Optimal resource reallocation can achieve water conservation, emissions reduction, and improve irrigated agricultural systems

CONTEXT

Crop production consumes large volumes of fresh water and is a key contributor to anthropogenic greenhouse gas (GHG) emissions. Increasing crop output to ensure adequate food supplies under water and land scarcity relies excessively on intensive agricultural inputs (e.g., fertilizers, pesticides, and agricultural films), leading to irreparable environmental consequences (water scarcity and degradation and GHG emissions). Therefore, research on a nexus approach and resource optimization model were carried out.

OBJECTIVE

To fill the gap of objectives priority and optimal allocation of water resources at irrigation area scale, this study constructed a model to achieve optimal water conservation, GHG emissions reduction, and economic benefit improvement, covering the cumulative environmental burden of agricultural inputs, production processes, trade and consumption related to agricultural activities.

METHODS

Based on a resource-environmental-economic framework, we took the blue water footprint (${\mathrm{WF}}_{\mathrm{blue}}$) as a decision variable and developed an integrated water resource optimization model, which was solved by the non-dominated Sorting Genetic Algorithm-II in Matlab. Minimizing crop water footprint (${\mathrm{WF}}_{\mathrm{crop}}$), minimizing crop carbon emissions (${\mathrm{CE}}_{\mathrm{crop}}$) and maximizing crop economic benefits (${\mathrm{EB}}_{\mathrm{crop}}$) were the objectives of the model, and blue water resource, food security, electric energy consumption and land security were the constraint conditions. In addition, three scenarios were tested based on the priority of the objective functions.

RESULTS AND CONCLUSIONS

Annually, ${\mathrm{WF}}_{\mathrm{crop}}$ was 1234.29 × 10⁶ m³ and ${\mathrm{CE}}_{\mathrm{crop}}$ was 522.45 Gg CO₂ eq for food production in Lianshui Irrigation District from 2005 to 2019. Grain crops exhibited a greater ${\mathrm{WF}}_{\mathrm{crop}}$ and contributed significantly more to ${\mathrm{CE}}_{\mathrm{crop}}$ than oilseed crops. Virtual water and carbon flows increased with food transfer. By adjusting the ${\mathrm{WF}}_{\mathrm{blue}}$ of crops compared to the baseline scenario (BS), the average ${\mathrm{WF}}_{\mathrm{crop}}$ decreased by 10.0 %, ${\mathrm{CE}}_{\mathrm{crop}}$ decreased by 4.0 %, and ${\mathrm{EB}}_{\mathrm{crop}}$ increased by 6.4 % under Scenario 2 (minimizing ${\mathrm{WF}}_{\mathrm{crop}}$ and maximizing ${\mathrm{EB}}_{\mathrm{crop}}$), respectively. Similarly, there were average reductions of 9.2 % in ${\mathrm{WF}}_{\mathrm{crop}}$, 6.2 % in ${\mathrm{CE}}_{\mathrm{crop}}$, and ${\mathrm{EB}}_{\mathrm{crop}}$ increased by 5.6 % under Scenario 3 (minimizing ${\mathrm{CE}}_{\mathrm{crop}}$ and maximizing ${\mathrm{EB}}_{\mathrm{crop}}$) compared to the BS. Therefore, the integrated model achieved the optimization objectives.

SIGNIFICANCE

This research not only broadens the scope of traditional environmental impact assessments in agricultural production, but also underscores the positive impact of scientifically and rationally redistributing resources for water conservation, GHG emissions reduction, and economic benefit improvement.