An observational study was conducted in the northern Sacramento Valley in California, United States to determine crop water use and crop coefficients of three adjacent young Nonpareil/Monterey almond ...orchards. Methods used to quantify evapotranspiration estimates of crop water use include (1) a soil water balance and (2) a land surface energy balance using eddy covariance. Three adjacent almond orchards that were planted in 2016, 2017, and 2018 were monitored from 2018 to 2020. Actual crop coefficients were determined using actual evapotranspiration estimates from each orchard and short grass reference evapotranspiration from the Gerber South California Irrigation Management Information System station. Results showed that crop water use and crop coefficients increased until the 4th year, indicating the need to closely consider tree development and orchard age as factors in irrigation scheduling of young almond trees. The results led to the conclusion that farmers should use development or age-specific crop coefficients in developing orchards for irrigation scheduling until the 4th year when they can start using mature almond crop coefficients. The mid-season actual crop coefficients were 0.35, 0.55, 0.88, 1.04, and 0.99 for 1-, 2-, 3-, 4-, and 5-year-old almond orchards. This study has generated baseline data on crop water requirements of young almond orchards that could be useful for (1) developing irrigation scheduling tools for young almond orchards, and (2) determining water budgets for areas with new almond orchards.
Regime shifts of major salinity constituents (Ca, Mg, Na, K, SO
4
, Cl, HCO
3
, and NO
3
) in the lower Salinas River, an agricultural ecosystem, can have major impacts on ecosystem services central ...to continued agricultural production in the region. Regime shifts are large, persistent, and often abrupt changes in the structure and dynamics of social-ecological systems that occur when there is a reorganization of the dominant feedbacks in the system. Monitoring information on changes in the system state, controlling variables, and feedbacks is a crucial contributor to applying sustainability and ecosystem resilience at an operational level. To better understand the factors driving salinization of the lower Salinas River on the central coast of California, we examined a 27-year record of concentrations of major salinity constituents in the river. Although limited in providing an understanding of solute flux behavior during storm events, long-term “grab sampling” datasets with accompanying stream discharges can be used to estimate the actual history of concentrations and fluxes. We developed new concentration–discharge relationships to evaluate the dynamics of chemical weathering, hydrological processes, and agricultural practices in the watershed. Examinations of long-term records of surface water and groundwater salinity are required to provide both understanding and perspective towards managing salinity in arid and semi-arid regions while also enabling determination of the influence of external climatic variability and internal drivers in the system. We found that rock weathering is the main source of Ca, Mg, Na, HCO
3
, and SO
4
in the river that further enables ion exchange between Ca, Mg, and Na. River concentrations of K, NO
3
, and Cl were associated with human activities while agricultural practices were the major source of K and NO
3
. A more direct anthropogenic positive trend in NO
3
that has persisted since the mid-1990s is associated with the lag or memory effects of field cropping and use of flood irrigation. Event to inter-year scale patterns in the lower Salinas River salinity are further controlled by antecedent hydrologic conditions. This study underscores the importance of obtaining long-term monitoring records towards understanding watershed changes-of-state and time constants on the range of driving processes.
Salinity and nutrient deficiency, especially nitrogen, are two important factors that reduce the crop yield in arid and semi-arid regions. Water absorption by root is an important factor in the ...distribution of soil-water and solute transport. In order to investigate of water uptake by the plant roots under simultaneous water, salinity, and nitrogen stresses by mathematical models, four levels of soil water content (50, 75, 100, and 120 percent of water requirement), six levels of salinity (1, 2, 4, 6, 8, and 10dS/m) and three levels of nitrogen (zero, 50, and 100 percent of the fertilizer demands) was applied on tomato plant with three repetitions. The experiments were carried out in a factorial randomized complete block design. Mathematical models of the root water uptake under simultaneous salinity and nitrogen stresses showed modified Mitscherlich-Baule (MB) model fitted better while under simultaneous water and nitrogen stresses, Mitscherlich-Baule and Feddes (MB-F) has best fitted regarding measured data. The results showed that derived models of Mitscherlich-Baule and Homaee (MB-H), Mitscherlich-Baule and Feddes (MB-F), Mitscherlich-Baule and Dirksen (MB-D), Mitscherlich-Baule and van Genuchten (MB-VG) have more accuracy under simultaneous water and nitrogen stresses and MB-F model has the best fit for measurement of data in comparison with other models. Under simultaneous water, salinity, and nitrogen stresses, multiplicative MB-MB-F model best fitted in comparison with other proposed models. Moreover, the research results showed that in severe salinity, increasing the amount of fertilizer doesn't increase crop yield while increasing the amount of irrigation water increases yield.
To ensure agricultural sustainability and desirable environmental outcomes, stakeholders need systems-based model-driven decision support tools. The objective of this study was to develop a global ...scale web-based geospatial crop modeling application called Food, Agriculture, and Resource Management system (FARMs), to simplify the application of the crop simulation model —Decision Support System for Agrotechnology Transfer (DSSAT) without requiring users to create input weather, climate, and soil files. FARMs was built based on open source Geographic Information System (GIS) technologies and DSSAT to allow for adaptive management through its ability to perform in-season yield predictions for alfalfa and maize, currently. Validation of FARMs against variety trial data in California was acceptable between measured and simulated yields for alfalfa. The work done in this study showed how a complex model like DSSAT can be translated into a useable web-based decision support tool for near-real-time simulation with the help of open-source GIS technologies.
•Processing tomato was irrigated according to model-based irrigation schedules.•Deterministic and stochastic simulation-optimization approaches were implemented.•Irrigation treatment based on neutron ...probe readings was used as benchmark.•No significant difference in yield was observed between the treatments.•No substantial difference in water use efficiency was observed between treatments.
Due to climate change, increased regulation of water resources and competition from other beneficial uses, the agricultural sector is under pressure to use water more efficiently. This paper reports the field evaluation of two model-based simulation-optimization approaches for irrigation scheduling: deterministic optimization and stochastic optimization. The field experiments were conducted at the University of California Davis research farm with a processing tomato crop. The crop growth simulation model used in the study was DSSAT-CROPGRO processing tomato. In order to mitigate the impact of weather forecasts inaccuracies, irrigation schedules were updated every 5 to 10 days, depending on operational constraints. These updates were performed via custom graphical user interfaces that enabled the user to visualize the expected outcomes of various decisions or scenarios before choosing which irrigation schedule to implement. An irrigation treatment based on manual monitoring of soil water content with a field-calibrated neutron probe served as benchmark. The model-based treatments achieved yields and water use efficiencies that were not significantly different from those obtained in the neutron probe-based treatment. These results demonstrate the high potential of model-based simulation-optimization approaches for in-season adaptive irrigation scheduling, especially since neutron probes, which are considered one of the most accurate indirect methods of measuring soil water content, are not commonly used by growers.
Proximal sensing is being integrated into vineyard management as it provides rapid assessments of spatial variability of soils’ and plants’ features. The electromagnetic induction (EMI) technology is ...used to measure soil apparent electrical conductivity (EC
a
) with proximal sensing and enables to appraise soil characteristics and their possible effects on plant physiological responses. This study was conducted in a micro irrigated Cabernet Sauvignon (
Vitis vinifera
L.) vineyard to investigate the technical feasibility of appraising plant water status and its spatial variability using soil EC
a
and must carbon isotope ratio analysis (δ
13
C). Soil temperature and soil water content were monitored
in-situ
using time domain reflectometry (TDR) sensors. Soil EC
a
was measured with EMI at two depths 0–1.5 m (deep EC
a
) and 0–0.75 m (shallow EC
a
) over the course of the crop season to capture the temporal dynamics and changes. At the study site, the main physical and chemical soil characteristics, i.e. soil texture, gravel, pore water electrical conductivity (EC
e
), organic carbon, and soil water content at field capacity, were determined from samples collected auguring the soil at equidistant points that were identified using a regular grid. Midday stem water potential (Ψ
stem
) and leaf gas exchange, including stomatal conductance (
g
s
), net carbon assimilation (
A
n
), and intrinsic water use efficiency (WUE
i
) were measured periodically in the vineyard. The δ
13
C of produced musts was measured at harvest. The results indicated that soil water content (relative importance = 24%) and texture (silt: relative importance = 22.4% and clay: relative importance = 18.2%) were contributing the most towards soil EC
a
. Deep soil EC
a
was directly related to Ψ
stem
(r
2
= 0.7214) and
g
s
(r
2
= 0.5007). Likewise, δ
13
C of must was directly related to Ψ
stem
(r
2
= 0.9127),
g
s
(r
2
= 0.6985), and
A
n
(r
2
= 0.5693). Results from this work provided relevant information on the possibility of using spatial soil EC
a
sensing and δ
13
C analysis to infer plant water status and leaf gas exchange in micro irrigated vineyards.
Low-cost, accurate soil water sensors combined with wireless communication in an internet of things (IoT) framework can be harnessed to enhance the benefits of precision irrigation. However, the ...accuracy of low-cost sensors (e.g., based on resistivity or capacitance) can be affected by many factors, including salinity, temperature, and soil structure. Recent developments in wireless sensor networks offer new possibilities for field-scale monitoring of soil water content (SWC) at high spatiotemporal scales, but to install many sensors in the network, the cost of the sensors must be low, and the mechanism of operation needs to be robust, simple, and consume low energy for the technology to be practically relevant. This study evaluated the performance of a resistivity-capacitance-based wireless sensor (Sensoterra BV, 1018LE Amsterdam, Netherlands) under different salinity levels, temperature, and soil types in a laboratory. The sensors were evaluated in glass beads, Oso Flaco sand, Columbia loam, and Yolo clay loam soils. A nonlinear relationship was exhibited between the sensor measured resistance (Ω) and volumetric soil water content (
). The Ω-θ relationship differed by soil type and was affected by soil solution salinity. The sensor was extremely sensitive at higher water contents with high uncertainty, and insensitive at low soil water content accompanied by low uncertainty. The soil solution salinity effects on the Ω-θ relationship were found to be reduced from sand to sandy loam to clay loam. In clay soils, surface electrical conductivity (
) of soil particles had a more dominant effect on sensor performance compared to the effect of solution electrical conductivity (
). The effect of temperature on sensor performance was minimal, but sensor-to-sensor variability was substantial. The relationship between bulk electrical conductivity (
) and volumetric soil water content was also characterized in this study. The results of this study reveal that if the sensor is properly calibrated, this low-cost wireless soil water sensor has the potential of improving soil water monitoring for precision irrigation and other applications at high spatiotemporal scales, due to the ease of integration into IoT frameworks.
Water scarcity and soil salinization are the top abiotic stresses impeding agricultural production in arid and semi‐arid regions. To evaluate maize growth is depressed by water stress or salt stress ...independently as well as in combination under drip irrigation, a 3‐year field experiment was conducted in the Hetao Irrigation District, north‐west China. The soil was moderately saline with ECe (electrical conductivity of saturated extract) of 7.1 dS/m. Five threshold values of soil matric potential (SMP): −10 kPa (S1), −20 kPa (S2), −30 kPa (S3), −40 kPa (S4), and −50 kPa (S5), were used to trigger a 10‐mm drip irrigation. With triplicate for each treatment, 15 plots were arranged in a randomized block design permanently during the experimental period. Results showed that the higher SMP facilitated the formation of low‐salinity zone. The water holding depths in root zone were generally above the refill point (threshold of readily available water, 0.23 cm3/cm3 for maize) during the growing seasons for all treatments, indicating maize could extract water easily from soil. Controlling SMP > −30 kPa (S1, S2, S3) produced the higher leaf area index, specific leaf area, biomass and grain yield significantly than S4 and S5; however, no significant difference in relative chlorophyll contents was detected among treatments. Grain yield was reduced by 6.8% per dS/m increase in soil ECe beyond salt tolerance of maize. Based on the soil readily available water for maize growth, crop's responses and data analysis, it could be concluded that salt stress, rather than water stress, was the key factor causing the reduced grain yield in this study. Taking into account the grain yield and water‐use efficiency, SMP threshold of −30 kPa was recommended for drip irrigation maize in this saline soil. These findings are conducive to the extension of drip irrigation, and increasing the resilience of crop production under the arid saline condition.
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