Coupling Coordination Evaluation of Water and Soil Resource Matching and Grain Production, and Analysis of Obstacle Factors in a Typical Black Soil Region of Northeast China
Abstract
:1. Introduction
2. Materials and Methods
2.1. Theoretical Mechanism
2.1.1. Logical Analysis of Water and Soil Resource Matching and Grain Production
2.1.2. Coupling Mechanism of Water and Soil Resource Matching and Grain Production
2.2. Study Area and Data Sources
2.3. Research Methodology
2.4. Construction of Index System
3. Results
3.1. Analysis of the Matching of Water and Soil Resources under the Water Footprint Perspective
3.2. Analysis Coupling of Water and Soil Resource Matching and Grain Production
3.3. Obstacle Factors Identification
4. Discussion
5. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Liu, X.; Xu, Y.; Sun, S.; Zhao, X.; Wang, Y. Analysis of the coupling characteristics of water resources and food security: The case of Northwest China. Agriculture 2022, 12, 1114. [Google Scholar] [CrossRef]
- Sun, B.; Luo, Y.; Yang, D.; Yang, J.; Zhao, Y.; Zhang, J. Coordinative management of soil resources and agricultural farmland environment for food security and sustainable development in China. Int. J. Environ. Res. Public Health 2023, 20, 3233. [Google Scholar] [CrossRef] [PubMed]
- Sun, Z.; Jia, S.F.; Yan, J.B.; Zhu, W.B.; Liang, Y. Study on the matching pattern of water and potential arable land resources in China. J. Nat. Resour. 2018, 33, 2057–2066. [Google Scholar]
- Liang, A.; Li, L.; Zhu, H. Protection and Utilization of Black Land and Making Concerted and Unremitting Efforts for Safeguarding Food Security Promoted by Sci-tech Innovation—Countermeasures in Conservation and Rational Utilization of Black Land. Bull. Chin. Acad. Sci. 2021, 36, 557–564. [Google Scholar]
- Yang, H.Y.; Zhao, H.F. Analysis of spatio-temporal characteristics and effects of land and water resources matching under cultivated land structure change: A case study of Heilongjiang province. J. Nat. Resour. 2022, 37, 2247–2263. [Google Scholar] [CrossRef]
- Zuniga-Teran, A.A.; González-Méndez, B.; Scarpitti, C.; Yang, B.; Murrieta Saldivar, J.; Pineda, I.; Peñúñuri, G.; Hinojosa Robles, E.; Irineo, K.S.; Müller, S.; et al. Green Belt Implementation in Arid Lands through Soil Reconditioning and Landscape Design: The Case of Hermosillo, Mexico. Land 2022, 11, 2130. [Google Scholar] [CrossRef]
- Gao, Y.; Li, P.; Hou, H.; Liang, Z.; Zhang, Y.; Qi, X. Evaluation of agricultural water and soil resource matching characteristics considering increased precipitation-derived “green water”: A case study in the Yellow River Basin, China. Mitig. Adapt. Strateg. Glob. Chang. 2023, 28, 6. [Google Scholar] [CrossRef]
- Xu, C.; Lin, J.; Song, M. Research on the spatial effects of water and soil matching degree on economic growth of regional agriculture based on empirical analysis during 2003–2013 in China. China Popul. Resour. Environ. 2016, 26, 153–158. [Google Scholar]
- Zhang, Y.; Lei, G.; Zhang, H.; Wang, H. Spatiotemporal Dynamics of Land and Water Resources Matching of Cultivated Land in Typical Basin of Sanjiang Plain—A case Study of Naoli River Basin. Chin. Agric. Resour. Reg. 2022, 43, 49–59. [Google Scholar]
- Abulizi, A.; Ren, Q.; Wang, Y.; Yu, J.; Long, A.; Zhang, J. Analysis on the matching characteristics and stability of oasis water and land resources in the Tarim river basin. J. China Inst. Water Resour. Hydropower Res. 2022, 20, 71–78. [Google Scholar]
- Gao, Y.; Qi, X.B.; Li, P.; Liang, Z.J.; Zhang, Y. Analysis on spatial-temporal matching characteristics of agricultural water and soil resources in the Yellow River Basin. J. Irrig. Drain. 2021, 40, 113–118. [Google Scholar]
- Wang, S.; Wang, L. Matching degree between agricultural water and land resources in the Xijiang River Basin under changing environment. Water 2023, 15, 827. [Google Scholar] [CrossRef]
- Jiang, Q.X.; Fu, Q.; Wang, Z.L.; Jiang, N. Spatial matching patterns of land and water resources in Sanjiang Plain. J. Nat. Resour. 2011, 26, 270–277. [Google Scholar]
- Zhang, Y.; Gao, C.; Liu, C.; Li, P.; Chen, X.; Liang, Z. Evaluation of agricultural water resources allocation efficiency and its influencing factors in the Yellow River Basin. Agronomy 2023, 13, 2449. [Google Scholar] [CrossRef]
- Peng, L.; Deng, W.; Tan, J.; Lin, L. Restriction of economic development in the Hengduan Mountains Area by land and water resources. Acta Geogr. Sin. 2020, 75, 1996–2008. [Google Scholar]
- Wang, J.; Xin, L.; Dai, E. Spatio-temporal variations of the matching patterns of agricultural land and water resources in typical mountainous areas of China. Geogr. Res. 2020, 39, 1879–1891. [Google Scholar]
- Nan, J.Q.; Wang, J.L.; Qin, A.Z.; Liu, Z.D.; Ning, D.F.; Zhao, B. Study on utilization potential of agricultural soil and water resources in northwest arid area. J. Nat. Resour. 2017, 32, 292–300. [Google Scholar]
- Hou, S.; Yuan, W.; Chen, J.; Wang, S.; Chen, Y.; Li, Q. Matching Pattern and Regional of Agricultural Water and Land Resources in Heilongjiang Province. Bull. Soil Water Conserv. 2022, 42, 150–157. [Google Scholar]
- Li, X.; Hao, J.; Chen, A. Time-space matching pattern and evaluation of agricultural water and soil resources in Shandong Province. J. China Agric. Univ. 2020, 25, 1–11. [Google Scholar]
- Huang, K.; Yuan, P.; Liu, G. Research on Water and Soil Resources Matching in Sichuan Province Based on DEA. China Rural Water Hydropower 2015, 10, 58–61. [Google Scholar]
- Yu, Y.; Wu, J.; Li, Z.; Hu, L. Spatial-temporal patterns variation of grain production and security evalution in Shandong Province. J. China Agric. Univ. 2020, 25, 176–186. [Google Scholar]
- Zhao, D.; Chen, X.; Han, Y.; Zhao, Y.; Men, X. Study on the matching method of agricultural water and land resources from the perspective of total water footprint. Water 2022, 14, 1120. [Google Scholar] [CrossRef]
- Fan, H.; Fu, W. Analysis of Water and Soil Resources Matching and Agricultural Economic Growth in China from the Percepective of Water Footprint—Taking the Yangtze River Economic Belt as an Example. Chin. J. Agric. Resour. Reg. Plan. 2020, 41, 193–203. [Google Scholar]
- Zhang, Y.; Li, X. Analyses of supply-demand balance of agricultural products in China and its policy implication. J. Nat. Resour. 2021, 36, 1573–1587. [Google Scholar] [CrossRef]
- Luan, J.; Wang, R.; Zhu, Z.; Li, T. Study on agricultural production pattern under the change of grain supply and demand in Shandong Province. Chin. J. Agric. Resour. Reg. Plan. 2021, 42, 201–209. [Google Scholar]
- Abbass, K.; Qasim, M.Z.; Song, H.; Murshed, M.; Mahmood, H.; Younis, I. A review of the global climate change impacts, adaptation, and sustainable mitigation measures. Environ. Sci. Pollut. Res. 2022, 29, 42539–42559. [Google Scholar] [CrossRef]
- Webb, R.; Buratini, J. Global challenges for the 21st century: The role and strategy of the agri-food sector. Anim. Reprod. 2018, 13, 133–142. [Google Scholar] [CrossRef]
- Qi, Y.; Qiang, W.; Ma, X. Spatiotemporal Pattern Evolution of Food and Nutrient Production in China. Foods 2023, 12, 3791. [Google Scholar] [CrossRef]
- Zhang, J.; Fang, Y.; Zheng, H.; Fan, S.; Du, T. The Spatio-Temporal Evolution of Food Production and Self-Sufficiency in China from 1978 to 2020: From the Perspective of Calories. Foods 2023, 12, 956. [Google Scholar] [CrossRef]
- Xia, W.; Zhang, B.; He, M.; Cui, X. The Matching pattern of water and soil resources of food crops in Beijing-Tianjin-Hebei counties from the perspective of water footprint. Chin. J. Agric. Resour. Reg. Plan. 2022, 43, 22–33. [Google Scholar]
- Liu, Y.; Liu, F.; Qin, A. Effects of Irrigation and Mechanical Inputs on Rice Production Efficiency Under Constraints of Water and Soil Resources. J. Huazhong Agric. Univ. 2023, 03, 67–78. [Google Scholar]
- Cui, N.; Liu, Z.; Dong, J. Internal Logic and Long—Term Mechanism Construction of Smart Agriculture for Reducing Losses of Grain Production. Issues Agric. Econ. 2023, 116–128. [Google Scholar] [CrossRef]
- Qu, L.; Li, Y.; Wang, J. Simulation and optimization of agricultural production scenarios in loess hilly and gully region. Geogr. Res. 2023, 42, 1647–1662. [Google Scholar]
- Liu, Y.S.; Wu, C.J. Situation of land-water resources and analysis of sustainable food security in China. J. Nat. Resour. 2002, 17, 270–275. [Google Scholar]
- Liu, B.; Zhang, G.; Xie, Y.; Shen, B.; Gu, Z.; Ding, Y. Delineating the black soil region and typical black soil region of northeastern China. Chin. Sci. Bull. 2021, 66, 96–106. [Google Scholar] [CrossRef]
- Hoekstra, A.; Chapagain, A.K.; Aldaya, M.M.; Mekonnen, M.M. The Water Footprint Assessment Manual: Setting the Global Standard; Routledge: Oxfordshire, UK, 2012. [Google Scholar]
- Li, B.; Huang, F. Defining the Baselines for China Agricultural Water Use in Green and Blue Water Approach. Sci. Agric. Sin. 2015, 48, 3493–3503. [Google Scholar]
- Luo, X.; Yuan, Q. Spatial-Temporal Coupling relationship between New Urbanization and Agricultural Technology Progress. J. South China Agric. Univ. 2017, 16, 19–27. [Google Scholar]
- Wang, S.; Mu, Y. Spatial pattern evolution of grain production and its impact on grain-land matching in China. J. China Agric. Univ. 2022, 27, 1–11. [Google Scholar]
- Yang, Z.; Cai, H.; Qin, C.; Liu, H. Analysis on the Spatial and Temporal Pattern of China’s Grain Production and Its Influencing Factors. J. Agric. Sci. Technol. 2018, 20, 1–11. [Google Scholar]
- Han, Y.; Li, X.; Huang, H.; Jia, D. Spatial and temporal distribution of water footprint of main crops and its influencing factors in Beijing-Tianjing-Hebei region. South-North Water Transf. Water Sci. Technol. 2018, 16, 26–34. [Google Scholar]
- Wang, Q.; Liu, J.; Zhao, D. Study on water footprint of main crop production in Jing-Jin-Ji Region. Water Resour. Prot. 2018, 34, 22–27. [Google Scholar]
- Liu, B.; Liu, Y.; Zheng, F.; Zhu, Y.; Guo, A.; Chen, D.; Yang, X.; Mei, X. Assessment Regional Grain Yield Loss Based on Re-Examination of Disaster-Yield Model in Three Northeastern Provinces. Chin. J. Agrometeorol. 2022, 43, 487–498. [Google Scholar]
- Chen, H.; Wang, H.; Qin, S. Study on Green Efficiency of Grain Water Resources in Heilongjiang Province from the Perspective of Water Footprint: Based on Three–stage Sbm–malmquist Index Analysis Method. Resour. Environ. Yangtze Basin 2020, 29, 2790–2804. [Google Scholar]
- Yin, Z.; Qin, X.; Li, C. Study on water consumption and deficiency of main crops in northeastern China. Sci. Technol. Rev. 2009, 13, 42–49. [Google Scholar]
- Li, B.; Niu, M.; Zhao, J.; Zheng, X.; Chen, R.; Ling, X.; Wang, Y. Agricultural Cultivation Structure in Arid Areas Based on Water–Carbon Nexus—Taking the Middle Reaches of the Heihe River as an Example. Land 2023, 12, 1442. [Google Scholar] [CrossRef]
- Cao, Y.; Zhang, R.; Feng, X. Matching characteristics of agricultural soil and water resources in Liaoning province based on spring corn water footprint. J. China Inst. Water Resour. Hydropower Res. 2022, 20, 295–305. [Google Scholar]
- Xu, Y.; Mu, Y.; Zhang, Z. The Influencing Factors and Spatial Spillover Effects of Water Use Efficiency of Grain Production in China. J. Huazhong Agric. Univ. 2022, 76–89. [Google Scholar] [CrossRef]
- Liu, Y.; Gan, H.; Zhang, F. Analysis of the Matching Patterns of Land and Water Resources in Northeast China. Acta Geogr. Sin. 2006, 61, 847–854. [Google Scholar]
- Nie, Y.; Li, X.; Jiang, W.; Liu, N. Planting structure optimization of three main grain crops in 10 northern China provinces based on water footprint method. Resour. Sci. 2022, 44, 2315–2329. [Google Scholar] [CrossRef]
- Cui, N.; Wang, X.; Yu, Z. Analysis Ecological Efficiency Evaluation and Influencing Factors of Cultivated Land of Grain Production in Northeast Main Production Area. Ecol. Econ. 2021, 37, 104–110. [Google Scholar]
- Wang, L.; Yan, C.; Zhang, W.; Zhang, Y. Water Footprint Assessment of Agricultural Crop Productions in the Dry Farming Region, Shanxi Province, Northern China. Agronomy 2024, 14, 546. [Google Scholar] [CrossRef]
- Geng, Q.; Liu, H.; He, X.; Tian, Z. Integrating Blue and Green Water to Identify Matching Characteristics of Agricultural Water and Land Resources in China. Water 2022, 14, 685. [Google Scholar] [CrossRef]
- Xu, C.; Hu, X.; Liu, Z.; Wang, X.; Tian, J.; Zhao, Z. Predicting the Evolution Trend of Water and Land Resource Carrying Capacity Based on CA–Markov Model in an Arid Region of Northwest China. Sustainability 2023, 15, 1269. [Google Scholar] [CrossRef]
- Luo, H.; Huang, Y.; Zhang, X. Major Challenges and Coping Strategies for Food Security in China in the New Era. Soc. Sci. Xinjiang 2023, 4, 31–43. [Google Scholar]
- Li, R.; Chen, J.; Xu, D. The Impact of Agricultural Socialized Service on Grain Production: Evidence from Rural China. Agriculture 2024, 14, 785. [Google Scholar] [CrossRef]
- Yu, A.; Cai, E.; Yang, M.; Li, Z. An Analysis of Water Use Efficiency of Staple Grain Productions in China: Based on the Crop Water Footprints at Provincial Level. Sustainability 2022, 14, 6682. [Google Scholar] [CrossRef]
- Shang, X.; Zhu, S.; Duan, J. Policy Supply Choice of National Food Security under Water Resources Restriction. Econ. Probl. 2019, 12, 81–88. [Google Scholar]
Project | Value Range | Stage |
---|---|---|
Coupling value C | 0 < C ≤ 0.3 | Low-level coupling stage |
0.3 < C ≤ 0.5 | Fly-down stage | |
0.5 < C ≤ 0.8 | Break-in period | |
0.8 < C ≤ 1 | High-level coupling stage | |
Coupling harmonization value D | 0 < D ≤ 0.3 | Low coupling coordination |
0.3 < D ≤ 0.5 | Moderate coupling coordination | |
0.5 < D ≤ 0.8 | High coupling coordination | |
0.8 < D ≤ 1 | Quality coupling coordination |
Subsystem | Factor Layer | Index Level | Explanation of Indicators | Unit | Characteristic |
---|---|---|---|---|---|
Agricultural land and water resources system | Matching of water and soil resources (MR) | Matching coefficient of water and soil resources (MR1) | Agricultural water and soil resource allocation | m3/kg | Positive |
Grain production system | Natural endowment (NE) | Effective irrigation area (NE1) | Measuring regional agricultural water use | Thousand hectares | Positive |
Disaster proportion (NE2) | Measuring climate impacts on agriculture | Percent | Negative | ||
Agricultural factor inputs (AF) | Year-end cultivated land area (AF1) | Land factor inputs | Hectares | Positive | |
Agricultural labor force (AF2) | Labor factor inputs | Person | Positive | ||
Grain sown area (AF3) | Measuring the amount of seed inputs | Hectares | Positive | ||
Fertilizer application amount (AF4) | Measuring fertilizer inputs | Ton | Positive | ||
Total power of agricultural machinery (AF5) | Measuring agricultural machinery inputs | Kilowatt | Positive | ||
Agricultural outputs (AO) | Per capita yield of grain (AO1) | Measuring crop yields | Kg/ha | Positive | |
Gross agricultural output (AO2) | Measuring the value of food crop output | CNY 10,000 | Positive |
Crop (per Unit Mass) | Rice | Wheat | Maize | Soybean | Tubers |
---|---|---|---|---|---|
WFblue | 0.96 | 0.20 | 0.11 | 0.82 | 0.13 |
WFgreen | 0.79 | 0.51 | 0.42 | 1.46 | 0.37 |
WFtotal | 1.75 | 0.71 | 0.53 | 2.28 | 0.50 |
Region | Matching Coefficient of Water and Soil Resources R (104 m3/hm2) | |||||||||
---|---|---|---|---|---|---|---|---|---|---|
2005 | 2007 | 2009 | 2011 | 2013 | 2015 | 2017 | 2019 | 2021 | ||
Hulunbeier | 0.27 | 0.61 | 0.79 | 0.74 | 0.64 | 0.98 | 0.37 | 0.68 | 0.30 | 0.60 |
Xing’an League | 0.62 | 0.16 | 0.19 | 0.24 | 0.30 | 0.34 | 0.37 | 0.59 | 0.59 | 0.38 |
Tongliao | 0.23 | 0.27 | 0.25 | 0.23 | 0.27 | 0.34 | 0.33 | 0.41 | 0.43 | 0.31 |
Chifeng | 0.67 | 0.65 | 0.63 | 0.23 | 1.04 | 0.24 | 1.10 | 1.14 | 1.10 | 0.76 |
Harbin | 0.79 | 0.69 | 0.69 | 0.81 | 0.66 | 0.67 | 0.57 | 0.57 | 0.63 | 0.68 |
Qiqihar | 0.29 | 0.23 | 0.35 | 0.41 | 0.39 | 0.41 | 0.38 | 0.50 | 0.53 | 0.39 |
Hegang | 0.44 | 0.33 | 0.63 | 0.59 | 0.59 | 0.58 | 0.59 | 2.05 | 2.11 | 0.88 |
Shuangyashan | 0.15 | 0.15 | 0.39 | 0.20 | 0.20 | 0.20 | 0.21 | 0.69 | 0.72 | 0.32 |
Daqing | 0.20 | 0.22 | 0.35 | 0.51 | 0.48 | 0.48 | 0.42 | 0.46 | 0.48 | 0.40 |
Jiamusi | 0.03 | 0.03 | 0.04 | 0.09 | 0.08 | 0.08 | 0.07 | 0.73 | 0.76 | 0.21 |
Qitaihe | 0.35 | 0.24 | 0.29 | 0.29 | 0.22 | 0.27 | 0.26 | 0.29 | 0.29 | 0.28 |
Heihe | 0.16 | 0.12 | 0.26 | 0.22 | 0.18 | 0.21 | 0.20 | 0.33 | 0.33 | 0.22 |
Suihua | 0.40 | 0.43 | 0.56 | 0.65 | 0.53 | 0.55 | 0.50 | 0.50 | 0.50 | 0.51 |
Changchun | 0.58 | 0.56 | 0.47 | 0.49 | 0.55 | 0.56 | 0.58 | 0.53 | 0.67 | 0.55 |
Siping | 0.55 | 0.53 | 0.43 | 0.52 | 0.54 | 0.58 | 0.60 | 0.54 | 0.36 | 0.52 |
Songyuan | 0.36 | 0.33 | 0.41 | 0.40 | 0.40 | 0.48 | 0.52 | 0.50 | 0.52 | 0.44 |
Baicheng | 0.22 | 0.26 | 0.28 | 0.26 | 0.29 | 0.42 | 0.51 | 0.59 | 0.66 | 0.39 |
Typical black soil region | 0.37 | 0.34 | 0.41 | 0.40 | 0.43 | 0.43 | 0.45 | 0.65 | 0.65 | 0.46 |
2005 | 2021 | ||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Region | C | Stage | Region | D | Stage | Region | C | Stage | Region | D | Stage |
Jiamusi | 0.304 | Fly-down stage | Jiamusi | 0.253 | Low coupling coordination | Hegang | 0.599 | Break-in period | Qitaihe | 0.318 | Moderate coupling coordination |
Xing’an League | 0.873 | High-level coupling stage | Shuangyashan | 0.271 | Shuangyashan | 0.943 | High-level coupling stage | Hulunbeier | 0.413 | ||
Hegang | 0.902 | Heihe | 0.297 | Chifeng | 0.944 | Heihe | 0.424 | ||||
Suihua | 0.910 | Qitaihe | 0.320 | Moderate coupling coordination | Suihua | 0.952 | Siping | 0.434 | |||
Qiqihar | 0.923 | Hulunbeier | 0.336 | Qiqihar | 0.957 | Daqing | 0.468 | ||||
Qitaihe | 0.925 | Baicheng | 0.338 | Hulunbeier | 0.963 | Xing’an League | 0.480 | ||||
Heihe | 0.941 | Daqing | 0.339 | Harbin | 0.964 | Shuangyashan | 0.485 | ||||
Tongliao | 0.943 | Hegang | 0.353 | Tongliao | 0.969 | Tongliao | 0.496 | ||||
Daqing | 0.946 | Tongliao | 0.373 | Heihe | 0.976 | Songyuan | 0.530 | High coupling coordination | |||
Chifeng | 0.954 | Xing’an League | 0.407 | Qitaihe | 0.979 | Baicheng | 0.539 | ||||
Baicheng | 0.973 | Songyuan | 0.431 | Songyuan | 0.983 | Suihua | 0.556 | ||||
Shuangyashan | 0.974 | Qiqihar | 0.433 | Siping | 0.984 | Qiqihar | 0.567 | ||||
Siping | 0.982 | Siping | 0.454 | Xing’an League | 0.987 | Hegang | 0.577 | ||||
Songyuan | 0.988 | Chifeng | 0.475 | Changchun | 0.991 | Jiamusi | 0.588 | ||||
Harbin | 0.996 | Changchun | 0.500 | Baicheng | 0.999 | Changchun | 0.593 | ||||
Changchun | 0.999 | Suihua | 0.526 | High coupling coordination | Jiamusi | 1.000 | Chifeng | 0.603 | |||
Hulunbeier | 0.999 | Harbin | 0.579 | Daqing | 1.000 | Harbin | 0.615 |
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Chu, H.; Wu, C.; Wang, G.; Lang, Y.; Aynalem, M. Coupling Coordination Evaluation of Water and Soil Resource Matching and Grain Production, and Analysis of Obstacle Factors in a Typical Black Soil Region of Northeast China. Sustainability 2024, 16, 5030. https://doi.org/10.3390/su16125030
Chu H, Wu C, Wang G, Lang Y, Aynalem M. Coupling Coordination Evaluation of Water and Soil Resource Matching and Grain Production, and Analysis of Obstacle Factors in a Typical Black Soil Region of Northeast China. Sustainability. 2024; 16(12):5030. https://doi.org/10.3390/su16125030
Chicago/Turabian StyleChu, Hao, Cui Wu, Guixia Wang, Yu Lang, and Mezgebu Aynalem. 2024. "Coupling Coordination Evaluation of Water and Soil Resource Matching and Grain Production, and Analysis of Obstacle Factors in a Typical Black Soil Region of Northeast China" Sustainability 16, no. 12: 5030. https://doi.org/10.3390/su16125030