Crop Water Use Research Articles

Response of soil moisture and water use efficiency to straw mulching amount and mulching period in black soil zone of northeast China

To reveal the mechanisms of straw mulching amounts and mulching periods on soil moisture in the black soil zone of Northeast China. Three types of straw mulching (0.4, 0.8, and 1.2 kg/m2) and two mulching periods (sowing stage and three-leaf stage) were set up as interactive experiments, and no straw mulching was used as the control (CK) to analyze the response mechanisms of soil moisture content, water consumption, and water use efficiency to straw mulching periods and mulching amounts at different depths. The results showed that straw mulching improved the moisture storage capacity compared with no straw mulching, and the straw mulching rate of 0.8 kg/m2 at the three-leaf stage improved the moisture storage capacity and reduced the water consumption capacity compared with the straw mulching at the sowing stage, CK and other straw mulching treatments at the three-leaf stage; the crop yield and water use efficiency increased and then decreased with the increase of straw mulching. The increase of crop yield and water use efficiency under the straw mulching treatments at the three-leaf stage was higher than that under the same straw mulching treatments at the sowing stage. The analysis of the dual effects of straw mulching amounts and mulching periods on moisture gain and loss showed that the straw mulching amounts of 0.8 kg/m2 at the three-leaf stage had the best effect on soil moisture characteristics and water use efficiency.

Deficit irrigation combined with nitrogen application in the early growth stage of sugar beet increases the production capacity of canopy and avoids yield loss.

Properly reduced irrigation combined with nitrogen (N) application can be used to improve crop water use efficiency (WUE) in arid regions, but its effect on sugar beet is unknown at present. A two-year field experiment was conducted to evaluate the effects of N application (N0, 0; N1, 150; N2, 225 kg N ha-1 ) on the canopy production capacity (CPC), yield and WUE of sugar beet under normal irrigation (W1, 70% of field capacity (FC)) and deficit irrigation (DI) (W2, 50% FC) in the early growth stage (EGS). The results showed that the W2 treatment reduced the CPC by reducing gas exchange, leaf area index (LAI) and chlorophyll content (SPAD value) of sugar beet leaves compared to the W1 treatment. However, DI combined with N application increased these parameters. Specifically, N application increased the net photosynthetic rate by 40.7% by increased gas exchange, SPAD and LAI compared to the N0 treatment. In addition, N application increased WUE by 12.5% by increasing thickness of upper surface, stomatal aperture and cross-sectional area of petiole. This ultimately led to a significant increase in taproot yield (TY; 19.7%) and sugar yield (SY; 57.6%). Although the TY of the N2 treatment was higher than that of the N1 treatment, the SY and WUE did not increase significantly and the harvest index decreased significantly by 9.3%. DI combined with 150 kg N ha-1 in the EGS of sugar beet increases the WUE in arid areas while avoiding yield loss by improving the CPC. © 2023 Society of Chemical Industry.

The effect of silicon on the antioxidant system of tomato seedlings exposed to individual and combined nitrogen and water deficit

AbstractExploring sustainable strategies for improving crop water and nitrogen use efficiency is essential. Silicon (Si) has been reported as a beneficial metalloid for plants since it alleviates several abiotic stresses (including drought) by triggering the plants' antioxidant system. However, its role in mitigating the negative impact of nitrogen (N) deficit alone or when combined with water (W) deficit is not well studied. This study applied 0 or 2 mM of Na₂SiO3 to 3‐week‐old tomato cv. Micro‐Tom seedlings that were grown under the following conditions: control (CTR; 100%N + 100% Field Capacity), N deficit (N; 50% N + 100% Field Capacity), water deficit (W; 100% N + 50% Field Capacity) or combined stress (N + W; 50% N + 50% Field Capacity). The Si effect on tomato plant growth depended on the type of stress. Si could only alleviate stress caused by N + W deficit resulting in a higher root dry weight (by 28%), total dry weight (by 23%) and root length (by 37%). Alongside this, there was an increase in the antioxidant (AOX) system activity with the root activity of ascorbate peroxidase and catalase enzymes being enhanced by 48% and by 263%, respectively. Si application also enhanced AOX enzyme activity when tomato plants were subjected to individual deficits but to a lesser extent. In conclusion, Si‐treated tomato plants could efficiently modulate their AOX networks in a situation of combined N and water limitation, thus mitigating some of the adverse effects of this combined stress.

Accuracy of Estimated Crop Evapotranspiration Using Locally Developed Crop Coefficients against Satellite-Derived Crop Evapotranspiration in a Semiarid Climate

Actual crop evapotranspiration (ETa) is measured or estimated using different methods, and its accuracy is critical for water management under precision agriculture. The objective of this study was to compare maize ETa estimated by the two-step approach using a locally developed crop coefficient curve with satellite-retrieved evapotranspiration by six models incorporated in the OpenET to identify the best evapotranspiration estimation alternatives to the two-step approach for water management in northern New Mexico. Maize (Zea mays L.) was planted at the NMSU Agricultural Science Center at Farmington from 2017 to 2022 and uniformly managed across years. Water management in plants was based on maize’s actual evapotranspiration estimated as the product of the reference evapotranspiration and the local crop coefficient, which is described as a third-order polynomial function of the accumulated heat units by maize plants. For the same growing seasons, maize ETa was retrieved from satellite, and was estimated by six models listed within the OpenET from 2017 to 2022. The results show that maize daily ETa was consistently smaller when measured by SIMS and PT-JPL during maize initial and actively growing stages, while ETc(kc), SIMS and eeMETRIC showed similar maize daily ETa during maize full canopy development and mid-season, and which overcome the evapotranspiration estimated by DisALEXI, PT-JPL, geeSEBAL, and SSBop. ETc(kc) drastically dropped and became the lowest value among all ETa estimation models after the first fall snow or the first killing frost. Regarding the seasonal average, all six models included in OpenET showed smaller maize evapotranspiration. Maize seasonal evapotranspiration varied from 589.7 to 683.2 mm. eeMETRIC compares most similarly to the ETc(kc) model, followed by SIMS, with percent errors of 2.58 and 7.74% on a daily basis and 2.43 and 7.88% on a seasonal basis, with the lowest MBE and RMSE values, respectively, and could be used as an alternative for maize actual daily evapotranspiration for water management in northern New Mexico. The results of this study could be used by water managers and crop growers to improve water management in the Four Corners region, using eeMETRIC for crop water use to improve water management and conservation under sustainable agriculture.

Effect of furrow irrigation systems and irrigation levels on maize agronomy and water use efficiency in Arba Minch, Southern, Ethiopia

Improved irrigation water management is the main strategy to improve water use efficiency in areas with limited water resources. Optimizing scarce water by selecting suitable furrow irrigation systems in arid and semi-arid parts of Ethiopia is rarely practiced. A field experiment was carried out to evaluate the effect of conventional, alternate, and fixed furrow irrigation systems with three levels of irrigation (100%ETc, 75%ETc, and 50%ETc) on maize agronomy and water use efficiency in Arba Minch, Southern, Ethiopia. The experimental study had nine treatments under a randomized complete block design with three replications. Furrow irrigation system and deficit irrigation levels had a significant impact (P < 0.01) on maize agronomy, grain yield, and water use efficiency. The maximum grain yield of 7.99 ton ha−1 obtained under a conventional furrow irrigation system at 100%ETc was significantly higher than the other treatments and the minimum grain yield of 4.24 ton ha−1 obtained under a fixed furrow irrigation system at 50%ETc was significantly inferior as compared to other treatments. The maximum values of crop, field, and expense water use efficiencies were 2.49, 2.80, and 1.72 kg m−3 under conventional furrow irrigation at 50%ETc, respectively. The minimum values of crop, field, and expense water use efficiencies were 1.47, 1.28, and 1.05 kg m−3 under a fixed furrow irrigation system at 100%ETc, respectively. A conventional furrow irrigation system at 50%ETc can increase 0.64 ha net additional irrigable land pre each hectare compared to the conventional furrow irrigation system at 100%ETc. Water saving up to 50%ETc in conventional furrow irrigation can solve the water shortage problem by improving water use efficiency with insignificant yield reduction.

The Effect of Dry Farming and Water Stress under Subsurface Drip Irrigation System on Water and Rice Productivity

A field experiment was carried out during the 2020 season at the College of Agricultural Engineering/ University of Baghdad, Al-Jadriya to evaluate the effect of dry farming when applying water stress under the subsurface drip irrigation system on water productivity and rice yield. The experiment was conducted with three levels of irrigation water stress when 10, 20 and 40% of the available water was depleted and in three dimensions between drip lines 10, 15 and 20 cm. The experiment was designed according to a randomized complete block design, according to the split plot design, with three replications. Determine the depth of irrigation water depending on the moisture depletion of the soil, the results showed a difference in the depth of water according to the moisture depletion, which amounted to 900 mm. Season-1 treatment for 10% depletion and decreased to 10 and 16.6% when 20 and 40% of the prepared water was depleted, respectively. The intervention between drip lines and irrigation treatments led to a significant increase in grain yield when using a distance of 10 cm and irrigation when 10% of the available water was depleted. There were no significant differences in grain yield at I10 despite the difference in the distance between the drip lines. The efficiency of field and crop water use and the profitability of water outperformed I10.

A global synthetic analysis of the effects of reclaimed water irrigation on crop yield and water use efficiency

Abstract To quantitatively evaluate the effect of RW irrigation on yield, WUE, and IWUE, and identify aqueous, edaphic, and management factors that favor improved yield, WUE, and IWUE compared to control practices, a meta-analysis was conducted. The results indicated that RW irrigation is beneficial for improving crop yields, WUE, and IWUE (16.8, 23.8, and 18.7%, respectively). However, its effectiveness is highly dependent on the aqueous, edaphic, and management factors of the studies evaluated. Greater responses were found in practices using RW with a pH &amp;lt; 7 or a nitrogen content &amp;lt;100 mg/L. The soils with a pH ≥ 7, electrical conductivity between 2 and 4 dS/m, bulk density &amp;lt;1.35 g/cm3, and/or initial nitrogen content between 200 and 2,000 mg/kg produced the highest effect size. Furthermore, using a surface drip irrigation system, with a nitrogen fertilizer rate &amp;lt;1,000 kg/ha and irrigation level at 100% crop evapotranspiration are effective ways to use RW. Our findings highlight the potential of RW irrigation to improve crop yield, WUE, and IWUE and identify the conditions under which these results can be achieved. These results can provide a better understanding of RW irrigation and guide the practice of RW utilization in the future.

Fractional coefficient for estimating physiologically meaningful and diurnal transpiration cycle weighted VPD from daily ambient environmental data

Appropriate representation of environmental conditions via meaningful metrics is critical for their effectiveness in modeling crop physiological and resource use processes. Vapor pressure deficit (VPD) is a primary determinant of crop water use efficiency, commonly reported as daily average. However, VPD can vary substantially during the day in relation to diurnal cycle of transpiration, in which case daily average VPD may not suffice. In such scenarios, integrating VPD over the course of diurnal transpiration cycle into a weighted VPD (VPDw) can be physiologically meaningful as a metric. The goal of this research is to characterize the fractional coefficient (Frac) that can be used to effectively calculate VPDw from daily temperature and relative humidity data without the need for sub-daily environmental data. Site-specific and seasonal estimates of Frac, which represent the relative positioning of VPDw to diurnal extremes of saturation vapor pressure are currently lacking for semi-arid regions. To address this, we quantified Frac at 101 sites in the U.S. Central Plains using long-term (1982–2019) hourly and daily radiation and VPD datasets. Frac varied substantially across the region, with growing season mean values ranging from 0.59 to 0.92. Summer months had the highest Frac values with relatively lower uncertainty as compared to lower Frac during winter. Local observations of Frac deviated significantly from previously assumed stationary estimates implying that site-specific and month-specific Frac may be necessary for robust water use estimations. VPDw measured at an experimental site in Central U.S. Plains explained greater variance in daytime crop transpiration than daily mean VPD in maize, soybean, and sorghum canopies. Site-specific Frac was also assessed to perform better than commonly used Frac estimate of 0.75 to explain day-to-day variation in transpiration, demonstrating effective use of long-term mean Frac values presented here to estimate VPDw using daily datasets.

Farm consolidation and turnover dynamics linked to increased crop diversity and higher agricultural input use

ContextCrop-type composition and configuration at field and landscape scales are known to impact ecological functions in agricultural landscapes. However, links between regional farmland structures (e.g., variable farm size, ownership, configuration, etc.), which are important determinants of farm-level management decisions, and subsequent changes in agroecosystem impacts, remain understudied.Objective:To investigate these dynamics, we examined relationships between changing farm structures, as indicated by farm consolidation and persistence, and concurrent changes in crop diversity and agricultural resource use between 2002 and 2018 in Kern County, California.Methods:We integrated parcel-level datasets documenting farm size, operatorship, crop cover, pesticide usage and evapotranspiration rates for 2002 and 2018. We then applied seemingly unrelated regression analyses to quantify potential relationships between these key variables.Results and conclusions:In our study area we observed low (28%) persistence of farm operators from 2002 to 2018 and farm consolidation, as evidenced by a 43% increase in farm midpoint size in the studied time period. We further found significant associations between farm structures and agro-environmental outcomes. A doubling in farm size was associated with an 8% increase in crop diversity, but also with an 18% increase in pesticide-use and a 7% increase in water use at the farm level, raising concerns about the impact of large farms on landscape-scale resource use. Both crop diversity and water use were higher in persistent farms (8% and 11%, respectively) than in replaced or emergent farms. Our findings illustrate how regional shifts in farm size and operatorship may link to changes in crop diversity and resource use. SignificanceGiven continued concerns about the impacts that landscape simplification, pesticide use, and water shortages may have on agroecosystems both in our study region and beyond, our study highlights regional farm structure dynamics as a key element to investigate further and to consider in policies aiming to increase the sustainability of future agricultural landscapes.

Modelling Crop Evapotranspiration and Water Use Efficiency of Maize Using Artificial Neural Network and Linear Regression Models in Biochar and Inorganic Fertilizer-Amended Soil under Varying Water Applications

The deficit irrigation strategy is a well-known approach to optimize crop water use through the estimation of crop water use efficiency (CWUE). However, studies that comprehensively reported the prediction of crop evapotranspiration (ETc) and CWUE under deficit irrigation for improved water resources planning are scarce. The objective of the study is to predict seasonal ETc and CWUE of maize using multiple linear regression (MLR) and artificial neural network (ANN) models under two scenarios, i.e., (1) when only climatic parameters are considered and (2) when combining crop parameter(s) with climatic data in amended soil. Three consecutive field experimentations were carried out with biochar applied at rates of 0, 3, 6, 10 and 20 t/ha, while inorganic fertilizer was applied at rates of 0 and 300 Kg/ha, under three water regimes: 100% Full Irrigation Treatment (FIT), 80% and 60% FIT. Seasonal ETc was determined using the soil water balance method, while growth data were monitored weekly. The CWUE under each treatment was also estimated and modelled. The MLR and ANN models were developed, and their evaluations showed that the ANN model was satisfactory for the predictions of both ETc and CWUE under all soil water conditions and scenarios. However, the MLR model without crop data was poor in predicting CWUE under extreme soil water conditions (60% FIT). The coefficient of determination (R2) increased from 0.03 to 0.67, while root mean-square error (RMSE) decreased from 4.07 to 1.98 mm after the inclusion of crop data. The model evaluation suggests that using a simple model such as MLR, crop water productivity could be accurately predicted under different soil and water management conditions.

Long-Term Nutrient Cycle in Improved Grain Yield of Dryland Winter Wheat (Triticum aestivum L.) under Hydrological Process of Plant Ecosystem Distribution in the Loess Plateau of China.

Precipitation is the major cause of crop yield variation in rainfed agriculture production in the Loess Plateau. As over fertilization is economically and environmentally undesirable, and crop yield and the resulting returns for N input are uncertain when rainfall variability is high, optimizing N management according to precipitation during fallow season is vital for efficient crop water use and high yield in dryland rainfed farming systems. Results show that the nitrogen treatment rate of 180 treatment significantly increased the tiller percentage rate, and the leaf area index at anthesis, the jointing anthesis, anthesis maturity dry matter, and nitrogen accumulation was closely related to yield. N150 treatment compared to N180 treatment significantly increased the percentage of ear-bearing tiller by 7%, dry substance accretion from jointing to anthesis by 9%, and yield by 17% and 15%, respectively. Our study has important implications for the assessment of the effects of fallow precipitation, as well as for the sustainable development of dryland agriculture in the Loess Plateau. Our results indicate that adjusting N fertilizer inputs based on summer rainfall variation could enhance wheat yield in rainfed farming systems.

Data-driven irrigation scheduling increases the crop water use efficiency of Cabernet Sauvignon grapevines

In the context of water management in agriculture, irrigation scheduling is critically important as it optimises water application to crops and can also target specific production goals. However, there is no consensus on the ideal irrigation scheduling strategy regarding crop water use efficiency (WUEc). In a premium Cabernet Sauvignon vineyard in Coonawarra, South Australia, over three growing seasons, irrigation scheduling strategies based on experience or historical knowledge (‘GROW’ treatment) were compared to data-driven strategies including crop evapotranspiration, and plant and soil water status thresholds to evaluate their effects on leaf- and vine-level WUEs. A final treatment, GROW + , that doubled the GROW level of irrigation was also evaluated in the third season. The WUE metrics were determined at the leaf, vine, and fruit scales as intrinsic WUE (WUEi), crop WUE (WUEc), and carbon isotope ratio (δ13C), respectively. Furthermore, the irrigation strategies were evaluated in the background of two contrasting soil types: Terra Rossa (light clay, well-drained) and Rendzina (heavier clay, poorly drained). Seasonal soil and vine water status, leaf gas exchange, and light interception were measured, and yield components and pruning weights were obtained following harvest. The amount of seasonal irrigation water based on the data-driven strategies was up to 65% lower across both soil types compared with the GROW or GROW + approaches. WUEi and δ13C were largely similar between treatments. However, for vines grown on Terra Rossa soil, little to no yield penalty was observed when data-driven irrigation scheduling was applied, in addition to increased WUEc values of up to 41%. It can be concluded that irrigation scheduling decisions based on data were superior to the conventional irrigation scheduling method on account of reducing irrigation water volume and increasing WUE, particularly in Terra Rossa soils.

Agronomic Considerations for Sustainable Intensification of Crop Production

Sustainable intensification of crop production is a multifaceted strategy aimed at meeting the increasing global demand for food while minimizing the environmental impact of agriculture. This article delves into key agronomic considerations crucial for achieving sustainable intensification. Conservation agriculture practices, including minimum tillage and crop residue retention, are explored for their role in promoting soil health and reducing erosion. Precision agriculture technologies, such as GPS and remote sensing, are highlighted for optimizing resource use. Crop diversification, rotation, and water use efficiency strategies are discussed to address issues of monoculture, nutrient imbalance, and water scarcity. Integrated nutrient management, incorporating organic sources and precision application, is examined for its contribution to soil fertility. Agroforestry and biodiversity promotion are explored as means to enhance ecosystem resilience. By integrating these agronomic considerations, farmers can contribute to a more sustainable and resilient agricultural system capable of meeting global food demands while safeguarding the environment.

Broadband Measurements of Soil Complex Permittivity.

Agriculture is a major consumer of freshwater and is often associated with low water productivity. To prevent drought, farmers tend to over-irrigate, putting a strain on the ever-depleting groundwater resources. To improve modern agricultural techniques and conserve water, quick and accurate estimates of soil water content (SWC) should be made, and irrigation timed correctly in order to optimize crop yield and water use. In this study, soil samples common to the Maltese Islands having different clay, sand, and silt contents were, primarily, investigated to: (a) deduce whether the dielectric constant can be considered as a viable indicator of the SWC for the soils of Malta; (b) determine how soil compaction affects the dielectric constant measurements; and (c) to create calibration curves to directly relate the dielectric constant and the SWC for two different soil types of low and high density. The measurements, which were carried out in the X-band, were facilitated by an experimental setup comprising a two-port Vector Network Analyzer (VNA) connected to a rectangular waveguide system. From data analysis, it was found that for each soil investigated, the dielectric constant increases notably with an increase in both density and SWC. Our findings are expected to aid in future numerical analysis and simulations aimed at developing low-cost, minimally invasive Microwave (MW) systems for localized SWC sensing, and hence, in agricultural water conservation. However, it should be noted that a statistically significant relationship between soil texture and the dielectric constant could not be determined at this stage.

Optimizing drip fertigation at different periods to improve yield, volatile compounds and cup quality of Arabica coffee.

How to improve and regulate coffee bean yield and quality through split fertilization in the whole life cycle of coffee is still unclear and deserves further study. A field experiment of 5-year-old Arabica coffee trees was conducted for 2 consecutive years from 2020 to 2022. The fertilizer (750kg ha-1 year-1, N-P2O5-K2O:20%-20%-20%) was split in three times at early flowering (FL), the berry expansion (BE), and the berry ripening (BR). Taking equal fertilization throughout the growth cycle (FL250BE250BR250) as the control check, variable fertilizations including FL150BE250BR350, FL150BE350BR250, FL250BE150BR350, FL250BE350BR150, FL350BE150BR250, and FL350BE250BR150. Leaf net photosynthetic rate (A net), stomatal conductance (g s), transpiration rate (T r), leaf water use efficiency (LWUE), carboxylation efficiency (CE), partial factor productivity of fertilizer (PFP), bean yield, crop water use efficiency (WUE), bean nutrients, volatile compounds and cup quality, and the correlation of nutrients with volatile compounds and cup quality was evaluated. FL350BE250BR150 had the maximum A net and g s, followed by FL250BE350BR150. The highest dry bean yield and WUE were obtained from FL250BE350BR150, which increased by 8.86% and 8.47% compared with FL250BE250BR250 in two-year average. The ash, total sugar, fat, protein, caffeine and chlorogenic acid in FL250BE350BR150 were 6.47%, 9.48%, 3.60%, 14.02%, 4.85% and 15.42% higher than FL250BE250BR250. Cluster analysis indicated FL150BE350BR250, FL250BE350BR150, FL350BE150BR250 and FL350BE250BR150 under medium roasted degree increased pyrazines, esters, ketones and furans, FL150BE350BR250 and FL250BE350BR150 under dark roasted degree increased ketones and furans. The aroma, flavor, acidity and overall score of medium roasted coffee were higher than dark roasted coffee, while the body score of dark roasted coffee was higher than medium roasted coffee. The nutrient contents were correlated with the volatile compounds and cup quality. TOPSIS indicated that FL250BE350BR150 was the optimal fertilization mode in the xerothermic regions. The obtained optimum fertilization mode can provide a scientific basis for coffee fertilization optimization and management.

CROP WATER CONSUMPTION MODELLING AT OUTLET LEVEL BY USING REMOTE SENSING AND GIS

The enlarged demand of water due to agriculture expansion, increasing industrial and domestic needs, compounded with climate change is causing scarcity of water globally and Pakistan is also facing same conditions. Due to limited availability of water, it is necessary to adopt global best practices being employed for sustainable agricultural water management. Remote sensing techniques are being intensively used around the globe with confidence to monitor the crops growth and crop water use. The aim of the research is to develop crop water consumption monitoring system at the outlet level to regulate irrigation water distribution at farm level. Surface Energy Balance Algorithm for Land (SEBAL) is used to develop pilot case study for year 2017-18 at a distributary canal command level named 5R-Yousafwala located in Sahiwal District. Crop classification based on Landsat-8 imagery was provided by Punjab Irrigation Department. Landsat-8 and Sentinel-2 images were acquired for NDVI monitoring. Metrological data for Penman Monteith based evapotranspiration calculation was acquired from Global Land Data Assimilation System (GLDAS). Analogue cadastral maps of outlet command areas were converted to digital georeferenced format. The provided crop classification was verified after discussion with farmers during detailed field survey. In Rabi season of 2017-18, mean evapotranspiration (ET) actual was estimated about 352 mm, while in Kharif season of 2018, it was estimated as 425 mm. The crop water deficit was estimated as 36 % in rabi season and 30 % in kharif season. Irrigation share was only 37 % in Rabi season and 48% in Kharif season. Rainfall contributed 09 % in Rabi season and 30% in Kharif season. Groundwater was paramount contributor with 54 % share in rabi season while in Kharif season it contributed relatively minor share of 22%. The ET potential and ET actual fluctuate in all outlet commands due to the diverse crop cover and economic capacity to pump groundwater. The results could be proved very useful for irrigation department to monitor and reform the irrigation supplies at particular outlets by observing the crop demand, weather conditions and crop stage instead of monitoring outlet discharge only.

Cropping pattern optimization considering water shadow price and virtual water flows: A case study of Yellow River Basin in China

Cropping pattern determines the agricultural water use requirement and efficiency, as well as economic benefits of crop production. Agricultural water resources include blue water (irrigation water) and green water (soil moisture from precipitation), which have different shadow prices. The virtual water (VW) flow embedded in the interregional food trade causes burden shifts of water resources pressures in space. However, these intertwined economic and social effects have been neglected in regional cropping structure management. Using the case of the Yellow River Basin in China, here, we propose a two-stage multi-objective cropping pattern optimization scheme to maximize crop economic output, while minimize blue water scarcities (the first stage), and considered the criteria of maximum economic benefits of the interprovincial crop-related VW flows based on the shadow prices of crop green and blue water use (the second stage). Results show considerable differences in shadow prices of crop water use by colures, crops and location. With the optimized cropping pattern, which appropriately expands the planting scale of vegetables with higher water shadow price and comparative advantage and reduces the crop planting with lower water shadow price and intensive blue water consumption (e.g., soybean and wheat), blue water scarcity can be alleviated by ∼20%, combined with a ∼5% increase in crop economic output and up to ∼3% (800 million USD) higher benefits of VW flows. The premise to achieve above goals is to improve crop water resources utilization efficiency and break down the barriers of dietary preferences and trade policy.

Study and Development of IOT based Smart Irrigation System using Soil Moisture and Weather Prediction

Abstract: The smart irrigation system was developed to optimize water use of crops. The system has a distributed wireless network of soil-moisture temperature sensors placed in the root zone of the plants. Also, a gateway unit handles sensor information, triggers, actuators, and transmits data to the web application. The intelligence of The proposed system is based on a smart algorithm, which considers sensed data along with the weather forecast parameters like precipitation, air temperature, humidity, and UV for the near future. The complete system has been developed and deployed on a pilot scale, where the sensor node data is wirelessly collected over the cloud using web- services and a web-based information visualization and decision support system provides real-time information insights based on the analysis of sensor dataand weather forecast data. The paper describes the system and discusses in detail the information processing results of three weeks data based on the proposed algorithm. The system is fully functional and the prediction results are very encouraging

Balancing water and radiation productivity suggests a clue for improving yields in wheat under combined water deficit and terminal heat stress.

Sustaining crop yield under abiotic stresses with optimized resource use is a prerequisite for sustainable agriculture, especially in arid and semi-arid areas. Water and heat stress are major abiotic stresses impacting crop growth and yield by influencing complex physiological and biochemical processes during the life cycle of crops. In a 2-year (2015-2017) research, spring wheat cv. HD-2967 was grown under deficit irrigation and delayed sowing conditions to impose water and terminal heat stresses, respectively. The data were analyzed for seasonal crop water use, radiation interception, water productivity (WP), and radiation productivity (RP) under combined water deficit and terminal heat stresses. Seasonal crop water use was significantly affected by stresses in the order of water + terminal heat > water > terminal heat. Water stress showed minimal effect on the light extinction coefficient and consequently on seasonal intercepted photosynthetically active radiation (IPAR). However, seasonal IPAR was primarily affected by combined water + terminal heat and terminal heat stress alone. The slope of crop water use and IPAR, i.e., canopy conductance, an indicator of canopy stomatal conductance, was more influenced by water stress than by terminal heat stress. Results showed that linear proportionality between WP and RP is no longer valid under stress conditions, as it follows a curvilinear relation. This is further supported by the fact that independent productivity (either water or radiation) lacked the ability to explain variability in the final economic yield or biomass of wheat. However, the ratio of RP to WP explained the variability in wheat yield/biomass under individual or combined stresses. This suggests a clue for improving higher wheat yield under stress by managing WP and RP. The highest biomass or yield is realized when the ratio of RP to WP approaches unity. Screening of genotypes for traits leading to a higher ratio of RP to WP provides an opportunity for improving wheat productivity under stressed environments.

Irrigation Optimization via Crop Water Use in Saline Coastal Areas-A Field Data Analysis in China's Yellow River Delta.

Freshwater resources are becoming increasingly scarce in coastal areas, limiting crop productivity in coastal farmlands. Although the characteristic of crop water use is an important factor for water conservation in coastal farmlands, it has not been studied extensively. This study aimed to depict the water use process of soil-plant systems under saline stress in coastal ecosystems and optimize water management. An intensive observation experiment was performed within China's Yellow River Delta to identify the water use processes and crop coefficients (KC) and also quantify the impacts of salt stress on crop water use. The results show that shallow groundwater did not contribute to soil water in the whole rotation; KC values for wheat-maize, wheat-sorghum, and wheat-soybean rotation systems were 45.0, 58.4, and 57% less, respectively, than the FAO values. The water use efficiency of the maize (8.70) and sorghum (9.00) in coastal farmlands was higher than that of the soybean (4.37). By identifying the critical periods of water and salt stress, this paper provides suggestions for water-saving and salinity control in coastal farmlands. Our findings can inform the sustainable development of coastal farmlands and provide new insights to cope with aspects of the global food crisis.