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Understanding aquatic habitat and water resource responses to rapid and ongoing changes in both climate and land-use provide the basis for monitoring physical processes in ten streams and their watersheds in the northeastern portion of the National Petroleum Reserve in Alaska (NPR-A). Streams selected for monitoring were originally based on planned development in their upstream catchments and to represent reference (undeveloped) conditions. Monitoring periods for each station (up to 15 years) vary according to adaptive management of water resources in response to broader NPR-A management planning as well as alignment with proposed and ongoing monitoring efforts in Arctic Alaska. Stream discharge and water temperature data provide basic information to characterize physical regimes and variability among drainage units with respect to flood hazards, responses to land and permafrost dynamics, and connectivity and suitability of habitat for fish and other aquatic organism. Evaluating potential impacts of petroleum development primarily in the from lake water extraction, roads, and oil drilling and transport infrastructure are also an intended use of the data and reason for maintaining these monitoring stations. These data also support basic scientific studies of several National Science Foundation and U.S. Fish and Wildlife funded projects to characterize and understand the Arctic system. Data collection was primarily supported by the Bureau of Land Management. 

This dataset contains lake bathymetry measurements acquired in 2012 on six lakes [INI01, INI03, INI04, INI05, INI06, and INI07] in Inigok region in the North Slope of Alaska. The measurements were conducted with a Garmin GPSMAP 531s using variable settings for Tracking depending on lake size (e.g. time- vs. distance-based). For each lake there is a spreadsheet with latitude, longitude, and lake depth (in meters) for each measurement point. 

This set of eleven lakes located in the Fish Creek Watershed in northern Alaska have been monitored for varying periods of time starting as early as 2011 as part of the Fish Creek Watershed Observatory (http://www.fishcreekwatershed.org/) and in coordination with several NSF supported projects. Lakes were primarily selected for long-term monitoring because of interest in water supply for industrial activities and corresponding ecosystem services along with dynamics related to climate change and variability. These data include basic lake attributes of water surface elevation and water temperature at the lake bed of interest to studies of water balance, aquatic habitat, and permafrost stability. In some cases, additional data or studies have been completed on some of these lakes which are reported separately in other datasets or scientific papers or reports. 

Understanding aquatic habitat and water resource responses to rapid and ongoing changes in both climate and land-use provide the basis for monitoring physical processes in ten streams and their watersheds in the northeastern portion of the National Petroleum Reserve in Alaska (NPR-A). Streams selected for monitoring were originally based on planned development in their upstream catchments and to represent reference (undeveloped) conditions. Monitoring periods for each station (up to 12 years) vary according to adaptive management of water resources in response to broader NPR-A management planning as well as alignment with proposed and ongoing monitoring efforts in Arctic Alaska. Stream discharge and water temperature data provide basic information to characterize physical regimes and variability among drainage units with respect to flood hazards, responses to land and permafrost dynamics, and connectivity and suitability of habitat for fish and other aquatic organism. Evaluating potential impacts of petroleum development primarily in the from lake water extraction, roads, and oil drilling and transport infrastructure are also an intended use of the data and reason for maintaining these monitoring stations. These data also support basic scientific studies of several National Science Foundation and U.S. Fish and Wildlife funded projects to characterize and understand the Arctic system. Data collection was primarily supported by the Bureau of Land Management. 

Assessment of lakes for their future potential to drain relied on the 2002/03 airborne Interferometric Synthetic Aperture Radar (IFSAR) Digital Surface Model (DSM) data for the western Arctic Coastal Plain in northern Alaska. Lakes were extracted from the IfSAR DSM using a slope derivative and manual correction (Jones et al., 2017). The vertical uncertainty for correctly detecting lake-based drainage gradients with the IfSAR DSM was defined by comparing surface elevation differences of several overlapping DSM tile edges. This comparison showed standard deviations of elevation between overlapping IfSAR tiles ranging from 0.0 to 0.6 meters (m). Thus, we chose a minimum height difference of 0.6 m to represent a detectable elevation gradient adjacent to a lake as being most likely to contribute to a rapid drainage event. This value is also in agreement with field verified estimates of the relative vertical accuracy (~0.5 m) of the DSM dataset around Utqiaġvik (formerly Barrow) (Manley et al., 2005) and the stated vertical RMSE (~1.0 m) of the DSM data (Intermap, 2010). Development of the potential lake drainage dataset involved several processing steps. First, lakes were classified as potential future drainage candidates if the difference between the elevation of the lake surface and the lowest elevation within a 100 m buffer of the lake shoreline exceeded our chosen threshold of 0.6 m. Next, we selected lakes with a minimum size of 10 ha to match the historic lake drainage dataset. We further filtered the dataset by selecting lakes estimated to have low hydrological connectivity based on relations between lake contributing area as determined for specific surficial geology types and presented in Jones et al. (2017). This was added to the future projection workflow to isolate the lake population that likely responds to changes in surface area driven largely by geomorphic change as opposed to differences in surface hydrology. Lakes within a basin with low to no hydrologic connectivity that had an elevation change gradient between the lake surface and surrounding landscape are considered likely locations to assess for future drainage potential. Further, the greater the elevation difference, the greater the drainage potential. This dataset provided a first-order estimate of lakes classified as being prone to future drainage. We further refined our assessment of potential drainage lakes by identifying the location of the point with the lowest elevation within the 100 m buffer of the lake shoreline and manually interpreted lakes to have a high drainage potential based on the location of the likely drainage point to known lake drainage pathways using circa 2002 orthophotography or more recent high resolution satellite imagery available for the Western Coastal Arctic Plain (WACP). Lakes classified as having a high drainage potential typically had the likely drainage location associated with one or more of the following: (1) an adjacent lake, (2) the cutbank of a river, (3) the ocean, (4) were located in an area with dense ice-wedge networks, (5) appeared to coincide with a potentially headward eroding stream, or (6) were associated with thermokarst lake shoreline processes in the moderate to high ground ice content terrain. We also added information on potential lake drainage pathways to the high potential drainage dataset by manually interpreting the landform associated with the likely drainage site to draw comparisons with the historic lake drainage dataset. 

We identified all lakes larger than 10 hectares (ha) that drained completely or partially (greater than 25 %) between 1955 and 2017 using historical (original) USGS topographic maps and aerial photography (1955) and Landsat Imagery (circa 1975, circa 2000, and annually since 2000). For each lake drainage event, we inferred the drainage mechanism and categorized the drainage pathway based on known lake drainage mechanisms using interpretation of high-resolution remote sensing data and field observations.