The main objective of FORWARD is to understand and increase the resilience of water resources of agricultural systems and forestry through data mining and modelling in a Big Data setting. Hereto, the project has the following three specific objectives: 1. To develop and implement an extensible and tailorable Big Data approach and framework able to manage and process multivariable information sources (see the Methodology section for a short and preliminary list of sources and variables), data-mining techniques and models at several scales (local, regional, nation and continental). 2. To provide improved model forecasting (daily-monthly-seasonal-long term; and at different spatial scales) and monitoring capabilities of eco-hydrological variables and indicators (see the Methodology section for a preliminary list of indicators) relevant to forestry and agricultural applications by combining different modeling types (data-driven, process based and statistical time series analysis) in a Big Data framework 3. To understand the resilience of forest and agricultural ecosystems in water-limited regions to extreme events, in particular drought, and in the context of climate change. Provide maps of most vulnerable sites to those through combining all available data sources and advanced data mining techniques.More

Main outputs:

• Moyano, M.C.; Garcia, M.; Palacios-Orueta, A.; Tornos, L.; Fisher, J.B.; Fernández, N.; Recuero, L.; Juana, L. 2018. Vegetation Water Use Based on a Thermal and Optical Remote Sensing Model in the Mediterranean Region of Doñana. Remote Sensing. 2018, 10, 1105

• Li Y., Kustas WP., Huang C., Nieto H., Haghighi E., Anderson M., Domingo F., Garcia M., Russell S. 2018. Evaluating Soil Resistance Formulations in Thermal‐Based Two‐Source Energy Balance (TSEB) Model: Implications for Heterogeneous Semiarid and Arid Regions Water Resources Research 55 (2), 1059-1078.

• Wang, S, Ibrom, A, Bauer-Gottwein, P & Garcia, M. 2018. Incorporating diffuse radiation into a light use efficiency and evapotranspiration model: an 11-year study in a high latitude deciduous forest. Agricultural and Forest Meteorology, 248, 479-493.

• Vicente-Serrano, S.M., Azorin-Molina, C., Peña-Gallardo, M., Tomas-Burguera, M., Domínguez-Castro, F., Martín Hernández, N., Beguería, S., El Kenawy, A., Noguera, I., García, M., 2019. A high-resolution spatial assessment of the impacts of drought variability on vegetation activity in Spain from 1981 to 2015. Nat. Hazards Earth Syst.

• Vicente-Serrano, Sergio, Azorin-Molina, Cesar, PeñaGallardo Marina, Miquel Tomas-Burguera, Fernando Domínguez-Castro, Natalia Martín-Hernández, Santiago Beguería, Ahmed El Kenawy, Iván Noguera and M. García. 2020. Impact of interannual drought variability on remote sensing vegetation activity in Spain: a high spatial resolution analysis from 1981 to 2015. International Journal of Remote Sensing, vol. 41, 1709-1740.