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An Evaluation of the Resilience of the Regional Agricultural Water and Soil Resource System in Heilongjiang Province, China

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Abstract

Water and soil resources are fundamental natural resources. Therefore, it is highly important to understand the resilience of regional water and soil resources, the characteristics of which are nonlinear, self-organized and unpredictable. This study used a projection pursuit model based on the firefly algorithm (FA-PP) to quantitatively evaluate the water and soil system resilience of 15 farms in the Jiansanjiang administration of Heilongjiang Province, China. The results were compared with the results obtained by the projection pursuit model based on the genetic algorithm (GA-PP), and the validity and feasibility of the FA-PP model were verified. Further analysis revealed that the key factor influencing the resilience of agricultural water and soil resources was the irrigated area. The research results revealed the restoring situation of the local water and soil resource system and provided a foundation for the management of agricultural water and soil resources.

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References

  1. Atkinson G, Dubourg R, Hamilton K, Munasinghe M, Pearce D, Young C (1997) Measuring sustainable development: macroeconomics and the environment. JSTOR 41(5):647

    Google Scholar 

  2. Batabyal AA (1998) On some aspects of ecological resilience and the conservation of species ☆. J Environ Manag 52(4):373–378

    Article  Google Scholar 

  3. Chang SE, Shinozuka M (2004) Measuring improvements in the disaster resilience of communities. Earthq Spectra 20(3):739–755

    Article  Google Scholar 

  4. Deb K, Pratap A, Agarwal S, Meyarivan T (2002) A fast and elitist multiobjective genetic algorithm: NSGA-II. IEEE Trans Evol Comput 6(2):182–197

    Article  Google Scholar 

  5. Eberhart R, Kennedy J (1995)A new optimizer using particle swarm theory. In: International symposium on MICRO machine and human science, pp 39–43

  6. Feng Z, Zheng H, Liu B (2005) Comprehensive evaluation of agricultural water use efficiency based on genetic projection pursuit model[J]. Trans CSAE 21(3):66–70

    Google Scholar 

  7. Friedman JH, Tukey JW (1973) A Projection pursuit algorithm for exploratory data analysis. IEEE Trans Comput c-23(9):881–890

    Article  Google Scholar 

  8. Fu Q, Jin J (2002) Application of projection pursuit classification model based on real-time accelerated genetic algorithm in optimization of rice irrigation schedule. J Hydraul Eng 33(10):39–45

    Google Scholar 

  9. Goldberg DE (1989) Genetic Algorithms in Search, Optimization and Machine learning[M]. Addison-Wesley Longman Press, Boston

    Google Scholar 

  10. Holling CS (2003) Resilience and Stability of Ecological Systems. Annu Rev Ecol Syst 4(4):1–23

    Google Scholar 

  11. Li H, Jia L, Yao Y, Liu T, Ru S (2013) Analysis on dynamic characteristics of groundwater in Sanjiang Branch of Heilongjiang Province. Water Sav Irrig 06:14–17

    Google Scholar 

  12. Liu J, Shi P, Ge Y, Wang J, Lv H (2006) A summary of the research progress of disaster recovery. Adv Earth Sci 21(2):211–218

    Google Scholar 

  13. Liu J, Shi PJ, Yi GE, Wang JA, Feng LH (2006) The review of disaster resilience research. Adv Earth Sci 4(7):112–118

    Google Scholar 

  14. Lv P, Liu D, Zhao F (2011) Fuzzy matter—element evaluation model of water resources carrying capacity of Sanjiang branch based on entropy. Res Soil Water Conserv 18(2):246–250

    Google Scholar 

  15. Ma J, Guo X, Fu Q, Wang K, Ma X (2014) Study on the configuration of complex adaptation system of regional agricultural water and soil resources—taking Sanjiang plain as an example. Res Soil Water Conserv 21(3):256–260

    Google Scholar 

  16. Mccall J (2005) Genetic algorithms for modelling and optimisation. J Comput Appl Math 184(1):205–222

    Article  Google Scholar 

  17. Ni C, Wang S, Cui P (2006) Projection pursuit dynamic clustering model and its application in groundwater classification. Adv Eng Sci 38(6):29–33

    Google Scholar 

  18. Perrings C (1998) Resilience in the dynamics of economy-environment systems. Environ Resour Econ 11(3):503–520

    Article  Google Scholar 

  19. Perrings C, Stern DI (2000) Modelling loss of resilience in agroecosystems: rangelands in Botswana. Environ Resour Econ 16(2):185–210

    Article  Google Scholar 

  20. Roeva O (2012) Optimization of E. coli cultivation model parameters using firefly algorithm. Int J Bioautom 16(1):242–251

    Google Scholar 

  21. Song X, Du L, Li S, Yan Z, Hou G (2003) Research on the concept, influencing factors and evaluation of ecosystem health. J Henan Agric Univ 37(4):375–378

    Google Scholar 

  22. Sun CZ, Dong-Ling HU, Yang L (2011) Recovery capacity of groundwater system in lower Liaohe River Plain. Adv Sci Technol Water Resour 31(5):5–10

    CAS  Google Scholar 

  23. Wang B, Zhang Z, Wei Y et al. (2009) Assessment of agricultural basic drought based om projection pursuit[J]. Trans CASE 25(4):157–162

    CAS  Google Scholar 

  24. Wang S, Yang Z, Jing D (2004) Projection pursuit method for comprehensive evaluation of groundwater resources carrying capacity in Guanzhong Plain. Resour Sci 26(6):104–110

    Google Scholar 

  25. Yang XS (2009) Firefly algorithms for multimodal optimization. Mathematics 5792:169–178

    Google Scholar 

  26. Yang XS (2013) Multiobjective firefly algorithm for continuous optimization. Eng Comput 29(2):175–184

    Article  Google Scholar 

  27. Yang XS (2008) Nature-inspired metaheuristic algorithms. Luniver Press, Beckington

    Google Scholar 

  28. Yang XS, He X (2013) Firefly algorithm: recent advances and applications. Int J Swarm Intell 1(1):13–20

    Article  Google Scholar 

  29. Yu X, Liu D (2012) Regional groundwater system complexity measure and its influence on model prediction accuracy. China Rural Water Hydropower 8:65–69

    Google Scholar 

  30. Yu C (2007) Quantitative assessment of water resource system resilience. J Hydraul Eng s1:13–17

    Google Scholar 

  31. Zeng B, Li M, Zhang Y et al. (2013) Research on assembly sequence planning based on fire algorithm[J]. J Mech Eng 49(11):177–184

    Article  Google Scholar 

  32. Zhao F, Liu D, Liu M (2012) Analysis on driving forces of land use structure in Jiansanjiang based on information entropy and gray relation. Res Soil Water Conserv 19(3):250–253

    Google Scholar 

  33. Zhong-En XI, Wang SY (2007) On negative Cronbach alpha coefficient and split-half reliability coefficient. J Chongqing Univ Posts Telecommun 8(5):187–196

    Google Scholar 

  34. Zilong G, Sun’An W, Jian Z (2006) A novel immune evolutionary algorithm incorporating chaos optimization. Pattern Recogn Lett 27(1):2–8

    Article  Google Scholar 

Download references

Acknowledgements

This study was supported by the National Natural Science Foundation of China (Nos. 51579044, No. 41071053, No. 51479032), National Key R&D Program of China (No. 2017YFC0406002), Science and Technology Program of Water Conservancy of Heilongjiang Province (Nos. 201319, 201501, 201503).

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Correspondence to Qiang Fu.

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Liu, D., Mu, R., Fu, Q. et al. An Evaluation of the Resilience of the Regional Agricultural Water and Soil Resource System in Heilongjiang Province, China. Agric Res 7, 311–320 (2018). https://doi.org/10.1007/s40003-018-0312-z

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  • DOI: https://doi.org/10.1007/s40003-018-0312-z

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