Assessment of Water, Food, and Energy Productivity Indices Using the WA+ Water Accounting Framework and a Nexus Approach

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Homepage: https://jwim.ut.ac.ir/

University of Tehran Press

Assessment of Water, Food, and Energy Productivity Indices Using the WA+ Water Accounting Framework and a Nexus Approach

Seyyed Ali Moasheri¹ | Saman Javadi²^ | Mahmoud Mashal³ | Hamid Kardan Moghadam⁴ | Behzad Azadegan⁵

1. Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Iran. E-mail:

[email protected]

2. Corresponding Author, Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Iran. E-mail: [email protected]

3. Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Iran. E-mail:

[email protected]

4. Water Research Institute, Ministry of Energy Water Research Institute, Tehran, Iran. E-mail: [email protected] 5. Department of Water Engineering, Faculty of Agricultural Technology, University of Tehran, Iran. E-mail:

[email protected]

Article Info ABSTRACT

Article type:

Research Article

Article history:

Received 27 April 2023 Received in revised form 17 June 2023

Accepted 17 June 2023

Published online 12 October 2023

Keywords:

Groundwater NEXUS Plasjan plain Water accounting

With the aim of increasing water, food and energy productivity, this study was carried out in two stages to develop and validate a tool for evaluating agricultural management strategies in relation to the link between water, food and energy security (NEXUS). In the first part, using the WA+ water accounting framework, with the aim of analyzing the parameters of hydro climatology, the four worksheets of basic resources, evaporation and transpiration, harvesting of water resources and productivity of the Plasjan watershed were calculated and management scenarios were determined to increase productivity, and in the second part, management scenarios with The NEXUS approach were evaluated and prioritized. The results of WA+ showed that in the Plasjan basin, the high volume of evaporation and transpiration was useless. In the second part of this research, among the 4 main scenarios (48 sub-scenarios) introduced to improve productivity, the scenarios of cultivar change and irrigation treatment, change of cultivated area and rainfed cultivation with supplementary irrigation had a positive effect on water, food and energy productivity index. After prioritizing the influential sub-scenarios with the TOPSIS multi-criteria decision-making model, the sub-scenario of wheat variety 6 with full irrigation treatment had the most positive effect on water, food and energy productivity and was identified as an indicator scenario for evaluating productivity in agricultural management.

Cite this article: Moasheri, S. A., Javadi, S., Mashal, M., Kardan Moghadam, H., & Azadegan, B. (2023). Assessment of Water, Food, and Energy Productivity Indices Using the WA+ Water Accounting Framework and a Nexus Approach.

Journal of Water and Irrigation Management, 13 (3), 715-733. DOI: https://doi.org/10.22059/jwim.2023.357988.1069

DOI: https://doi.org/ 10.22059/jwim.2023.357988.1069

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Figure 1. Studied area (Rahimzadeh et al., 2019)

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Figure 2. Using the NEXUS approach in evaluating water, food energy productivity indicators using the WA+ water accounting system

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Table 1. Defined scenarios and sub-scenarios

Scenario Sub-scenario

Sub-scenario code Scenario

Sub-scenario Sub-scenario

code

10% addiction in Alfalfa cultivation area Scp22

Intense Deficit irrigation S.atd1

S1 Medium deficit irrigation

S.atd2

Mild deficit irrigation S.atd3

10% addiction in Barley cultivation area Scp25

10% reduction in fodder corn cultivation area Scp1

S2 20% addiction in Barley cultivation area Scp26

30% addiction in Barley cultivation area Scp27

10% addiction in Wheat cultivation area Scp28

10% reduction in canola cultivation area Scp4

Supplemental irrigation with rain 448mm SR1

10% reduction in Alfalfa cultivation area Scp7

S3 Supplemental irrigation with rain 339mm SR2

Supplemental irrigation with rain 193mm SR3

Wheat cultivar1 and full irrigation Sc1t1

10% reduction in Barley cultivation area Scp10

Wheat cultivar1 and deficit irrigation Sc1t2

20% reduction in Barley cultivation area Scp11

S2 30% reduction in Barley cultivation area

Scp12

10% reduction in Wheat cultivation area Scp13

20% reduction in Wheat cultivation area Scp14

S4 Wheat cultivar3 and deficit irrigation

Sc3t2 30% reduction in Wheat cultivation area

Scp15

10% addition in fodder corn cultivation area Scp16

20% addition in fodder corn cultivation area Spc17

30% addition in fodder corn cultivation area Spc18

10% addiction in canola cultivation area Spc19

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Table 2. Resources and consumption management scenarios in line with implementation of the drought adaptation program Sub-scenario Water consumption (million cubic meters/Year) Cultivation area(ha)

Fodder corn

^Canola ^Alfalfa ^Barley ^Wheat Fodder corn ^Canola ^Alfalfa ^Barley ^Wheat

Current 12.96 ^0.07 ^31.08 ^5.22 ^8.98 ¹²⁰⁰ ¹⁴ ³⁰⁰⁰ ⁷⁰⁰ ²³⁵⁰

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Table 3. Water, food and energy productivity indices

Water productivity index Food productivity index

Energy productivity index (Kg/J) Sub-scenario code

Scenario

8.537 0.873

28.097 Current Situation

8.537 0.575

11.520 S.atd1

S1 S.atd2 15.173 0.665 8.537

8.537 0.798

22.759 S.atd3

8.537 0.808

26.716 Scp1

S2

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25.292 Scp2

8.537 0.682

23.825 Scp3

8.537 0.871

28.100 Scp4

8.537 0.871

28.102 Scp5

8.537 0.871

28.105 Scp6

8.537 0.845

28.979 Scp7

8.537 0.819

29.971 Scp8

8.537 0.793

31.096 Scp9

8.537 0.869

28.195 Scp10

8.537 0.867

28.293 Scp11

8.537 0.864

28.393 Scp12

8.537 0.863

28.538 Scp13

8.537 0.855

29.001 Scp14

8.537 0.847

29.487 Scp15

8.537 0.934

29.440 Scp16

8.537 0.997

30.744 Scp17

8.537 1.061

32.012 Scp18

8.537 0.871

28.095 Scp19

8.537 0.872

28.090 Scp20

8.537 0.871

28.095 Scp21

8.537 0.898

27.309 Scp22

8.537 0.924

26.601 Scp23

8.537 0.950

25.960 Scp24

8.537 0.874

28.001 Scp25

8.537 0.876

27.906 Scp26

8.537 0.879

27.812 Scp27

8.537 0.880

27.677 Scp28

8.537 0.888

27.275 Scp29

8.537 0.896

26.891 Scp30

8.666 0.895

33.400 Sr1

S3 Sr2 28.411 0.877 8.947

8.321 0.883

31.062 Sr3

11.723 0.872

33.797 Sc1t1

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33.354 Sc1t2

11.839 0.883

34.178 Sc2t1

18.976 0.868

33.679 Sc2t2

11.553 0.878

34.018 Sc3t1

19.431 0.869

33.707 Sc3t2

11.750 0.873

33.845 Sc4t1

18.247 0.868

33.651 Sc4t2

11.966 0.879

34.025 Sc5t1

21.057 0.869

33.714 Sc5t2

11.990 0.878

34.011 Sc6t1

17.923 0.865

33.568 Sc6t2

Table 4. Energy index in the current situation in the production system of studied products in Plasjan region

Energy index Unit Wheat Barley Canola Alfalfa Fodder corn

Output energy MJ. ha-1 123430 114652.1 51805.2 218561.4 171810

Pure energy MJ. ha-1 77171.758 75044.916 12992.855 123384.33 111143.99

Energy efficiency - 2.67 2.89 7.33 2.30 2.83

Special energy MJ. ha-1 11.564 9.902 17.530 9.517 1.0111

Energy efficiency MJ. ha-1 0.086 0.101 0.057 0.105 0.989

Forms of energy

Direct energy MJ. ha-1 30424 25192.86 26366.6 79165.6 45272.18

Indirect energy MJ. ha-1 15834.242 14414.324 12445.745 16011.47 15393.83

Renewable energy MJ. ha-1 9913.5 9707.04 5920.16 24402.2 12315.43

Non-renewable energy MJ. ha-1 36344.742 29900.144 32892.185 70774.87 48350.58

(12)

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Figure 3. Radar graph of productivity increase scenarios with a NEXUSNEXUS approach

Figure 4. Comparing the performance of scenarios with a positive effect on increasing productivity with a NEXUS approach

0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0

water efficiency index

Food efficiency index Energy efficiency index

Sc6t1

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(14)

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index

Food efficiency index

Water efficiency index

Subscenario

code Scenario description Subscenarios

prioritization

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3.000 3.431 3.279 Scp18 30% addition in fodder corn cultivation area 6 3.000 3.286 3.188 Scp17 20% addition in fodder corn cultivation area 7

3.030 3.051 3.377 Sr1 Supplemental irrigation with rain 448mm 8

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