Efficient Irrigation Strategies Research Articles

Combining proximal and remote sensing to assess 'Calatina' olive water status.

Developing an efficient and sustainable precision irrigation strategy is crucial in contemporary agriculture. This study aimed to combine proximal and remote sensing techniques to show the benefits of using both monitoring methods, simultaneously assessing the water status and response of 'Calatina' olive under two distinct irrigation levels: full irrigation (FI), and drought stress (DS, -3 to -4 MPa). Stem water potential (Ψstem) and stomatal conductance (gs) were monitored weekly as reference indicators of plant water status. Crop water stress index (CWSI) and stomatal conductance index (Ig) were calculated through ground-based infrared thermography. Fruit gauges were used to monitor continuously fruit growth and data were converted in fruit daily weight fluctuations (ΔW) and relative growth rate (RGR). Normalized difference vegetation index (NDVI), normalized difference RedEdge index (NDRE), green normalized difference vegetation index (GNDVI), chlorophyll vegetation index (CVI), modified soil-adjusted vegetation index (MSAVI), water index (WI), normalized difference greenness index (NDGI) and green index (GI) were calculated from data collected by UAV-mounted multispectral camera. Data obtained from proximal sensing were correlated with both Ψstem and gs, while remote sensing data were correlated only with Ψstem. Regression analysis showed that both CWSI and Ig proved to be reliable indicators of Ψstem and gs. Of the two fruit growth parameters, ΔW exhibited a stronger relationship, primarily with Ψstem. Finally, NDVI, GNDVI, WI and NDRE emerged as the vegetation indices that correlated most strongly with Ψstem, achieving high R2 values. Combining proximal and remote sensing indices suggested two valid approaches: a more simplified one involving the use of CWSI and either NDVI or WI, and a more comprehensive one involving CWSI and ΔW as proximal indices, along with WI as a multispectral index. Further studies on combining proximal and remote sensing data will be necessary in order to find strategic combinations of sensors and establish intervention thresholds.

Calibration, testing and application of the AquaCrop model for bean crop under irrigation regimes.

Crop growth simulation models relate the soil-water-plant-atmosphere components to estimate the development and yield of plants in different scenarios, enabling the identification of efficient irrigation strategies. The aim of this study was to calibrate crop coefficients for a common bean cultivar (IAPAR 57) and assess the AquaCrop model's efficacy in simulating crop growth under different irrigation regimes (T0 - non-irrigated, T1-fully irrigated, and T2-deficit irrigated) and sowing dates (S1-March 21, S2-April 24, and S3-August 23). Successful calibration was achieved for crop seasons with suitable temperatures to crop growth (S1 and S3). However, during periods with suboptimal temperatures (April 24 season), coupled with reduced irrigation supply (T0 and T2), the AquaCrop model did not appropriately account for the combined effects of thermal and water stresses. Despite adjustments to stress coefficients, this led to an overestimation of crop growth and yield. In long-term simulations, the model successfully replicated the variability of crop water availability over cropping seasons, reflecting the impact of precipitation variations. It recommended irrigation strategies for the study region (irrigate at depletion of 120 and 170% of readily available water for sowing on March 21 and August 24, respectively) to achieve high crop yield (> 2,769kgha-1) and water productivity (1,050 to 1,445kgm-3) with minimal application depths (< 150mm). While acknowledging the need for improvements in thermal stress calculations, the AquaCrop model demonstrates promising utility in studies and applications where water availability significantly influences crop production.

Optimization of irrigation period improves wheat yield by regulating source-sink relationship under water deficit

The optimization of irrigation scheduling presents an effective methodology for augmenting crop yields and enhancing water utilization efficiency. Nonetheless, a comprehensive understanding of the intricate mechanisms through which this strategy influences crop growth and yield formation is yet to be fully understood. In this study, a field experiment was conducted during the winter wheat cultivation period from 2018 to 2020 on two wheat cultivars: JM418, known for its drought tolerance, and SX828, known for its drought sensitivity. These treatments were subjected to four distinct irrigation schedules and two sowing stages. The timing of irrigation was specifically designed to coincide with the visibility of the 3rd, 4th, 5th, and 6th leaves for normal and postponed sowing. Our findings revealed that commencing irrigation at the stage when the 4th leaf becomes visible serves as an advantageous strategy for deficit irrigation. This approach significantly amplified winter wheat yield by 6.96–54.09 % and improved water use efficiency by 9.88–47.62 %. Quantitative analysis of source ability parameters demonstrated that postponed irrigation adversely affected the mean leaf area index (MLAI), total leaf area duration (TLAD), and biomass at maturity (BAM). Furthermore, an increase in mean net assimilation rate (MEAR) and harvest index (HI) was noted during the delayed irrigation phase when the 4th leaf was visible. The highest spike count per hectare was observed when irrigation was executed at the 4th leaf visibility stage, with an average increase of 13.98 %. Conversely, with a postponed irrigation schedule, the mean count of grain number per spike decreased by 2.47, while the 1000-grain weight saw an increase of 1.65 g. Higher sink capacity was obtained with irrigation when the 3rd and 4th leaves were visible. Despite this, the grain-leaf ratios when irrigated at the 4th, 5th, and 6th leaf visibility stages were significantly higher than those irrigated at the 3rd leaf visibility stage. In conclusion, our findings elucidate that the irrigation strategy coinciding with the 4th leaf visibility stage exhibits superior grain yield and water use efficiency (WUE) stability. This can be attributed to the enhanced harvest index, effective spike number per unit area, and biomass accumulation. Concurrently, the number of grains per panicle and the 1000-grain weight were relatively balanced. Our research offers novel insights into the mechanism of source-sink regulation in crops under deficit irrigation conditions and lays the groundwork for the development of precise and efficient irrigation strategies.

Do rainfed production systems have lower environmental impact over irrigated production systems?: On -farm mitigation strategies

The intensive agriculture practices improved the crop productivity but escalated energy inputs (EI) and carbon foot print (CF) which contributes to global warming. Hence designing productive, profitable crop management practices under different production systems with low environmental impact (EI and CF) is the need of the hour. To identify the practices, quantification of baseline emissions and the major sources of emissions are required. Indian agriculture has diversified crops and production systems but there is dearth of information on both EI and CF of these production systems and crops. Hence the present study was an attempt to find hot spots and identify suitable strategies with high productivity, energy use efficiency (EUE) and carbon use efficiency (CUE). Energy and carbon balance of castor, cotton, chickpea, groundnut, maize, rice (both rainfed and irrigated), wheat, sugarcane (only irrigated), pigeon pea, soybean, sorghum, pearl millet (only rainfed) in different production systems was assessed. Field specific data on different crop management practices as well as grain and biomass yields were considered. Rainfed production systems had lower EI and CF than irrigated system. The nonrenewable sources of energy like fertilizer (64 %), irrigation (78 %), diesel fuel (75 %) and electricity (67 %) are the major source of energy input. Rainfed crops recorded higher CUE over irrigated condition. Adoption of technologies like efficient irrigation strategies (micro irrigation), enhancing fertilizer use efficiency (site specific nutrient management or slow release fertilizer), conservation agriculture (conservation or reduced tillage) rice cultivation methods (SRI or Direct seeded rice) were the mitigation strategies. These results will help policy makers and stake holders in adoption of suitable strategies for sustainable intensification.

Measurement and simulation of irrigation performance in continuous and surge furrow irrigation using WinSRFR and SIRMOD models

The SIRMOD and WinSRFR models were used to model and assess the irrigation performance under continuous and surge irrigation strategies with two furrow lengths of 70 m and 90 m and stream sizes of 0.4 l/s and 0.6 l/s for each length. According to the normalized root mean squared error (NRMSE) and the relative error (RE), WinSRFR had, on average, excellent accuracy in the continuous and surge irrigation for simulating advance-recession times (NRMSE: 6.15 and 4.24% for advance time, and 2.20 and 5.20% for recession time), infiltrated water depth (NRMSE: 3.37 and 6.38%), and runoff volume (RE: 6.93 and 2.57%), respectively. SIRMOD had also, on average, excellent simulation in the continuous and surge irrigation for advance-recession times (NRMSE: 3.34 and 2.45% for advance time, and 2.28 and 6.41% for recession time), infiltrated water depth (NRMSE: 2.98 and 5.27%), and runoff volume (RE: 5.31 and 17.49%), respectively. The average of irrigation application efficiency (AE), distribution uniformity (DU), deep percolation (DP), and tail-water ratio (TWR) were 61.50, 90.25, 11.75, and 26.75% in continuous irrigation, and 72.03, 94.09, 8.39, and 19.57% in surge irrigation, respectively, which shows that surge irrigation increased AE (irrigation management performance) and DU (irrigation method performance) and reduced DP and TWR compared to continuous irrigation. Moreover, longer furrow lengths increased AE and DP under both irrigation methods, while it decreased TWR and DU. However, increasing the stream size decreased AE and DP and increased TWR under both continuous and surge irrigations. The higher stream size improved DU in continuous irrigation but reduced DU in surge irrigation. The results confirmed that both SIRMOD and WinSRFR are reliable analytical tools to evaluate furrow irrigation strategies for improving irrigation management. In conclusion, this study showed that surface irrigation models could be employed in practice by irrigation engineers and practitioners to design and define the optimized furrow length and stream size in arid and semi-arid areas where efficient and high performance irrigation strategies are required to save water and reduce water loss.

Adapting Irrigation Strategies to Mitigate Climate Change Impacts: A Value Engineering Approach

Water scarcity and climate change are posing new challenges to irrigation management. Climate change increases water demand and decreases crop yields. The aim of this paper is to propose a framework to select the most efficient irrigation strategy to mitigate the impacts of climate change and achieve food security. Value engineering (VE) methodology is utilized to assure the functionality of the strategy and add an element of creativity while creating the value alternatives. The life cycle cost (LCC) technique is utilized to provide the optimum irrigation strategy from an economic perspective. The findings showed three different value alternatives for different crops, soil types, and irrigation systems. This paper contributes to the current state of knowledge by a) utilizing the Value Engineering methodology in irrigation management studies; b) evaluating irrigation strategies to ensure efficient irrigation water management; and c) providing policymakers with a tool to incorporate the added value and functionality into their policies regarding irrigation water.

Economic penalties associated with irrigation during high rainfall years in the southeastern United States

Although cotton is a drought-tolerant crop, irrigation is still needed to ensure productivity, even in the humid Southeastern United States. Irrigation must be carefully managed to limit unnecessary water use while ensuring maximum economic productivity. To better understand the costs and net returns of irrigation and cultivar selection, field experiments were conducted in 2016 and 2017 to compare cotton lint yield and fiber quality in dryland plots and plots irrigated using the University of Georgia checkbook method (UGA Checkbook) at a field site near Camilla, Georgia. Results showed cultivar differences in fiber quality parameters of micronaire and uniformity in 2016, but there was no cultivar difference in fiber quality in 2017. Cultivar differences were not observed in yield or net returns for both years. However, stoplight chart analysis of net returns indicated differences in cultivar selection for irrigated or dryland production. ST 6182 GLB2 would be a better option for a producer to minimize downside risk under dryland conditions, and PHY 333 WRF would be a better option under irrigated production. Results also indicated that broadly applying simplistic water balance approaches could decrease yield, water productivity, and net returns, especially in environments where rainfall is sufficient yet unpredictable. Overirrigation affected some fiber quality parameters but did not impact the overall market price for cotton. In 2016, irrigating according to the UGA Checkbook method negatively impacted yield and net returns. In 2017, irrigation did not affect yield but negatively impacted net returns. Average losses in net returns associated with excessive irrigation in these two wet years were $336 per hectare for net return over irrigation variable costs, and $645 per hectare for net return over irrigation total costs. Implementing robust, efficient irrigation strategies is necessary to achieve high cotton yields, reduce water usage, and improve economic returns.

Spatial diffusion of efficient irrigation systems: a study of São Paulo, Brazil*

Finding ways to stimulate the diffusion of water‐saving irrigation systems is essential to mitigate the negative impacts of climate change on water supply. We analyse the spatial diffusion of more efficient irrigation strategies in São Paulo, Brazil, comparing the two most common irrigation technologies: conventional sprinkler irrigation and the localised irrigation. We use longitudinal municipal‐level information for 2006 and 2017 and test different spatial panel models' specifications, representing different hypotheses about technological transfer channels. Our results highlight how the diffusion of water‐saving irrigation systems (localised irrigation) in one municipality is strongly influenced by the diffusion in neighbouring municipalities. Membership in cooperatives or farmers' associations plays a significant role in this technological transfer. On the other hand, the diffusion of less efficient systems (sprinkler irrigation) depends fundamentally on the local availability of water and unobservable factors in the neighbourhood. The discussion highlights how easing knowledge transmission may contribute to the diffusion of more sustainable agriculture practices.

Improving Peach Fruit Quality Traits Using Deficit Irrigation Strategies in Southern Tunisia Arid Area.

The peach (Prunus persica L.) is one of Tunisia’s major commercial fruit crops and is considered one of the biggest water consumers of all crops. In warm and arid areas of southern Tunisia, irrigation is necessary to ensure orchard longevity and high yield and fruit quality. Nevertheless, under water-scarcity conditions and low water quality, water management should rely on efficient deficit irrigation strategies. In this study, sustained deficit irrigation (DI) and partial root-zone drying (PRD50) at 50% of crop evapotranspiration (ETc) were evaluated for their impact on the primary and secondary metabolites of the peach fruit of early cultivar Flordastar grown in the Tataouine region. A full irrigation (FI) treatment at 100%, etc., was used as a control treatment. Color, dry-matter content, firmness, organic acids, sugars, phenolic compounds, vitamin C, β-carotene and minerals were assessed on harvested mature fruits. Dry-matter content and firmness increased significantly under DI and PRD50 (13% and 15.5%). DI fruit had the highest soluble-solid content (SSC), reaching Brix values of 14.3°. Fruit sorbitol and sucrose contents were not affected by Di and PRD50. Higher glucose in fruit juice was observed in PRD50 (23%) and DI (21.5%) compared to FI, which had the highest malic acid content (33.5–37%). Quinic and citric acids decreased with DI and PRD50, while almost all individual phenolic compounds increased with deficit irrigation. Hydroxycinnamates and anthocyanins were significantly higher in fruits harvested from DI and PRD50 treatments. Proanthocyanidins (catechin and epicatechin) were only improved by DI, while flavone compounds and vitamin C were not affected by irrigation restrictions. β-carotene was higher in fruits yielded under FI (0.71 mg/100 g DM) than DI and PRD50 (0.21–0.43 mg/100 g DM). Macro- and micronutrients significantly increased in DI and PRD50 fruit. A significant difference between DI and PRD50 fruits was observed for Zn and Fe concentrations. This research highlights the positive impact of reduced irrigation on bioactive-fruit quality attributes and the suitability of PRD50 and DI as tools for irrigation management in arid areas of southern Tunisia, contributing to water-saving in orchards and the improvement of fruit commercial value.

Integrated surface and groundwater modeling to enhance water resource sustainability in agricultural watersheds

Management of water resources is essential to maintain sustainable agricultural productivity and preserve groundwater and surface ecosystems. The long-term sustainability of these systems depends on the understanding of complex surface-groundwater flow interactions at different temporal and spatial scales, and the impacts of agricultural practices on water use. To support these efforts, an integrated AnnAGNPS-MODFLOW modeling technology is proposed and evaluated. It combines the capability of the AnnAGNPS model to detailed characterization of farming practices with groundwater flow estimation tools of the MODFLOW model. The AnnAGNPS-MODFLOW model was evaluated in Upper Sunflower River watershed at the Lower Mississippi River Alluvial Plain. The integrated modeling technology in conjunction with observed values of streamflow at the outlet and well water levels were used to estimate irrigation strategies with application rates varying in time and space at field scale. Utilization of improved irrigation characterization have provided evidence of the sensitivity of streamflow and groundwater levels to irrigation strategies. Simulation results indicate that a reduction of irrigation application rates by 20–40% can impact aquifer long-term water levels. This finding supports the need to investigate more efficient irrigation strategies to promote the aquifer sustainable use. The proposed technology provides a management tool critical to understanding and evaluating the impact of agricultural practices, irrigation, and aquifer recharge strategies that are important to sustaining water resources in irrigated agricultural watersheds.

Evaluation of water use efficiency and optimal irrigation quantity of spring maize in Hetao Irrigation District using the Noah-MP Land Surface Model

Hetao Irrigation District (HID), one of the main grain-producing areas in China, is facing the severe challenge of agricultural water shortages. Improving water use efficiency (WUE) is the most appropriate way to achieve sustainable agricultural development and obtain high returns. However, farmers knew little about efficient irrigation strategies for flood-irrigated fields in the HID. In this study, the Noah-MP Land Surface Model (LSM) with dynamic crop and irrigation schemes is used to jointly simulate the maize yield and irrigation amount in the HID from 2003 to 2012. A sensitivity test for ten sets of irrigation setup with different soil moisture (SM) triggering thresholds (CRI=0–1) is conducted, and the corresponding WUE and irrigation water use efficiency (IWUE) are evaluated and analyzed. In addition, irrigation at different crop growth stages affects total irrigation amounts and crop yield. The results show that under rain-fed conditions, the severe SM deficit during the growing season significantly decreases the maize yield in the HID, with almost no harvest in dry years. With traditional flood irrigation, the irrigation amount per unit area exceeds 1000 mm, leading to low WUE and IWUE, while more than 18–25% of irrigation water is wasted as runoff. With the increase of irrigation intensity, both WUE and IWUE show a significant diminishing marginal effect, usually occurring when SM is greater than 0.24–0.27 m3/m3. The optimal WUE is obtained near CRI= 0.6, while the worst WUE is obtained at CRI= 1. In a normal year, efficient irrigation amount is about 390–480 mm, 53–63% less than that in flood irrigation. In this scenario, most irrigation water becomes SM and transpiration, and less than 5% becomes runoff. With effective irrigation in the reproductive stage, only a small amount of irrigation is needed to promote yield formation. Fully considering the maize yield, WUE, ecosystems, and the available water resources in the HID, the recommended irrigation amount is about 600–650 mm to achieve the optimal maize yield and WUE.

The synergy between water conservation and economic profitability of adopting alternative irrigation systems for cotton production in the Texas High Plains

Declining water levels of the Ogallala Aquifer challenge economic availability of the groundwater and necessitate adoption of advanced irrigation systems with efficient irrigation strategies. Irrigation methods and application levels affect water productivity and farm profitability. This study evaluated the synergy between water conservation through a deficit irrigation strategy and economic profitability of agricultural production. The economic feasibility of cotton production was compared using field data for mid- and low-elevation spray application (MESA and LESA, respectively), low-energy precision application (LEPA), and subsurface drip irrigation (SDI) systems in the Texas High Plains (THP) region. Treatments included irrigated cotton with water application at 25%, 50%, 75%, and 100% evapotranspiration (ET) replacement levels and near-dryland cotton production. Both field-level data and well-calibrated model simulation data were used to assess cotton profitability at varying risk attitudes of producers. Results showed that more irrigation water consistently increased average net return of cotton production for all irrigation systems, except for SDI, which produced a similar net return at both 75% and 100% ET replacement levels. A larger chance of getting a net return greater than $380 ha−1 was observed for MESA, LESA and LEPA systems with the full irrigation at the 100% ET replacement level as well as for SDI with 75% ET replacement. Economic risk analysis showed that LEPA had a higher net return than other systems at each of the four irrigation levels and it would be preferred by risk-neutral, somewhat risk-averse, and rather risk-averse cotton producers. For each irrigation system, full irrigation was most preferred by risk-neutral producers and only minor differences were observed in the expected returns between 75% and 100% ET replacements as the producers became somewhat or more risk-averse. Groundwater conservation can be achieved with SDI without compromising crop yield or farm income, while government policies and financial incentives can help motivate producers to save irrigation water and maintain a high farm profit under spray and LEPA systems.

Water productivity in maize, at different levels of deficit irrigation in humid climate

En regiones de clima templado y húmedo como Uruguay el riego estabiliza y aumenta los rendimientos de los cultivos estivales, suplementando las precipitaciones. El riego a demanda tiene mayor consumo de agua, afectando la sostenibilidad del sistema de producción por el uso ineficiente de los recursos, y es ambientalmente negativo (uso excesivo de agua dulce y energía para su extracción). Es necesario evaluar alternativas de riego deficitario que aumenten la productividad del agua riego. Para ello se evaluaron tres láminas máximas de reposición: (T2) 3 mm día-1, (T3) 6 mm día-1, (T4) 9 mm día-1, y (T1) testigo sin riego, (solo agua de lluvia), sobre la producción de maíz, para definir estrategias de riego más eficientes. Los resultados indican que existe respuesta a diferentes niveles de riego deficitario. Cuando las precipitaciones fueron superiores al promedio, su mala distribución durante el ciclo del cultivo generó déficit hídrico en momentos puntuales, afectando el rendimiento. El T1 y T2 no cubrieron la etc durante el Periodo Crítico y llenado de grano, causando menores rendimientos. El T3 y T4 dieron rendimientos mayores y en el promedio de tres años fueron diferentes significativamente. El T3 no siempre cubrió la etc, pero la reserva del suelo y las precipitaciones contribuyeron para cubrirlo, ahorrando casi 20 % de agua de riego respecto a T4. Sin embargo, los indicadores de productividad del agua (eua, euar) muestran que T4 es mejor estrategia de riego, aunque realice menor aprovechamiento de las precipitaciones y del agua del suelo.

Efficient Irrigation of Maize Through Soil Moisture Monitoring and Modeling

Agriculture is the major user of water resources, accounting for 70% of global freshwater demand. As the demand for clean water increases, so does the need to implement more efficient strategies for water management in irrigated agriculture. While the benefits of precision irrigation in high-value crops, such as cannabis, tomatoes, and potatoes, are fully recognized, there is still need to investigate and implement cheap and efficient irrigation strategies for widespread low-value crops such as maize. In this study, the soil moisture dynamics in a sprinkler-irrigated maize field in Veneto (Northeastern Italy) was monitored using six time domain reflectometry (TDR) probes for the entire growing season. The TDR sensors were positioned at different depths into two separate sites: an Uninformed Site irrigated based on the farmer's experience and an Informed Site in which a water balance irrigation strategy was applied based on soil moisture measurements. A parsimonious hydrological model was then implemented and calibrated to quantify the different water balance terms (precipitation, evapotranspiration, lateral fluxes, and deep percolation). The comparison between the water budget terms in the two sites highlights that soil moisture monitoring during agriculture activities leads to substantial savings in terms of irrigation water volumes requirements and cost, without compromising the productivity of the crop field. A simplified upscaling of the results at the regional scale, assuming average conditions as in this study site and growing season, reveals that potentially significant economic savings, compared to the total profits linked to maize crops, could be possible.

Simulated efficient growth-stage-based deficit irrigation strategies for maximizing cotton yield, crop water productivity and net returns

Declining water levels in the southern Ogallala Aquifer and associated reduction in irrigation capacities and increasing pumping costs necessitate adoption of deficit/limited irrigation practices for sustaining cotton production in the Texas High Plains (THP) region. The overall goal of this study was to evaluate the response of cotton crop to water stress in different growth stages and suggest efficient growth-stage-based deficit (GSBD) irrigation schedules for maximizing yield, crop water productivity (CWP) and economic returns under contrasting weather conditions using the CROPGRO-Cotton model. Five growth stages including seedling emergence/germination, squaring, early bloom/flower initiation, peak bloom, and boll opening/late bloom were considered. A combination of five irrigation scenarios (S1 through S5 with seasonal irrigation amounts of 240, 300, 360, 420 and 480 mm) and six irrigation treatments (T1 through T5: no irrigation in one of the five growth stages, and T6: irrigation applied in all five growth stages) were then simulated with a center pivot irrigation system. Skipping irrigation during the peak bloom growth stage (T4 treatment) resulted in the lowest yield, CWP and net returns under all weather conditions. The T1 irrigation treatment in which irrigation was skipped during the seedling emergence/germination stage was identified as the most efficient irrigation strategy for maximizing yield, CWP and net returns among all irrigation scenarios. Application of more than 360, 420 and 480 mm of irrigation water in wet, normal and dry years, respectively, did not significantly improve yield or net returns, and resulted in a decrease in CWP. These results imply that cotton responses to water deficit vary by growth stages, and adoption of appropriate GSBD irrigation strategies could optimize the use of limited water resources and extend the life of the southern Ogallala Aquifer.

Development of a transpiration model for precise tomato (Solanum lycopersicum L.) irrigation control under various environmental conditions in greenhouse

Transpiration can directly reflect the response of the crop growth and development, therefore irrigation design based on a transpiration model is an important factor towards establishing an efficient irrigation strategy. Thus, the purpose of this experiment is to develop and verify a tomato transpiration model by correcting the relationship between the transpiration rate and environmental factors by measuring the actual transpiration rate. The actual crop transpiration rate, which is measured using a load cell, and the weight changes calculated at 10-min intervals, are applied to the development of the transpiration model. The experimental results show that the transpiration rate has no linear relationship with the radiation amount (Rad) or vapor pressure deficit (VPD). The relationship between Rad and VPD with transpiration rate was fitted by the exponential rise to maximum, and gaussian peak curve, respectively. This allowed a transpiration model to be developed by compensating the Rad and VPD based on the existing Penman–Monteith (P-M) equation. The developed transpiration model showed higher regression constant values than the existing one. The developed transpiration model from the experiment can be utilized for precise irrigation control.

Simulation of Water-Use Efficiency of Crops under Different Irrigation Strategies

Irrigation management is a key factor in attaining optimal yields, as different irrigation strategies lead to different yields even when using the same amount of water or under the same weather conditions. Our research aimed to simulate the water-use efficiency (WUE) of crops considering different irrigation strategies in the Central Valley of Chile. By means of AquaCrop-OS, we simulated expected yields for combinations of crops (maize, sugar beet, wheat), soil (clay loam, loam, silty clay loam, and silty loam), and bulk density. Thus, we tested four watering strategies: rainfed, soil moisture-based irrigation, irrigation with a fixed interval every 1, 3, 5, and 7 days, and an algorithm for optimal irrigation scheduling under water supply constraints (GET-OPTIS). The results showed that an efficient irrigation strategy must account for soil and crop characteristics. Among the tested strategies, GET-OPTIS led to the best performance for crop yield, water use, water-use efficiency, and profit, followed by the soil moisture-based strategy. Thus, soil type has an important influence on the yield and performance of different irrigation strategies, as it provides a significant storage and buffer for plants, making it possible to produce “more crop per drop”. This work can serve as a methodological guide for simulating the water-use efficiency of crops and can be used alongside evidence from the field.

Evaluation of Deficit Irrigation and Water Quality on Production and Water Productivity of Tomato in Greenhouse

This study deals with the evaluation of the effects of deficit irrigation (DI) and water quality (WQ) on the vegetative and productive response of greenhouse-grown tomatoes (Lycopersicon esculentum Mill. cv. Izmir). A pot-based experiment was carried out over two growing seasons. Three WQ: (groundwater, recycled wastewater and a mix of both) were applied in four irrigation scenarios which targeted soil moisture content (SMC) maintaining at 60%, 70%, 80% and 100% of field capacity (FC). Results showed that both DI and WQ had significant effects on crop development, yield and water productivity. The highest values of plant height (186.0 ± 0.58 cm) and stem diameter (23.40 ± 0.02 mm) were found at 100% FC (control). Total yield ranged from 2.33 ± 0.03 kg/plant (60% FC) to 4.05 ± 0.06 kg/plant (control). However, mild water stress (SMC maintaining at 80% FC) showed a positive effect on irrigation water use efficiency (IWUE) without significant yield reduction compared to control. IWUE was at its maximum (31.77 ± 0.47 kg/m3) at 80% FC. A DI regime based on 80% FC could be an efficient irrigation strategy particularly in water-limiting condition. Recycled wastewater was superior among the three WQ for achieving a better crop growth, yield and water productivity at same DI level.

Using high-spatiotemporal thermal satellite ET retrievals to monitor water use over California vineyards of different climate, vine variety and trellis design

Mapping the spatial variability of actual evapotranspiration (ETa) across vineyards is useful for optimizing irrigation scheduling and efficiency, leading to conservation of water resources and more sustainable wine grape production. To support efficient irrigation strategies, we investigate the utility of thermal infrared-based ETa maps over a range of vineyards located throughout California, each representing a unique local climate, trellis design, grape variety, row orientation and management practice. ETa maps are derived by combining the Disaggregated Atmosphere Land Exchange Inverse (ALEXI/DisALEXI) surface energy balance model and the Spatial Temporal Adaptive Reflectance Fusion Model (STARFM) to generate ETa estimates at high spatial (30 m) and temporal (daily) resolution. Model output is evaluated for years 2017 and 2018 over vineyard sites located in Sonoma, Sacramento, and Madera counties in California that are being monitored as part of the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Overall, modeled daily ET estimates compare well with flux tower observations, with average root mean square error (RMSE), mean absolute error (MAE) and mean bias error (MBE) of 0.88 mm day−1, 0.70 mm day−1, and 0.17 mm day−1 respectively, over all four individual vineyard locations, aligning with past GRAPEX studies. Despite general agreement, record wildfires in northern California during 2018 likely resulted in positive model bias, while misrepresentation of leaf area index within a double-trellis designed canopy at the southern-most vineyard resulted in negative model bias. Spatial analysis of monthly total ET highlights the advantages of utilizing a satellite-based approach to characterize the variability in water use within and surrounding the targeted vineyards. A reliable spatial ET product at scale has the potential to improve water allocation and conservation efforts by identifying areas of uneven water use due to variations in soil texture and composition and other environmental or anthropogenic factors.

Determining Optimum Irrigation Termination Periods for Cotton Production in the Texas High Plains

HighlightsIrrigation water use efficiency was consistently higher under deficit irrigation as compared to full irrigation.Irrigation water use was always less than the annual allowable pumping limit under deficit irrigation.The first/second week of September was ideal for terminating irrigation under full/deficit irrigation in normal years.Ideal irrigation termination periods in wet/dry years were a week earlier/later than those in normal years.Abstract. Cotton ( L.) production in the Texas High Plains (THP) region relies heavily on irrigation with groundwater from the underlying Ogallala Aquifer. However, rapidly declining groundwater levels in the aquifer and increasing pumping costs pose challenges for sustainability of irrigated cotton production in this region. Adoption of efficient irrigation strategies, such as terminating irrigation at an appropriate time in the growing season, could enable producers to increase irrigation water use efficiency (IWUE) while maintaining desired yield goals. The objective of this study was to determine optimum irrigation termination periods for cotton production in the THP under full and deficit irrigation conditions using the Decision Support System for Agrotechnology Transfer (DSSAT) CROPGRO-Cotton model, which was evaluated in a prior study in the THP using measured data from an IWUE field experiment at Halfway, Texas. The treatment factors in the field experiment included irrigation capacities of 0 mm d-1 (low, L), 3.2 mm d-1 (medium, M), and 6.4 mm d-1 (high, H), applied during the vegetative, reproductive, and maturation growth stages. This study focused on a full irrigation (HHH) treatment and three deficit irrigation (LMH, LHM, and LMM) treatments. Eight irrigation termination dates with a one-week interval between 15 August and 30 September were simulated, and the impact of irrigation termination date on cotton IWUE and seed cotton yield were studied by dividing the 39-year (1978 to 2016) simulation period into dry, normal, and wet years based on the precipitation received from 1 April to the simulated irrigation termination date. Results indicated that the simulated IWUE was consistently higher under the LHM, LMH, and LMM treatments when compared to the HHH treatment. Based on the simulated average seed cotton yield and IWUE, optimum irrigation termination periods for cotton were found to be the first week of September (about 118 days after planting, DAP) for the HHH and LMH treatments and the second week of September (125 DAP) for the LHM and LMM treatments in normal years. In wet years, optimum irrigation termination periods were a week earlier than those in normal years and a week later in dry years for the HHH, LHM, and LMM treatments. For the LMH treatment, the optimum irrigation termination period in wet years was the same as that in normal years and two weeks later in dry years. The results from this study along with field-specific, late-season information will assist THP cotton producers in making appropriate irrigation termination decisions for improving economic productivity of the Ogallala Aquifer and thereby ensuring water security for agriculture. However, the recommendations from this study should be used with caution, as the optimum irrigation termination periods could potentially change with changes in cultivar characteristics, soil type, climate, and, crop management practices. Keywords: CROPGRO-Cotton, Deficit irrigation, DSSAT, Full irrigation, Irrigation water use efficiency, Seed cotton yield.