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    The STARFM algorithm uses comparisons of one or more pairs of observed Landsat/MODIS maps, collected on the same day, to predict maps at Landsat-scale on other MODIS observation dates. STARFM was initially developed at the NASA Goddard Space Flight Center by Dr. Feng Gao. This version (v1.2) has been greatly improved in computing efficiency (e.g. one run for multiple dates and parallel computing) for large-area processing (Gao et al., 2015). Additional improvements (e.g. Landsat and MODIS images co-registration, daily MODIS nadir BRDF-adjusted reflectance) in the operational data fusion system (Wang et al., 2014) are beyond the STARFM program and are not included in this package. Improvement and continuous maintenance are being undertaken in the USDA-ARS Hydrology and Remote Sensing Laboratory (HRSL), Beltsville, MD by Dr. Feng Gao.

    The Ogallala Agro-Climate Tool

      The Ogallala Agro-Climate Tool is a Visual Basic application that estimates irrigation demand and crop water use over the Ogallala Aquifer region.

      USDA-ARS Colorado Maize Water Productivity Dataset 2012-2013

        The USDA-Agricultural Research Service carried out an experiment on water productivity in response to seasonal timing of irrigation of maize (*Zea mays* L.) at the Limited Irrigation Research Farm (LIRF) facility in northeastern Colorado (40°26’ N, 104°38’ W) starting in 2012. Twelve treatments involved different water availability targeted at specific growth-stages. This dataset includes data from the first two years, which were complete years with intact treatments. Data includes canopy growth and development (canopy height, canopy cover and LAI), irrigation, precipitation, and soil water storage measured periodically through the season; daily estimates of crop evapotranspiration; and seasonal measurement of crop water use, harvest index and crop yield. Hourly and daily weather data are also provided from the CoAgMET, Colorado’s network of meteorological information.

        Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) Simulation Model

          The Agricultural Land Management Alternative with Numerical Assessment Criteria (ALMANAC) model simulates crop growth, competition, light interception by leaves, biomass accumulation, partitioning of biomass into grain, water use, nutrient uptake, and growth constraints such as water, temperature, and nutrient stress. Plant development is temperature driven, with duration of growth stages dependent on degree days. Each plant species has a defined base temperature and optimum temperature.

          Water Resources of the United States

            Water is one of six science mission areas of the U.S. Geological Survey (USGS). Water's mission is to collect and disseminate reliable, impartial, and timely information that is needed to understand the Nation's water resources. This database contains downloadable water-related spatial data files for exploration and analysis.

            NRCS Regional Conservation Partnership Program - Colorado River Basin

              Irrigated agriculture is vitally important to the economy and quality of life in many areas of the Colorado River Basin. It also accounts for a significant share of the basin’s existing water use, shared among 33 million people in the United States plus 3 million in Mexico. Faced with historic drought conditions and water supply pressures, farmers, ranchers, Indian tribes and other water users are in urgent need of accelerated conservation on working agricultural lands. This dataset includes a printer-friendly CCA map and shapefiles for GIS.