Agent-Based Modeling for Water–Energy–Food Nexus and Its Application in Ningdong Energy and Chemical Base
Abstract
:1. Introduction
2. Case Study Area and Data
2.1. Overview of Ningdong Base Research Area
2.2. Data
3. Methodology
3.1. Agent-Based Modeling (ABM)
3.2. The Programming Software
3.3. Model Design
3.3.1. Agent Designed in the Model
3.3.2. Defining Attributes and Behaviors for an Agent-Based Model Development
3.3.3. The Modeling Framework
- (1)
- “Supply by quantity” and “living first, then production”, giving priority to residential water and important industrial water, and reasonably arranging production, ecological and other water;
- (2)
- The unified deployment of Yellow River water, non-conventional water sources (mine water, recycled water) and groundwater;
- (3)
- The superior water supply. The water needed for living in each park is supplied by the Yellow River, and the water used in coal mines is given priority over mine dewatering water, while the remaining mine dewatering water is mainly used in coal washing and other water industries with low water quality requirements.
4. Results and Discussion
4.1. Model Validation
4.2. Scenario Design
4.3. Scenario Analysis
5. Conclusions
6. Limitations and Future Research Directions
Supplementary Materials
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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---|---|---|
Per capita daily water consumption (m3) | Per capita daily water consumption in urban area | China Economic and Social Big Data Research Platform [24] |
Population (People) | Population in the current year | China Economic and Social Big Data Research Platform [24] |
Irrigation water utilization coefficient | The ratio of the amount of effective water delivered to the field to the water amount diverted to the canal | Represented by the irrigation water utilization coefficient of Ningxia in the Ningxia Water Resources Bulletin [25] |
Sources of water | Yellow River water, groundwater, unconventional water, and reservoirs | Ningxia Water Resources Bulletin [25] |
Coal and coal products (104 t) | Including coal, olefins, ethylene glycol, methanol, thermal power installed capacity, and new energy installed capacity | China Energy Statistical Yearbook [26] |
Urban green space coverage area (km2) | The area of all vegetation in the city, including trees, shrubs, lawns, etc. | China Economic and Social Big Data Research Platform [24] |
Crop prices (CNY/kg) | Prices of wheat, corn, and rice | China Economic and Social Big Data Research Platform [24] |
Crop planting area (km2) | Annual planting area of wheat, corn, and rice | Using genetic algorithms to calculate the irrigation area of crops with the goal of maximizing profits |
Daily electricity demand (kwh) | 6 | https://wen.baidu.com/question/1712571590435501860.html ( accessed on 1 September 2021) [27] |
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Industrial water quota (m3/t) | Water quota for coal and coal products | Ningxia Industrial Water Quota [29] |
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Irrigation water quota (m3/mu) | Irrigation water quota for wheat, corn, and rice | Ningxia Agricultural Water Consumption Quota [31] |
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Energy consumption of sewage treatment (kWh/t) | About 0.35 | https://kns.cnki.net/kns8/Detail?sfield=fn&QueryID=7&CurRec=3&recid=&FileName=BJJN202303029&DbName=CJFDLAST2023&DbCode=CJFD&yx=&pr=&URLID= ( accessed on 25 March 2023) [33] |
Higher-Level Entities | Lower-Level Entities |
---|---|
Resources | Water |
Energy | |
Food | |
Managers | Nature and Ecology Department |
Users | Life Department |
Food Department | |
Energy Department | |
Nature and Ecology Department | |
Water Administration Department |
Agent | Attributes (Data Source) | Behaviors |
---|---|---|
Nature and Ecology Department | Population growth rate [24], cropping structure [24], Irrigation water utilization factor [25], energy structure [26], water sourceb [25] | Coordination of five major departments |
Water Administration Department | Yellow River water [25] Groundwater [25] Others (reclaimed water, mine water) [25] | Domestic water supply Industrial water supply Agricultural water supply Ecological water supply |
Life Department | Population growth rate [24] Domestic water quota [24] Domestic energy consumption quotas [27] | Population water consumption Population energy consumption Food consumption by population Ecological land use per capita |
Nature and Ecology Department | Urban green space coverage area [24] Ecological water quotas [24] Ecological energy consumption Quotas [33] | Ecological greening water consumption Energy consumption of ecological greening |
Energy Department | Coal [26] Coal products [26] New energy [26] Industrial water quota [29] Energy consumption for water supply treatment [33] Energy consumption quotas [33] Drainage energy consumption [33] | Domestic energy consumption Food energy consumption Energy industry water consumption Ecological energy consumption Energy consumption for water treatment in the energy industry Drainage energy consumption |
Food Department | Agricultural water quota [31] Planting area (Calculated by genetic algorithm) Unit energy consumption [41,42] | Irrigation water consumption Irrigation energy consumption Food production |
Time (Year) | Measured Value (Billion m3) | Simulated Value (Billion m3) | Relative Error% between Measured and Simulated Values (%) |
---|---|---|---|
2016 | 1.662 | 1.659 | 0.18 |
2017 | 1.952 | 1.941 | 0.56 |
2018 | 1.900 | 1.859 | 2.16 |
2019 | 1.987 | 1.913 | 3.73 |
2020 | 1.953 | 1.966 | 0.67 |
Scenario Name | Description of Changes in Water Supply and Water Demand Settings | |
---|---|---|
Water Supply Settings | Requirement Setting | |
Baseline scenario | Current water supply: from Yellow River water, groundwater and non-conventional water; irrigation water utilization coefficient according to the actual value, but none of them exceed 0.6 | Current demand situation: calculation of demand for each department based on actual measured data |
Water saving scenarios | The water supply source remains unchanged and the irrigation water utilization factor is increased to 0.68 | Same baseline scenario |
Increased reservoir scenario | Same baseline scenario | Consistent supply and demand |
Integrated scenarios | The water supply source is the same as the baseline scenario, and the irrigation water use factor is the same as the water saving scenario | Same as adding the reservoir scenario |
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Zhu, M.; Yang, G.; Jiang, Y.; Wang, X. Agent-Based Modeling for Water–Energy–Food Nexus and Its Application in Ningdong Energy and Chemical Base. Sustainability 2023, 15, 11428. https://doi.org/10.3390/su151411428
Zhu M, Yang G, Jiang Y, Wang X. Agent-Based Modeling for Water–Energy–Food Nexus and Its Application in Ningdong Energy and Chemical Base. Sustainability. 2023; 15(14):11428. https://doi.org/10.3390/su151411428
Chicago/Turabian StyleZhu, Meilian, Guoli Yang, Yanan Jiang, and Xiaojun Wang. 2023. "Agent-Based Modeling for Water–Energy–Food Nexus and Its Application in Ningdong Energy and Chemical Base" Sustainability 15, no. 14: 11428. https://doi.org/10.3390/su151411428