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Long Term Ecological Research (LTER), Jornada Basin Data Catalog

    This dataset links to the Jornada data homepage, which links to 153 individual datasets. Those datasets can then be searched based on Title, Keyword, or Investigator. The Jornada Basin Long Term Ecological Research Program (JRN LTER) has been investigating desertification processes since 1982.

    A dataset of spatiotemporally sampled MODIS Leaf Area Index with corresponding Landsat surface reflectance over the contiguous US

      This dataset was built to assist a machine-learning-based approach for mapping LAI from 30m-resolution Landsat images across the contiguous US (CONUS). The data was derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) Version 6 LAI/FPAR, Landsat Collection 1 surface reflectance, and NLCD Land Cover datasets over 2006 – 2018 using Google Earth Engine.

      Metadata for: Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States

        These research data are associated with the manuscript entitled “Climate-driven prediction of land water storage anomalies: An outlook for water resources monitoring across the conterminous United States” (https://doi.org/10.1016/j.jhydrol.2020.125053). The study focused on the conterminous United States (CONUS) which extends over a region of contrasting climates with an uneven distribution of freshwater resources. Under climate change, an exacerbation of the contrast between dry and wet regions is expected across the CONUS and could drastically affect local ecosystems, agriculture practices, and communities. Hence, efforts to better understand long-term spatial and temporal patterns of freshwater resources are needed to plan and anticipate responses. Since 2002, the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) satellite observations provide estimates of large-scale land water storage changes with an unprecedented accuracy. However, the limited lifetime and observation gaps of the GRACE mission have sparked research interest for GRACE-like data reconstruction. This study developed a predictive modeling approach to quantify monthly land liquid water equivalence thickness anomaly (LWE) using climate variables including total precipitation (PRE), number of wet day (WET), air temperature (TMP), and potential evapotranspiration (PET). The approach builds on the achievements of the GRACE mission by determining LWE footprints using a multivariate regression on principal components model with lag signals. The performance evaluation of the model with a lag signals consideration shows 0.5 ≤ R2 ≤ 0.8 for 41.2% of the CONUS. However, the model’s predictive power is unevenly distributed. The model could be useful for predicting and monitoring freshwater resources anomalies for the locations with high model performances. The processed data used as inputs in the study are here provided including the GIS files of the different maps reported. Data reported in the csv files are 0.5-degree gridded monthly time-series of Land water Equivalence anomalies (USlwe163.csv), Potential evapotranspiration (USpet163.csv), Precipitation (USpre163.csv), above-ground air temperature (UStmp163.csv), and number of wet days (USwet163.csv) for 163 consecutive months over the period 2002 to 2017.

        LTAR Walnut Gulch Experimental Watershed DAP GIS Layers

        NAL Geospatial Catalog
          The USDA-ARS Southwest Watershed Research Center (SWRC) operates the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona as an outdoor laboratory for studying semiarid rangeland hydrologic, ecosystem, climate, and erosion processes.

          Walnut Gulch Experimental Watershed, Lucky Hills (Carbon Dioxide and Water Flux)

            The meteorological data and Bowen ratio energy balance systems (BREB) (Model 023/CO2 Campbell Scientific Inc., Logan, Utah, USA) data are used to calculate carbon dioxide and evapotranspiration (ET) fluxes at Lucky Hills. The stored Bowen ration instrument data from the measurement site were transmitted by radio daily to our research station in Tombstone, AZ.