Daily evapotranspiration (ET) is modeled globally for the period 2000-2013 based on the Penman-Monteith equation with radiation and vapor pressures derived using remotely sensed Land Surface Temperature (LST) from the MODerate resolution Imaging Spectroradiometer (MODIS) on the Aqua and Terra satellites. The ET for a given land area is based on four surface conditions: wet/dry and vegetated/non-vegetated. For each, the ET resistance terms are based on land cover, leaf area index (LAI) and literature values. The vegetated/non-vegetated fractions of the land surface are estimated using land cover, LAI, a simplified version of the Beer-Lambert law for describing light transition through vegetation and newly derived light extension coefficients for each MODIS land cover type. The wet/dry fractions of the land surface are nonlinear functions of LST derived humidity calibrated using in-situ ET measurements. Results are compared to in-situ measurements (average of the root mean squared errors and mean absolute errors for 39 sites are 0.81 mm day −1 and 0.59 mm day −1 , respectively) and the MODIS ET product, MOD16, (mean bias during 2001-2013 is −0.2 mm day −1 ). Although the mean global difference between MOD16 and ET estimates is only 0.2 mm day −1 , local temperature derived vapor pressures are the likely contributor to differences, especially in energy and water limited regions. The intended application for the presented model is simulating ET based on long-term climate forecasts (e.g., using only minimum, maximum and mean daily or monthly temperatures).

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Climate-driven alterations of hydro-meteorological conditions can change river flow regimes and potentially affect the migration behaviour of fishes and the productivity of important fisheries in the Amazon basin, such as those for the continental-scale migratory goliath catfishes (Brachyplatystoma, Pimelodidae). In this study, we investigated hydrologic responses to climate change using a hydrologic model forced with climate inputs, which integrate historical (2001-2010) observations and general circulation model (GCM) projections under the emission scenario Representative Concentration Pathway 8.5. We developed an empirical model to characterize future (2090-2099) climate-change impacts on goliath catfish spawning migrations as a function of river flow depth dynamics at the upstream elevational limit of spawning (250 m) in headwater basins of the Amazon. The model results revealed spatially variable impacts of climate change on the catfish spawning migrations. The Marañón, Ucayali, Juruá, Purus, and Madeira basins had a predicted increase in the annual mean (3-8%) and maximum (1.1-4.9%) spawning migration rate (i.e., the fraction of fish that migrate to the spawning grounds in a day), mainly due to the lengthened rising phase of flow-driven migratory events during wet seasons. The Caquetá-Japurá, Putumayo-Içá, Napo, and Blanco rivers had predicted decreases (3-7%) in the mean migration rate because of decreases in the length of the rising season of flow depth and the frequency of migratory events. The predicted timing of fish spawning migrations (quantified by the temporal centroid of migration rates) was delayed by

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