Optimization of the Cropping Pattern of Main Cereals and Improving Water Productivity: Application of the Water Footprint Concept

Bozorg‐Haddad

et al. 2021

Sci Rep

The worsening water scarcity has imposed a significant stress on food production in many parts of the world. This stress becomes more critical when countries seek self-sufficiency. A literature review shows that food self-sufficiency has not been assessed as the main factor in determining the optimal cultivation patterns. However, food self-sufficiency is one of the main policies of these countries and requires the most attention and concentration. Previous works have focused on the virtual water trade to meet regional food demand and to calculate trade flows. The potential of the trade network can be exploited to improve the cropping pattern to ensure food and water security. To this end, and based on the research gaps mentioned, this study develops a method to link intra-country trade networks, food security, and total water footprints (WFs) to improve food security. The method is applied in Iran, a water-scarce country. The study shows that 781 × 106 m3 of water could be saved by creating a trade network. Results of the balanced trade network are input to a multi-objective optimization model to improve cropping patterns based on the objectives of achieving food security and preventing water crises. The method provides 400 management scenarios to improve cropping patterns considering 51 main crops in Iran. Results show a range of improvements in food security (19–45%) and a decrease in WFs (2–3%). The selected scenario for Iran would reduce the blue water footprint by 1207 × 106 m3, and reduce the cropland area by 19 × 103 ha. This methodology allows decision makers to develop policies that achieve food security under limited water resources in arid and semi-arid regions.

Section: Introductionmentioning

confidence: 99%

Optimal virtual water flows for improved food security in water-scarce countries

Bozorg‐Haddad

et al. 2021

Sci Rep

“…They reported improvement in net financial return by 92.5% and increase in cropped area by 109.7% under deficit irrigation. Etedali et al (2019) employed the linear programming technique to compute the optimal cultivated area for cereals in order to maximize the total national water footprint volume in irrigated and rainfed lands.…”

Section: Introductionmentioning

confidence: 99%

Optimization of water productivity in Bhagwanpur distributary command of India employing TLBO and cuckoo search algorithms

Upadhyaya

2021

Water Policy

Efficient and judicious use of land and water is the need of the hour. In other words, evolving a cropping pattern, which optimizes productivity or net return considering prevailing constraints is quite useful to farmers, because such a cropping pattern is expected to be better than the existing cropping pattern in terms of yielding optimum productivity or net return. A single objective problem consisting of an objective function of optimization of water productivity with prevailing constraints was formulated and three optimization algorithms, namely (i) LINPROG, (ii) teaching learning based optimization (TLBO) and (iii) cuckoo search (CS) were employed to compute optimum water productivity corresponding to various affinity levels. It was observed that all three approaches yielded exactly the same values of water productivity at different affinity levels. TLBO showed better convergence capability as it reached the optimum value of objective function at a lower number of iterations than CS technique. Optimum water productivity at 20% affinity level seems quite practical and reasonable to be recommended in this distributary command for adoption because water productivity value is 2.57 times higher with 98.25 ha less cropped area as compared to the value of water productivity for the existing cropping pattern.

“…Although there are a few studies investigates the uncertainty of parameters with grey data or grey numbers in machine scheduling problems, there are lots of examples about mathematical programming with grey numbers for other problems such as reservoir watershed planning (Chang et al, 1996), water quality management (Huang, 1996;Karmakar and Mujumdar, 2006), project selection (Amirian and Sahraeian, 2018), waste management planning (Huang et al, 1994(Huang et al, , 1995a, game theory (Kose and Forrest, 2015), irrigation planning (Ramezani Etedali et al, 2019), resource allocation (Chalvatzis et al, 2019), electricity generation planning (Malekpoor et al, 2018), economy management (Wang, 2017) and assembly line balancing (Arık et al, 2019). These examples are diversified.…”

Section: Introductionmentioning

confidence: 99%

Single machine earliness/tardiness scheduling problem with grey processing times and the grey common due date

Arık

2020

PurposeThis paper presents a mixed-integer programming model for a single machine earliness/tardiness scheduling problem where the objective is to minimize total earliness/tardiness duration when the uncertainty of parameters such as processing times and due date is coded with grey numbers.Design/methodology/approachGrey theory and grey numbers are used for illustrating the uncertainty of parameters in processing times and common due date, where the objective is to minimize the total earliness/tardiness duration. The paper proposes a 0–1 mathematical model for the problem and an effective heuristic method for the problem by using expected processing times for ordering jobs.FindingsThe uncertainty of the processing times and common due date are encoded with grey numbers and a position-dependent mixed-integer mathematical programming model is proposed for the problem in order to minimize total grey earliness/tardiness duration of jobs having grey processing times and a common due date. By using expected processing times for ranking grey processing times, V-shaped property of the problem and an efficient heuristic method for the problem are proposed. Solutions obtained from the heuristic method show that the heuristic is effective. The experimental study also reveals that while differences between upper and lower bounds of grey processing times decrease, the proposed heuristic's performance decreases.Originality/valueThe grey theory and grey numbers have been rarely used as machine scheduling problems. Therefore, this study provides an important contribution to the literature.