Water is a key ecosystem service that provides life to vegetation, animals, and human communities. The distribution and flow of water on a landscape influences many ecological functions, such as the distribution and health of vegetation and soil development and function. However, the future of many important water resources remains uncertain. Reduced snowfall and snowpack, earlier spring runoff, increased winter streamflow and flooding, and decreased summer streamflow have all been identified as potential impacts to water resources due to climate change. These factors all influence the water balance in the Pacific Coastal Temperate Rainforest (PCTR).
Ensuring healthy flow and availability of water resources is often highlighted as a priority in land management planning and adaptation. Improved measurement and modeling of water is required to develop predictive estimates for future plant distributions, soil moisture, and snowpack, which all play important roles in ecosystem planning.
The goal of this project was to develop a model to predict future groundwater. Using remote sensing, digital elevation models, GIS, and spatial analysis techniques, the project team aimed to create a data framework to support modeling of hydrology at the landscape scale in the Alaska PCTR. The primary data deliverable is expected to be a “viable wetness index” validated with extensive soil water measurement records. This index is meant to be be used to identify zones of soil moisture accumulation and flow routing to stream networks and provide a critical input variable for the
Integrated Ecosystem Model, a tool to illustrate how landscapes may change in the future.
