Assessing the impacts of groundwater management policies on farmer cooperation using agent-based modeling
Sayed-Ali OHAB-YAZDI1, Azadeh AHMADI2()
. Department of Civil Engineering, Isfahan University of Technology, Isfahan 8415683111, Iran . Faculty of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran 1983969411, Iran
This study presents a new holistic framework for modeling farmer decision-making by integrating both top-down and bottom-up approaches. It uses three interlinked subsystems to evaluate how changes in water policies impact farmer decisions and profits: the first model simulates water balance, the second simulates farmer behavior, and the third assesses farmer profits. Two scenarios are explored: Scenario I introduces penalties for groundwater overexploitation, and Scenario II implements awareness raising and training to encourage using modern irrigation systems. The results show that penalties lead to reductions in water requests exceeding limits by 8%, 45%, and 68% for fines of 1000, 5000, and 10,000 IRR·m−3, with corresponding net profit decreases of 1.3%, 8.0%, and 11.6%. The ranges of farmer cooperation for groundwater management vary from 20% to 50% over the 10-year simulation period. In Scenario II, increasing the radius of awareness from 0.5 to 2 km substantially increases the adoption of modern irrigation from 1457 to 2057 farmers. These findings highlight how different policy measures impact various types of farmer based on their specific characteristics and preferences.
Fig.1 Development stages of the behavioral and water resources model.
Water resources
Plain
Total
Urban
Agriculture
Industrial
Urban
Agriculture
Industrial
Groundwater
3.4
175
0.5
5.4
197
0.7
Surface water
23.8
187
84.9
23.8
190
84.9
Total
27.2
362
85.4
29.2
387
85.6
Tab.1 Water consumption volumes (MCM) in the Lenjanat study area
Year
Cereal cultivated area (ha)
Garden cultivated area (ha)
Total (ha)
2004–2005
25,150
3897
29,047
2006–2007
25,245
4521
29,766
2008–2009
16,894
4645
21,539
2010–2011
15,652
5010
20,662
2012–2013
15,031
4576
19,607
2014–2015
13,948
4587
18,535
Tab.2 Irrigated areas in different years in the study area
Fig.2 Agricultural benefits, costs, and net benefits in Lenjanat region.
Parameter
Description
Initial value
Best value
a1
Conversion factor of precipitation in heights
[0.02, 1]
0.025
a2
Conversion factor of precipitation in plains
[0.1, 0.25]
0.21
b
Conversion factor of precipitation over the aquifer area to percolating of the aquifer
[0.1, 0.25]
0.24
c1
Conversion factor of the surface runoff formed in heights
[0.001, 0.01]
0.0078
c2
Conversion factor of the surface runoff formed in plain
[0.01, 0.05]
0.0356
d
Return flow into the aquifer from agricultural water consumption
[0.2, 0.35]
0.222
e
Rate of return flow into the aquifer from industrial water consumption
[0.08, 0.12]
0.0945
f
Rate of return flow into the aquifer from domestic water consumption
[0.5, 0.75]
0.565
S
Groundwater storage coefficient
[0.025, 0.06]
0.0385
C
Rates of water transfer from/into the river
[0.01, 0.08]
0.01
B.f
Boundary flow
[107, 2.7 × 108]
1.58 × 107
Tab.3 Calibration (96 months) and validation (24 months) results of the water resources model
Fig.3 The historical and simulated values of groundwater levels of the calibration (96 months) and validation (24 months).
Fig.4 Variations in water level in the aquifer for different penalties.
Fig.5 Farmer non-cooperation throughout the simulation period.
Fig.6 Excess water demand changes in response to water penalties during the simulation period.
Fig.7 Variations in net crop profits throughout the simulation period.
Fig.8 Changes in the number of users encouraged to install modern irrigation system.
Fig.9 Changes in the water level of the aquifer with users exposed to training or publicity for different neighborhood radii.
Fig.10 Changes in cultivated area irrigated with modern systems during the simulation period.
Fig.11 Expenditures on installing modern irrigation systems.
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