Water management for irrigation, crop yield and social attitudes: a socio-agricultural agent-based model to explore a collective action problem

References

• Acheampong, D., et al., 2018. Assessing the effectiveness and impact of agricultural water management interventions: the case of small reservoirs in northern Ghana. Agricultural Water Management, 209, 163–170. doi:10.1016/j.agwat.2018.07.009
   Web of Science ®Google Scholar
• Bouldin, J.L., et al., 2004. Tailwater recovery systems for irrigation: benefit/cost analysis and water resource conservation technique in Northeast Arkansas. Journal of the Arkansas Academy of Science, 58 (Article 6), 23–31.
   Google Scholar
• Bussmann, A., et al., 2016. Sowing date determinants for Sahelian rainfed agriculture in the context of agricultural policies and water management. Land Use Policy, 52, 316–328. doi:10.1016/j.landusepol.2015.12.007
   Web of Science ®Google Scholar
• Campbell, G.S., 1974. A simple method for determining unsaturated conductivity from moisture retention data. Soil Science, 117 (6), 311–314. doi:10.1097/00010694-197406000-00001
   Web of Science ®Google Scholar
• Cavero, J., et al., 2000. Simulation of Maize yield under water stress with the EPICphase and CROPWAT models. Agronomy Journal, 92 (4), 679–690.
   Google Scholar
• Céréghino, R., et al., 2014. The ecological role of ponds in a changing world. Hydrobiologia, 723 (1), 1–6. doi:10.1007/s10750-013-1719-y
   Web of Science ®Google Scholar
• Cheng, H., et al., 2019. A circular economy system for breaking the development dilemma of ‘ecological fragility–economic poverty’ vicious circle: A CEEPS-SD analysis. Journal of Cleaner Production, 212, 381–392. doi:10.1016/j.jclepro.2018.12.014
   Web of Science ®Google Scholar
• Cialdini, R.B., Kallgren, C.A., and Reno, R.R., 1991. A focus theory of normative conduct: A theoretical refinement and reevaluation of the role of norms in human behavior. Advances in Experimental Social Psychology, 24, 201–234.
   Web of Science ®Google Scholar
• den Besten, N.I., Pande, S., and Savenije, H.H.G., 2016. A socio-hydrological comparative assessment explaining regional variances in suicide rate amongst farmers in Maharashtra, India. Proceedings of the International Association of Hydrological Sciences, 373, 115–118. doi:10.5194/piahs-373-115-2016
   Google Scholar
• Di Baldassarre, G., et al., 2013. Socio-hydrology: conceptualising human-flood interactions. Hydrology and Earth System Sciences, 17 (8), 3295–3303. doi:10.5194/hess-17-3295-2013
   Web of Science ®Google Scholar
• Di Baldassarre, G., et al., 2017. Drought and flood in the Anthropocene: feedback mechanisms in reservoir operation. Earth System Dynamics, 8 (1), 225–233. doi:10.5194/esd-8-225-2017
   Web of Science ®Google Scholar
• El-Naqa, A., et al., 2007. Groundwater deterioration of shallow groundwater aquifers due to overexploitation in Northeast Jordan. CLEAN – Soil, Air, Water, 35 (2), 156–166. doi:10.1002/clen.200700012
   Web of Science ®Google Scholar
• Evans, L.T. and Fischer, R.A., 1999. Yield potential: its definition, measurement, and significance. Crop Science, 39 (6), 1544–1551. doi:10.2135/cropsci1999.3961544x
   Web of Science ®Google Scholar
• Feng, Y., et al., 2019. Comparison of maize water consumption at different scales between mulched and non-mulched croplands. Agricultural Water Management, 216, 315–324. doi:10.1016/j.agwat.2019.02.016
   Web of Science ®Google Scholar
• Hardin, G., 1968. The tragedy of the commons. Science, 162 (3859), 1243–1248.
   PubMed Web of Science ®Google Scholar
• Hay, R.K.M., 1995. Harvest index: a review of its use in plant breeding and crop physiology. Annals of Applied Biology, 126 (1), 197–216. doi:10.1111/j.1744-7348.1995.tb05015.x
   Web of Science ®Google Scholar
• Heggenstaller, A.H., Liebman, M., and Anex, R.P., 2009. Growth analysis of biomass production in sole-crop and double-crop corn systems. Crop Science, 49 (6), 2215–2224. doi:10.2135/cropsci2008.12.0709
   Web of Science ®Google Scholar
• Hofstede, G., 1991. Cultures and organizations. Intercultural cooperation and its importance for survival. Software of the mind. London: McGraw-Hill.
   Google Scholar
• Hofstede, G., 2011. Dimensionalizing cultures: the Hofstede model in context. Online Readings in Psychology and Culture, 2 (1), 8. doi:10.9707/2307-0919.1014
   Google Scholar
• IPCC, 2014. Climate change 2014–impacts, adaptation and vulnerability: regional aspects. Cambridge: Cambridge University Press.
   Google Scholar
• Kahneman, D., 2011. Thinking, fast and slow. New York: Macmillan.
   Google Scholar
• Kahneman, D. and Tversky, A., 1979. Prospect theory: an analysis of decision under risk. Econometrica, 47 (2), 263–291. doi:10.2307/1914185
   Web of Science ®Google Scholar
• Kuil, L., et al., 2018. Exploring the influence of smallholders’ perceptions regarding water availability on crop choice and water allocation through socio-hydrological modeling. Water Resources Research, 54 (4), 2580–2604. doi:10.1002/2017WR021420
   Web of Science ®Google Scholar
• Laio, F., et al., 2001. Plants in water-controlled ecosystems: active role in hydrologic processes and response to water stress: II. Probabilistic soil moisture dynamics. Advances in Water Resources, 24 (7), 707–723. doi:10.1016/S0309-1708(01)00005-7
   Web of Science ®Google Scholar
• Moore, T.L.C. and Hunt, W.F., 2012. Ecosystem service provision by stormwater wetlands and ponds – A means for evaluation? Water Research, 46 (20), 6811–6823. doi:10.1016/j.watres.2011.11.026
   PubMed Web of Science ®Google Scholar
• NRAA, 2013. Position paper 6: contingency and compensatory agricultural plans for droughts and floods in India- 2012. DPS Marg, New Dehli: Planning Commission, Government of India.
   Google Scholar
• O’Keeffe, J., et al., 2018. Including farmer irrigation behavior in a sociohydrological modeling framework with application in North India. Water Resources Research, 54 (7), 4849–4866. doi:10.1029/2018WR023038
   Web of Science ®Google Scholar
• OECD (Organization for Economic Cooperation and Development), 2013. Providing agri-environmental public goods through collective action. Paris: Organization for Economic Cooperation and Development, OECD Publishing.
   Google Scholar
• Öhlmér, B., Olson, K., and Brehmer, B., 1998. Understanding farmers’ decision making processes and improving managerial assistance. Agricultural Economics, 18 (3), 273–290. doi:10.1016/S0169-5150(97)00052-2
   Web of Science ®Google Scholar
• Omer, A.R., et al., 2019. Economic analyses of implemented tailwater recovery systems in the Lower Mississippi Alluvial Valley. Sustainable Water Resources Management, 5 (2), 901–919. doi:10.1007/s40899-018-0266-0
   Web of Science ®Google Scholar
• Omer, A.R. and Baker, B.H., 2019. Water quality improvements from implementation of tailwater recovery systems. Sustainable Water Resources Management, 5 (2), 703–713. doi:10.1007/s40899-018-0249-1
   Web of Science ®Google Scholar
• Ostrom, E., 1998. A behavioral approach to the rational choice theory of collective action: presidential address, American political science association, 1997. American Political Science Review, 92 (1), 1–22. doi:10.2307/2585925
   Web of Science ®Google Scholar
• Ostrom, E., et al., 1999. Revisiting the commons: local lessons, global challenges. Science, 284 (5412), 278–282. doi:10.1126/science.284.5412.278
   PubMed Web of Science ®Google Scholar
• Ouyang, Y., et al., 2016. Estimating the ratio of pond size to irrigated soybean land in Mississippi: a case study. Water Supply, 16 (6), 1639–1647. doi:10.2166/ws.2016.087
   Google Scholar
• Palanisami, K., Meinzen-Dick, R., and Giordano, M., 2010. Climate change and water supplies: options for sustaining tank irrigation potential in India. Economic and Political Weekly, 45 (26/27), 183–190.
   Google Scholar
• Pande, S. and Savenije, H.H.G., 2016. A sociohydrological model for smallholder farmers in Maharashtra, India. Water Resources Research, 52 (3), 1923–1947. doi:10.1002/2015WR017841
   Web of Science ®Google Scholar
• Payo, A., et al., 2016. Experiential lock-in: characterizing avoidable maladaptation in infrastructure systems. Journal of Infrastructure Systems, 22 (1), 02515001. doi:10.1061/(ASCE)IS.1943-555X.0000268
   Web of Science ®Google Scholar
• Prince Czarnecki, J.M., Omer, A.R., and Dyer, J.L., 2016. Quantifying capture and use of tailwater recovery systems. Journal of Irrigation and Drainage Engineering, 143 (1), 05016010. doi:10.1061/(ASCE)IR.1943-4774.0001124
   Web of Science ®Google Scholar
• Rao, C.S., et al., 2017. Farm ponds for climate-resilient rainfed agriculture. Current Science, 112 (3), 471–477. doi:10.18520/cs/v112/i03/471-477
   Web of Science ®Google Scholar
• Reba, M.L., et al., 2017. Aquifer depletion in the Lower Mississippi River Basin: challenges and solutions. Journal of Contemporary Water Research & Education, 162 (1), 128–139. doi:10.1111/j.1936-704X.2017.03264.x
   Web of Science ®Google Scholar
• Rodriguez-Iturbe, I., et al., 1999. Probabilistic modelling of water balance at a point: the role of climate, soil and vegetation. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 455 (1990), 3789–3805. doi:10.1098/rspa.1999.0477
   Web of Science ®Google Scholar
• Scanlon, B.R., et al., 2012. Groundwater depletion and sustainability of irrigation in the US High Plains and Central Valley. Proceedings of the National Academy of Sciences, 109 (24), 9320–9325. doi:10.1073/pnas.1200311109
   PubMed Web of Science ®Google Scholar
• Schill, C., et al., 2019. A more dynamic understanding of human behaviour for the Anthropocene. Nature Sustainability, 2 (12), 1075–1082. doi:10.1038/s41893-019-0419-7
   Web of Science ®Google Scholar
• Schlüter, M., et al., 2017. A framework for mapping and comparing behavioural theories in models of social-ecological systems. Ecological Economics, 131, 21–35. doi:10.1016/j.ecolecon.2016.08.008
   Web of Science ®Google Scholar
• Scholer, A.A., et al., 2010. When risk seeking becomes a motivational necessity. Journal of Personality and Social Psychology, 99 (2), 215–231. doi:10.1037/a0019715
   PubMed Web of Science ®Google Scholar
• Sikka, A.K., Islam, A., and Rao, K.V., 2018. Climate-smart land and water management for sustainable agriculture. Irrigation and Drainage, 67 (1), 72–81. doi:10.1002/ird.2162
   Web of Science ®Google Scholar
• Sivapalan, M., Savenije, H.H., and Blöschl, G., 2012. Socio‐hydrology: A new science of people and water. Hydrological Processes, 26 (8), 1270–1276. doi:10.1002/hyp.8426
   Web of Science ®Google Scholar
• Song, L., Jin, J., and He, J., 2019. Effects of severe water stress on maize growth processes in the field. Sustainability, 11 (18), 5086. doi:10.3390/su11185086
   Web of Science ®Google Scholar
• USDA (US Departmet of Agriculture), 1982. Ponds - planning, design, construction. Techical report.  Washington, DC: USDA Agricultural Handbook.
   Google Scholar
• USDA NRCS, 2014. Conservation practice standard irrigation reservoir. Washington, DC: USDA NRCS.
   Google Scholar
• Van den Bergh, J.C.J.M., Ferrer-i-Carbonell, A., and Munda, G., 2000. Alternative models of individual behaviour and implications for environmental policy. Ecological Economics, 32 (1), 43–61. doi:10.1016/S0921-8009(99)00088-9
   Web of Science ®Google Scholar
• van Valkengoed, A.M. and Steg, L., 2019. Meta-analyses of factors motivating climate change adaptation behaviour. Nature Climate Change, 9 (2), 158–163. doi:10.1038/s41558-018-0371-y
   Web of Science ®Google Scholar
• Vico, G. and Porporato, A., 2011. From rainfed agriculture to stress-avoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture. Advances in Water Resources, 34 (2), 263–271. doi:10.1016/j.advwatres.2010.11.010
   Web of Science ®Google Scholar
• Vico, G. and Porporato, A., 2013. Probabilistic description of crop development and irrigation water requirements with stochastic rainfall. Water Resources Research, 49 (3), 1466–1482. doi:10.1002/wrcr.20134
   Web of Science ®Google Scholar
• Vico, G., Tamburino, L., and Rigby, J.R., 2020. Designing on-farm irrigation ponds for high and stable yield for different climates and risk-coping attitudes. Journal of Hydrology, 584, 124634. doi:10.1016/j.jhydrol.2020.124634
   Web of Science ®Google Scholar
• Viglione, A., et al., 2014. Insights from socio-hydrology modelling on dealing with flood risk - roles of collective memory, risk-taking attitude and trust. Journal of Hydrology, 518, 71–82. doi:10.1016/j.jhydrol.2014.01.018
   Web of Science ®Google Scholar
• Wada, Y., van Beek, L.P.H., and Bierkens, M.F.P., 2012. Nonsustainable groundwater sustaining irrigation: A global assessment. Water Resources Research, 48 (6), W00L06. doi:10.1029/2011WR010562
   Web of Science ®Google Scholar
• Yaeger, M., et al., 2018. Trends in the construction of on-farm irrigation reservoirs in response to aquifer decline in eastern Arkansas: implications for conjunctive water resource management. Agricultural Water Management, 208, 373–383. doi:10.1016/j.agwat.2018.06.040
   Web of Science ®Google Scholar
• Zavalloni, M., Raggi, M., and Viaggi, D., 2018. Socio-ecological systems and the distributional effect of collective conditionality constraints in rural policies: A case study in Emilia-Romagna. International Journal of the Commons, 12 (1), 460–484. doi:10.18352/ijc.833
   Web of Science ®Google Scholar