Sensitivity Analysis of Soil Hydraulic Properties on Subsurface Water Flow in Furrows

Knowledge of the sensitivity of various soil hydraulic properties is beneficial for model development and application purposes. It can lead to better estimated values, better understanding, and thus reduced uncertainty. In the present study, an extensive sensitivity analysis was performed to investigate the effects that various soil hydraulic properties have on subsurface water flow below furrows during two successive irrigation events to see which irrigation event was more sensitive and to analyze the effect of spatial variations in the initial soil water contents within the soil profile. Testing the sensitivity of the various soil hydraulic parameters in the van Genuchten-Mualem expression was carried out using the HYDRUS-2D model for two irrigation events 10?days apart. Results showed that the first irrigation event was clearly more sensitive than the second one. The latter event was mainly associated with the nonuniformity of the initial soil water contents within the soil profile. Pressure heads in the soil profile were more sensitive than cumulative outlet fluxes and soil water contents. Sensitivity analysis results for pressure heads, cumulative fluxes, and water contents indicated that in every case the most sensitive parameter was the hydraulic property shape factor (n) followed by the saturated water content (θs), the saturated hydraulic conductivity (Ks), the residual water content (θr), and the shape factor in the soil water retention curve (α), with the pore-connectivity parameter (l) the least sensitive parameter during both irrigation events. Pressure head sensitivity analysis for all parameters studied showed that the least sensitivity was linked with the wetting front as it gradually moved deeper with time, and the highest sensitivity was observed in those regions where the initial soil water contents were lower. Similarly, for water contents, higher sensitivity occurred in the drier regions during the first irrigation event and near the moisture front in the second irrigation event. Both pressure heads and water contents showed some sensitivity near the soil surface during both irrigation events, suggesting the importance of evaporation from the soil surface.     

Comparison of Water Distribution Uniformities between Increased-Discharge and Continuous-Flow Irrigations in Blocked-End Furrows

A comparative analysis of the distribution uniformities of infiltrated water depth in blocked end furrows between three irrigations with increased-discharge (IDI) and three irrigations with constant flow rate (CFI) is presented. The goal is to evaluate IDI irrigation contrasted to CFI irrigation, which is the most commonly used in underdeveloped countries. The average distribution uniformities of IDI irrigation is 9% higher than that of CFI irrigation. Therefore, IDI irrigation is a viable alternative of efficient irrigation in blocked end furrows. Field assays were performed in 290?m?long×0.75?m?wide, 0.6% slope furrows in clay loam.     

Modeling Two-Dimensional Infiltration from Irrigation Furrows

Numerical simulation of the two-dimensional (2D) infiltration process during furrow irrigation requires considerable computational effort, which can be reduced by analytical modeling. This paper deals with the further development of the semianalytical infiltration model FURINF (furrow infiltration). Considering the varying impact of gravity and furrow geometry, the new approach models the impact of furrow geometry on infiltration progress using a transient geometric shape factor as a function of infiltration time and furrow geometry. FURINF portrays 2D infiltration from the wetted furrow perimeter by a series of one-dimensional (1D) infiltration computations that are performed in this paper on the basis of an analytical as well as a numerical solution of the 1D Richards equation. Comparing the FURINF results provided by the analytical and numerical 1D infiltration model confirmed the adequacy and reliability of the robust and simple analytical approach, which only requires soil parameters provided by rather simple measurements. The results and performances of the analytical FURINF model (FURINF-A) are compared within the frame of a sensitivity and error analysis with the outcome of the numerical subsurface flow model HYDRUS-2D considering three different soils.     

Physically Based Coupled Model for Simulating 1D Surface–2D Subsurface Flow and Plant Water Uptake in Irrigation Furrows. II: Model Test and Evaluation

A physically based seasonal Furrow Irrigation Model was developed, which comprises three modules: The one-dimensional surface flow, the two-dimensional subsurface flow, and a crop model. The modeling principles of these modules, their simultaneous coupling, and the solution strategies were described in a companion paper (W?hling and Schmitz 2007). In the current contribution, we present the model testing with experimental data from five real-scale laboratory experiments [Hubert-Engels Laboratory (HEL)], two field experiments in Kharagpur, Eastern India (KGP), one literature data set [Flowell-wheel (FW)], and data from three irrigations during a corn growing season in Montpellier, Southern France [Lavalette experiments (LAT)]. The simulated irrigation advance times match well with the observations of the HEL, FW, and KGP experiments, which is confirmed by coefficients of determination R2 ≥ 0.99 and coefficients of efficiency Ce ≥ 0.7. Predicted recession times also match with the observations of the HEL runs, however, the values of R2 ≥ 0.9 and Ce ≥ 0.6 are lower for predicted recession times as compared to predicted advance times. In contrast to the other experiments in the study, advance times are underpredicted for the experiments in France. The established soil hydraulic parameters for this site lead to an underestimation of the actual initial infiltration capability of the soil. In the long-term simulation, however, the overall change in soil moisture storage is correctly predicted by the model and the calculated yield of 12.8?t?ha?1 is in very good agreement with the observations (12.7?t?ha?1). We evaluated the sensitivity of the input parameters with regards to predicted advance time and runoff in both a 26.4?m long furrow and a long 360?m long furrow. The analysis revealed that calculated runoff is four to five times more sensitive to the inlet flow rate than to infiltration parameters. Furrow geometry parameters are most sensitive to calculated advance times in the short furrow with low infiltration opportunity time, whereas the inflow rate and infiltration parameters are more sensitive to calculated advance times in the long furrow with larger infiltration opportunity time.     

Comparison of Crop Contamination by Microorganisms during Subsurface Drip and Furrow Irrigation

This study was conducted to compare subsurface drip irrigation (SDI) with furrow irrigation (FI) in crop contamination with microbial-contaminated water irrigation. Escherichia coli, Clostridium perfringens, and coliphage PRD-1 were added to water used to irrigate cantaloupe, lettuce, and bell pepper. Samples of produce, surface, and subsurface (10?cm) soil for each irrigation system were collected on Days 1, 3, 5, 7, 10, and 14 after the application of the study microorganisms. Overall, greater contamination of produce occurred in FI plots than in SDI plots. The microorganisms were detected on the surfaces of cantaloupe and lettuce, but were never recovered on the bell peppers. The greatest amount of contamination occurred with PRD-1 on cantaloupe. The study microorganisms survived longer in the subsurface soil than the soil surface. PRD-1 showed greater persistence than E. coli in soil, while C. perfringens experienced little inactivation during the experiment periods. This study showed that subsurface drip irrigation has great potential to reduce health risks when microbial-contaminated water is used for irrigation water.     

Fertigation in Furrows and Level Furrow Systems. I: Model Description and Numerical Tests

The simulation of fertigation in furrows and level furrow systems faces a number of problems resulting in relevant restrictions to its widespread application. In this paper, a simulation model is proposed that addresses some of these problems by: (1) implementing an infiltration model that adjusts to the variations in wetted perimeter; (2) using a friction model that adjusts to different flows and which uses an absolute roughness parameter; (3) adopting an equation for the estimation of the longitudinal diffusion coefficient; and (4) implementing a second-order TVD numerical scheme and specific treatments for the boundary conditions and the junctions. The properties of the proposed model were demonstrated using three numerical tests focusing on the numerical scheme and the treatments. The application of the model to the simulation of furrows and furrow systems is presented in a companion paper, in which the usefulness of the innovative aspects of the proposed model is demonstrated.     

Fertigation in Furrows and Level Furrow Systems. II: Field Experiments, Model Calibration, and Practical Applications

Furrow fertigation can be an interesting practice when compared to traditional overland fertilizer application. In the first paper of this series, a model for furrow fertigation was presented. The simulation model combined overland water flow (Saint-Venant equations), solute transport (advection-dispersion), and infiltration. Particular attention was paid to the treatment of junctions present in level furrow systems. In this paper, the proposed model is validated using five furrow fertigation evaluations differing in irrigation discharge, fertilizer application timing, and furrow geometry. Model parameters for infiltration and roughness were estimated using error minimization techniques. The error norm was based on observed and simulated values of advance time, flow depth, and fertilizer concentration. Model parameters could be adequately predicted from just one discharge experiment, although the use of more experiments resulted in decreased error. The validated model was applied to the simulation of a level furrow system from the literature. The model adequately reproduced irrigation advance and flow depth. Fertigation events differing in application timing were simulated to identify conditions leading to adequate fertilizer uniformity.     

Effects of Magnetized Water and Irrigation Water Salinity on Soil Moisture Distribution in Trickle Irrigation

Magnetized water is obtained by passing water through a strong permanent magnet installed in or on a feed pipeline. This study was performed at Gorgan Agricultural and Natural Resources Research Center, Gorgan province, Iran, to investigate soil moisture distribution under trickle irrigation. Two main treatments of magnetic and nonmagnetic water and three subtreatments of irrigation water salts, including well water as a control, 200-ppm calcium carbonate, and 400-ppm calcium carbonate were used. The experiment was laid out with a complete randomized block design with three replications. Soil moisture distribution around the emitters were measured 24?h after irrigation during the 3-month irrigation period. The results showed that the mean soil moisture contents at depths of 0–20, 20–40, and 40–60?cm below the emitter for the magnetized irrigation water treatment were more than the nonmagnetized irrigation water treatment, and the differences were significant at the 5% level. The irrigation with magnetic water as compared with the nonmagnetic water increased soil moisture up to 7.5%, and this increase was significant at the 1% level. The effect of irrigation water salinity on soil moisture was significant. The highest soil moisture content was from the 400-ppm calcium carbonate subtreatment. The use of magnetized water for irrigation is recommended to save irrigation water.     

Physically Based Coupled Model for Simulating 1D Surface–2D Subsurface Flow and Plant Water Uptake in Irrigation Furrows. I: Model Development

Physically based modeling of the interacting water flow during a furrow irrigation season can contribute to both a sustainable irrigation management and an improvement of the furrow irrigation efficiency. This paper presents a process based seasonal furrow irrigation model which describes the interacting one-dimensional surface–two-dimensional subsurface flow and crop growth during a whole growing period. The irrigation advance model presented in a previous study is extended to all hydraulic phases of an irrigation event. It is based on an analytical solution of the zero-inertia surface flow equations and is iteratively coupled with the two-dimensional subsurface flow model HYDRUS-2. A conceptual crop growth model calculates daily evaporation, transpiration and leaf area index. The crop model and HYDRUS-2 are coupled via its common boundaries, namely (1) by the flux across the soil-atmosphere interface; and (2) by the flux from the root zone, which is associated with the plant water uptake. We assume the water stress is the only environmental factor reducing crop development and hence final crop yield. The model performance is evaluated with field experimental data in the companion paper, Part II: Model Test and Evaluation (W?hling and Mailhol 2007).     

New Strategy for Optimizing Water Application under Trickle Irrigation

The determination of water application parameters for creating an optimal soil moisture profile represents a complex nonlinear optimization problem which renders traditional optimization into a cumbersome procedure. For this reason, an alternative methodology is proposed which combines a numerical subsurface flow model and artificial neural networks (ANN) for solving the problem in two, fully separate steps. The first step employs the flow model for calculating a large number of wetting profiles (output), obtained from a systematic variation of both water application and initial soil moisture (input). The resulting matrix of corresponding input/output values is used for training the ANN. The second step, the application of the fully trained ANN, then provides the irrigation parameters which range from a specified initial soil moisture to a desired crop-specific soil moisture profile. In order to avoid substantial disadvantages associated with the common feedforward backpropagation approach, a self-organizing topological feature map is implemented to perform this task. After a comprehensive sensitivity analysis, the new methodology is applied to the outcome of an irrigation experiment. The convincing results recommend the new methodology as a positive contribution towards an improved irrigation efficiency.     

Application of Conditioner Solution by Subsurface Emitters for Stabilizing the Surrounding Soil

Poor uniformity of water application by subsurface drip irrigation has been examined and some explanations are suggested in this paper. Use of soil conditioners for soil structure stabilization around subsurface drip irrigation pipes was suggested by the authors and tested in the laboratory. The conditioners preserve the structure of existing aggregated and may effectively reduce soil clogging. A silt loam soil was uniformly packed in a 1×0.8×0.15?m box. Two holes were dilled in the box wall through which two emitters were inserted, one for applying solution of soil conditioner and one as a control. Stabilization was achieved by applying two types of polymer solutions differing by their molecular weights through an emitter buried in a silt loam soil. A measured water volume was injected through the emitters into the soil and, after 48?h following irrigation, the box was dismantled. Gravimetric soil moisture content and aggregate water stability were measured in vertical and horizontal distances from the emitter. The highest stabilizing effectiveness was obtained with a volume of 1.5?L polymer solution at 5?g/L concentration, which was applied to the soil at an initial moisture content of 13%. The volume of stabilized soil increased with the volume of applied solution, but the volume ratio of stabilized soil to applied solution decreased with the increase in solution volume. A polymer of relatively low molecular weight was found less effective since a large portion of the solution was consumed by fast penetration into soil aggregates without improving the soil structure. The proposed method offers a simple and easy means for preparing a stabilized soil envelope around subsurface drip irrigation pipes, which may improve the long-term performance and uniformity of the application of these systems. Yet for some of these aspects, further field evaluation is needed, since the results of the study are from a laboratory experiment limited to one soil only.     

Validation of a Predictive Form of Horton Infiltration for Simulating Furrow Irrigation

Due to spatially varying conditions the improvement of furrow irrigation efficiency should be sought not just for a limited number of furrows or for one specific irrigation event. A simplified predictive modeling approach of the averaged advance-infiltration process is proposed in this paper. Horton’s equation, derived from the asymptotic form of the Talsma-Parlange infiltration equation, allows us to use a predictive approach for the advance infiltration process by means of the exact solution of the Lewis and Milne water balance equation. The references to the works of White and Sully, for a surface point source, result in the use of parameters which characterize the hydraulic properties of the soil: Δθ (saturated water content minus initial water content); Ks (saturated conductivity); and λc (macroscopic capillary length). The physical meaning of parameters involved in the proposed modeling is attested using field experiments carried out in a loamy soil plot context. Assuming a same Δθ measured value before irrigation for the whole of a 30 furrow sample, the averaged values of λc and Ks obtained from calibration on the advance trajectory are comparable to those derived from local infiltration tests (disk permeameter and double ring methods). The applicability of the model is then extended to heavy clay soil where the parameters λc and Ks still agree with the values proposed in the literature. This paper can be considered as a contribution to the development of a tool for evaluating the impact of irrigation practices on the efficiency at the plot and cropping season scale.     

Estimating Soil Moisture Under Low Frequency Surface Irrigation Using Crop Water Stress Index

The present study investigated the relationship between the crop water stress index (CWSI) and soil moisture for surface irrigated cotton (Gossypium hirsutum, Delta Pine 90b) at Maricopa, Arizona during the 1998 season. The CWSI was linked to soil moisture through the water stress coefficient Ks that accounts for reduced crop evapotranspiration when there is a shortage of soil water. A stress recovery coefficient Krec was introduced to account for reduced crop evapotranspiration as the crop recovered from water stress after irrigation events. A soil water stress index (SWSI) was derived in terms of Ks and Krec. The SWSI compared reasonably well to the CWSI, but atmospheric stability correction for the CWSI did not improve comparisons. When the CWSI was substituted into the SWSI formulation, it gave good prediction of soil moisture depletion (fDEP; when to irrigate) and depth of root zone depletion (Dr; how much to irrigate). Disagreement was greatest for fDEP<0.6 because cotton is less sensitive to water stress in this range.     

Infiltration under Variable Ponding Depths of Water

Cumulative infiltration was computed as a function of time-varying ponded water depths using a Green and Ampt analysis. The input water depths were field-measured values from two irrigation events on Superstition sand, one from a basin and one from a border. For both types of irrigation, the computed cumulative infiltration at a given measuring station was nearly the same whether using a variable head input or a constant (average) head during the time of opportunity. As an example, at the first measurement station for the basin event, the ponded depth went from a 0 to 9 cm depth over the 2–12 min. from the time water was introduced into the basin; this was followed by a decrease to a depth of 4 cm at 60 min. The computed infiltration using the depth hydrograph was 14.3 cm compared to 14.1 cm when using an average depth. A smaller value of 13.7 cm is found using the appropriate time of opportunity with a field averaged depth and a considerably smaller value of 12.4 cm was found when a zero-depth boundary is considered. Basin and border uniformities were also computed based on variable and different constant depths and the results were found to be reasonably robust whether infiltration is computed using a variable or an appropriate constant ponded depth.     

Water Distribution in Laterals and Units of Subsurface Drip Irrigation. I: Simulation

A complete methodology to predict water distribution in laterals and units of subsurface drip irrigation (SDI) is proposed. Two computer programs have been developed for the hydraulic characterization of SDI; one for laterals and the other for units. Emitter discharge was considered to depend on hydraulic variability, emitter’s manufacture and wear variation, and soil pressure variation. A new procedure to solve the hydraulic calculation of SDI looped network has been established. Moreover, spatial distribution of soil variability was estimated by a geostatistical modeling software that is coupled with the computer programs. Thus the evaluation and performance of laterals and units of SDI can be addressed by changing input variables such us: length and diameters of laterals; coefficients of emitter’s discharge equation; coefficient of variation of emitter’s manufacture and wear; local losses at the emitter insertion; inlet pressure; and soil hydraulic properties and its spatial variability. Finally, the methodology has been applied to different scenarios, and some recommendations are outlined for the selection of emitter discharge and inlet pressures.     

Water Distribution in Laterals and Units of Subsurface Drip Irrigation. II: Field Evaluation

The performance of drip irrigation and subsurface drip irrigation (SDI) laterals has been compared. Two emitter models (one compensating and the other noncompensating) were assessed. Field tests were carried out with a pair of laterals working at the same inlet pressure. A procedure was developed that recorded head pressures at both lateral extremes and inlet flow during irrigation. Both models showed similar behavior and soil properties affected their discharge. On the other hand, the performance of a field SDI unit of compensating emitters was characterized by measuring pressures at different points and inlet flow. Finally, the distribution of water and soil pressure in the laterals and the unit were predicted and irrigation uniformity and soil pressure variability were also determined. Predictions agreed reasonably well with the experimental observations. Thus, the methodology proposed could be used to support the decision making for the design and management of SDI systems.     

Demand Forecasting for Irrigation Water Distribution Systems

One of the main problems in the management of large water supply and distribution systems is the forecasting of daily demand in order to schedule pumping effort and minimize costs. This paper examines methodologies for consumer demand modeling and prediction in a real-time environment for an on-demand irrigation water distribution system. Approaches based on linear multiple regression, univariate time series models (exponential smoothing and ARIMA models), and computational neural networks (CNNs) are developed to predict the total daily volume demand. A set of templates is then applied to the daily demand to produce the diurnal demand profile. The models are established using actual data from an irrigation water distribution system in southern Spain. The input variables used in various CNN and multiple regression models are (1) water demands from previous days; (2) climatic data from previous days (maximum temperature, minimum temperature, average temperature, precipitation, relative humidity, wind speed, and sunshine duration); (3) crop data (surfaces and crop coefficients); and (4) water demands and climatic and crop data. In CNN models, the training method used is a standard back-propagation variation known as extended-delta-bar-delta. Different neural architectures are compared whose learning is carried out by controlling several threshold determination coefficients. The nonlinear CNN model approach is shown to provide a better prediction of daily water demand than linear multiple regression and univariate time series analysis. The best results were obtained when water demand and maximum temperature variables from the two previous days were used as input data.     

Modeling Soil Water Uptake by Plants Using Nonlinear Dynamic Root Density Distribution Function

Water uptake by plants is one of the major components of water balance of the vadose zone that greatly influences the contaminant and moisture movement in variably saturated soils. In this study, a nonlinear macroscopic root water uptake model that includes the impact of soil moisture stress is developed. The model incorporates the spatial and temporal variation of root density in addition to the dynamic root depth considerations. The governing moisture flow equation coupled with the water extraction by plants term is solved numerically by an implicit finite-difference method. The simulation is performed for various physical scenarios subjected to different boundary conditions. The model is tested first without considering the water uptake and results are compared with observed data available in the literature for two cases. A nonlinear water uptake term is subsequently incorporated in the model which is then simulated for corn crop for constant root depth under various characteristic moisture availability environments. Results show that the water extraction rate is closely related to the soil moisture availability in addition to the root density. The plants are observed to extract moisture mainly from the upper root dense soil profile when water content is in an optimal range, otherwise, the peak of the uptake moves to other soil layers where the moisture is easily available. Finally, the model is applied to a corn field and simulated results are validated with field data. The simulated moisture content for 2 months of crop growing season shows a reasonably good agreement with the observed data.     

Considerations for the Design of Intercepting Drainage for Collecting Water from Seep Areas

Springs that appear at multiple sites on sloping lands and create problems of excess soil moisture and reduced crop yield require the implementation of a network of intercepting drains. The water removed by the intercepting drains also needs to be conducted to a collecting shaft or main drain, whereby it can be safely utilized or discharged back to a lower-lying position in the landscape. In this paper, we present a design method for establishing the position of the first row of interceptor drains and the number of successive rows of intercepting drains, as well as the distances between them. The first row of intercepting drains must be placed upstream of the upper limit of the wet area, through those points at which water-bearing material is found at 40–50?cm underground. The number of rows of necessary intercepting drains is determined from the ratio between the thickness of water-bearing material and the thickness of the filter+drain. For multiple springs that are concentrated on the surface of sloping lands, we propose the solution of a collecting chamber with a side drain and bottom filter.