Forest hydrology modeling tools for watershed management: A review

Demands for water services from forested watersheds have dramatically increased since the 1950s and the trend continues as global environmental change intensifies in the 21st century. The goal of this study is to provide an overview of existing hydrological modeling tools that can be used in watershed management in a forest environment, offer guidance of model uses, and identify knowledge gaps in model development and applications. We classify 47 selected hydrological models according to their development purposes, theories, functionalities, and potentials to be applied in Decision Support Systems (DSS) for addressing five emerging watershed management challenges. We found that generic field, forest stand, and watershed-scale hydrological models developed in the 1980s–1990s are readily available for being incorporated into DSS for projecting hydrological responses to climate and land cover changes and address other watershed management problems. However, these models rarely explicitly link forest structure and species-level information to hydrological processes and functions, thus have limited utilities to answer specific forest management questions. Since early 2000s, hydrological models have incorporated energy, vegetation, terrain, and ecohydrological processes to begin to answer questions at hillslope to regional scales. However, routine uses of advanced modeling tools in forest watershed decision making remain challenging. Future model development should integrate multiple stressors and fine scale ecosystem and surface processes (e.g., vegetation dynamics, energy partitioning, and biogeochemical cycling), and balance model complexity, applicability, and access. Effective forest watershed DSS should have the ability to forecast short and long-term consequences of forest management decisions that often involve high risk and uncertainty under environmental change. In addition, DSS should integrate both physical and social aspects of watershed sciences that value indigenous culture and values.