H152-02
Identifying and generating valuable hydrologic information for decisions about natural infrastructure

Monday, 14 December 2020: 11:34
Virtual
Kate A Brauman1, Gena Gammie2, Leah Bremer3, Vivien Bonnesoeur4, Edwing Arapa4, Francisco Román4 and Boris F Ochoa-Tocachi5, (1)University of Minnesota Twin Cities, Minneapolis, MN, United States, (2)Forest Trends, Washington, DC, United States, (3)University of Hawaii, Department of Botany, Manoa, HI, United States, (4)CONDESAN Consortium for the Sustainable Development of the Andean Ecoregion, Lima, Peru, (5)Imperial College London, Civil and Environmental Engineering, London, SW7, United Kingdom
Abstract:
Ensuring that emerging science is both policy relevant and well-communicated to policy makers is critical, particularly in water resources. However, even hydrologic studies explicitly commissioned by and for specific decisions often fail to provide the desired insight. To remedy this, the need for more data or more sophisticated models is often invoked. However, we have found that increased accuracy and precision of results is seldom the key to providing useful and usable information. Drawing on studies of watershed investment programs in the Brazilian Atlantic Forest and the Andes, as well as an in-depth post-hoc evaluation of a watershed study in northern Peru, we set forward two important principles in making hydrologic studies relevant. First, it is critical to develop shared understanding of the decision context, including helping relevant stakeholders articulate both broader water security aims and the hydrologic variables and targets that are of importance to them. Doing this makes it possible to select a method for hydrologic assessment that will provide valuable information at an appropriate cost. Perhaps more importantly, it also builds the legitimacy of the analyst with the decision-making body, increasing the likelihood that findings will be used. Second, working with both stakeholders and technicians to understand the limits of hydrologic models will help in selecting and interpreting a model or modeling approach that will capture the variable of interest. This is of particular importance when modeling the hydrologic impact of changes in natural infrastructure, which is generally not what hydrologic models are developed to evaluate.