Univrsity Of Tehran Press Journal of Public Administration 2008-5877 17 3 2025 09 23 Designing a Model for Avoiding Non – knowledge and Ignorance in Water Management Policy-Making Designing a Model for Avoiding Non – knowledge and Ignorance in Water Management Policy-Making 613 652 103961 10.22059/jipa.2025.391977.3671 FA Abbas Monavvarian Prof., Department of Public Policy and Administration, Faculty of Public Administration and Organizational Sciences, College of Management, University of Tehran, Tehran, Iran. Journal Article 2025 03 26 Objective This study aims to design a comprehensive and practical model for reducing ignorance and non-knowledge in the water management policymaking process. In complex policy environments such as water governance, decision-makers frequently face uncertainties, fragmented information, and institutional blind spots. The proposed model is intended to address cognitive, informational, communicational, structural, and organizational barriers that hinder the formulation of effective water policies. By identifying and mitigating the sources of ignorance and non-knowledge, the model seeks to improve the overall quality, precision, and adaptability of decisions in water resource management. This work contributes to the growing body of knowledge on policy intelligence, organizational learning, and adaptive governance. Methods This research is situated within the interpretive paradigm and follows a hybrid inductive–deductive logic. The methodological strategy is based on the multi-grounded theory approach, specifically the version developed by Goldkuhl and Cronholm. Data were collected through semi-structured interviews, allowing for flexibility while maintaining a structured line of inquiry. Using theoretical sampling, 19 key informants—including senior experts, policymakers, technical advisors, and experienced managers in the water sector—were selected. The study applied three methodological quality criteria to ensure the credibility, transferability, and dependability of findings.   Results The findings reveal that ignorance and non-knowledge in the water policymaking process are often systemic and multifaceted. They originate from a lack of reliable and timely data, inadequate information-sharing mechanisms, weak analytical capabilities within public institutions, and limited access to interdisciplinary knowledge. Additional factors include low stakeholder involvement, fragmented communication among governing bodies, and insufficient integration of scientific knowledge into policy processes. The presence of economic pressures and political interference further compounds these challenges, leading to reactive rather than proactive policymaking. Moreover, rapidly changing environmental conditions and technological complexities exacerbate uncertainty and risk in decision-making processes. Conclusion The proposed model presents a systematic approach to overcoming these challenges by improving knowledge flows, fostering institutional coordination, and promoting evidence-based decision-making. It advocates for the use of modern data analytics, participatory governance practices, transparent information infrastructures, and continuous learning mechanisms. The model not only strengthens the internal capacities of policymaking institutions but also builds resilience in the face of climate change, population growth, and increasing water demand. It is particularly valuable in regions facing water stress and high variability in hydrological conditions. By embedding the principles of adaptive management and informed deliberation, this model supports the development of sustainable, inclusive, and future-ready water policies. It enhances the capability of institutions to learn from past failures, anticipate emerging risks, and respond flexibly to change. Ultimately, the model contributes to a governance framework that reduces ignorance, supports long-term planning, and ensures the preservation and equitable distribution of water resources. Objective This study aims to design a comprehensive and practical model for reducing ignorance and non-knowledge in the water management policymaking process. In complex policy environments such as water governance, decision-makers frequently face uncertainties, fragmented information, and institutional blind spots. The proposed model is intended to address cognitive, informational, communicational, structural, and organizational barriers that hinder the formulation of effective water policies. By identifying and mitigating the sources of ignorance and non-knowledge, the model seeks to improve the overall quality, precision, and adaptability of decisions in water resource management. This work contributes to the growing body of knowledge on policy intelligence, organizational learning, and adaptive governance. Methods This research is situated within the interpretive paradigm and follows a hybrid inductive–deductive logic. The methodological strategy is based on the multi-grounded theory approach, specifically the version developed by Goldkuhl and Cronholm. Data were collected through semi-structured interviews, allowing for flexibility while maintaining a structured line of inquiry. Using theoretical sampling, 19 key informants—including senior experts, policymakers, technical advisors, and experienced managers in the water sector—were selected. The study applied three methodological quality criteria to ensure the credibility, transferability, and dependability of findings.   Results The findings reveal that ignorance and non-knowledge in the water policymaking process are often systemic and multifaceted. They originate from a lack of reliable and timely data, inadequate information-sharing mechanisms, weak analytical capabilities within public institutions, and limited access to interdisciplinary knowledge. Additional factors include low stakeholder involvement, fragmented communication among governing bodies, and insufficient integration of scientific knowledge into policy processes. The presence of economic pressures and political interference further compounds these challenges, leading to reactive rather than proactive policymaking. Moreover, rapidly changing environmental conditions and technological complexities exacerbate uncertainty and risk in decision-making processes. Conclusion The proposed model presents a systematic approach to overcoming these challenges by improving knowledge flows, fostering institutional coordination, and promoting evidence-based decision-making. It advocates for the use of modern data analytics, participatory governance practices, transparent information infrastructures, and continuous learning mechanisms. The model not only strengthens the internal capacities of policymaking institutions but also builds resilience in the face of climate change, population growth, and increasing water demand. It is particularly valuable in regions facing water stress and high variability in hydrological conditions. By embedding the principles of adaptive management and informed deliberation, this model supports the development of sustainable, inclusive, and future-ready water policies. It enhances the capability of institutions to learn from past failures, anticipate emerging risks, and respond flexibly to change. Ultimately, the model contributes to a governance framework that reduces ignorance, supports long-term planning, and ensures the preservation and equitable distribution of water resources. https://jipa.ut.ac.ir/article_103961_28823d650ebe2e6f3e386c7afa70949e.pdf