Improving Irrigation Water Use Research Articles

Accelerated integrated watershed management enhances agricultural carbon sequestration and water use efficiency in an endorheic basin

With the continuous promotion of integrated river basin management (IRBM) in endorheic watersheds, the oasis surface processes have undergone significant changes. However, these underlying surface characteristics have not been well integrated into models for simulating carbon-water flux thus far. In this work, a regional SWAT-TECO model was constructed by coupling the modified TECO simulator with irrigation, film mulching, and soil hydraulic redistribution processes within the SWAT framework. The results indicated that the carbon sequestration and water use efficiency (WUE) showed an increasing trend after IRBM implementation in Heihe endorheic basin. WUE was projected to improve under future climate change and can be further enhanced by a maximum of 6.37 % through improving irrigation water use efficiency by 20 %, maintaining existing planting scale, increasing film mulching by 20 %, and reducing fertilizer application by 10 %. These findings can guide the formulation of high-water efficiency agricultural management strategies in global endorheic basins.

Modelling effects of water stress on the productivity of irrigated wheat (Triticum Aestivum L.) in a semiarid condition of Northeastern Nigeria

Lake Chad region is currently experiencing trending issues. Climate change is among the major influencers of these issues that require inevitable consideration for a sustainable ecosystem. Various crop models have been developed and employed in various environmental conditions and management practices, which are cheaper and easier than field experiments. Therefore, crop models could be used to simulate various water management strategies and suggest suitable options. In this work, the FAO AquaCrop model has been evaluated to simulate deficit irrigation (DI) scenarios for wheat crops using data generated from a field experiment. The model simulated grain yield (GY), biomass yield (BMY), biomass production (BMP) and canopy cover (CC) adequately during its calibration and validation. However, its performance in simulating water productivity (WP) and actual crop evapotranspiration (ETa) was low with average r2, NRMSE, model efficiency (EF) and Willmot Index of agreement (d) of 0.58, 11.0 %, -1.40 and 0.69 respectively. The study of DI scenarios using the model revealed that the application of DI throughout the growth stages of the crop could significantly affect GY and WP. The highest GY and WP of 5.3 t/ha and 1.50 kg/m3 were respectively obtained at the application of full irrigation (T100). Increasing DI beyond 20 % depressed both GY and WP significantly. However, increasing the irrigation interval from seven to ten days did not affect GY, thereby improving WP from 1.28 kg/m3 to 1.38 kg/m3. Therefore, applying an 80 % irrigation requirement throughout the wheat growing season at 10-day intervals could save 25 % of irrigation water, a valuable strategy to improve irrigation water use without significant yield reduction. Furthermore, irrigation-related scientists and managers can use the validated model to decide the current and future irrigation water management for similar wheat varieties in similar environmental conditions.

Demonstration of Center Pivot Uniformity Evaluation and Retrofit to Improve Water Use Efficiency

Agricultural irrigation is a primary user for freshwater withdrawal. Irrigation plays an important role in crop production, as it provides the benefit of reducing the effects of prolonged dryness and erratic precipitation. Center pivot irrigation system is the most common irrigation system in agriculture. As the center pivot irrigation system ages, the system could develop a leaking joint, clogged sprinklers, and physical damage. This can cause areas of non-uniformity that can lead to under- or over-irrigated in some areas of the land, resulting in excess energy use and cost, wasting resources, and environmental impacts. Thus, it is important to evaluate the performance of a center pivot irrigation system regularly to maximize return on investments and minimize wasting resources. This study focuses on evaluating the impacts and benefits of improved center pivot irrigation distribution uniformity by performing distribution uniformity evaluations pre- and post-retrofit. This study also focused on demonstrating an unmanned aerial vehicle (UAV) to assess the performance of the center pivot irrigation system in two irrigated farmlands. The Coefficient of Uniformity (CU), Distribution Uniformity (DU), and Scheduling Coefficient (SC) were calculated based on the catch can test data. The values were utilized to evaluate water and energy savings from the improved coefficients. The team has found that replacing sprinkler packages increased the CU from 78 to 89 and the DU from 77 to 82, and reduced the SC from 1.3 to 1.2 in Field A. In Field B, replacing sprinkler packages increased the CU from 73 to 91 and the DU from 62 to 84 and reduced the SC from 1.6 to 1.2. The estimated water savings in Field A due to the reduced scheduling coefficient was approximately 151,000 liters/hectare/year, with consideration of the corn and soybean rotation field in Michigan. The estimated water savings in Field B was 608,000 liters/hectare/year. The data from this demonstration study showed the value of distribution uniformity evaluation and retrofit of irrigation systems. This information will encourage farmers and agricultural industries to consider performing more distribution uniformity evaluations, ultimately improving irrigation water use efficiency and supporting sustainable water management in agriculture.

Row spacing and irrigation management affect soybean yield, water use efficiency and economics

Declining water levels in the Mississippi River Valley Alluvial Aquifer necessitates research on the management practices that can reduce irrigation water use and improve irrigation water use efficiency. A three-year field study from 2019 to 2021 evaluated the effects of row spacing and irrigation management on soybean seed yield and quality, irrigation water use efficiency (IWUE), water productivity (WP), and profitability. Soybean was planted in two row spacings [single- (SR) and twin-row (TR)] and irrigated with three different methods [every row irrigated (ERI), alternate row irrigated (ARI), non-irrigated (NI)]. Soybean yields were increased with application of irrigation either as ERI or ARI as compared to NI in all three years ranging from 20% to 79%. The ERI had 20% increase in yield over ARI in 2021, whereas no significant differences were found between ERI and ARI in 2019 and 2020. Averaged over row spacing, IWUE was 66–91% greater with ARI compared to ERI. Only 2021 showed an increase (34%) in WP with irrigation applied as ARI than NI. Differences in rainfall amount among years and amount of irrigation applied under different treatments affected the soybean yields. Soybean yield showed reduction by 0.37–1.2 kg ha−1 with each unit increase in cumulative stress (kPa-days) for soil moisture potential drier than the −40 kPa on very fine sandy loam soils. Twin-row soybean had higher expected returns in all cases except for the NI and ERI in 2021. The TR soybean produced the greatest average risk-return than other treatments. The ARI with TR had the second highest overall risk-return trade-off. The ARI resulted in an equivalent risk-return production system as ERI for SR soybeans. Alterations in furrow irrigation methods could be more beneficial than row spacing to improve soybean productivity and IWUE.

Moderate soil drying improves physiological performances and kernel yield of maize

AbstractWater shortage is a serious problem in crop production, and maize (Zea mays L.) is the largest grain crop worldwide. It would have great significance in increasing kernel yield and water use efficiency to establish a high‐yielding and water‐saving irrigation technology in maize. In this study, two high‐yielding maize varieties were used and two irrigation regimes composed of well‐watered (WW) and moderate soil drying (MD) were conducted. Physiological performances, kernel yield, and water use efficiency were investigated. Compared with WW, the MD increased kernel yield by 4.69–6.40%, reduced irrigation water by 26.5–33.3%, and improved irrigation water use efficiency by 43.1–59.3%. In terms of physiological performances, the MD enhanced the leaf superoxide dismutase (SOD) activity, decreased malondialdehyde (MDA) content, increased the leaf photosynthetic rate and the contents of indole‐3‐acetic acid (IAA), zeatin (Z) + zeatin riboside (ZR), gibberellin‐3 (GA3), and abscisic acid (ABA) in inferior kernels, promoted the remobilization of non‐structural carbohydrates (NSC) from stalks and sheaths to kernels, and improved the filling rate and weight of inferior kernels. Correlation analysis showed that IAA, Z + ZR, and ABA contents in kernels were significantly and positively correlated with the kernel filling rate. These results suggest that the moderate soil drying imposed during the whole growth period of maize can achieve the dual goal of increasing food production and saving water by improving physiological performance, especially regulating hormonal levels in the kernel.

Assimilation of Remotely Sensed Leaf Area Index Enhances the Estimation of Anthropogenic Irrigation Water Use.

Representation of irrigation in Earth System Models has advanced over the past decade, yet large uncertainties persist in the effective simulation of irrigation practices, particularly over locations where the on-ground practices and climate impacts are less reliably known. Here we investigate the utility of assimilating remotely sensed vegetation data for improving irrigation water use and associated fluxes within a land surface model. We show that assimilating optical sensor-based leaf area index estimates significantly improves the simulation of irrigation water use when compared to the USGS ground reports. For heavily irrigated areas, assimilation improves the evaporative fluxes and gross primary production (GPP) simulations, with the median correlation increasing by 0.1-1.1 and 0.3-0.6, respectively, as compared to the reference datasets. Further, bias improvements in the range of 14-35mmmo-1 and 10-82gm-2mo-1 are obtained in evaporative fluxes and GPP as a result of incorporating vegetation constraints, respectively. These results demonstrate that the use of remotely sensed vegetation data is an effective, observation-informed, globally applicable approach for simulating irrigation and characterizing its impacts on water and carbon states.

Precision Irrigation Scheduling Based on Wireless Soil Moisture Sensors to Improve Water Use Efficiency and Yield for Winter Wheat in Sub-Saharan Africa

In Sub-Saharan Africa, where most irrigation systems are manually operated, water allocation and irrigation scheduling are often based on uniform application irrespective of crop needs and growth stages, which results in nonoptimal water use. Recently, a lot of research has been carried out to improve irrigation water use efficiency through automation by employing wireless sensor-based monitoring systems. Further to the improvement of water use efficiency and yield, while reducing costs, a field trial was carried out at a farm in Harare, Zimbabwe, during the 2016, 2017, and 2018 winter seasons to test whether a new approach to the automated irrigation systems, one based on IoT and wirelessly connected soil sensors (called hereafter as WCSS), improves water use efficiency without reducing yield. WCSS method was compared with three widely used conventional irrigation methods, that is, manual scheduling, tensiometer-based scheduling, and weather-based scheduling. Impacts on water savings and yield of winter wheat crops under drip irrigation were evaluated. WCSS saved up to 25% more water compared to typical fixed irrigation schedule rates used by wheat growers during the winter season.

Closing the irrigation water productivity gap to alleviate water shortage in an endorheic basin

Closing the irrigation water productivity (IWP) gap is an effective approach to alleviating water deficits and ensuring food security. However, few studies have attempted to quantify the IWP gap and the potential benefits of closing it. This study adopted the Heihe River Basin, the second-largest inland basin in China, as a typical study area. The aims of this study were to: (1) assess the positive achievements and potential risks triggered by the Heihe Ecological Water Diversion Project (EWDP) according to multi-source and multi-scale measured data; (2) analyze potential approaches to improve the IWP and quantify the potential benefits that can be achieved by closing its IWP gap. The results of this study indicated that the EWDP effectively reallocated surface water resources, replenished groundwater in the lower reaches, and facilitated the recovery of oases and economic development in the downstream regions. However, this project has indirectly led to an imbalance in the groundwater resource between the middle and lower reaches, resulting in decline in groundwater levels and degradation of local vegetation in the midstream regions. In addition, the expansion of cultivated land in the midstream and downstream oases has resulted in the deterioration of farmland environment. The water transfer resulted in a deceleration in the growth of IWP from 2.44 % to 1.15 %, and the existing IWP gap was 1.43 kg/m3 between 1984 and 2017. This study predicted a future increase in the IWP to 2.01 kg/m3 with a reduction in the gap to 0.45 kg/m3 while maintaining food production. The potential for conserving water in the Heihe agricultural region can reach 552 million m3 by reducing the planting area by 10 %, improving irrigation water use efficiency by 20 %, maintaining existing agricultural film inputs, and reducing fertilizer application by 10 %. Following the research recommendations can greatly alleviate the agricultural water shortage and over-extraction of groundwater in the middle reaches and ensure meeting ecological water demand in the lower reaches. This study can act as a reference for sustainable management of an endorheic basin.

Water Demand Pattern and Irrigation Decision-Making Support Model for Drip-Irrigated Tomato Crop in a Solar Greenhouse

The knowledge of crop water requirements is critical for agricultural water conservation, especially for accurate irrigation decision making in the greenhouse. Investigating the water demand pattern of the tomato in the solar greenhouse environment and constructing an appropriate irrigation decision-making model are urgently needed to improve irrigation water use efficiency. We designed four irrigation-level treatments: 100% ET0 (T1), 85% ET0 (T2), 70% ET0 (T3), and 55% ET0 (T4), and conducted a two-vegetation-season tomato planting trial under drip irrigation conditions in a solar greenhouse. The Pearson’s correlation coefficient method analyzed the intrinsic linkage and influence between soil–crop–environment and tomatoes’ water demand patterns. Indicators suitable for irrigation decision making in greenhouse tomatoes were selected, and regression functions were constructed for environmental and crop physiological parameters by combining path analysis and multiple regression methods. Finally, a fusion irrigation decision-making model was constructed by introducing a distance function in the Dempster–Shafer (D–S) theory primary probability assignment (BPA) synthesis algorithm and combining it with a triangular affiliation function. The results showed that: (1) the soil coefficient of variation was shallow > middle > deep, and tomatoes absorbed water mainly in the 0–60 cm soil layer; (2) the crop stem flow rate, net photosynthetic rate, and transpiration rate were positively correlated with irrigation water and had the highest correlation with net radiation, relative humidity, and relative humidity, with correlation coefficients of 0.9441, 0.9441, and 0.7679, respectively; (3) the constructed decision model had a significantly lower value of uncertainty than other methods, while the highest decision value could reach over 0.99, which achieved the best decision accuracy compared to other algorithms.

Economic valuation and its determinates of improved irrigation water use; evidence based on South Gondar Zone, Ethiopia

Economic valuation and its determinates of improved irrigation water use; evidence based on South Gondar Zone, Ethiopia

Effects of water and NPK fertigation on watermelon yield, quality, irrigation-water, and nutrient use efficiency under alternate partial root-zone drip irrigation

Alternate partial root-zone drip irrigation (APRD) is efficient in improving irrigation water use efficiency (IWUE). However, little is known about the coupling effects of irrigation and NPK fertilisers on watermelon performance and resource use efficiency under APRD. This study investigated the effects of drip irrigation modes (conventional drip irrigation [CDI], APRD) coupled with NPK fertilisation rates on watermelon growth, IWUE, nutrient use efficiency, yield, and fruit quality. There were five treatments coded as CSH, CDH, CDL, ADH and ADL. The capital letters in the codes indicate drip irrigation modes as CDI (C) or APRD (A), irrigation amount as sufficient (S) or deficit (D, 60% of the total amount of S), and NPK fertilisation rates as high (H) or low (L, 60% of the amount of H). The results showed that compared with CDI at the same fertigation level, APRD increased the photosynthetic rate by 10.1%, plant growth by 25.5%, and NPK absorption by 29.1% across all growth stages, respectively. The promotion effect of APRD was more prominent at early growth stages. APRD increased watermelon yield by 10.4%, thus increased IWUE and fertiliser partial productivity at the same extent, while decreased the NPK use efficiency by 7.0% compared with the CDI counterparts. Compared with CSH, APRD increased vitamin C, total soluble solids (TSS), and the ratio of TSS to total organic acids by 63.2%, 6.2% and 17.2%, respectively. Additionally, the yield didn’t decrease in ADL whereas it increased in ADH, leading to an increase in IWUE of 67.8–78.7% under APRD treatments compared with CSH. Conclusively, APRD could save 40% of total irrigation water and NPK fertilisers without yield reduction while improving fruit quality. Thus, it is suggested as a sustainable practice for watermelon production.

Soil-plant water dynamics, yield, quality and profitability of spring sweet corn under variable irrigation scheduling, crop establishment and moisture conservation practices

Spring sweet corn as a short duration cash crop is gaining popularity in northern India owing to increasing demand in urban and peri-urban regions. Under hot dry climate and minimal rainfall, irrigation is the major yield contributing factor for attaining superior quality cobs and higher economic returns. The study aimed at examining the effect of irrigation scheduling (I) (IW/CPE 1.0, 1.2, 1.4), sowing methods (S) (flat and furrow) and moisture conservation practices (M) (no-residue, rice straw mulch 6.0 t ha −1 and rice straw biochar 3.0 t ha −1 ) on spring sown sweet corn yield, quality, profitability and water use efficiency in the Tarai region (sandy loam soil texture) of Uttarakhand, India. The experiment was conducted in split factorial design (Main I x S, Sub M) with 18 treatment combinations and three replications. Results indicated that the combination IW/CPE 1.4 +furrow+mulch being at par with IW/CPE 1.4 +furrow+biochar were superior in terms of dehusked cob yield which was ~42% higher over IW/CPE 1.0 +flat+control. Application of biochar 6 t ha −1 and straw mulch 3 t ha −1 increased dehusked cob yield of sweet corn by ~6–9% over control (no-residue) during both years. Among irrigation schedules, IW/CPE 1.0 obtained highest irrigation water use efficiency (IWUE) followed by IW/CPE 1.2. Mulch and biochar being on par recorded 7–10% higher IWUE over no-residue control. Likewise, furrow sowing increased IWUE by 39–44% over flat method with ~25% higher water savings. Average soil moisture content under mulch and biochar was 25% and 12% higher respectively over no-residue. Maximum net returns was obtained under the combination IW/CPE 1.4 +furrow+mulch (1672 USD ha −1 ) which was 69% higher over IW/CPE 1.0 +flat+no-residue. Sweet corn quality parameters viz., total soluble solids and non-reducing sugar was significantly higher under IW/CPE 1.0 and 1.2 in comparison to 1.4, as well as under furrow sowing over flat sowing. Therefore, although maximum yield and profitability of sweet corn was obtained under irrigation schedule IW/CPE 1.4, the treatment combination of IW/CPE 1.2 with furrow sowing and mulch/biochar application may be adopted for attaining superior quality parameters and improved water use efficiency of sweet corn. • Irrigation scheduled at IW/CPE 1.4 & 1.2 increased sweet corn yield over IW/CPE 1.0. • IW/CPE 1.2 improved irrigation water use efficiency (IWUE) by 7% over IW/CPE 1.4. • Furrow sowing had 4–8% and 39–44% higher cob yield and IWUE resp. than flat sowing. • Mulch 6 t ha −1 & biochar 3 t ha −1 observed 7–10% higher IWUE of sweet corn over control. • Virtual water of sweet corn was lowest with IW/CPE 1.0, furrow and mulch.

Water Use and Soil Water Balance of Mediterranean Vineyards under Rainfed and Drip Irrigation Management: Evapotranspiration Partition and Soil Management Modelling for Resource Conservation

Vineyards represent complex Mediterranean agrosystems that deliver significant ecosystem services to society. Yet, many vine-growers still need to assimilate the importance of crop and soil management to the conservation of soil and water resources. The main objective of this study was to evaluate water use and the water balance terms in rainfed and irrigated vineyards in Italy and Portugal, respectively, in both cases aiming at the sustainability of natural resources use. The SIMDualKc model is used for both sites after calibration and validation by fitting soil water content measurements. The Italian case study focused on the impacts of inter-row conservation management in hillslope vineyards while the Portuguese case study analyzed irrigation water management under scarcity in flat vineyards. For the Italian vineyards, the model results focused on the evapotranspiration fluxes and their partition, control of surface runoff, and soil water recharge provided by the inter-row soil management using cover crops. Model results of the Portuguese case study showed the need for improving irrigation water use and the terms of water balance, namely referring to percolation and soil water evaporation. Both case studies further demonstrated the advantages of using computational tools to better cope with climate variability in the Mediterranean region and made evident the benefits of improved crop and soil management practices in counteracting land degradation and valuing the use and conservation of natural resources.

Productivity and Irrigation Water Use Efficiency of Sewi Date Palm under Different Irrigation System

This work was carried out during three successive seasons of 2018, 2019 and 2020 on Sewi date palm grown on sandy soil in a private farm at El-Baharia Oasis, Giza Governorate, Egypt, (28° 19ʹ 10ʺ N: 28° 57ʹ 35ʺ E. 130 m a.s.l.) to evaluate the effectiveness of irrigation water levels (100, 80 and 60% IR) under different irrigation system (drip and bubbler) on growth, yield, fruit quality and irrigation water use efficiency. Results showed that the studied quality parameters (except the soluble solid content (S.S.C.) of the date palm fruits were highest under the DIS, IR=100% for the tested seasons. Data referred to all the studied properties significantly affected with increasing water supply under any irrigation system. Used drip irrigation system led to produce good quality compared with bubbler ones. Evaluation of drip irrigation system with 100 % of IR enhanced yield and improved irrigation water use efficiency in the three tested seasons. Thus, this study recommends using the DIS, IR=100 % to irrigate date palm trees under El-Baharia Oasis conditions.

Exploring the optimisation of mulching and irrigation management practices for mango production in a dry hot environment based on the entropy weight method

Rational application of field-management technology can not only improve mango (Mangifera indica L.) fresh fruit yield and quality but also improve irrigation water use efficiency (IWUE). However, few studies have involved the simultaneous use of mulch and irrigation-management techniques in hot and dry environments to achieve a relatively good level of performance. We used the entropy weight method (EWM) to explore an optimal mulching and irrigation-management technology for mango production in a dry hot environment. Three irrigation levels [FI, 100% mango evapotranspiration (ETC); DI75, 75% ETC; DI50, 50% ETC] were designed with (SM) and without (NM) sugarcane leaf mulching in 2018 and 2019 in a dry hot environment. The results showed that the photosynthetic rate, stomatal conductance, transpiration rate, leaf water-use efficiency, and carboxylation efficiency in the SM treatment were 12.5% to 83.7% higher than those in the NM treatment in both years. Compared with the NM treatment, the SM treatment increased the fresh fruit yield and IWUE by 45.7% and 49.7% in 2018 and by 46.1% and 63.2% in 2019. The solid-to-acid ratio and sugar-to-acid ratio in the SM treatment were 48.5% and 50.4% higher than those in the NM treatment, respectively, but the titratable acid content decreased by 31.3%. Compared with FI, DI75 increased carotenoid content, total soluble solids, solid-to-acid ratio and sugar-to-acid ratio by 8.4%–40.7%, while it reduced titratable acid by 22.8%. Compared with FI, DI50 reduced fresh fruit yield by 24.3% and 21.9% in 2018 and 2019, respectively, while it increased IWUE by 13.6% and 17.7%. The fresh fruit yield of SMDI75 was the highest, which was 1.42 and 1.44 times that of NMFI in both years, respectively. A comprehensive evaluation by EWM also showed that the SMDI50 treatment had the highest comprehensive scores of mango yield, quality and water-use efficiency, which could provide a basis for the scientific management of mango fertiliser in dry and hot areas of China.

Hybrid Bermudagrass and Tall Fescue Turfgrass Irrigation in Central California: II. Assessment of NDVI, CWSI, and Canopy Temperature Dynamics

As the drought conditions persist in California and water continues to become less available, the development of methods to reduce water inputs is extremely important. Therefore, improving irrigation water use efficiency and developing water conservation strategies is crucial for maintaining urban green infrastructure. This two-year field irrigation project (2018–2019) focused on the application of optical and thermal remote sensing for turfgrass irrigation management in central California. We monitored the response of hybrid bermudagrass and tall fescue to varying irrigation treatments, including irrigation levels (percentages of reference evapotranspiration, ETo) and irrigation frequency. The ground-based remote sensing data included NDVI and canopy temperature, which was subsequently used to calculate the crop water stress index (CWSI). The measurements were done within two hours of solar noon under cloud-free conditions. The NDVI and canopy temperature data were collected 21 times in 2018 and 10 times in 2019. For the tall fescue, a strong relationship was observed between NDVI and visual rating (VR) values in both 2018 (r = 0.92) and 2019 (r = 0.83). For the hybrid bermudagrass, there was no correlation in 2018 and a moderate correlation (r = 0.72) in 2019. There was a moderate correlation of 0.64 and 0.88 in 2018 and 2019 between tall fescue canopy minus air temperature difference (dt) and vapor pressure deficit (VPD) for the lower CWSI baseline. The correlation between hybrid bermudagrass dt and VPD for the lower baseline was 0.69 in 2018 and 0.64 in 2019. Irrigation levels significantly impacted tall fescue canopy temperature but showed no significant effect on hybrid bermudagrass canopy temperature. For the same irrigation levels, increasing irrigation frequency slightly but consistently decreased canopy temperature without compromising the turfgrass quality. The empirical CWSI values violated the minimum expected value (of 0) 38% of the time. Our results suggest NDVI thresholds of 0.6–0.65 for tall fescue and 0.5 for hybrid bermudagrass to maintain acceptable quality in the central California region. Further investigation is needed to verify the thresholds obtained in this study, particularly for hybrid bermudagrass, as the recommendation is only based on 2019 data. No CWSI threshold was determined to maintain turf quality in the acceptable range because of the high variability of CWSI values over time and their low correlation with VR values.

Spatial water footprint optimization of crop planting: A fuzzy multiobjective optimal approach based on MOD16 evapotranspiration products

Agriculture is required to produce more food while reduce water consumption at the same time. To improve the irrigation water use efficiency in agricultural production, this study proposed a fuzzy multiobjective optimal modeling approach based on Moderate-resolution Imaging Spectroradiometer (MODIS) global evapotranspiration products for optimizing spatial water footprint of crop planting. This study attempts to accurately estimate the spatial crop water footprint based on remote sensing information, and effectively plan crop planting structure considering conflicting targets, spatial water footprint, and limited irrigation water resources under fuzzy uncertainty. To test its feasibility, the proposed approach is employed to a typical semi-arid region in Northwest China. Three performance evaluation indicators, including synthetic degree (SD), sustainability index (SI), and approximation degree of ideal objective value (AD), are applied for measuring model performance and try to give a more comprehensive picture of agricultural land use strategies. Results show that (1) the remote sensing data can effectively improve the accuracy of water footprint estimation, and identify crop planting advantage distribution in spatial; (2) the planting area of crops with high evapotranspiration should be increased in irrigation districts near the upstream with high precipitation, which can improve economic benefit, increase utilization rate of green water, and fairness of allocation; (3) through optimization, the average total, blue, and gray water footprint among IDs are drop while green water utilization rates is raised comparing with status quo (2014); (4) Water scarcity will not only damage the coordinated development degree of economy, society and environment, but also hurt the regional sustainable development ability and the realization of development objectives. The proposed optimal modeling framework can help optimize the spatial water footprint of crop planting and improve irrigation water use efficiency, which can be applied to similar regions that suffer from water scarcity.

Improving Irrigation Water Use Efficiency of Robusta Coffee (Coffea canephora) Production in Lam Dong Province, Vietnam

Recent prolonged dry periods and lack of irrigation water have severely affected the productivity of coffee farms in the Central Highlands of Vietnam. This paper analyzes the efficiency of irrigation water use for Robusta coffee (Coffea canephora) in the Lam Dong province. A Cobb–Douglas production function was used to determine coffee productivity’s response to the application of irrigation water and other production factors using data collected from 194 farmers, while the technical efficiency (TE) and irrigation water use efficiency (IWUE) were analyzed using a data envelopment analysis (DEA) model. The correlation of different factors to IWUE was determined using the Tobit model. The production function analysis using Cobb–Douglas shows that the volume of irrigation water, amount of working capital, labor, and farm size significantly influence coffee productivity. Indigenous farmers are more efficient in utilizing irrigation water than migrant farmers. The Tobit result indicates that farmers’ experience, education level, the distance of farm to water sources, security of access to water sources, extension contact, and credit access significantly affect IWUE. The study findings further suggest that mitigating water shortages in coffee farms require subregional and national policy support such as better access to credit and extension services, training, land management, and household-level efforts to improve farming practices through the application of appropriate technologies and traditional knowledge.

Development and Evaluation of a Variable-Rate Irrigation Management Method in the Mississippi Delta

HighlightsWe developed and evaluated a variable-rate irrigation (VRI) management method for five crop years in the Mississippi Delta.VRI management significantly reduced irrigation water use in comparison with uniform-rate irrigation (URI). There was no significant difference in grain yield and irrigation water productivity between VRI and URI management.Soil apparent electrical conductivity (ECa) was used to delineate irrigation management zones and generate VRI prescriptions.Sensor-measured soil water content was used in irrigation scheduling.Abstract. Variable-rate irrigation (VRI) allows producers to site-specifically apply irrigation water at variable rates within a field to account for the temporal and spatial variability in soil and plant characteristics. Developing practical VRI methods and documenting the benefits of VRI application are critical to accelerate the adoption of VRI technologies. Using apparent soil electrical conductivity (ECa) and soil moisture sensors, a VRI method was developed and evaluated with corn and soybean for five crop years in the Mississippi Delta. Soil ECa of the study fields was mapped and used to delineate VRI management zones and create VRI prescriptions. Irrigation was scheduled using soil volumetric water content measured by soil moisture sensors. A center pivot VRI system was employed to deliver irrigation water according to the VRI prescription. Grain yield, irrigation water use, and irrigation water productivity in the VRI treatment were determined and compared with that in a uniform-rate irrigation (URI) treatment. Results showed that the grain yield and irrigation water productivity between the VRI and URI treatments were not statistically different with both corn and soybean crops. The VRI management significantly reduced the amount of irrigation water by 22% in corn and by 11% in soybean (p = 0.05). Adoption of VRI management could improve irrigation water use efficiency in the Mississippi Delta. Keywords: Soil electrical conductivity, Soil moisture sensor, Variable rate irrigation, Water management.

Fitting of Water Requirement and Yield of Winter Wheat in North China Plain Based on Artificial Neural Network

The fitting of water requirement and yield during the growth period of winter wheat can improve yield effectively and improve irrigation water use efficiency with a certain amount of resource input. This paper selects the irrigation amount, precipitation and yield of winter wheat at the Wuqiao Scientific Observation and Experimental Station. Fitting the water requirement and yield of winter wheat based on three types of artificial neural networks. This paper uses support vector machine (SVM), thought evolution algorithm to optimize BP neural network (MAE-BP) and generalized regression neural network (GRNN) to fit the water requirement and yield of two crops. The SVM is the model with the highest fitting accuracy among the three models, the RMSE, MAE, NS and R2 between predictive value and true value are 7.45 kg/hectares, 213.64 kg/hectares, 0.8086, 0.9409 respectively.