Articles | Volume 18, issue 3
https://doi.org/10.5194/hess-18-1199-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-18-1199-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Mar 2014
Research article |
| 28 Mar 2014
A physically based approach for the estimation of root-zone soil moisture from surface measurements
S. Manfreda
School of Engineering, University of Basilicata, Potenza, Italy
L. Brocca
Research Institute for Geo-Hydrological Protection (IRPI), National Research Council, Perugia, Italy
T. Moramarco
Research Institute for Geo-Hydrological Protection (IRPI), National Research Council, Perugia, Italy
F. Melone
Research Institute for Geo-Hydrological Protection (IRPI), National Research Council, Perugia, Italy
J. Sheffield
Department of Civil and Environmental Engineering, Princeton University, Princeton, NJ, USA
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M. G. Ziliani, M. U. Altaf, B. Aragon, R. Houborg, T. E. Franz, Y. Lu, J. Sheffield, I. Hoteit, and M. F. McCabe
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We evaluate 63 years of changes in annual streamflow volume across Europe, using a data set of more than 3000 stations, with a special focus on the Mediterranean basin. The results show decreasing (increasing) volumes in the southern (northern) regions. These trends are strongly consistent with the changes in temperature and precipitation.
Robert Ljubičić, Dariia Strelnikova, Matthew T. Perks, Anette Eltner, Salvador Peña-Haro, Alonso Pizarro, Silvano Fortunato Dal Sasso, Ulf Scherling, Pietro Vuono, and Salvatore Manfreda
Hydrol. Earth Syst. Sci., 25, 5105–5132, https://doi.org/10.5194/hess-25-5105-2021, https://doi.org/10.5194/hess-25-5105-2021, 2021
Short summary
Short summary
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed widespread use of image velocimetry techniques in place of more traditional, usually slower, methods during hydrometric campaigns. In order to minimize the velocity estimation errors, one must stabilise the acquired videos. In this research, we compare the performance of different UAS video stabilisation tools and provide guidelines for their use in videos with different flight and ground conditions.
Cited articles
Albergel, C., Rüdiger, C., Pellarin, T., Calvet, J.-C., Fritz, N., Froissard, F., Suquia, D., Petitpa, A., Piguet, B., and Martin, E.: From near-surface to root-zone soil moisture using an exponential filter: an assessment of the method based on in-situ observations and model simulations, Hydrol. Earth Syst. Sci., 12, 1323–1337, https://doi.org/10.5194/hess-12-1323-2008, 2008.
Albergel, C., Dorigo, W., Balsamo, G., Muñoz-Sabater, J., de Rosnay, P., Isaksen, L., Brocca, L., de Jeu, R., and Wagner, W.: Monitoring multi-decadal satellite earth observation of soil moisture products through land surface reanalyses, Remote Sens. Environ., 138, 77–89, https://doi.org/10.1016/j.rse.2013.07.009, 2013.
AMMA: AMMA-CATCH, 2014: Hydrological and meteorological observatory on West Africa, available at: http://www.amma-catch.org, last access: December 2013, 2014.
AMMA Database: AMMA Data User Interface, available at: http://database.amma-international.org/, last access: December 2013, 2014.
Brocca, L., Melone, F., Moramarco, T., Wagner, W., Naeimi, V., Bartalis, Z., and Hasenauer, S.: Improving runoff prediction through the assimilation of the ASCAT soil moisture product, Hydrol. Earth Syst. Sci., 14, 1881–1893, https://doi.org/10.5194/hess-14-1881-2010, 2010.
Brocca, L., Moramarco, T., Melone, F., Wagner, W., Hasenauer, S., and Hahn, S.: Assimilation of surface and root-zone ASCAT soil moisture products into rainfall-runoff modelling, IEEE T. Geosci. Remote, 50, 2542–2555, 2012.
Brooks, R. H. and Corey A. T.: Hydraulic properties of porous media, Hydrol. Pap. 3, Colorado State Univ., Fort Collins, USA, 1964.
Ceballos, A., Scipal, K., Wagner, W., and Mart?nez-Fernandez, J.: Validation of ERS Scatterometer-Derived Soil Moisture Data in the Central Part of the Duero Basin, Spain, Hydrol. Process., 19, 1549–1566, 2005.
Crow, W. T., Kustas, W. P., and Prueger, J. H.: Monitoring root-zone soil moisture through the assimilation of a thermal remote sensing-based soil moisture proxy into a water balance model, Remote Sens. Environ., 112, 1268–1281, 2008.
De Lange, R., Beck, R., Van De Giesen, N., Friesen, J., De Wit, A., and Wagner, W.: Scatterometer-derived soil moisture calibrated for soil texture with a onedimensional water-flow model, IEEE Trans. Geosci. Remote Sens., 46, 4041–4049, https://doi.org/10.1109/TGRS.2008.2000796, 2008.
de Rosnay, P., Gruhier, C., Timouk, F., Baup, F., Mougin, E., Hiernaux, P., Kergoat, L., and LeDantec, V.: Multi-scale soil moisture measurements at the Gourma meso-scale site in Mali, J. Hydrol., 375, 241–252, 2009.
Dorigo, W. A., Wagner, W., Hohensinn, R., Hahn, S., Paulik, C., Xaver, A., Gruber, A., Drusch, M., Mecklenburg, S., van Oevelen, P., Robock, A., and Jackson, T.: The International Soil Moisture Network: a data hosting facility for global in situ soil moisture measurements, Hydrol. Earth Syst. Sci., 15, 1675–1698, https://doi.org/10.5194/hess-15-1675-2011, 2011.
Escorihuela, M., Chanzy, A., Wigneron, J., and Kerr, Y.: Effective soil moisture sampling depth of L-band radiometry: a case study, Remote Sens. Environ., 114, 995–1001, 2010.
Gao, H., Wood, E. F., Jackson, T. J., Drusch, M., and Bindlish, R.: Using TRMM/TMI to Retrieve Surface Soil Moisture over the Southern United States from 1998 to 2002, J. Hydrometeorol., 7, 23–38, 2006.
Green, W. H. and Ampt, G.: Studies of soil physics, part I – the flow of air and water through soils, J. Agr. Sci., 4, 1–24, 1911.
ISMN (International Soil Moisture Network): The ISMN Data Portal, available at: http://ismn.geo.tuwien.ac.at, last access: December 2013, 2014.
Laio, F.: A vertically extended stochastic model of soil moisture in the root zone, Water Resour. Res., 42, W02406, https://doi.org/10.1029/2005WR004502, 2006.
Li, F., Crow, W. T., and Kustas, W. P.: Towards the estimation of root-zone soil moisture via the simultaneous assimilation of thermal and microwave soil moisture retrievals, Adv. Water Resour., 33, 201–214, 2010.
Liang, X., Lettenmaier, D. P., Wood, E. F., and Burges, S. J.: A simple hydrologically based model of land surface water and energy fluxes for GCMs, J. Geophys. Res., 99, 14415–14428, 1994.
Liang, X., Lettenmaier, D. P., and Wood, E. F.: One-dimensional statistical dynamic representation of subgrid spatial variability of precipitation in the two-layer variable infiltration capacity model, J. Geophys. Res., 101, 21403–21422, 1996.
Manfreda, S. and Fiorentino, M.: A stochastic approach for the description of the water balance dynamics in a river basin, Hydrol. Earth Syst. Sci., 12, 1189–1200, https://doi.org/10.5194/hess-12-1189-2008, 2008.
Manfreda, S., McCabe, M., Wood, E. F., Fiorentino, M., and Rodriguez-Iturbe, I.: Spatial Patterns of Soil Moisture from Distributed Modeling, Adv. Water Resour., 30, 2145–2150, 2007.
Manfreda, S., Lacava, T., Onorati, B., Pergola, N., Di Leo, M., Margiotta, M. R., and Tramutoli, V.: On the use of AMSU-based products for the description of soil water content at basin scale, Hydrol. Earth Syst. Sci., 15, 2839–2852, https://doi.org/10.5194/hess-15-2839-2011, 2011.
Matgen, P., Heitz, S., Hasenauer, S., Hissler, C., Brocca, L., Hoffmann, L., Wagner, W., and Savenije, H. H. G.: On the potential of METOP ASCAT-derived soil wetness indices as a new aperture for hydrological monitoring and prediction: a field evaluation over Luxembourg, Hydrol. Process., 26, 2346–2359, 2012a.
Matgen, P., Fenicia, F., Heitz, S., Plaza, D., de Keyser, R., Pauwels, V. R. N., Wagner, W., and Savenije, H.: Can ASCAT-derived soil wetness indices reduce predictive uncertainty in well-gauged areas? A comparison with in situ observed soil moisture in an assimilation application, Advances in Water Resources, 44, 49–65, https://doi.org/10.1016/j.advwatres.2012.03.022, 2012b.
Moran, M. S., Peters-Lidard, C. D., Watts, J. M., and McElroy, S.: Estimating soil moisture at the watershed scale with satellite-based radar and land surface models, Can. J. Remote Sens., 30, 805–826, 2004.
Nied, M., Hundecha, Y., and Merz, B.: Flood-initiating catchment conditions: a spatio-temporal analysis of large-scale soil moisture patterns in the Elbe River basin, Hydrol. Earth Syst. Sci., 17, 1401–1414, https://doi.org/10.5194/hess-17-1401-2013, 2013.
Ochsner, T., Cosh, M., Cuenca, R., Dorigo, W., Draper, C., Hagimoto, Y., Kerr, Y., Larson, K. M., Njoku, E. G., Small, E. E., and Zreda, M.: The state of the art in large-scale soil moisture monitoring, Soil Sci. Soc. Am. J., 77, 1888–1919,https://doi.org/10.2136/sssaj2013.03.0093, 2013.
Pan, F., Peters-Lidard, C. D., and Sale, M. J.: An analytical method for predicting surface soil moisture from rainfall observations, Water Resour. Res., 39, 1314, https://doi.org/10.1029/2003WR002142, 2003.
Pellarin, T., Laurent, J. P., Cappelaere, B., Decharme B., Descroix, L., and Ramier, D.: Hydrological modelling and associated microwave emission of a semi-arid region in South-western Niger, J. Hydrol., 375, 262–272, 2009a.
Pellarin, T., Tran, T., Cohard, J.-M., Galle, S., Laurent, J.-P., de Rosnay, P., and Vischel, T.: Soil moisture mapping over West Africa with a 30-min temporal resolution using AMSR-E observations and a satellite-based rainfall product, Hydrol. Earth Syst. Sci., 13, 1887–1896, https://doi.org/10.5194/hess-13-1887-2009, 2009b.
Porporato, A., Daly, E., and Rodriguez-Iturbe, I.: Soil water balance and ecosystem response to climate change, Am. Nat., 164, 625–632, 2004.
Puma, M. J., Celia, M. A., Rodriguez-Iturbe, I., and Guswa, A. J.: Functional relationship to describe temporal statistics of soil moisture averaged over different depths, Adv. Water Resour., 28, 553–566, 2005.
Ragab, R.: Towards a continuous operational system to estimate the root zone soil moisture from intermittent remotely sensed surface moisture, J. Hydrol., 173, 1–25, 1995.
Rawls, W. J. and Brakensiek D. L.: Estimation of soil water retention and hydraulic properties, in: Unsaturated Flow in Hydrologic Modeling, Kluwer Acad., Dordrecht, Netherlands, 275–300, 1989.
Rawls, W. J., Ahuja, L. R., Brakensiak, D. L., and Shirmohammadi, A.: Infiltration and soil water movement, in: Handbook of Hydrology, edited by: Maidment, D. R., 5.1–5.51, 1993.
Redelsperger, J.-L., Thorncroft, C. D., Diedhiou, A., Lebel, T., Parker, D., and Polcher, J.: African Monsoon Multidisciplinary Analysis: An International Research Project and Field Campaign, B. Am. Meteorol. Soc., 87, 1739–1746, 2006.
Reichle, R., McLaughlin, D., and Entekhabi, D.: Hydrologic data assimilation with the ensemble kalman filter, Mon. Weather Rev., 130, 103–114, 2002.
Reichle, R., Koster, R., Dong, J., and Berg, A.: Global soil moisture from satellite observations, land surface models, and ground data: implications for data assimilation, J. Hydrometeorol., 5, 430–442, 2004.
Rodriguez-Iturbe, I., Isham, V., Cox, D. R., Manfreda, S., and Porporato, A.: Space-time modeling of soil moisture: stochastic rainfall forcing with heterogeneous vegetation, Water Resour. Res., 42, W06D05, https://doi.org/10.1029/2005WR004497, 2006.
Sabater, J. M., Jarlan, L., Calvet, J. C., Bouyssel, F., and De Rosnay, P.: From Near-Surface to Root-Zone Soil Moisture Using Different Assimilation Techniques, J. Hydrometeorol., 8, 194–206, 2007.
Schaefer, G. L., Cosh, M. H., and Jackson, T. J.: The USDA Natural Resources Conservation Service Soil Climate Analysis Network (SCAN), J. Atmos. Ocean. Tech., 24, 2073–2077, 2007.
Scipal, K., Drusch, M., and Wagner, W.: Assimilation of a ERS scatterometer derived soil moisture index in the ECMWF numerical weather prediction system, Adv. Water Resour., 31, 1101–1112, 2008.
Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., and Teuling, A. J.: Investigating soil moisture-climate interactions in a changing climate: A review, Earth-Sci. Rev., 99, 125–161, 2010.
Wagner, W., Lemoine, G., and Rott, H.: A method for estimating soil moisture from ERS scatterometer and soil data, Remote Sens. Environ., 70, 191–207, 1999.
Walker, J. P. and Houser, P. R.: Requirements of a global near-surface soil moisture satellite mission: accuracy, repeat time, and spatial resolution, Adv. Water Resour., 27, 785–801, 2004.
Wood, E. F., Lettenmaier, D. P., Liang, X., Nijssen, B., and Wetzel, S. W.: Hydrological modeling of continental-scale basins, Annu. Rev. Earth Pl. Sc., 25, 279–300, 1997.
Ye, M., Meyer, P. D., and Neuman S. P.: On model selection criteria in multimodel analysis, Water Resour. Res., 44, W03428, https://doi.org/10.1029/2008WR006803, 2008.
