Deficit irrigation (DI) has been widely investigated as a valuable and sustainable production strategy in dry regions. By limiting water applications to drought-sensitive growth stages, this practice ...aims to maximize water productivity and to stabilize – rather than maximize – yields. We review selected research from around the world and we summarize the advantages and disadvantages of deficit irrigation. Research results confirm that DI is successful in increasing water productivity for various crops without causing severe yield reductions. Nevertheless, a certain minimum amount of seasonal moisture must be guaranteed. DI requires precise knowledge of crop response to drought stress, as drought tolerance varies considerably by genotype and phenological stage. In developing and optimizing DI strategies, field research should therefore be combined with crop water productivity modeling.
•Water consumption and economic profits of maize production under different irrigation methods and water levels were evaluated in an arid area.•Lower Ky under drip irrigation indicates the lesser ...reduction in yield caused by the declined ETc than furrow irrigation.•Drip irrigation had the higher water consumption coefficient in maize’s R3-R6 stages than border and furrow irrigations.•Drip irrigation with SMP threshold of −30 kPa or 360-mm furrow irrigation is recommended.
Water scarcity is everywhere and more prominent in arid and semi-arid regions. Moreover, water allocation for irrigation is hit by other economic sectors for low per capita profit. It is inevitable to extend higher-efficient irrigations to replace conventional border irrigation. A three-year field experiment was conducted to examine the effects of different irrigation methods on maize’s water use and economics in the Hetao Irrigation District of China. Taking 525-mm border irrigation as the control, furrow and drip irrigations at three water levels were implemented. Furrow irrigation included 100 % (450 mm), 80 % (360 mm) and 60 % (270 mm) of the recommended level, while three threshold values of soil matric potential: −10 kPa, −30 kPa, and −50 kPa, were used to trigger drip irrigation. The grain yield, ETc (water consumption for the whole growing season), ETcs (water consumption during a special growth stage), and water productivity were affected significantly by the irrigation methods and water levels. The average ETc of border, furrow and drip irrigations was 537.4 mm, 401.8–514.4 mm, and 306.6–496.2 mm for different levels, respectively. On average 10 % of the irrigation water was lost through deep percolation under border irrigation, while 10.5–29.0 mm of groundwater contributed to ETc under drip irrigation with −50 kPa. The higher Kwc (water consumption coefficient) was observed in R3-R6 (Milk-Maturity) stages under drip than border and furrow irrigations. The lower Ky (yield response factor) of drip (0.68) than furrow (0.82) indicated the lesser reduction in yield induced by the decreased ETc under drip irrigation. The 360-mm furrow irrigation obtained a comparable grain yield and net profit with the control, but reduced water application by 31 %. Drip irrigation at −30 kPa enhanced yield by 15 %, increased net profit by 23 %, and reduced water application by 57 %. Thus, drip irrigation at −30 kPa is recommended as the priority to replace border irrigation for maize production in the study area. If drip irrigation is unavailable, a 360-mm furrow irrigation is also an alternative to reduce water application without compromising benefit.
•A two-level optimization model was developed with combined use of SWAP-EPIC model.•CWFPs were derived using SWAP-EPIC considering effects of crop, soil and climate.•Irrigation water and crop area ...allocation was optimized on farm and district scale.•A case study of the YID indicated that 23% water-saving amount could be obtained.
Water scarcity has been a crucial issue for sustainable irrigated agriculture in the arid regions. In these regions where conserving water is paramount, optimal allocation and utilization of irrigation water is particularly important. In this study, a process-based regional economic optimization (PBREOP) model was developed for maximizing irrigation water use efficiency and economic benefit of an irrigation system. The PBREOP model is a two-level optimization model with combined use of an agro-hydrological model (SWAP-EPIC). The first level (farm scale) dealt with the optimal distribution of irrigation water and cropping pattern considering various crops and soils in a subsystem, using a non-linear programing technique. The second level (district scale) sought out the optimal strategy for irrigation water allocation among different subsystems using a dynamic programing algorithm. The crop water production functions (CWPFs) were an important component of the first-level objective function. They were derived with the SWAP-EPIC model considering different irrigation alternatives. The model was solved using the decomposition-harmonization method for large systems. The Yingke Irrigation District (YID) in the middle Heihe River basin, Northwest China was used as a case to test the PBREOP model. Nine CWPFs for three major crops and three major soils were firstly derived based on the simulations of different irrigation levels and climate conditions (20 years). Next, the PBREOP model for YID was established with 11 subsystems, and applied to the irrigation water use optimization under five water supply scenarios. Results showed that the total economic benefit in YID could be increased by 15% on average through the optimization of water allocation and cropping pattern with the same water supply amount as that of the current situation. A variation range of the risk was also obtained with considering the impacts of climate uncertainties. Scenario analysis showed that the total irrigation water could be reduced by 23% on average without benefit reduction when compared to the benefit of the present situation. Model test indicated that the proposed PBREOP model can efficiently optimize irrigation water use and cropping pattern on a regional scale.
To optimize the irrigation scheduling of field crops to maximize irrigation water productivity requires expert knowledge of the crop development and its productive response to water deficit. ...Implementing this idea with commodities such as barley, whose current global profitability is low, and, more specifically, in areas where the availability of water resources for irrigation is limited, requires a proper decision support system. In this research, AquaCrop and MOPECO models were used to compute and compare both the crop-water production and irrigation water productivity functions generated by several irrigation strategies provided by each model for the typical irrigated crop barley grown in the area. Furthermore, we evaluated both models’ performance with a 3-year field experiment applying the methodology of optimized regulated deficit irrigation for limited volumes of irrigation water (ORDIL) in barley crop. The results obtained from the production functions show that gross irrigation water depths (GIWD) of more than 310 mm can be useful to attain the potential crop yield, depending on the criteria considered to generate the irrigation scheduling. However, with less GIWD available, the simulated barley development was subjected to water deficit, leading to a reduction in both crop yield and irrigation water productivity. Thus MOPECO simulated higher crop yields and irrigation water productivity values than those obtained by AquaCrop, being between 16% and 27% for crop yields and between 8.0% and 27.5% for irrigation water productivity, under similar GIWD levels. These differences are mainly due to how the irrigation strategies are outlined in the two models and the different evapotranspiration methodologies they deploy. Finally, both models provided performed appropriately in simulating final crop yield (errors lower than 0.50 × 103 kg ha−1), as well as canopy cover and aboveground biomass evolution, in the case of AquaCrop, whose goodness of fit indicators were close to 0.90 or higher. In terms of crop evapotranspiration, AquaCrop simulated a 12% higher average value than MOPECO. It can be concluded that both models are complementary, and their use will depend on the necessities of the final user. Thus, MOPECO offers a wider range of irrigation strategies, while AquaCrop offers a more detailed information about the physiological response of the crop during its development, being the results of the simulations accurate enough in both models.
•Barley water production functions generated by AquaCrop and MOPECO were assessed.•Results were compared with those reached in a 3-year deficit irrigation experiment.•No significant water productivity differences arose for similar irrigation schedules.•AquaCrop offers a wider range of results and the progression of the crop development.•MOPECO offers tools for optimizing deficit irrigation that increase water productivity.
Precision irrigation management is the key to saving water, improving fruit quality and increasing yield of citrus. In this study, six water-yield models and three water-fruit quality models were ...proposed based on 4-year field data. Then, six scenarios were set with crop total available water (CTW) from 550 to 800 mm at intervals of 50 mm, and a simulation optimization model coupling water-yield, water-fruit quality models and NSGA-II was developed to optimize water allocation strategies. The results showed that six water-yield models performed well in predicting citrus yield, especially Minhas model (R2=0.81). Three water-fruit quality models could well predict the physical quality of citrus fruit (R2=0.72–0.92), but only the Q-Rao model could accurately predict the chemical quality due to its development considering the response processes of fruit quality to deficit irrigation. Therefore, Minhas and Q-Rao models were recommended to predict citrus yield and fruit quality, respectively. The optimization results showed that the optimal water allocation strategy under CTW= 630 mm produced an acceptable yield while improving fruit chemical quality and water use efficiency. When CTW was greater than 630 mm, the optimal water allocation strategy had little difference. Therefore, the optimal water allocation strategy under CTW= 630 mm, which was 14, 104, 325, and 187 mm at bud bust to flowering stage, young fruit stage, fruit expansion stage, and fruit maturation stage, respectively, was recommended to be used under sufficient water resources conditions (CTW ≥ 630 mm). When CTW was between 550 and 630 mm, the optimal water allocation strategy changed. As a result, the optimal water allocation strategy was chosen based on the findings as well as the actual local CTW under limited water resource conditions (CTW = 550–630 mm). The findings of this study will be useful in developing appropriate irrigation strategies in Southwest China, to achieve efficient and sustainable citrus production.
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•Minhas and Q-Rao models showed high accuracy in predicting citrus yield and fruit quality, respectively.•Developed Q-Rao model considered the response of fruit quality to water deficit.•Coupling Minhas, Q-Rao models with NSGA-II to optimize water allocation schedule.•The optimal water allocation plans raised fruit quality and water use efficiency under different scenarios.
•Effects of main tillage practices on crop yield, water consumption and water use efficiency of wheat and maize in Northern China were evaluated.•Subsoiling (SS) increased crop yield but consumed ...more water, and is suitable for winter wheat and summer maize in North-central China.•Mulching (M) significantly increased crop yield and conserved more soil water.•Ridge and Furrow Planting with Mulching (F–M) increased both wheat and maize yield, and was of more beneficial for maize than wheat.•M and F–M are suitable for spring maize in North-central China as well as wheat and maize in Northwest and Northeast China.
Water deficiency seriously restricts the agricultural production in Northern China. Soil tillage practices can conserve water and increase yield effectively, but the regional applicability of soil tillage practices has not been systematically studied so far. It is significant to study the regional characteristics of tillage practices on water-conserving and yield-increasing so that the optimal practices for improving the crop water production and maintaining the agricultural sustainable development can be determined. This study applied the meta-analysis method to analyze results extracted from 156 peer-reviewed published papers conducted at 62 agricultural experimental sites for evaluating the effects of commonly used tillage practices, i.e., No-tillage (NT), Subsoiling (SS), Mulching (M), Ridge and Furrow Planting without Mulching (F), and Ridge and Furrow Planting with Mulching (F–M) on crop yield, water consumption and water use efficiency (WUE) of wheat and maize in Northern China. The results showed that NT only increased yield of winter wheat in North-central China and spring maize in Northeast China. SS increased wheat and maize yield by 16.3 ± 3.2 % and 9.2 ± 3.0 %, and increased water consumption by 8.4 ± 3.4 % and 1.8 ± 1.8 %, respectively. M increased the yield of wheat and maize by 14.9 ± 2.9 % and 17.7 ± 6.2 %, respectively, while it did not increase the water consumption. F increased the yield of wheat by 5.0 ± 1.1 %. F–M increased wheat and maize yield by 18.9 ± 6.3 % and 36.6 ± 11.8 %, respectively. This study recommends that, SS is suitable for winter wheat and summer maize in North-central China. M and F–M are suitable for spring maize in North-central China as well as wheat and maize in Northwest and Northeast China
The crop-water production function (CWPF) is widely used to quantitatively describe relationships between crop water deficit and yield, and evaluate the effects of different irrigation strategies in ...agro-hydrological models. In order to reasonably and reliably estimate crop yield and optimize irrigation scheduling, a novel CWPF was proposed by combining the plant water deficit index (PWDI), estimated based on root-weighted soil water availability, with a daily water sensitivity index derived from a sigmoidal cumulative function. Parameterized using data from a two-year winter wheat field lysimetric experiment conducted in the North China Plain and from a previously published two-year spring maize field drip irrigation experiment in Inner Mongolia, China, the CWPFs provided reasonable estimation of different crop yields with different water stress response characteristics under different field environments. Through coupling the genetic algorithm with the integrated simulations of soil water dynamics, PWDI and CWPF in the soil-wheat system, an optimization procedure was developed to determine PWDI threshold combinations to timely trigger irrigation according to pre-designed crop water deficit status. Crop yield and water use efficiency (WUE) of winter wheat were estimated and compared under different optimized constant and variable PWDI threshold combinations. In addition, the effects of climate change on the optimized variable PWDI threshold combinations were investigated using 38 years of historic meteorological data. The results showed that regulated deficit irrigation (RDI) with a variable threshold combination, in which the sensitivity characteristics to water deficit were considered for the crop at different growth stages, was superior to a constant threshold in enhancing crop yield and WUE. Irrespective of the number of irrigation events (1, 2, 3 or 4) during the growing season, the coefficients of variation (CV) of optimized PWDI thresholds for different combinations of irrigation sequence and events were not very large under the same kind of hydrological year (wet, normal or dry), with CV < 0.39 and a median of 0.21. When the mean (MN) of the optimized PWDI threshold combinations for different irrigation sequence and events was used to schedule RDI of winter wheat in terms of various hydrological years, up to 91% of the estimated relative yield was found to be higher than 90% of the corresponding maximum values. Therefore, the MN can be valuable in formulating rational irrigation management strategies of winter wheat to achieve relatively high yields with limited water under changing climatic conditions.
•An agro-economic model is developed to connect producer evapotranspiration (ET) targets to expected profit and water use.•The model is used to investigate the economic optimality of deficit ...irrigation (ET targets <100%).•Deficit irrigation can be optimal under a range of maize grain prices and input costs if the opportunity cost of water is sufficiently high ($0.207m−3 given 2015 prices and costs).
In many arid regions of the world, population growth, groundwater depletion, and uncertain supplies have caused water for agricultural production to become increasingly scarce. Deficit irrigation (DI) provides a potential response to water scarcity, but no consensus exists on its economic viability. In this paper, we develop an agro-economic model that connects plant growth-stage-specific evapotranspiration (ET) targets with farm profitability. We use the model to determine the economic conditions under which ET targets of less than 100% are optimal for profit-maximizing maize farmers in Colorado. With 2015 input costs, as maize grain prices increase beyond $0.19kg−1, DI can become optimal during the late vegetative growth stage but requires a water cost greater than U.S. $0.21m−3. Under some output price and water cost combinations, DI in the maturation stage also becomes optimal. These results suggest that producers could respond to increasing water scarcity with deficit irrigation, but only in a range of water costs that depends on output price and production costs.
The potential of digital agriculture to support on-farm decision making is predicated on the assumption that ‘cause-and-effect’ relationships can be encoded in a mathematical form. One particularly ...important application area is irrigation decision making, which is informed by the relationship between applied water and end-of-season crop yield (‘water production relations’). Yet this relationship is often partial, owing to its many determining factors, especially for woody perennial crops such as grapevines. Process-based models are a way in which to represent these relationships in a manner that is both interpretable and generalizable. Here we conduct numerical experiments using a process-based crop model to evaluate water production relations for grapevines and how these relations are influenced by genetic and environmental factors as well as irrigation timing decisions. A real-world case study representing a Shiraz vineyard in South Australia is considered. Results show a largely linear relation between total irrigation applied and yield across all numerical experiments, notwithstanding significant uncertainty due to genetic and environmental factors. However, when considering water production relations in relative terms (e.g., change in tonnes per megalitre), the influence of these factors between seasons is reduced, allowing for more robust insights. Exploration of water productivity as a function of phenological stage shows that the average production sensitivity is greatest during veraison (3.5 tonnes per megalitre) and least between bud burst and flowering (2.3 tonnes per megalitre), despite considerable overlap in productivity range between stages. By putting meaningful bounds on water production relations through process-based modeling, growers and their advisors can achieve improved farm outcomes by better informed water application decisions.
•Numerical experiments with a crop model used to evaluate water production relations.•Accounted for influence of water application decisions as well as genetic and environmental factors.•A viticulture case study is considered.
•Regional crop water production function accounting for the spatial heterogeneity of sensitive crop yield parameter is acquired with a distributed ecohydrological model.•Natural runoff of sub-basins ...is reproduced by this distributed ecohydrological model in the period with great human activities.•An agricultural water optimization model at the basin scale is constructed with the derived crop water production function and natural runoff.•The agricultural water optimization can effectively guarantee the crop yield and improve the water resources utilization.
Agricultural water optimization at the basin scale is critical for sustainable irrigated agriculture and water resources management. Crop Water Production Function (CWPF) and surface water are key components of agricultural water optimization. CWPF relates closely to crop yield/growth-related parameters, and surface water of sub-basins is often different and impacted by water withdrawals. However, CWPF accounting for the crop yield-related parameter and natural runoff of sub-basins were scarcely involved in agricultural water optimization at the basin scale. To fill this gap, CWPFs of different water units are estimated using a distributed ecohydrological model involving the spatial heterogeneity of crop photosynthetic capacity parameter, and the natural runoff of sub-basins is reproduced by this model. Integrating these functions and variables, and taking the agricultural benefit of the whole basin as the main objective, an agricultural water optimization model at the basin scale (AWOMB) is developed and applied to a mountain-plain basin in North China. The results showed that agricultural water optimization in a representative year would lead to 0.4% increase of crop production for the whole basin at the expense of certain urban ecological water and equity of agricultural water. In this scenario, the river ecological water requirements in all sub-basins would be satisfied. Assuming the domestic, industrial and river ecological water demand being fully satisfied in 2020s, water deficits will be 8% and 26% for the whole basin under the normal and dry year scenarios, respectively. Correspondingly, increments of 2% and 7% crop production are predicted in these two scenarios by agricultural water optimization. It is demonstrated that water resources utilization and agricultural production are effectively improved by coupling a distributed ecohydrological model with water resources optimization in the study basin. This research provides a methodology for integrative catchment water resources management.
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