TRADE-OFFS IN THE DESIGN OF SUSTAINABLE CROPPING SYSTEMS AT A REGIONAL LEVEL: A CASE STUDY ON THE NORTH CHINA PLAIN

doi:10.15302/J-FASE-2021434

Front. Agr. Sci. Eng.

2022, Vol. 9

Issue (2) : 295-308 https://doi.org/10.15302/J-FASE-2021434

RESEARCH ARTICLE

TRADE-OFFS IN THE DESIGN OF SUSTAINABLE CROPPING SYSTEMS AT A REGIONAL LEVEL: A CASE STUDY ON THE NORTH CHINA PLAIN

Jeroen C. J. GROOT^1,^2,³, Xiaolin YANG⁴(

)

¹. Farming Systems Ecology, Wageningen University & Research, P.O. Box 430, 6700 AK Wageningen, the Netherlands
². International Maize and Wheat Improvement Center (CIMMYT), Sustainable Intensification Program, Carretera México-Veracruz, Km. 45, El Batán, 56237 Texcoco, México
³. Alliance of Bioversity International and CIAT, Performance, Innovation and Strategic Analysis for Impact unit, Via di San Domenico 1, 00153 Rome, Italy
⁴. College of Water Resources & Civil Engineering, China Agricultural University, Beijing 100193, China

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Abstract

● Impacts of 30 cropping systems practiced on the North China Plain were evaluated.

● Trade-offs were assessed among productive, economic and environmental indicators.

● An evolutionary algorithm was used for multi-objective optimization.

● Conflict exists between productivity and profitability versus lower ground water decline.

● Six strategies were identified to jointly mitigate the trade-offs between objectives.

Since the Green Revolution cropping systems have been progressively homogenized and intensified with increasing rates of inputs such as fertilizers, pesticides and water. This has resulted in higher crop productivity but also a high environmental burden due to increased pollution and water depletion. To identify opportunities for increasing the productivity and reducing the environmental impact of cropping systems, it is crucial to assess the associated trade-offs. The paper presents a model-based analysis of how 30 different crop rotations practiced in the North China Plain could be combined at the regional level to overcome trade-offs between indicators of economic, food security, and environmental performance. The model uses evolutionary multi-objective optimization to maximize revenues, livestock products, dietary and vitamin C yield, and to minimize the decline of the groundwater table. The modeling revealed substantial trade-offs between objectives of maximizing productivity and profitability versus minimizing ground water decline, and between production of livestock products and vitamin C yield. Six strategies each defining a specific combination of cropping systems and contributing to different extents to the various objectives were identified. Implementation of these six strategies could be used to find opportunities to mitigate the trade-offs between objectives. It was concluded that a holistic analysis of the potential of a diversity cropping systems at a regional level is needed to find integrative solutions for challenges due to conflicting objectives for food production, economic viability and environmental protection.

Keywords crop rotation food security multi-objective optimization water use

Corresponding Author(s): Xiaolin YANG

Just Accepted Date: 18 February 2022 Online First Date: 17 March 2022 Issue Date: 25 May 2022

Cite this article:

Jeroen C. J. GROOT,Xiaolin YANG. TRADE-OFFS IN THE DESIGN OF SUSTAINABLE CROPPING SYSTEMS AT A REGIONAL LEVEL: A CASE STUDY ON THE NORTH CHINA PLAIN[J]. Front. Agr. Sci. Eng. , 2022, 9(2): 295-308.

URL:

https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2021434
https://academic.hep.com.cn/fase/EN/Y2022/V9/I2/295

Fig.1 Methodological framework of the research. PCA, principal component analysis; HCA, hierarchical cluster analysis.

Fig.2 Performance of cropping systems in terms of the selected model indicators of economic revenues, decline in water table (NWD) (a) nutritional systems yield of livestock products (NSY_LP) (b, c), dietary energy (NSY_DE) (d-f), and vitamin C (NSY_VC) (g-j). The dominant cropping system of winter wheat-summer maize is labeled as 0 and the five most frequently selected cropping systems in the multi-objective optimization as 1 to 5 (see Table 1). Cropping systems 1 and 2 overlap for most indicators and are indicated with ‘1/2’. P, persons.

Fig.3 Relationships between indicators in the multi-objective optimization: economic revenues, decline in water table (NWD) (a) nutritional systems yield of livestock products (NSY_LP) (b, c), dietary energy (NSY_DE) (d-f), and vitamin C (NSY_VC) (g-j). The result set contained 2500 configurations; each dot represents a different configuration of cropping system areas. The set of options is surrounded by a “hull” (gray line). Solutions were clustered into six clusters based on objectives and cropping system areas. P, persons.

Fig.4 Proportion of area occupied by five different cropping systems for six clusters in the solution set of the multi-objective optimization. Cropping systems: (a) rainfed spring peanut, (b) rainfed spring soybean, (c) ryegrass-sorghum-WM, (d) Spinach-spring maize, (e) sweet potato-cotton-sweet potato-WM. WM, winter wheat–summer maize.

Tab.1 Proportions of cropping systems and performance indicators for five development scenarios focusing on economy, environment, nutrition or constituting a compromise

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