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Call :    Water4All Call 2026 on "Sustainable Water Management"
Looking for :    a partner (for my project)
PhD. Alvaro Moreno Martinez
Mr.
alvaro.moreno@uv.es
EspaƱa
Valencia
University of Valencia
Public
Image and Signal Processing group
https://isp.uv.es/
https://www.researchgate.net/profile/Alvaro-Moreno-2?ev=hdr_xprf

a partner (for my project)
Assistant Professor, Image and Signal Processing group (ISP), Univ. of Valencia (Spain). I work on remote sensing and AI/ML to estimate evapotranspiration (ET), latent heat and carbon fluxes from field to global scale.

Co-author of the NASA MODIS ET product (MOD16A2/A3 and gap-filled versions, C6/C6.1). I can port and recalibrate MOD16 at Landsat/Sentinel-2 resolution for Mediterranean, irrigated and semi-arid basins. I also build FLUXCOM-type and physics-aware ML models that upscale eddy-covariance fluxes with uncertainty, running in Google Earth Engine.

Keywords: ET/latent heat (MOD16, Penman-Monteith); hybrid ML flux upscaling (FLUXCOM); multi-sensor data fusion (HISTARFM); Google Earth Engine.

Selected work: MOD16 C6/C6.1 (NASA LP DAAC); kNDVI (Science Advances 2021); HISTARFM (RSE 2020); ML uncertainty in retrieval (RSE 2022); satellite ET models in S. America (WRR 2021); causal inference of carbon and water fluxes (Sci. Rep. 2022); plant traits (Nat. Commun. 2026).

Ongoing: BenchFlux (scale-aware AI flux benchmarks), CARBON-GEM, continental mapping of tree hydraulics.

Offer (Topics 1-2): high-resolution ET monitoring for water accounting, irrigation, drought and NBS impact. Seeking partners with flux sites, hydrological modelling, water authorities or end users, and governance expertise.

Contact: alvaro.moreno@uv.es
Topic 1. Integrated Monitoring and Assessment for Sustainable Water Management
Topic 2. Nature-Based Approaches for Resilient Water Management at Hydrological and Hydrogeological System Scale
Project: Water and carbon trade-offs of nature-based solutions for climate change (Topics 2 and 1).

NBS such as reforestation, agroforestry, cover crops, hedgerows or wetland restoration are judged mostly by carbon, but they also change water use. We will quantify both at 10-30 m resolution (Landsat/Sentinel-2):

Port and recalibrate the NASA MOD16 ET model at high resolution.
Upscale latent heat, ET and CO2 from flux towers with FLUXCOM-type and hybrid physics-aware ML, with uncertainty.
Estimate crop water demand, irrigation use and water use efficiency.
Counterfactual analysis to separate NBS effects from climate and drought.
What-if scenarios for basin water availability.

We bring EO, AI/ML, MOD16, data fusion and Google Earth Engine, and coordinate.

Partners needed:

Flux tower, lysimeter, or sap-flow data near NBS or crop sites
Hydrological or groundwater modeling
Agronomy and irrigation data
End users: basin authorities, irrigation districts, NBS implementers
Socio-economics and governance (desirable)

Flexible about pilots (Mediterranean, temperate, boreal).
evapotranspiration, latent heat flux, mod16, fluxcom, machine learning, nature-based solutions, crop water demand, counterfactual analysis, eddy covariance, landsat/sentinel-2
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