Lost in translation: Reconciling different streamflow permanence data products

Area of Science:

• Hydrology and Water Resource Management
• Geospatial Data Analysis
• Environmental Science

Background:

• Accurate streamflow permanence classification is crucial for land and water management decisions.
• Resource managers face challenges reconciling diverse streamflow permanence datasets.
• Field verification for stream classification is often costly and time-consuming.

Purpose of the Study:

• To develop a framework for reconciling perennial and nonperennial streamflow permanence products.
• To evaluate the agreement and reliability of different streamflow permanence datasets.
• To provide a reproducible and flexible decision procedure for land managers.

Main Methods:

• Evaluation of two datasets: National Hydrography Dataset Plus High Resolution (NHDPlus HR) and PRObability of Streamflow PERmanence (PROSPER).
• A two-level framework assessing dataset agreement and reliability.
• Comparison of datasets across different ecoregions and stream types in the Pacific Northwest.

Main Results:

• Datasets show 68% agreement on flowlines, with higher concordance for nonperennial streams.
• PROSPER nonperennial classifications are reliable in arid regions but less so in high mountains and large rivers.
• Over 75% of NHDPlus HR classifications are deemed reliable based on climate conditions at the time of assignment.

Conclusions:

• The developed framework aids in reconciling imperfect streamflow permanence data.
• It offers cost-saving opportunities for land managers through strategic field verification.
• The procedure enhances decision-making by leveraging available geospatial data.