Articles | Volume 385
https://doi.org/10.5194/piahs-385-71-2024
https://doi.org/10.5194/piahs-385-71-2024
Post-conference publication
 | 
18 Apr 2024
Post-conference publication |  | 18 Apr 2024

Agent-Based Modelling for representing water allocation methodologies in the irrigation system of the Formoso River Basin, Brazil

Déborah Sousa, Conceição Alves, Fernán Vergara, Cássio Coelho, and Célia Ralha

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Cited articles

Akhbari, M. and Grigg, N.: A Framework for an Agent-Based Model to Manage Water Resources Conflicts, Water Resour. Manag., 27, 4039–4052, https://doi.org/10.1007/s11269-013-0394-0, 2013. a
Alves, K. C. C. L. F., Viola, M., de Mello, C., Giongo, M., and dos Santos, A.: Distribuição da precipitação mensal, anual e máxima diária anual na bacia hidrográfica do rio Formoso Tocantins, Ambiência, 12, 49–70, https://doi.org/10.5935/ambiencia.2016.01.03, 2016. a
ANA: Atlas Irrigação: uso da água na agricultura irrigada, Agência Nacional de Águas (ANA), MDR, Governo Federal, 2 Edn., http://atlasirrigacao.ana.gov.br (last access: 23 January 2023), 2021. a, b
Berglund, E. Z.: Using Agent-Based Modeling for Water Resources Planning and Management, J. Water Resour. Plan. Manag., 141, 04015025, https://doi.org/10.1061/(ASCE)WR.1943-5452.0000544, 2015. a
Blöschl, G., Bierkens, M. F., Chambel, A., Cudennec, C., Destouni, G., Fiori, A., Kirchner, J. W., McDonnell, J. J., Savenije, H. H., Sivapalan, M., Stumpp, C., Toth, E., Volpi, E., Carr, G., Lupton, C., Salinas, J., Széles, B., Viglione, A., Aksoy, H., Allen, S. T., Amin, A., Andréassian, V., Arheimer, B., Aryal, S. K., Baker, V., Bardsley, E., Barendrecht, M. H., Bartosova, A., Batelaan, O., Berghuijs, W. R., Beven, K., Blume, T., Bogaard, T., de Amorim, P. B., Böttcher, M. E., Boulet, G., Breinl, K., Brilly, M., Brocca, L., Buytaert, W., Castellarin, A., Castelletti, A., Chen, X., Chen, Y., Chen, Y., Chifflard, P., Claps, P., Clark, M. P., Collins, A. L., Croke, B., Dathe, A., David, P. C., de Barros, F. P. J., de Rooij, G., Baldassarre, G. D., Driscoll, J. M., Duethmann, D., Dwivedi, R., Eris, E., Farmer, W. H., Feiccabrino, J., Ferguson, G., Ferrari, E., Ferraris, S., Fersch, B., Finger, D., Foglia, L., Fowler, K., Gartsman, B., Gascoin, S., Gaume, E., Gelfan, A., Geris, J., Gharari, S., Gleeson, T., Glendell, M., Bevacqua, A. G., González-Dugo, M. P., Grimaldi, S., Gupta, A. B., Guse, B., Han, D., Hannah, D., Harpold, A., Haun, S., Heal, K., Helfricht, K., Herrnegger, M., Hipsey, M., Hlaváčiková, H., Hohmann, C., Holko, L., Hopkinson, C., Hrachowitz, M., Illangasekare, T. H., Inam, A., Innocente, C., Istanbulluoglu, E., Jarihani, B., Kalantari, Z., Kalvans, A., Khanal, S., Khatami, S., Kiesel, J., Kirkby, M., Knoben, W., Kochanek, K., Kohnová, S., Kolechkina, A., Krause, S., Kreamer, D., Kreibich, H., Kunstmann, H., Lange, H., Liberato, M. L. R., Lindquist, E., Link, T., Liu, J., Loucks, D. P., Luce, C., Mahé, G., Makarieva, O., Malard, J., Mashtayeva, S., Maskey, S., Mas-Pla, J., Mavrova-Guirguinova, M., Mazzoleni, M., Mernild, S., Misstear, B. D., Montanari, A., Müller-Thomy, H., Nabizadeh, A., Nardi, F., Neale, C., Nesterova, N., Nurtaev, B., Odongo, V. O., Panda, S., Pande, S., Pang, Z., Papacharalampous, G., Perrin, C., Pfister, L., Pimentel, R., Polo, M. J., Post, D., Sierra, C. P., Ramos, M.-H., Renner, M., Reynolds, J. E., Ridolfi, E., Rigon, R., Riva, M., Robertson, D. E., Rosso, R., Roy, T., Sá, J. H., Salvadori, G., Sandells, M., Schaefli, B., Schumann, A., Scolobig, A., Seibert, J., Servat, E., Shafiei, M., Sharma, A., Sidibe, M., Sidle, R. C., Skaugen, T., Smith, H., Spiessl, S. M., Stein, L., Steinsland, I., Strasser, U., Su, B., Szolgay, J., Tarboton, D., Tauro, F., Thirel, G., Tian, F., Tong, R., Tussupova, K., Tyralis, H., Uijlenhoet, R., van Beek, R., van der Ent, R. J., van der Ploeg, M., Loon, A. F. V., van Meerveld, I., van Nooijen, R., van Oel, P. R., Vidal, J.-P., von Freyberg, J., Vorogushyn, S., Wachniew, P., Wade, A. J., Ward, P., Westerberg, I. K., White, C., Wood, E. F., Woods, R., Xu, Z., Yilmaz, K. K., and Zhang, Y.: Twenty-three unsolved problems in hydrology (UPH) – a community perspective, Hydrol. Sci. J., 64, 1141–1158, https://doi.org/10.1080/02626667.2019.1620507, 2019. a
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Agent-Based Models (ABMs) are an alternative modelling approach to traditional models that neglect important dynamic and heterogeneous social aspects. In ABMs, agents are represented according to their goals, actions, and perception of their environment. We use water demand data to model distinct cooperative and non-cooperative farmers and regulators as agents in an ABM application to the Formoso River Basin in Brazil, a basin with intense agricultural activity and conflicts among water users.