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Journal of Hydrology and Hydromechanics

The Journal of Institute of Hydrology SAS Bratislava and Institute of Hydrodynamics CAS Prague

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IMPACT FACTOR 2015: 1.469
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0042-790X
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Rainfall estimation from in situ soil moisture observations at several sites in Europe: an evaluation of the SM2RAIN algorithm

Luca Brocca
  • Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Via Madonna Alta 126, 06128 Perugia, Italy
  • :
/ Christian Massari
  • Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Via Madonna Alta 126, 06128 Perugia, Italy
/ Luca Ciabatta
  • Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Via Madonna Alta 126, 06128 Perugia, Italy
/ Tommaso Moramarco
  • Research Institute for Geo-Hydrological Protection, National Research Council, Perugia, Via Madonna Alta 126, 06128 Perugia, Italy
/ Daniele Penna
  • Faculty of Science and Technology, Free University of Bozen-Bolzano, Piazza dell'Università 5, Bolzano, Italy
/ Giulia Zuecco
  • Department of Land and Agroforest Environments, University of Padova, Via dell'Università 16, Legnaro, Italy
/ Luisa Pianezzola
  • Department of Land and Agroforest Environments, University of Padova, Via dell'Università 16, Legnaro, Italy
/ Marco Borga
  • Department of Land and Agroforest Environments, University of Padova, Via dell'Università 16, Legnaro, Italy
/ Patrick Matgen
  • Luxembourg Institute of Science and Technology (LIST), ERIN, Avenue Des Hauts-Fourneaux 5, Esch-Sur-Alzette, Luxembourg
/ José Martínez-Fernández
  • Centro Hispano Luso de Investigaciones Agrarias, USAL, Calle del Duero 12, Villamayor, Spain
Published Online: 2015-06-25 | DOI: https://doi.org/10.1515/johh-2015-0016

Abstract

Rain gauges, weather radars, satellite sensors and modelled data from weather centres are used operationally for estimating the spatial-temporal variability of rainfall. However, the associated uncertainties can be very high, especially in poorly equipped regions of the world. Very recently, an innovative method, named SM2RAIN, that uses soil moisture observations to infer rainfall, has been proposed by Brocca et al. (2013) with very promising results when applied with in situ and satellite-derived data. However, a thorough analysis of the physical consistency of the SM2RAIN algorithm has not been carried out yet. In this study, synthetic soil moisture data generated from a physically-based soil water balance model are employed to check the reliability of the assumptions made in the SM2RAIN algorithm. Next, high quality and multiyear in situ soil moisture observations, at different depths (5-30 cm), and rainfall for ten sites across Europe are used for testing the performance of the algorithm, its limitations and applicability range.

SM2RAIN shows very high accuracy in the synthetic experiments with a correlation coefficient, R, between synthetically generated and simulated data, at daily time step, higher than 0.940 and an average Bias lower than 4%. When real datasets are used, the agreement between observed and simulated daily rainfall is slightly lower with average R-values equal to 0.87 and 0.85 in the calibration and validation periods, respectively. Overall, the performance is found to be better in humid temperate climates and for sensors installed vertically. Interestingly, algorithms of different complexity in the reproduction of the underlying hydrological processes provide similar results. The average contribution of surface runoff and evapotranspiration components amounts to less than 4% of the total rainfall, while the soil moisture variations (63%) and subsurface drainage (30%) terms provide a much higher contribution. Overall, the SM2RAIN algorithm is found to perform well both in the synthetic and real data experiments, thus offering a new and independent source of data for improving rainfall estimation, and consequently enhancing hydrological, meteorological and climatic studies.

Keywords : Rainfall; Soil moisture; In situ observations; Experimental sites; SM2RAIN.

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Received: 2014-11-08

Accepted: 2015-01-13

Published Online: 2015-06-25

Published in Print: 2015-09-01


Citation Information: Journal of Hydrology and Hydromechanics. Volume 63, Issue 3, Pages 201–209, ISSN (Online) 0042-790X, DOI: https://doi.org/10.1515/johh-2015-0016, June 2015

© 2015. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. (CC BY-NC-ND 3.0)

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