DOI: 10.5061/dryad.m905qfv9z
title: Fish slough remote sensing and geospatial database

description: Remote sensing and field investigations were conducted to assess how
 cimate and groundwater pumping influence surface water flows, groundwater
 levels, and vegetation conditions at Fish Slough. This database contains
 all related remote sensing and geospatial datasets used in the
 analysis. 
description: Remote sensing- and field-investigations were conducted at Fish
 Slough using Google Earth Engine, ESRI's ArcGIS Pro and ArcMap, and
 an Apple iPad. Additionally, a DJI Phantom 4 Pro drone was used to collect
 high-resolution imagery of the study area. Collected datasets were
 post-processed using Google Earth Engine, ESRI's ArcGIS Pro and
 ArcMap, and Agisoft Metashape.
description: # Fish Slough Remote Sensing and Geospatial Database ## Description of the
 data and file structure Assessment of Potential Drivers of Surface and
 Groundwater Decline at Fish Slough, Owens Valley, CA: Geospatial Database
 Prepared by Blake Minor, Christine Albano, Guy Smith, and Justin
 Huntington from the Desert Research Institute, in coordination with the
 U.S. Fish and Wildlife Service. This database contains geospatial,
 hydrology, climate, and remote sensing data gathered/prepared in 2022 for
 the Assessment of Potential Drivers of Surface and Groundwater Declines at
 Fish Slough, Owen's Valley, CA. Federal Geographic Data Committee
 (FGDC) metadata is provided for each type of data in a separate
 "metadata "folder. There are 11 folders containing various
 datasets and metadata: agricultural_et basin_boundary bcm_climate_data
 groundwater_level_data ndvi_ndwi_trend pumping_inventory site_data
 surface_water_data zonal_stats_aois FishSlough_arcpro metadata The
 "agricultural_et" folder contains field boundary polygons
 (FishSlough_SSEBOP_irrigated_ag_WaterApplicationRate_field_polys.shp) for
 Fish Lake Valley and the Tri-Valley areas with estimates of annual
 application rates (feet per year and millimeters per year) provided as
 shapefile attributes for each feature. Additionally, a summary table
 (FishSlough_SSEBOP_annual_ag_TotalWaterApplied_summary.xlsx) containing
 estimates of total applied water and pumping inventories (acre-feet) for
 different regions near the study area is provided. Cells with
 "NaN" represent years where no pumping inventory data was
 available. The "basin_boundary" folder contains the Crowley Lake
 HUC-8 (18090102) boundary (e.g. Fish_slough_HUC8_basin.shp) for the Fish
 Slough study area, which is derived from the National Hydrography Dataset
 (NHD) Water Boundary Dataset (WBD). The "bcm_climate_data"
 folder contains a monthly timeseries
 (Fish_Slough_area_HUC10_monthlytimeseries.xlsx) of the spatially averaged
 Basin Characterization Model (BCM) data variables for HUC-10 boundaries
 that comprise the Fish Slough Catchment Area. The field names within the
 excel file are as follows and follow the descriptions in the USGS report
 (https://pubs.usgs.gov/publication/tm6H1): huc10 - HUC10 number name -
 HUC10 name areaacres - Total area of the HUC10 in units of acres areasqkm
 - Total area of the HUC10 in units of square kilometers aet - Actual
 evapotranspiration in millimeters cwd - Climatic water deficit in
 millimeters pck - Snowpack in millimeters pet - Potential
 evapotranspiration in millimeters ppt - Precipitation in millimeters rch -
 Recharge in millimeters run - Runoff in millimeters str - Soil moisture
 storage in millimeters tmn - Minimum air temperature in degrees celsius
 tmx - Maximum air temperature in degrees celsius states - The states
 within which the HUC10 boundary is located datetime - The date The
 "groundwater_level_data" folder contains the following files: 1)
 one shapefile of well locations (e.g.
 NDWR_CDWR_and_USGS_Combined_wells.shp), 2) a symbology layer, which is
 used to illustrate the depth to groundwater trends
 (NDWR_CDWR_and_USGS_Combined_wells.lyr), and 3) three excel files. The
 first excel file (Combined_Site_Data.csv) contains site information about
 the wells. Site information includes the site name (well name), site ID,
 owner, well depth in feet, land surface elevation in feet asl, basin
 number, agency, permit number, well log number, perforations, latitude in
 decimal degrees, and the longitude in decimal degrees. The second excel
 file (Combined_WL_Data.csv) contains water level measurement information
 from each well. Columns include the site name (SITE_ID), measurement
 dates, depth to groundwater (DTW) in feet below ground surface, and water
 level elevations in feet above mean sea level (WL_AMSL). The third excel
 file (resampled_water_year_WL_Data.csv) contains resampled (water year
 average) depth to groundwater information for the wells. The
 "ndvi_ndwi_trend" folder contains 2 trend raster grids and 2
 corresponding p-value grids. One of the trend rasters represents the
 long-term trends (1985-2021) in the annual July 15 - Sept 15 median
 Landsat Collection 2-derived normalized difference vegetation index (NDVI,
 dimensionless) based on the Theil-Sen slope estimator
 (FishSlough_NDVI_slope_desc_85_21.tif). The other trend raster represents
 the long-term trends (1985-2021) in Landsat derived Normalized Difference
 Water Index (NDWI, dimensionless) using the green and near-infrared
 wavelengths (FishSlough_NDWI_slope_desc_85_21.tif). The NDVI and NDWI
 trend rasters each have a p-value raster associated with their trends
 (e.g. FishSlough_NDVI_pvalue_85_21.tif), which represents the Mann-Kendall
 p-value significance of their respective Theil-Sen slope. References for
 the statistical analysis of trends can be found here: Kendall, M. G.
 (1975). Rank Correlation Methods. Griffin, London, UK. Mann, H. B. (1945).
 Nonparametric Tests Against Trend. Econometrica, 13(3), 245–259.
 https://doi.org/10.2307/1907187 Sen, P. K. (1968). Estimates of the
 Regression Coefficient Based on Kendall’s Tau. Journal of the American
 Statistical Association, 63(324), 1379–1389.
 https://doi.org/10.1080/01621459.1968.10480934
 https://docs.scipy.org/doc/scipy-0.15.1/reference/generated/scipy.stats.mstats.theilslopes.html https://docs.scipy.org/doc/scipy-0.15.1/reference/generated/scipy.stats.kendalltau.html For the NDVI trend maps, the red colors indicate areas where NDVI trends are decreasing, whereas blue colors indicate areas where NDVI trends are increasing. Yellow/ tan colors indicate areas with little to no NDVI trends. For the p-value maps, black indicates that the NDVI trend is significant at the 0.1 level, and white indicates that the NDVI trend is not significant at the 0.1 level. The "pumping_inventory" folder contains the following files: 1) one excel file (InyoValleyPumpingRunoffAnnual_Laws_only.xlsx) that contains the groundwater pumping data (in units of acre-feet) for the Laws area that was obtained from the Inyo County Water Department (ICWD; https://www.inyowater.org/maps-data/hydrology/runoff-pumping/) and 2) another excel file (FishLakeValley_pumping_inv_summary.xlsx) that contains the groundwater pumping data (in units of acre-feet) for the Nevada portion of Fish Lake Valley that were obtained from the Nevada Department of Water Resources (NDWR, https://water.nv.gov/). The "site_data" folder contains 1 sub-folder: field_survey_data Within the "field_survey_data" subfolder are ground_photograph_locations (e.g. FS_transect_photograph_locations_nad83z11.shp), corresponding ground_photographs (feature attributes in locations shapefile match file names for photographs) taken at the field transects, and corresponding observation forms (scanned pdfs). The "surface_water_data" folder contains the following files: 1) one excel file (Fish_Slough_surface_water_discharge_data.xlsx) that contains the streamflow/discharge measurements (in units of acre-feet) at gauges located within Fish Slough and 2) one shapefile (FishSlough_surface_water_gauge_locs.shp) that contains the locations of the four gauges shown in the discharge measurments excel file. The "zonal_stats_aois" sub-folder contains aoi sub-folders, each containing three excel files and numerous figures summarizing zonal statistics computed for the AOIs. Along with the statistics folders there is a shapefile (e.g. FishSlough_veg_response_polygons_UTM11NWGS84.shp) that was used during the zonal statistics computations. The first excel file (aoi name followed by \_gridmet_daily.csv) contains spatially averaged daily summaries of gridMET variables for AOIs: Precipitation in millimeters (PPT), ASCE Grass Reference Evapotranspiration in millimeters (ETO), Minimum Temperature in kelvin (TMIN), Maximum Temperature in kelvin (TMAX), and Mean Temperature in kelvin (TMEAN). The second excel file (aoi name followed by \_gridmet_monthly.csv) contains spatially averaged monthly summaries of the gridMET variables for AOIs as above. The third excel file (aoi name followed by \_landsat_daily.csv) contains spatially averaged Landsat derived variables. The columns in this file include the site name (ZONE_NAME), unique feature ID (ZONE_FID), image acquisition date (DATE), unique Landsat scene ID (SCENE_ID), satellite platform (PLATFORM), satellite path (PATH), satellite row (ROW), year (YEAR), month (MONTH), day of month (DAY), day of year (DOY), area of input feature in acres (AREA), pixel size (PIXEL_SIZE), the  total number of pixels that were used in the computation (PIXEL_COUNT), the total number of pixel that could theoretically be used in the computation (PIXEL_TOTAL), the amount of masked pixels (FMASK_COUNT), the total number of pixels that could theoretically be masked (FMASK_TOTAL), the percentage of masked pixels (FMASK_PCT), a simple cloud score value (CLOUD_SCORE, percentage), the QA number if applied (QA), surface albedo (ALBEDO_SUR, dimensionless), the enhanced vegetation index (EVI_SUR, dimensionless), the normalized difference vegetation index (NDVI_SUR, dimensionless), the land surface temperature (TS, kelvin), the modified soil-adjusted vegetation index (MSAVI_SUR, dimensionless), the normalized difference water index using the green and near-infrared bands (NDWI_GREEN_NIR_SUR, dimensionless), the normalized difference water index using the green and shortwave-infrared bands (NDWI_GREEN_SWIR1_SUR, dimensionless), the normalized difference water index using the shortwave-infrared and green bands (NDWI_SWIR1_GREEN_SUR, dimensionless), the normalized difference water index using the near-infrared and shortwave-infrared bands (NDWI_NIR_SWIR1_SUR, dimensionless), the soil-adjusted vegetation index (SAVI_SUR, dimensionless), the blue wavelength band (BLUE_SUR, dimensionless), the green wavelength band(GREEN_SUR, dimensionless), the red wavelength band (RED_SUR, dimensionless), the near-infrared wavelength band (NIR_SUR, dimensionless), the 1st short-wave infrared wavelength band (SWIR1_SUR, dimensionless), and the 2nd short-wave infrared wavelength band (SWIR2_SUR, dimensionless), and an outlier score (OUTLIER_SCORE). The "figures" folder within the "zonal_stats_aois" sub-folder contains summary plots of variables used during zonal statistics. A list of variables are as follows: EVI_SUR - Enhanced Vegetation Index surface reflectance ETO - ASCE Grass Reference Evapotranspiration (millimeters) PPT - Precipitation (millimeters) NDVI_SUR - Normalized Difference Vegetation Index surface reflectance (dimensionless) NDVI_TOA - Normalized Difference Vegetation Index top-of-atmosphere (dimensionless) Albedo - Surface Albedo (dimensionless) NDWI - Normalized Difference Water Index, dimensionless (with associated wavelength bands used to compute the normalized difference) associated wavelength band abbreviations: green = green, red = red, nir = near-infrared, swir1 = short-wave infrared TS - Surface Temperature (kelvin) Along with these summary figures are two comma separated files (*aoi_name*_gridmet_figures.csv, and *aoi_name*_landsat_figures.csv) used to generate the figures. All datasets are derived from either the gridded spatial data of GridMET or Landsat. Additionally, an annual summary excel file (Fish_Slough_veg_response_unit_annual_data_and_summary.xlsx) is provided to show detailed summaries of various trend statistics and annual vegetation index values for the areas of interest described above. The definitions of the variables within the summary file are as follows: ZONE_NAME - Unique name for the area of interest ZONE_FID - Unique feature ID DATE - Date of Landsat Overpass SCENE_ID - Landsat scene ID PLATFORM - Landsat platform PATH - Landsat path ROW - Landsat row YEAR - Year MONTH - Month DAY - Day of month DOY - Day of year PIXEL_COUNT - Number of pixels used to calculate zonal statistics PIXEL_TOTAL - Number of pixels that could theoretically be used for zonal statistics based on intersection with polygon FMASK_COUNT - Number of pixels masked FMASK_TOTAL - Number of pixels that could theoretically be masked ETSTAR_COUNT - Number of pixels meeting the minimum ET* threshold of the NDVI - ET* regression CLOUD_SCORE - Simple cloud score as a percentage QA - Qualtiy assessment flag NDVI_SUR - Average normalized difference vegetation index surface reflectance value (dimensionless) NDVI_TOA - Average normalized difference vegetation index top-of-atmosphere value (dimensionless) NDWI_TOA - Average normalized difference water index top-of-atmosphere value (dimensionless) SAVI_SUR - Average soil-adjusted vegetation index surface reflectance value (dimensionless) ALBEDO_SUR - Average albedo value (dimensionless) TS - Average surface temperature value in kelvin Landsat true color scene image thumbnails are also provided to show the image quality of the Landsat data used to generate figures and tables. The "metadata" sub-folder contains individual Federal Geographic Data Committee (FGDC) standard metadata files for the various datasets described above. The above datasets have been integrated into an ArcGIS Pro Project File within the "FishSlough_arcpro" Project subfolder (FishSlough_arcpro.aprx, version 3.2.1). NOTE: if your version of ArcGIS Pro is older than 3.2.1 then you won't be able to save the Project File after opening it. Additionally, an open-source QGIS file (FishSlough_QGIS.qgz) is provided in the main folder to visualize the same datasets if the user is not licensed to use ESRI's ArcGIS Pro software. ## Sharing/Access information NOTE: This version of the database does not include the high-resolution orthomosaic and NDVI imagery for Fish Slough because of how large the images are. If you require these additional data, please reach out to Blake Minor at DRI ([blake.minor@dri.edu](mailto:blake.minor@dri.edu)). Report: * [http://dx.doi.org/10.13140/RG.2.2.11988.62083](http://...)