Consistent validation of H-SAF soil moisture satellite and model products against ground measurements for selected sites in Europe (original) (raw)
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Validation of remote sensing soil moisture products with a distributed continuous hydrological model
2014 IEEE Geoscience and Remote Sensing Symposium, 2014
The reliable estimation of soil moisture in space and time is of fundamental importance in operational hydrology to improve the forecast of the rainfall-runoff response of catchments and, consequently, flood predictions. Nowadays several satellite-derived soil moisture products are available and can offer a chance to improve hydrological model performances especially in environments with scarce ground based data. The goal of this work is to test the effects of the assimilation of different satellite soil moisture products in a distributed physically based hydrological model. Among the currently available different satellite platforms, four soil moisture products, from both the ASCAT scatterometer and the SMOS radiometer, have been assimilated using a Nudging scheme. The model has been applied to a test basin (area about 800 km 2) located in Northern Italy for the period July 2012-June 2013.
2016
Soil moisture content is a key variable for numerous disciplines hence the need for its constant monitoring at a global scale. Satellite imagery is the only mean to fulfil this objective. New generations of satellite sensors such as the Sentinel-1 SAR (Synthetic Aperture Radar) system provide measurements at fine spatial and temporal scales. In order to validate such estimates dense in-situ networks measuring soil moisture are required. The scarcity of such networks was the main motivation to establish two validation sites over the Biebrza wetlands within the project funded by the ESA (European Space Agency). The sites are covered by grassland and marshland and are internally homogeneous as far as the soil type and vegetation cover are concerned. Each site is equipped with 9 soil moisture monitoring stations installed every 130 m which allows the derivation of reliable mean soil moisture estimates across the site featuring small standard deviation (0.035 m 3 /m 3 for the grassland site and 0.074 m 3 /m 3 for the marshland site). The main objective of the presented study is to review the soil moisture derivation and validation methodologies suitable for the Sentinel-1 SAR satellite data and to describe physiographical settings of the Biebrza validation sites together with the installed instrumentation. Furthermore, the relationship between the time series of soil moisture measurements and Sentinel-1 sigma nought backscatter coefficient (σ 0) is examined. Ultimately, the validation results of the low resolution SM-DAS-2 soil moisture product are presented due to the unavailability of the high resolution product.
2010
The SMOSMANIA soil moisture network in Southwestern France is used to evaluate modelled and remotely sensed soil moisture products. The surface soil moisture (SSM) measured in situ at 5 cm permits to evaluate SSM from the SIM operational hydrometeorological model of Météo-France and to perform a cross-evaluation of the normalised SSM estimates derived from coarse-resolution (25 km) active microwave observations from the ASCAT scatterometer instrument (C-band, onboard METOP), issued by EUMETSAT and resampled to the Discrete Global Grid (DGG, 12.5 km gridspacing) by TU-Wien (Vienna University of Technology) over a two year period (2007-2008). A downscaled ASCAT product at one kilometre scale is evaluated as well, together with operational soil moisture products of two meteorological services, namely the ALADIN numerical weather prediction model (NWP) and the Integrated Forecasting System (IFS) analysis of Météo-France and ECMWF, respectively. In addition to the operational SSM analysis of ECMWF, a second analysis using a simplified extended Kalman filter and assimilating the ASCAT SSM estimates is tested. The ECMWF SSM estimates correlate better with the in situ observations than the Météo-France products. This may be due to the higher ability of the multi-layer land surface model used at ECMWF to represent the soil moisture profile. However, the SSM derived from SIM corresponds to a thin soil surface layer and presents good correlations with ASCAT SSM estimates for the very first centimetres of soil. At ECMWF, the use of a new data assimilation technique, which is able to use the AS-CAT SSM, improves the SSM and the root-zone soil moisture analyses.
… and Remote Sensing …, 2012
The European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission was launched on November 2, 2009. Providing accurate soil moisture (SM) estimation is one of its main scientific objectives. Since the end of the commissioning phase, preliminary global SMOS SM data [Level 2 (L2) product] are distributed to users. In this paper, we carried out a first assessment of the reliability of this product through a comparison with in situ observed and modeled SM over three different sites: One is located in Luxemburg, and two are located in Italy. The period from August 1, 2010, to July 1, 2011, has been analyzed, giving us the opportunity to evaluate the satellite response to different SM states. The selected period is important for hydrological predictions as it is typically characterized by a sequence of transitions from dry to wet and from wet to dry conditions. In order to compare SMOS and ground SM measurements, a two-step approach has been applied. First, an exponential filter has been applied to approximate root-zone SM, and second, a cumulative distribution function matching has been employed to remove systematic differences between satellite and in situ observations and model simulations of SM. Our results indicate rather good reliability of the filtered and bias-corrected SM estimates derived from the first SMOS L2 products. Bearing in mind that an updated/advanced version of the SMOS SM product has been recently produced, our preliminary results already seem to confirm the potential of SMOS for monitoring of water in soils.
Remote Sensing of Environment, 2012
Accurate estimates of soil moisture as initial conditions to hydrological models are expected to greatly increase the accuracy of flood and drought predictions. As in-situ soil moisture observations are scarce, satellite-based estimates are a suitable alternative. The validation of remotely sensed soil moisture products is generally hampered by the difference in spatial support of in-situ observations and satellite footprints. Unsaturated zone modeling may serve as a valuable validation tool because it could bridge the gap of different spatial supports. A stochastic, distributed unsaturated zone model (SWAP) was used in which the spatial support was matched to these of the satellite soil moisture retrievals. A comparison between point observations and the SWAP model was performed to enhance understanding of the model and to assure that the SWAP model could be used with confidence for other locations in Spain. A timeseries analysis was performed to compare surface soil moisture from the SWAP model to surface soil moisture retrievals from three different microwave sensors, including AMSR-E, SMOS and ASCAT. Results suggest that temporal dynamics are best captured by AMSR-E and ASCAT resulting in an averaged correlation coefficient of 0.68 and 0.71, respectively. SMOS shows the capability of capturing the long-term trends, however on short timescales the soil moisture signal was not captured as well as by the other sensors, resulting in an averaged correlation coefficient of 0.42. Root mean square errors for the three sensors were found to be very similar (± 0.05 m 3 m −3 ). The satellite uncertainty is spatially correlated and distinct spatial patterns are found over Spain.
European Journal of Remote Sensing, 2013
More than two years of soil moisture data derived from the Advanced SCATterometer (ASCAT) and from the Soil Moisture and Ocean Salinity (SMOS) radiometer are analysed and compared. The comparison has been performed within the framework of an activity aiming at validating the EUMETSAT Hydrology Satellite Application Facility (H-SAF) soil moisture product derived from ASCAT. The available database covers a large part of the SMOS mission lifetime (2010, 2011 and partially 2012) and both Europe and North Africa are considered. A specific strategy has been set up in order to enable the comparison between products representing a volumetric soil moisture content, as those derived from SMOS, and a relative saturation index, as those derived from ASCAT. Results demonstrate that the two products show a fairly good degree of correlation. Their consistency has some dependence on season, geographical zone and surface land cover. Additional factors, such as spatial property features, are also preliminary investigated.
Towards land surface model validation from using satellite retrieved soil moisture
Piantadosi, J., Anderssen, R.S. and Boland J. (eds) MODSIM2013, 20th International Congress on Modelling and Simulation, 2013
Land surface model validation at distributed scales is important for model improvements. Recent advances in satellite technology provide an opportunity for distributed calibration and validation of land surface models. In the past years, a number of active and passive microwave soil moisture products have become available. While passive microwave soil moisture is the preferred approach for soil moisture observation, its disadvantage is the coarse spatial resolution it affords. Moreover, many of the available satellites use sub-optimal wavelengths, and the satellite retrieval algorithms are still under development. Consequently, the accuracy of these satellite data sets needs to be verified prior to their application. However, the spatial and temporal discrepancies between in-situ monitoring and satellite footprint retrievals continue to make absolute verification of satellite retrieved soil moisture a difficult problem. The Advanced Microwave Scanning Radiometer-2 (AMSR-2) onboard the Global Change Observation Mission 1-Water (GCOM-W1) was launched by JAXA in May 2012. AMSR-2 is a follow on of the AMSR-Earth Observing System (AMSR-E) onboard Aqua and of the AMSR onboard the Advanced Earth Observing Satellite 2 (ADEOS-II). By combining data from AMSR, AMSR-E and AMSR-2, a 20-year record of near-continuous C-band measurements of soil moisture content is expected to be available, starting from 2001. This study makes an inter-comparison between in-situ data from the OzNet soil moisture network (www.oznet.org.au), the AMSR-2 soil moisture product, and simulated soil moisture using JULES (Joint UK Land Environment Simulator) for the period July to December 2012. The area selected is a 60 km × 60 km study site in Yanco, NSW, Australia (34.561°S, 35.170°S, 145.826°E, 146.439°E). 10 km and 25 km soil moisture products from the descending orbit of AMSR-2, which has a repeat time of 1 to 2 days, has been used. The JULES land surface model was run at hourly time-steps and approximately 1 km (0.01°) resolution for the entire 60 km × 60 km Yanco area, which coincides with twenty-five 10 km and four 25 km AMSR-2 product grids at hourly time-steps. Due to the co-location between in-situ monitoring stations and AMSR-2 grids, comparison between both data sets was only possible at five 10 km and two 25 km AMSR-2 pixels. Where in-situ stations are available, time series of AMSR-2 soil moisture and JULES simulations were validated against in-situ measurements. AMSR-2 products and JULES simulations were also compared against each other. The average RMSD for both 10 km and 25 km products were found to be 0.05 m 3 /m 3 when compared to insitu data, which meets the target accuracy of the mission. The AMSR-2 soil moisture was used to evaluate simulated soil moisture. Being a consistent product across time and space, AMSR-2 soil moisture can be used to identify where model simulations are inaccurate due to forcing data, parameter assignment or model physics. Whilst the opportunity in using AMSR-2 soil moisture to validate land surface models run at distributed scales was demonstrated, this study could not conclude whether the satellite or simulated soil moisture is more accurate due to possible inaccuracies in the current radiative transfer model, parameterization of soil and vegetation characteristics and prescription of precipitation data in the land surface model. The study also indicated prospects in further studies for better understanding of the Yanco site in relation to 1) representativeness of the sites used for validation and 2) effects caused by vegetation and standing water within the satellite footprint to improve the retrieval algorithm of AMSR-2 soil moisture for Australian conditions.
A multi-sensor (SMOS, AMSR-E and ASCAT) satellite-based soil moisture products inter-comparison
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
Soil Moisture (SM), being one of the main variables within the system that controls the hydrological interactions among soil, vegetation and atmosphere, plays a key role in the water cycle. Satellite systems, both active and passive, have already demonstrated their capability to provide reliable SM measurements. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission, launched in November 2009, was the first specific SM satellite mission. In this work we assessed the capability of SMOS data to accurately capture SM dynamics over a long time period by comparing them with in situ observations. To better assess the performance of such results, they were also compared with those obtained with alternative satellite-based SM products, considering in particular those generated by Advanced Microwave Sounding Radiometer (AMSR-E) and Advanced SCATterometer (ASCAT) data.
Surface soil moisture in central Europe from SMOS satellite
The water in oceans, rivers, lakes and soil is a very important resource which governs the water cycle, both at the regional and global scales. The knowledge of the soil moisture content allows for prediction and prevention of dangerous phenomena such as floods, droughts and soil erosion. Despite of the numerous applications, knowledge about the spatial distribution and temporal behaviour of soil moisture used to be very limited. The aim of the research was to examine the spatial distribution of surface soil moisture at chosen dates, for different sites in Europe, especially in the context of floods and discharge. Soil moisture was assessed by measuring brightness temperature from Earth orbit via satellite SMOS (Soil Moisture and Ocean Salinity) using the interferometric radiometer method in the frequency 1.4 GHz. The results proved that satellite soil moisture measurements can be useful for many applications: hydrological models, climate change, agricultural and environmental asses...
This paper examines the potential of scatterometer data from ERS satellites for improving hydrological simulations in both gauged and ungauged catchments. We compare the soil moisture dynamics simulated by a semidistributed hydrologic model in 320 Austrian catchments with the soil moisture dynamics inferred from the satellite data. The most apparent differences occur in the Alpine areas. Assimilating the scatterometer data into the hydrologic model during the calibration phase improves the relationship between the two soil moisture estimates without any significant decrease in runoff model efficiency. For the case of ungauged catchments, assimilating scatterometer data does not improve the daily runoff simulations but does provide more consistent soil moisture estimates. If the main interest is in obtaining estimates of catchment soil moisture, reconciling the two sources of soil moisture information seems to be of value because of the different error structures.