In: Journal of Hydrology and Hydromechanics, vol. 63, no. 3
Luca Brocca - Christian Massari - Luca Ciabatta - Tommaso Moramarco - Daniele Penna - Giulia Zuecco - Luisa Pianezzola - Marco Borga - Patrick Matgen - José Martínez-Fernández
Detaily:
Rok, strany: 2015, 201 - 209
Kľúčové slová:
Rainfall; Soil moisture; In situ observations; Experimental sites; SM2RAIN.
URL originálneho zdroja: http://www.ih.savba.sk/jhh
O článku:
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.
Ako citovať:
ISO 690:
Brocca, L., Massari, C., Ciabatta, L., Moramarco, T., Penna, D., Zuecco, G., Pianezzola, L., Borga, M., Matgen, P., Martínez-Fernández, J. 2015. Rainfall estimation from in situ soil moisture observations at several sites in
Europe: an evaluation of the SM2RAIN algorithm. In Journal of Hydrology and Hydromechanics, vol. 63, no.3, pp. 201-209. 0042-790X (until 2019) .
APA:
Brocca, L., Massari, C., Ciabatta, L., Moramarco, T., Penna, D., Zuecco, G., Pianezzola, L., Borga, M., Matgen, P., Martínez-Fernández, J. (2015). Rainfall estimation from in situ soil moisture observations at several sites in
Europe: an evaluation of the SM2RAIN algorithm. Journal of Hydrology and Hydromechanics, 63(3), 201-209. 0042-790X (until 2019) .