Updated classifications of flow permanence on streams in the Colville National Forest
The Issue: Streamflow permanence refers to the probability that a stream will lose surface flow (become a dry channel), as well as the timing, duration, and frequency of drying. Patterns of streamflow permanence drive important decisions regarding forest management and other land uses. The Colville National Forest Land and Resource Management Plan (2019), for example, specifies riparian management areas with sizes that differ, in part, based on streamflow permanence. Existing classifications of streamflow permanence, as well as delineations of stream hydrography depend heavily on decades-old information and are in urgent need of updating. To address these critical needs, stream hydrography is being updated across the Pacific Northwest using high-resolution Light Detection and Ranging (LiDAR) elevation data and new models predict flow permanence throughout entire stream networks.
How USGS will help: The study will use wet/dry field observations collected in 2021 using the FLOwPER data collection mobile application to produce a new predictive empirical model to map the likelihood of stream drying for streams flowing within the Colville Nati
Problem: Streamflow permanence refers to the probability that a stream will lose surface flow (become a dry channel), as well as the timing, duration, and frequency of drying. Patterns of streamflow permanence drive important decisions regarding forest management and other land uses, as well as vulnerability of native fishes – especially species in headwater streams. The new Colville National Forest Land and Resource Management Plan (2019), for example, specifies riparian management areas with sizes that differ, in part, based on streamflow permanence (i.e., perennial or seasonally flowing). Existing classifications of streamflow permanence, as well as delineations of stream hydrography (i.e., digital maps of the stream network) depend heavily on decades-old information and are in urgent need of updating (Hafen et al. 2020). To address these critical needs, stream hydrography is being updated across the Pacific Northwest using high-resolution elevation data that is now widely available via application of Light Detection and Ranging (LiDAR) technology. In addition, new tools have been developed to measure (Gendaszek et al. 2020, Jaeger et al. 2020) and predict (Jaeger et al. 2019) flow permanence throughout entire stream networks.
Objectives: We propose to use new data planned for collection in 2021 to produce a new predictive empirical model to map the likelihood of stream drying at both observed and unobserved sites on the Colville National Forest. This model is intended to serve as a prototype application for updating information on hydrography and flow permanence on short time frames (2-3 years) across broad landscapes such as National Forests, National Parks, or BLM lands.
Relevance and Benefits: The study is consistent with the USGS strategic science directions “A National hazards, risk, and resilience assessment program” and “Understanding Ecosystems and Predicting Ecosystem Change” identified in the 2007-17 science strategy of the USGS (U.S. Geological Survey, 2007). The results from this study help guide future management decisions in the Colville National Forest (and surrounding areas) by providing high resolution maps of where streams are likely to have year-round flow or may go dry. This information can information has important regulatory information related to USFS management decisions related to timber harvest practices and aerial application of materials on forest lands such as fire retardants.
Approach: The study will be based on field data collected in 2021 to track potential drying of streams as indicated by thermal signatures within stream channels (e.g., Gendaszek et al. 2020) and use of the FLOwPER (FLOw PERmanence) data collection app (Jaeger et al. 2020). A design-based survey will direct National Forest Crews to specific locations for data collection. These data will be processed and incorporated into a spatial predictive model to provide estimates of the probability of stream drying across seasons (July-October) when drying is most likely for all streams within the newly routed hydrography.
Probability of Streamflow Permanence (PROSPER)
The Issue: Streamflow permanence refers to the probability that a stream will lose surface flow (become a dry channel), as well as the timing, duration, and frequency of drying. Patterns of streamflow permanence drive important decisions regarding forest management and other land uses. The Colville National Forest Land and Resource Management Plan (2019), for example, specifies riparian management areas with sizes that differ, in part, based on streamflow permanence. Existing classifications of streamflow permanence, as well as delineations of stream hydrography depend heavily on decades-old information and are in urgent need of updating. To address these critical needs, stream hydrography is being updated across the Pacific Northwest using high-resolution Light Detection and Ranging (LiDAR) elevation data and new models predict flow permanence throughout entire stream networks.
How USGS will help: The study will use wet/dry field observations collected in 2021 using the FLOwPER data collection mobile application to produce a new predictive empirical model to map the likelihood of stream drying for streams flowing within the Colville Nati
Problem: Streamflow permanence refers to the probability that a stream will lose surface flow (become a dry channel), as well as the timing, duration, and frequency of drying. Patterns of streamflow permanence drive important decisions regarding forest management and other land uses, as well as vulnerability of native fishes – especially species in headwater streams. The new Colville National Forest Land and Resource Management Plan (2019), for example, specifies riparian management areas with sizes that differ, in part, based on streamflow permanence (i.e., perennial or seasonally flowing). Existing classifications of streamflow permanence, as well as delineations of stream hydrography (i.e., digital maps of the stream network) depend heavily on decades-old information and are in urgent need of updating (Hafen et al. 2020). To address these critical needs, stream hydrography is being updated across the Pacific Northwest using high-resolution elevation data that is now widely available via application of Light Detection and Ranging (LiDAR) technology. In addition, new tools have been developed to measure (Gendaszek et al. 2020, Jaeger et al. 2020) and predict (Jaeger et al. 2019) flow permanence throughout entire stream networks.
Objectives: We propose to use new data planned for collection in 2021 to produce a new predictive empirical model to map the likelihood of stream drying at both observed and unobserved sites on the Colville National Forest. This model is intended to serve as a prototype application for updating information on hydrography and flow permanence on short time frames (2-3 years) across broad landscapes such as National Forests, National Parks, or BLM lands.
Relevance and Benefits: The study is consistent with the USGS strategic science directions “A National hazards, risk, and resilience assessment program” and “Understanding Ecosystems and Predicting Ecosystem Change” identified in the 2007-17 science strategy of the USGS (U.S. Geological Survey, 2007). The results from this study help guide future management decisions in the Colville National Forest (and surrounding areas) by providing high resolution maps of where streams are likely to have year-round flow or may go dry. This information can information has important regulatory information related to USFS management decisions related to timber harvest practices and aerial application of materials on forest lands such as fire retardants.
Approach: The study will be based on field data collected in 2021 to track potential drying of streams as indicated by thermal signatures within stream channels (e.g., Gendaszek et al. 2020) and use of the FLOwPER (FLOw PERmanence) data collection app (Jaeger et al. 2020). A design-based survey will direct National Forest Crews to specific locations for data collection. These data will be processed and incorporated into a spatial predictive model to provide estimates of the probability of stream drying across seasons (July-October) when drying is most likely for all streams within the newly routed hydrography.