This study aimed to assess the impact of salinity in the root zone on crop yields and profitability in the Central Valley. A comprehensive biophysical model was developed by integrating soil ...variables, climate conditions, irrigation inputs, and economic data. The model considered four key crops (alfalfa, almonds, table grapes, and processing tomatoes), five levels of irrigation water salinity (ranging from 0.5 to 5.5 dS/m), and daily irrigation water amounts (ranging from 0 to 12 mm). The results indicated strong predictive capabilities of the model, with R2 values for predicted yields of 0.82, 0.77, 0.78, and 0.64 for alfalfa, almonds, grapes, and tomatoes, respectively. The corresponding RMSE values were 9%, 8%, 23%, and 11% for the same crops. Profit predictions showed an R2 value of 0.99 for alfalfa, almonds, and processing tomatoes, and 0.74 for grapes. The RMSE values were 48, 211, 2461, and 68 $/ha for alfalfa, almonds, grapes, and processing tomatoes, respectively. Furthermore, the model incorporated a spatial component, revealing variations in yield and profitability based on soil type and groundwater salinity across the Central Valley. Results indicated that at daily irrigation rates of 3 mm, no profits were predicted for any of the crops. However, a daily irrigation rate of 6 mm produced profits of up to $1000/ha for alfalfa and processing tomatoes, while almonds and grapes required more than 8 mm/day to achieve profitable outcomes. This integrated modeling framework provides valuable insights for policymakers to identify areas unsuitable for sustainable and profitable irrigated agriculture. It can help prioritize such areas for multi-benefit land repurposing, reducing agricultural water demand, and achieving groundwater sustainability. Additionally, the model serves as a decision-aid tool for growers in arid regions, enabling them to anticipate potential losses in crop yield and profitability due to irrigation water salinity.
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•Salt accumulation in the root zone can impair crop yields and profitability.•High irrigation water salinity diminishes the relative yield and profits.•Water, salinity, and crop prices all impacted profits from crop production.•Higher market values rather than salinity tolerance influence crop profitability.•Better groundwater quality in the eastern region of the Central Valley yields higher profits.
Intensification of olive orchard management entails increased use of fertilizers, especially nitrogen, phosphorus, and potassium. In this review, plant responses to nutritional aspects, as well as ...environmental considerations, are discussed. Nutrient deficiency impairs production, whereas over-fertilization may reduce yields and oil quality, and increase environmental hazards and production costs. The effect of irrigation on nutrient availability and uptake is very significant. Application of organic matter (e.g., manure, compost) and cover crops can serve as substitutes for mineral fertilization with additional benefits to soil properties. Recycling of the pruned orchard material, olive pomace and olive mill wastewater, as well as the use of recycled wastewater for irrigation, are all potentially beneficial to olive orchard sustainability, but present the risk of environmental pollution. Some considerations regarding optimization of olive orchard nutrition are discussed.
Determination of relative root-zone water depletion (RRWD) thresholds to trigger irrigation is crucial to create optimal irrigation schedules targeting maximum yield and/or water productivity with ...limited water supply for a crop. In this study, a numerical procedure to determine RRWD thresholds was developed through coupling AquaCrop software with genetic-simplex algorithms. Using a two-year field lysimetric experiment for winter wheat conducted in the North China Plain (NCP), AquaCrop adequately simulated canopy cover, final aboveground biomass, grain yield, seasonal evapotranspiration, and soil water storage, with the normalized root mean squared error (NRMSE) smaller than 15 % and determination coefficient (R2) larger than 0.84. The global optimum range of RRWD thresholds was preliminarily determined using the genetic algorithm, and subsequently final RRWD thresholds were optimized by fine tuning using the simplex algorithm. The RRWD threshold combinations (composed of the RRWD thresholds to trigger different sequential irrigation events) for varying number of irrigation events (i.e.1–4) were optimized based on 39 years of historical meteorological data, and the effects of climate change on the optimal crop yield (Ya, opt), water productivity (WPopt), and the combinations of optimized RRWD threshold (RRWDopt) were investigated. The results indicated that both Ya, opt and WPopt generally increased with time showing a tendency of gradually elevated annual CO2 concentration and seasonal average effective temperature. Irrespective of the number of irrigation events during the winter wheat growing season, the differences of RRWDopt for different combinations of irrigation sequence and event in the same kind of hydrological year were relatively small, with a coefficient of variation consistently less than 23 % and a mean of 8 %. When combinations of mean RRWDopt were applied into AquaCrop to trigger irrigation for winter wheat in various hydrological years, the simulated yield (Ya, sim) and water productivity (WPsim) under 1–4 irrigation events were found to be comparable to their respective optimums (Ya, opt and WPopt), with all the values of Ya, sim (WPsim) falling in the range of 92 %Ya, opt (90 %WPopt). Therefore, the mean RRWDopt should be helpful to formulate rational irrigation management strategies of winter wheat under changing climatic conditions in the NCP.
●AquaCrop was calibrated for simulating winter wheat growth and soil water depletion.●Relative root-zone water depletion (RRWD) thresholds were employed to trigger irrigation.●RRWD thresholds were optimized by coupling AquaCrop with genetic-simplex algorithms.●Effects of climate change on optimized RRWD threshold combinations were evaluated.●Mean optimized thresholds were useful in scheduling irrigation in changing climate.
Many functions have been proposed to describe the response of root water uptake to water and/or salinity stresses. In practice, choosing a reliable stress response function is challenging, ...particularly when water and salinity stresses occur simultaneously. To explore and quantify the effects of soil water and salinity conditions, separately and combined, on root water uptake, two experiments culturing winter wheat in artificial climate chambers were conducted with various water and salinity levels. As the key index, plant water status was evaluated by: a) considering the relative position of water and salinity to roots; b) rectifying estimation of potential transpiration for stressed plants; c) excluding data during recovery periods dominated by the hysteresis process of historical stress; and d) quantifying the interaction between water and salinity stresses. Including only one fitting parameter and two water or salinity thresholds with clear physical meaning and available recommendations, concave-convex function could quantify the effects of water or salinity stress more accurately than the others, leading to more reliable estimation of relative transpiration rate (RMSE < 0.07, R2 > 0.91, MAE < 0.24). Under combined water-salinity stress conditions, neither an additive nor multiplicative approach was able to describe the interaction accurately. In addition to cumulative effect, by quantifying cross-adaptation effect with an exponential function, the multiplicative concave-convex functions significantly improved the estimation of relative transpiration rate for water- and salinity-stressed plants (RMSE < 0.08, R2 > 0.72, MAE < 0.28). Nevertheless, mechanisms underlying the interaction between water and salinity stresses are still unclear and should be further investigated. To avoid the hysteresis effect of historical stress, excluding data during recovery periods was helpful, but its quantitative characterization is also necessary for accurate simulation of root water uptake and should be further studied.
•Improved method to screen soil water and salinity stress response functions.•Concave-convex soil water and salinity stress response functions are superior.•Cross-adaptation effect between water and salinity stresses was quantified.•Multiplicative approach was improved to quantify combined water and salinity stress.
As a critical index for irrigation scheduling, plant water deficit index (PWDI) is defined as the ratio of water deficit to water demand to reflect the extent of abiotic stresses such as water and ...salinity. Recently, smart irrigation scheduling, according to PWDI thresholds to maintain desirable or acceptable stress levels, has been suggested to maximize yields while minimizing negative environmental effects under non-saline conditions. To investigate and quantify the potential for PWDI-driven irrigation on agricultural production under conditions of salinity, a two-year experiment with six specific thresholds was conducted in Shawan of Xinjiang for drip-irrigated cotton under film mulch. Results indicated that, with increasing PWDI threshold, irrigation depth per event increased, while irrigation frequency and total volume decreased. Consequently, the soil water and salt environment deteriorated, resulting in less nutrient uptake, slower growth, and lower yield and net profit. With particularly high PWDI thresholds leading to serious stress conditions, fiber quality was also negatively affected. Within a designed range of PWDI thresholds between 0.39 and 0.62, an elliptic function characterized the processes of water application, yield and net profit (R2 ≥ 0.95), and water productivity could be described by a parabolic function (R2 = 0.77). These quantitative results were used to provide guidelines for smart irrigation scheduling under local conditions considering water management measures and market prices of cotton. For a reference market price of 7.5 CNY kg-1, a PWDI threshold of 0.49 was found to optimize economic benefits while maximizing water productivity. When prices of cotton are prohibitively low, a lower threshold should be considered to obtain an acceptable net profit. Otherwise, a higher threshold would be preferable to use water more efficiently. Further verification and improvement are necessary to deal with more complex scenarios, such as, considering crop sensitivity to water and salinity stresses at different growth stages and optimizing irrigation depth per event.
•Plant water deficit index (PWDI) is used for smart irrigation under saline conditions.•PWDI threshold affects soil water and salt dynamics, crop growth and production.•Relations between PWDI threshold and water productivity/net profit are quantified.•A PWDI threshold of 0.49 was used to balance local ecological and economic benefits.•Irrigation regime is optimized with market factors and water management measures.
Excessive use of N fertilizers in agriculture often leads to NO3− accumulation in the unsaturated zone and to groundwater pollution. There is uncertainty regarding the variability in fertilizer ...transport and uptake efficiency due to the lack of studies based on continuous nondestructive measurements in unsaturated soils. In this study, we analyzed solute dynamics across the unsaturated zone underlying cultivated agricultural fields. Commercial crop rotations under four treatments, comprising two N fertilization regimes and two irrigation water salinity levels, were conducted in loess soil in the semiarid climate of the northern Negev Desert, Israel. The impact of the various treatments on water and solute dynamics below the root zone was monitored by a vadose zone monitoring system. The patterns of variations in soil water content and solute concentrations were analyzed using nonnegative tensor factorization. We found that irrigating using higher salinity water resulted in the earlier arrival of wetting fronts to the deeper layers and increased NO3− concentrations relative to the lower salinity treatments. Surprisingly, this effect was only seen in the deeper soil levels, whereas there was no significant difference in the arrival times and concentrations in the upper soil layers. Possible mechanisms are suggested and discussed.
An accessible solution capable of reliably predicting plant‐environmental interrelationships for variable species, climates, soils, and management options is a necessary tool for creating sustainable ...agriculture and environmental preservation. A mechanism‐based analytical solution, the first of its kind that considers multiple environmental variables and their combined effects on plant response, was developed and tested. Water uptake by plants, water and salt leakage below the roots, and yield are calculated by solving for transpiration in a single mathematical expression according to limitations imposed by root zone salinity and water status. Input variables include the quantity and salinity of applied water, terms for plant sensitivity to salinity and to water stress, potential evapotranspiration, and soil hydraulic parameters. Where water was not limiting, regression of predicted versus measured data resulted in r2 = 0.96 with slope of 0.937 and intercept of 0.033 (not different from 1 and 0 at 99% confidence), where irrigation varied and salinity was not limiting the r2 = 0.94 with slope of 0.906 and intercept of 0.044 (not different from 1 and 0 at 99% confidence), where both salinity and water levels varied r2 = 0.94 with slope of 0.966 and intercept of 0.033 (not different from 1 and 0 at 99% confidence). Application of the model for agricultural and environmental management and economic analysis is discussed. For example, a farmer in the Arava in Israel where irrigation water salinity is high (electrical conductivity of 3 dS m−1) cannot expect to reach greater than 70% of the potential yield for a pepper crop with any amount of irrigation. By choosing melon, the farmer can achieve 90% of potential yield with the same quality and quantity of water.
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