Association for Public Policy Analysis & Management

Management of water-related data varies across a wide range of practices and contexts, with some entities having no formal water data management system, while others have robust processes in place. Since 2000, the European Union’s Water Framework Directive has employed an integrated river basin management approach, which requires data collection and sharing for collaboration among member-states. Australia’s National Water Initiative similarly provides an overarching framework for states and territories to contribute to and benefit from standardized data collection and reporting.

The State of California has struggled to create and implement a comprehensive and integrated water management platform. Groups and agencies, both academic and governmental, have respective data collection and sharing systems that focus on particular aspects (e.g., surface water quality, distribution of precipitation), but data have no central management location. This, in part, gave rise to the 2016 Open and Transparent Water Data Act (California AB 1755), which mandates California’s Department of Water Resources to establish a statewide integrated water data platform.

In this work, a Water Data Management Index (WDMI) is developed and California is selected as a case study for evaluating effects of proposed components of such a platform.

The WDMI provides a quantitative measure of the efficiency and effectiveness of water data management using a range of relevant political, social, and scientific indicators to meet pre-identified objectives. The WDMI score of various states and nations can be calculated and compared to the strength of their water systems and effectiveness of water policies. Applied to California, the WDMI will identify areas for potential improvement, and be compared to the results of a meta-analysis of current and historical water data management recommendations. This meta-analysis elucidated four key recommendations for improvement: increase stakeholder collaboration, improve data transparency and accessibility, increase data monitoring and collection, and normalize metrics used in various water sectors. Each recommendation (and combination of recommendations) will be assessed by its impact on California’s WDMI score.  

Explicit weights are assigned to the objectives and indicators to create an aggregate WDMI score. While subjective, the weightings were developed in collaboration with experts in the field. The WDMI ranges from 0 to 100, with higher values indicating better performance.

We expect California’s WDMI score to increase with implementation of any of the four recommendations. Ultimately, a cost-benefit analysis of each option will be conducted to recommend priority actions. The WDMI can be translated beyond this case study to identify other bodies that may benefit from investment in water data management. This will be increasingly relevant for natural resources managers in the modern era of big data technology and innovation.

California represents a timely example of how investment in data management can improve natural resource management and improve resilience in times of stress. By evaluating changes to the WDMI (with and without these proposed improvements) in response to  stressors (prolonged drought, population growth, repeated flooding), this work will further show that effective water data management can create more robust and dynamic policy environments in the face of future uncertainties.