Long-term SMOS soil moisture products: A comprehensive evaluation across scales and methods in the Duero Basin (Spain)

The European Space Agency’s Soil Moisture and Ocean Salinity (SMOS) Level 2 soil moisture and the new L3 product from the Barcelona Expert Center (BEC) were validated from January 2010 to June 2014 using two in situ networks in Spain. The first network is the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS), which has been extensively used for validating remotely sensed observations of soil moisture. REMEDHUS can be considered a small-scale network that covers a 1300 km² region. The second network is a large-scale network that covers the main part of the Duero Basin (65,000 km²). At an existing meteorological network in the Castilla y Leon region (Inforiego), soil moisture probes were installed in 2012 to provide data until 2014. Comparisons of the temporal series using different strategies (total average, land use, and soil type) as well as using the collocated data at each location were performed. Additionally, spatial correlations on each date were computed for specific days. Finally, an improved version of the Triple Collocation (TC) method, i.e., the Extended Triple Collocation (ETC), was used to compare satellite and in situ soil moisture estimates with outputs of the Soil Water Balance Model Green-Ampt (SWBM-GA). The results of this work showed that SMOS estimates were consistent with in situ measurements in the time series comparisons, with Pearson correlation coefficients (R) and an Agreement Index (AI) higher than 0.8 for the total average and the land-use averages and higher than 0.85 for the soil-texture averages. The results obtained at the Inforiego network showed slightly better results than REMEDHUS, which may be related to the larger scale of the former network. Moreover, the best results were obtained when all networks were jointly considered. In contrast, the spatial matching produced worse results for all the cases studied.These results showed that the recent reprocessing of the L2 products (v5.51) improved the accuracy of soil moisture retrievals such that they are now suitable for developing new L3 products, such as the presented in this work. Additionally, the validation based on comparisons between dense/sparse networks and satellite retrievals at a coarse resolution showed that temporal patterns in the soil moisture are better reproduced than spatial patterns.     

Soil water content in southern England derived from a cosmic‐ray soil moisture observing system – COSMOS‐UK

Cosmic‐ray soil moisture sensors have the advantage of a large measurement footprint (approximately 700 m in diameter) and are able to operate continuously to provide area‐averaged near‐surface (top 10–20 cm) volumetric soil moisture content at the field scale. This paper presents the application of this technique at four sites in southern England over almost 3 years. Results show the soil moisture response to contrasting climatic conditions during 2011–2014 and are the first such field‐scale measurements made in the UK. These four sites are prototype stations for a UK COsmic‐ray Soil Moisture Observing System, and particular consideration is given to sensor operating conditions in the UK. Comparison of these soil water content observations with the Joint UK Land Environment Simulator 10‐cm soil moisture layer shows that these data can be used to test and diagnose model performance and indicate the potential for assimilation of these data into hydro‐meteorological models. The application of these large‐area soil water content measurements to evaluate remotely sensed soil moisture products is also demonstrated. Numerous applications and the future development of a national COsmic‐ray Soil Moisture Observing System network are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Comparison of SMOS,modelled and in situ long-term soil moisture series in the northwest of Spain

ABSTRACT

This work aimed to evaluate the capability of modelled vs in situ soil moisture observations in the northwest of Spain for a period of four years (2010–2013) in order to validate the SMOS L2 product. Comparisons were performed for a set of representative stations of the Soil Moisture Measurement Stations network of the University of Salamanca (REMEDHUS) at both point and area scales. The SMOS series showed good correlation with the modelled series, better than that obtained with the in situ observations (0.77 vs 0.68 average correlation coefficients). However, some underestimation or overestimation of the SMOS series, related to the soil characteristics, was observed with respect to both the in situ and the modelled series. The SMOS data normalization produced a notable improvement in the results, highlighting the capability of the modelled data to validate the SMOS soil moisture series. This research provides a solid foundation for the future validation of SMOS at large scales, overcoming the spatial representativeness issues arising from the use of in situ point measurements.

Editor M.C. Acreman; Associate editor N. Verhoest     

Active microwave remote sensing for soil moisture measurement: a field evaluation using ERS‐2

Active microwave remote sensing observations of backscattering, such as C‐band vertically polarized synthetic aperture radar (SAR) observations from the second European remote sensing (ERS‐2) satellite, have the potential to measure moisture content in a near‐surface layer of soil. However, SAR backscattering observations are highly dependent on topography, soil texture, surface roughness and soil moisture, meaning that soil moisture inversion from single frequency and polarization SAR observations is difficult. In this paper, the potential for measuring near‐surface soil moisture with the ERS‐2 satellite is explored by comparing model estimates of backscattering with ERS‐2 SAR observations. This comparison was made for two ERS‐2 overpasses coincident with near‐surface soil moisture measurements in a 6 ha catchment using 15‐cm time domain reflectometry probes on a 20 m grid. In addition, 1‐cm soil moisture data were obtained from a calibrated soil moisture model. Using state‐of‐the‐art theoretical, semi‐empirical and empirical backscattering models, it was found that using measured soil moisture and roughness data there were root mean square (RMS) errors from 3·5 to 8·5 dB and r² values from 0·00 to 0·25, depending on the backscattering model and degree of filtering. Using model soil moisture in place of measured soil moisture reduced RMS errors slightly (0·5 to 2 dB) but did not improve r² values. Likewise, using the first day of ERS‐2 backscattering and soil moisture data to solve for RMS surface roughness reduced RMS errors in backscattering for the second day to between 0·9 and 2·8 dB, but did not improve r² values. Moreover, RMS differences were as large as 3·7 dB and r² values as low as 0·53 between the various backscattering models, even when using the same data as input. These results suggest that more research is required to improve the agreement between backscattering models, and that ERS‐2 SAR data may be useful for estimating fields‐scale average soil moisture but not variations at the hillslope scale. Copyright © 2004 John Wiley & Sons, Ltd.     

Use of multi‐platform,multi‐temporal remote‐sensing data for calibration of a distributed hydrological model: an application in the Arno basin,Italy

Images from satellite platforms are a valid aid in order to obtain distributed information about hydrological surface states and parameters needed in calibration and validation of the water balance and flood forecasting. Remotely sensed data are easily available on large areas and with a frequency compatible with land cover changes. In this paper, remotely sensed images from different types of sensor have been utilized as a support to the calibration of the distributed hydrological model MOBIDIC, currently used in the experimental system of flood forecasting of the Arno River Basin Authority. Six radar images from ERS‐2 synthetic aperture radar (SAR) sensors (three for summer 2002 and three for spring–summer 2003) have been utilized and a relationship between soil saturation indexes and backscatter coefficient from SAR images has been investigated. Analysis has been performed only on pixels with meagre or no vegetation cover, in order to legitimize the assumption that water content of the soil is the main variable that influences the backscatter coefficient. Such pixels have been obtained by considering vegetation indexes (NDVI) and land cover maps produced by optical sensors (Landsat‐ETM). In order to calibrate the soil moisture model based on information provided by SAR images, an optimization algorithm has been utilized to minimize the regression error between saturation indexes from model and SAR data and error between measured and modelled discharge flows. Utilizing this procedure, model parameters that rule soil moisture fluxes have been calibrated, obtaining not only a good match with remotely sensed data, but also an enhancement of model performance in flow prediction with respect to a previous calibration with river discharge data only. Copyright © 2006 John Wiley & Sons, Ltd.     

Using data‐driven methods to explore the predictability of surface soil moisture with FLUXNET site data

Soil moisture (SM) is a key variable of land surface‐atmosphere interactions. Data‐driven methods have been used to predict SM, but the predictability of SM has not been well evaluated. This study investigated what variables and methods can be used to better predict SM for leading times of 7 days or longer with a global coverage of FLUXNET site data for the first time. Three machine‐learning models, that is, Bayesian linear regression, random forest, and gradient boosting regression tree, are used for the prediction. Variables including atmospheric forcing, surface soil temperature, time variables (year, day of year, and hour), the Fourier transformation of time variables, and lagged SM (7‐ to 14‐day lagged) were sequentially added into models. A framework with five experiments is designed for factorial exploration of SM predictability. A stepwise method was used to build the best models for each site. The performance of regression models became better when adding more explaining variables in most cases. The results showed that from 50 to 95% of variation of the best models can be explained. The important explaining variables are lagged surface SM, followed by day of year, year, soil temperature, and atmospheric forcing. The predictability of SM depends highly on SM memory characteristics and the persistence of seasonality. The effect of SM memory characteristics on SM prediction as an initial condition question has been widely discussed in this paper. Our results also provide an insight that mechanisms of seasonality effects on SM should be also paid more attention to.     

Modeling of terracette‐hillslope soil moisture as a function of aspect,slope and vegetation in a semi‐arid environment

In the semi‐arid western United States, water availability plays a defining role in land use. Soil moisture, vegetation, and microtopography are key variables in the hydrologic function of these ecosystems. Previous research has not addressed the influence of site‐specific aspect, vegetation, or slope gradient on terracette soil moisture patterns in semi‐arid rangelands. Therefore, the objectives of this study were to: (1) assess the influence of terracette site aspect, vegetation cover, and slope on soil moisture; (2) conceptualize conditions at the hillslope scale given terracette morphology; and (3) estimate the extent of terracettes at a regional scale. The Simultaneous Heat and Water (SHAW) model was used to simulate soil water dynamics of terracettes given variations in site conditions. These results were coupled with time‐of‐flight laser scans to quantify terracette bench and riser percent‐area, and statewide assessments of terracette extent using digital orthoimagery and a geographical information system (GIS). Modeling results indicated site aspect had minimal influence (±0.005 m³ m^?3) on terracette soil moisture. Vegetation, represented as leaf area index (LAI), had the single‐most influential effect on terracette volumetric water content (θ _v) demonstrated by an inverse relationship of LAI to mean terracette hillslope θ _v; and slope increases of ≥15% on northern azimuths increased mean θ _v which contrasted with southern azimuths for similar slope increases. Laser scanning results indicated bench width and riser length could be estimated from mean site slope (R ² = 0.82 risers and R ² = 0.93 benches). Aerial orthoimagery/GIS assessments estimated >159 000 ha of terracettes throughout the State of Idaho, with >41 000 ha (~26%) occurring on lands managed as grazing allotments. These findings provide an increased understanding of rangeland hydrologic processes as influenced by cattle density, vegetation, and terracettes which can aide land managers in their selection and application of best management practices on these lands. Copyright © 2017 John Wiley & Sons, Ltd.     

The contrasted evolution of high and low flows and precipitation indices in the Duero basin (Spain)

Abstract

Trends in high and low flows are valuable indicators of hydrological change because they highlight changes in various parts of the frequency distribution of streamflow series. This enables improved assessment of water availability in regions with high seasonal and inter-annual variability. There has been a substantial reduction in water resources in the Duero basin (Iberian Peninsula, Spain) and other areas of the Mediterranean region during the last 50 years, and this is likely to continue because of climate change. In this study, we investigated the evolution and trends in high and low flows in the Spanish part of the Duero basin, and in equivalent or closely-related precipitation indices for the period 1961–2005. The results showed a general trend of decrease in the frequency and magnitude of high flows throughout most of the basin. Moreover, the number of days with low flows significantly increased over this period. No clear relationship was evident between the evolution of high/low flows and changes in the distribution frequencies of the precipitation series. In contrast to what was expected, the number of days with heavy precipitation and the mean annual precipitation did not show significant trends across the basin, and the number of days without rainfall decreased slightly. The divergence between precipitation and runoff evolution was more accentuated in spring and summer. In the absence of trends in precipitation, it is possible that reforestation processes in the region, and increasing temperatures in recent decades, could be related to the decreasing frequency of high flows and the increasing frequency of low flows.

Editor Z.W. Kundzewicz; Associate editor S. Grimaldi

Citation Morán-Tejeda, E., López-Moreno, J.I., Vicente-Serrano, S.M., Lorenzo-Lacruz, J. and Ceballos-Barbancho, A., 2012. The contrasted evolution of high and low flows and precipitation indices in the Duero basin (Spain). Hydrological Sciences Journal, 57 (4), 591–611.     

Improving the representation of soil moisture by using a semi‐analytical infiltration model

Soil moisture is widely recognized as a fundamental variable governing the mass and energy fluxes between the land surface and the atmosphere. In this study, the soil moisture modelling at sub‐daily timescale is addressed by using an accurate representation of the infiltration component. For that, the semi‐analytical infiltration model proposed by Corradini et al. (1997) has been incorporated into a soil water balance model to simulate the evolution in time of surface and profile soil moisture. The performances of this new soil moisture model [soil water balance module‐semi‐analytical (SWBM‐SA)] are compared with those of a precedent version [SWBM‐Green–Ampt (GA)] where the GA approach was employed. Their capability to reproduce in situ soil moisture observations at three sites in Italy, Spain and France is analysed. Hourly observations of quality‐checked rainfall, temperature and soil moisture data for a 2‐year period are used for testing the modelling approaches. Specifically, different configurations for the calibration and validation of the models are adopted by varying a single parameter, that is, the saturated hydraulic conductivity. Results indicate that both SWBMs are able to reproduce satisfactorily the hourly soil moisture temporal pattern for the three sites with root mean square errors lower than 0.024 m³/m³ both in the calibration and validation periods. For all sites, the SWBM‐SA model outperforms the SWBM‐GA with an average reduction of the root mean square error of ~20%. Specifically, the higher improvement is observed for the French site for which in situ observations are measured at 30 cm depth, and this is attributed to the capability of the SA infiltration model to simulate the time evolution of the whole soil moisture profile. The reasonable models performance coupled with the need to calibrate only a single parameter makes them useful tools for soil moisture simulation in different regions worldwide, also in scarcely gauged areas. Copyright © 2013 John Wiley & Sons, Ltd.     

Year‐round estimation of soil moisture content using temporally variable soil hydraulic parameters

Soil moisture plays a key role in the hydrological cycle as it controls the flux of water between soil, vegetation, and atmosphere. This study is focused on a year‐round estimation of soil moisture in a forested mountain area using the bucket model approach. For this purpose, three different soil moisture models are utilised. The procedure is based on splitting the whole year into two complement periods (dormant and vegetation). Model parameters are allowed to vary between the two periods and also from year to year in the calibration procedure. Consequently, two sets of average model parameters corresponding to dormant and vegetation seasons are proposed. The process of splitting is strongly supported by the experimental data, and it enables us to variate saturated hydraulic conductivity and pore‐size characterisation. The use of the two different parameter sets significantly enhances the simulation of two (Teuling and Troch model and soil water balance model‐green–ampt [SWBM‐GA]) out of three models in the 6‐year period from 2009 to 2014. For these two models, the overall Nash‐Sutcliffe coefficient increased from 0.64 to 0.79 and from 0.55 to 0.80. The third model (the Laio approach) proved to be insensitive to parameter changes due to its insufficient drainage prediction. The variability of the warm and cold parameter sets between particular years is more pronounced in the warm periods. The cold periods exhibited approximately similar character during all 6 years.     

Spatial prediction of temporal soil moisture dynamics using HYDRUS‐1D

This article investigates the soil moisture dynamics within two catchments (Stanley and Krui) in the Goulburn River in NSW during a 3‐year period (2005–2007) using the HYDRUS‐1D soil water model. Sensitivity analyses indicated that soil type, and leaf area index were the key parameters affecting model performance. The model was satisfactorily calibrated on the Stanley microcatchment sites with a single point rainfall record from this microcatchment for both surface 30 cm and full‐profile soil moisture measurements. Good correlations were obtained between observed and simulated soil water storage when calibrations for one site were applied to the other sites. We extended the predictions of soil moisture to a larger spatial scale using the calibrated soil and vegetation parameters to the sites in the Krui catchment where soil moisture measurement sites were up to 30 km distant from Stanley. Similarly good results show that it is possible to use a calibrated soil moisture model with measurements at a single site to extrapolate the soil moisture to other sites for a catchment with an area of up to 1000 km² given similar soils and vegetation and local rainfall data. Site predictions were effectively improved by our simple data assimilation method using only a few sample data collected from the site. This article demonstrates the potential usefulness of continuous time, point‐scale soil moisture data (typical of that measured by permanently installed TDR probes) and simulations for predicting the soil wetness status over a catchment of significant size (up to 1000 km²). Copyright © 2012 John Wiley & Sons, Ltd.     

First approximations of soil moisture retention curves using the filter‐paper method

Relationships between gravimetric soil moisture content (w) and matric potential (ϕ), and between volumetric soil moisture content (θ_v) and pressure head (h) were approximated for the unsaturated zone on Long Island, New York. Soil samples were collected from two sites using a hand auger. The soil moisture content was determined using the filter‐paper (w_f) and gravimetric (w) methods, respectively. The w_f was then used in an empirical equation to estimate ϕ_m. Each set of ϕ_m and w was combined with a straight‐line empirical model to obtain a w(ϕ_m) relationship. Soil ϕ_m was converted to h, and w to the volumetric moisture content θ_v, in order to produce a θ_v(h) curve. Graphical and statistical comparison showed that the resulting θ_v(h) curves fell within one order of magnitude of similar curves generated by a more sophisticated non‐linear model developed previously. The simplicity and low cost of the filter‐paper approach described in this study recommends it for preliminary studies of hydraulic properties in the unsaturated zone. Copyright © 2000 John Wiley & Sons, Ltd.     

How soil texture,channel shape and cross-sectional area affect moisture dynamics and water loss in irrigation channels

To enhance the utilization efficiency of farmland irrigation water and reduce the leakage of water conveyance channels, the leakage process of channels was simulated dynamically. The simulated results were compared with data measured in laboratory experiments, and the performance of the model was evaluated. The results indicated that the simulated values of the model were consistent with the observation values, and the R² values varied between 0.91 and 0.99. In addition, based on the laboratory experiments, a water supply system (Mariotte bottles) and soil box were built using plexiglass. Three influencing factors, namely, the channel form, soil texture and channel cross-sectional area, were varied to observe and calculate the resulting cumulative infiltration amount, infiltration rate and wetting front migration distance. HYDRUS-3D software was used to solve the three-dimensional soil water movement equation under different initial conditions. The results demonstrated that the U-shaped channel was more effective than the trapezoidal channel in increasing the utilization efficiency of the water resources. A U-shaped channel with a small channel cross-sectional area should be adopted and the soil particle size should be prioritized in the construction of water conveyance channels for farmlands. The simulation results were in agreement with the observed results, which indicates that HYDRUS-3D is a reliable tool that can accurately simulate the soil moisture movement in water conveyance channels. The research results can provide a reference for the design and operation of farmland irrigation systems.     

On the role of soil moisture in daytime evolution of temperatures

This paper explores the relationship between temperature, evaporation and soil moisture using a planetary boundary layer (PBL) model. It focuses on illustrating and quantifying the effect of soil moisture on the evolution of daytime temperatures. A simple convective PBL model coupled with the Penman–Monteith (PM) equation is used to estimate evapotranspiration. Following calibration and sensitivity analysis, the model was used to simulate the relative impact of dry and wet soil moisture conditions on daytime temperatures by changing the surface resistance parameter in the PM equation. It was found that the maximum temperature that can be reached during a day is constrained by the amount of soil moisture and the available net radiation, confirming previously published results. Higher temperatures can be reached with greater net radiation and dry soil moisture conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling soil moisture in a high‐latitude landscape using LiDAR and soil data

Soil moisture has a pronounced effect on earth surface processes. Global soil moisture is strongly driven by climate, whereas at finer scales, the role of non‐climatic drivers becomes more important. We provide insights into the significance of soil and land surface properties in landscape‐scale soil moisture variation by utilizing high‐resolution light detection and ranging (LiDAR) data and extensive field investigations. The data consist of 1200 study plots located in a high‐latitude landscape of mountain tundra in north‐western Finland. We measured the plots three times during growing season 2016 with a hand‐held time‐domain reflectometry sensor. To model soil moisture and its temporal variation, we used four statistical modelling methods: generalized linear models, generalized additive models, boosted regression trees, and random forests. The model fit of the soil moisture models were R² = 0.60 and root mean square error (RMSE) 8.04 VWC% on average, while the temporal variation models showed a lower fit of R² = 0.25 and RMSE 13.11 CV%. The predictive performances for the former were R² = 0.47 and RMSE 9.34 VWC%, and for the latter R² = 0.01 and RMSE 15.29 CV%. Results were similar across the modelling methods, demonstrating a consistent pattern. Soil moisture and its temporal variation showed strong heterogeneity over short distances; therefore, soil moisture modelling benefits from high‐resolution predictors, such as LiDAR based variables. In the soil moisture models, the strongest predictor was SAGA (System for Automated Geoscientific Analyses) wetness index (SWI), based on a 1 m² digital terrain model derived from LiDAR data, which outperformed soil predictors. Thus, our study supports the use of LiDAR based SWI in explaining fine‐scale soil moisture variation. In the temporal variation models, the strongest predictor was the field‐quantified organic layer depth variable. Our results show that spatial soil moisture predictions can be based on soil and land surface properties, yet the temporal models require further investigation. Copyright © 2017 John Wiley & Sons, Ltd.     

Estimation of near surface soil moisture in a sloping terrain of a Himalayan watershed using ENVISAT ASAR multi‐incidence angle alternate polarisation data

Soil moisture is one of the important input variables in hydrological and water erosion models. The extraction of information on near surface soil moisture from synthetic aperture radar (SAR) is well established mostly for flat terrain and using low incidence angle single polarisation data. The ENVISAT advanced SAR (ASAR) data available in multiple incidence angles and alternate polarisation modes were investigated in this study for soil moisture estimation in sloping terrain. The test site was Sitla Rao watershed in the Lesser Himalayas of northern India. Empirical models were developed to estimate near surface soil moisture in bare agricultural fields using alternate polarisation ASAR data. Both soil moisture and surface roughness field measurements were performed during the satellite passes. Backscatter from medium incidence angle (IS‐4) and vertical‐vertical (VV) polarisation signal is correlated better with volumetric soil moisture content compared to other incidence angles. The model parameters were further improved, and soil moisture estimation was refined by combining medium incidence angle (IS4) vertical‐horizontal polarisation response as another variable along with VV polarisation response. The effect of slope on the radar backscatter was minimized by incorporating local incidence angles derived from an ASTER DEM. Copyright © 2012 John Wiley & Sons, Ltd.     

Obstacles to long‐term soil moisture monitoring with heated distributed temperature sensing

The field deployment of a heated distributed temperature sensor (DTS) for over three years has revealed two obstacles to estimating soil moisture (θ) that may hamper subsurface DTS applications as well as use of other subsurface thermal probes. The first observed obstacle was a hysteretic response of the DTS sensor. The relationship between θ and the temperature response (?T) within the cable was not only dependent on θ of the soil, but also on the previous wetting and drying cycles leading to that state. The second observed obstacle was soil structure healing. Soil structure healing causes the relationship between ?T and θ to evolve through time; this calibration curve becomes flatter, or less sensitive, as the surrounding soil makes better contact with the cable. Effects of the hysteretic response of the instrument and soil structure healing are largely the result of small gaps between the cable and soil. These small gaps can be approximated by a contact resistance between the cable and soil. In this article we characterize the occurrence of hysteretic and soil structure healing effects from field data and parameterize contact resistance by simulating heat transfer using a numerical modelling approach Copyright © 2015 John Wiley & Sons, Ltd.