Amount Of Irrigation Water Research Articles

Effect of Partial Root Drying and Deficit Irrigation on Yield and Water Use Efficiency of Tomato Grown Under Greenhouse

Water conservation strategies are becoming increasingly important as a result of the shortage of water and climate change. The purpose of this study is to address water-saving irrigation strategies by evaluating the effect of partial root drying irrigation (PRD) and Deficit Irrigation (DI) practice on the yield and water use efficiency of tomatoes (Shivam variety). The treatments were partial root drying (PRD) at 75% and 50% crop evapotranspiration, ETc (PRD25 and PRD50, respectively), and deficit irrigation (DI) at 75% and 50% of ETc (DI25 and DI50, respectively). The PRD practice requires wetting one half of the root zone and keeping the other half dry, consequently using less amount of irrigation water that was applied. In the successive irrigations, the wet and dry sides were alternated. Over a growing season after transplanting, the highest fruit yield was obtained under FULL irrigation (225 t ha-1). In comparison to deficit irrigation that received the same quantity of water, the PRD treatments produced an increased yield of 5–10%. PRD and DI irrigation improved WUE considerably, and that was 30.35% and 25.71% respectively higher than FI. Results suggest that PRD treatment may be an option in a water shortage.

Effect of Irrigation Scheduling at Different Phonological Phases on Growth and Yield of Mustard (Brassica juncea l.) in Northern Telangana

Optimum crop yield is not possible without the timely application and right amount of irrigation water. Since rainfall during rabi is inadequate and uncertain, scheduling of irrigation during critical stages could boost the growth, yield and water productivity of mustard. So, in order to identify critical stages of irrigation for mustard in Northern Telangana Zone, a field experiment was conducted during rabi, 2021-22 at Agricultural college, Jagtial to investigate the effect of irrigation scheduling at different phenological phases on growth and yield of mustard. The experiment was laid out in randomized complete block design with twelve treatments and replicated thrice. Treatments includes two irrigations each at vegetative and flowering stage (T1), two irrigations each at vegetative and siliqua development (T2), two irrigations each at flowering and siliqua development (T3), three irrigations each at vegetative, flowering and siliqua development (T4), three irrigations each at vegetative, pre-flowering and siliqua development (T5), three irrigations each at pre-flowering, siliqua initiation and siliqua development (T6), four irrigations each at vegetative, pre-flowering, flowering and siliqua development (T7), four irrigations each at vegetative, pre-flowering, flowering and siliqua initiation (T8), four irrigations each at vegetative, pre-flowering, siliqua initiation and siliqua development (T9), four irrigations each at pre-flowering, flowering, siliqua initiation and siliqua development (T10), five irrigations each at vegetative, pre-flowering, flowering, siliqua initiation and siliqua development (T11) and scheduling of irrigation at IW/CPE ratio of 1.0 (T12). The results of the experiment revealed that maximum plant height (146 cm), LAI (0.89), dry matter accumulation (416 g m-2), number of siliquae plant -1 (124), number of filled seeds siliquae-1 (13.65), seed yield (1113 kg ha-1) and stover yield (2224 kg ha-1) were recorded with five irrigations each at vegetative, pre-flowering, flowering, siliqua initiation and siliqua development (T11). However, it was on par with irrigation scheduled at IW/CPE ratio of 1.0 (T12). While, the lowest plant height (102 cm), LAI (0.42), dry matter accumulation (198 g m-2), number of siliquae plant -1 (63), number of filled seeds siliquae-1 (10.43), seed yield (431 kg ha-1) and stover yield (923 kg ha-1) was recorded with scheduling two irrigations at vegetative and siliqua development (T2).

Optimization of water and land allocation in salinity and deficit- irrigation conditions at farm level in Qazvin plain.

Improper extraction of water from resources especially in arid and semi-arid regions leads to a decrease in the quality of water and soil resources. In such areas, management activities such as increasing water productivity in agricultural sector would be a key step towards sustainable development. Therefore, water resources management to improve the allocation of limited water supplies is essential. In this study, a non-linear programming optimization model have been combined with a AquaCrop model to determine the optimal water and land allocation considering the quality issues of both water and soil resources with focusing on enhancing agriculture water productivity. For this purpose, the spatial variations of chemical and physical properties of soil in the Qazvin plain were taken into account. The soil of study site was divided into three salinity classes, and three weather conditions were identified by Standardized Precipitation Index (SPI). Moreover, five irrigation strategies were modeled under each weather condition. To understand the response of major crops under cultivation to water and salinity, the AquaCrop model was calibrated and validated (2005-2020) and utilized in the objective function. Accordingly, the production functions of the different products were obtained, and the cultivation area as well as amount of water consumption of the crops were optimized by using the target functions of maximum net income and maximum water use efficiency. The results showed that the model is capable of simulating crop yield in salinity and water deficit conditions. The coefficient of determination (R2) for barley, wheat and maize was equal to 0.86, 0.92, and 0.96, respectively. Findings reveal that total irrigation water could be reduced by 20% on average without profit reduction when compared to the profit of the present situation. Total economic profit could be increased by 18% on average through the optimization of water allocation and cropping pattern with the same water supply amount as that of the current situation. Also, the water productivity increased between 12 to 30% under these conditions. Therefore, the proposed model can efficiently optimize the amount of irrigation water and cultivation area on a regional scale considering salinity conditions.

Stackelberg equilibrium water allocation patterns in shallow groundwater area under uncertainties

The hierarchical agricultural water resource management problem in shallow groundwater area is expected to be solved through establishing a practical and feasible mathematical model. This study proposes a multi-level programming model with considerations of process-based crops growth model and uncertainties. The model is solved by a fuzzy approach that ensures the decision-making proceeds from top to bottom sequentially and the leader supervises the solution search direction. The leeway given by each level decision maker expands the decision-making space and lets Stackelberg equilibrium solution more satisfactory. The model is applied in Hetao Irrigation District in China. After optimization, the Stackelberg equilibrium water allocation pattern and satisfaction degrees of each level decision makers can be identified. Summarized conclusions are as follows: (1) under uncertainties of available water, the water diversion is allocated in a similar pattern, while the groundwater allocation has larger variabilities; (2) when available water decreases, local farmers can improve crop production through modifying or optimizing irrigation water amount in each growth period; (3) the combined use of water diversion and groundwater is expected to become an effective approach for achieving a win–win situation between government managers and local farmers. The proposed model performs well in generating Stackelberg equilibrium solutions satisfied by multi-level decision makers. It can be extended to provide decision makers a more complete decision support system and also has potential to be applied in other similar areas.

English

Declining quantity and quality of irrigation water coupled with increasing water demand are serious challenges facing paddy rice production in the world. Reuse of agricultural waste water is increasingly popular in paddy systems but few studies have been done with regards to its quality and effects on soil productivity and environmental risks. The aim of this study was to assess the suitability of effluents from the Mwea Irrigation scheme in Kenya for recycling within the scheme and for reuse in new areas downstream. Water was sampled from River Thiba intake (point 1, control) and waste water from farmers plots, Kiruara drain (point 2) and Thiba main drain (point 3). Corresponding adjacent soils were sampled and analyzed for important physico-chemical quality parameters. Results showed that the EC, TDS, TSS, Ca2+, Mg2+, K+, Na+, HCO3-, NO3- and SO42- significantly (p<0.05) increased in wastewater as point 1< point 2< point 3. Whereas, 88.3% of Mwea rice farmers experienced water shortage during peak demand, 51.5% of them recycled wastewater from paddy fields. The soil total N and available P from the wastewater reuse sites increased by 48.4 and 400% respectively to amounts that could save fertilizer P application once every 3 seasons. The wastewater NO3- concentrations increased above 8 mg/L likely to cause damage to N sensitive plants and eutrophication in the receiving water masses. The fresh water and wastewater in the Mwea scheme were suitable for irrigated rice production since all the nutrient parameters were within critical limits as recommended by FAO standards.   Key words: Irrigation, recycling, rice production, wastewater, effluent, physico-chemical, Water quality, precision agriculture. 

Assessment of Crop Water Demand and Irrigation Water Supply in a Run-off-the-river Based Canal System

Proper assessment of irrigation water need for a canal command is required for long term planning and management of water resources. The present study was carried out in the Phulnakhara distributary command of the Puri main canal system distributed in Cuttack and Khurda districts of Odisha. During Kharif season, the Phulnakhara distributary command receives more than the required amount of irrigation water. However, during Rabi season, the canal does not flow at its full supply level as a result of which the total irrigation demand of the canal command area is not met leading to lower cropping intensity and poor crop productivity. The year-wise highest irrigation water demand in Kharif season was found to be 48646195 m3 during 2015-16 and the lowest was 22291100 m3 in 2017-18. Whereas the highest Kharif irrigation supply at the head regulator was 43402176 m3 during 2015-16 and the lowest was 29831328 m3 during 2013-14. The highest Rabi irrigation water demand was found to be 21700766 m3 during 2008-09 and the lowest was 9570257 m3 in 2017-18. Whereas the highest Rabi irrigation supply at head regulator was 26379648 m3 during 2008-09 and the lowest was 615168 m3 during 2009-10. As evident, there is a mismatch between the supply and demand in both the seasons and it is more prominent in the Rabi season. In order to bridge this gap, conjunctive use of canal water with groundwater is found to be a promising solution.

An Analysis Based on Japonica Rice Root Characteristics and Crop Growth Under the Interaction of Irrigation and Nitrogen Methods.

Water shortages and nitrogen (N) fertilizer overuse limit japonica rice production in Northeastern China. The interactions between water-saving irrigation and nitrogen management on rice root and shoot growth is still our research focus. Here, japonica rice (DN425) was subjected to the irrigation methods W1 (flooding irrigation), W2 [mild alternate wetting and drying irrigation (AWD); −10 kPa], W3 (severe AWD; −30 kPa), and different N fertilizer ratios were applied in different growth stages, namely, N1 (6:3:1:0), N2 (5:3:1:1), and N3 (4:3:2:1). From jointing to full heading stages, the highest photosynthate production capacity and root activity were obtained under W1N2. AWD markedly affected the root system and resulted in root senescence at later growth stages. Grain yield and N utilization efficiency were closely and positively correlated with the relative water content, crop growth rate (CGR), leaf area duration (LAD), the increase rate of root length density, root surface area density, and root volume density (RVD) from the jointing to full heading stages. This positive correlation was also observed in the increased rate of root bleeding sap (RBS) under W1N2 and CGR under W2N3. From full heading to maturity stages, N2 could promote root growth, LAD, and CGR under AWD to a greater extent than those under the other treatments. Water use efficiency (WUE) and N uptake efficiency (NUpE) were both negatively associated with the decreased rate of RVD, root dry weight (RDW), and RBS. They were closely and positively correlated with the increased rate of RDW and CGR. Our results suggested that W2N2 treatment delayed root senescence, maintained leaf photosynthesis, optimized the crop growth rate from full heading to maturity stages, and improved grain yield. The optimal grain yield, WUE, and NUpE were achieved at the irrigation water amount and topdressing fertilizer ratio of 41.40–50.34 × 102 and 31.20–34.83 kg ha–1, respectively.

Effect of irrigation water quantity and salinity level on growth and internal chemical contents of Moringa plants

Effect of irrigation water quantity and salinity level on growth and internal chemical contents of Moringa plants

Irrigation water use, shadow values and productivity: Evidence from stochastic production frontiers in vineyards

Increasing agricultural water use efficiency has the potential to contribute significantly to hydrological sustainability and to coping with increasing water scarcity. This paper focuses on the role of the quantity of irrigation water applied and irrigation method used in explaining output in wine grape farms. We applied propensity score matching to reduce potential selection bias from observables that might mediate in the choice of irrigation system. Stochastic Production Frontier models are then estimated for a sample of 371 Chilean wine grape growers. The results show that pressurized irrigation leads to higher production at all levels of water applied; however, at lower levels the impact on TVP is more pronounced. Shadow values calculated at observed output for pressurized and gravity systems are 0.026 USD m−3 and 0.033 USD m−3, respectively. Significant differences are found between low (0.046 USDm−3), medium (0.027 USD m−3) and high (0.018 USD m−3) levels of water applied. The average technical efficiency for the sample is 70.4% and there is no significant difference between growers using pressurized and gravity methods. Our findings suggest that irrigation water can be saved without compromising output, which has important implications for sustainability given that agriculture is the most water demanding sector in the world.

Estimating Irrigation Water Consumption Using Machine Learning and Remote Sensing Data in Kansas High Plains

Groundwater-based irrigation has dramatically expanded over the past decades. It has important implications for terrestrial water, energy fluxes, and food production, as well as local to regional climates. However, irrigation water use is hard to monitor at large scales due to various constraints, including the high cost of metering equipment installation and maintenance, privacy issues, and the presence of illegal or unregistered wells. This study estimates irrigation water amounts using machine learning to integrate in situ pumping records, remote sensing products, and climate data in the Kansas High Plains. We use a random forest regression to estimate the annual irrigation water amount at a reprojected spatial resolution of 6 km based on various data, including remotely sensed vegetation indices and evapotranspiration (ET), land cover, near-surface meteorological forcing, and a satellite-derived irrigation map. In addition, we assess the value of ECOSTRESS ET products for irrigation water use estimation and compare with the baseline results by using MODIS ET. The random forest regression model can capture the temporal and spatial variability of irrigation amounts with a satisfactory accuracy (R2 = 0.82). It performs reasonably well when it is calibrated on the western portion of the study area and tested on the eastern portion that receives more rain than the western one, suggesting its potential transferability to other regions. ECSOTRESS ET and MODIS ET yield a similar irrigation estimation accuracy.

Optimization of winter irrigation management for salinized farmland using a coupled model of soil water flow and crop growth

Drip irrigation under film mulch (DIUFM) and subsurface pipe drainage (SPD) are important measures to cope with water shortages and soil salinization in arid areas of northwest China. To investigate the coordinated operation mode of DIUFM and SPD, a new H2DSWAP model was developed based on coupling the HYDRUS-2D with a Soil–Water–Atmosphere–Plant model (SWAP). In the H2DSWAP model, real-time evapotranspiration, simple root growth, and the interaction between crops and soil water and salt are considered to improve the simulation accuracy. The model was calibrated and validated using parameter estimation and uncertainty analysis software (PEST) using field experiment datasets in 2019 and 2020 respectively. Compared with the original HYDRUS-2D model, the simulation accuracy of the H2DSWAP for soil water (root mean square error (RMSE) = 0.011 cm3·cm−3; mean absolute error (MAE) = 0.008 cm3·cm−3; determinant coefficient (R2) = 0.869) and soil salt (RMSE = 0.296 g·kg−1; MAE = 0.231 g·kg−1; R2 = 0.959) contents has been greatly improved. In addition, the simulation of the leaf area index (LAI) and yield also fitted well with field observations. The calibrated model was used to predict salt transport at depths of 0–100 cm and the change in maize yield under DIUFM. The results indicated that maize yield decreased yearly, and soil salinity increased yearly under DIUFM without SPD. Based on the obtained results, the management strategies of winter irrigation (WIR) under different drip irrigation water amounts, namely 600 mm (S1), 540 mm (S2), 480 mm (S3), and 420 mm (S4), were further investigated. Water productivity (WP) and yield were used as evaluation indices. The WIR was carried out every 4–5 years when the drip irrigation amount of the maize field was S1 and S2 was recommended. However, it was recommended to carry out WIR every 2 and 3 years under S3 and S4, respectively. Overall, the H2DSWAP model can be used as a useful tool to guide the operation mode of drip irrigation under mulch and subsurface pipe drainage in saline soils.

Optimizing frequency and amount of irrigation needed to establish cool‐season turfgrasses

AbstractLimited information is available on the optimal frequency and amounts of irrigation water needed to establish cool‐season turfgrasses from seed in arid environments. A 2 × 2 factorial study was conducted at New Mexico State University in 2012 and repeated in 2017 to investigate the effect of four irrigation treatments: two reference evapotranspiration (ETo) rates (60 and 120%), and two frequencies (daily and every other day [EOD]) on the establishment of several varieties of Kentucky bluegrass (Poa pratensis L.), perennial ryegrass (Lolium perenne L.), and tall fescue [Schedonorus arundinaceus (Schreb.) Dumort] (TF). Our hypothesis was that irrigation rates below 100% ETo replacement applied EOD would negatively affect turfgrass establishment. Turfgrasses were seeded in the fall and digital image analysis was used to estimate percent coverage. The Area Under the Curve model was used to estimate days after seeding needed to reach 50 (DAS50) and 90% coverage (DAS90). Statistical analysis indicated a significant interaction (p < .0001) between ETo and species and that irrigation frequency did affect establishment. Perennial ryegrass established the fastest and DAS90 was not affected by irrigation treatment. Kentucky bluegrass and TF established faster when irrigated daily at 120% ETo. Varieties within the same species all performed equally. In general, our study suggests that cool‐season turfgrasses can be established in arid regions using water conserving measures such as irrigating EOD at rates below 100% ETo replacement. Further studies are needed to determine lowest ETo replacement levels or irrigation frequency possible to achieve establishment.

Determining effects of foliar boron applications on yield and fruit quality of apricot trees for reducing water stress

Aims: The research was carried out to determine the effects of different boron doses on yield, yield components and quality on 5-6 years old apricot trees of Mogador variety, which were exposed to water stress in the Amik Plain in 2019. Methods and Results: The factorial experimental design was conducted on apricot trees of Mogador variety, using four doses of foliar boron (ppm) (0-B0, 150-B150, 225-B225 and 300-B300 ppm) and four irrigation levels (100%-I100, 75%-I75, 50%-I50 and 25%-I25 of available water holding capacity) in four replications. Each replication consisted of two apricot trees. The quantity of irrigation water applied in the experiment ranged from 179 to 742 mm, while the evapotranspiration varied between 295 and 832 mm during the irrigation season. Irrigation water use efficiency (IWUE) and water use efficiency (WUE) varied between 3.51-5.18 kg m-3 and 2.89-4.17 kg m-3, respectively. Boron doses did not cause significant differences in WUE and IWUE values. Each unit increase in crop water use caused an average yield increase of 16.8 kg ha-1. Relative to the full irrigation (I100), fruit weight decreased by 13 and 3% in I25 and I50, respectively, but increased by 2% in I75. Relative to the control group (B0), fruit weight increased by 2, 4, and 2% with B150, B225, and B300, respectively. Average fruit size varied between 47.40 (I75) and 42.99 mm (I25); total soluble solids (TSS) between 16.13 (I100) and 12.65 (I25); and pH between 3.16 (I100) and 3.30 (I50). The increased boron dose did not cause a significant difference in fruit size and width. The leaf boron content increased up to the B225 dose and tended to decrease at the B300 dose.Conclusions: Boron element provides an increase in yield in deficit irrigation conditions, the yield increase is higher in fully irrigated apricot trees. In full irrigation treatment (I100), the B225 treatment was more effective on the yield.Significance and Impact of the Study: The boron element is an important element that causes an increase in photosynthesis by light adsorption. There is not a lot of research investigating the effects of nutrient elements to relieve the negative effect of water stress in orchards. This research is important in terms of revealing the effects of the element boron in water stress conditions.

EFFECT OF LAND PREPARATION, WATER MANAGEMENT PRACTICES, AND PLANTING OPERATION ON PLANTING QUALITY IN RICE PRODUCTION

This study was conducted at Sungai Burong Tanjung Karang Kuala Selangor, Malaysia to investigate the effects of planting methods and techniques on planting quality. The problem is that the farmers do not follow Rice Check quality points in land preparations for flooding, drainage, and water depth which affects the planting quality (planting density, spacing, and planting losses). The results showed that following standardized practices has a positive effect on planting quality. Soil penetration resistance and soil bulk density decrease with the increase of the field flooding period and increase with the sedimentation period increase. Soil penetration resistance and bulk density have a negative effect on planting losses. The working speed of the transplanting machine was affected by the field condition SPR, Db, and WC affect the transplanting speed which affects the planting quality (planting density, spacing, and planting losses). The flooding period has a positive effect on planting losses, while the sedimentation period has a negative effect. Floating hills and buried hills decrease with the increase of flooding periods, and water depth, and with the decrease of the sedimentation soil penetration resistance, and soil bulk density. Bulk density and soil penetration resistance have a positive effect on planting density and spacing as they decrease, planting density and spacing decreases, and vice versa. The flooding period has a negative effect on planting density and spacing, while the sedimentation period has a positive effect. About 50.5% of the farmers used the right required amount of water for irrigation, and also the right time for irrigation.

Simulation of Water–Energy Nexus of the Spatial Patterns of Crops and Irrigation Technologies in the Cascade Pump Station Irrigation District

Cascade pump station irrigation districts (CPSIDs) consume vast amounts of irrigation water and energy. The aim of this study was to adjust the spatial patterns of crops and irrigation technologies in the CPSID to reduce the consumption of water and energy under the condition of conserving crop irrigation water. The irrigation district (ID) is divided into several sub-districts according to the topography elevation difference and the distribution of cascade pump stations (CPSs). The mathematical models of the irrigation water and energy consumption in each sub-district were established based on the relationship between the spatial patterns of crops and irrigation technologies in each sub-district. According to the present situation of the Jingdian Phase I Irrigation District in the arid region of northwest China, three modes of adjusting the crop planting structure and drip irrigation area were proposed. Based on the combination of these modes, three schemes of the spatial patterns of crops and irrigation technologies were generated. The annual energy consumption and irrigation water consumption of each sub-district in the ID of these three schemes were obtained through simulation. Compared with the present spatial patterns of crops and irrigation technologies in the Jingdian Phase I Irrigation District, Scheme 3 has the best water-saving and energy-saving effects, with an annual water saving and energy saving of 1753 × 104 m3 and 2898 × 104 kWh, and the water-saving rate and energy-saving rate were 12.34% and 15.74%, respectively. This paper also shows that the synchronous adjustment of crops and irrigation technologies among the sub-districts of ID can achieve significant water-saving and energy-saving effects.

UAV-based multispectral vegetation indices for assessing the interactive effects of water and nitrogen in irrigated horticultural crops production under tropical sub-humid conditions: A case of African eggplant

UAV-based multispectral vegetation indices are often used to assess crop performance and water consumptive use. However, their ability to assess the interaction between water, especially deficit irrigation, and nitrogen application rates in irrigated agriculture has been less explored. Understanding the effect of water-nitrogen interactions on vegetation indices could further support optimal water and N management. Therefore, this study used a split plot design with water being the main factor and N being the sub-factor. African eggplants were drip irrigated at 100% (I100), 80% (I80) or 60% (I60) of the crop water requirements and received 100% (F100), 75% (F75), 50% (F50) or 0% (F0) of the crop N requirements. Results showed that the transformed difference vegetation index (TDVI) was best in distinguishing differences in leaf moisture content (LMC) during the vegetative stage irrespective of the N treatment. The green normalized difference vegetation index (GNDVI) worked well to distinguish leaf N during vegetative and full vegetative stages. However, the detection of the interactive effect of water and N on crop performance required a combination of GNDVI, NDVI and OSAVI across both stages as each of these 3 VI showed an ability to detect some but not all treatments. The fact that a certain amount of irrigation water can optimize the efficiency of N uptake by the plant is an important criterion to consider in developing crop specific VI based decision trees for crop performance assessments and yield prediction.

Effect of the optimized regulated deficit irrigation methodology on quality, profitability and sustainability of barley in water scarce areas

A three-year experiment (2015–2017) was conducted under the semiarid conditions of the Hydrogeological Unit Eastern Mancha (HUEM) (Spain), using the optimized regulated deficit irrigation for a limited amount of irrigation water (ORDIL) methodology on barley. Five irrigation treatments were performed during the experiment: no deficit (ND), 100% (T100), 90% (T90), 80% (T80), and 70% (T70) of barley net typical irrigation requirements (2500 m3 ha-1) in the area. The aim was to determine the effect of ORDIL: 1) on the quality of grain and malt; 2) on the profitability and use of water at farm scale; and 3) on the profitability and sustainability of the HUEM. Despite using less water, ORDIL treatments showed no significant differences in grain quality with respect to ND, while T80 achieved the highest economic water productivity (average 0.17 € m-3). Thus, by using T80 instead of ND and increasing the irrigated area of barley on the farm by 14%, it is possible to save up to 31% of water with the same profitability. This amount of water could be used for more profitable crops, increasing the profitability of the farm. The use of ORDIL at basin scale, using T80 instead of ND and increasing the cultivated area by 9%, could have saved up to 55.9 hm3 over the 3 experimental years (16% of annual extractions in the HUEM). Supplying this water to more profitable crops, the profitability of the basin could have increased by up to 44.4 M€. In the case of saving this amount of groundwater, piezometric levels would have risen, decreasing the pumping costs and improving the environmental conditions in the area. Consequently, applying ORDIL in low-profit crops, such as barley, and in water scarce areas, could improve the profitability and/or the sustainability of agricultural systems, maintaining the production.

Enhancement of soil water characteristics curve (SWCC) and water use efficiency of cucumber (Cucumis sativus L.) in sandy soils by using silica nanoparticles

A field experiment was carried out in sandy soil at the Research and Training Station at King Faisal University, Al-Hassa, Saudi Arabia, during the 2016–2017 season, to study the effect of five rates of silica nanoparticle (Si-NP) treatments on soil soluble Si4+, water characteristics curve, yield and water use efficiency of cucumber (Cucumis sativus L.) after harvesting. A randomized complete block design with three replicates was used to conduct the study in the greenhouse where the amount of irrigation water was at 100 % evapotranspiration 78 L Plant−1 at the end of the season. The nano-silica particle (Si-NP) treatments were Si-NP0 (0 mg kg−1), Si-NP100 (100 mg kg−1), Si-NP200 (200 mg kg−1), Si-NP300 (300 mg kg−1) and Si-NP400 (400 mg kg−1). The results revealed that the Si-NP had a significant effect (p < 0.0001) on the soluble silicon (Si mg kg−1), field capacity (Fc, cm3cm−3), welting point (WP, cm3cm−3), available water (AW, cm3cm−3) and moisture content (θs, cm3cm−3), of the soil after harvesting crop and also, yield (g plant−1) and water use efficiency (WUE, g cm−3). The values of all parameters in the study increased with increasing the rates of silicon-nano particles. The main results can be summarized as follows: An increase of soluble Si4+ in the soil according to the application of Si-NP leads to a rise of all behaviour water properties in the soil such as FC, WP, AW and θs, which caused the increase in cucumber yield and water use efficiency by 178% as compared with Si-NP0. The higher mean values of all properties were found in plants exposed to Si-NP400 treatment.

Irrigation and phosphorous fertilization management to minimize rice grain arsenic content

This research sought to minimize inorganic arsenic levels in polished rice grain by using different irrigation and phosphorous fertilization practices while also maintaining crop yield and water productivity. Two experiments were conducted during seasons 2018–2019 and 2019–2020 using a split-plot design with three blocks, five irrigation treatments (main-plots) and two phosphorous levels (sub-plots). Irrigation treatments consisted of a traditional continuous flood (CF) control and four alternatives irrigation techniques with one or two drying events during the irrigation cycle. The phosphorous fertilization levels investigated were an unfertilized control (0 kg P2O5 ha−1) and the recommended fertilization level of 50 kg P2O5 ha−1. Soil pH and redox potentials were measured in each treatment. Strategically-timed, low severity drying events were effective at achieving aerobic soil conditions, resulting in Eh values over 50 mV. The alternative irrigation treatment with two drying events, implemented at panicle initiation and full flowering, was the most effective in reducing inorganic arsenic in grain without affecting grain yield or the amount of irrigation water applied. This irrigation technique could be considered as an alternative management to the traditional continuous flooded to reach minimal inorganic arsenic accumulation in grain in order to attend special quality standards or specific market requirements. Accumulated inorganic arsenic in grain was below international maximum levels in all analyzed samples, with an average value of 0.084 mg kg−1.

A Novel Prediction and Planning Model for the Benefit of Irrigation Water Allocation Based on Deep Learning and Uncertain Programming

Due to population growth and human activities, water shortages have become an increasingly serious concern in the North China Plain, which has become the world’s largest underground water funnel. Because the yield per unit area, planting area of crops, and effective precipitation in the region are uncertain, it is not easy to plan the amount of irrigation water for crops. In order to improve the applicability of the uncertainty programming model, a hybrid LSTM-CPP-FPP-IPP model (long short-term memory, chance-constrained programming, fuzzy possibility programming, interval parameter programming) was developed to plan the irrigation water allocation of irrigation system under uncertainty. The LSTM (long short-term memory) model was used to predict crop yield per unit area, and CPP-FPP-IPP programming (chance-constrained programming, fuzzy possibility programming, interval parameter programming) was used to plan the crop area and the effective precipitation under uncertainty. The hybrid model was used for the crop production profit of winter wheat and summer corn in five cities in the North China Plain. The average absolute error between the model prediction value and the actual value of the yield per unit area of winter wheat and summer maize in four cities in 2020 was controlled within the range of 14.02 to 696.66 kg/hectare. It shows that the model can more accurately predict the yield per unit area of crops. The planning model for the benefit of irrigation water allocation generated three scenarios of rainfall level and four planting intentions, and compared the planned scenarios with the actual production benefits of the two crops in 2020. In a dry year, the possibility of planting areas for winter wheat and summer corn is optimized. Compared with the traditional deterministic planning method, the model takes into account the uncertain parameters, which helps decision makers seek better solutions under uncertain conditions.