Investigation, Modeling, and Optimization Nexus of Water, Energy, and Food in Paddy Production in Rasht County

Document Type : Research Paper

Authors

1 Department of Biosystems Engineering, Faculty of Agriculture, Shahid Chamran University of Ahvaz,, Ahvaz, Iran

2 Department of Biosystems Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran

3 Department of Water Engineering, Faculty of Agricultural Sciences, University of Guilan, Rasht

Abstract

The growing population and increasing demand for natural resources present significant challenges. The nexus approach, which involves modeling and optimizing the consumption of water, energy, and food, enhances resource efficiency and ensures the sustainability of interconnected systems. This study focuses on investigating, modeling, and optimizing the water-energy-food nexus for paddy production in Rasht County. The objectives were pursued through two scenarios: high-yield paddy production and agricultural consolidation, utilizing the LEAP, WEAP, and MGP models. Data were collected from farmers, organizations, and library sources. Optimization was conducted using the NSGA-II algorithm. Inputs such as fuel, electricity, agricultural machinery, chemicals, organic materials, labor, and water were analyzed. The water resources considered included those for drinking, industrial, and agricultural purposes, as well as rivers, channels, ponds, and groundwater. The results revealed that the average energy consumption and production in the high-yield paddy variety scenario were higher compared to the agricultural consolidation scenario. The average water consumption in both scenarios showed no significant difference until 2040. Modeling results indicated that under ideal conditions, the RMSE, R², MAPE, and EF values were 353.110, 0.9032, 10.831, and 0.891, respectively. The optimization findings demonstrated that under ideal conditions, water and energy consumption, and paddy production were reduced by 0.94%, 0.53%, and 3.26%, respectively.

Keywords

Main Subjects

EXTENDED ABSTRACT

Introduction

The increasing population and growing demand for natural resources pose significant challenges. By 2030, water demand is expected to rise by 40%, and food and energy demands are projected to increase by 15% each. The agricultural sector, a major food provider, requires substantial water and energy, contributing to challenges such as droughts, global warming, and ecosystem damage. The nexus approach, focusing on sustainable use of limited resources, improves understanding of the interconnections between water, energy, and food. Modeling and optimizing this approach can improve resource efficiency and ensure sustainability in these interconnected systems.

Materials and Methods

This study aims to investigate, model, and optimize the water-energy-food nexus in paddy production in Rasht County, Iran. This objective was addressed through two scenarios using LEAP and WEAP software, along with the MGP model, and optimization was performed using the NSGA-II algorithm. Data were collected through questionnaires, documentary sources, and field interviews from a statistical population consisting of farmers and authorized fertilizer and pesticide distributors in Rasht County. Water consumption was simulated from 2020 to 2040 using the WEAP platform. The water resources supplying paddy production, household consumption, and industry in the study area, including channel irrigation, groundwater, ponds, and rivers, were examined. Model calibration was performed using the PEST Calibration plugin. The simulation in LEAP software involved energy resources and consumption data for households and paddy production in the study area. To calculate energy consumption, the usage of each input—such as electricity, fuel, agricultural machinery, labor, pesticides, chemical fertilizers, organic matter, and water—were collected and converted into their equivalent energy values using the relevant energy equivalence coefficients. The production of high-yield rice varieties, such as Fajr and Shiroodi, was considered the first scenario and compared with traditional local rice varieties. Paddy-field consolidation and its comparison with pre-consolidation conditions were considered as the second scenario. Since paddy fields face challenges such as traditional irrigation, irregular land shapes, lack of access paths, and reduced efficiency of agricultural machinery, the consolidation process has led to more uniform water distribution, reduced agricultural input consumption, and alleviated boundary-related issues. The WEAP-LEAP model output was presented in matrix form for the two scenarios. For analysis, the MGP model employed the latest branches of genetic programming. The predicted values (from the MGP model) and the observed values (from the integrated WEAP and LEAP models) were evaluated using EF, R², RMSE, and MAPE. For optimization, three multi-objective functions were used to maximize paddy production, minimize water and energy consumption, with constraints applied.

Results and Discussion

A comparison of energy consumption and production in local and high-yield paddy varieties indicated that local varieties consumed more energy, while high-yield varieties produced higher energy. The energy ratio was found to be 0.53 for local varieties and 0.99 for high-yield varieties. In the second scenario, results showed that energy consumption and production were higher in consolidation fields compared to traditional fields, with an energy ratio of 1.06 for consolidation fields and 0.975 for traditional fields. The analysis of two scenarios revealed that the second scenario was more efficient in terms of water and energy consumption and paddy production. The MGP tree diagram includes 14 nodes, 4 levels, and a complexity of 44, representing potential solutions, evolutionary depth, and the alternatives required to reach feasible solutions. Under optimal conditions, the RMSE, R², MAPE, and EF values were calculated as 110.353, 0.9032, 10.831, and 0.891, respectively. According to the optimization results for water consumption, water demand, cultivated area, and maximum rice production showed improvements of 17.91%, 1.42%, and 0.66%, respectively. Pareto optimization results indicated that under optimal conditions, it is possible to achieve a maximum rice production of 10.666 t/ha. In this case, the minimum water consumption is 652.32 MCM, and the energy consumption is 106223 MJ/ha. Furthermore, Pareto optimization results showed that under optimal conditions, it is possible to achieve a minimum water consumption of 633 MCM and a minimum energy consumption of 152,310 MJ/ha. Under these conditions, rice production was 10,120 and 10,360 t/ha, respectively.

Conclusion

This study investigated, modeled, and optimized the nexus between water, energy, and food in paddy production in Rasht County, Iran. The modeling and optimization results indicated improved results.

Credit authorship contribution statement

Sina Sharifi: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Visualization.

Abbas Asakereh: Conceptualization, Resources, Review and Editing, Supervision, Project administration, Funding acquisition.

Mostafa Kiani Deh Kiani: Review and Editing, Supervision.

Somaye Janatrostami: Supervision.

All authors have read and agreed to the published version of the manuscript.

Data Availability Statement

All data utilized in this study are provided within the text, as well as in the form of tables and figures. Additional data are available from the authors on request.

Acknowledgments

The authors express their gratitude to the Vice Chancellor for Research and Technology of Shahid Chamran University of Ahvaz, Iran, for providing financial support through the research grant (No. SCU.AA98.29747).

Ethical considerations

The authors avoided data fabrication, falsification, plagiarism, and misconduct.

Conflict of interest

The author declares no conflict of interest.

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Iranian Journal of Biosystems Engineering
Volume 55, Issue 4
February 2025
Pages 21-43

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History

  • Receive Date: 09 January 2025
  • Revise Date: 13 February 2025
  • Accept Date: 23 February 2025

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