Articles | Volume 22, issue 12
Hydrol. Earth Syst. Sci., 22, 6611–6626, 2018
Hydrol. Earth Syst. Sci., 22, 6611–6626, 2018

Research article 21 Dec 2018

Research article | 21 Dec 2018

Developing a drought-monitoring index for the contiguous US using SMAP

Sara Sadri et al.

Related authors

Nonstationarity of low flows and their timing in the eastern United States
S. Sadri, J. Kam, and J. Sheffield
Hydrol. Earth Syst. Sci., 20, 633–649,,, 2016
Short summary

Related subject area

Subject: Engineering Hydrology | Techniques and Approaches: Uncertainty analysis
An uncertainty partition approach for inferring interactive hydrologic risks
Yurui Fan, Kai Huang, Guohe Huang, Yongping Li, and Feng Wang
Hydrol. Earth Syst. Sci., 24, 4601–4624,,, 2020
Predicting discharge capacity of vegetated compound channels: uncertainty and identifiability of one-dimensional process-based models
Adam Kiczko, Kaisa Västilä, Adam Kozioł, Janusz Kubrak, Elżbieta Kubrak, and Marcin Krukowski
Hydrol. Earth Syst. Sci., 24, 4135–4167,,, 2020
Short summary
Uncertainty quantification of floodplain friction in hydrodynamic models
Guilherme Luiz Dalledonne, Rebekka Kopmann, and Thomas Brudy-Zippelius
Hydrol. Earth Syst. Sci., 23, 3373–3385,,, 2019
Short summary
Technical note: Assessment of observation quality for data assimilation in flood models
Joanne A. Waller, Javier García-Pintado, David C. Mason, Sarah L. Dance, and Nancy K. Nichols
Hydrol. Earth Syst. Sci., 22, 3983–3992,,, 2018
Sedimentation monitoring including uncertainty analysis in complex floodplains: a case study in the Mekong Delta
N. V. Manh, B. Merz, and H. Apel
Hydrol. Earth Syst. Sci., 17, 3039–3057,,, 2013

Cited articles

AMS: Drought, available at: (last access: 30 April 2018), 2012. a
Brocca, L., Hasenauer, S., Lacava, T., Melone, F., Moramarco, T., Wagner, W., Dorigo, W., Matgen, P., Martinez-Fernandez, J., Llorens, P., Latron, J., Martin, C., and Bittelli, M.: Soil moisture estimation through ASCAT and AMSR-E sensors: An intercomparison and validation study across Europe, Remote Sens. Environ., 115, 3390–3408,, 2010. a
Cai, X., Pan, M., Chaney, N. W., Colliander, A., Misra, S., Cosh, M. H., Crow, W. T., Jackson, T. J., and Wood, E. F.: Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper-resolution model, Water Resour. Res., 53, 3013–3028, 2017. a
California Dept. of Water Resources: Wells, available at:, last access: 25 April 2018. a
Entekhabi, D., Rodriguez-Iturbe, I., and Castelli, F.: Mutual interaction of soil moisture state and atmospheric processes, J. Hydrol., 184, 3–17, 1996. a
Short summary
Of particular interest to NASA's SMAP-based agricultural applications is a monitoring product that assesses near-surface soil moisture in terms of probability percentiles for dry and wet conditions. However, the short SMAP record length poses a statistical challenge for the meaningful assessment of its indices. This study presents initial insights about using SMAP Level 3 and Level 4 for monitoring drought and pluvial regions with a first application over the contiguous United States (CONUS).