A Comparative Analysis of Root Growth Modules in HYDRUS for SWC of Rice under Deficit Drip Irrigation

Root distribution during rice cultivation is a governing factor that considerably affects soil water content (SWC) and root water uptake (RWU). In this study, the effects of activating root growth (using growth function) and assigning a constant average root depth (no growth during simulation) on SWC and RWU for rice cultivation under four deficit drip irrigation treatments (T90, T80, T70, and T60) were compared in the HYDRUS-2D/3D model version 3.03. A secondary objective was to investigate the effect of applied deficit irrigation treatments on grain yield, irrigation water use efficiency (IWUE), and growth traits of rice. The simulated DI system was designed to reflect a representative field experiment implemented in El-Fayoum Governorate, Egypt, during two successive seasons during 2017 and 2018. The deficit treatments (T90, T80, T70, and T60) used in the current study represent scenarios at which the first irrigation event was applied when the pre-irrigation average SWC within the upper 60 cm of soil depth was equal to 90%, 80%, 70%, and 60% of plant-available water, respectively. Simulation results showed that as water deficiency increased, SWC in the simulation domain decreased, and thereby, RWU decreased. The average SWC within the root zone during rice-growing season under different deficit treatments was slightly higher when activating root growth function than when considering constant average root depth. Cumulative RWU fluxes for the case of no growth were slightly higher than for the case of root growth function for T90, T80, and T70 accounting for 1289.50, 1179.30, and 1073.10 cm2, respectively. Average SWC during the growth season (24 h after the first irrigation event, mid-season, and 24 h after the last irrigation event) between the two cases of root growth was strongly correlated for T90, T80, T70, and T60, where r2 equaled 0.918, 0.902, 0.892, and 0.876, respectively. ANOVA test showed that there was no significant difference for SWC between treatments for the case of assigning root growth function while the difference in SWC among treatments was significant for the case of the constant average root depth, where p-values equaled 0.0893 and 0.0433, respectively. Experimental results showed that as water deficiency decreased, IWUE increased. IWUE equaled 1.65, 1.58, 1.31, and 1.21 kg m−3 for T90, T80, T70, and T60, respectively. Moreover, higher grain yield and growth traits of rice (plant height, tillers number plant−1, panicles length, panicle weight, and grain number panicles−1) were obtained corresponding to T90 as compared with other treatments. Activating the root growth module in HYDRUS simulations can lead to more precise simulation results for specific dates within different growth stages. Therefore, the root growth module is a powerful tool for accurately investigating the change in SWC during simulation. Users of older versions of HYDRUS-2D/3D (version 2.05 and earlier) should consider the limitations of these versions for irrigation scheduling.

Exploring Substrate Water Capture in Common Greenhouse Substrates through Preconditioning and Irrigation Pulsing Techniques

Particles in a substrate create a network of pore pathways for water to move through, with size and shape determining the efficacy of these channels. Reduced particle size diversity can lead to increased leachate, poor substrate hydration, and an inefficient irrigation practice. This research examined the hydration characteristics of three greenhouse substrate components at three preconditioned initial moisture contents using subirrigation under five different irrigation durations and three water depths (2 mm, 20 mm, and 35 mm). Sphagnum peatmoss, coconut coir, and aged pine bark were tested at 67%, 50%, and 33% initial moisture (by weight). The objectives were to determine the impact of varying irrigation event durations (5, 10, 20, 30, 60 min) over a 60-min period, and the further influence of water depth and initial moisture, on the water capture abilities of peat, coir, and pine bark. The number of irrigation events depended on the irrigation event time of that experimental unit divided by the total time of 60 min, varying from 12, 6, 3, 2, and 1 event. Hydration efficiency was influenced by initial moisture content (IMC), water depth, pulsing duration, and inherent substrate characteristics (hydrophobicity/hydrophilicity). Initial MC had the largest impact on peat, regardless of water level or irrigation duration. Lower IMCs increased the hydrophobic response of peat, further reducing the amount of water the substrate was able to absorb. Pine bark had a 5–10% decrease in initial hydration between 67%, 50%, and 33% IMC, while coir’s hydrophilic nature reduced any IMC affects. At 50% IMC or less, coir had the highest volumetric water content (VWC) across all substrates, pulsing durations, and water depths. Water depth was found to increase initial hydration and final hydration 6–8% across all substrates. These three materials had altered and varied water capture responses depending on the combination of treatments employed. This work demonstrated the effects of intensity and exposure on substrates and the need for more integrated research for improving water use efficiency on container crops.

Using short-term ensemble weather forecast to evaluate outcomes of irrigation

<p>Irrigation water is an expensive and limited resource. Previous studies show that irrigation scheduling can boost efficiency by 20-60%, while improving water productivity by at least 10%. In practice, scheduling decisions are often needed several days prior to an irrigation event, so a key aspect of irrigation scheduling is the accurate prediction of crop water use and soil water status ahead of time. This prediction relies on several key inputs such as soil water, weather and crop conditions. Since each input can be subject to its own uncertainty, it is important to understand how these uncertainties impact soil water prediction and subsequent irrigation scheduling decisions.</p><p>This study aims to evaluate the outcomes of alternative irrigation scheduling decisions under uncertainty, with a focus on the uncertainties arising from short-term weather forecast. To achieve this, we performed a model-based study to simulate crop root-zone soil water content, in which we comprehensively explored different combinations of ensemble short-term rainfall forecast and alternative decisions of irrigation scheduling. This modelling produced an ensemble of soil water contents to enable quantification of risks of over- and under-irrigation; these ensemble estimates were summarized to inform optimal timing of next irrigation event to minimize both the risks of stressing crop and wasting water. With inclusion of other sources of uncertainty (e.g. soil water observation, crop factor), this approach shows good potential to be extended to a comprehensive framework to support practical irrigation decision-making for farmers.</p>

Vertical mobility and cotton tolerance to trifludimoxazin, a new protoporphyrinogen oxidase-inhibiting herbicide, in three West Texas soils

Trifludimoxazin, a new protoporphyrinogen oxidase–inhibiting herbicide, is being evaluated for possible use as a soil-residual active herbicide treatment in cotton for control of small-seeded annual broadleaf weeds. Laboratory and greenhouse studies were conducted to compare vertical mobility and cotton tolerance of trifludimoxazin to flumioxazin and saflufenacil, which are two currently registered protoporphyrinogen oxidase–inhibiting herbicides for use in cotton, in three West Texas soils. Vertical soil mobility of trifludimoxazin was similar to flumioxazin in Acuff loam and Olton loam soils, but was more mobile than flumioxazin in the Amarillo loamy sand soil. The depth of trifludimoxazin movement after a 2.5-cm irrigation event ranged from 2.5 to 5.0 cm in all soils, which would not allow for crop selectivity based on herbicide placement, because ideal cotton seeding depth is from 0.6 to 2.54 cm deep. Greenhouse studies indicated that PRE treatments were more injurious than the 14 d preplant treatment when summarized across soils for the three herbicides (43% and 14% injury, respectively). No differences in visual cotton response or dry weight was observed after trifludimoxazin preplant as compared with the nontreated control within each of the three West Texas soils and was similar to the flumioxazin preplant across soils. On the basis of these results, a use pattern for trifludimoxazin in cotton may be established with the use of a more than 14-d preplant restriction before cotton planting.

Accounting for the Three-Dimensional Distribution of Escherichia coli Concentrations in Pond Water in Simulations of the Microbial Quality of Water Withdrawn for Irrigation

Evaluating the microbial quality of irrigation water is essential for the prevention of foodborne illnesses. Generic Escherichia coli (E. coli) is used as an indicator organism to estimate the microbial quality of irrigation water. Monitoring E. coli concentrations in irrigation water sources is commonly performed using water samples taken from a single depth. Vertical gradients of E. coli concentrations are typically not measured or are ignored; however, E. coli concentrations in water bodies can be expected to have horizontal and vertical gradients. The objective of this work was to research 3D distributions of E. coli concentrations in an irrigation pond in Maryland and to estimate the dynamics of E. coli concentrations at the water intake during the irrigation event using hydrodynamic modeling in silico. The study pond is about 22 m wide and 200 m long, with an average depth of 1.5 m. Three transects sampled at 50-cm depth intervals, along with intensive nearshore sampling, were used to develop the initial concentration distribution for the application of the environmental fluid dynamic code (EFDC) model. An eight-hour irrigation event was simulated using on-site data on the wind speed and direction. Substantial vertical and horizontal variations in E. coli concentrations translated into temporally varying concentrations at the intake. Additional simulations showed that the E. coli concentrations at the intake reflect the 3D distribution of E. coli in the limited pond section close to the intake. The 3D sampling revealed E. coli concentration hot spots at different depths across the pond. Measured and simulated 3D E. coli concentrations provide improved insights into the expected microbial water quality of irrigation water compared with 1D or 2D representations of the spatial variability of the indicator concentration.

Detection of irrigation events on maize plots using sentinel-1 soil moisture products

<p>An accurate knowledge of irrigation timing and rate is essential to compute the water balance of irrigated plots. However, at the plot scale irrigation is a data essentially known by the irrigator. These data do not go up to higher management scales, thus limiting both the management of water resources on a regional scale and the development of irrigation decision support tools at the farm scale. The study focuses on 6 experimental plots in the south-west of France. The new method consists in assessing surface soil moisture (SSM) change between observations and a water balance model. The approach was tested using both in situ measurements and surface soil moisture (SSM) maps derived from Sentinel-1 radar data. The score is obtained by assessing if the irrigation event is detected within +/- three days. The use of in situ SSM showed that: (1) the best revisit time between two SSM observations is 3 days; short gaps is subject to uncertainties while longer gap miss possible SSM variations; (2) in general, higher rates (>20mm) of irrigation are well identified while it is very difficult to identify irrigation event when it is raining or when irrigation rates are small (<10mm). When using the SSM microwave product, the performances are degraded but are still acceptable given the discontinuity of irrigation events: 34% of absolute error and a bias of 5% for the whole season. Although high vegetation cover degrades the SSM absolute estimates, the dynamic appeared to be in accordance with in-situ measurements.</p>

Proximal remote sensing to quantify plot-scale overland flow connectivity

<p>Irrigation of crops and grazed pastures can lead to harmful losses of nutrients via overland flow across the edge of the field. While good irrigation design can assist with avoiding overland flow, soil surface conditions can change rapidly and lead to surface flow even under well-designed irrigation systems. Therefore, real-time methods to detect emerging flow conditions, early enough to prevent substantial flow from the field during irrigation, is a potential mitigation option. But these methods require a prediction of the initiation of overland flow conditions in order to make the connection with real-time observations.</p><p>On a naturally-rough agricultural soil, triggering of overland flow is primarily related to the process of gradual filling of small (~50 mm across) depressions. As depressions fill, hydraulic connections are established with their neighbours and this eventually leads to sufficient connectivity that overland flow is initiated. The initiation of overland flow generally occurs at a critical value of connectivity (C<sub>OF</sub>); the proportion of the soil surface that is connected via a water-filled pathway to an exit point of the field. As water ponding in, and flowing through, local depressions increases, the C<sub>OF</sub> of the field increases and this leads to flow across the field boundaries. Quantifying the development of C<sub>OF</sub> during an irrigation event, therefore, is key to predicting the initiation of overland flow.</p><p>We propose a method to continuously monitor the development of C<sub>OF</sub> during an irrigation event that requires two elements. The first is a new proximal sensing technique, which exploits acoustic technology to continuously monitor A<sub>sw</sub>, the proportion of the soil surface covered in water. The acoustic method comprises directional acoustic transmitter and receiver arrays. The directionality of the arrays provides a well-defined footprint area on the ground beneath the instrument. The A<sub>sw</sub> can be reliably estimated from changes in the amplitude of reflected sound waves. The second element is a ponding and redistribution model which simulates the flow of water over a rough soil surface and assists by converting A<sub>sw</sub> into C<sub>OF</sub>.</p><p>Our preliminary results show that this real-time method of monitoring C<sub>OF</sub> has a considerable scope in a variety of environments where prediction of overland flow initiation is desirable.</p>

Garden irrigation as household end-use in the presence of supplementary groundwater supply

Garden irrigation is a significant and variable household water end‑use, while groundwater abstraction may be a notable supplementary water source available in some serviced residential areas. Residential groundwater is abstracted by means of garden boreholes or well points and – in the study area – abstracted groundwater is typically used for garden irrigation. The volume irrigated per event is a function of event duration, frequency of application and flow rate, which in turn are dependent on numerous factors that vary by source – including water availability, pressure and price. The temperature variation of groundwater abstraction pipes at residential properties was recorded and analysed as part of this study in order to estimate values for three model inputs, namely, pumping event duration, irrigation frequency, and flow rate. This research incorporates a basic end‑use model for garden irrigation, with inputs derived from the case study in Cape Town, South Africa. The model was subsequently used to stochastically evaluate garden irrigation. Over an 11-d period, 68 garden irrigation events were identified in the sample group of 10 residential properties. The average garden irrigation event duration was 2 h 16 min and the average daily garden irrigation event volume was 1.39 m3.

Evaluation of Root Water Uptake and Urea Fertigation Distribution under Subsurface Drip Irrigation

Shallow groundwater contamination by nitrate is frequent in agricultural lands in Egypt because of the use of urea fertilizers. The urea transformation process in the vadose zone was simulated using a HYDRUS-2D model, Software package for simulations of 2D movement of water, heat, and multiple solutes in variably saturated media, for subsurface drip irrigation. The root water and nutrient uptake were assessed for three soil types (sandy loam, loam, and silty loam) with three emitter discharge levels (1.0 L h−1, 1.50 L h−1, and 2.0 L h−1), for a comparison of three fertigation strategies (A) at the beginning, (B) at the end, and (C) at the middle of the irrigation cycle. The extension of the wetted area mainly depends on soil hydraulic conductivity. The high emitter discharge with a short irrigation time is suitable for shallow-rooted crops. The cumulative flux was highest for silty loam soil and the lowest was for the sandy loam soil (1891, and 1824 cm3) for the 2 L h−1 emitter discharge within the 35 days simulation. The cumulative drainage significantly differs among soil types with little effect of emitter discharge. It recorded 1213, 295, 11.9 cm3 for sandy loam, loam, silty loam, respectively. Urea transformation is controlled by hydrolysis and nitrification as well as the adsorption coefficient of ammonium. Nitrate distribution is mainly governed by soil type rather than the emitter discharge where the sandy loam soil is more highly susceptible to nitrate leaching than to silty loam. Nitrate concentration has recorded the minimum possible level when applying the urea fertilizer at the beginning of the irrigation event for sandy loam and loam soil while for the silty loam soil, urea application at the middle of the irrigation event is more effective. Urea application at the end of the irrigation event gives the highest accumulated leached nitrate concentration below the root zone and should be avoided (the worst strategy).