Environmental and Ecological Statistics

, Volume 26, Issue 1, pp 47–86 | Cite as

Modelling relationships between socioeconomy, landscape and water flows in Mediterranean agroecosystems: a case study in Adra catchment (Spain) using Bayesian networks

  • Rosa F. RoperoEmail author
  • Rafael Rumí
  • Pedro A. Aguilera


In Mediterranean areas, the co-evolution between social and natural systems has given rise to heterogeneous and complex systems of interactions called agroecosystems, in which strong relationships between socioeconomy, landscape and water flows have been identified. In this context, water resources management is a prominent area of research, particularly in semi-arid conditions, where a special set of challenges requires novel tools to deal with uncertainty, multiple sources of information and expert knowledge. In this paper, Bayesian Networks are proposed as a means to model the relationships between socioeconomy, landscape and water flows in a Mediterranean agroecosystem, studying its behaviour under two scenarios of change in land use trends: maintenance of traditional Mediterranean agriculture, and agricultural intensification through the development of greenhouses. Results show that an increase in the area of traditional agriculture would lead to better control of runoff and increased primary productivity, measured as green water flows. By contrast, agricultural intensification of the territory would provoke an increase in evaporation and water losses. Due to the versatility of Bayesian networks, results can be expressed not only as probabilities, but also using other metrics that can be computed from them. Accordingly, Sensitivity Analysis to Evidence, Sensitivity Analysis to Parameters and the Kullback–Leibler divergence were carried out. Bayesian Networks have demonstrated their ability to deal with uncertainty inherent to natural systems, combining expert knowledge, data from regional datasets and Geographical Information Systems, and automatic training algorithms giving robust and proper results.


Bayesian networks Green and blue water Kullback–Leibler divergence Landscape change trends Mediterranean agroecosystems Sensitivity analysis 



This work has been supported by the Spanish Ministry of Economy and Competitiveness through projects TIN2013-46638-C3-1-P and TIN2016-77902-C3-3-P; by the Junta de Andalucía through project P12-TIC-2541, and from ERDF funds.


  1. Aguilera PA, Fernández A, Fernández R, Rumí R, Salmerón A (2011) Bayesian networks in environmental modelling. Environ Model Softw 26:1376–1388CrossRefGoogle Scholar
  2. Andersen SK, Olesen KG, Jensen FV, Jensen F (1990) HUGIN: a shell for building Bayesian belief universes for expert systems. In: Shafer G, Pearl J (eds) Readings in uncertain reasoning. Kaufmann, San Mateo, pp 332–337Google Scholar
  3. Aranzabal ID, Schmitz MF, Aguilera PA, Pineda FD (2008) Modelling of landscape changes derived from the dynamics of socio-ecological systems. A case in a semiarid Mediterraneam landscape. Ecol Indic 8:672–685CrossRefGoogle Scholar
  4. Baynes J, Herbohn J, Russell I, Smith C (2011) Bringing agroforestry technology to farmers in the philippines: identifying constraints to the success of extension activities using systems modelling. Small Scale For 10:357–376CrossRefGoogle Scholar
  5. Bonneau M, Peyrard N, Gaba S, Sabbadin R (2016) Sampling for weed spatial distribution mapping need not be adaptive. Environ Ecol Stat 23:233–255CrossRefGoogle Scholar
  6. Bromley J, Jackson NA, Clymer OJ, Giacomello AM, Jensen FV (2005) The use of Hugin® to develop Bayesian networks as aid to integrated water resource planning. Environ Model Softw 20:231–242CrossRefGoogle Scholar
  7. Caillault S, Mialhe F, Vannier C, Delmotte S, Kedowidé C, Amblard F, Etienne M, Bécu N, Gautreau P, Houet T (2013) Influence of incentive networks on landscape changes: a simple agent-based simulation approach. Environ Model Softw 45:64–73CrossRefGoogle Scholar
  8. Casadei S, Pierleoni A, Bellezza M (2016) Integrated water resources management in lake system: a case study in central italy. Water 8(12):1–18CrossRefGoogle Scholar
  9. Castelletti A, Soncini-Sessa R (2007a) Bayesian networks and participatory modelling in water resource management. Environ Model Softw 22:1075–1088CrossRefGoogle Scholar
  10. Castelletti A, Soncini-Sessa R (2007b) Coupling real-time control and socio-economic issues in participatory river basin planning. Environ Model Softw 22:1114–1128CrossRefGoogle Scholar
  11. Castro-Nogueira H, de la Guerra MM, de Lucio-Fernández J, Alandi C, Sastre-Olmos P, Atauuri-Mezquida J, Montes C, Molina-Vázquez F, Rosarío-García-Mora M (2002) Integración territorial de espacios naturales protegidos y conectividad ecológica en paisajes mediterráneos. ISBN 84-95785-21-8Google Scholar
  12. De-Lucio-Fernández J, Atauri-Mezquida J, Sastre-Olmos P, Martínez-Alandi C (2002) Conectividad y redes de espacios naturales protegidos: Del modelo teórico a la visión práctica de la gestión. In: Environmental connectivity: protected areas the mediterranean context. 26–28 September. Málaga, SpainGoogle Scholar
  13. Falk MG, OLeary R, Nayak M, Collins P, Low-Choy S (2015) A bayesian hyurdle model for analysis of an insect resistence monitoring database. Environ Ecol Stat 22:207–226CrossRefGoogle Scholar
  14. Falkenmark M (1997) Society interaction with the water cycle: a conceptual framework for a more holistic approach. Hydrol Sci 42(4):451–466CrossRefGoogle Scholar
  15. Falkenmark M, Folke C (2002) The ethics of socio-ecohydrological catchment management: towards hydrosolidarity. Hydrol Earth Syst Sci 6(1):1–9CrossRefGoogle Scholar
  16. Foley JA, DeFries R, Asner GP, Barford C, Bonan C, Carpenter SR, CHapin FS, Coe MT, Daily GC, Gibss HK, Helkowski JH, Holloway T, Howard EA, Kucharik CJ, Monfreda C, Patz JA, Prentice IC, Ramankutty N, Snyder P (2005) Global consequences of land use. Science 309:50–574CrossRefGoogle Scholar
  17. Frayer J, Sun Z, Muller D, Munroe D, Xu J (2014) Analyzing the drivers of tree planting in Yunnan, china, with Bayesian networks. Land Use Policy 36:248–258CrossRefGoogle Scholar
  18. Fung R, Chang KC (1990) Weighting and integrating evidence for stochastic simulation in Bayesian networks. In: Uncertainty in artificial intelligence, pp 209–220Google Scholar
  19. García-Álvarez-Coque JM (2002) La agricultura mediterránea en el siglo XXI. Caja Rural Intermediterránea, Cajamar, Almería. Spain, pp 7–312Google Scholar
  20. García-Latorre J, Sánchez-Picón A (2001) Dealing with aridity: socio-economic structures and environmental changes in an arid Mediterranean region. Land Use Policy 18:53–64CrossRefGoogle Scholar
  21. Gitelman A, Herlihy A (2007) Isomorphic chain graphs for modeling spatial dependence in ecological data. Environ Ecol Stat 14:27–40CrossRefGoogle Scholar
  22. González-Bernáldez F (1981) Ecología y PaisajeGoogle Scholar
  23. Gordon L, Finlayson C, Falkenmark M (2010) Managing water in agriculture for food production and other ecosystem services. Agric Water Manag 97:512–519CrossRefGoogle Scholar
  24. Grau HR, Aide TM, Zimmerman JK, Thomlinson JR, Helmer E, Zou X (2003) The ecological consequences of socioeconomic and land-use changes in postagriculture puerto rico. Bioscience 53:1159–1168CrossRefGoogle Scholar
  25. Henriksen HJ, Barlebo HC (2008) Reflections on the use of Bayesian belief networks for adaptive management. J Environ Manag 88:1025–1036CrossRefGoogle Scholar
  26. Henriksen HJ, Rasmussen P, Brandt G, von Bülow D, Jensen FV (2007) Public participation modelling using Bayesian networks in management of groundwater contamination. Environ Model Softw 22:1101–1113CrossRefGoogle Scholar
  27. Hui X, Lei C, Zehenyao S (2015) Assessment of agricultural best management practices using models: current issues and future perspectives. Water 73(3):1–21Google Scholar
  28. Irvine KM, Gitelman A (2011) Graphical spatial models: a new view on interpreting spatial pattern. Environ Ecol Stat 18:447–469CrossRefGoogle Scholar
  29. Jensen FV, Nielsen TD (2007) Bayesian networks and decision graphs. Springer, BerlinCrossRefGoogle Scholar
  30. Joshi L, Wibawa G, Sinclair F (2001) Local ecological knowledge and socio-economic factors influencing farmersÕ management decisions in jungle rubber agroforestry systems in Jambi, Indonesia. DFID Project R7264 Forestry Research ProgrammeGoogle Scholar
  31. Kelly R, Jakeman AJ, Barreteau O, Borsuk M, ElSawah S, Hamilton S, Henriksen HJ, Kuikka S, Maier H, Rizzoli E, Delden H, Voinov A (2013) Selecting among five common approaches for integrated environmental assessment and management. Environ Model Softw 47:159–181CrossRefGoogle Scholar
  32. Kersebaum KC, Kroes J, Gobin A, Takac J, Hlavinka P, Trnka M, Ventrella D, Giglio L, Ferrise R, Moriondo M, Marta AD, Luo Q, Eitzinger J, Mirschel W, Weigel HJ, Manderscheid R, Hoffmann M, Nejedlik P, Iqbal MA, Hosch J (2016) Assessing uncertainties of water footprints using an ensemble of crop growth models on winter wheat. Water 8(12):1–20CrossRefGoogle Scholar
  33. Lambin EF, Meyfroidt P (2010) Land use transitions: socio-ecological feedback versus socio-economic change. Land Use Policy 27:108–118CrossRefGoogle Scholar
  34. Lauritzen SL, Spiegelhalter DJ (1988) Local computations with probabilities on graphical structures and their application to expert systems. J R Stat Soc Ser B 50:157–224Google Scholar
  35. Maes WH, Hueuvelmans G, Muys B (2009) Assessment of land use impact on water-related ecosystem services capturing the integrated terrestrial—aquatic system. Environ Sci Technol 43:7324–7330CrossRefGoogle Scholar
  36. Mantyka-Pringle CS, Martin TG, Moffatt DB, Linke S, Rhodes JR (2014) Understanding and predicting the combined effects of climate change and land-use change on freshwater macroinvertebrates and fish. J Appl Ecol 51:572–581CrossRefGoogle Scholar
  37. Pal C, Swayne D, Frey B (2001) The automated extraction of environmentally relevant features from digital imagery using Bayesian multi-resolution analysis. Adv Environ Res 5:435–444CrossRefGoogle Scholar
  38. Pearl J (1988) Probabilistic reasoning in intelligent systems: network of plausible inference. Morgan Kaufmann, San Mateo, CaliforniaGoogle Scholar
  39. Phan TD, Smart JC, Capon SJ, Hadwen W (2016) Applications of Bayesian belief networks in water resource management: a systemic review. Environ Model Softw 85:98–111CrossRefGoogle Scholar
  40. Rockstroem J (2000) Water resources management in smallholder farms in eastern and southern Africa: an overview. Phys Chem Earth 25:275–283CrossRefGoogle Scholar
  41. Rockstroem J, Karlberg L, Wani S, Barron J, Hatibu N, Oweis T, Bruggeman A, Farahani J, Quiang Z (2010) Managing water in rainfed agriculture—the need for a paradigm shift. Agric Water Manag 97:543–550CrossRefGoogle Scholar
  42. Ropero R, Renooij S, van der Gaag L (2018) Discretizing environmental data for learning bayesian-network classifiers. Ecol Model 368:391–403CrossRefGoogle Scholar
  43. Rudel TK, Schneider L, Uriarte M, Turner B, DeFries R, Lawrence D, Geoghegan J, Hecht S, Ickowitz A, Lambin EF, Birkenholtz T, Baptista S, Grau R (2009) Agricultural intensification and changes in cultivated areas, 1970-2005. PNAS 106:20,675–20,680Google Scholar
  44. Sadoddin A, Letcher RA, Jakeman A, Newham L (2005) A bayesian decision network approach for assessing the ecological impacts of salinity management. Math Comput Simul 69:162–176CrossRefGoogle Scholar
  45. Sal AG, García AG (2007) A comprehensive assessment of multifunctional agricultural land-use systems in spain using a multi-dimensional evaluative model. Agric Ecosyst Environ 120:82–91CrossRefGoogle Scholar
  46. Scanlon BR, Reedy R, Stonestrom D, Prudic D, Dennehys K (2005) Impact of land use and land cover change on groundwater recharge and quality in the southwestern US. Global Change Biol 11:1577–1593CrossRefGoogle Scholar
  47. Schmitz M, Pineda F, Castro H, Aranzabal ID, Aguilera P (2005) Cultural landscape and socioeconomic structure. Environmental value and demand for tourism in a Mediterranean territory. Consejería de Medio Ambiente. Junta de Andalucía. SevillaGoogle Scholar
  48. Spirtes P, Glymour C, Scheines R (1993) Causation, prediction and search, Lecture Notes in Statistics, vol 81. SpringerGoogle Scholar
  49. Stafford R, Clitherow TJ, Howlett SJ, Spiers EK, Williams RL, Yaselga B, Valarezo SZ, Vera-Izutieta DF, Cornejo M (2016) An integrated evaluation of potential management processes on marine reserves in continental Ecuador based on a Bayesian belief network model. Ocean Coast Manag 121:60–69CrossRefGoogle Scholar
  50. Teegavarapu RSV (2010) Modeling climate change uncertainties in water resources management models. Environ Model Softw 25:1261–1265CrossRefGoogle Scholar
  51. Uusitalo L (2007) Advantages and challenges of Bayesian networks in environmental modelling. Ecol Model 203:312–318CrossRefGoogle Scholar
  52. Van Deer Gag L, Renooij S (2001) Analysing sensitivity data from probabilistic networks. UAI pp 530–537Google Scholar
  53. Varis O, Kuikka S (1997) BENE-EIA: a Bayesian approach to expert judgment elicitation with case studies on climate change impacts on surface waters. Clim Change 37:539–563CrossRefGoogle Scholar
  54. Willaarts BA (2009) Dinámica del paisaje en la Sierra Norte de Sevilla. Cambios funcionales e implicaciones en el suministro de servicios de los ecosistemas. PhD thesis, Facultad de Ciencias Experimentales. Departamento de Biología Vegetal y Ecología. Universidad de AlmeríaGoogle Scholar
  55. Willaarts BA, Volk M, Aguilera PA (2012) Assessing the ecosystem services supplied by freshwater flows in Mediterranean agroecosystems. Agric Water Manag 105:21–31CrossRefGoogle Scholar
  56. Zhang K, Peters J, Janzing D, Scholkopf B (eds) (2012) Kernel-based conditional independence test and application in causal discovery. In: UAI’11 proceedings of the twenty-seventh conference on uncertainty in artificial intelligence, pp 804–813Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Informatics and Environmental Research Group, Department of Biology and GeologyUniversity of AlmeríaAlmeríaSpain
  2. 2.Department of MathematicsUniversity of AlmeríaAlmeríaSpain

Personalised recommendations