Articles | Volume 16, issue 6
https://doi.org/10.5194/essd-16-2741-2024
https://doi.org/10.5194/essd-16-2741-2024
Data description paper
 | 
13 Jun 2024
Data description paper |  | 13 Jun 2024

LamaH-Ice: LArge-SaMple DAta for Hydrology and Environmental Sciences for Iceland

Hordur Bragi Helgason and Bart Nijssen

Related authors

Ubiquitous increases in flood magnitude in the Columbia River basin under climate change
Laura E. Queen, Philip W. Mote, David E. Rupp, Oriana Chegwidden, and Bart Nijssen
Hydrol. Earth Syst. Sci., 25, 257–272, https://doi.org/10.5194/hess-25-257-2021,https://doi.org/10.5194/hess-25-257-2021, 2021
Short summary
Simulating human impacts on global water resources using VIC-5
Bram Droppers, Wietse H. P. Franssen, Michelle T. H. van Vliet, Bart Nijssen, and Fulco Ludwig
Geosci. Model Dev., 13, 5029–5052, https://doi.org/10.5194/gmd-13-5029-2020,https://doi.org/10.5194/gmd-13-5029-2020, 2020
Short summary
Dual state/rainfall correction via soil moisture assimilation for improved streamflow simulation: evaluation of a large-scale implementation with Soil Moisture Active Passive (SMAP) satellite data
Yixin Mao, Wade T. Crow, and Bart Nijssen
Hydrol. Earth Syst. Sci., 24, 615–631, https://doi.org/10.5194/hess-24-615-2020,https://doi.org/10.5194/hess-24-615-2020, 2020
Short summary
Assessing the impacts of hydrologic and land use alterations on water temperature in the Farmington River basin in Connecticut
John R. Yearsley, Ning Sun, Marisa Baptiste, and Bart Nijssen
Hydrol. Earth Syst. Sci., 23, 4491–4508, https://doi.org/10.5194/hess-23-4491-2019,https://doi.org/10.5194/hess-23-4491-2019, 2019
Short summary
MetSim v2.0.0: A flexible and extensible framework for the estimation and disaggregation of meteorological data
Andrew R. Bennett, Joseph J. Hamman, and Bart Nijssen
Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2019-179,https://doi.org/10.5194/gmd-2019-179, 2019
Preprint withdrawn
Short summary

Related subject area

Domain: ESSD – Land | Subject: Hydrology
High-resolution mapping of monthly industrial water withdrawal in China from 1965 to 2020
Chengcheng Hou, Yan Li, Shan Sang, Xu Zhao, Yanxu Liu, Yinglu Liu, and Fang Zhao
Earth Syst. Sci. Data, 16, 2449–2464, https://doi.org/10.5194/essd-16-2449-2024,https://doi.org/10.5194/essd-16-2449-2024, 2024
Short summary
Evapotranspiration evaluation using three different protocols on a large green roof in the greater Paris area
Pierre-Antoine Versini, Leydy Alejandra Castellanos-Diaz, David Ramier, and Ioulia Tchiguirinskaia
Earth Syst. Sci. Data, 16, 2351–2366, https://doi.org/10.5194/essd-16-2351-2024,https://doi.org/10.5194/essd-16-2351-2024, 2024
Short summary
Simbi: historical hydro-meteorological time series and signatures for 24 catchments in Haiti
Ralph Bathelemy, Pierre Brigode, Vazken Andréassian, Charles Perrin, Vincent Moron, Cédric Gaucherel, Emmanuel Tric, and Dominique Boisson
Earth Syst. Sci. Data, 16, 2073–2098, https://doi.org/10.5194/essd-16-2073-2024,https://doi.org/10.5194/essd-16-2073-2024, 2024
Short summary
CAMELE: Collocation-Analyzed Multi-source Ensembled Land Evapotranspiration Data
Changming Li, Ziwei Liu, Wencong Yang, Zhuoyi Tu, Juntai Han, Sien Li, and Hanbo Yang
Earth Syst. Sci. Data, 16, 1811–1846, https://doi.org/10.5194/essd-16-1811-2024,https://doi.org/10.5194/essd-16-1811-2024, 2024
Short summary
A hydrogeomorphic dataset for characterizing catchment hydrological behavior across the Tibetan Plateau
Yuhan Guo, Hongxing Zheng, Yuting Yang, Yanfang Sang, and Congcong Wen
Earth Syst. Sci. Data, 16, 1651–1665, https://doi.org/10.5194/essd-16-1651-2024,https://doi.org/10.5194/essd-16-1651-2024, 2024
Short summary

Cited articles

Abbas, A., Boithias, L., Pachepsky, Y., Kim, K., Chun, J. A., and Cho, K. H.: AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods, Geosci. Model Dev., 15, 3021–3039, https://doi.org/10.5194/gmd-15-3021-2022, 2022. 
Addor, N., Newman, A. J., Mizukami, N., and Clark, M. P.: The CAMELS data set: catchment attributes and meteorology for large-sample studies, Hydrol. Earth Syst. Sci., 21, 5293–5313, https://doi.org/10.5194/hess-21-5293-2017, 2017. 
Addor, N., Do, H. X., Alvarez-Garreton, C., Coxon, G., Fowler, K., and Mendoza, P. A.: Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges, Hydrolog. Sci. J., 65, 712–725, https://doi.org/10.1080/02626667.2019.1683182, 2020. 
Allen, R. G., Pereira, L. S., Raes, D., and Smith, M.: Crop evapotranspiration – Guidelines for computing crop water requirements – FAO Irrigation and drainage paper no. 56, FAO, Rome, 1998. 
Download
Short summary
LamaH-Ice is a large-sample hydrology (LSH) dataset for Iceland. The dataset includes daily and hourly hydro-meteorological time series, including observed streamflow and basin characteristics, for 107 basins. LamaH-Ice offers most variables that are included in existing LSH datasets and additional information relevant to cold-region hydrology such as annual time series of glacier extent and mass balance. A large majority of the basins in LamaH-Ice are unaffected by human activities.
Altmetrics
Final-revised paper
Preprint