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).

Report:

• http://dx.doi.org/10.13140/RG.2.2.11988.62083