Articles | Volume 28, issue 17
https://doi.org/10.5194/hess-28-4157-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-28-4157-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Making a case for power-sensitive water modelling: a literature review
Rozemarijn ter Horst
CORRESPONDING AUTHOR
Water Resources Management Group, Department of Environmental Sciences, Wageningen University and Research, Wageningen, 6708 PB, the Netherlands
Water Governance Department, IHE Delft Institute for Water Education, Delft, 2611 AX, the Netherlands
Rossella Alba
Geography Department and Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Berlin 10099, Germany
Jeroen Vos
Water Resources Management Group, Department of Environmental Sciences, Wageningen University and Research, Wageningen, 6708 PB, the Netherlands
Maria Rusca
Global Development Institute, University of Manchester, Manchester, M13 9PL, United Kingdom
Jonatan Godinez-Madrigal
Water Governance Department, IHE Delft Institute for Water Education, Delft, 2611 AX, the Netherlands
Lucie V. Babel
Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, 3584 CB, the Netherlands
Gert Jan Veldwisch
Water Resources Management Group, Department of Environmental Sciences, Wageningen University and Research, Wageningen, 6708 PB, the Netherlands
Jean-Philippe Venot
UMR G-EAU, IRD, University Montpellier, 34000 Montpellier, France
Bruno Bonté
UMR G-EAU, INRAE, University Montpellier, 34000 Montpellier, France
David W. Walker
Water Resources Management Group, Department of Environmental Sciences, Wageningen University and Research, Wageningen, 6708 PB, the Netherlands
Tobias Krueger
Geography Department and Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Berlin 10099, Germany
Related authors
Janneke O. E. Remmers, Rozemarijn ter Horst, Ehsan Nabavi, Ulrike Proske, Adriaan J. Teuling, Jeroen Vos, and Lieke A. Melsen
EGUsphere, https://doi.org/10.5194/egusphere-2025-673, https://doi.org/10.5194/egusphere-2025-673, 2025
Short summary
Short summary
In hydrological modelling, a notion exists that a model is a neutral tool. However, this notion has several, possibly harmful, consequences. In critical social sciences, this non-neutrality in methods and results is an established topic of debate. We propose that in order to deal with it in hydrological modelling, the hydrological modelling network can learn from, and with, critical social sciences. The main lesson, from our perspective, is that responsible modelling is a shared responsibility.
Silvia De Angeli, Lorenzo Villani, Giulio Castelli, Maria Rusca, Giorgio Boni, Elena Bresci, and Luigi Piemontese
Nat. Hazards Earth Syst. Sci., 25, 2571–2589, https://doi.org/10.5194/nhess-25-2571-2025, https://doi.org/10.5194/nhess-25-2571-2025, 2025
Short summary
Short summary
Despite transdisciplinary approaches being increasingly explored to study droughts and their impacts, their depth and breadth are yet to be fully exploited. By integrating insights from different research fields, we present five key dimensions to deepen and broaden the knowledge co-creation process for drought impact studies. Emphasizing social dynamics and power imbalances, we support hydrologists in developing more integrated, power-sensitive, inclusive, situated, and reflexive studies.
Louise Cavalcante, David W. Walker, Sarra Kchouk, Germano Ribeiro Neto, Taís Maria Nunes Carvalho, Mariana Madruga de Brito, Wieke Pot, Art Dewulf, and Pieter R. van Oel
Nat. Hazards Earth Syst. Sci., 25, 1993–2005, https://doi.org/10.5194/nhess-25-1993-2025, https://doi.org/10.5194/nhess-25-1993-2025, 2025
Short summary
Short summary
Drought affects not only water availability but also agriculture, the economy, and communities. This study explores how public policies help reduce these impacts in Ceará, Northeast Brazil. Using qualitative drought monitoring data, interviews, and policy analysis, we found that policies supporting local economies help lessen drought effects. However, most reported impacts are still related to water shortages, showing the need for broader strategies beyond water supply investment.
Sarra Kchouk, Louise Cavalcante, Lieke A. Melsen, David W. Walker, Germano Ribeiro Neto, Rubens Gondim, Wouter J. Smolenaars, and Pieter R. van Oel
Nat. Hazards Earth Syst. Sci., 25, 893–912, https://doi.org/10.5194/nhess-25-893-2025, https://doi.org/10.5194/nhess-25-893-2025, 2025
Short summary
Short summary
Droughts impact water and people, yet monitoring often overlooks impacts on people. In northeastern Brazil, we compare official data to local experiences, finding data mismatches and blind spots. Mismatches occur due to the data's broad scope missing finer details. Blind spots arise from ignoring diverse community responses and vulnerabilities to droughts. We suggest enhanced monitoring by technical extension officers for both severe and mild droughts.
Janneke O. E. Remmers, Rozemarijn ter Horst, Ehsan Nabavi, Ulrike Proske, Adriaan J. Teuling, Jeroen Vos, and Lieke A. Melsen
EGUsphere, https://doi.org/10.5194/egusphere-2025-673, https://doi.org/10.5194/egusphere-2025-673, 2025
Short summary
Short summary
In hydrological modelling, a notion exists that a model is a neutral tool. However, this notion has several, possibly harmful, consequences. In critical social sciences, this non-neutrality in methods and results is an established topic of debate. We propose that in order to deal with it in hydrological modelling, the hydrological modelling network can learn from, and with, critical social sciences. The main lesson, from our perspective, is that responsible modelling is a shared responsibility.
Márk Somogyvári, Fabio Brill, Mikhail Tsypin, Lisa Rihm, and Tobias Krueger
EGUsphere, https://doi.org/10.5194/egusphere-2024-4031, https://doi.org/10.5194/egusphere-2024-4031, 2025
Short summary
Short summary
In this study, we examined regional differences in groundwater behavior in Berlin-Brandenburg. We have developed a novel approach, combining standard groundwater modelling tools such with special data analysis techniques. The presented methodology can help to separate areas with different groundwater behavior from each other, which could be used as a starting point for further analysis.
Sophie Wagner, Fabian Stenzel, Tobias Krueger, and Jana de Wiljes
Hydrol. Earth Syst. Sci., 28, 5049–5068, https://doi.org/10.5194/hess-28-5049-2024, https://doi.org/10.5194/hess-28-5049-2024, 2024
Short summary
Short summary
Statistical models that explain global irrigation rely on location-referenced data. Traditionally, a system based on longitude and latitude lines is chosen. However, this introduces bias to the analysis due to the Earth's curvature. We propose using a system based on hexagonal grid cells that allows for distortion-free representation of the data. We show that this increases the model's accuracy by 28 % and identify biophysical and socioeconomic drivers of historical global irrigation expansion.
Márk Somogyvári, Dieter Scherer, Frederik Bart, Ute Fehrenbach, Akpona Okujeni, and Tobias Krueger
Hydrol. Earth Syst. Sci., 28, 4331–4348, https://doi.org/10.5194/hess-28-4331-2024, https://doi.org/10.5194/hess-28-4331-2024, 2024
Short summary
Short summary
We study the drivers behind the changes in lake levels, creating a series of models from least to most complex. In this study, we have shown that the decreasing levels of Groß Glienicker Lake in Germany are not simply the result of changes in climate but are affected by other processes. In our example, reduced inflow from a growing forest, regionally sinking groundwater levels and the modifications in the local rainwater infrastructure together resulted in an increasing lake level loss.
Germano G. Ribeiro Neto, Sarra Kchouk, Lieke A. Melsen, Louise Cavalcante, David W. Walker, Art Dewulf, Alexandre C. Costa, Eduardo S. P. R. Martins, and Pieter R. van Oel
Hydrol. Earth Syst. Sci., 27, 4217–4225, https://doi.org/10.5194/hess-27-4217-2023, https://doi.org/10.5194/hess-27-4217-2023, 2023
Short summary
Short summary
People induce and modify droughts. However, we do not know exactly how relevant human and natural processes interact nor how to evaluate the co-evolution of people and water. Prospect theory can help us to explain the emergence of drought impacts leading to failed welfare expectations (“prospects”) due to water shortage. Our approach helps to explain socio-hydrological phenomena, such as reservoir effects, and can contribute to integrated drought management considering the local context.
Fanny Frick-Trzebitzky, Rossella Alba, and Kristiane Fehrs
Geogr. Helv., 78, 397–409, https://doi.org/10.5194/gh-78-397-2023, https://doi.org/10.5194/gh-78-397-2023, 2023
Short summary
Short summary
Institutional bricolage and socio-technical tinkering are lenses that expose everyday entanglements, arrangements and processuality in governance. We combine both lenses to analyse adaptive water governance in Accra, Ghana, and Mansfeld-Südharz, Germany. We conclude that the bricolage perspective contributes to bringing multiple forms of being and knowing into engagement when envisioning adaptive water governance in the Anthropocene.
Jonatan Godinez Madrigal, Nora Van Cauwenbergh, Jaime Hoogesteger, Pamela Claure Gutierrez, and Pieter van der
Zaag
Hydrol. Earth Syst. Sci., 26, 885–902, https://doi.org/10.5194/hess-26-885-2022, https://doi.org/10.5194/hess-26-885-2022, 2022
Short summary
Short summary
Urban water systems are facing an increasing pressure on their water resources to guarantee safe and sufficient water access. Water managers often use tried and tested strategies like large supply augmentation infrastructure to address water problems. However, these projects do not address key problems and cause water conflicts. We conducted transdisciplinary research to show how water conflicts can change the development pathway of urban water systems by implementing alternative solutions.
Sarra Kchouk, Lieke A. Melsen, David W. Walker, and Pieter R. van Oel
Nat. Hazards Earth Syst. Sci., 22, 323–344, https://doi.org/10.5194/nhess-22-323-2022, https://doi.org/10.5194/nhess-22-323-2022, 2022
Short summary
Short summary
The aim of our study was to question the validity of the assumed direct linkage between drivers of drought and its impacts on water and food securities, mainly found in the frameworks of drought early warning systems (DEWSs). We analysed more than 5000 scientific studies leading us to the conclusion that the local context can contribute to drought drivers resulting in these drought impacts. Our research aims to increase the relevance and utility of the information provided by DEWSs.
Rossella Alba, Silja Klepp, and Antje Bruns
Geogr. Helv., 75, 363–368, https://doi.org/10.5194/gh-75-363-2020, https://doi.org/10.5194/gh-75-363-2020, 2020
Short summary
Short summary
Taking as an example coastal protection infrastructure under construction in the Venetian Lagoon, we reflect on how environmental justice approaches are useful to analyse the socio-political processes shaping coastal environments and climate change adaptation interventions.
Jonatan Godinez-Madrigal, Nora Van Cauwenbergh, and Pieter van der Zaag
Hydrol. Earth Syst. Sci., 24, 4903–4921, https://doi.org/10.5194/hess-24-4903-2020, https://doi.org/10.5194/hess-24-4903-2020, 2020
Short summary
Short summary
Our research studies whether science depoliticizes water conflicts or instead conflicts politicize science–policy processes. We analyze a water conflict due to the development of large infrastructure. We interviewed key actors in the conflict and replicated the results of water resources models developed to solve the conflict. We found that knowledge produced in isolation has no positive effect in transforming the conflict; instead, its potential could be enhanced if produced collaboratively.
Cited articles
Abbott, M. B. and Vojinovic, Z.: Towards a hydroinformatics praxis in the service of social justice, J. Hydroinform., 16, 516–530, https://doi.org/10.2166/hydro.2013.198, 2014.
Addor, N. and Melsen, L. A.: Legacy, Rather Than Adequacy, Drives the Selection of Hydrological Models, Water Resour. Res., 55, 378–390, https://doi.org/10.1029/2018WR022958, 2019.
Alam, M. F., McClain, M., Sikka, A., and Pande, S.: Understanding human–water feedbacks of interventions in agricultural systems with agent based models: A review, Environ. Res. Lett., 17, 103003, https://doi.org/10.1088/1748-9326/ac91e1, 2022.
Andersson, L.: Experiences of the use of riverine nutrient models in stakeholder dialogues, Int. J. Water Resour. D., 20, 399–413, https://doi.org/10.1080/0790062042000248547, 2004.
Babel, L. and Vinck, D.: The “sticky air method” in geodynamics: Modellers dealing with the constraints of numerical modelling, Rev. Anthropol. Connaiss., 16, https://doi.org/10.4000/rac.27795, 2022.
Babel, L., Vinck, D., and Karssenberg, D.: Decision-making in model construction: Unveiling habits, Environ. Modell. Softw., 120, 104490, https://doi.org/10.1016/j.envsoft.2019.07.015, 2019.
Beck, M. B.: Coping with ever larger problems, models, and data bases. Water Sci. Technol., 39, 1–11, https://doi.org/10.2166/wst.1999.0183, 1999.
Bergström, S.: Principles and confidence in hydrological modelling, Hydrol. Res., 22, 123–136, https://doi.org/10.2166/nh.1991.0009, 1991.
Beven, K.: Environmental modelling: an uncertain future?, CRC Press, 328 pp., https://doi.org/10.1201/9781482288575, 2009.
Beven, K.: How to make advances in hydrological modelling, Hydrol. Res., 50, 1481–1494, https://doi.org/10.2166/nh.2019.134, 2019.
Bijker, W.: Constructing Worlds: Reflections on Science, Technology and Democracy (and a Plea for Bold Modesty), Engag. Sci. Technol. Soc., 3, 315, https://doi.org/10.17351/ests2017.170, 2017.
Bijker, W. E., Hughes, T. P., and Pinch, T. (Eds.): The Social construction of technological systems: new directions in the sociology and history of technology, MIT Press, Cambridge, Mass, 405 pp., ISBN 0-262-02262-1, 1987.
Bouleau, G.: The co-production of science and waterscapes: The case of the Seine and the Rhône Rivers, France, Geoforum, 57, 248–257, https://doi.org/10.1016/j.geoforum.2013.01.009, 2014.
Bremer, L. L., Hamel, P., Ponette-González, A. G., Pompeu, P. V., Saad, S. I., and Brauman, K. A.: Who Are we Measuring and Modeling for? Supporting Multilevel Decision-Making in Watershed Management, Water Resour. Res., 56, e2019WR026011, https://doi.org/10.1029/2019WR026011, 2020.
Budds, J.: Contested H2O: Science, policy and politics in water resources management in Chile, Geoforum, 40, 418–430, https://doi.org/10.1016/j.geoforum.2008.12.008, 2009.
Cash, D., Clark, W. C., Alcock, F., Dickson, N., Eckley, N., and Jäger, J.: Salience, Credibility, Legitimacy and Boundaries: Linking Research, Assessment and Decision Making, SSRN Electron. J., https://doi.org/10.2139/ssrn.372280, 2003.
Clark, M. J.: Putting water in its place: A perspective on GIS in hydrology and water management, Hydrol. Process., 12, 823–834, https://doi.org/10.1002/(SICI)1099-1085(199805)12:6<823::AID-HYP656>3.0.CO;2-Z, 1998.
Chilvers, J. and Kearnes, M. (Eds.): Remaking participation: towards reflexive engagement, in: Remaking Participation: Science, Environment and Emergent Publics, Routledge, 28, https://doi.org/10.1177/0162243919850885, 2015.
Connor, L., Higginbotham, N., Freeman, S., and Albrecht, G.: Watercourses and Discourses: Coalmining in the Upper Hunter Valley, New South Wales, Oceania, 78, 76–90, https://doi.org/10.1002/j.1834-4461.2008.tb00029.x, 2008.
Constanza, R. and Ruth, M.: Using Dynamic Modeling to Scope Environmental Problems and Build Consensus, Environ. Manage., 22, 183–195, https://doi.org/10.1007/s002679900095, 1998.
Cornejo P., S. M. and Niewöhner, J.: How Central Water Management Impacts Local Livelihoods: An Ethnographic Case Study of Mining Water Extraction in Tarapacá, Chile, Water, 13, 3542, https://doi.org/10.3390/w13243542, 2021.
Cowardin, L., Carter, V., Golet, F. C., and LaRoe, E. T.: Classification of wetlands and deep water habitats in the United States, number FWS/OBS-79/31, US Fish and Wildlife Service, https://pubs.usgs.gov/publication/2000109 (last access: 27 August 2024), 1979.
Cronin, P., Ryan, F., and Coughlan, M.: Undertaking a literature review: a step-by-step approach, B. J. Nursing, 17, 38–43, https://doi.org/10.12968/bjon.2008.17.1.28059, 2008.
Dadson, S., Hall, J. W., Garrick, D., Sadoff, C., Grey, D., and Whittington, D.: Water security, risk, and economic growth: insights from a dynamical systems model, Water Resour. Res. 53, 6425–6438, https://doi.org/10.1002/2017WR020640, 2017.
de Oliveira Ferreira Silva, C.: The Challenge of Model Validation and Its (Hydrogeo)ethical Implications for Water Security, in: Computational Intelligence for Water and Environmental Sciences, edited by: Bozorg-Haddad, H. and Zolghadr-Asli, B., Springer Nature Singapore, 477–489, https://doi.org/10.1007/978-981-19-2519-1, 2022.
Deitrick, A. R., Torhan, S. A., and Grady, C. A.: Investigating the Influence of Ethical and Epistemic Values on Decisions in the Watershed Modeling Process, Water Resour. Res., 57, e2021WR030481, https://doi.org/10.1029/2021WR030481, 2021.
Demeritt, D.: The Construction of Global Warming and the Politics of Science, Ann. Am. Assoc. Geogr., 91, 307–337, https://doi.org/10.1111/0004-5608.00245, 2001.
Demeritt, D.: Science studies, climate change and the prospects for constructivist critique, Econ. Soc. 35, 453–479, https://doi.org/10.1080/03085140600845024, 2006.
Dobson, B., Wagener, T., and Pianosi, F.: How Important Are Model Structural and Contextual Uncertainties when Estimating the Optimized Performance of Water Resource Systems?, Water Resour. Res., 55, 2170–2193, https://doi.org/10.1029/2018WR024249, 2019.
Doorn, N.: Responsibility Ascriptions in Technology Development and Engineering: Three Perspectives, Sci. Eng. Ethics, 18, 69–90, https://doi.org/10.1007/s11948-009-9189-3, 2012.
Étienne, M.: Companion modelling: a participatory approach to support sustainable development, Editions Quae, 368 pp., https://doi.org/10.1007/978-94-017-8557-0, 2011.
Falconi, S. M. and Palmer, R. N.: An interdisciplinary framework for participatory modeling design and evaluation – What makes models effective participatory decision tools?, Water Resour. Res., 53, 1625–1645, https://doi.org/10.1002/2016WR019373, 2017.
Fernandez, S.: Much Ado About Minimum Flows…Unpacking indicators to reveal water politics, Geoforum, 57, 258–271, https://doi.org/10.1016/j.geoforum.2013.04.017, 2014.
Garcia-Cuerva, L., Berglund, E. Z., and Rivers, L.: Exploring Strategies for LID Implementation in Marginalized Communities and Urbanizing Watersheds, in: World Environmental and Water Resources Congress 2016, World Environmental and Water Resources Congress 2016, West Palm Beach, Florida, 22–26 May 2016, 41–50, https://doi.org/10.1061/9780784479889.005, 2016.
Godinez-Madrigal, J., Van Cauwenbergh, N., and van der Zaag, P.: Production of competing water knowledge in the face of water crises: Revisiting the IWRM success story of the Lerma-Chapala Basin, Mexico, Geoforum, 103, 3–15, https://doi.org/10.1016/j.geoforum.2019.02.002, 2019.
Golinski, J.: Making Natural Knowledge: Constructivism and the History of Science, University of Chicago Press, Chicago, 368 pp., https://doi.org/10.7208/chicago/9780226302324.001.0001, 2005.
Haas, P. M.: Introduction: Epistemic Communities and International Policy Coordination, Int. Organ., 46, 1–35, https://doi.org/10.1017/S0020818300001442, 1992.
Haddaway, N. R., Macura, B., Whaley, P., and Pullin, A. S.: ROSES RepOrting standards for Systematic Evidence Syntheses: pro forma, flow-diagram and descriptive summary of the plan and conduct of environmental systematic reviews and systematic maps, Environ. Evid., 7, 1–8, https://doi.org/10.1186/s13750-018-0121-7, 2018.
Haeffner, M., Jackson-Smith, D., and Flint, C. G.: Social Position Influencing the Water Perception Gap Between Local Leaders and Constituents in a Socio-Hydrological System, Water Resour. Res., 54, 663–679, https://doi.org/10.1002/2017WR021456, 2018.
Haeffner, M., Hellman, D., Cantor, A., Ajibade, I., Oyanedel-Craver, V., Kelly, M., Schifman, L., and Weasel, L.: Representation justice as a research agenda for socio-hydrology and water governance, Hydrolog. Sci. J., 66, 1611–1624, https://doi.org/10.1080/02626667.2021.1945609, 2021.
Haines, S.: Reckoning resources: Political lives of anticipation in Belize’s water sector, Sci. Tech. Studies, 32, 97–118, https://doi.org/10.23987/sts.64650, 2019.
Hamilton, S. H., Pollino, C. A., Stratford, D. S., Fu, B., and Jakeman, A. J.: Fit-for-purpose environmental modeling: Targeting the intersection of usability, reliability and feasibility, Environ. Modell. Softw., 148, 105278, https://doi.org/10.1016/j.envsoft.2021.105278, 2022.
Haraway, D.: Situated Knowledges: The Science Question in Feminism and the Privilege of Partial Perspective, Fem. Stud., 14, 575, https://doi.org/10.2307/3178066, 1988.
Harmel, R. D., Smith, P. K., Migliaccio, K. W., Chaubey, I., Douglas-Mankin, K. R., Benham, B., Shukla, S., Muñoz-Carpena, R., and Robson, B. J.: Evaluating, interpreting, and communicating performance of hydrologic/water quality models considering intended use: A review and recommendations, Environ. Modell. Softw., 57, 40–51, 2014.
Harvey, F. and Chrisman, N.: Boundary Objects and the Social Construction of GIS Technology, Environ. Plan. Econ. Space, 30, 1683–1694, https://doi.org/10.1068/a301683, 1998.
Hasala, D., Supak, S., and Rivers, L.: Green infrastructure site selection in the Walnut Creek wetland community: A case study from southeast Raleigh, North Carolina, Landscape Urban Plan., 196, 103743, https://doi.org/10.1016/j.landurbplan.2020.103743, 2020.
Holifield, R.: How to speak for aquifers and people at the same time: Environmental justice and counter-network formation at a hazardous waste site, Geoforum, 40, 363–372, https://doi.org/10.1016/j.geoforum.2008.02.005, 2009.
Holifield, R.: Environmental justice as recognition and participation in risk assessment: negotiating and translating health risk at a superfund site in Indian country, Ann. Assoc. Am. Geogr., 102, 591–613, https://doi.org/10.1080/00045608.2011.641892, 2012.
Holländer, H. M., Bormann, H., Blume, T., Buytaert, W., Chirico, G. B., Exbrayat, J.-F., Gustafsson, D., Hölzel, H., Krauße, T., Kraft, P., Stoll, S., Blöschl, G., and Flühler, H.: Impact of modellers' decisions on hydrological a priori predictions, Hydrol. Earth Syst. Sci., 18, 2065–2085, https://doi.org/10.5194/hess-18-2065-2014, 2014.
Jackson, S.: Water models and water politics: design, deliberation, and virtual accountability, Proc. Int. Conf. Digit. Gov. Res., San Diego California, USA, 21–24 May 2006, 95–104, https://doi.org/10.1145/1146598.1146632, 2006.
Jasanoff, S. and Kim, S.-H.: Containing the Atom: Sociotechnical Imaginaries and Nuclear Power in the United States and South Korea, Minerva, 47, 119–146, https://doi.org/10.1007/s11024-009-9124-4, 2009.
Jenkins, D. G. and McCauley, L. A.: GIS, SINKS, FILL, and Disappearing Wetlands: Unintended Consequences in Algorithm Development and Use, SAC'06: Proceedings of the 2006 ACM symposium on Applied computing, Dijon, France, 23–27 April 2006, 277–282, https://doi.org/10.1145/1141277.1141342, 2006.
Jensen, C. B.: A flood of models: Mekong ecologies of comparison, Soc. Stud. Sci., 50, 76–93, https://doi.org/10.1177/0306312719871616, 2020.
Junier, S. J.: Modelling expertise: Experts and expertise in the implementation of the Water Framework Directive in the Netherlands, Delft University of Technology, https://doi.org/10.4233/UUID:EEA8A911-F786-4158-A67E-B99663275BF8, 2017.
King, J. L. and Kraemer, K. L.: Models, Facts, and the Policy Process: The Political Ecology of Estimated Truth, Working Paper #URB-006, Center for Research on Information Systems and Organizations, University of California, Irvine, https://escholarship.org/uc/item/1c31s58g (last access: 16 July 2024), 1993.
Knorr-Cetina, K.: Epistemic cultures: how the sciences make knowledge, Harvard University Press, Cambridge, Massachusetts, 329 pp., ISBN 9780674258945, 1999.
Kouw, M.: Standing on the Shoulders of Giants – And Then Looking the Other Way? Epistemic Opacity, Immersion, and Modeling in Hydraulic Engineering, Perspect. Sci., 24, 206–227, https://doi.org/10.1162/POSC_a_00201, 2016.
Kouw, M.: Risks in the Making: The Mediating Role of Models in Water Management and Civil Engineering in the Netherlands, Ber. Wissgesch., 40, 160–174, https://doi.org/10.1002/bewi.201701823, 2017.
Kroepsch, A. C.: Groundwater Modeling and Governance: Contesting and Building (Sub)Surface Worlds in Colorado's Northern San Juan Basin, Engag. Sci. Technol. Soc., 4, 43–66, https://doi.org/10.17351/ests2018.208, 2018.
Krueger, T. and Alba, R.: Ontological and epistemological commitments in interdisciplinary water research: Uncertainty as an entry point for reflexion, Front. Water, 4, 1038322, https://doi.org/10.3389/frwa.2022.1038322, 2022.
Krueger, T., Maynard, C., Carr, G., Bruns, A., Mueller, E. N., and Lane, S.: A transdisciplinary account of water research, WIREs Water, 3, 369–389, https://doi.org/10.1002/wat2.1132, 2016.
Laborde, S.: Environmental Research from Here and There: Numerical Modelling Labs as Heterotopias, Environ. Plann. D, 33, 265–280, https://doi.org/10.1068/d14128p, 2015.
Landström, C., Whatmore, S. J., and Lane, S. N.: Virtual engineering: computer simulation modelling for flood risk management in England, Sci. Technol. Stud., 24, 3–22, 2011a.
Landström, C., Whatmore, S. J., Lane, S. N., Odoni, N., Ward, N., and Bradley, S.: Coproducing flood risk knowledge: redistributing expertise in critical “participatory modelling,” Environ. Plan. Econ. Space, 43, 1616–1633, 2011b.
Lane, S. N.: Making mathematical models perform in geographical space(s), in: Handbook of Geographical Knowledge, Chap. 17, edited by: Agnew, J. and Livingstone, D., Sage, London, https://doi.org/10.4135/9781446201091, 2012.
Lane, S. N.: Acting, predicting and intervening in a socio-hydrological world, Hydrol. Earth Syst. Sci., 18, 927–952, https://doi.org/10.5194/hess-18-927-2014, 2014.
Lane, S. N., Landström, C., and Whatmore, S. J.: Imagining flood futures: risk assessment and management in practice, Philos. T. R. Soc. A, 369, 1784–1806, https://doi.org/10.1098/rsta.2010.0346, 2011a.
Lane, S. N., Odoni, N., Landström, C., Whatmore, S. J., Ward, N., and Bradley, S.: Doing flood risk science differently: an experiment in radical scientific method, T. I. Brit. Geogr., 36, 15–36, 2011b.
Lane, S. N., November, V., Landström, C., and Whatmore, S.: Explaining rapid transitions in the practice of flood risk management, Ann. Assoc. Am. Geogr., 103, 330–342, https://doi.org/10.1080/00045608.2013.754689, 2013.
Lasswell, H. D.: Politics: Who Gets What, When, How, Whittlesey House, Cleveland, New York, 264, https://doi.org/10.1007/978-3-531-90400-9_60, 1936.
Latour, B.: When things strike back: a possible contribution of “science studies” to the social sciences, Brit. J. Sociol., 51, 107–123, 2000.
Latour, B.: The promises of constructivism, in: Chasing Technology: Matrix of Materiality, Indiana Series for the Philosophy of Science, edited by: Ihde, D., Indiana University Press, 27–46, https://sciencespo.hal.science/hal-01027765 (last access: 16 July 2024), 2003.
Latour, B. and Woolgar, S.: Laboratory life: the construction of scientific facts, Princeton University Press, Princeton, NJ, 294 pp., ISBN 9780691028323, 1986.
Law, J.: After method: Mess in social science research, Routledge, Oxon, United Kingdom, ISBN 0-203-48114-3, 2004.
Linton, J. and Budds, J.: The hydrosocial cycle: Defining and mobilizing a relational-dialectical approach to water, Geoforum, 57, 170–180, https://doi.org/10.1016/j.geoforum.2013.10.008, 2014.
Losee, R. M.: A discipline independent definition of information, J. Am. Soc. Inform. Sci., 48, 254–269, https://doi.org/10.1002/(SICI)1097-4571(199703)48:3<254::AID-ASI6>3.0.CO;2-W, 1997.
MacKenzie, D.: An engine, not a camera: How financial models shape markets, The MIT Press, Cambridge, 392 pp., https://doi.org/10.7551/mitpress/9780262134606.001.0001, 2006.
MacKenzie, D. and Wajcman, J. (Eds.): The social shaping of technology, 2nd edn., Open University Press, Buckingham, Philadelphia, 462 pp., ISBN 9780335199143, 1999.
Macnaghten, P.: Governing Science and Technology: From the Linear Model to Responsible Research and Innovation, in: The Cambridge Handbook of Environmental Sociology, edited by: Legun, K., Keller, J., Bell, M., and Carolan, M., Cambridge University Press, 347–361, https://doi.org/10.1017/9781108554510.023, 2020.
Maeda, E. E., Haapasaari, P., Helle, I., Lehikoinen, A., Voinov, A., and Kuikka, S.: Black Boxes and the Role of Modeling in Environmental Policy Making, Front. Environ. Sci., 9, 629336, https://doi.org/10.3389/fenvs.2021.629336, 2021.
Meenar, M., Fromuth, R., and Soro, M.: Planning for watershed-wide flood-mitigation and stormwater management using an environmental justice framework, Environmental Practice, 20, 55–67, 2018.
Melsen, L. A.: It Takes a Village to Run a Model – The Social Practices of Hydrological Modeling, Water Resour. Res., 58, e2021WR030600, https://doi.org/10.1029/2021WR030600, 2022.
Melsen, L. A., Addor, N., Mizukami, N., Newman, A. J., Torfs, P. J. J. F., Clark, M. P., Uijlenhoet, R., and Teuling, A. J.: Mapping (dis)agreement in hydrologic projections, Hydrol. Earth Syst. Sci., 22, 1775–1791, https://doi.org/10.5194/hess-22-1775-2018, 2018a.
Melsen, L. A., Vos, J., and Boelens, R.: What is the role of the model in socio-hydrology? Discussion of “Prediction in a socio-hydrological world,” Hydrolog. Sci. J., 63, 1435–1443, https://doi.org/10.1080/02626667.2018.1499025, 2018b.
Melsen, L. A., Teuling, A. J., Torfs, P. J. J. F., Zappa, M., Mizukami, N., Mendoza, P. A., Clark, M. P., and Uijlenhoet, R.: Subjective modeling decisions can significantly impact the simulation of flood and drought events, J. Hydrol., 568, 1093–1104, https://doi.org/10.1016/j.jhydrol.2018.11.046, 2019.
Mendoza, P. A., Clark, M. P., Mizukami, N., Gutmann, E. D., Arnold, J. R., Brekke, L. D., and Rajagopalan, B.: How do hydrologic modeling decisions affect the portrayal of climate change impacts?, Hydrol. Process., 30, 1071–1095, https://doi.org/10.1002/hyp.10684, 2016.
Morgan, M. S. and Morrison, M. (Eds.): Models as mediators: Perspectives on natural and social science, Cambridge University Press, Cambridge, 401 pp., https://doi.org/10.1017/CBO9780511660108, 1999.
Munk, A. K.: Risking the Flood: Cartographies of Things to Come, University of Oxford, Oxford, 268 pp., uuid:55c2df2e-3506-4a93-8cab-37f133866182, 2010.
Nearing, G. S., Kratzert, F., Sampson, A. K., Pelissier, C. S., Klotz, D., Frame, J. M., Prieto, C., and Gupta, H. V.: What role does hydrological science play in the age of machine learning?, Water Resour. Res., 57, e2020WR028091, https://doi.org/10.1029/2020WR028091, 2021.
Odoni, N. A. and Lane, S. N.: Knowledge-theoretic models in hydrology, Prog. Phys. Geog., 34, 151–171, https://doi.org/10.1177/0309133309359893, 2010.
Opitz-Stapleton, S. and MacClune, K.: Scientific and Social Uncertainties in Climate Change: The Hindu Kush-Himalaya in Regional Perspective, Chap. 11, in: Community, Environment and Disaster Risk Management, vol. 11, edited by: Lamadrid, A. and Kelman, I., Emerald Group Publishing Limited, 207–237, https://doi.org/10.1108/S2040-7262(2012)0000011017, 2012.
Packett, E., Grigg, N. J., Wu, J., Cuddy, S. M., Wallbrink, P. J., and Jakeman, A. J.: Mainstreaming gender into water management modelling processes, Environ. Modell. Softw., 127, 104683, https://doi.org/10.1016/j.envsoft.2020.104683, 2020.
Petticrew, M. and Roberts, H.: Systematic reviews in the social sciences: A practical guide, Blackwell Publishing Ltd, Malden, USA, 352 pp., ISBN 978-1-4051-2110-1, 2006.
Pielke Jr., R. A.: The Role of Models in Prediction for Decision, in: Models in Ecosystem Science, edited by: Canham, C. D., Cole, J. J., and Lauenroth, W. K., Princeton University Press, 113–137, ISBN: 9780691092898, 2003.
Puy, A., Sheikholeslami, R., Gupta, H. V., Hall, J. W., Lankford, B., Lo Piano, S., Meier, J., Pappenberger, F., Porporato, A., Vico, G., and Saltelli, A.: The delusive accuracy of global irrigation water withdrawal estimates, Nat. Commun., 13, 3183, https://doi.org/10.1038/s41467-022-30731-8, 2022.
Rainwater, K., Stovall, J., Frailey, S., and Urban, L.: Transboundary Impacts on Regional Ground Water Modeling in Texas, Groundwater, 43, 706–716, https://doi.org/10.1111/j.1745-6584.2005.00068.x, 2005.
Ramsey, K.: GIS, modeling, and politics: On the tensions of collaborative decision support, J. Environ. Manage., 90, 1972–1980, https://doi.org/10.1016/j.jenvman.2007.08.029, 2009.
Refsgaard, J. C. and Henriksen, H. J.: Modelling Guidelines – Terminology and Guiding Principles, Adv. Water. Resour., 27, 71–82, https://doi.org/10.1016/j.advwatres.2003.08.006, 2004.
Rusca, M. and Di Baldassarre, G.: Interdisciplinary Critical Geographies of Water: Capturing the Mutual Shaping of Society and Hydrological Flows, Water, 11, 1973, https://doi.org/10.3390/w11101973, 2019.
Rusca, M., Mazzoleni, M., Barcena, A., Savelli, E., and Messori, G.: Speculative Political Ecologies: (re)imagining urban futures of climate extremes, J. Polit. Ecol., 30, 581–608, https://doi.org/10.2458/jpe.4827, 2023.
Saltelli, A. and Di Fiore, M. (Eds.): The Politics of Modelling: Numbers Between Science and Policy, Oxford University Press, 231 pp., ISBN 9780198872412, 2023.
Saltelli, A., Bammer, G., Bruno, I., Charters, E., Di Fiore, M., Didier, E., Nelson Espeland, W., Kay, J., Lo Piano, S., Mayo, D., and Pielke Jr., R.: Five ways to ensure that models serve society: a manifesto, Nature, 582, 482–484, https://doi.org/10.1038/d41586-020-01812-9, 2020.
Sanz, D., Vos, J., Rambags, F., Hoogesteger, J., Cassiraga, E., and Gómez-Alday, J. J.: The social construction and consequences of groundwater modelling: insight from the Mancha Oriental aquifer, Spain, Int. J. Water Resour. D., 35, 808–829, https://doi.org/10.1080/07900627.2018.1495619, 2019.
Shapiro, C.: Coordination and integration of wetland data for status and trend and inventory estimates, Technical Report 2, Federal Geographic Data Committee, Wetlands Subcommittee, 210 pp., https://www.govinfo.gov/content/pkg/CZIC-qh545-a1-c88-1995/html/CZIC-qh545-a1-c88-1995.htm (last access: 27 August 2024), 1995.
Shrader-Frechette, K.: Hydrogeology and framing questions having policy consequences, Philos. Sci., 64, S149–S160, https://doi.org/10.1086/392595, 1997.
Sismondo, S.: Models, Simulations, and Their Objects, Sci. Context, 12, 247–260, https://doi.org/10.1017/S0269889700003409, 1999.
Sivapalan, M., Savenije, H. H. G., and Blöschl, G.: Socio-hydrology: A new science of people and water, Hydrol. Process., 26, 1270–1276, https://doi.org/10.1002/hyp.8426, 2011.
Srinivasan, V., Sanderson, M., Garcia, M., Konar, M., Blöschl, G., and Sivapalan, M.: Prediction in a socio-hydrological world, Hydrolog. Sci. J., 62, 1–8, https://doi.org/10.1080/02626667.2016.1253844, 2016.
Srinivasan, V., Sanderson, M., Garcia, M., Konar, M., Blöschl, G., and Sivapalan, M.: Moving socio-hydrologic modelling forward: unpacking hidden assumptions, values and model structure by engaging with stakeholders: reply to “What is the role of the model in socio-hydrology?,” Hydrolog. Sci. J., 63, 1444–1446, https://doi.org/10.1080/02626667.2018.1499026, 2018.
Stengers, I.: Another science is possible: A manifesto for slow science, John Wiley & Sons, ISBN 978-1-509-52181-4, 2018.
Thompson, E. L. and Smith, L. A.: Escape from model-land, Economics, 13, 20190040, https://doi.org/10.5018/economics-ejournal.ja.2019-40, 2019.
Trombley, J. M.: An Environmental Anthropology of Modeling and Management on the Chesapeake Bay Watershed, PhD thesis, University of Maryland, College Park, https://doi.org/10.13016/M2CV4BS14, 2017.
Turner, M. D.: Production of environmental knowledge: Scientists, complex natures, and the question of agency, in: Knowing Nature: Conversations at the Intersection of Political Ecology and Science Studies, edited by: Goldman, M. J., Nadasdy, P., and Turner, M. D., University of Chicago Press, Chicago, 25–29, ISBN 9780226301402, 2011.
Turnhout, E., Hisschemöller, M., and Eijsackers, H.: Ecological indicators: between the two fires of science and policy, Ecol. Indic., 7, 215–228, https://doi.org/10.1016/j.ecolind.2005.12.003, 2007.
Venot, J.-P., Vos, J., Molle, F., Zwarteveen, M., Veldwisch, G. J., Kuper, M., Mdee, A., Ertsen, M., Boelens, R., Cleaver, F., Lankford, B., Swatuk, L., Linton, J., Harris, L. M., Kemerink-Seyoum, J., Kooy, M., and Schwartz, K.: A bridge over troubled waters, Nat. Sustain., 5, 92, https://doi.org/10.1038/s41893-021-00835-y, 2022.
Voinov, A., Seppelt, R., Reis, S., Nabel, J. E., and Shokravi, S.: Values in socio-environmental modelling: Persuasion for action or excuse for inaction. Environ. Modell. Softw., 53, 207–212, https://doi.org/10.1016/j.envsoft.2013.12.005, 2014.
Voinov, A., Kolagani, N., McCall, M. K., Glynn, P. D., Kragt, M. E., Ostermann, F. O., Pierce, S. A., and Ramu, P.: Modelling with stakeholders – Next generation, Environ. Modell. Softw., 77, 196–220, https://doi.org/10.1016/j.envsoft.2015.11.016, 2016.
Wardropper, C. B., Gillon, S., and Rissman, A. R.: Uncertain monitoring and modeling in a watershed nonpoint pollution program, Land Use Policy, 67, 690–701, https://doi.org/10.1016/j.landusepol.2017.07.016, 2017.
Wesselink, A., de Vriend, H., Barneveld, H., Krol, M., and Bijker, W.: Hydrology and hydraulics expertise in participatory processes for climate change adaptation in the Dutch Meuse, Water Sci. Technol., 60, 583–595, 2009.
Wesselink, A., Kooy, M., and Warner, J.: Socio-hydrology and hydrosocial analysis: toward dialogues across disciplines, WIREs Water, 4, e1196, https://doi.org/10.1002/wat2.1196, 2017.
Whatmore, S. J. and Landström, C.: Manning's N: Putting roughness to work, in: How well do facts travel?: The dissemination of reliable knowledge, edited by: Howlett, P. and Morgan, M. S., Cambridge University Press, 111–135, ISBN 9780521159586, 2010.
Wheeler, K. G., Hall, J. W., Abdo, G. M., Dadson, S. J., Kasprzyk, J. R., Smith, R., and Zagona, E. A.: Exploring Cooperative Transboundary River Management Strategies for the Eastern Nile Basin, Water Resour. Res., 54, 9224–9254, https://doi.org/10.1029/2017WR022149, 2018a.
Wheeler, K. G., Robinson, C. J., and Bark, R. H.: Modelling to bridge many boundaries: the Colorado and Murray-Darling River basins, Reg. Environ. Change, 18, 1607–1619, https://doi.org/10.1007/s10113-018-1304-z, 2018b.
Woolgar, S. and Cooper, G.: Do artefacts have ambivalence: Moses' bridges, Winner's bridges and other urban legends in S&TS, Soc. Stud. Sci., 29, 433–449, https://doi.org/10.1177/030631299029003005, 1999.
Zwarteveen, M., Kemerink-Seyoum, J. S., Kooy, M., Evers, J., Guerrero, T. A., Batubara, B., Biza, A., Boakye-Ansah, A., Faber, S., Cabrera Flamini, A., Cuadrado-Quesada, G., Fantini, E., Gupta, J., Hasan, S., ter Horst, R., Jamali, H., Jaspers, F., Obani, P., Schwartz, K., Shubber, Z., Smit, H., Torio, P., Tutusaus, M., and Wesselink, A.: Engaging with the politics of water governance, WIREs Water, 4, e01245, https://doi.org/10.1002/wat2.1245, 2017.
Short summary
The exact power of models often remains hidden, especially when neutrality is claimed. Our review of 61 scientific articles shows that in the scientific literature little attention is given to the power of water models to influence development processes and outcomes. However, there is a lot to learn from those who are openly reflexive. Based on lessons from the review, we call for power-sensitive modelling, which means that people are critical about how models are made and with what effects.
The exact power of models often remains hidden, especially when neutrality is claimed. Our...