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Improved water resource management through remote sensing: methods to quantify irrigation water use
Regional data sets of high-resolution (1 and 6 km) irrigation estimates from space
- Dari, Jacopo, Brocca, Luca, Quintana-Seguí, Pere, Bretreger, David, Volden, Espen, Modanesi, Sara, Massari, Christian, Tarpanelli, Angelica, Barbetta, Silvia, Quast, Raphael, Vreugdenhil, Mariette, Freeman, Vahid, Barella-Ortiz, Anaïs
- Bretreger, David, Yeo, In-Young, Hancock, Greg
- Kumari, Nikul, Srivastava, Ankur, Sahoo, Bhabagrahi, Raghuwanshi, Narendra Singh, Bretreger, David
- Bretreger, David, Yeo, In-Young, Kuczera, George, Hancock, Greg
- Bretreger, David, Yeo, In-Young, Melchers, Robert
LiDAR derived terrain wetness indices to infer soil moisture above underground pipelines
- Bretreger, David, Yeo, In-Young, Melchers, Robert
- Bretreger, David, Yeo, In-Young, Hancock, Greg, Willgoose, Garry
Comparing remote sensing and tabulated crop coefficients to assess irrigation water use
- Bretreger, David, Warner, Alexander, Yeo, In-Young
Monitoring irrigation water use over paddock scales using climate data and landsat observations
- Bretreger, David, Yeo, In-Young, Quijano, Juan, Awad, John, Hancock, Greg, Willgoose, Gary
The effects of SILO & AWRA wind speeds on irrigation depth simulations
- Bretreger, David, Yeo, In-Young
Monitoring irrigation volumes using climate data and remote sensing observations
- Bretreger, David, Quijano, Juan, Awad, John
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