Policy network and content analysis : applications in water resources management and science

This study extends previous work using the state water plans from 1961-2017 with the most recent 2016 regional plan submissions from the Texas Water Development Board, to implement and evaluate a topic analysis methodology. The approach uses statistical analysis of the collection of text documents or corpus to evaluate. Topic Modeling is a systematic approach for analyzing the relationships, usage frequency of words and communities of words to extract themes, concepts, and informational meaning from a selected corpus. This research documents methods for content analysis that can be used on state water plans, as well as other environmental science and policy documents. For this study, nearly 19,658 pages of text from the state and regional water plans for Texas were analyzed. Unsurprisingly, results indicate that “water” is the central common theme connecting all topics. Early results identified a set of primary topics that are shared throughout all regions including planning, strategy, and groundwater. Interestingly, themes varied from west to east reflecting the gradient of arid to humid climates respectively. In the West, themes indicate that regional water planning groups focus more heavily on irrigation and wells for agriculture, while in the East the focus tends to be for municipal uses and surface water strategies, such as reservoirs and infrastructure. This thematic pattern also aligns with the population distribution of Texas, with larger numbers of people in the east, and much less dense populations in the west. Analyses of the state water plans over time illustrate that topics related to drought, planning, and water needs have increased over the period under study. Network statistics reveal that the largest change between state water plans occurred between the 1961 and 1968 plans. Topic analysis methodologies provide an accessible and systematic approach to evaluate the context of water planning, management, and policy across the state. The approach may provide a mechanism for linking quantitative science knowledge about water resources in the state with the qualitative planning and policy perspectives used to manage these critical resources.