Dynamic management zones for irrigation scheduling

Irrigation scheduling decision-support tools can improve water use efficiency by matching irrigation recommendations to prevailing soil and crop conditions within a season. Yet, little research is available on how to support real-time precision irrigation that varies within-season in both time and space. We investigate the integration of remotely sensed NDVI time-series, soil moisture sensor measurements, and root zone simulation forecasts for in-season delineation of dynamic management zones (MZ) and for a variable rate irrigation scheduling in order to improve irrigation scheduling and crop performance. Delineation of MZ was conducted in a 5.8-ha maize field during 2018 using Sentinel-2 NDVI time-series and an unsupervised classification. The number and spatial extent of MZs changed through the growing season. A network of soil moisture sensors was used to interpret spatiotemporal changes of the NDVI. Soil water content was a significant contributor to changes in crop vigor across MZs through the growing season. Real-time cluster validity function analysis provided in-season evaluation of the MZ design. For example, the total within-MZ daily soil moisture relative variance decreased from 85% (early vegetative stages) to below 25% (late reproductive stages). Finally, using the Hydrus-1D model, a workflow for in-season optimization of irrigation scheduling and water delivery management was tested. Data simulations indicated that crop transpiration could be optimized while reducing water applications between 11 and 28.5% across the dynamic MZs. The proposed integration of spatiotemporal crop and soil moisture data can be used to support management decisions to effectively control outputs of crop × environment × management interactions.Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the U.S. Department of Agriculture. This study was supported by the European Commission Horizon 2020 Programme for Research and Innovation (H2020) in the context of the Marie Sklodowska-Curie Research and Innovation Staff Exchange (RISE) action (ACCWA project, grant agreement no.: 823965). This study was also funded by the project ‘Low Input Sustainable Agriculture (LISA)’ under the Operational program FEDER for Catalonia 2014‐2020 RIS3CAT (http://www.lisaproject.cat/introduction/).Peer ReviewedPostprint (author's final draft

Reproducible Research in Vadose Zone Sciences

A significant portion of present-day soil and Earth science research is computational, involving complex data analysis pipelines, advanced mathematical and statistical models, and sophisticated computer codes. Opportunities for scientific progress are greatly diminished if reproducing and building on published research is difficult or impossible due to the complexity of these computational systems. Vadose Zone Journal (VZJ) is launching a Reproducible Research (RR) program in which code and data underlying a research article will be published alongside the article, thereby enabling readers to analyze data in a manner similar to that presented in the article and build on results in future research and applications. In this article, we discuss reproducible research, its background and use across other disciplines, its value to the scientific community, and its implementation in VZJ

Stochastic particle packing with specified granulometry and porosity

This work presents a technique for particle size generation and placement in arbitrary closed domains. Its main application is the simulation of granular media described by disks. Particle size generation is based on the statistical analysis of granulometric curves which are used as empirical cumulative distribution functions to sample from mixtures of uniform distributions. The desired porosity is attained by selecting a certain number of particles, and their placement is performed by a stochastic point process. We present an application analyzing different types of sand and clay, where we model the grain size with the gamma, lognormal, Weibull and hyperbolic distributions. The parameters from the resulting best fit are used to generate samples from the theoretical distribution, which are used for filling a finite-size area with non-overlapping disks deployed by a Simple Sequential Inhibition stochastic point process. Such filled areas are relevant as plausible inputs for assessing Discrete Element Method and similar techniques

Measured and simulated soil wetting patterns under porous clay pipe sub-surface irrigation

Sub-surface irrigation with porous clay pipe can be an efficient, water saving method of irrigation for many less developed arid and semi-arid regions. Maximizing the efficiency of clay pipe irrigation requires guidelines and criteria for system design and operation. In this study, experimental and simulated (with HYDRUS (2D/3D)) soil wetting patterns were investigated for sub-surface pipe systems operating at different water pressures. Predictions of the soil water content made with HYDRUS were found to be in good agreement (R2=0.98) with the observed data. Additional simulations with HYDRUS were used to study the effects of various design parameters on soil wetting. Increasing the system pressure increased the size of the wetted zone. The installation depth affects the recommended lateral spacing as well as the amount of evaporative water loss. For a given water application, the potential rate of surface evaporation affected the shape of the wetted region only minimally. Soil texture, due to its connection to soil hydraulic conductivity and water retention, has a larger impact on the wetting geometry. In general, greater horizontal spreading occurs in fine texture soils, or in the case of layered soils, in the finer textured layers.Porous clay pipe Sub-surface irrigation Micro-irrigation Soil wetting Hydraulic conductivity HYDRUS

Calibration of capacitance probe sensors in a saline silty clay soil

Capacitance probe sensors are a popular electromagnetic method of measuring soil water content. However, there is concern about the influence of soil salinity on the sensor readings. In this study capacitance sensors are calibrated for a saline silty clay soil. An electric circuit model is used to relate the sensor's resonant frequency F to the permittivity () of the soil. The circuit model is able to account for the effect of dielectric losses on the resonant frequency. Dielectric mixing models and empirical models are used to relate the permittivity to the soil water content (). The results show that the electric circuit model does not fit the F¿() data if the calibrated bulk electrical conductivity (EC) model is used. The dielectric losses are overestimated. Increasing the exponent c in the tortuosity factor of the bulk EC model and thereby lowering the bulk EC and the dielectric losses improves the performance of the model. Measured and calculated volumetric water contents compare reasonably well (R2 = 0.884). However, only 73 out of 88 data points can be described. The rejected points are invariably at high water contents where the high dielectric losses result in the sensor frequency being insensitive to ()

Analytical solutions of the one-dimensional advection–dispersion solute transport equation subject to time-dependent boundary conditions

Analytical solutions of the advection–dispersion solute transport equation remain useful for a large number of applications in science and engineering. In this paper we extend the Duhamel theorem, originally established for diffusion type problems, to the case of advective–dispersive transport subject to transient (time-dependent) boundary conditions. Generalized analytical formulas are established which relate the exact solutions to corresponding time-independent auxiliary solutions. Explicit analytical expressions were developed for the instantaneous pulse problem formulated from the generalized Dirac delta function for situations with first-type or third-type inlet boundary conditions of both finite and semi-infinite domains. The developed generalized equations were evaluated computationally against other specific solutions available from the literature. Results showed the consistency of our expressions

Changes in spatial and temporal variability of SAR affected by shallow groundwater management of an irrigated field, California

In the irrigated western U.S. disposal of drainage water has become a significant economic and environmental liability. Development of irrigation water management practices that reduce drainage water volumes is essential. One strategy combines restricted drainage outflow (by plugging the drains) with deficit irrigation to maximize shallow groundwater consumption by crops, thus reducing drainage that needs disposal. This approach is not without potential pitfalls; upward movement of groundwater in response to crop water uptake may increase salt and sodium concentrations in the root zone. The purposes for this study were: to observe changes in the spatial and temporal distributions of SAR (sodium adsorption ratio) and salt in a field managed to minimize drainage discharge; to determine if in situ drainage reduction strategy affects SAR distribution in the soil profile; and to identify soil or management factors that can help explain field wide variability. We measured SAR, soil salinity (EC1:1) and soil texture over 3 years in a 60-ha irrigated field on the west side of the San Joaquin Valley, California. At the time we started our measurements, the field was beginning to be managed according to a shallow groundwater/drainage reduction strategy. Soil salinity and SAR were found to be highly correlated in the field. The observed spatial and temporal variability in SAR was largely a product of soil textural variations within the field and their associated variations in apparent leaching fraction. During the 3-year study period, the percentage of the field in which the lower profile (90-180cm) depth averaged SAR was above 10, increased from 20 to 40%. Since salinity was increasing concomitantly with SAR, and because the soil contained gypsum, sodium hazard was not expected to become a limiting factor for long term shallow groundwater management by drain control. It is anticipated that the technology will be viable for future seasons.Drainage control Shallow groundwater management Sodium

A soil moisture accounting-procedure with a Richards' equation-based soil texture-dependent parameterization

Given a time-series of potential evapotranspiration and rainfall data, there are at least two approaches for estimating vertical percolation rates. One approach involves solving Richards' equation (RE) with a plant uptake model. An alternative approach involves applying a simple soil moisture accounting procedure (SMAP) based on a set of conceptual stores and conditional statements. It is often desirable to parameterize distributed vertical percolation models using regional soil texture maps. This can be achieved using pedotransfer functions when applying RE. However, robust soil texture based parameterizations for more simple SMAPs have not previously been available. This article presents a new SMAP designed to emulate the response of a one-dimensional homogenous RE model. Model parameters for 231 different soil textures are obtained by calibrating the SMAP model to 20 year time-series from equivalent RE model simulations. The results are then validated by comparing to an additional 13 years of simulated RE model data. The resulting work provides a new simple two parameter (% sand and % silt) SMAP, which provides consistent vertical percolation data as compared to RE based models. Results from the 231 numerical simulations are also found to be qualitatively consistent with intuitive ideas concerning soil texture and soil moisture dynamics. Vertical percolation rates are found to be highest in sandy soils. Sandy soils are found to provide less water for evapotranspiration. Surface runoff is found to be more important in soils with high clay content

Calibration of capacitance probe sensors using Electric Circuit Theory

Capacitance probe sensors are an attractive electromagnetic technique for estimating soil water content. There is concern, however, about the influence of soil salinity and soil temperature on the sensors. We present an electric circuit model that relates the sensor frequency to the permittivity of the medium and that is able to correct for dielectric losses due to ionic conductivity and relaxation. The circuit inductance L is optimized using sensor readings in a modified setup where ceramic capacitors replace the sensor's capacitance plates. The three other parameters in the model are optimized using sensor readings in a range of nonconductive media with different permittivities. The geometric factor for the plastic access tube gp is higher than the geometric factor for the medium gm, indicating that most of the electromagnetic field does not go beyond the access tube. The effect of ionic conductivity on the sensor readings is assessed by mixing salts in three of the media. The influence is profound. The sensor frequency decreases with increasing conductivity. The effect is most pronounced for the medium with the lowest permittivity. The circuit model is able to correct for the conductivity effect on the sensors. However, as the dielectric losses increase, the frequency becomes relatively insensitive to permittivity and small inaccuracies in the measured frequency or in the sensor constants result in large errors in the calculated permittivity. Calibration of the capacitance sensors can be simplified by fixing two of the constants and calculating the other two using sensor readings in air and water