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Scientific Tools

Distributed Hydrologic Models

In contrast to traditional modeling approaches, integrated hydrologic models simulate all of the important watershed processes using a comprehensive physically-based approach.  These models provide a means of leveraging point-based streamflow and groundwater measurements at monitoring sites into a comprehensive understanding of the spatial and temporal variations in hydrologic conditions. 


Once developed for a given watershed these models serve as powerful management tools for evaluating projects proposing to use water resources and for planning and optimizing habitat restoration efforts.  These models are also well-suited for evaluating the effects of climate change.  Through linkages to global and regional climate model predictions, distributed hydrologic models can help us understand how changes in temperature and precipitation regimes will impact all aspects of the hydrologic cycle and empower us to develop successful adaptation strategies.

Conceptual diagram shwoing the framework of a distributed hydrologic model courtesy of DHI, Inc.


Light Detection and Ranging (LiDAR) is a remote sensing technology that provides high-resolution topographic and vegetation canopy data for large areas at relatively low cost.  Floodplain studies and habitat restoration designs have traditionally been investigated using 1-dimensional hydraulic models that produce a very simplified picture of hydrologic conditions.  LiDAR datasets are now available for large portions of California making it possible to develop 2-dimensional hydraulic and sediment transport models for projects where the required topographic data for such models would otherwise be cost-prohibited.  


LiDAR-driven 2-dimensional hydraulic models are well-suited for characterizing floodplain flows which are inherently two-dimensional in nature and utilizing such models provides a detailed picture of floodplain processes which can lead to more effective flood mitigation planning and characterization of off-channel habitat conditions.  These tools have also proved invaluable for designing fish passage improvement and instream habitat enhancement projects.  By characterizing the lateral and longitudinal variations in depths and velocities that these projects seek to create, these tools help reduce the uncertainty of project designs and maximize the chances of their success.

Example of a LiDAR point cloud derived from the Sonoma County LiDAR project.







Simulated water depths and velocity vectors generated with a LiDAR-based 2-dimensional hydraulic model.

Habitat Suitability Mapping

Habitat suitability mapping provides a simple but effective method of prioritizing where habitat restoration efforts should be focused in large watersheds.  This approach is based on the premise that projects should be located in reaches where background hydraulic conditions, such as the presence of winter refugia, are most favorable.  However, it can readily be adapted to include other factors, such as the persistence of summer flows.

Mapping is based on LiDAR and regional stream gaging data which can be combined to create a simple but powerful model to estimate flow depth and velocity.  Depth and velocity are then used to create fine-scale estimates of the quantity and quality of winter refugia.  These parameters can be estimated at a three-foot spatial resolution and for a wide range of flows.  This detailed mapping allows for a variety of prioritization metrics to be used, including the presence of suitable hydraulic conditions in the main channel or the presence of off channel features.  Where available, prioritization may incorporate other data such as the continuity of summer flows, observed fish counts, and the presence of large woody debris.  Mapping is available for the East Austin, Mill, Pena, and Redwood Creek watersheds in the Russian River Basin.  However, this simple approach can be applied to much of Coastal California.


These maps are intended to aid with the planning and design of habitat restoration projects. At the planning level, they may help identify promising features to enhance or and at what flows certain features become activated.  At the conceptual design level, hydraulic model results may be used as reconnaissance-level estimates of flow depth and velocity.

For additional details about channel prioritization mapping, please see the following resources courtesy of O'Connor Environmental, Inc.

Lower Russian River Salmonid Habitat Prioritization

Geospatial Salmonid Habitat Modeling Results

Technical Documentation


Story Map




Example of model simulated habitat suitability indices for juvenile salmonids in Mill Creek.




Current availability of Habitat Suitability Mapping

Availability of LiDAR elevation datasets.  Image accessed from the USGS's 3D Elevation (3DEP) program.

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