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M. H. J. van Huijgevoort, P. Hazenberg, H. A. J. van Lanen, A. J. Teuling, D. B. Clark, S. Folwell, S. N. Gosling, N. Hanasaki, J. Heinke, S. Koirala, T. Stacke, F. Voss, J. Sheffield, and R. Uijlenhoet

cells in total) were considered by the models. Model forcing was provided by the WATCH forcing data (WFD) developed by Weedon et al. (2011) . The WFD consist of gridded time series of meteorological variables (e.g., rainfall, snowfall, temperature, and wind speed) both on a subdaily and daily basis for 1958–2001 with a resolution of 0.5° × 0.5°. The WFD originate from modification (bias correction and downscaling) of the 40-yr European Centre for Medium-Range Weather Forecasts (ECMWF) Re

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Eli J. Dennis and Ernesto Hugo Berbery

use of a soil texture map paired with a lookup table is a practical solution for enabling large-scale land surface modeling and a standard practice at operational forecast centers either coupled or uncoupled. The lookup table is an important constraint since it assumes a uniform hydraulic behavior for each soil category anywhere in the world. In recent years, the soil sciences community has been working intensely to advance the development of pedotransfer functions (PTFs) that should improve

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Rolf H. Reichle, Qing Liu, Joseph V. Ardizzone, Wade T. Crow, Gabrielle J. M. De Lannoy, Jianzhi Dong, John S. Kimball, and Randal D. Koster

fields, including surface (0–5 cm) and root-zone (0–100 cm) soil moisture, soil temperature, and surface fluxes. The L4_SM product also provides important data assimilation diagnostics, including the assimilated Tb observations and corresponding model forecasts. Here, we use 3-hourly instantaneous surface and root-zone soil moisture and brightness temperature from the L4_SM “analysis-update” files ( Reichle et al. 2018a ). We further use 3-hourly time-average total runoff data (including surface

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Zhe Zhang, Youcun Qi, Donghuan Li, Ziwei Zhu, Meilin Yang, Nan Wang, Yin Yang, and Qiyuan Hu

QPE. Furthermore, hydrological disasters such as flood, debris flow, and urban waterlogging are usually attributed to the heavy precipitation caused by strong convection. Therefore, accurately identifying convective precipitation is practically helpful for hydrological forecasting. Previous studies have proposed different algorithms to discriminate convective and stratiform precipitation. Steiner et al. (1995 , hereafter SHY95) proposed a convection and stratiform separation algorithm by

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Ning Zhang, Steven M. Quiring, and Trent W. Ford

, the longer latency is problematic for applications requiring more rapid updates, including flash flood forecasting and field condition monitoring for agriculture. In addition, soil moisture products based entirely on remote sensing observations do not represent soil moisture conditions in the primary root zone. Although we do not examine root zone soil moisture in this study, the methods are easily applicable for blending root zone soil moisture from in situ and model sources. Last, many blended

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Martin G. De Kauwe, Christopher M. Taylor, Philip P. Harris, Graham P. Weedon, and Richard. J. Ellis

failure or screening for pixel contamination by cloud and/or dust. One solution might be to gap-fill the time series using an interpolation technique; however, this can result in bias because of the suppression of high-frequency components ( Schulz and Mudelsee 2002 ). Alternatively, a model may be used to estimate missing data points, using a sequential filtering algorithm such as a Kalman filter to update model forecasts when observations are available. However, this solution requires the necessary

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Wenyi Xie, Xiankui Zeng, Dongwei Gui, Jichun Wu, and Dong Wang

(MODFLOW-2005). USGS Techniques and Methods 6-D1, 240 pp., https://pubs.usgs.gov/tm/tm6d1/ . 10.3133/tm6D1 Marsh , P. , 1999 : Snowcover formation and melt: Recent advances and future prospects . Hydrol. Processes , 13 , 2117 – 2134 , https://doi.org/10.1002/(SICI)1099-1085(199910)13:14/15<2117::AID-HYP869>3.0.CO;2-9 . 10.1002/(SICI)1099-1085(199910)13:14/15<2117::AID-HYP869>3.0.CO;2-9 Martinec , J. , 1975 : Snowmelt runoff model for stream flow forecasts . Hydrol. Res. , 6 , 145 – 154

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James Cleverly, Chao Chen, Nicolas Boulain, Randol Villalobos-Vega, Ralph Faux, Nicole Grant, Qiang Yu, and Derek Eamus

partitioning ET into soil and plant components for olive orchards in a semi-arid region . Agric. Water Manage. , 97 , 1769 – 1778 , doi:10.1016/j.agwat.2010.06.009 . Hutley, L. B. , Leuning R. , Beringer J. , and Cleugh H. A. , 2005 : The utility of the eddy covariance techniques as a tool in carbon accounting: Tropical savanna as a case study . Aust. J. Bot. , 53 , 663 – 675 , doi:10.1071/BT04147 . Isaac, P. R. , Leuning R. , Hacker J. M. , Cleugh H. A. , Coppin P. A. , Denmead

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Maxime Turko, Marielle Gosset, Modeste Kacou, Christophe Bouvier, Nanee Chahinian, Aaron Boone, and Matias Alcoba

1. Introduction During the last 10 years, rainfall measurement from commercial microwave link (CML) network has gradually emerged as a useful complement to traditional rainfall measurement based on gauges, weather radar or satellites. Uijlenhoet et al. (2018) and Chwala and Kunstmann (2019) provide a good review of the state of the art and the research developed since the pioneering work of Messer et al. (2006) and Leijnse et al. (2007b) . The CML technique is based on the analysis of

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Pravat Jena, Sourabh Garg, and Sarita Azad

subsequently brings forth the importance of the evaluation of gridded data. Further, satellite estimates are currently being used as an alternate source of data for monitoring and validation purposes since they are available at high spatiotemporal scales as models ( Dinku et al. 2014 ). Some of these products are, Climate Prediction Center Morphing technique (CMORPH), Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR), Tropical

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