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Romaguera, Mireia, Krol, Maarten, Salama, Mhd., Su, Zhongbo, Hoekstra, Arjen (2014) Application of a Remote Sensing Method for Estimating Monthly Blue Water Evapotranspiration in Irrigated Agriculture. Remote Sensing, 6 (10). doi:10.3390/rs61010033

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Reference TypeJournal (article/letter/editorial)
TitleApplication of a Remote Sensing Method for Estimating Monthly Blue Water Evapotranspiration in Irrigated Agriculture
JournalRemote Sensing
AuthorsRomaguera, MireiaAuthor
Krol, MaartenAuthor
Salama, Mhd.Author
Su, ZhongboAuthor
Hoekstra, ArjenAuthor
Year2014 (October 21)Volume6
Issue10
PublisherMDPI AG
DOIdoi:10.3390/rs61010033Search in ResearchGate
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Mindat Ref. ID17804917Long-form Identifiermindat:1:5:17804917:1
GUID0
Full ReferenceRomaguera, Mireia, Krol, Maarten, Salama, Mhd., Su, Zhongbo, Hoekstra, Arjen (2014) Application of a Remote Sensing Method for Estimating Monthly Blue Water Evapotranspiration in Irrigated Agriculture. Remote Sensing, 6 (10). doi:10.3390/rs61010033
Plain TextRomaguera, Mireia, Krol, Maarten, Salama, Mhd., Su, Zhongbo, Hoekstra, Arjen (2014) Application of a Remote Sensing Method for Estimating Monthly Blue Water Evapotranspiration in Irrigated Agriculture. Remote Sensing, 6 (10). doi:10.3390/rs61010033
In(2014, October) Remote Sensing Vol. 6 (10). MDPI AG

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Romaguera, Mireia, Salama, Mhd., Krol, Maarten, Hoekstra, Arjen, Su, Zhongbo (2014) Towards the Improvement of Blue Water Evapotranspiration Estimates by Combining Remote Sensing and Model Simulation. Remote Sensing, 6 (8). doi:10.3390/rs6087026
Romaguera, Mireia, Hoekstra, Arjen Y., Su, Zhongbo, Krol, Maarten S., Salama, Mhd. Suhyb (2010) Potential of Using Remote Sensing Techniques for Global Assessment of Water Footprint of Crops. Remote Sensing, 2 (4). doi:10.3390/rs2041177
Huang, Ying, Salama, Mhd. Suhyb, Krol, Maarten S., Su, Zhongbo, Hoekstra, Arjen Y., Zeng, Yijian, Zhou, Yunxuan (2015) Estimation of human‐induced changes in terrestrial water storage through integration of GRACE satellite detection and hydrological modeling: A case study of the Y angtze R iver basin. Water Resources Research, 51 (10). 8494-8516 doi:10.1002/2015wr016923
Yuan, Xu, Salama, Mhd., Su, Zhongbo (2018) An Observational Perspective of Sea Surface Salinity in the Southwestern Indian Ocean and Its Role in the South Asia Summer Monsoon. Remote Sensing, 10 (12). doi:10.3390/rs10121930
Poon, Patrick, Kinoshita, Alicia (2018) Estimating Evapotranspiration in a Post-Fire Environment Using Remote Sensing and Machine Learning. Remote Sensing, 10 (11). doi:10.3390/rs10111728
Shen, Fang, Suhyb Salama, MHD., Zhou, Yun-Xuan, Li, Jiu-Fa, Su, Zhongbo, Kuang, Ding-Bo (2010) Remote-sensing reflectance characteristics of highly turbid estuarine waters – a comparative experiment of the Yangtze River and the Yellow River. International Journal of Remote Sensing, 31 (10). doi:10.1080/01431160903085610
Salama, Mhd. Suhyb, Verhoef, Wouter (2015) Two-stream remote sensing model for water quality mapping: 2SeaColor. Remote Sensing of Environment, 157. 111-122 doi:10.1016/j.rse.2014.07.022
Chukalla, Abebe D., Krol, Maarten S., Hoekstra, Arjen Y. (2017) Marginal cost curves for water footprint reduction in irrigated agriculture: guiding a cost-effective reduction of crop water consumption to a permit or benchmark level. Hydrology and Earth System Sciences, 21 (7) 3507-3524 doi:10.5194/hess-21-3507-2017
Ozdogan, Mutlu, Yang, Yang, Allez, George, Cervantes, Chelsea (2010) Remote Sensing of Irrigated Agriculture: Opportunities and Challenges. Remote Sensing, 2 (9). doi:10.3390/rs2092274
Zhong, Lei, Ma, Yaoming, Fu, Yunfei, Pan, Xiao, Hu, Wei, Su, Zhongbo, Salama, Mhd. Suhyb, Feng, Lu (2014) Assessment of soil water deficit for the middle reaches of Yarlung-Zangbo River from optical and passive microwave images. Remote Sensing of Environment, 142. 1-8 doi:10.1016/j.rse.2013.11.008
Arabi, Behnaz, Salama, Mhd., Wernand, Marcel, Verhoef, Wouter (2016) MOD2SEA: A Coupled Atmosphere-Hydro-Optical Model for the Retrieval of Chlorophyll-a from Remote Sensing Observations in Complex Turbid Waters. Remote Sensing, 8 (9). doi:10.3390/rs8090722
 
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