Evaluation of SMOS soil moisture retrievals over the central United States for hydro-meteorological application

Soil moisture has been widely recognized as a key variable in hydro-meteorological processes and plays an important role in hydrological modelling. Remote sensing techniques have improved the availability of soil moisture data, however, most previous studies have only focused on the evaluation of retrieved data against point-based observations using only one overpass (i.e., the ascending orbit). Recently, the global Level-3 soil moisture dataset generated from Soil Moisture and Ocean Salinity (SMOS) observations was released by the Barcelona Expert Center. To address the aforementioned issues, this study is particularly focused on a basin scale evaluation in which the soil moisture deficit is derived from a three-layer Xinanjiang model used as a hydrological benchmark for all comparisons. In addition, both ascending and descending overpasses were analyzed for a more comprehensive comparison. It was interesting to find that the SMOS soil moisture accuracy did not improve with time as we would have expected. Furthermore, none of the overpasses provided reliable soil moisture estimates during the frozen season, especially for the ascending orbit. When frozen periods were removed, both overpasses showed significant improvements (i.e., the correlations increased from r = −0.53 to r = −0.65 and from r = −0.62 to r = −0.70 for the ascending and descending overpasses, respectively). In addition, it was noted that the SMOS retrievals from the descending overpass consistently were approximately 11.7% wetter than the ascending retrievals by volume. The overall assessment demonstrated that the descending orbit outperformed the ascending orbit, which was unexpected and enriched our knowledge in this area. Finally, the potential reasons were discussed.     

The GGOS as the backbone for global observing and local monitoring: A user driven perspective

A key geodetic contribution to both the three Global Observing Systems and initiatives like the European Global Monitoring for Environment and Security is an accurate, long-term stable, and easily accessible reference frame as the backbone. Many emerging scientific as well as non-scientific high-accuracy applications require access to an unique, technique-independent reference frame decontaminated for short-term fluctuations due to global Earth system processes. Such a reference frame can only be maintained and made available through an observing system such as the Global Geodetic Observing System (GGOS), which is currently implemented and expected to provide sufficient information on changes in the Earth figure, its rotation and its gravity field. Based on a number of examples from monitoring of infrastructure, point positioning, maintenance of national references frames to global changes studies, likely future accuracy requirements for a global terrestrial reference frame are set up as function of time scales. Expected accuracy requirements for a large range of high-accuracy applications are less than 5 mm for diurnal and sub-diurnal time scales, 2–3 mm on monthly to seasonal time scales, better than 1 mm/year on decadal to 50 years time scales. Based on these requirements, specifications for a geodetic observing system meeting the accuracy requirements can be derived.     

A temperature-dependent multi-relaxation spectroscopic dielectric model for thawed and frozen organic soil at 0.05–15 GHz

A dielectric model for thawed and frozen Arctic organic-rich soil (50% organic matter) has been developed. The model is based on soil dielectric measurements that were collected over ranges of gravimetric moisture from 0.03 to 0.55 g/g, dry soil density from 0.72 to 0.87 g/cm³, and temperature from 25 to −30 °C (cooling run) in the frequency range of 0.05–15 GHz. The refractive mixing dielectric model was applied with the Debye multi-relaxation equations to fit the measurements of the soil’s complex dielectric constant as a function of soil moisture and wave frequency. The spectroscopic parameters of the dielectric relaxations for the bound, transient bound, and unbound soil water components were derived and were complimented by the thermodynamic parameters to obtain a complete set of parameters for the proposed temperature-dependent multi-relaxation spectroscopic dielectric model for moist soils. To calculate the complex dielectric constant of the soil, the following input variables must be assigned: (1) density of dry soil, (2) gravimetric moisture, (3) wave frequency, and (4) temperature. The error of the dielectric model was evaluated and yielded RMSE_ε′ values of 0.348 and 0.188 for the soil dielectric constant and the loss factor, respectively. These values are on the order of the dielectric measurement error itself. The proposed dielectric model can be applied in active and passive microwave remote sensing techniques to develop algorithms for retrieving the soil moisture and the freeze/thaw state of organic-rich topsoil in the Arctic regions.     

Applying local Green's functions to study the influence of the crustal structure on hydrological loading displacements

The influence of the elastic Earth properties on seasonal or shorter periodic surface deformations due to atmospheric surface pressure and terrestrial water storage variations is usually modeled by applying a local half-space model or an one dimensional spherical Earth model like PREM from which a unique set of elastic load Love numbers, or alternatively, elastic Green's functions are derived. The first model is valid only if load and observer almost coincide, the second model considers only the response of an average Earth structure. However, for surface loads with horizontal scales less than 2500 km², as for instance, for strong localized hydrological signals associated with heavy precipitation events and river floods, the Earth elastic response becomes very sensitive to inhomogeneities in the Earth crustal structure.We derive a set of local Green's functions defined globally on a 1° × 1° grid for the 3-layer crustal structure TEA12. Local Green's functions show standard deviations of ±12% in the vertical and ±21% in the horizontal directions for distances in the range from 0.1° to 0.5°. By means of Green's function scatter plots, we analyze the dependence of the load response to various crustal rocks and layer thicknesses. The application of local Green's functions instead of a mean global Green's function introduces a variability of 0.5–1.0 mm into the hydrological loading displacements, both in vertical and in horizontal directions. Maximum changes due to the local crustal structures are from −25% to +26% in the vertical and −91% to +55% in the horizontal displacements. In addition, the horizontal displacement can change its direction significantly. The lateral deviations in surface deformation due to local crustal elastic properties are found to be much larger than the differences between various commonly used one-dimensional Earth models.     

Geoelectrical constraints on radar probing of shallow water-saturated zones within karstified carbonates in semi-arid environments

Shallow carbonates are of utmost importance as potential sources of groundwater in karstified semi-arid terrains. Ground-Penetrating Radar (GPR) is being increasingly used as a prominent mapping tool in such environments. However, its potential in exploring and identifying shallow water-saturated zones (WSZs) in carbonates is constrained by the geoelectrical properties of carbonate soils as a function of moisture content. We report results of a case study that includes laboratory geoelectrical characterization and their comparison to in situ GPR attenuation measurements performed on Cretaceous Edwards Formation rudist mounds in central Texas, which we hypothesize as analogs for water-bearing formations in semi-arid karstified carbonate terrains. Dielectric measurements on field-collected rock samples carried out in the laboratory under controlled conditions of moisture saturation suggest that real and imaginary parts of dielectric constants of rocks with higher porosity and/or permeability have steeper dependence on pore moisture content; they produce better dielectric contrasts but allow shallower penetration. Our analyses suggest that within carbonates, dielectric contrasts improve with decrease in sounding frequency and/or increase in moisture content; and the relationship between dielectric permittivity and moisture content may be represented by 3rd order polynomial equations. GPR surveys using a wide-band 400 MHz antenna reveal subsurface mound morphologies with heights of ～ 1–2 m and basal diameters of ～ 8–10 m resembling outcrop analogs. Each mound appears to be composed of smaller amalgamated lithounits that seem geoelectrically similar. Amplitudes decays of the backscattered radar signal correlate to moisture distribution. Measuring the differences in signal attenuation allows differentiation between saturated and non-saturated zones. Velocity analyses of GPR profiles enable estimation of moisture distribution in the vicinity of the mounds. Optimal delineation and production of high-resolution GPR data up to a depth of ～ 10 m were observed for a sounding frequency of ～ 250 MHz with moisture content of ～ 5% by weight. Below this moisture level, the dielectric contrast is insufficient to uniquely identify water-saturated zones from the surrounding geoelectrical context, and above it, the radar signal is substantially attenuated leading to a total inefficiency of the method.     

The origins and concentrations of water,carbon, nitrogen and noble gases on Earth

The isotopic compositions of terrestrial hydrogen and nitrogen are clearly different from those of the nebular gas from which the solar system formed, and also differ from most of cometary values. Terrestrial N and H isotopic compositions are in the range of values characterizing primitive meteorites, which suggests that water, nitrogen, and other volatile elements on Earth originated from a cosmochemical reservoir that also sourced the parent bodies of primitive meteorites. Remnants of the proto-solar nebula (PSN) are still present in the mantle, presumably signing the sequestration of PSN gas at an early stage of planetary growth. The contribution of cometary volatiles appears limited to a few percents at most of the total volatile inventory of the Earth. The isotope signatures of H, N, Ne and Ar can be explained by mixing between two end-members of solar and chondritic compositions, respectively, and do not require isotopic fractionation during hydrodynamic escape of an early atmosphere.The terrestrial inventory of ⁴⁰Ar (produced by the decay of ⁴⁰K throughout the Earth's history) suggests that a significant fraction of radiogenic argon may be still trapped in the silicate Earth. By normalizing other volatile element abundances to this isotope, it is proposed that the Earth is not as volatile-poor as previously thought. Our planet may indeed contain up to ~ 3000 ppm water (preferred range: 1000–3000 ppm), and up to ~ 500 ppm C, both largely sequestrated in the solid Earth. This volatile content is equivalent to an ~ 2 (± 1) % contribution of carbonaceous chondrite (CI-CM) material to a dry proto-Earth, which is higher than the contribution of chondritic material advocated to account for the platinum group element budget of the mantle. Such a (relatively) high contribution of volatile-rich matter is consistent with the accretion of a few wet planetesimals during Earth accretion, as proposed by recent dynamical models.The abundance pattern of major volatile elements and of noble gases is also chondritic, with two notable exceptions. Nitrogen is depleted by one order of magnitude relative to water, carbon and most noble gases, which is consistent with either N retention in a mantle phase during magma generation, or trapping of N in the core. Xenon is also depleted by one order of magnitude, and enriched in heavy isotopes relative to chondritic or solar Xe (the so-called “xenon paradox”). This depletion and isotope fractionation might have taken place due to preferential ionization of xenon by UV light from the early Sun, either before Earth's formation on parent material, or during irradiation of the ancient atmosphere. The second possibility is consistent with a recent report of chondritic-like Xe in Archean sedimentary rocks that suggests that this process was still ongoing during the Archean eon (Pujol et al., 2011). If the depletion of Xe in the atmosphere was a long-term process that took place after the Earth-building events, then the amounts of atmospheric ¹²⁹Xe and ^131–136Xe, produced by the short-lived radioactivities of ¹²⁹I (T_1/2 = 16 Ma) and ²⁴⁴Pu (T_1/2 = 82 Ma), respectively, need to be corrected for subsequent loss. Doing so, the I–Pu–Xe age of the Earth becomes ≤ 50 Ma after start of solar system formation, instead of ~ 120 Ma as computed with the present-day atmospheric Xe inventory.     

High resolution mapping of Earth tide response based on GPS data in Japan

We observe the Earth tidal fields at diurnal and semi-diurnal periods using Kinematic Precise Point Positioning (KPPP) GPS analysis. Our KPPP GPS solutions compare well with super-conducting gravimeter (SG) observations and a theoretical Earth tidal model, that includes both ocean tide loading model and body tides. We make a high resolution map of the observed Earth tidal response fields using the Japanese GEONET GPS network which consists of 1200 sites. We find that: (1) the average phase of GPS data lags 0.11 ± 0.04° from our theoretical Earth tidal model, (2) the average amplitude ratio between GPS and the theoretical Earth tidal model is 1.007 ± 0.003, (3) the amplitude in the Kyushu district is about 1.0–1.5 ± 0.3% larger than in the Hokkaido district, and (4) the amplitude at the Japan Sea side is about 0.5 ± 0.2% larger than that at the Pacific Ocean side. These results suggest that we may be able to place constraints on Earth structure using GPS-derived tidal information.     

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.     

Estimation of in-situ density and moisture content in HMA pavements based on GPR trace reflection amplitude using different frequencies

The basic goal of the present research is to investigate the estimation of both the in-situ density and moisture content within the Hot Mix Asphalt (HMA) pavement layer(s) in a non-destructive way using Ground Penetrating Radar (GPR) trace reflection amplitude. For this purpose, an extensive pavement survey was conducted using an air-coupled GPR system, operating at 1 GHz or alternatively with a 2 GHz central frequency. The collected data were analyzed comparatively for the two antennae. The variability of electric permittivity caused by variations in HMA material is discussed, while the effect of the different frequencies is compared on the ability to retrieve permittivity, in-situ density and moisture content of the compacted HMA material using relationships suggested in reviewed international literature. The main finding of the present research is that for the same type of HMA material, the assessment of the material properties appears to be independent from the two central frequencies of investigation. However, there is evidence concerning the variations between the GPR wave data for the two different frequencies. The research highlights that the increased penetration depth of the 1 GHz antenna can provide an increased identification of areas of potential moisture within the body of HMA layer, and suggests that the variations between the permittivity values for the two different frequencies could be used to assess the homogeneity of material density with depth as an indicator of the mixture compaction. Additional findings are included within the paper.     

Parametric exponentially correlated surface emission model for L-band passive microwave soil moisture retrieval

Surface soil moisture is an important parameter in hydrology and climate investigations. Current and future satellite missions with L-band passive microwave radiometers can provide valuable information for monitoring the global soil moisture. A factor that can play a significant role in the modeling and inversion of microwave emission from land surfaces is the surface roughness. In this study, an L-band parametric emission model for exponentially correlated surfaces was developed and implemented in a soil moisture retrieval algorithm. The approach was based on the parameterization of an effective roughness parameter of H_p in relation with the geometric roughness variables (root mean square height s and correlation length l) and incidence angle. The parameterization was developed based on a large set of simulations using an analytical approach incorporated in the advanced integral equation model (AIEM) over a wide range of geophysical properties. It was found that the effective roughness parameter decreases as surface roughness increases, but increases as incidence angle increases. In contrast to previous research, H_p was found to be expressed as a function of a defined slope parameter m = s²/l, and coefficients of the function could be well described by a quadratic equation. The parametric model was then tested with L-band satellite data in soil moisture retrieval algorithm over the Little Washita watershed, which resulted in an unbiased root mean square error of about 0.03 m³/m³ and 0.04 m³/m³ for ascending and descending orbits, respectively.     

Multidecadal changes in moisture condition during climatic growing period of crops in Northeast China

Investigating the spatiotemporal dynamics of agricultural water status during crop growth season can provide scientific evidences for more efficient use of water resources and sustainable development of agricultural production under climate change. In this study, the following were used to evaluate the multidecadal changes in moisture condition during climatic growth period of crops in Northeast China from 1961 to 2010: (1) the daily climate variables gathered from 101 meteorological stations in Northeast China for 1961–2010; (2) FAO (Food and Agriculture Organization) Penman–Monteith equation; (3) 80% guaranteed probability for agro-climatic indicators; and (4) the daily average temperature stably passing 0 °C, which is the threshold temperature of climatic growth period for crops. Reference crop evapotranspiration (ET₀) and relative moisture index were further calculated. The results showed that Northeast China’s climate in the main agricultural areas over the past 50 years was warmer and drier in general, with a growing range and intensity of drought. From 1961 to 2010, when the daily average temperature stably passed 0 °C, the average annual total precipitation (P) and ET₀ with 80% guaranteed probability in Northeast China both emerged as decreasing trends with averages of 555.0 mm and 993.7 mm, respectively. However, the decline in P was greater than that of annual total ET₀. As a result, the annual relative moisture indices sharply decreased with an average of −0.44, mostly fluctuating from −0.59 to −0.25. As far as spatial distributions were concerned, the inter-regional reductions in P and relative moisture index over the past 50 years were conspicuous, especially in some agricultural areas of central Heilongjiang Province, northeastern Jilin Province and northeastern Liaoning Province. On the contrary, ET₀ obviously increased in some agricultural areas of central and northwestern Heilongjiang Province (eg. Qiqiha’er, Shuangyashan, Hegang, Suihua, etc.), and northeastern Jilin Province (eg. Baicheng). This indicated that drought existed and was unfavorable for crop growth and development, especially during the period of 2001–2010. This finding revealed that drought was still one of the most important agricultural meteorological disasters in Northeast China. Some countermeasures should be formulated to adapt to climate change. Our findings have important implications for improving climate change impact studies, for breeding scientists to breed higher yielding cultivars, and for agricultural production to cope with ongoing climate change.     

Detection of microwave emission due to rock fracture as a new tool for geophysics: A field test at a volcano in Miyake Island,Japan

This paper describes a field test to verify a newly discovered phenomenon of microwave emission due to rock fracture in a volcano. The field test was carried out on Miyake Island, 150 km south of Tokyo. The main objective of the test was to investigate the applicability of the phenomenon to the study of geophysics, volcanology, and seismology by extending observations of this phenomenological occurrence from the laboratory to the natural field.We installed measuring systems for 300 MHz, 2 GHz, and 18 GHz-bands on the mountain top and mountain foot in order to discriminate local events from regional and global events. The systems include deliberate data subsystems that store slowly sampled data in the long term, and fast sampled data when triggered. We successfully obtained data from January to February 2008. During this period, characteristic microwave pulses were intermittently detected at 300 MHz. Two photographs taken before and after this period revealed that a considerably large-scale collapse occurred on the crater cliff. Moreover, seismograms obtained by nearby observatories strongly suggest that the crater subsidence occurred simultaneously with microwave signals on the same day during the observation period.For confirmation of the microwave emission caused by rock fracture, these microwave signals must be clearly discriminated from noise, interferences, and other disturbances. We carefully discriminated the microwave data taken at the mountaintop and foot, checked the lightning strike data around the island, and consequently concluded that these microwave signals could not be attributed to lightning. Artificial interferences were discriminated by the nature of their waveforms. Thus, we inferred that the signals detected at 300 MHz were due to rock fractures during cliff collapses. This result may provide a useful new tool for geoscientists and for the mitigation of natural hazards.     

Using machine learning to produce near surface soil moisture estimates from deeper in situ records at U.S. Climate Reference Network (USCRN) locations: Analysis and applications to AMSR-E satellite validation

Surface soil moisture is a critical parameter for understanding the energy flux at the land atmosphere boundary. Weather modeling, climate prediction, and remote sensing validation are some of the applications for surface soil moisture information. The most common in situ measurement for these purposes are sensors that are installed at depths of approximately 5 cm. There are however, sensor technologies and network designs that do not provide an estimate at this depth. If soil moisture estimates at deeper depths could be extrapolated to the near surface, in situ networks providing estimates at other depths would see their values enhanced. Soil moisture sensors from the U.S. Climate Reference Network (USCRN) were used to generate models of 5 cm soil moisture, with 10 cm soil moisture measurements and antecedent precipitation as inputs, via machine learning techniques. Validation was conducted with the available, in situ, 5 cm resources. It was shown that a 5 cm estimate, which was extrapolated from a 10 cm sensor and antecedent local precipitation, produced a root-mean-squared-error (RMSE) of 0.0215 m³/m³. Next, these machine-learning-generated 5 cm estimates were also compared to AMSR-E estimates at these locations. These results were then compared with the performance of the actual in situ readings against the AMSR-E data. The machine learning estimates at 5 cm produced an RMSE of approximately 0.03 m³/m³ when an optimized gain and offset were applied. This is necessary considering the performance of AMSR-E in locations characterized by high vegetation water contents, which are present across North Carolina. Lastly, the application of this extrapolation technique is applied to the ECONet in North Carolina, which provides a 10 cm depth measurement as its shallowest soil moisture estimate. A raw RMSE of 0.028 m³/m³ was achieved, and with a linear gain and offset applied at each ECONet site, an RMSE of 0.013 m³/m³ was possible.     

Himalayan metamorphic CO2 fluxes: Quantitative constraints from hydrothermal springs

Hot springs in the Marsyandi Valley, Nepal, vent CO₂ sourced from metamorphic fluids that mix with shallow groundwaters before degassing near the Earth's surface. The δ¹³C of spring waters ranges up to + 13‰, while that of the coexisting free gas phase is close to ? 4‰. Empirical and thermodynamic modelling of this isotopic fractionation suggests > 97 ± 1% CO₂ degassing. The calculated minimum total CO₂ degassing in the Marsyandi catchment is 5.4 × 10⁹ mol/yr from a Cl-based estimate of the spring water discharge to the Marsyandi River and the fraction of CO₂ degassed. Extrapolated to the whole of the Himalayas, this implies a probable minimum metamorphic CO₂ flux of 0.9 × 10¹² mol/yr, or ～ 13% of solid Earth CO₂ degassing. The calculated flux is a factor of three greater than the estimated CO₂ drawdown by silicate weathering in the Himalayas. Himalayan metamorphic degassing contributes a significant fraction of the global solid Earth CO₂ flux and implies that metamorphism may cause changes in long-term climate that oppose those resulting from the orogenic forcing of chemical weatherability.     

Stable isotopic characteristic of Taiwan's precipitation: A case study of western Pacific monsoon region

The stable oxygen and hydrogen isotopic features of precipitation in Taiwan, an island located at the western Pacific monsoon area, are presented from nearly 3,500 samples collected during the past decade for 20 stations. Results demonstrate that moisture sources from diverse air masses with different isotopic signals are the main parameter in controlling the precipitation's isotope characteristics. The air mass from polar continental (Pc) region contributes the precipitation with high deuterium excess values (up to 23‰) and relatively enriched isotope compositions (e.g., ? 3.2‰ for δ¹⁸O) during the winter with prevailing northeasterly monsoon. By contrast, air masses from equatorial maritime (Em) and tropical maritime (Tm) supply the precipitation with low deuterium excess values (as low as about 7‰) and more depleted isotope values (e.g., ? 8.9‰ and ? 6.0‰ for δ¹⁸O of Tm and Em, respectively) during the summer with prevailing southwesterly monsoon. Thus seasonal differences in terms of δ¹⁸O, δD, and deuterium excess values are primarily influenced by the interactions among various precipitation sources. While these various air masses travel through Taiwan, secondary evaporation effects further modify the isotope characteristics of the inland precipitation, such as raindrop evaporation (reduces the deuterium excess of winter precipitation) and moisture recycling (increases the deuterium excess of summer precipitation). The semi-quantitative estimations in terms of evaluation for changes in the deuterium excess suggest that the raindrop evaporation fractions for winter precipitation range 7% to 15% and the proportions of recycling moisture in summer precipitation are less than 5%. Additionally, the isotopic altitude gradient in terms of δ¹⁸O for summer precipitation is ? 0.22‰/100 m, greater than ? 0.17‰/100 m of winter precipitation. The greater isotopic gradient in summer can be attributed to a higher temperature vs. altitude gradient relative to winter. The observed spatial and seasonal stable isotopic characteristics in Taiwan's precipitation not only contribute valuable information for regional monsoon research crossing the continent–ocean interface of East Asia, but also can serve as very useful database for local water resources management.     

Assessment of methods for mapping snow cover from MODIS

Characterization of snow is critical for understanding Earth’s water and energy cycles. Maps of snow from MODIS have seen growing use in investigations of climate, hydrology, and glaciology, but the lack of rigorous validation of different snow mapping methods compromises these studies. We examine three widely used MODIS snow products: the “binary” (i.e., snow yes/no) global snow maps that were among the initial MODIS standard products; a more recent standard MODIS fractional snow product; and another fractional snow product, MODSCAG, based on spectral mixture analysis. We compare them to maps of snow obtained from Landsat ETM+ data, whose 30 m spatial resolution provides nearly 300 samples within a 500 m MODIS nadir pixel. The assessment uses 172 images spanning a range of snow and vegetation conditions, including the Colorado Rocky Mountains, the Upper Rio Grande, California’s Sierra Nevada, and the Nepal Himalaya. MOD10A1 binary and fractional fail to retrieve snow in the transitional periods during accumulation and melt while MODSCAG consistently maintains its retrieval ability during these periods. Averaged over all regions, the RMSE for MOD10A1 fractional is 0.23, whereas the MODSCAG RMSE is 0.10. MODSCAG performs the most consistently through accumulation, mid-winter and melt, with median differences ranging from −0.16 to 0.04 while differences for MOD10A1 fractional range from −0.34 to 0.35. MODSCAG maintains its performance over all land cover classes and throughout a larger range of land surface properties. Characterizing snow cover by spectral mixing is more accurate than empirical methods based on the normalized difference snow index, both for identifying where snow is and is not and for estimating the fractional snow cover within a sensor’s instantaneous field-of-view. Determining the fractional value is particularly important during spring and summer melt in mountainous terrain, where large variations in snow, vegetation and soil occur over small distances and when snow can melt rapidly.     

Beyond the semivariogram: Patterns,scale, and hydrology in a semi-arid landscape

As an alternative to geostatistical modeling, we characterized the hydrology of a semi-arid landscape in southeastern Washington state, USA, by coupling spatial patterns identified in the distributions of relative relief and vegetation with the influence each has on soil moisture storage and evapotranspiration at the appropriate scale. Gauging precipitation, soil moisture, and evapotranspiration over a two-year period while concurrently mapping relative relief and vegetation distributions at three scales ranging from centimeters to 90 m, we determined that soil moisture and soil moisture storage are significantly greater in topographic concavities than in convexities at the microrelief (20–50 cm) scale but are not significantly different in relief features at larger scales. A generalized microrelief surface produced using a two-dimensional Fourier transformation provided a good representation of the distribution of soil moisture within microrelief when scaled to soil moisture values. Applying a spatial point process analysis we determined that big sage are randomly distributed across the landscape at all scales, suggesting that lysimeter-derived sage evapotranspiration rates also be distributed randomly across the landscape. Where sage were not present, we applied an autoregressive moving-average model conditioned on grass lysimeter measurements to derive evapotranspiration rates. Combining these hydrologic spatial patterns derived from distributions in relief and vegetation with measured precipitation inputs and evapotranspiration outputs, we created a spatially distributed model of soil moisture which we tested against measured values over an eight-week period. The model provides accurate characterization of soil moisture, allows estimates of soil moisture between measurement points, permits extrapolation of soil moisture distributions outside the gauged area, and maintains small-scale variability when aggregating soil moisture to successively larger scales.     

Characterization of recharge through complex vadose zone of a granitic aquifer by time-lapse electrical resistivity tomography

The vadose zone is the main region controlling water movement from the land surface to the aquifer and has a very complex structure. The use of non-invasive or minimally invasive geophysical methods especially electrical resistivity imaging is a cost-effective approach adapted for long-term monitoring of the vadose zone. The main aim of this work is to know the fractures in the vadose zone, of granitic terrene, through which the recharge or preferred path recharge to the aquifer takes place and thus to relate moisture and electrical resistivity. Time lapse electrical resistivity tomography (TLERT) experiment was carried out in the vadose zone of granitic terrene at the Indian Geophysical Research Institute, Hyderabad along two profiles to a depth of 18 m and 13 m each. The profiles are 300 m apart. Piezometric, rainfall and soil moisture data were recorded to correlate with changes in the rainfall recharge. These TLERT difference images showed that the conductivity distribution was consistent with the recharge occurring along the minor fractures. We mapped the fractures in hard rock or granites to see the effect of the recharge on resistivity variation and estimation of moisture content. These fractures act as the preferred pathways for the recharge to take place. A good correlation between the soil moisture and resistivity is established in the vadose zone of granitic aquifer. Since the vadose zone exhibits extremely high variability, both in space and time, the surface geophysical investigations such as TLERT have been a simple and useful method to characterize the vadose zone, which would not have been possible with the point measurements alone. The analyses of the pseudosection with time indicate clearly that the assumption of the piston flow of the moisture front is not valid in hard rocks. The outcome of this study may provide some indirect parameters to the well known Richard's equation in studying the unsaturated zone.     

Vertical distribution of HTO and 125I− transport parameters in Boom Clay in the Essen-1 borehole (Mol,Belgium)

In the frame of the R&D activities performed on the Boom Clay for assessing the suitability of deep clayey formations for radioactive waste disposal, the transferability of the scientific results obtained on the Boom Clay in Mol to the whole Campine Basin is investigated. Boreholes were drilled at different locations (e.g. Mol, Doel, Essen) and cores were sampled over the entire thickness of the Boom Clay formation on which the migration parameters for iodide and tritiated water (HTO) are determined.At Essen, the transport parameters in the Boom Clay can be considered as homogeneous in the range from 159 m to 241 m Below Drilling Table. The average hydraulic conductivity is (5.4 ± 1.7) × 10⁻¹² m/s. The average ηR value for iodide is 0.25 ± 0.03 and 0.42 ± 0.05 for HTO. For HTO, this high value is mainly due to a higher value in the Putte Member (0.46 ± 0.03) compared to the other members (0.39 ± 0.02). The apparent diffusion coefficient is (1.3 ± 0.1) × 10⁻¹⁰ m²/s for HTO and (1.1 ± 0.2) × 10⁻¹⁰ m²/s for iodide. The expected effect of ionic strength (increasing with depth) on the ηR value of iodide is of the same size as the measurement error, what might explain why it was not observed.On a lateral (horizontal) level, the hydraulic conductivity at the Essen-1 borehole (5.4 × 10⁻¹² m/s) lies between that of Boom Clay in Mol-1 (2.5 × 10⁻¹² m/s) and that of Boom Clay in Doel-2b (1.4 × 10⁻¹¹ m/s). For iodide, the higher ηR value in Essen-1 and Doel-2b (ηR ≈ 0.25) than in Mol-1 (ηR ≈ 0.16) can partly be explained by a higher ionic strength of the pore water. Apart from the Putte Member at Essen-1, the HTO porosities of the Terhagen Member and the Transition zone in Essen are in the range of the average porosities observed in Mol and Doel (ηR ≈ 0.37–0.39). For both iodide and HTO, the value of the apparent diffusion coefficient D_app is similar in Mol-1 and in Doel-2b, with a clearly higher value for HTO than for iodide. In Essen-1, the apparent diffusion coefficients for iodide and HTO are nearly equal, and slightly smaller than the iodide value in Mol-1/Doel-2b. Accordingly, the HTO apparent diffusion coefficient is considerably smaller in Essen-1 than in Mol-1/Doel-2b.     

Integration of remote sensing data into hydrological models for reservoir management

Abstract

The purpose of this paper is to present the methodology set up to derive catchment soil moisture from Earth Observation (EO) data using microwave spaceborne Synthetic Aperture Radar (SAR) images from ERS satellites and to study the improvements brought about by an assimilation of this information into hydrological models. The methodology used to derive EO data is based on the appropriate selection of land cover types for which the radar signal is mainly sensitive to soil moisture variations. Then a hydrological model is chosen, which can take advantage of the new information brought by remote sensing. The assimilation of soil moisture deduced from EO data into hydrological models is based principally on model parameter updating. The main assumption of this method is that the better the model simulates the current hydrological system, the better the following forecast will be. Another methodology used is a sequential one based on Kalman filtering. These methods have been put forward for use in the European AIMWATER project on the Seine catchment upstream of Paris (France) where dams are operated to alleviate floods in the Paris area.