Water quality is one of the world's most valued natural resources. Given recent and predicted changes in both climate (more frequent and intense droughts in some regions) and land use (agricultural intensification associated with increasing global demand for meat, dairy, and forestry products), it is important to understand how simultaneous changes in climate and land use affect water quality. For example, does agricultural intensification during a drought increase sediment runoff into rivers, and at what scales do these effects take place? This project will use remote sensing and computer visualization tools to analyze how interactions between shifting climate and land use affect river water quality across multiple interacting scales: from minutes to decades, and from small catchments to regional drainage basins. The proposed research will demonstrate how these cross-scale interactions affect a natural resource with multidimensional societal relevance: water treatment, recreation, safety, tourism, and ecosystem health. Findings from this research will inform emerging US data monitoring networks as to at which spatial and temporal scales water sampling should be conducted to capture interactions from climate and land use. Project results and data will be communicated to the public through various means, including open-access journals, a public website, and college/high school workshops.
A fundamental question that this project will investigate is whether simultaneous shifts in climate and land use result in positive feedbacks and cascading events that lead to dramatic and widespread changes in river water quality. Previous studies have not been able to assess the effects of climate-land use interactions on river water quality over multiple spatial and temporal scales simultaneously due to (1) not having a toolkit that can analyze multiple dimensions and spatial-temporal scales simultaneously; (2) lack of resources (i.e., long-term and consistent water quality datasets with fine resolution); and (3) lack of technology (i.e., ability to capture land cover changes with fine spatial and temporal resolution). This project overcomes these limitations by using (1) a sophisticated set of visualization tools to analyze in combination; (2) one of the world's most comprehensive and extensive water quality datasets (25 years with corresponding climate data); and (3) a fused 8-day temporal resolution and 30-meter spatial resolution land cover dataset that has been developed for the entire country of New Zealand. Thus, this research will be the first time that the interactive effects of climate and land use changes on a suite of water quality variables will be assessed over multiple spatial-temporal scales simultaneously. Further, the application of sophisticated visual analysis tools to investigate landscape dynamics across multiple scales simultaneously could be the impetus for a new paradigm in Geography and Spatial Sciences.
