scholarly journals Cotton Irrigation Scheduling Using a Crop Growth Model and FAO-56 Methods: Field and Simulation Studies

2017 ◽  
Vol 60 (6) ◽  
pp. 2023-2039 ◽  
Author(s):  
Kelly R. Thorp ◽  
Douglas J. Hunsaker ◽  
Kevin F. Bronson ◽  
Pedro Andrade-Sanchez ◽  
Edward M. Barnes
Keyword(s):  
Soil Moisture ◽  
Water Use ◽  
Root Zone ◽  
Crop Coefficient ◽  
Irrigation Scheduling ◽  
Crop Growth ◽  
Statistical Testing ◽  
Fine Tuning ◽  
Cotton Yield ◽  
Post Hoc

Abstract. Crop growth simulation models can address a variety of agricultural problems, but their use to directly assist in-season irrigation management decisions is less common. Confidence in model reliability can be increased if models are shown to provide improved in-season management recommendations, which are explicitly tested in the field. The objective of this study was to compare the CSM-CROPGRO-Cotton model (with recently updated ET routines) to a well-tested FAO-56 irrigation scheduling spreadsheet by (1) using both tools to schedule cotton irrigation during 2014 and 2015 in central Arizona and (2) conducting a post-hoc simulation study to further compare outputs from these tools. Two replications of each irrigation scheduling treatment and a water-stressed treatment were established on a 2.6 ha field. Irrigation schedules were developed on a weekly basis and administered via an overhead lateral-move sprinkler irrigation system. Neutron moisture meters were used weekly to estimate soil moisture status and crop water use, and destructive plant samples were routinely collected to estimate cotton leaf area index (LAI) and canopy weight. Cotton yield was estimated using two mechanical cotton pickers with differing capabilities: (1) a two-row picker that facilitated manual collection of yield samples from 32 m2 areas and (2) a four-row picker equipped with a sensor-based cotton yield monitoring system. In addition to statistical testing of field data via mixed models, the data were used for post-hoc reparameterization and fine-tuning of the irrigation scheduling tools. Post-hoc simulations were conducted to compare measured and simulated evapotranspiration, crop coefficients, root zone soil moisture depletion, cotton growth metrics, and yield for each irrigation treatment. While total seasonal irrigation amounts were similar among the two scheduling tools, the crop model recommended more water during anthesis and less during the early season, which led to higher cotton fiber yield in both seasons (p < 0.05). The tools calculated cumulative evapotranspiration similarly, with root mean squared errors (RMSEs) less than 13%; however, FAO-56 crop coefficient (Kc) plots demonstrated subtle differences in daily evapotranspiration calculations. Root zone soil moisture depletion was better calculated by CSM-CROPGRO-Cotton, perhaps due to its more complex soil profile simulation; however, RMSEs for depletion always exceeded 20% for both tools and reached 149% for the FAO-56 spreadsheet in 2014. CSM-CROPGRO-Cotton simulated cotton LAI, canopy weight, canopy height, and yield with RMSEs less than 21%, while the FAO-56 spreadsheet had no capability for such outputs. Through field verification and thorough post-hoc data analysis, the results demonstrated that the CSM-CROPGRO-Cotton model with updated FAO-56 ET routines could match or exceed the accuracy and capability of an FAO-56 spreadsheet tool for cotton water use calculations and irrigation scheduling. Keywords: Cottonseed, Crop coefficient, Decision support, Depletion, Evapotranspiration, Fiber, Management, Simulation, Soil moisture, Yield.

Field evaluation of a water use model for potatoes

1998 ◽  
Vol 78 (3) ◽  
pp. 441-448 ◽  
Author(s):  
C. F. Shaykewich ◽  
G. H. B. Ash ◽  
R. L. Raddatz ◽  
D. J. Tomasiewicz
Keyword(s):  
Water Use ◽  
Field Data ◽  
Root Zone ◽  
Growth Parameters ◽  
Solanum Tuberosum L ◽  
Ground Cover ◽  
Field Evaluation ◽  
Irrigation Scheduling ◽  
Crop Growth ◽  
Rooting Depth

A water use model for potatoes (Solanum tuberosum L.) was calibrated and tested. The model requires phenological relationships for estimating emergence, degree of crop cover and rooting depth. These weather-driven crop growth functions were previously calibrated using field data from 1994 and 1995. In this paper, the model was tested using field data from the 1996 growing season at two locations. The 1996 crop growth parameters were estimated fairly accurately. This contributed to reasonably accurate (average bias <3 mm, root mean square error <15 mm) root zone available soil water estimates by the model. Thus, the model could be used in irrigation scheduling. Key words: Evapotranspiration, rooting depth, ground cover

scholarly journals High-Resolution Spatiotemporal Water Use Mapping of Surface and Direct-Root-Zone Drip-Irrigated Grapevines Using UAS-Based Thermal and Multispectral Remote Sensing

2021 ◽  
Vol 13 (5) ◽  
pp. 954
Author(s):  
Abhilash K. Chandel ◽  
Lav R. Khot ◽  
Behnaz Molaei ◽  
R. Troy Peters ◽  
Claudio O. Stöckle ◽  
...  
Keyword(s):  
High Resolution ◽  
Water Use ◽  
Root Zone ◽  
Lateral Roots ◽  
Irrigation Treatment ◽  
Crop Coefficient ◽  
Spatiotemporal Resolution ◽  
Site Specific ◽  
Canopy Transpiration ◽  
Irrigation Treatments

Site-specific irrigation management for perennial crops such as grape requires water use assessments at high spatiotemporal resolution. In this study, small unmanned-aerial-system (UAS)-based imaging was used with a modified mapping evapotranspiration at high resolution with internalized calibration (METRIC) energy balance model to map water use (UASM-ET approach) of a commercial, surface, and direct-root-zone (DRZ) drip-irrigated vineyard. Four irrigation treatments, 100%, 80%, 60%, and 40%, of commercial rate (CR) were also applied, with the CR estimated using soil moisture data and a non-stressed average crop coefficient of 0.5. Fourteen campaigns were conducted in the 2018 and 2019 seasons to collect multispectral (ground sampling distance (GSD): 7 cm/pixel) and thermal imaging (GSD: 13 cm/pixel) data. Six of those campaigns were near Landsat 7/8 satellite overpass of the field site. Weather inputs were obtained from a nearby WSU-AgWeatherNet station (1 km). First, UASM-ET estimates were compared to those derived from soil water balance (SWB) and conventional Landsat-METRIC (LM) approaches. Overall, UASM-ET (2.70 ± 1.03 mm day−1 [mean ± std. dev.]) was higher than SWB-ET (1.80 ± 0.98 mm day−1). However, both estimates had a significant linear correlation (r = 0.64–0.81, p < 0.01). For the days of satellite overpass, UASM-ET was statistically similar to LM-ET, with mean absolute normalized ET departures (ETd,MAN) of 4.30% and a mean r of 0.83 (p < 0.01). The study also extracted spatial canopy transpiration (UASM-T) maps by segmenting the soil background from the UASM-ET, which had strong correlation with the estimates derived by the standard basal crop coefficient approach (Td,MAN = 14%, r = 0.95, p < 0.01). The UASM-T maps were then used to quantify water use differences in the DRZ-irrigated grapevines. Canopy transpiration (T) was statistically significant among the irrigation treatments and was highest for grapevines irrigated at 100% or 80% of the CR, followed by 60% and 40% of the CR (p < 0.01). Reference T fraction (TrF) curves established from the UASM-T maps showed a notable effect of irrigation treatment rates. The total water use of grapevines estimated using interpolated TrF curves was highest for treatments of 100% (425 and 320 mm for the 2018 and 2019 seasons, respectively), followed by 80% (420 and 317 mm), 60% (391 and 318 mm), and 40% (370 and 304 mm) of the CR. Such estimates were within 5% to 11% of the SWB-based water use calculations. The UASM-T-estimated water use was not the same as the actual amount of water applied in the two seasons, probably because DRZ-irrigated vines might have developed deeper or lateral roots to fulfill water requirements outside the irrigated soil volume. Overall, results highlight the usefulness of high-resolution imagery toward site-specific water use management of grapevines.

scholarly journals THE WATER RELATIONS AND IRRIGATION REQUIREMENTS OF SUGAR CANE (SACCHARUM OFFICINARUM): A REVIEW

2011 ◽  
Vol 47 (1) ◽  
pp. 1-25 ◽  
Author(s):  
M. K. V. CARR ◽  
J. W. KNOX
Keyword(s):  
Water Stress ◽  
Water Relations ◽  
Sugar Cane ◽  
Root Zone ◽  
Water Productivity ◽  
Crop Coefficient ◽  
Saccharum Officinarum ◽  
Irrigation Scheduling ◽  
Background Information ◽  
Technology Choice

SUMMARYThe results of research on the water relations and irrigation needs of sugar cane are collated and summarized in an attempt to link fundamental studies on crop physiology to irrigation practices. Background information on the centres of production of sugar cane is followed by reviews of (1) crop development, including roots; (2) plant water relations; (3) crop water requirements; (4) water productivity; (5) irrigation systems and (6) irrigation scheduling. The majority of the recent research published in the international literature has been conducted in Australia and southern Africa. Leaf/stem extension is a more sensitive indicator of the onset of water stress than stomatal conductance or photosynthesis. Possible mechanisms by which cultivars differ in their responses to drought have been described. Roots extend in depth at rates of 5–18 mm d−1 reaching maximum depths of > 4 m in ca. 300 d providing there are no physical restrictions. The Penman-Monteith equation and the USWB Class A pan both give good estimates of reference crop evapotranspiration (ETo). The corresponding values for the crop coefficient (Kc) are 0.4 (initial stage), 1.25 (peak season) and 0.75 (drying off phase). On an annual basis, the total water-use (ETc) is in the range 1100–1800 mm, with peak daily rates of 6–15 mm d−1. There is a linear relationship between cane/sucrose yields and actual evapotranspiration (ETc) over the season, with slopes of about 100 (cane) and 13 (sugar) kg (ha mm)−1 (but variable). Water stress during tillering need not result in a loss in yield because of compensatory growth on re-watering. Water can be withheld prior to harvest for periods of time up to the equivalent of twice the depth of available water in the root zone. As alternatives to traditional furrow irrigation, drag-line sprinklers and centre pivots have several advantages, such as allowing the application of small quantities of water at frequent intervals. Drip irrigation should only be contemplated when there are well-organized management systems in place. Methods for scheduling irrigation are summarized and the reasons for their limited uptake considered. In conclusion, the ‘drivers for change’, including the need for improved environmental protection, influencing technology choice if irrigated sugar cane production is to be sustainable are summarized.

scholarly journals Soil moisture heterogeneity regulates water use in Populus nigra L. by altering root and xylem sap phytohormone concentrations

2020 ◽  
Vol 40 (6) ◽  
pp. 762-773 ◽  
Author(s):  
Jaime Puértolas ◽  
Marta Pardos ◽  
Carlos de Ollas ◽  
Alfonso Albacete ◽  
Ian C Dodd
Keyword(s):  
Soil Moisture ◽  
Water Use ◽  
Deficit Irrigation ◽  
Xylem Sap ◽  
Irrigation Scheduling ◽  
Populus Nigra ◽  
Soil Drying ◽  
Plant Water ◽  
Plant Water Use ◽  
Soil Moisture Heterogeneity

Abstract Soil moisture heterogeneity in the root zone is common both during the establishment of tree seedlings and in experiments aiming to impose semi-constant soil moisture deficits, but its effects on regulating plant water use compared with homogenous soil drying are not well known in trees. Pronounced vertical soil moisture heterogeneity was imposed on black poplar (Populus nigra L.) grown in soil columns by altering irrigation frequency, to test whether plant water use, hydraulic responses, root phytohormone concentrations and root xylem sap chemical composition differed between wet (well-watered, WW), and homogeneously (infrequent deficit irrigation, IDI) and heterogeneously dry soil (frequent deficit irrigation, FDI). At the same bulk soil water content, FDI plants had greater water use than IDI plants, probably because root abscisic acid (ABA) concentration was low in the upper wetter layer of FDI plants, which maintained root xylem sap ABA concentration at basal levels in contrast with IDI. Soil drying did not increase root xylem concentration of any other hormone. Nevertheless, plant-to-plant variation in xylem jasmonic acid (JA) concentration was negatively related to leaf stomatal conductance within WW and FDI plants. However, feeding detached leaves with high (1200 nM) JA concentrations via the transpiration stream decreased transpiration only marginally. Xylem pH and sulphate concentration decreased in FDI plants compared with well-watered plants. Frequent deficit irrigation increased root accumulation of the cytokinin trans-zeatin (tZ), especially in the dry lower layer, and of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC), in the wet upper soil layer. Root hormone accumulation might explain the maintenance of high root hydraulic conductance and water use in FDI plants (similar to well-watered plants) compared with IDI plants. In irrigated tree crops, growers could vary irrigation scheduling to control water use by altering the hormone balance.

Usage of soil moisture models in agronomic research

1996 ◽  
Vol 76 (3) ◽  
pp. 285-295 ◽  
Author(s):  
O. O. Akinremi ◽  
S. M. McGinn
Keyword(s):  
Soil Moisture ◽  
Grain Yield ◽  
Water Use ◽  
Crop Yield ◽  
Drought Index ◽  
Regional Scale ◽  
Irrigation Scheduling ◽  
Water Model ◽  
Yield Reduction ◽  
Efficiency Coefficient

Soil moisture controls many important processes in the soil-plant system and the extent of these processes cannot be quantified without knowing moisture status of the root zone. Of agronomic importance these include, seedling emergence, evapotranspiration, mineralization of the soil organic fraction, surface runoff, leaching and crop yield. Many models have been developed to simulate these processes based on algorithms of varying degrees of complexity that describe the dynamic nature of soil moisture at different temporal and spatial scales. This paper reviews the direct applications of soil moisture models in agronomy from the field to regional scale and for daily to seasonal time steps. At every level of detail, the lack of model validation beyond the region where it was developed is the main limitation to the application of soil moisture models in agronomy. At the field scale, models have been used for irrigation scheduling to ensure efficient utilization of irrigation water and maximize crop yields. Models are also used to estimate crop yield based on the growing season water use. The water use of crops is converted to biomass accumulation and grain yield using a water-use efficiency coefficient and a harvest index. Other empirical equations are available that relate cumulative crop water use directly to grain yield. On a regional scale, in a study of drought climatology on the Canadian prairie, we coupled a soil water model, the Versatile Soil Moisture Budget, with the Palmer Drought Index model to improve the modelling of soil moisture. This was found to improve the relationship of the Palmer drought index to wheat yield reduction resulting from drought. Key words: Soil moisture, modelling, water-use, evapotranspiration, aridity index, Canadian prairies

Detecting changes in root zone soil moisture from radar vegetation backscatter

2020 ◽  
Author(s):  
Coleen Carranza ◽  
Tim van Emmerik ◽  
Martine van der Ploeg
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Hydrological Cycle ◽  
Root Zone ◽  
Water Status ◽  
Roughness Parameter ◽  
Growing Season ◽  
Irrigation Scheduling ◽  
Vegetation Water Content ◽  
Vegetation Water

&lt;p&gt;Root zone soil moisture (&amp;#952;&lt;sub&gt;rz&lt;/sub&gt;) is a crucial component of the hydrological cycle and provides information for drought monitoring, irrigation scheduling, and carbon cycle modeling. During vegetation conditions, estimation of &amp;#952;&lt;sub&gt;rz&lt;/sub&gt; thru radar has so far only focused on retrieving surface soil moisture using the soil component of the total backscatter (&amp;#963;&lt;sub&gt;soil&lt;/sub&gt;), which is then assimilated into physical hydrological models. The utility of the vegetation component of the total backscatter (&amp;#963;&lt;sub&gt;veg&lt;/sub&gt;) has not been widely explored and is commonly corrected for in most soil moisture retrieval methods. However, &amp;#963;&lt;sub&gt;veg &lt;/sub&gt;provides information about vegetation water content. Furthermore, it has been known in agronomy that pre-dawn leaf water potential is in equilibrium with that of the soil. Therefore soil water status can be inferred by examining&amp;#160; the vegetation water status. In this study, our main goal is to determine whether changes in root zone soil moisture (&amp;#916;&amp;#952;&lt;sub&gt;rz&lt;/sub&gt;) shows corresponding changes in vegetation backscatter (&amp;#916;&amp;#963;&lt;sub&gt;veg&lt;/sub&gt;) at pre-dawn. We utilized Sentinel-1 (S1) descending pass and in situ soil moisture measurements from 2016-2018 at two soil moisture networks (Raam and Twente) in the Netherlands. We focused on corn and grass which are the most dominant crops at the sites and considered the depth-averaged &amp;#952;&lt;sub&gt;rz&lt;/sub&gt; up to 40 cm to capture the rooting depths for both crops. Dubois&amp;#8217; model formulation for VV-polarization was applied to estimate the surface roughness parameter (H&lt;sub&gt;rms&lt;/sub&gt;) and &amp;#963;&lt;sub&gt;soil &lt;/sub&gt;during vegetated periods. Afterwards, the Water Cloud Model was used to derive &amp;#963;&lt;sub&gt;veg&lt;/sub&gt; by subtracting &amp;#963;&lt;sub&gt;soil&lt;/sub&gt; from S1 backscatter (&amp;#963;&lt;sub&gt;tot&lt;/sub&gt;). To ensure that S1 only measures vegetation water content, rainy days were excluded to remove the influence of intercepted rainfall on the backscatter. The slope of regression lines (&amp;#946;) fitted over plots of &amp;#916;&amp;#963;&lt;sub&gt;veg&lt;/sub&gt; against &amp;#916;&amp;#952;&lt;sub&gt;rz&lt;/sub&gt; were used investigate the dynamics over a growing season. Our main result indicates that &amp;#916;&amp;#963;&lt;sub&gt;veg &lt;/sub&gt;- &amp;#916;&amp;#952;&lt;sub&gt;rz&lt;/sub&gt; relation is influenced by crop growth stage and changes in water content in the root zone. For corn, changes in &amp;#946;&amp;#8217;s over a growing season follow the trend in a crop coefficient (K&lt;sub&gt;c&lt;/sub&gt;) curve, which is a measure of crop water requirements. Grasses, which are perennial crops, show trends corresponding to the mature crop stage. The correlation between soil moisture (&amp;#916;&amp;#952;) at specific soil depths (5, 10, 20, and 40 cm) and &amp;#916;&amp;#963;&lt;sub&gt;veg &lt;/sub&gt; matches root growth for corn and known rooting depths for both corn and grass. Dry spells (e.g. July 2018) and a large increase in root zone water content in between two dry-day S1 overpass (e.g. from rainfall) result in a lower &amp;#946;, which indicates that &amp;#916;&amp;#963;&lt;sub&gt;veg&lt;/sub&gt; does not match well with &amp;#916;&amp;#952;&lt;sub&gt;rz&lt;/sub&gt;. The influence of vegetation on S1 backscatter is more pronounced for corn, which translated to a clearer &amp;#916;&amp;#963;&lt;sub&gt;veg&lt;/sub&gt; - &amp;#916;&amp;#952;&lt;sub&gt;rz&lt;/sub&gt; relation compared to grass. The sensitivity of &amp;#916;&amp;#963;&lt;sub&gt;veg&lt;/sub&gt; to &amp;#916;&amp;#952;&lt;sub&gt;rz&lt;/sub&gt; in corn means that the analysis may be applicable to other broad leaf crops or forested areas, with potential applications for monitoring&amp;#160; periods of water stress.&lt;/p&gt;

Area-representative validation of remotely sensed high resolution soil moisture using a cosmic-ray neutron sensor

2020 ◽  
Author(s):  
Dragana Panic ◽  
Isabella Pfeil ◽  
Andreas Salentinig ◽  
Mariette Vreugdenhil ◽  
Wolfgang Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Root Zone ◽  
Spatial Scales ◽  
Temporal Frequency ◽  
Cosmic Ray ◽  
Irrigation Scheduling ◽  
Water Index ◽  
The Impact

&lt;p&gt;Reliable measurements of soil moisture (SM) are required for many applications worldwide, e.g., for flood and drought forecasting, and for improving the agricultural water use efficiency (e.g., irrigation scheduling). For the retrieval of large-scale SM datasets with a high temporal frequency, remote sensing methods have proven to be a valuable data source. (Sub-)daily SM is derived, for example, from observations of the Advanced Scatterometer (ASCAT) since 2007. These measurements are available on spatial scales of several square kilometers and are in particular useful for applications that do not require fine spatial resolutions but long and continuous time series. Since the launch of the first Sentinel-1 satellite in 2015, the derivation of SM at a spatial scale of 1 km has become possible for every 1.5-4 days over Europe (SSM1km) [1]. Recently, efforts have been made to combine ASCAT and Sentinel-1 to a Soil Water Index (SWI) product, in order to obtain a SM dataset with daily 1 km resolution (SWI1km) [2]. Both datasets are available over Europe from the Copernicus Global Land Service (CGLS, https://land.copernicus.eu/global/). As the quality of such a dataset is typically best over grassland and agricultural areas, and degrades with increasing vegetation density, validation is of high importance for the further development of the dataset and for its subsequent use by stakeholders.&lt;/p&gt;&lt;p&gt;Traditionally, validation studies have been carried out using in situ SM sensors from ground networks. Those are however often not representative of the area-wide satellite footprints. In this context, cosmic-ray neutron sensors (CRNS) have been found to be valuable, as they provide integrated SM estimates over a much larger area (about 20 hectares), which comes close to the spatial support area of the satellite SM product. In a previous study, we used CRNS measurements to validate ASCAT and S1 SM over an agricultural catchment, the Hydrological Open Air Laboratory (HOAL), in Petzenkirchen, Austria. The datasets were found to agree, but uncertainties regarding the impact of vegetation were identified.&lt;/p&gt;&lt;p&gt;In this study, we validated the SSM1km, SWI1km and a new S1-ASCAT SM product, which is currently developed at TU Wien, using CRNS. The new S1-ASCAT-combined dataset includes an improved vegetation parameterization, trend correction and snow masking. The validation has been carried out in the HOAL and on a second site in Marchfeld, Austria&amp;#8217;s main crop producing area. As microwaves only penetrate the upper few centimeters of the soil, we applied the soil water index concept [3] to obtain soil moisture estimates of the root zone (approximately 0-40 cm) and thus roughly corresponding to the depth of the CRNS measurements. In the HOAL, we also incorporated in-situ SM from a network of point-scale time-domain-transmissivity sensors distributed within the CRNS footprint. The datasets were compared to each other by calculating correlation metrics. Furthermore, we investigated the effect of vegetation on both the satellite and the CRNS data by analyzing detailed information on crop type distribution and crop water content.&lt;/p&gt;&lt;p&gt;[1] Bauer-Marschallinger et al., 2018a: https://doi.org/10.1109/TGRS.2018.2858004&lt;br&gt;[2] Bauer-Marschallinger et al., 2018b: https://doi.org/10.3390/rs10071030&lt;br&gt;[3] Wagner et al., 1999: https://doi.org/10.1016/S0034-4257(99)00036-X&lt;/p&gt;

Better placement of soil moisture point measurements guided by 2D resistivity tomography for improved irrigation scheduling

Soil Research ◽  
2011 ◽  
Vol 49 (6) ◽  
pp. 504 ◽  
Author(s):  
B. F. J. Kelly ◽  
R. I. Acworth ◽  
A. K. Greve
Keyword(s):  
Soil Moisture ◽  
Spatial Information ◽  
Root Zone ◽  
Irrigation Scheduling ◽  
Measurement Methods ◽  
Deep Drainage ◽  
Resistivity Tomography ◽  
Point Measurement ◽  
Irrigated Crops ◽  
2D Resistivity

Soil moisture beneath irrigated crops has traditionally been determined using point measurement methods such as neutron probes or capacitance systems. These approaches cannot measure soil moisture at depths beyond the root-zone of plants and have limited lateral coverage. It is shown that surface two-dimensional electrical resistivity tomography (ERT) can be used to map the spatial heterogeneity in soil moisture throughout a field under irrigated cotton. The case study demonstrates that ERT provides a better understanding of the pathways of water migration, and provides spatial information on how water storage changes throughout the growing season. We conclude that ERT should be integrated into farm water management surveys to delineate zones of excessive water loss due to deep drainage and to improve the positioning of point measurement methods for measuring soil moisture, thereby improving irrigation scheduling.

scholarly journals Development of a Simple Irrigation Scheduling Calendar for Mesilla Valley Pecan Growers

2008 ◽  
Vol 18 (4) ◽  
pp. 714-725 ◽  
Author(s):  
Jeffery C. Kallestad ◽  
John G. Mexal ◽  
Theodore W. Sammis ◽  
Richard Heerema
Keyword(s):  
Soil Moisture ◽  
Water Use ◽  
Sandy Loam ◽  
Irrigation Scheduling ◽  
Time Interval ◽  
Silty Clay ◽  
Climate Data ◽  
Evaporative Demand ◽  
Consumptive Water Use ◽  
Consumptive Water

For farmers to accurately schedule future water delivery for irrigations, a prediction method based on time-series measurements of soil moisture depletion and climate-based indicators of evaporative demand is needed. Yet, numerous reports indicate that field instruments requiring high in-season labor input are not likely to be used by farmers. In New Mexico, pecan (Carya illinoensis) farmers in the Mesilla Valley have been reluctant to adopt new soil-based or climate-based irrigation scheduling technologies. In response to low adoption rates, we have developed a simple, practical irrigation scheduling tool specifically for flood-irrigated pecan production. The information presented in the tool was derived using 14 years of archived climate data and model-simulated consumptive water use. Using this device, farmers can estimate the time interval between their previous and the next irrigation for any date in the growing season, in a range of representative soil types. An accompanying metric for extending irrigation intervals based on field-scale rainfall accumulation was also developed. In modeled simulations, irrigations scheduled with the tool while using the rainfall rule were within 3 days of the model-predicted irrigation dates in silty clay loam and loam soil, and less than 2 days in sandy loam and sand soil. The simulations also indicated that irrigations scheduled with the tool resulted in less than 1% reduction in maximum annual consumptive water use, and the overall averaged soil moisture depletion was 45.14% with an 18.1% cv, relative to a target management allowable depletion of 45%. Our long-term objective is that farmers using this tool will better understand the relationships between seasonal climate variation and irrigation scheduling, and will seek real-time evapotranspiration information currently available from local internet resources.

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