation losses through the bund decreased when the evaporation losses increased from the soil surface. The results of this study indicate that the percolation losses from a ponded field may be predicted accurately for a wide range of soil and hydrological conditions when the values of hydraulic conductivity, evaporation rate, depth of ponding, and water table depth are accurately known.     

QUALITY OF RUNOFF FROM PLOTS WITH SIMULATED GRAZING1

ABSTRACT: Grazed pastures represent a potential source of non‐point pollution. In comparison to other nonpoint sources (e.g., row‐cropped lands), relatively little information exists regarding possible magnitudes of nutrient losses from grazed pasture, how those losses are affected by management variables, and how the losses can be minimized. The objective of this study was to measure concentrations of nitrogen (N), phosphorus (P), and solids in runoff from fescue plots and relate those measurements to simulated forage management strategy. The study was conducted at the University of Kentucky Maine Chance Agricultural Experiment Station north of Lexington. Plots (2.4 m wide by 6.1 m long) were constructed and established in Kentucky 31 fescue (Festuca arundinacea Schreb.) to represent pasture. The experimental treatments applied to the plots varied in terms of forage height and material applied (none, manure, or manure and urine). Runoff was sampled for six simulated rainfall events applied over the summer of 1997 and analyzed for nitrate N (NO₃‐N), ammonia N (NH3‐N), total Kjeldahl N (TKN), ortho‐P (PO₄‐P), total P (TP), and total suspended solids (TSS). All runoff constituents exhibited dependence on the date of simulated rainfall with generally higher concentrations measured when simulated rainfall followed relatively dry periods. The effects of forage height and manure addition were mixed. Highest runoff N concentrations were associated with the greatest forage heights, whereas highest P concentrations occurred for the least forage heights. Manure/urine addition increased runoff P concentrations relative to controls (no manure/urine) for both the greatest and least forage heights, but runoff N concentrations were increased only for the greatest forage heights. These findings indicate that runoff of N and P is at least as sensitive to amount and proximity of preceding rainfall and suggest that managing forage to stimulate growth and plant uptake can reduce runoff of N.     

SIMPLE DESIGN FOR SIMULTANEOUS STEADY-STATE INFILTRATION EXPERIMENTS WITH RING INFILTROMETERS1

ABSTRACT: A successful procedure for measuring steady-state infiltration rates at remote locations is described. The equipment for the simultaneous experiments is of simple design, inexpensive, and rugged. A total of 247 steady-state infiltration measurements were made across a small rangeland catchment using the procedure as described. The reason for the measurements was to characterize the spatial variability of infiltration across the catchment. The limiting factor for the multiple-ring system as employed in this study was a sufficient water supply to conduct the experiments to completion.     

APPLICABILITY OF THE GREEN AND AMPT INFILTRATION EQUATION TO RANGELANDS1

ABSTRACT: The objective of this study was to investigate the use of Green and Ampt infiltration equation parameters (determined by least squares fitting of field infiltration data or predicted from soil texture properties) to characterize infiltration on spatially varying rangeland sites. It was found that a least squares regression approach reduces the physically based parameters in the Green and Ampt to empirical coefficients since negative coefficients are obtained, particularly on plots with low infiltration rates. Green and Ampt parameters predicted from soil texture data describe infiltration rates less than 3 cm/hr. The applicability of these Green and Ampt parameters appears limited to sites with lower infiltration rates. Results indicate that soil texture predictive triangles, developed to describe infiltration on agricultural soils, need revision to adequately describe infiltration patterns on rangelands.     

WATER LOSS EQUATIONS AND COEFFICIENTS TO ESTIMATE RUNOFF FROM RAINFALL1

Infiltration models are based on physical characteristics of the soil and initial soil moisture. For a given soil it is based on the initial soil moisture distribution. A computer simulation model for flood runoff systems (FH-Model) was used to analyze 39 sets of rainfall-runoff data on four small watersheds ranging in size from 17 to 342 square kilometers located in the Yamaska River basin in Quebec. From these analyses, parameters and coefficients have been determined for a water loss (infiltration) equation. A method for determining the loss parameters, using a nonlinear least square curve fitting technique, is presented. Expressions were made to relate the loss parameters to antecedent precipitation. The equations were tested on 11 storm rainfall and runoff events on a watershed located in the same region and close agreements were found.     

IMPACT OF VARIED DATA RESOLUTION ON HYDRAULIC MODELING AND FLOODPLAIN DELINEATION1

ABSTRACT: Current data collection technologies such as light detection and ranging (LIDAR) produce dense digital terrain data that result in more accurate digital terrain models (DTMs) for engineering applications. However, such data are redundant and often cumbersome for hydrologic and hydraulic modeling purposes. Data filtering provides a means of eliminating redundant points and facilitates model preparation. This paper demonstrates the impact of varied data resolution on a case study completed for a 2.3 mi² area with mild slopes (about 001 ft/ft) along Leith Creek near Laurinburg, North Carolina. For the original data set and seven filtered data sets, filtering induced changes in elevation, area, and hydraulic radius were determined for 10 water depths at 23 cross sections. Water surface elevations resulting from HEC‐RAS (Hydrologic Engineering Center‐River Analysis System) models for each data set were then compared. A hydraulic model sensitivity analysis was also conducted to compare filtering error to error introduced by variation in flow rates and roughness values. Finally, automated floodplain delineation was performed for each filter level based on the computed hydraulic model results and the filtered LIDAR elevations. Data filtering results indicate that significant time savings are achieved throughout the modeling process and that filtering to four degrees can be performed without compromising cross‐sectional geometry, hydraulic model results, or floodplain delineation results.     

A STRIP MODEL APPROACH TO PARAMETERIZE A COUPLED GREEN‐AMPT KINEMATIC WAVE MODEL1

ABSTRACT: Infiltration processes at the plot scale are often described and modeled using a single effective hydraulic conductivity (Kg) value. This can lead to errors in runoff and erosion prediction. An integrated field measurement and modeling study was conducted to evaluate: (1) the relationship among rainfall intensity, spatially variable soil and vegetation characteristics, and infiltration processes; and (2) how this relationship could be modeled using Green and Ampt and a spatially distributed hydrologic model. Experiments were conducted using a newly developed variable intensity rainfall simulator on 2 m by 6 m plots in a rangeland watershed in southeastern Arizona. Rainfall application rates varied between 50 and 200 mm/hr. Results of the rainfall simulator experiments showed that the observed hydrologic response changed with changes in rainfall intensity and that the response varied with antecedent moisture condition. A distributed process based hydrologic simulation model was used to model the plots at different levels of hydrologic complexity. The measurement and simulation model results show that the rainfall runoff relationship cannot be accurately described or modeled using a single Kg value at the plot scale. Multi‐plane model configurations with infiltration parameters based on soil and plot characteristics resulted in a significant improvement over single‐plane configurations.     

SOLUTE TRANSPORT IN THREE‐DIMENSIONAL SATURATED POROUS MEDIA HAVING SELF‐SIMILAR HYDRAULIC CONDUCTIVITY DISTRIBUTION1

ABSTRACT: Customarily, it has been assumed that hydraulic conductivity is a stationary, homogeneous stochastic process with a finite variance for stochastic analysis of solute transport in the subsurface. That the distribution of hydraulic conductivity may have a fractal behavior with long range correlations was suggested from field data analyses. This motivates us to further investigate how the fractal behavior of permeability distribution impacts solute transport in porous media. This study provides longitudinal and transverse macrodispersivity coefficients and the variance of the solute concentration. Longitudinal and transverse macrodispersivity coefficients are found to depend strongly on the fractal dimension (D) of logarithmic hydraulic conductivity (logK). The longitudinal and transverse macrodispersivity coefficients are the highest when D = 1, and the values decrease monotonically to zero at D = 2. Both coefficients correspond to the characteristic length scale of the logK distribution, thus are scale dependent parameters. The ratio of the transverse to the longitudinal macrodispersivity coefficient is on the order of 10^‐1 to 10^‐4. Concentration variance also decreases with the fractal dimension of logK. There is no spatial spreading of solute for D = 2, and the concentration variance reaches zero for this case.