| Abstract: |
In this paper, the soil moisture content (SMC) estimated from the synergic use of both active and passive microwave acquisitions was compared with the outputs of a hydrological model. The data used in the algorithm for the estimate of SMC are those of the Advanced Microwave Scanning Radiometer 2 (AMSR2) and the Soil Moisture Active and Passive (SMAP) satellite sensors. The algorithm takes advantage of the integration of microwave data at different frequencies from SMAP and AMSR2 for realizing a SMC product at enhanced resolution (10 km) and improved accuracy with respect to the original SMAP radiometric SMC product due to the correction of vegetation effect obtained at higher frequencies.
The ANN based “HydroAlgo” algorithm [1], originally developed for AMSR-E, was adapted and re-trained for working with AMSR2 data in combination with SMAP. The disaggregation technique implemented in HydroAlgo [2], devoted to the improvement of ground resolution, made this algorithm particularly suitable for the application to such a heterogeneous environment as the Italian landscape. The reference SMC was generated by using the soil water balance model (SWBM) [3], which is a well assessed hydrological model that was found to perform very well in the reproduction of observed soil moisture data in the study area.
The algorithm has been defined and tested using experimental datasets and RT model simulations and then validated using consistent time series of SMAP and AMSR2 co-located data in Central Italy. Spatially distributed SMC values at 10 km resolution generated by the Soil Water Balance Model (SWBM) are considered as a reference for validation. The synergy between SMAP and AMSR2 data allowed increasing the correlation between estimated and reference SMC from R 0.68 of the SMAP based retrieval algorithm up to R > 0.75. The corresponding error decreased from RMSE 0.04 m3/m3 to RMSE 0.03 m3/m3 in both ascending and descending orbits.
Then, the SMC generated by HydroAlgo using AMSR2 and SMAP data was assimilated into the MISDc rainfall-runoff model (‘Modello Idrologico Semi-Distribuito in continuo’ [4]) over some basins in the Upper Tiber River basin in Central Italy. The assimilation of coarser resolution SMAP (36 km) and AMSR2 (25 km) soil moisture original products was performed as well, in order to show the beneficial impact of using high resolution information for hydrological applications. The added-value is assessed in terms of the improvements obtained for simulating flood events. Results highlight the potential of the SMC generated by HydroAlgo for operational hydrological applications at regional scale, and particularly in heterogeneous environments as the Italian territory.
REFERENCES.
[1] Santi E., S. Pettinato, S. Paloscia, P. Pampaloni, G. Macelloni, and M. Brogioni (2012), “An algorithm for generating soil moisture and snow depth maps from microwave spaceborne radiometers: HydroAlgo”, Hydrology and Earth System Sciences, 16, pp. 3659-3676, doi:10.5194/hess-16-3659-2012.
[2] Santi E. (2010), “An application of SFIM technique to enhance the spatial resolution of microwave radiometers”, Intern. J. Remote Sens., vol. 31, 9, pp. 2419-2428.
[3] Brocca, L.; Melone, F.; Moramarco, T. On the estimation of antecedent wetness conditions in rainfall–runoff modelling. Hydrol. Process. 2008, 642, 629–642.
[4] Masseroni, D., Cislaghi, A., Camici, S., Massari, C., Brocca, L. (2017). A reliable rainfall-runoff model for flood forecasting: review and application to a semiurbanized watershed at high flood risk in Italy. Hydrology Research, 48(3), 726-740, doi:10.2166/nh.2016.037. http://dx.doi.org/10.2166/nh.2016.037. |
