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This study seeks to expand empirical research on how municipalities have adapted and innovated (or not) their water systems as a result of climate change. We analyze characteristics of water governance at the municipal scale in Oklahoma, USA. ArcMap 10.3 was used to build a qualitative geographic information system (GIS) based on fieldwork, including interviews and site-observations, to compare dynamic capabilities that lead to innovation in 38 cities in the state. The GIS enables visualization of our digitalized research to understand the interconnections between drivers of innovativeness-the combination of dynamic capabilities and innovation rates-and state of water resource infrastructure in place specific and regional planning contexts. In particular, the GIS takes into consideration income level, the influence of state-level water policy (Water for 2060 Act), water manager certification levels, population, dynamic capabilities, and perceptions of risk and vulnerability to water system change. Digitizing this information provides a diverging perspective on the historical lack of innovation in the public sector, as different socio-cultural, socio-economic, and socio-political contexts occur throughout Oklahoma, a state notorious for its oil centered economy and its climate change deniers. The findings suggest that innovativeness is directly related to dynamic capabilities and indirectly related to population size, income level, and the educational backgrounds of water decision-makers. The visualizations also show that some cities have surplus capacity for adaptation, while others were able to more efficiently turn capacity into water management innovations. Seeing representations of water governance success and failure in communities affords the opportunity to educate citizens and decision-makers to adapt water infrastructures to the effects of climate change, showcasing the utility of digitalization in a quest for sustainable solutions.

Visualizing dynamic capabilities as adaptive capacity for municipal water governance