WorldWideScience

Sample records for soil moisture prediction

  1. Predictability of soil moisture and streamflow on subseasonal timescales: A case study

    Science.gov (United States)

    Orth, Rene; Seneviratne, Sonia I.

    2013-10-01

    Hydrological forecasts constitute an important tool in water resource management, especially in the case of impending extreme events. This study investigates the potential predictability of soil moisture and streamflow in Switzerland using a conceptual model including a simple water balance representation and a snow module. Our results show that simulated soil moisture and streamflow are more predictable (as indicated by significantly improved performance compared to climatology) until lead times of approximately 1 week and 2-3 days, respectively, when using initial soil moisture information and climatological atmospheric forcing. Using also initial snow information and seasonal weather forecasts as forcing, the predictable lead time doubles in case of soil moisture and triples for streamflow. The skill contributions of the additional information vary with altitude; at low altitudes the precipitation forecast is most important, whereas in mountainous areas the temperature forecast and the initial snow information are the most valuable contributors. We find furthermore that the soil moisture and streamflow forecast skills increase with increasing initial soil moisture anomalies. Comparing the respective value of realistic initial conditions and state-of-the-art forcing forecasts, we show that the former are generally more important for soil moisture forecasts, whereas the latter are more valuable for streamflow forecasts. To relate the derived predictabilities to respective soil moisture and streamflow memories investigated in other publications, we additionally illustrate the similarity between the concepts of memory and predictability as measures of persistence in the last part of this study.

  2. Impact of Soil Moisture Initialization on Seasonal Weather Prediction

    Science.gov (United States)

    Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor)

    2002-01-01

    The potential role of soil moisture initialization in seasonal forecasting is illustrated through ensembles of simulations with the NASA Seasonal-to-Interannual Prediction Project (NSIPP) model. For each boreal summer during 1997-2001, we generated two 16-member ensembles of 3-month simulations. The first, "AMIP-style" ensemble establishes the degree to which a perfect prediction of SSTs would contribute to the seasonal prediction of precipitation and temperature over continents. The second ensemble is identical to the first, except that the land surface is also initialized with "realistic" soil moisture contents through the continuous prior application (within GCM simulations leading up to the start of the forecast period) of a daily observational precipitation data set and the associated avoidance of model drift through the scaling of all surface prognostic variables. A comparison of the two ensembles shows that soil moisture initialization has a statistically significant impact on summertime precipitation and temperature over only a handful of continental regions. These regions agree, to first order, with regions that satisfy three conditions: (1) a tendency toward large initial soil moisture anomalies, (2) a strong sensitivity of evaporation to soil moisture, and (3) a strong sensitivity of precipitation to evaporation. The degree to which the initialization improves forecasts relative to observations is mixed, reflecting a critical need for the continued development of model parameterizations and data analysis strategies.

  3. Identification of optimal soil hydraulic functions and parameters for predicting soil moisture

    Science.gov (United States)

    We examined the accuracy of several commonly used soil hydraulic functions and associated parameters for predicting observed soil moisture data. We used six combined methods formed by three commonly used soil hydraulic functions – i.e., Brooks and Corey (1964) (BC), Campbell (19...

  4. Use of satellite and modeled soil moisture data for predicting event soil loss at plot scale

    Science.gov (United States)

    Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

    2015-09-01

    The potential of coupling soil moisture and a Universal Soil Loss Equation-based (USLE-based) model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e., the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the USLE enhances the capability of the model to account for variations in event soil losses, the soil moisture being an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to ~ 0.35 and a root mean square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

  5. Use of satellite and modelled soil moisture data for predicting event soil loss at plot scale

    Science.gov (United States)

    Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.

    2015-03-01

    The potential of coupling soil moisture and a~USLE-based model for event soil loss estimation at plot scale is carefully investigated at the Masse area, in Central Italy. The derived model, named Soil Moisture for Erosion (SM4E), is applied by considering the unavailability of in situ soil moisture measurements, by using the data predicted by a soil water balance model (SWBM) and derived from satellite sensors, i.e. the Advanced SCATterometer (ASCAT). The soil loss estimation accuracy is validated using in situ measurements in which event observations at plot scale are available for the period 2008-2013. The results showed that including soil moisture observations in the event rainfall-runoff erosivity factor of the RUSLE/USLE, enhances the capability of the model to account for variations in event soil losses, being the soil moisture an effective alternative to the estimated runoff, in the prediction of the event soil loss at Masse. The agreement between observed and estimated soil losses (through SM4E) is fairly satisfactory with a determination coefficient (log-scale) equal to of ~ 0.35 and a root-mean-square error (RMSE) of ~ 2.8 Mg ha-1. These results are particularly significant for the operational estimation of soil losses. Indeed, currently, soil moisture is a relatively simple measurement at the field scale and remote sensing data are also widely available on a global scale. Through satellite data, there is the potential of applying the SM4E model for large-scale monitoring and quantification of the soil erosion process.

  6. Coupling rainfall observations and satellite soil moisture for predicting event soil loss in Central Italy

    Science.gov (United States)

    Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang

    2015-04-01

    The accuracy of water soil loss prediction depends on the ability of the model to account for effects of the physical phenomena causing the output and the accuracy by which the parameters have been determined. The process based models require considerable effort to obtain appropriate parameter values and their failure to produce better results than achieved using the USLE/RUSLE model, encourages the use of the USLE/RUSLE model in roles of which it was not designed. In particular it is widely used in watershed models even at the event temporal scale. At hillslope scale, spatial variability in soil and vegetation result in spatial variations in soil moisture and consequently in runoff within the area for which soil loss estimation is required, so the modeling approach required to produce those estimates needs to be sensitive to those spatial variations in runoff. Some models include explicit consideration of runoff in determining the erosive stresses but this increases the uncertainty of the prediction due to the difficulty in parameterising the models also because the direct measures of surface runoff are rare. The same remarks are effective also for the USLE/RUSLE models including direct consideration of runoff in the erosivity factor (i.e. USLE-M by Kinnell and Risse, 1998, and USLE-MM by Bagarello et al., 2008). Moreover actually most of the rainfall-runoff models are based on the knowledge of the pre-event soil moisture that is a fundamental variable in the rainfall-runoff transformation. In addiction soil moisture is a readily available datum being possible to have easily direct pre-event measures of soil moisture using in situ sensors or satellite observations at larger spatial scale; it is also possible to derive the antecedent water content with soil moisture simulation models. The attempt made in the study is to use the pre-event soil moisture to account for the spatial variation in runoff within the area for which the soil loss estimates are required. More

  7. On the assimilation of satellite derived soil moisture in numerical weather prediction models

    Science.gov (United States)

    Drusch, M.

    2006-12-01

    Satellite derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analysed from the modelled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. Three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-range Weather Forecasts (ECMWF) have been performed for the two months period of June and July 2002: A control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating bias corrected TMI (TRMM Microwave Imager) derived soil moisture over the southern United States through a nudging scheme using 6-hourly departures. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analysed in the nudging experiment is the most accurate estimate when compared against in-situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage. The transferability of the results to other satellite derived soil moisture data sets will be discussed.

  8. Historical precipitation predictably alters the shape and magnitude of microbial functional response to soil moisture.

    Science.gov (United States)

    Averill, Colin; Waring, Bonnie G; Hawkes, Christine V

    2016-05-01

    Soil moisture constrains the activity of decomposer soil microorganisms, and in turn the rate at which soil carbon returns to the atmosphere. While increases in soil moisture are generally associated with increased microbial activity, historical climate may constrain current microbial responses to moisture. However, it is not known if variation in the shape and magnitude of microbial functional responses to soil moisture can be predicted from historical climate at regional scales. To address this problem, we measured soil enzyme activity at 12 sites across a broad climate gradient spanning 442-887 mm mean annual precipitation. Measurements were made eight times over 21 months to maximize sampling during different moisture conditions. We then fit saturating functions of enzyme activity to soil moisture and extracted half saturation and maximum activity parameter values from model fits. We found that 50% of the variation in maximum activity parameters across sites could be predicted by 30-year mean annual precipitation, an indicator of historical climate, and that the effect is independent of variation in temperature, soil texture, or soil carbon concentration. Based on this finding, we suggest that variation in the shape and magnitude of soil microbial response to soil moisture due to historical climate may be remarkably predictable at regional scales, and this approach may extend to other systems. If historical contingencies on microbial activities prove to be persistent in the face of environmental change, this approach also provides a framework for incorporating historical climate effects into biogeochemical models simulating future global change scenarios. © 2016 John Wiley & Sons Ltd.

  9. Predicting cation exchange capacity from hygroscopic moisture in agricultural soils of Western Europe

    Energy Technology Data Exchange (ETDEWEB)

    Torrent, J.; Campillo, M.C. del; Barrón, V.

    2015-07-01

    Soil cation exchange capacity (CEC) depends on the extent and negative charge density of surfaces of soil mineral and organic components. Soil water sorption also depends on the extent of such surfaces, giving thus way to significant relationships between CEC and hygroscopic moisture (HM) in many soils. In this work, we explored whether CEC could be accurately predicted from HM in agricultural soils of Mediterranean and humid temperate areas in Western Europe. For this purpose, we examined 243 soils across a wide variation range of their intrinsic properties. Soil CEC was determined using 1 M ammonium acetate at pH 7 and HM at an equilibrium air relative humidity (RH) of 43% (HM43). Most of the variation of soil CEC was explained by HM43 through a linear function (CEC = 1.4 + 0.78HM43; R2 = 0.962; standard deviation = 2.30 cmolc/kg). Coefficients of the regression equation were similar for subgroups of soils differing in moisture regime, clay mineralogy, carbonate content and organic carbon content. Therefore, soil hygroscopic moisture measurements at a fixed RH level provided a simple, robust, inexpensive method for predicting soil CEC. (Author)

  10. Initializing numerical weather prediction models with satellite-derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

    Science.gov (United States)

    Drusch, M.

    2007-02-01

    Satellite-derived surface soil moisture data sets are readily available and have been used successfully in hydrological applications. In many operational numerical weather prediction systems the initial soil moisture conditions are analyzed from the modeled background and 2 m temperature and relative humidity. This approach has proven its efficiency to improve surface latent and sensible heat fluxes and consequently the forecast on large geographical domains. However, since soil moisture is not always related to screen level variables, model errors and uncertainties in the forcing data can accumulate in root zone soil moisture. Remotely sensed surface soil moisture is directly linked to the model's uppermost soil layer and therefore is a stronger constraint for the soil moisture analysis. For this study, three data assimilation experiments with the Integrated Forecast System (IFS) of the European Centre for Medium-Range Weather Forecasts (ECMWF) have been performed for the 2-month period of June and July 2002: a control run based on the operational soil moisture analysis, an open loop run with freely evolving soil moisture, and an experimental run incorporating TMI (TRMM Microwave Imager) derived soil moisture over the southern United States. In this experimental run the satellite-derived soil moisture product is introduced through a nudging scheme using 6-hourly increments. Apart from the soil moisture analysis, the system setup reflects the operational forecast configuration including the atmospheric 4D-Var analysis. Soil moisture analyzed in the nudging experiment is the most accurate estimate when compared against in situ observations from the Oklahoma Mesonet. The corresponding forecast for 2 m temperature and relative humidity is almost as accurate as in the control experiment. Furthermore, it is shown that the soil moisture analysis influences local weather parameters including the planetary boundary layer height and cloud coverage.

  11. The moisture response of soil heterotrophic respiration: interaction with soil properties

    DEFF Research Database (Denmark)

    Moyano, F E; Vasilyeva, N; Bouckaert, L

    2012-01-01

    the heterotrophic respiration response to moisture have limited empirical support and introduce an uncertainty of at least 4% in global soil carbon stock predictions by 2100. The necessity of improving the representation of this relationship in models has been highlighted in recent studies. Here we present a data......Soil moisture is of primary importance for predicting the evolution of soil carbon stocks and fluxes, both because it strongly controls organic matter decomposition and because it is predicted to change at global scales in the following decades. However, the soil functions used to model......-driven analysis of soil moisture-respiration relations based on 90 soils. With the use of linear models we show how the relationship between soil heterotrophic respiration and different measures of soil moisture is consistently affected by soil properties. The empirical models derived include main effects...

  12. Impact of Direct Soil Moisture and Revised Soil Moisture Index Methods on Hydrologic Predictions in an Arid Climate

    Directory of Open Access Journals (Sweden)

    Milad Jajarmizadeh

    2014-01-01

    Full Text Available The soil and water assessment tool (SWAT is a physically based model that is used extensively to simulate hydrologic processes in a wide range of climates around the world. SWAT uses spatial hydrometeorological data to simulate runoff through the computation of a retention curve number. The objective of the present study was to compare the performance of two approaches used for the calculation of curve numbers in SWAT, that is, the Revised Soil Moisture Index (SMI, which is based on previous meteorological conditions, and the Soil Moisture Condition II (SMCII, which is based on soil features for the prediction of flow. The results showed that the sensitive parameters for the SMI method are land-use and land-cover features. However, for the SMCII method, the soil and the channel are the sensitive parameters. The performances of the SMI and SMCII methods were analyzed using various indices. We concluded that the fair performance of the SMI method in an arid region may be due to the inherent characteristics of the method since it relies mostly on previous meteorological conditions and does not account for the soil features of the catchment.

  13. Use of Soil Moisture Variability in Artificial Neural Network Retrieval of Soil Moisture

    Directory of Open Access Journals (Sweden)

    Bert Veenendaal

    2009-12-01

    Full Text Available Passive microwave remote sensing is one of the most promising techniques for soil moisture retrieval. However, the inversion of soil moisture from brightness temperature observations is not straightforward, as it is influenced by numerous factors such as surface roughness, vegetation cover, and soil texture. Moreover, the relationship between brightness temperature, soil moisture and the factors mentioned above is highly non-linear and ill-posed. Consequently, Artificial Neural Networks (ANNs have been used to retrieve soil moisture from microwave data, but with limited success when dealing with data different to that from the training period. In this study, an ANN is tested for its ability to predict soil moisture at 1 km resolution on different dates following training at the same site for a specific date. A novel approach that utilizes information on the variability of soil moisture, in terms of its mean and standard deviation for a (sub region of spatial dimension up to 40 km, is used to improve the current retrieval accuracy of the ANN method. A comparison between the ANN with and without the use of the variability information showed that this enhancement enables the ANN to achieve an average Root Mean Square Error (RMSE of around 5.1% v/v when using the variability information, as compared to around 7.5% v/v without it. The accuracy of the soil moisture retrieval was further improved by the division of the target site into smaller regions down to 4 km in size, with the spatial variability of soil moisture calculated from within the smaller region used in the ANN. With the combination of an ANN architecture of a single hidden layer of 20 neurons and the dual-polarized brightness temperatures as input, the proposed use of variability and sub-region methodology achieves an average retrieval accuracy of 3.7% v/v. Although this accuracy is not the lowest as comparing to the research in this field, the main contribution is the ability of ANN in

  14. Assesment of a soil moisture retrieval with numerical weather prediction model temperature

    Science.gov (United States)

    The effect of using a Numerical Weather Prediction (NWP) soil temperature product instead of estimates provided by concurrent 37 GHz data on satellite-based passive microwave retrieval of soil moisture retrieval was evaluated. This was prompted by the change in system configuration of preceding mult...

  15. Short communication: Predicting cation exchange capacity from hygroscopic moisture in agricultural soils of Western Europe

    Directory of Open Access Journals (Sweden)

    José Torrent

    2015-12-01

    Full Text Available Soil cation exchange capacity (CEC depends on the extent and negative charge density of surfaces of soil mineral and organic components. Soil water sorption also depends on the extent of such surfaces, giving thus way to significant relationships between CEC and hygroscopic moisture (HM in many soils. In this work, we explored whether CEC could be accurately predicted from HM in agricultural soils of Mediterranean and humid temperate areas in Western Europe. For this purpose, we examined 243 soils across a wide variation range of their intrinsic properties. Soil CEC was determined using 1 M ammonium acetate at pH 7 and HM at an equilibrium air relative humidity (RH of 43% (HM43. Most of the variation of soil CEC was explained by HM43 through a linear function (CEC = 1.4 + 0.78HM43; R2 = 0.962; standard deviation = 2.30 cmolc/kg. Coefficients of the regression equation were similar for subgroups of soils differing in moisture regime, clay mineralogy, carbonate content and organic carbon content. Therefore, soil hygroscopic moisture measurements at a fixed RH level provided a simple, robust, inexpensive method for predicting soil CEC.

  16. Linking precipitation, evapotranspiration and soil moisture content for the improvement of predictability over land

    Science.gov (United States)

    Catalano, Franco; Alessandri, Andrea; De Felice, Matteo

    2013-04-01

    Climate change scenarios are expected to show an intensification of the hydrological cycle together with modifications of evapotranspiration and soil moisture content. Evapotranspiration changes have been already evidenced for the end of the 20th century. The variance of evapotranspiration has been shown to be strongly related to the variance of precipitation over land. Nevertheless, the feedbacks between evapotranspiration, soil moisture and precipitation have not yet been completely understood at present-day. Furthermore, soil moisture reservoirs are associated to a memory and thus their proper initialization may have a strong influence on predictability. In particular, the linkage between precipitation and soil moisture is modulated by the effects on evapotranspiration. Therefore, the investigation of the coupling between these variables appear to be of primary importance for the improvement of predictability over the continents. The coupled manifold (CM) technique (Navarra and Tribbia 2005) is a method designed to separate the effects of the variability of two variables which are connected. This method has proved to be successful for the analysis of different climate fields, like precipitation, vegetation and sea surface temperature. In particular, the coupled variables reveal patterns that may be connected with specific phenomena, thus providing hints regarding potential predictability. In this study we applied the CM to recent observational datasets of precipitation (from CRU), evapotranspiration (from GIMMS and MODIS satellite-based estimates) and soil moisture content (from ESA) spanning a time period of 23 years (1984-2006) with a monthly frequency. Different data stratification (monthly, seasonal, summer JJA) have been employed to analyze the persistence of the patterns and their characteristical time scales and seasonality. The three variables considered show a significant coupling among each other. Interestingly, most of the signal of the

  17. The Contribution of Soil Moisture Information to Forecast Skill: Two Studies

    Science.gov (United States)

    Koster, Randal

    2010-01-01

    This talk briefly describes two recent studies on the impact of soil moisture information on hydrological and meteorological prediction. While the studies utilize soil moisture derived from the integration of large-scale land surface models with observations-based meteorological data, the results directly illustrate the potential usefulness of satellite-derived soil moisture information (e.g., from SMOS and SMAP) for applications in prediction. The first study, the GEWEX- and ClIVAR-sponsored GLACE-2 project, quantifies the contribution of realistic soil moisture initialization to skill in subseasonal forecasts of precipitation and air temperature (out to two months). The multi-model study shows that soil moisture information does indeed contribute skill to the forecasts, particularly for air temperature, and particularly when the initial local soil moisture anomaly is large. Furthermore, the skill contributions tend to be larger where the soil moisture initialization is more accurate, as measured by the density of the observational network contributing to the initialization. The second study focuses on streamflow prediction. The relative contributions of snow and soil moisture initialization to skill in streamflow prediction at seasonal lead, in the absence of knowledge of meteorological anomalies during the forecast period, were quantified with several land surface models using uniquely designed numerical experiments and naturalized streamflow data covering mUltiple decades over the western United States. In several basins, accurate soil moisture initialization is found to contribute significant levels of predictive skill. Depending on the date of forecast issue, the contributions can be significant out to leads of six months. Both studies suggest that improvements in soil moisture initialization would lead to increases in predictive skill. The relevance of SMOS and SMAP satellite-based soil moisture information to prediction are discussed in the context of these

  18. Preliminary results of an attempt to provide soil moisture datasets in order to verify numerical weather prediction models

    International Nuclear Information System (INIS)

    Cassardo, C.; Loglisci, N.

    2005-01-01

    In the recent years, there has been a significant growth in the recognition of the soil moisture importance in large-scale hydrology and climate modelling. Soil moisture is a lower boundary condition, which rules the partitioning of energy in terms of sensible and latent heat flux. Wrong estimations of soil moisture lead to wrong simulation of the surface layer evolution and hence precipitations and cloud cover forecasts could be consequently affected. This is true for large scale medium-range weather forecasts as well as for local-scale short range weather forecasts, particularly in those situations in which local convection is well developed. Unfortunately; despite the importance of this physical parameter there are only few soil moisture data sets sparse in time and in space around in the world. Due to this scarcity of soil moisture observations, we developed an alternative method to provide soil moisture datasets in order to verify numerical weather prediction models. In this paper are presented the preliminary results of an attempt to verify soil moisture fields predicted by a mesoscale model. The data for the comparison were provided by the simulations of the diagnostic land surface scheme LSPM (Land Surface Process Model), widely used at the Piedmont Regional Weather Service for agro-meteorological purposes. To this end, LSPM was initialized and driven by Synop observations, while the surface (vegetation and soil) parameter values were initialized by ECOCLIMAP global dataset at 1km 2 resolution

  19. Application of Modular Modeling System to Predict Evaporation, Infiltration, Air Temperature, and Soil Moisture

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    Boggs, Johnny; Birgan, Latricia J.; Tsegaye, Teferi; Coleman, Tommy; Soman, Vishwas

    1997-01-01

    Models are used for numerous application including hydrology. The Modular Modeling System (MMS) is one of the few that can simulate a hydrology process. MMS was tested and used to compare infiltration, soil moisture, daily temperature, and potential and actual evaporation for the Elinsboro sandy loam soil and the Mattapex silty loam soil in the Microwave Radiometer Experiment of Soil Moisture Sensing at Beltsville Agriculture Research Test Site in Maryland. An input file for each location was created to nut the model. Graphs were plotted, and it was observed that the model gave a good representation for evaporation for both plots. In comparing the two plots, it was noted that infiltration and soil moisture tend to peak around the same time, temperature peaks in July and August and the peak evaporation was observed on September 15 and July 4 for the Elinsboro Mattapex plot respectively. MMS can be used successfully to predict hydrological processes as long as the proper input parameters are available.

  20. Using soil moisture forecasts for sub-seasonal summer temperature predictions in Europe

    Science.gov (United States)

    Orth, René; Seneviratne, Sonia I.

    2014-12-01

    Soil moisture exhibits outstanding memory characteristics and plays a key role within the climate system. Especially through its impacts on the evapotranspiration of soils and plants, it may influence the land energy balance and therefore surface temperature. These attributes make soil moisture an important variable in the context of weather and climate forecasting. In this study we investigate the value of (initial) soil moisture information for sub-seasonal temperature forecasts. For this purpose we employ a simple water balance model to infer soil moisture from streamflow observations in 400 catchments across Europe. Running this model with forecasted atmospheric forcing, we derive soil moisture forecasts, which we then translate into temperature forecasts using simple linear relationships. The resulting temperature forecasts show skill beyond climatology up to 2 weeks in most of the considered catchments. Even if forecasting skills are rather small at longer lead times with significant skill only in some catchments at lead times of 3 and 4 weeks, this soil moisture-based approach shows local improvements compared to the monthly European Centre for Medium Range Weather Forecasting (ECMWF) temperature forecasts at these lead times. For both products (soil moisture-only forecast and ECMWF forecast), we find comparable or better forecast performance in the case of extreme events, especially at long lead times. Even though a product based on soil moisture information alone is not of practical relevance, our results indicate that soil moisture (memory) is a potentially valuable contributor to temperature forecast skill. Investigating the underlying soil moisture of the ECMWF forecasts we find good agreement with the simple model forecasts, especially at longer lead times. Analyzing the drivers of the temperature forecast skills we find that they are mainly controlled by the strengths of (1) the soil moisture-temperature coupling and (2) the soil moisture memory. We

  1. Analysis of soil moisture memory from observations in Europe

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2012-08-01

    Soil moisture is known to show distinctive persistence characteristics compared to other quantities in the climate system. As soil moisture is governing land-atmosphere feedbacks to a large extent, its persistence can provide potential to improve seasonal climate predictions. So far, many modeling studies have investigated the nature of soil moisture memory, with consistent, but model-dependent results. This study investigates soil moisture memory in long-term observational records based on data from five stations across Europe. We investigate spatial and seasonal variations in soil moisture memory and identify their main climatic drivers. Also, we test an existing framework and introduce an extension thereof to approximate soil moisture memory and evaluate the contributions of its driving processes. At the analyzed five sites, we identify the variability of initial soil moisture divided by that of the accumulated forcing over the considered time frame as a main driver of soil moisture memory that reflects the impact of the precipitation regime and of soil and vegetation characteristics. Another important driver is found to be the correlation of initial soil moisture with subsequent forcing that captures forcing memory as it propagates to the soil and also land-atmosphere interactions. Thereby, the role of precipitation is found to be dominant for the forcing. In contrast to results from previous modeling studies, the runoff and evapotranspiration sensitivities to soil moisture are found to have only a minor influence on soil moisture persistence at the analyzed sites. For the central European sites, the seasonal cycles of soil moisture memory display a maximum in late summer and a minimum in spring. An opposite seasonal cycle is found at the analyzed site in Italy. High soil moisture memory is shown to last up to 40 days in some seasons at most sites. Extremely dry or wet states of the soil tend to increase soil moisture memory, suggesting enhanced prediction

  2. An Approach to Flooding Inundation Combining the Streamflow Prediction Tool (SPT) and Downscaled Soil Moisture

    Science.gov (United States)

    Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.

    2017-12-01

    Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.

  3. Evaluation of Assimilated SMOS Soil Moisture Data for US Cropland Soil Moisture Monitoring

    Science.gov (United States)

    Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping

    2016-01-01

    Remotely sensed soil moisture data can provide timely, objective and quantitative crop soil moisture information with broad geospatial coverage and sufficiently high resolution observations collected throughout the growing season. This paper evaluates the feasibility of using the assimilated ESA Soil Moisture Ocean Salinity (SMOS)Mission L-band passive microwave data for operational US cropland soil surface moisture monitoring. The assimilated SMOS soil moisture data are first categorized to match with the United States Department of Agriculture (USDA)National Agricultural Statistics Service (NASS) survey based weekly soil moisture observation data, which are ordinal. The categorized assimilated SMOS soil moisture data are compared with NASSs survey-based weekly soil moisture data for consistency and robustness using visual assessment and rank correlation. Preliminary results indicate that the assimilated SMOS soil moisture data highly co-vary with NASS field observations across a large geographic area. Therefore, SMOS data have great potential for US operational cropland soil moisture monitoring.

  4. Multiscale soil moisture estimates using static and roving cosmic-ray soil moisture sensors

    Science.gov (United States)

    McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross

    2017-12-01

    Soil moisture plays a critical role in land surface processes and as such there has been a recent increase in the number and resolution of satellite soil moisture observations and the development of land surface process models with ever increasing resolution. Despite these developments, validation and calibration of these products has been limited because of a lack of observations on corresponding scales. A recently developed mobile soil moisture monitoring platform, known as the rover, offers opportunities to overcome this scale issue. This paper describes methods, results and testing of soil moisture estimates produced using rover surveys on a range of scales that are commensurate with model and satellite retrievals. Our investigation involved static cosmic-ray neutron sensors and rover surveys across both broad (36 × 36 km at 9 km resolution) and intensive (10 × 10 km at 1 km resolution) scales in a cropping district in the Mallee region of Victoria, Australia. We describe approaches for converting rover survey neutron counts to soil moisture and discuss the factors controlling soil moisture variability. We use independent gravimetric and modelled soil moisture estimates collected across both space and time to validate rover soil moisture products. Measurements revealed that temporal patterns in soil moisture were preserved through time and regression modelling approaches were utilised to produce time series of property-scale soil moisture which may also have applications in calibration and validation studies or local farm management. Intensive-scale rover surveys produced reliable soil moisture estimates at 1 km resolution while broad-scale surveys produced soil moisture estimates at 9 km resolution. We conclude that the multiscale soil moisture products produced in this study are well suited to future analysis of satellite soil moisture retrievals and finer-scale soil moisture models.

  5. Downscaling Satellite Data for Predicting Catchment-scale Root Zone Soil Moisture with Ground-based Sensors and an Ensemble Kalman Filter

    Science.gov (United States)

    Lin, H.; Baldwin, D. C.; Smithwick, E. A. H.

    2015-12-01

    Predicting root zone (0-100 cm) soil moisture (RZSM) content at a catchment-scale is essential for drought and flood predictions, irrigation planning, weather forecasting, and many other applications. Satellites, such as the NASA Soil Moisture Active Passive (SMAP), can estimate near-surface (0-5 cm) soil moisture content globally at coarse spatial resolutions. We develop a hierarchical Ensemble Kalman Filter (EnKF) data assimilation modeling system to downscale satellite-based near-surface soil moisture and to estimate RZSM content across the Shale Hills Critical Zone Observatory at a 1-m resolution in combination with ground-based soil moisture sensor data. In this example, a simple infiltration model within the EnKF-model has been parameterized for 6 soil-terrain units to forecast daily RZSM content in the catchment from 2009 - 2012 based on AMSRE. LiDAR-derived terrain variables define intra-unit RZSM variability using a novel covariance localization technique. This method also allows the mapping of uncertainty with our RZSM estimates for each time-step. A catchment-wide satellite-to-surface downscaling parameter, which nudges the satellite measurement closer to in situ near-surface data, is also calculated for each time-step. We find significant differences in predicted root zone moisture storage for different terrain units across the experimental time-period. Root mean square error from a cross-validation analysis of RZSM predictions using an independent dataset of catchment-wide in situ Time-Domain Reflectometry (TDR) measurements ranges from 0.060-0.096 cm3 cm-3, and the RZSM predictions are significantly (p < 0.05) correlated with TDR measurements [r = 0.47-0.68]. The predictive skill of this data assimilation system is similar to the Penn State Integrated Hydrologic Modeling (PIHM) system. Uncertainty estimates are significantly (p < 0.05) correlated to cross validation error during wet and dry conditions, but more so in dry summer seasons. Developing an

  6. Validation of soil moisture ocean salinity (SMOS) satellite soil moisture products

    Science.gov (United States)

    The surface soil moisture state controls the partitioning of precipitation into infiltration and runoff. High-resolution observations of soil moisture will lead to improved flood forecasts, especially for intermediate to large watersheds where most flood damage occurs. Soil moisture is also key in d...

  7. Use of digital images to estimate soil moisture

    Directory of Open Access Journals (Sweden)

    João F. C. dos Santos

    Full Text Available ABSTRACT The objective of this study was to analyze the relation between the moisture and the spectral response of the soil to generate prediction models. Samples with different moisture contents were prepared and photographed. The photographs were taken under homogeneous light condition and with previous correction for the white balance of the digital photograph camera. The images were processed for extraction of the median values in the Red, Green and Blue bands of the RGB color space; Hue, Saturation and Value of the HSV color space; and values of the digital numbers of a panchromatic image obtained from the RGB bands. The moisture of the samples was determined with the thermogravimetric method. Regression models were evaluated for each image type: RGB, HSV and panchromatic. It was observed the darkening of the soil with the increase of moisture. For each type of soil, a model with best fit was observed and to use these models for prediction purposes, it is necessary to choose the model with best fit in advance, according to the soil characteristics. Soil moisture estimation as a function of its spectral response by digital image processing proves promising.

  8. Enhancing Noah Land Surface Model Prediction Skill over Indian Subcontinent by Assimilating SMOPS Blended Soil Moisture

    Directory of Open Access Journals (Sweden)

    Akhilesh S. Nair

    2016-11-01

    Full Text Available In the present study, soil moisture assimilation is conducted over the Indian subcontinent, using the Noah Land Surface Model (LSM and the Soil Moisture Operational Products System (SMOPS observations by utilizing the Ensemble Kalman Filter. The study is conducted in two stages involving assimilation of soil moisture and simulation of brightness temperature (Tb using radiative transfer scheme. The results of data assimilation in the form of simulated Surface Soil Moisture (SSM maps are evaluated for the Indian summer monsoonal months of June, July, August, September (JJAS using the Land Parameter Retrieval Model (LPRM AMSR-E soil moisture as reference. Results of comparative analysis using the Global land Data Assimilation System (GLDAS SSM is also discussed over India. Data assimilation using SMOPS soil moisture shows improved prediction over the Indian subcontinent, with an average correlation of 0.96 and average root mean square difference (RMSD of 0.0303 m3/m3. The results are promising in comparison with the GLDAS SSM, which has an average correlation of 0.93 and average RMSD of 0.0481 m3/m3. In the second stage of the study, the assimilated soil moisture is used to simulate X-band brightness temperature (Tb at an incidence angle of 55° using the Community Microwave Emission Model (CMEM Radiative transfer Model (RTM. This is aimed to study the sensitivity of the parameterization scheme on Tb simulation over the Indian subcontinent. The result of Tb simulation shows that the CMEM parameterization scheme strongly influences the simulated top of atmosphere (TOA brightness temperature. Furthermore, the Tb simulations from Wang dielectric model and Kirdyashev vegetation model shows better similarity with the actual AMSR-E Tb over the study region.

  9. Multi-model assessment of the impact of soil moisture initialization on mid-latitude summer predictability

    Science.gov (United States)

    Ardilouze, Constantin; Batté, L.; Bunzel, F.; Decremer, D.; Déqué, M.; Doblas-Reyes, F. J.; Douville, H.; Fereday, D.; Guemas, V.; MacLachlan, C.; Müller, W.; Prodhomme, C.

    2017-12-01

    Land surface initial conditions have been recognized as a potential source of predictability in sub-seasonal to seasonal forecast systems, at least for near-surface air temperature prediction over the mid-latitude continents. Yet, few studies have systematically explored such an influence over a sufficient hindcast period and in a multi-model framework to produce a robust quantitative assessment. Here, a dedicated set of twin experiments has been carried out with boreal summer retrospective forecasts over the 1992-2010 period performed by five different global coupled ocean-atmosphere models. The impact of a realistic versus climatological soil moisture initialization is assessed in two regions with high potential previously identified as hotspots of land-atmosphere coupling, namely the North American Great Plains and South-Eastern Europe. Over the latter region, temperature predictions show a significant improvement, especially over the Balkans. Forecast systems better simulate the warmest summers if they follow pronounced dry initial anomalies. It is hypothesized that models manage to capture a positive feedback between high temperature and low soil moisture content prone to dominate over other processes during the warmest summers in this region. Over the Great Plains, however, improving the soil moisture initialization does not lead to any robust gain of forecast quality for near-surface temperature. It is suggested that models biases prevent the forecast systems from making the most of the improved initial conditions.

  10. Impact of Soil Moisture Assimilation on Land Surface Model Spin-Up and Coupled LandAtmosphere Prediction

    Science.gov (United States)

    Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.

    2016-01-01

    Advances in satellite monitoring of the terrestrial water cycle have led to a concerted effort to assimilate soil moisture observations from various platforms into offline land surface models (LSMs). One principal but still open question is that of the ability of land data assimilation (LDA) to improve LSM initial conditions for coupled short-term weather prediction. In this study, the impact of assimilating Advanced Microwave Scanning Radiometer for EOS (AMSR-E) soil moisture retrievals on coupled WRF Model forecasts is examined during the summers of dry (2006) and wet (2007) surface conditions in the southern Great Plains. LDA is carried out using NASAs Land Information System (LIS) and the Noah LSM through an ensemble Kalman filter (EnKF) approach. The impacts of LDA on the 1) soil moisture and soil temperature initial conditions for WRF, 2) land-atmosphere coupling characteristics, and 3) ambient weather of the coupled LIS-WRF simulations are then assessed. Results show that impacts of soil moisture LDA during the spin-up can significantly modify LSM states and fluxes, depending on regime and season. Results also indicate that the use of seasonal cumulative distribution functions (CDFs) is more advantageous compared to the traditional annual CDF bias correction strategies. LDA performs consistently regardless of atmospheric forcing applied, with greater improvements seen when using coarser, global forcing products. Downstream impacts on coupled simulations vary according to the strength of the LDA impact at the initialization, where significant modifications to the soil moisture flux- PBL-ambient weather process chain are observed. Overall, this study demonstrates potential for future, higher-resolution soil moisture assimilation applications in weather and climate research.

  11. Temporal observations of surface soil moisture using a passive microwave sensor

    International Nuclear Information System (INIS)

    Jackson, T.J.; O'Neill, P.

    1987-01-01

    A series of 10 aircraft flights was conducted over agricultural fields to evaluate relationships between observed surface soil moisture and soil moisture predicted using passive microwave sensor observations. An a priori approach was used to predict values of surface soil moisture for three types of fields: tilled corn, no-till corn with soybean stubble, and idle fields with corn stubble. Acceptable predictions were obtained for the tilled corn fields, while poor results were obtained for the others. The source of error is suspected to be the density and orientation of the surface stubble layer; however, further research is needed to verify this explanation. Temporal comparisons between observed, microwave predicted, and soil water-simulated moisture values showed similar patterns for tilled well-drained fields. Divergences between the observed and simulated measurements were apparent on poorly drained fields. This result may be of value in locating and mapping hydrologic contributing areas

  12. The effect of soil moisture anomalies on maize yield in Germany

    Science.gov (United States)

    Peichl, Michael; Thober, Stephan; Meyer, Volker; Samaniego, Luis

    2018-03-01

    Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intraseasonal predictability of soil moisture to estimate silage maize yield in Germany. We also evaluate how approaches considering soil moisture perform compare to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energiewende (energy transition). Reduced form fixed effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time-varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the interannual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture anomalies in August and September reduce silage maize yield more than 10 %, other factors being equal. In contrast, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictability than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

  13. Enhanced Soil Moisture Initialization Using Blended Soil Moisture Product and Regional Optimization of LSM-RTM Coupled Land Data Assimilation System.

    Science.gov (United States)

    Nair, A. S.; Indu, J.

    2017-12-01

    Prediction of soil moisture dynamics is high priority research challenge because of the complex land-atmosphere interaction processes. Soil moisture (SM) plays a decisive role in governing water and energy balance of the terrestrial system. An accurate SM estimate is imperative for hydrological and weather prediction models. Though SM estimates are available from microwave remote sensing and land surface model (LSM) simulations, it is affected by uncertainties from several sources during estimation. Past studies have generally focused on land data assimilation (DA) for improving LSM predictions by assimilating soil moisture from single satellite sensor. This approach is limited by the large time gap between two consequent soil moisture observations due to satellite repeat cycle of more than three days at the equator. To overcome this, in the present study, we have performed DA using ensemble products from the soil moisture operational product system (SMOPS) blended soil moisture retrievals from different satellite sensors into Noah LSM. Before the assimilation period, the Noah LSM is initialized by cycling through seven multiple loops from 2008 to 2010 forcing with Global data assimilation system (GDAS) data over the Indian subcontinent. We assimilated SMOPS into Noah LSM for a period of two years from 2010 to 2011 using Ensemble Kalman Filter within NASA's land information system (LIS) framework. Results show that DA has improved Noah LSM prediction with a high correlation of 0.96 and low root mean square difference of 0.0303 m3/m3 (figure 1a). Further, this study has also investigated the notion of assimilating microwave brightness temperature (Tb) as a proxy for SM estimates owing to the close proximity of Tb and SM. Preliminary sensitivity analysis show a strong need for regional parameterization of radiative transfer models (RTMs) to improve Tb simulation. Towards this goal, we have optimized the forward RTM using swarm optimization technique for direct Tb

  14. Predicting long-term moisture contents of earthen covers at uranium mill tailings sites

    International Nuclear Information System (INIS)

    Gee, G.W.; Nielson, K.K.; Rogers, V.C.

    1984-09-01

    The three methods for long-term moisture prediction covered in this report are: estimates from water retention (permanent wilting point) data, correlation with climate and soil type, and detailed model simulation. The test results have shown: soils vary greatly in residual moisture. Expected long-term moisture saturation ratios (based on generalized soil characteristics) range from 0.2 to 0.8 for soils ranging in texture from sand to clay, respectively. These values hold for noncompacted field soils. Measured radon diffusion coefficients for soils at 15-bar water contents ranged from 5.0E-2 cm 2 /s to 5.0E-3 cm 2 /s for sands and clays, respectively, at typical field densities. In contrast, fine-textured pit-run earthen materials, subjected to optimum compaction (>85% Proctor density) and dried to the 15-bar water content, ranged from 0.7 to 0.9 moisture saturation. Compacted pit-run soils at these moisture contents exhibited radon diffusion coefficients as low as 3.0E-4 cm 2 /s. The residual moisture saturation for cover soils is not known since no engineered barrier has been in place for more than a few years. A comparison of methods for predicting moisture saturation indicates that model simulations are useful for predicting effects of climatic changes on residual soil moisture, but that long-term moisture also can be predicted with some degree of confidence using generalized soil properties or empirical correlations based both on soils and climatic information. The optimal soil cover design will likely include more than one layer of soil. A two-layer system using a thick (1-m minimum) plant root zone of uncompacted soil placed over a moistened, tightly compacted fine-textured soil is recommended. This design concept has been tested successfully at the Grand Junction, Colorado, tailings piles

  15. Estimating Soil Organic Carbon of Cropland Soil at Different Levels of Soil Moisture Using VIS-NIR Spectroscopy

    Directory of Open Access Journals (Sweden)

    Qinghu Jiang

    2016-09-01

    Full Text Available Soil organic carbon (SOC is an essential property for soil function, fertility and sustainability of agricultural systems. It can be measured with visible and near-infrared reflectance (VIS-NIR spectroscopy efficiently based on empirical equations and spectra data for air/oven-dried samples. However, the spectral signal is interfered with by soil moisture content (MC under in situ conditions, which will affect the accuracy of measurements and calibration transfer among different areas. This study aimed to (1 quantify the influences of MC on SOC prediction by VIS-NIR spectroscopy; and (2 explore the potentials of orthogonal signal correction (OSC and generalized least squares weighting (GLSW methods in the removal of moisture interference. Ninety-eight samples were collected from the Jianghan plain, China, and eight MCs were obtained for each sample by a rewetting process. The VIS-NIR spectra of the rewetted soil samples were measured in the laboratory. Partial least squares regression (PLSR was used to develop SOC prediction models. Specifically, three validation strategies, namely moisture level validation, transferability validation and mixed-moisture validation, were designed to test the potentials of OSC and GLSW in removing the MC effect. Results showed that all of the PLSR models generated at different moisture levels (e.g., 50–100, 250–300 g·kg−1 were moderately successful in SOC predictions (r2pre = 0.58–0.85, RPD = 1.55–2.55. These models, however, could not be transferred to soil samples with different moisture levels. OSC and GLSW methods are useful filter transformations improving model transferability. The GLSW-PLSR model (mean of r2pre = 0.77, root mean square error for prediction (RMSEP = 3.08 g·kg−1, and residual prediction deviations (RPD = 2.09 outperforms the OSC-PLSR model (mean of r2pre = 0.67, RMSEP = 3.67 g·kg−1, and RPD = 1.76 when the moisture-mixed protocol is used. Results demonstrated the use of OSC

  16. Downscaling Coarse Scale Microwave Soil Moisture Product using Machine Learning

    Science.gov (United States)

    Abbaszadeh, P.; Moradkhani, H.; Yan, H.

    2016-12-01

    Soil moisture (SM) is a key variable in partitioning and examining the global water-energy cycle, agricultural planning, and water resource management. It is also strongly coupled with climate change, playing an important role in weather forecasting and drought monitoring and prediction, flood modeling and irrigation management. Although satellite retrievals can provide an unprecedented information of soil moisture at a global-scale, the products might be inadequate for basin scale study or regional assessment. To improve the spatial resolution of SM, this work presents a novel approach based on Machine Learning (ML) technique that allows for downscaling of the satellite soil moisture to fine resolution. For this purpose, the SMAP L-band radiometer SM products were used and conditioned on the Variable Infiltration Capacity (VIC) model prediction to describe the relationship between the coarse and fine scale soil moisture data. The proposed downscaling approach was applied to a western US basin and the products were compared against the available SM data from in-situ gauge stations. The obtained results indicated a great potential of the machine learning technique to derive the fine resolution soil moisture information that is currently used for land data assimilation applications.

  17. Divergent surface and total soil moisture projections under global warming

    Science.gov (United States)

    Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.

    2017-01-01

    Land aridity has been projected to increase with global warming. Such projections are mostly based on off-line aridity and drought metrics applied to climate model outputs but also are supported by climate-model projections of decreased surface soil moisture. Here we comprehensively analyze soil moisture projections from the Coupled Model Intercomparison Project phase 5, including surface, total, and layer-by-layer soil moisture. We identify a robust vertical gradient of projected mean soil moisture changes, with more negative changes near the surface. Some regions of the northern middle to high latitudes exhibit negative annual surface changes but positive total changes. We interpret this behavior in the context of seasonal changes in the surface water budget. This vertical pattern implies that the extensive drying predicted by off-line drought metrics, while consistent with the projected decline in surface soil moisture, will tend to overestimate (negatively) changes in total soil water availability.

  18. The sensitivity of soil respiration to soil temperature, moisture, and carbon supply at the global scale.

    Science.gov (United States)

    Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer

    2017-05-01

    Soil respiration (Rs) is a major pathway by which fixed carbon in the biosphere is returned to the atmosphere, yet there are limits to our ability to predict respiration rates using environmental drivers at the global scale. While temperature, moisture, carbon supply, and other site characteristics are known to regulate soil respiration rates at plot scales within certain biomes, quantitative frameworks for evaluating the relative importance of these factors across different biomes and at the global scale require tests of the relationships between field estimates and global climatic data. This study evaluates the factors driving Rs at the global scale by linking global datasets of soil moisture, soil temperature, primary productivity, and soil carbon estimates with observations of annual Rs from the Global Soil Respiration Database (SRDB). We find that calibrating models with parabolic soil moisture functions can improve predictive power over similar models with asymptotic functions of mean annual precipitation. Soil temperature is comparable with previously reported air temperature observations used in predicting Rs and is the dominant driver of Rs in global models; however, within certain biomes soil moisture and soil carbon emerge as dominant predictors of Rs. We identify regions where typical temperature-driven responses are further mediated by soil moisture, precipitation, and carbon supply and regions in which environmental controls on high Rs values are difficult to ascertain due to limited field data. Because soil moisture integrates temperature and precipitation dynamics, it can more directly constrain the heterotrophic component of Rs, but global-scale models tend to smooth its spatial heterogeneity by aggregating factors that increase moisture variability within and across biomes. We compare statistical and mechanistic models that provide independent estimates of global Rs ranging from 83 to 108 Pg yr -1 , but also highlight regions of uncertainty

  19. Spatial Variation of Soil Type and Soil Moisture in the Regional Atmospheric Modeling System

    Energy Technology Data Exchange (ETDEWEB)

    Buckley, R.

    2001-06-27

    Soil characteristics (texture and moisture) are typically assumed to be initially constant when performing simulations with the Regional Atmospheric Modeling System (RAMS). Soil texture is spatially homogeneous and time-independent, while soil moisture is often spatially homogeneous initially, but time-dependent. This report discusses the conversion of a global data set of Food and Agriculture Organization (FAO) soil types to RAMS soil texture and the subsequent modifications required in RAMS to ingest this information. Spatial variations in initial soil moisture obtained from the National Center for Environmental Predictions (NCEP) large-scale models are also introduced. Comparisons involving simulations over the southeastern United States for two different time periods, one during warmer, more humid summer conditions, and one during cooler, dryer winter conditions, reveals differences in surface conditions related to increases or decreases in near-surface atmospheric moisture con tent as a result of different soil properties. Three separate simulation types were considered. The base case assumed spatially homogeneous soil texture and initial soil moisture. The second case assumed variable soil texture and constant initial soil moisture, while the third case allowed for both variable soil texture and initial soil moisture. The simulation domain was further divided into four geographically distinct regions. It is concluded there is a more dramatic impact on thermodynamic variables (surface temperature and dewpoint) than on surface winds, and a more pronounced variability in results during the summer period. While no obvious trends in surface winds or dewpoint temperature were found relative to observations covering all regions and times, improvement in surface temperatures in most regions and time periods was generally seen with the incorporation of variable soil texture and initial soil moisture.

  20. Development of an Objective High Spatial Resolution Soil Moisture Index

    Science.gov (United States)

    Zavodsky, B.; Case, J.; White, K.; Bell, J. R.

    2015-12-01

    Drought detection, analysis, and mitigation has become a key challenge for a diverse set of decision makers, including but not limited to operational weather forecasters, climatologists, agricultural interests, and water resource management. One tool that is heavily used is the United States Drought Monitor (USDM), which is derived from a complex blend of objective data and subjective analysis on a state-by-state basis using a variety of modeled and observed precipitation, soil moisture, hydrologic, and vegetation and crop health data. The NASA Short-term Prediction Research and Transition (SPoRT) Center currently runs a real-time configuration of the Noah land surface model (LSM) within the NASA Land Information System (LIS) framework. The LIS-Noah is run at 3-km resolution for local numerical weather prediction (NWP) and situational awareness applications at select NOAA/National Weather Service (NWS) forecast offices over the Continental U.S. (CONUS). To enhance the practicality of the LIS-Noah output for drought monitoring and assessing flood potential, a 30+-year soil moisture climatology has been developed in an attempt to place near real-time soil moisture values in historical context at county- and/or watershed-scale resolutions. This LIS-Noah soil moisture climatology and accompanying anomalies is intended to complement the current suite of operational products, such as the North American Land Data Assimilation System phase 2 (NLDAS-2), which are generated on a coarser-resolution grid that may not capture localized, yet important soil moisture features. Daily soil moisture histograms are used to identify the real-time soil moisture percentiles at each grid point according to the county or watershed in which the grid point resides. Spatial plots are then produced that map the percentiles as proxies to the different USDM categories. This presentation will highlight recent developments of this gridded, objective soil moisture index, comparison to subjective

  1. Climate Prediction Center (CPC) NCEP-Global Forecast System (GFS) 0-10cm Soil-Moisture Forecast Product

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Global Forecast System (GFS) forecast 0-10cm soil-moisture data at 37.5km resolution is created at the NOAA Climate Prediction Center for the purpose of near...

  2. Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

    KAUST Repository

    Singh, Gurjeet

    2016-05-05

    Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA’s Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected at two nested scale extents (0.5 km and 3 km) to understand the trend of soil moisture variability across these scales. This ground-based soil moisture sampling was conducted in the 500 km2 Rana watershed situated in eastern India. The study area is characterized as sub-humid, sub-tropical climate with average annual rainfall of about 1456 mm. Three 3x3 km square grids were sampled intensively once a day at 49 locations each, at a spacing of 0.5 km. These intensive sampling locations were selected on the basis of different topography, soil properties and vegetation characteristics. In addition, measurements were also made at 9 locations around each intensive sampling grid at 3 km spacing to cover a 9x9 km square grid. Intensive fine scale soil moisture sampling as well as coarser scale samplings were made using both impedance probes and gravimetric analyses in the study watershed. The ground-based soil moisture samplings were conducted during the day, concurrent with the SMAP descending overpass. Analysis of soil moisture spatial variability in terms of areal mean soil moisture and the statistics of higher-order moments, i.e., the standard deviation, and the coefficient of variation are presented. Results showed that the standard deviation and coefficient of variation of measured soil moisture decreased with extent scale by increasing mean soil moisture. © (2016) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.

  3. Estimating soil hydraulic properties from soil moisture time series by inversion of a dual-permeability model

    Science.gov (United States)

    Dalla Valle, Nicolas; Wutzler, Thomas; Meyer, Stefanie; Potthast, Karin; Michalzik, Beate

    2017-04-01

    Dual-permeability type models are widely used to simulate water fluxes and solute transport in structured soils. These models contain two spatially overlapping flow domains with different parameterizations or even entirely different conceptual descriptions of flow processes. They are usually able to capture preferential flow phenomena, but a large set of parameters is needed, which are very laborious to obtain or cannot be measured at all. Therefore, model inversions are often used to derive the necessary parameters. Although these require sufficient input data themselves, they can use measurements of state variables instead, which are often easier to obtain and can be monitored by automated measurement systems. In this work we show a method to estimate soil hydraulic parameters from high frequency soil moisture time series data gathered at two different measurement depths by inversion of a simple one dimensional dual-permeability model. The model uses an advection equation based on the kinematic wave theory to describe the flow in the fracture domain and a Richards equation for the flow in the matrix domain. The soil moisture time series data were measured in mesocosms during sprinkling experiments. The inversion consists of three consecutive steps: First, the parameters of the water retention function were assessed using vertical soil moisture profiles in hydraulic equilibrium. This was done using two different exponential retention functions and the Campbell function. Second, the soil sorptivity and diffusivity functions were estimated from Boltzmann-transformed soil moisture data, which allowed the calculation of the hydraulic conductivity function. Third, the parameters governing flow in the fracture domain were determined using the whole soil moisture time series. The resulting retention functions were within the range of values predicted by pedotransfer functions apart from very dry conditions, where all retention functions predicted lower matrix potentials

  4. Soil moisture variability across different scales in an Indian watershed for satellite soil moisture product validation

    KAUST Repository

    Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra Belur

    2016-01-01

    Strategic ground-based sampling of soil moisture across multiple scales is necessary to validate remotely sensed quantities such as NASA’s Soil Moisture Active Passive (SMAP) product. In the present study, in-situ soil moisture data were collected

  5. Updated global soil map for the Weather Research and Forecasting model and soil moisture initialization for the Noah land surface model

    Science.gov (United States)

    DY, C. Y.; Fung, J. C. H.

    2016-08-01

    A meteorological model requires accurate initial conditions and boundary conditions to obtain realistic numerical weather predictions. The land surface controls the surface heat and moisture exchanges, which can be determined by the physical properties of the soil and soil state variables, subsequently exerting an effect on the boundary layer meteorology. The initial and boundary conditions of soil moisture are currently obtained via National Centers for Environmental Prediction FNL (Final) Operational Global Analysis data, which are collected operationally in 1° by 1° resolutions every 6 h. Another input to the model is the soil map generated by the Food and Agriculture Organization of the United Nations - United Nations Educational, Scientific and Cultural Organization (FAO-UNESCO) soil database, which combines several soil surveys from around the world. Both soil moisture from the FNL analysis data and the default soil map lack accuracy and feature coarse resolutions, particularly for certain areas of China. In this study, we update the global soil map with data from Beijing Normal University in 1 km by 1 km grids and propose an alternative method of soil moisture initialization. Simulations of the Weather Research and Forecasting model show that spinning-up the soil moisture improves near-surface temperature and relative humidity prediction using different types of soil moisture initialization. Explanations of that improvement and improvement of the planetary boundary layer height in performing process analysis are provided.

  6. Soil Moisture Retrieval Using Convolutional Neural Networks: Application to Passive Microwave Remote Sensing

    Science.gov (United States)

    Hu, Z.; Xu, L.; Yu, B.

    2018-04-01

    A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN). Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF) model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU) acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR) for soil moisture retrieval.

  7. SOIL MOISTURE RETRIEVAL USING CONVOLUTIONAL NEURAL NETWORKS: APPLICATION TO PASSIVE MICROWAVE REMOTE SENSING

    Directory of Open Access Journals (Sweden)

    Z. Hu

    2018-04-01

    Full Text Available A empirical model is established to analyse the daily retrieval of soil moisture from passive microwave remote sensing using convolutional neural networks (CNN. Soil moisture plays an important role in the water cycle. However, with the rapidly increasing of the acquiring technology for remotely sensed data, it's a hard task for remote sensing practitioners to find a fast and convenient model to deal with the massive data. In this paper, the AMSR-E brightness temperatures are used to train CNN for the prediction of the European centre for medium-range weather forecasts (ECMWF model. Compared with the classical inversion methods, the deep learning-based method is more suitable for global soil moisture retrieval. It is very well supported by graphics processing unit (GPU acceleration, which can meet the demand of massive data inversion. Once the model trained, a global soil moisture map can be predicted in less than 10 seconds. What's more, the method of soil moisture retrieval based on deep learning can learn the complex texture features from the big remote sensing data. In this experiment, the results demonstrates that the CNN deployed to retrieve global soil moisture can achieve a better performance than the support vector regression (SVR for soil moisture retrieval.

  8. Evaluation of a Soil Moisture Data Assimilation System Over West Africa

    Science.gov (United States)

    Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.

    2009-05-01

    simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

  9. Hydrological Storage Length Scales Represented by Remote Sensing Estimates of Soil Moisture and Precipitation

    Science.gov (United States)

    Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara

    2018-03-01

    The soil water content profile is often well correlated with the soil moisture state near the surface. They share mutual information such that analysis of surface-only soil moisture is, at times and in conjunction with precipitation information, reflective of deeper soil fluxes and dynamics. This study examines the characteristic length scale, or effective depth Δz, of a simple active hydrological control volume. The volume is described only by precipitation inputs and soil water dynamics evident in surface-only soil moisture observations. To proceed, first an observation-based technique is presented to estimate the soil moisture loss function based on analysis of soil moisture dry-downs and its successive negative increments. Then, the length scale Δz is obtained via an optimization process wherein the root-mean-squared (RMS) differences between surface soil moisture observations and its predictions based on water balance are minimized. The process is entirely observation-driven. The surface soil moisture estimates are obtained from the NASA Soil Moisture Active Passive (SMAP) mission and precipitation from the gauge-corrected Climate Prediction Center daily global precipitation product. The length scale Δz exhibits a clear east-west gradient across the contiguous United States (CONUS), such that large Δz depths (>200 mm) are estimated in wetter regions with larger mean precipitation. The median Δz across CONUS is 135 mm. The spatial variance of Δz is predominantly explained and influenced by precipitation characteristics. Soil properties, especially texture in the form of sand fraction, as well as the mean soil moisture state have a lesser influence on the length scale.

  10. Effects of Soil Temperature and Moisture on Soil Respiration on the Tibetan Plateau.

    Science.gov (United States)

    Bao, Xiaoying; Zhu, Xiaoxue; Chang, Xiaofeng; Wang, Shiping; Xu, Burenbayin; Luo, Caiyun; Zhang, Zhenhua; Wang, Qi; Rui, Yichao; Cui, Xiaoying

    2016-01-01

    Understanding of effects of soil temperature and soil moisture on soil respiration (Rs) under future warming is critical to reduce uncertainty in predictions of feedbacks to atmospheric CO2 concentrations from grassland soil carbon. Intact cores with roots taken from a full factorial, 5-year alpine meadow warming and grazing experiment in the field were incubated at three different temperatures (i.e. 5, 15 and 25°C) with two soil moistures (i.e. 30 and 60% water holding capacity (WHC)) in our study. Another experiment of glucose-induced respiration (GIR) with 4 h of incubation was conducted to determine substrate limitation. Our results showed that high temperature increased Rs and low soil moisture limited the response of Rs to temperature only at high incubation temperature (i.e. 25°C). Temperature sensitivity (Q10) did not significantly decrease over the incubation period, suggesting that substrate depletion did not limit Rs. Meanwhile, the carbon availability index (CAI) was higher at 5°C compared with 15 and 25°C incubation, but GIR increased with increasing temperature. Therefore, our findings suggest that warming-induced decrease in Rs in the field over time may result from a decrease in soil moisture rather than from soil substrate depletion, because warming increased root biomass in the alpine meadow.

  11. Robust Initial Wetness Condition Framework of an Event-Based Rainfall–Runoff Model Using Remotely Sensed Soil Moisture

    Directory of Open Access Journals (Sweden)

    Wooyeon Sunwoo

    2017-01-01

    Full Text Available Runoff prediction in limited-data areas is vital for hydrological applications, such as the design of infrastructure and flood defenses, runoff forecasting, and water management. Rainfall–runoff models may be useful for simulation of runoff generation, particularly event-based models, which offer a practical modeling scheme because of their simplicity. However, there is a need to reduce the uncertainties related to the estimation of the initial wetness condition (IWC prior to a rainfall event. Soil moisture is one of the most important variables in rainfall–runoff modeling, and remotely sensed soil moisture is recognized as an effective way to improve the accuracy of runoff prediction. In this study, the IWC was evaluated based on remotely sensed soil moisture by using the Soil Conservation Service-Curve Number (SCS-CN method, which is one of the representative event-based models used for reducing the uncertainty of runoff prediction. Four proxy variables for the IWC were determined from the measurements of total rainfall depth (API5, ground-based soil moisture (SSMinsitu, remotely sensed surface soil moisture (SSM, and soil water index (SWI provided by the advanced scatterometer (ASCAT. To obtain a robust IWC framework, this study consists of two main parts: the validation of remotely sensed soil moisture, and the evaluation of runoff prediction using four proxy variables with a set of rainfall–runoff events in the East Asian monsoon region. The results showed an acceptable agreement between remotely sensed soil moisture (SSM and SWI and ground based soil moisture data (SSMinsitu. In the proxy variable analysis, the SWI indicated the optimal value among the proposed proxy variables. In the runoff prediction analysis considering various infiltration conditions, the SSM and SWI proxy variables significantly reduced the runoff prediction error as compared with API5 by 60% and 66%, respectively. Moreover, the proposed IWC framework with

  12. Error characterization of microwave satellite soil moisture data sets using fourier analysis

    Science.gov (United States)

    Abstract: Soil moisture is a key geophysical variable in hydrological and meteorological processes. Accurate and current observations of soil moisture over mesoscale to global scales as inputs to hydrological, weather and climate modelling will benefit the predictability and understanding of these p...

  13. Use of active and passive microwave remote sensing for soil moisture estimation through corn

    International Nuclear Information System (INIS)

    O'Neill, P.E.; Chauhan, N.S.; Jackson, T.J.

    1996-01-01

    Over the past several years NASA, USDA, and Princeton University have collaborated to conduct hydrology field experiments in instrumented research watersheds in Pennsylvania and Oklahoma with a goal of characterizing the spatial and temporal variability of soil moisture using microwave sensors. As part of these experiments, L-band radar data from both truck and aircraft sensors were used to validate the performance of a vegetation scattering model in which discrete scatter random media techniques were employed to calculate vegetation transmissivity and scattering. These parameters were then used in a soil moisture prediction algorithm based on a radiative transfer approach utilizing aircraft passive microwave data from the L-band PBMR and ESTAR radiometers. Soil moisture was predicted in both experiments for several large corn fields which represented the densest vegetation canopies of all the test fields. Over the 20 per cent change in soil moisture encountered in the experiments, the match of predicted to measured soil moisture was excellent, with an average absolute error of about 0 · 02 cm 3 cm −3 . (author)

  14. Modeling soil moisture memory in savanna ecosystems

    Science.gov (United States)

    Gou, S.; Miller, G. R.

    2011-12-01

    Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants

  15. Role of subsurface physics in the assimilation of surface soil moisture observations

    Science.gov (United States)

    Soil moisture controls the exchange of water and energy between the land surface and the atmosphere and exhibits memory that may be useful for climate prediction at monthly time scales. Though spatially distributed observations of soil moisture are increasingly becoming available from remotely sense...

  16. Soil Moisture Active Passive (SMAP) Mission Level 4 Surface and Root Zone Soil Moisture (L4_SM) Product Specification Document

    Science.gov (United States)

    Reichle, Rolf H.; Ardizzone, Joseph V.; Kim, Gi-Kong; Lucchesi, Robert A.; Smith, Edmond B.; Weiss, Barry H.

    2015-01-01

    This is the Product Specification Document (PSD) for Level 4 Surface and Root Zone Soil Moisture (L4_SM) data for the Science Data System (SDS) of the Soil Moisture Active Passive (SMAP) project. The L4_SM data product provides estimates of land surface conditions based on the assimilation of SMAP observations into a customized version of the NASA Goddard Earth Observing System, Version 5 (GEOS-5) land data assimilation system (LDAS). This document applies to any standard L4_SM data product generated by the SMAP Project. The Soil Moisture Active Passive (SMAP) mission will enhance the accuracy and the resolution of space-based measurements of terrestrial soil moisture and freeze-thaw state. SMAP data products will have a noteworthy impact on multiple relevant and current Earth Science endeavors. These include: Understanding of the processes that link the terrestrial water, the energy and the carbon cycles, Estimations of global water and energy fluxes over the land surfaces, Quantification of the net carbon flux in boreal landscapes Forecast skill of both weather and climate, Predictions and monitoring of natural disasters including floods, landslides and droughts, and Predictions of agricultural productivity. To provide these data, the SMAP mission will deploy a satellite observatory in a near polar, sun synchronous orbit. The observatory will house an L-band radiometer that operates at 1.40 GHz and an L-band radar that operates at 1.26 GHz. The instruments will share a rotating reflector antenna with a 6 meter aperture that scans over a 1000 km swath.

  17. Predictability of soil moisture and river flows over France for the spring season

    Science.gov (United States)

    Singla, S.; Céron, J.-P.; Martin, E.; Regimbeau, F.; Déqué, M.; Habets, F.; Vidal, J.-P.

    2012-01-01

    Sources of spring predictability of the hydrological system over France were studied on a seasonal time scale over the 1960-2005 period. Two random sampling experiments were set up in order to test the relative importance of the land surface initial state and the atmospheric forcing. The experiments were based on the SAFRAN-ISBA-MODCOU hydrometeorological suite which computed soil moisture and river flow forecasts over a 8-km grid and more than 880 river-gauging stations. Results showed that the predictability of hydrological variables primarily depended on the seasonal atmospheric forcing (mostly temperature and total precipitation) over most plains, whereas it mainly depended on snow cover over high mountains. However, the Seine catchment area was an exception as the skill mainly came from the initial state of its large and complex aquifers. Seasonal meteorological hindcasts with the Météo-France ARPEGE climate model were then used to force the ISBA-MODCOU hydrological model and obtain seasonal hydrological forecasts from 1960 to 2005 for the entire March-April-May period. Scores from this seasonal hydrological forecasting suite could thus be compared with the random atmospheric experiment. Soil moisture and river flow skill scores clearly showed the added value in seasonal meteorological forecasts in the north of France, contrary to the Mediterranean area where values worsened.

  18. Observing and modeling links between soil moisture, microbes and CH4 fluxes from forest soils

    Science.gov (United States)

    Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue

    2017-04-01

    community responds different to environmental change dependent on the soil moisture regime. These results are important to include in future modeling efforts to predict changes in soil-atmosphere exchange of CH4 under global change.

  19. Contributions of Precipitation and Soil Moisture Observations to the Skill of Soil Moisture Estimates in a Land Data Assimilation System

    Science.gov (United States)

    Reichle, Rolf H.; Liu, Qing; Bindlish, Rajat; Cosh, Michael H.; Crow, Wade T.; deJeu, Richard; DeLannoy, Gabrielle J. M.; Huffman, George J.; Jackson, Thomas J.

    2011-01-01

    The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates from a land data assimilation system are assessed. Relative to baseline estimates from the Modern Era Retrospective-analysis for Research and Applications (MERRA), the study investigates soil moisture skill derived from (i) model forcing corrections based on large-scale, gauge- and satellite-based precipitation observations and (ii) assimilation of surface soil moisture retrievals from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E). Soil moisture skill is measured against in situ observations in the continental United States at 44 single-profile sites within the Soil Climate Analysis Network (SCAN) for which skillful AMSR-E retrievals are available and at four CalVal watersheds with high-quality distributed sensor networks that measure soil moisture at the scale of land model and satellite estimates. The average skill (in terms of the anomaly time series correlation coefficient R) of AMSR-E retrievals is R=0.39 versus SCAN and R=0.53 versus CalVal measurements. The skill of MERRA surface and root-zone soil moisture is R=0.42 and R=0.46, respectively, versus SCAN measurements, and MERRA surface moisture skill is R=0.56 versus CalVal measurements. Adding information from either precipitation observations or soil moisture retrievals increases surface soil moisture skill levels by IDDeltaR=0.06-0.08, and root zone soil moisture skill levels by DeltaR=0.05-0.07. Adding information from both sources increases surface soil moisture skill levels by DeltaR=0.13, and root zone soil moisture skill by DeltaR=0.11, demonstrating that precipitation corrections and assimilation of satellite soil moisture retrievals contribute similar and largely independent amounts of information.

  20. Soil moisture prediction: bridging event and continuous runoff modelling

    NARCIS (Netherlands)

    Sheikh, V.

    2006-01-01

    The general objective of this study was to investigate the possibility of providing spatially distributed soil moisture data for event-based hydrological models close before a rainfall event. The study area is known as "Catsop", a small catchmment in south Limburg. The models used are: LISEM and

  1. Measurement of soil moisture using gypsum blocks

    DEFF Research Database (Denmark)

    Friis Dela, B.

    the building. Consequently, measuring the moisture of the surrounding soil is of great importance for detecting the source of moisture in a building. Up till now, information has been needed to carry out individual calibrations for the different types of gypsum blocks available on the market and to account......For the past 50 years, gypsum blocks have been used to determine soil moisture content. This report describes a method for calibrating gypsum blocks for soil moisture measurements. Moisture conditions inside a building are strongly influenced by the moisture conditions in the soil surrounding...

  2. On-irrigator pasture soil moisture sensor

    International Nuclear Information System (INIS)

    Tan, Adrian Eng-Choon; Richards, Sean; Platt, Ian; Woodhead, Ian

    2017-01-01

    In this paper, we presented the development of a proximal soil moisture sensor that measured the soil moisture content of dairy pasture directly from the boom of an irrigator. The proposed sensor was capable of soil moisture measurements at an accuracy of  ±5% volumetric moisture content, and at meter scale ground area resolutions. The sensor adopted techniques from the ultra-wideband radar to enable measurements of ground reflection at resolutions that are smaller than the antenna beamwidth of the sensor. An experimental prototype was developed for field measurements. Extensive field measurements using the developed prototype were conducted on grass pasture at different ground conditions to validate the accuracy of the sensor in performing soil moisture measurements. (paper)

  3. Nematode survival in relation to soil moisture

    NARCIS (Netherlands)

    Simons, W.R.

    1973-01-01

    Established nematode populations are very persistent in the soil. It is known that they need sufficient soil moisture for movement, feeding and reproduction (fig. 5), and that there are adverse soil moisture conditions which they cannot survive. The influence of soil moisture on survival

  4. Australian Soil Moisture Field Experiments in Support of Soil Moisture Satellite Observations

    Science.gov (United States)

    Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco

    2010-01-01

    Large-scale field campaigns provide the critical fink between our understanding retrieval algorithms developed at the point scale, and algorithms suitable for satellite applications at vastly larger pixel scales. Retrievals of land parameters must deal with the substantial sub-pixel heterogeneity that is present in most regions. This is particularly the case for soil moisture remote sensing, because of the long microwave wavelengths (L-band) that are optimal. Yet, airborne L-band imagers have generally been large, heavy, and required heavy-lift aircraft resources that are expensive and difficult to schedule. Indeed, US soil moisture campaigns, have been constrained by these factors, and European campaigns have used non-imagers due to instrument and aircraft size constraints. Despite these factors, these campaigns established that large-scale soil moisture remote sensing was possible, laying the groundwork for satellite missions. Starting in 2005, a series of airborne field campaigns have been conducted in Australia: to improve our understanding of soil moisture remote sensing at large scales over heterogeneous areas. These field data have been used to test and refine retrieval algorithms for soil moisture satellite missions, and most recently with the launch of the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission, to provide validation measurements over a multi-pixel area. The campaigns to date have included a preparatory campaign in 2005, two National Airborne Field Experiments (NAFE), (2005 and 2006), two campaigns to the Simpson Desert (2008 and 2009), and one Australian Airborne Cal/val Experiment for SMOS (AACES), just concluded in the austral spring of 2010. The primary airborne sensor for each campaign has been the Polarimetric L-band Microwave Radiometer (PLMR), a 6-beam pushbroom imager that is small enough to be compatible with light aircraft, greatly facilitating the execution of the series of campaigns, and a key to their success. An

  5. Continuous data assimilation for downscaling large-footprint soil moisture retrievals

    KAUST Repository

    Altaf, M. U.

    2016-09-01

    Soil moisture is a crucial component of the hydrologic cycle, significantly influencing runoff, infiltration, recharge, evaporation and transpiration processes. Models characterizing these processes require soil moisture as an input, either directly or indirectly. Better characterization of the spatial variability of soil moisture leads to better predictions from hydrologic/climate models. In-situ measurements have fine resolution, but become impractical in terms of coverage over large extents. Remotely sensed data have excellent spatial coverage extents, but suffer from poorer spatial and temporal resolution. We present here an innovative approach to downscaling coarse resolution soil moisture data by combining data assimilation and physically based modeling. In this approach, we exploit the features of Continuous Data Assimilation (CDA). A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model’s large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (e.g., HYDRUS) are subjected to data assimilation conditioned upon the coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. The large scale features of the model output are constrained to the observations, and as a consequence, the misfit at the fine scale is reduced. The advantage of this approach is that fine resolution soil moisture maps can be generated across large spatial extents, given the coarse resolution data. The data assimilation approach also enables multi-scale data generation which is helpful to match the soil moisture input data to the corresponding modeling scale. Application of this approach is likely in generating fine and intermediate resolution soil

  6. Assessment of initial soil moisture conditions for event-based rainfall-runoff modelling

    OpenAIRE

    Tramblay, Yves; Bouvier, Christophe; Martin, C.; Didon-Lescot, J. F.; Todorovik, D.; Domergue, J. M.

    2010-01-01

    Flash floods are the most destructive natural hazards that occur in the Mediterranean region. Rainfall-runoff models can be very useful for flash flood forecasting and prediction. Event-based models are very popular for operational purposes, but there is a need to reduce the uncertainties related to the initial moisture conditions estimation prior to a flood event. This paper aims to compare several soil moisture indicators: local Time Domain Reflectometry (TDR) measurements of soil moisture,...

  7. Soil moisture memory at sub-monthly time scales

    Science.gov (United States)

    Mccoll, K. A.; Entekhabi, D.

    2017-12-01

    For soil moisture-climate feedbacks to occur, the soil moisture storage must have `memory' of past atmospheric anomalies. Quantifying soil moisture memory is, therefore, essential for mapping and characterizing land-atmosphere interactions globally. Most previous studies estimate soil moisture memory using metrics based on the autocorrelation function of the soil moisture time series (e.g., the e-folding autocorrelation time scale). This approach was first justified by Delworth and Manabe (1988) on the assumption that monthly soil moisture time series can be modelled as red noise. While this is a reasonable model for monthly soil moisture averages, at sub-monthly scales, the model is insufficient due to the highly non-Gaussian behavior of the precipitation forcing. Recent studies have shown that significant soil moisture-climate feedbacks appear to occur at sub-monthly time scales. Therefore, alternative metrics are required for defining and estimating soil moisture memory at these shorter time scales. In this study, we introduce metrics, based on the positive and negative increments of the soil moisture time series, that can be used to estimate soil moisture memory at sub-monthly time scales. The positive increments metric corresponds to a rapid drainage time scale. The negative increments metric represents a slower drying time scale that is most relevant to the study of land-atmosphere interactions. We show that autocorrelation-based metrics mix the two time scales, confounding physical interpretation. The new metrics are used to estimate soil moisture memory at sub-monthly scales from in-situ and satellite observations of soil moisture. Reference: Delworth, Thomas L., and Syukuro Manabe. "The Influence of Potential Evaporation on the Variabilities of Simulated Soil Wetness and Climate." Journal of Climate 1, no. 5 (May 1, 1988): 523-47. doi:10.1175/1520-0442(1988)0012.0.CO;2.

  8. SMOS validation of soil moisture and ocen salinity (SMOS) soil moisture over watershed networks in the U.S.

    Science.gov (United States)

    Estimation of soil moisture at large scale has been performed using several satellite-based passive microwave sensors and a variety of retrieval methods. The most recent source of soil moisture is the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission. A thorough validation must b...

  9. Global Soil Moisture from the Aquarius/SAC-D Satellite: Description and Initial Assessment

    Science.gov (United States)

    Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy

    2015-01-01

    Aquarius satellite observations over land offer a new resource for measuring soil moisture from space. Although Aquarius was designed for ocean salinity mapping, our objective in this investigation is to exploit the large amount of land observations that Aquarius acquires and extend the mission scope to include the retrieval of surface soil moisture. The soil moisture retrieval algorithm development focused on using only the radiometer data because of the extensive heritage of passive microwave retrieval of soil moisture. The single channel algorithm (SCA) was implemented using the Aquarius observations to estimate surface soil moisture. Aquarius radiometer observations from three beams (after bias/gain modification) along with the National Centers for Environmental Prediction model forecast surface temperatures were then used to retrieve soil moisture. Ancillary data inputs required for using the SCA are vegetation water content, land surface temperature, and several soil and vegetation parameters based on land cover classes. The resulting global spatial patterns of soil moisture were consistent with the precipitation climatology and with soil moisture from other satellite missions (Advanced Microwave Scanning Radiometer for the Earth Observing System and Soil Moisture Ocean Salinity). Initial assessments were performed using in situ observations from the U.S. Department of Agriculture Little Washita and Little River watershed soil moisture networks. Results showed good performance by the algorithm for these land surface conditions for the period of August 2011-June 2013 (rmse = 0.031 m(exp 3)/m(exp 3), Bias = -0.007 m(exp 3)/m(exp 3), and R = 0.855). This radiometer-only soil moisture product will serve as a baseline for continuing research on both active and combined passive-active soil moisture algorithms. The products are routinely available through the National Aeronautics and Space Administration data archive at the National Snow and Ice Data Center.

  10. Assessment of SMOS Soil Moisture Retrieval Parameters Using Tau-Omega Algorithms for Soil Moisture Deficit Estimation

    Science.gov (United States)

    Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika

    2014-01-01

    Soil Moisture and Ocean Salinity (SMOS) is the latest mission which provides flow of coarse resolution soil moisture data for land applications. However, the efficient retrieval of soil moisture for hydrological applications depends on optimally choosing the soil and vegetation parameters. The first stage of this work involves the evaluation of SMOS Level 2 products and then several approaches for soil moisture retrieval from SMOS brightness temperature are performed to estimate Soil Moisture Deficit (SMD). The most widely applied algorithm i.e. Single channel algorithm (SCA), based on tau-omega is used in this study for the soil moisture retrieval. In tau-omega, the soil moisture is retrieved using the Horizontal (H) polarisation following Hallikainen dielectric model, roughness parameters, Fresnel's equation and estimated Vegetation Optical Depth (tau). The roughness parameters are empirically calibrated using the numerical optimization techniques. Further to explore the improvement in retrieval models, modifications have been incorporated in the algorithms with respect to the sources of the parameters, which include effective temperatures derived from the European Center for Medium-Range Weather Forecasts (ECMWF) downscaled using the Weather Research and Forecasting (WRF)-NOAH Land Surface Model and Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) while the s is derived from MODIS Leaf Area Index (LAI). All the evaluations are performed against SMD, which is estimated using the Probability Distributed Model following a careful calibration and validation integrated with sensitivity and uncertainty analysis. The performance obtained after all those changes indicate that SCA-H using WRF-NOAH LSM downscaled ECMWF LST produces an improved performance for SMD estimation at a catchment scale.

  11. Space-time modeling of soil moisture

    Science.gov (United States)

    Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio

    2017-11-01

    A physically derived space-time mathematical representation of the soil moisture field is carried out via the soil moisture balance equation driven by stochastic rainfall forcing. The model incorporates spatial diffusion and in its original version, it is shown to be unable to reproduce the relative fast decay in the spatial correlation functions observed in empirical data. This decay resulting from variations in local topography as well as in local soil and vegetation conditions is well reproduced via a jitter process acting multiplicatively over the space-time soil moisture field. The jitter is a multiplicative noise acting on the soil moisture dynamics with the objective to deflate its correlation structure at small spatial scales which are not embedded in the probabilistic structure of the rainfall process that drives the dynamics. These scales of order of several meters to several hundred meters are of great importance in ecohydrologic dynamics. Properties of space-time correlation functions and spectral densities of the model with jitter are explored analytically, and the influence of the jitter parameters, reflecting variabilities of soil moisture at different spatial and temporal scales, is investigated. A case study fitting the derived model to a soil moisture dataset is presented in detail.

  12. Assessment of Multi-frequency Electromagnetic Induction for Determining Soil Moisture Patterns at the Hillslope Scale

    Science.gov (United States)

    Tromp-van Meerveld, I.; McDonnell, J.

    2009-05-01

    We present an assessment of electromagnetic induction (EM) as a potential rapid and non-invasive method to map soil moisture patterns at the Panola (GA, USA) hillslope. We address the following questions regarding the applicability of EM measurements for hillslope hydrological investigations: (1) Can EM be used for soil moisture measurements in areas with shallow soils?; (2) Can EM represent the temporal and spatial patterns of soil moisture throughout the year?; and (3) can multiple frequencies be used to extract additional information content from the EM approach and explain the depth profile of soil moisture? We found that the apparent conductivity measured with the multi-frequency GEM-300 was linearly related to soil moisture measured with an Aqua-pro capacitance sensor below a threshold conductivity and represented the temporal patterns in soil moisture well. During spring rainfall events that wetted only the surface soil layers the apparent conductivity measurements explained the soil moisture dynamics at depth better than the surface soil moisture dynamics. All four EM frequencies (7290, 9090, 11250, and 14010 Hz) were highly correlated and linearly related to each other and could be used to predict soil moisture. This limited our ability to use the four different EM frequencies to obtain a soil moisture profile with depth. The apparent conductivity patterns represented the observed spatial soil moisture patterns well when the individually fitted relationships between measured soil moisture and apparent conductivity were used for each measurement point. However, when the same (master) relationship was used for all measurement locations, the soil moisture patterns were smoothed and did not resemble the observed soil moisture patterns very well. In addition, the range in calculated soil moisture values was reduced compared to observed soil moisture. Part of the smoothing was likely due to the much larger measurement area of the GEM-300 compared to the Aqua

  13. Incorporation of Passive Microwave Brightness Temperatures in the ECMWF Soil Moisture Analysis

    Directory of Open Access Journals (Sweden)

    Joaquín Muñoz-Sabater

    2015-05-01

    Full Text Available For more than a decade, the European Centre for Medium-Range Weather Forecasts (ECMWF has used in-situ observations of 2 m temperature and 2 m relative humidity to operationally constrain the temporal evolution of model soil moisture. These observations are not available everywhere and they are indirectly linked to the state of the surface, so under various circumstances, such as weak radiative forcing or strong advection, they cannot be used as a proxy for soil moisture reinitialization in numerical weather prediction. Recently, the ECMWF soil moisture analysis has been updated to be able to account for the information provided by microwave brightness temperatures from the Soil Moisture and Ocean Salinity (SMOS mission of the European Space Agency (ESA. This is the first time that ECMWF uses direct information of the soil emission from passive microwave data to globally adjust the estimation of soil moisture by a land-surface model. This paper presents a novel version of the ECMWF Extended Kalman Filter soil moisture analysis to account for remotely sensed passive microwave data. It also discusses the advantages of assimilating direct satellite radiances compared to current soil moisture products, with a view to an operational implementation. A simple assimilation case study at global scale highlights the potential benefits and obstacles of using this new type of information in a global coupled land-atmospheric model.

  14. Improved Assimilation of Streamflow and Satellite Soil Moisture with the Evolutionary Particle Filter and Geostatistical Modeling

    Science.gov (United States)

    Yan, Hongxiang; Moradkhani, Hamid; Abbaszadeh, Peyman

    2017-04-01

    Assimilation of satellite soil moisture and streamflow data into hydrologic models using has received increasing attention over the past few years. Currently, these observations are increasingly used to improve the model streamflow and soil moisture predictions. However, the performance of this land data assimilation (DA) system still suffers from two limitations: 1) satellite data scarcity and quality; and 2) particle weight degeneration. In order to overcome these two limitations, we propose two possible solutions in this study. First, the general Gaussian geostatistical approach is proposed to overcome the limitation in the space/time resolution of satellite soil moisture products thus improving their accuracy at uncovered/biased grid cells. Secondly, an evolutionary PF approach based on Genetic Algorithm (GA) and Markov Chain Monte Carlo (MCMC), the so-called EPF-MCMC, is developed to further reduce weight degeneration and improve the robustness of the land DA system. This study provides a detailed analysis of the joint and separate assimilation of streamflow and satellite soil moisture into a distributed Sacramento Soil Moisture Accounting (SAC-SMA) model, with the use of recently developed EPF-MCMC and the general Gaussian geostatistical approach. Performance is assessed over several basins in the USA selected from Model Parameter Estimation Experiment (MOPEX) and located in different climate regions. The results indicate that: 1) the general Gaussian approach can predict the soil moisture at uncovered grid cells within the expected satellite data quality threshold; 2) assimilation of satellite soil moisture inferred from the general Gaussian model can significantly improve the soil moisture predictions; and 3) in terms of both deterministic and probabilistic measures, the EPF-MCMC can achieve better streamflow predictions. These results recommend that the geostatistical model is a helpful tool to aid the remote sensing technique and the EPF-MCMC is a

  15. Vegetation-induced turbulence influencing evapotranspiration-soil moisture coupling: Implications for semiarid regions

    Science.gov (United States)

    Haghighi, E.; Kirchner, J. W.; Entekhabi, D.

    2016-12-01

    The relationship between soil moisture and evapotranspiration (ET) fluxes is an important component of land-atmosphere interactions controlling hydrology-climate feedback processes. Important as this relationship is, it remains empirical and physical mechanisms governing its dynamics are insufficiently studied. This is particularly of importance for semiarid regions (currently comprising about half of the Earth's land surface) where the shallow surface soil layer is the primary source of ET and direct evaporation from bare soil is likely a large component of the total flux. Hence, ET-soil moisture coupling in these regions is hypothesized to be strongly influenced by soil evaporation and associated mechanisms. Motivated by recent progress in mechanistic modeling of localized heat and mass exchange rates from bare soil surfaces covered by cylindrical bluff-body elements, we developed a physically based ET model explicitly incorporating coupled impacts of soil moisture and vegetation-induced turbulence in the near-surface region. Model predictions of ET and its partitioning were in good agreement with measured data and suggest that the strength and nature of ET-soil moisture interactions in sparsely vegetated areas are strongly influenced by aerodynamic (rather than radiative) forcing namely wind speed and near-surface turbulence generation as a function of vegetation type and cover fraction. The results demonstrated that the relationship between ET and soil moisture varies from a nonlinear function (the dual regime behavior) to a single moisture-limited regime (linear relationship) by increasing wind velocity and enhancing turbulence generation in the near-surface region (small-scale woody vegetation species of low cover fraction). Potential benefits of this study for improving accuracy and predictive capabilities of remote sensing techniques when applied to semiarid environments will also be discussed.

  16. The impact of fog on soil moisture dynamics in the Namib Desert

    Science.gov (United States)

    Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.

    2018-03-01

    Soil moisture is a crucial component supporting vegetation dynamics in drylands. Despite increasing attention on fog in dryland ecosystems, the statistical characterization of fog distribution and how fog affects soil moisture dynamics have not been seen in literature. To this end, daily fog records over two years (Dec 1, 2014-Nov 1, 2016) from three sites within the Namib Desert were used to characterize fog distribution. Two sites were located within the Gobabeb Research and Training Center vicinity, the gravel plains and the sand dunes. The third site was located at the gravel plains, Kleinberg. A subset of the fog data during rainless period was used to investigate the effect of fog on soil moisture. A stochastic modeling framework was used to simulate the effect of fog on soil moisture dynamics. Our results showed that fog distribution can be characterized by a Poisson process with two parameters (arrival rate λ and average depth α (mm)). Fog and soil moisture observations from eighty (Aug 19, 2015-Nov 6, 2015) rainless days indicated a moderate positive relationship between soil moisture and fog in the Gobabeb gravel plains, a weaker relationship in the Gobabeb sand dunes while no relationship was observed at the Kleinberg site. The modeling results suggested that mean and major peaks of soil moisture dynamics can be captured by the fog modeling. Our field observations demonstrated the effects of fog on soil moisture dynamics during rainless periods at some locations, which has important implications on soil biogeochemical processes. The statistical characterization and modeling of fog distribution are of great value to predict fog distribution and investigate the effects of potential changes in fog distribution on soil moisture dynamics.

  17. Soil moisture effects during bioventing in fuel-contaminated arid soils

    International Nuclear Information System (INIS)

    Zwick, T.C.; Leeson, A.; Hinchee, R.E.; Hoeppel, R.E.; Bowling, L.

    1995-01-01

    This study evaluated the effects of soil moisture addition on microbial activity during bioventing of dry, sandy soils at the Marine Corps Air Ground Combat Center (MCAGCC), Twentynine Palms, California. Soils at the site have been contaminated to a depth of approximately 80 ft (24 m) with gasoline, JP-5 jet fuel, and diesel fuel. Based on the low soil moisture measured at the site (2 to 3% by weight), it was determined that soil moisture may be limiting biodegradation. To evaluate the effect that moisture addition had on microbial activity under field conditions, a subsurface drip irrigation system was installed above the fuel hydrocarbon plume. Irrigation water was obtained from two monitoring wells on the site, where groundwater was approximately 192 ft (59 m) below ground surface. Advancement of the wetting front was monitored. In situ respiration rates increased significantly after moisture addition. The results of this study provide evidence for the potential applicability of moisture addition in conjunction with bioventing for site remediation in arid environments. Further work is planned to investigate optimization of moisture addition

  18. Inversion of Farmland Soil Moisture in Large Region Based on Modified Vegetation Index

    Science.gov (United States)

    Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.

    2018-04-01

    Soil moisture is an important parameter for agricultural production. Efficient and accurate monitoring of soil moisture is an important link to ensure the safety of agricultural production. Remote sensing technology has been widely used in agricultural moisture monitoring because of its timeliness, cyclicality, dynamic tracking of changes in things, easy access to data, and extensive monitoring. Vegetation index and surface temperature are important parameters for moisture monitoring. Based on NDVI, this paper introduces land surface temperature and average temperature for optimization. This article takes the soil moisture in winter wheat growing area in Henan Province as the research object, dividing Henan Province into three main regions producing winter wheat and dividing the growth period of winter wheat into the early, middle and late stages on the basis of phenological characteristics and regional characteristics. Introducing appropriate correction factor during the corresponding growth period of winter wheat, correcting the vegetation index in the corresponding area, this paper establishes regression models of soil moisture on NDVI and soil moisture on modified NDVI based on correlation analysis and compare models. It shows that modified NDVI is more suitable as a indicator of soil moisture because of the better correlation between soil moisture and modified NDVI and the higher prediction accuracy of the regression model of soil moisture on modified NDVI. The research in this paper has certain reference value for winter wheat farmland management and decision-making.

  19. Elevated moisture stimulates carbon loss from mineral soils by releasing protected organic matter.

    Science.gov (United States)

    Huang, Wenjuan; Hall, Steven J

    2017-11-24

    Moisture response functions for soil microbial carbon (C) mineralization remain a critical uncertainty for predicting ecosystem-climate feedbacks. Theory and models posit that C mineralization declines under elevated moisture and associated anaerobic conditions, leading to soil C accumulation. Yet, iron (Fe) reduction potentially releases protected C, providing an under-appreciated mechanism for C destabilization under elevated moisture. Here we incubate Mollisols from ecosystems under C 3 /C 4 plant rotations at moisture levels at and above field capacity over 5 months. Increased moisture and anaerobiosis initially suppress soil C mineralization, consistent with theory. However, after 25 days, elevated moisture stimulates cumulative gaseous C-loss as CO 2 and CH 4 to >150% of the control. Stable C isotopes show that mineralization of older C 3 -derived C released following Fe reduction dominates C losses. Counter to theory, elevated moisture may significantly accelerate C losses from mineral soils over weeks to months-a critical mechanistic deficiency of current Earth system models.

  20. Irrigation scheduling using soil moisture sensors

    Science.gov (United States)

    Soil moisture sensors were evaluated and used for irrigation scheduling in humid region. Soil moisture sensors were installed in soil at depths of 15cm, 30cm, and 61cm belowground. Soil volumetric water content was automatically measured by the sensors in a time interval of an hour during the crop g...

  1. Use of midlatitude soil moisture and meteorological observations to validate soil moisture simulations with biosphere and bucket models

    Science.gov (United States)

    Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang

    1995-01-01

    Soil moisture observations in sites with natural vegetation were made for several decades in the former Soviet Union at hundreds of stations. In this paper, the authors use data from six of these stations from different climatic regimes, along with ancillary meteorological and actinometric data, to demonstrate a method to validate soil moisture simulations with biosphere and bucket models. Some early and current general circulation models (GCMs) use bucket models for soil hydrology calculations. More recently, the Simple Biosphere Model (SiB) was developed to incorporate the effects of vegetation on fluxes of moisture, momentum, and energy at the earth's surface into soil hydrology models. Until now, the bucket and SiB have been verified by comparison with actual soil moisture data only on a limited basis. In this study, a Simplified SiB (SSiB) soil hydrology model and a 15-cm bucket model are forced by observed meteorological and actinometric data every 3 h for 6-yr simulations at the six stations. The model calculations of soil moisture are compared to observations of soil moisture, literally 'ground truth,' snow cover, surface albedo, and net radiation, and with each other. For three of the stations, the SSiB and 15-cm bucket models produce good simulations of seasonal cycles and interannual variations of soil moisture. For the other three stations, there are large errors in the simulations by both models. Inconsistencies in specification of field capacity may be partly responsible. There is no evidence that the SSiB simulations are superior in simulating soil moisture variations. In fact, the models are quite similar since SSiB implicitly has a bucket embedded in it. One of the main differences between the models is in the treatment of runoff due to melting snow in the spring -- SSiB incorrectly puts all the snowmelt into runoff. While producing similar soil moisture simulations, the models produce very different surface latent and sensible heat fluxes, which

  2. Impact of the assimilation of satellite soil moisture and LST on the hydrological cycle

    Science.gov (United States)

    Laiolo, Paola; Gabellani, Simone; Delogu, Fabio; Silvestro, Francesco; Rudari, Roberto; Campo, Lorenzo; Boni, Giorgio

    2014-05-01

    The reliable estimation of hydrological variables (e.g. soil moisture, evapotranspiration, surface temperature) 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 remote sensing can offer a chance to provide good space-time estimates of several hydrological variables and then improve hydrological model performances especially in environments with scarce ground based data. The aim of this work is to investigate the impacts on the performances of a distributed hydrological model (Continuum) of the assimilation of satellite-derived soil moisture products and Land Surface (LST). In this work three different soil moisture (SM) products, derived by ASCAT sensor, are used. These data are provided by the EUMETSAT's H-SAF (Satellite Application Facility on Support to Operational Hydrology and Water Management) program. The considered soil moisture products are: large scale surface soil moisture (SM OBS 1 - H07), small scale surface soil moisture (SM OBS 2 - H08) and profile index in the roots region (SM DAS 2 - H14). These data are compared with soil moisture estimated by Continuum model on the Orba catchment (800 km2), in the northern part of Italy, for the period July 2012-June 2013. Different assimilation experiments have been performed. The first experiment consists in the assimilation of the SM products by using a simple Nudging technique; the second one is the assimilation of only LST data, derived from MSG satellite, and the third is the assimilation of both SM products and LST. The benefits on the model predictions of discharge, LST and soil moisture dynamics were tested.

  3. Investigating soil moisture-climate interactions with prescribed soil moisture experiments: an assessment with the Community Earth System Model (version 1.2)

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Seneviratne, Sonia I.

    2017-04-01

    Land surface hydrology is an important control of surface weather and climate. A valuable technique to investigate this link is the prescription of soil moisture in land surface models, which leads to a decoupling of the atmosphere and land processes. Diverse approaches to prescribe soil moisture, as well as different prescribed soil moisture conditions have been used in previous studies. Here, we compare and assess four methodologies to prescribe soil moisture and investigate the impact of two different estimates of the climatological seasonal cycle used to prescribe soil moisture. Our analysis shows that, though in appearance similar, the different approaches require substantially different long-term moisture inputs and lead to different temperature signals. The smallest influence on temperature and the water balance is found when prescribing the median seasonal cycle of deep soil liquid water, whereas the strongest signal is found when prescribing soil liquid and soil ice using the mean seasonal cycle. These results indicate that induced net water-balance perturbations in experiments investigating soil moisture-climate coupling are important contributors to the climate response, in addition to the intended impact of the decoupling. These results help to guide the set-up of future experiments prescribing soil moisture, as for instance planned within the Land Surface, Snow and Soil Moisture Model Intercomparison Project (LS3MIP).

  4. Effect of soil moisture on the temperature sensitivity of Northern soils

    Science.gov (United States)

    Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.

    2017-12-01

    Arctic and boreal ecosystems are vast reservoirs of carbon and are particularly sensitive to climate warming. Changes in the temperature and precipitation regimes of these regions could significantly alter soil respiration rates, impacting atmospheric concentrations and affecting climate change feedbacks. Many incubation studies have shown that both temperature and soil moisture are important environmental drivers of soil respiration; this relationship, however, has rarely been demonstrated with in situ data. Here we present the results of a study at six field sites in Alaska from 2016 to 2017. Low-power automated soil gas systems were used to measure soil surface CO2 flux from three forced diffusion chambers and soil profile concentrations from three soil depth chambers at hourly intervals at each site. HOBO Onset dataloggers were used to monitor soil moisture and temperature profiles. Temperature sensitivity (Q10) was determined at each site using inversion analysis applied over different time periods. With highly resolved data sets, we were able to observe the changes in soil respiration in response to changes in temperature and soil moisture. Through regression analysis we confirmed that temperature is the primary driver in soil respiration, but soil moisture becomes dominant beyond a certain threshold, suppressing CO2 flux in soils with high moisture content. This field study supports the conclusions made from previous soil incubation studies and provides valuable insights into the impact of both temperature and soil moisture changes on soil respiration.

  5. Passive microwave remote sensing of soil moisture

    International Nuclear Information System (INIS)

    Jackson, T.J.; Schmugge, T.J.

    1986-01-01

    Microwave remote sensing provides a unique capability for direct observation of soil moisture. Remote measurements from space afford the possibility of obtaining frequent, global sampling of soil moisture over a large fraction of the Earth's land surface. Microwave measurements have the benefit of being largely unaffected by cloud cover and variable surface solar illumination, but accurate soil moisture estimates are limited to regions that have either bare soil or low to moderate amounts of vegetation cover. A particular advantage of passive microwave sensors is that in the absence of significant vegetation cover soil moisture is the dominant effect on the received signal. The spatial resolutions of passive microwave soil moisture sensors currently considered for space operation are in the range 10–20 km. The most useful frequency range for soil moisture sensing is 1–5 GHz. System design considerations include optimum choice of frequencies, polarizations, and scanning configurations, based on trade-offs between requirements for high vegetation penetration capability, freedom from electromagnetic interference, manageable antenna size and complexity, and the requirement that a sufficient number of information channels be available to correct for perturbing geophysical effects. This paper outlines the basic principles of the passive microwave technique for soil moisture sensing, and reviews briefly the status of current retrieval methods. Particularly promising are methods for optimally assimilating passive microwave data into hydrologic models. Further studies are needed to investigate the effects on microwave observations of within-footprint spatial heterogeneity of vegetation cover and subsurface soil characteristics, and to assess the limitations imposed by heterogeneity on the retrievability of large-scale soil moisture information from remote observations

  6. Assimilation of a thermal remote sensing-based soil moisture proxy into a root-zone water balance model

    Science.gov (United States)

    Crow, W. T.; Kustas, W. P.

    2006-05-01

    Two types of Soil Vegetation Atmosphere Transfer (SVAT) modeling approaches are commonly applied to monitoring root-zone soil water availability. Water and Energy Balance (WEB) SVAT modeling are based forcing a prognostic water balance model with precipitation observations. In constrast, thermal Remote Sensing (RS) observations of canopy radiometric temperatures can be integrated into purely diagnostic SVAT models to predict the onset of vegetation water stress due to low root-zone soil water availability. Unlike WEB-SVAT models, RS-SVAT models do not require observed precipitation. Using four growings seasons (2001 to 2004) of profile soil moisture, micro-meteorology, and surface radiometric temperature observations at the USDA's OPE3 site, root-zone soil moisture predictions made by both WEB- and RS-SVAT modeling approaches are intercompared with each other and availible root- zone soil moisture observations. Results indicate that root-zone soil moisture estimates derived from a WEB- SVAT model have slightly more skill in detecting soil moisture anomalies at the site than comporable predictions from a competing RS-SVAT modeling approach. However, the relative advantage of the WEB-SVAT model disappears when it is forced with lower-quality rainfall information typical of continental and global-scale rainfall data sets. Most critically, root-zone soil moisture errors associated with both modeling approaches are sufficiently independent such that the merger of both information from both proxies - using either simple linear averaging or an Ensemble Kalman filter - creates a merge soil moisture estimate that is more accurate than either of its parent components.

  7. Effects of soil moisture on the diurnal pattern of pesticide emission: Comparison of simulations with field measurements

    Science.gov (United States)

    Reichman, Rivka; Yates, Scott R.; Skaggs, Todd H.; Rolston, Dennis E.

    2013-02-01

    Pesticide volatilization from agricultural soils is one of the main pathways in which pesticides are dispersed in the environment and affects ecosystems including human welfare. Thus, it is necessary to have accurate knowledge of the various physical and chemical mechanisms that affect volatilization rates from field soils. A verification of the influence of soil moisture modeling on the simulated volatilization rate, soil temperature and soil-water content is presented. Model simulations are compared with data collected in a field study that measured the effect of soil moisture on diazinon volatilization. These data included diurnal changes in volatilization rate, soil-water content, and soil temperature measured at two depths. The simulations were performed using a comprehensive non-isothermal model, two water retention functions, and two soil surface resistance functions, resulting in four tested models. Results show that the degree of similarity between volatilization curves simulated using the four models depended on the initial water content. Under fairly wet conditions, the simulated curves mainly differ in the magnitude of their deviation from the measured values. However, under intermediate and low moisture conditions, the simulated curves also differed in their pattern (shape). The model prediction accuracy depended on soil moisture. Under normal practices, where initial soil moisture is about field capacity or higher, a combination of Brooks and Corey water retention and the van de Grind and Owe soil surface resistance functions led to the most accurate predictions. However, under extremely dry conditions, when soil-water content in the top 1 cm is below the volumetric threshold value, the use of a full-range water retention function increased prediction accuracy. The different models did not affect the soil temperature predictions, and had a minor effect on the predicted soil-water content of Yolo silty clay soil.

  8. Hysteresis of soil temperature under different soil moisture and ...

    African Journals Online (AJOL)

    ... in a solar greenhouse. The objective of this study was to find a simple method to estimate the hysteresis of soil temperature under three soil moisture and two fertilizer levels in solar greenhouse conditions with tomato crop (Lycopersicon esculentum Mill). The results show that the soil moisture had no significant effects on ...

  9. Can current moisture responses predict soil CO2 efflux under altered precipitation regimes? A synthesis of manipulation experiments

    DEFF Research Database (Denmark)

    Vicca, S.; Bahn, M.; Estiarte, M.

    2014-01-01

    to fluctuations in soil temperature and soil water content can be used to predict SCE under altered rainfall patterns. Of the 58 experiments for which we gathered SCE data, 20 were discarded because either too few data were available or inconsistencies precluded their incorporation in the analyses. The 38...... remaining experiments were used to test the hypothesis that a model parameterized with data from the control plots (using soil temperature and water content as predictor variables) could adequately predict SCE measured in the manipulated treatment. Only for 7 of these 38 experiments was this hypothesis...... strongly on establishing response functions across a broader range of precipitation regimes and soil moisture conditions. Such experiments should make accurate measurements of water availability, should conduct high-frequency SCE measurements, and should consider both instantaneous responses...

  10. An Overview of Production and Validation of the SMAP Passive Soil Moisture Product

    Science.gov (United States)

    Chan, S.; O'Neill, P.; Njoku, E.; Jackson, T.; Bindlish, R.

    2015-01-01

    The Soil Moisture Active Passive (SMAP) mission is an L-band mission scheduled for launch in Jan. 2015. The SMAP instruments consist of a radar and a radiometer to obtain complementary information from space for soil moisture and freeze/thaw state research and applications. By utilizing novel designs in antenna construction, retrieval algorithms, and acquisition hardware, SMAP provides a capability for global mapping of soil moisture and freeze/thaw state with unprecedented accuracy, resolution, and coverage. This improvement in hydrosphere state measurement is expected to advance our understanding of the processes that link the terrestrial water, energy and carbon cycles, improve our capability in flood prediction and drought monitoring, and enhance our skills in weather and climate forecast. For swath-based soil moisture measurement, SMAP generates three operational geophysical data products: (1) the radiometer-only soil moisture product (L2_SM_P) posted at 36-kilometer resolution, (2) the radar-only soil moisture product (L2_SM_A) posted at 3-kilometers resolution, and (3) the radar-radiometer combined soil moisture product (L2_SM_AP) posted at 9-kilometers resolution. Each product draws on the strengths of the underlying sensor(s) and plays a unique role in hydroclimatological and hydrometeorological applications. A full suite of SMAP data products is given in Table 1.

  11. Spatio-temporal Root Zone Soil Moisture Estimation for Indo - Gangetic Basin from Satellite Derived (AMSR-2 and SMOS) Surface Soil Moisture

    Science.gov (United States)

    Sure, A.; Dikshit, O.

    2017-12-01

    Root zone soil moisture (RZSM) is an important element in hydrology and agriculture. The estimation of RZSM provides insight in selecting the appropriate crops for specific soil conditions (soil type, bulk density, etc.). RZSM governs various vadose zone phenomena and subsequently affects the groundwater processes. With various satellite sensors dedicated to estimating surface soil moisture at different spatial and temporal resolutions, estimation of soil moisture at root zone level for Indo - Gangetic basin which inherits complex heterogeneous environment, is quite challenging. This study aims at estimating RZSM and understand its variation at the level of Indo - Gangetic basin with changing land use/land cover, topography, crop cycles, soil properties, temperature and precipitation patterns using two satellite derived soil moisture datasets operating at distinct frequencies with different principles of acquisition. Two surface soil moisture datasets are derived from AMSR-2 (6.9 GHz - `C' Band) and SMOS (1.4 GHz - `L' band) passive microwave sensors with coarse spatial resolution. The Soil Water Index (SWI), accounting for soil moisture from the surface, is derived by considering a theoretical two-layered water balance model and contributes in ascertaining soil moisture at the vadose zone. This index is evaluated against the widely used modelled soil moisture dataset of GLDAS - NOAH, version 2.1. This research enhances the domain of utilising the modelled soil moisture dataset, wherever the ground dataset is unavailable. The coupling between the surface soil moisture and RZSM is analysed for two years (2015-16), by defining a parameter T, the characteristic time length. The study demonstrates that deriving an optimal value of T for estimating SWI at a certain location is a function of various factors such as land, meteorological, and agricultural characteristics.

  12. Microwave remote sensing of soil moisture for estimation of profile soil property

    International Nuclear Information System (INIS)

    Mattikalli, N.M.; Engman, E.T.; Ahuja, L.R.; Jackson, T.J.

    1998-01-01

    Multi-temporal microwave remotely-sensed soil moisture has been utilized for the estimation of profile soil property, viz. the soil hydraulic conductivity. Passive microwave remote sensing was employed to collect daily soil moisture data across the Little Washita watershed, Oklahoma, during 10-18 June 1992. The ESTAR (Electronically Steered Thin Array Radiometer) instrument operating at L -band was flown on a NASA C-130 aircraft. Brightness temperature (TB) data collected at a ground resolution of 200m were employed to derive spatial distribution of surface soil moisture. Analysis of spatial and temporal soil moisture information in conjunction with soils data revealed a direct relation between changes in soil moisture and soil texture. A geographical information system (GIS) based analysis suggested that 2-days initial drainage of soil, measured from remote sensing, was related to an important soil hydraulic property viz. the saturated hydraulic conductivity (Ksat). A hydrologic modelling methodology was developed for estimation of Ksat of surface and sub-surface soil layers. Specifically, soil hydraulic parameters were optimized to obtain a good match between model estimated and field measured soil moisture profiles. Relations between 2-days soil moisture change and Ksat of 0-5 cm, 0-30 cm and 0-60cm depths yielded correla tions of 0.78, 0.82 and 0.71, respectively. These results are comparable to the findings of previous studies involving laboratory-controlled experiments and numerical simulations, and support their extension to the field conditions of the Little Washita watershed. These findings have potential applications of microwave remote sensing to obtain 2-days of soil moisture and then to quickly estimate the spatial distribution of Ksat over large areas. (author)

  13. A Comparison of Methods for a Priori Bias Correction in Soil Moisture Data Assimilation

    Science.gov (United States)

    Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.

    2011-01-01

    Data assimilation is being increasingly used to merge remotely sensed land surface variables such as soil moisture, snow and skin temperature with estimates from land models. Its success, however, depends on unbiased model predictions and unbiased observations. Here, a suite of continental-scale, synthetic soil moisture assimilation experiments is used to compare two approaches that address typical biases in soil moisture prior to data assimilation: (i) parameter estimation to calibrate the land model to the climatology of the soil moisture observations, and (ii) scaling of the observations to the model s soil moisture climatology. To enable this research, an optimization infrastructure was added to the NASA Land Information System (LIS) that includes gradient-based optimization methods and global, heuristic search algorithms. The land model calibration eliminates the bias but does not necessarily result in more realistic model parameters. Nevertheless, the experiments confirm that model calibration yields assimilation estimates of surface and root zone soil moisture that are as skillful as those obtained through scaling of the observations to the model s climatology. Analysis of innovation diagnostics underlines the importance of addressing bias in soil moisture assimilation and confirms that both approaches adequately address the issue.

  14. COSMOS: the COsmic-ray Soil Moisture Observing System

    Directory of Open Access Journals (Sweden)

    M. Zreda

    2012-11-01

    Full Text Available The newly-developed cosmic-ray method for measuring area-average soil moisture at the hectometer horizontal scale is being implemented in the COsmic-ray Soil Moisture Observing System (or the COSMOS. The stationary cosmic-ray soil moisture probe measures the neutrons that are generated by cosmic rays within air and soil and other materials, moderated by mainly hydrogen atoms located primarily in soil water, and emitted to the atmosphere where they mix instantaneously at a scale of hundreds of meters and whose density is inversely correlated with soil moisture. The COSMOS has already deployed more than 50 of the eventual 500 cosmic-ray probes, distributed mainly in the USA, each generating a time series of average soil moisture over its horizontal footprint, with similar networks coming into existence around the world. This paper is written to serve a community need to better understand this novel method and the COSMOS project. We describe the cosmic-ray soil moisture measurement method, the instrument and its calibration, the design, data processing and dissemination used in the COSMOS project, and give example time series of soil moisture obtained from COSMOS probes.

  15. Exploiting Soil Moisture, Precipitation, and Streamflow Observations to Evaluate Soil Moisture/Runoff Coupling in Land Surface Models

    Science.gov (United States)

    Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.

    2018-05-01

    Accurate partitioning of precipitation into infiltration and runoff is a fundamental objective of land surface models tasked with characterizing the surface water and energy balance. Temporal variability in this partitioning is due, in part, to changes in prestorm soil moisture, which determine soil infiltration capacity and unsaturated storage. Utilizing the National Aeronautics and Space Administration Soil Moisture Active Passive Level-4 soil moisture product in combination with streamflow and precipitation observations, we demonstrate that land surface models (LSMs) generally underestimate the strength of the positive rank correlation between prestorm soil moisture and event runoff coefficients (i.e., the fraction of rainfall accumulation volume converted into stormflow runoff during a storm event). Underestimation is largest for LSMs employing an infiltration-excess approach for stormflow runoff generation. More accurate coupling strength is found in LSMs that explicitly represent subsurface stormflow or saturation-excess runoff generation processes.

  16. Effect of moisture content and dry unit weight on the resilient modulus of subgrade soils predicted by cone penetration test.

    Science.gov (United States)

    2002-06-01

    The objective of this study was to investigate the effect of moisture content and dry unit weight on the resilient characteristics of subgrade soil predicted by the cone penetration test. An experimental program was conducted in which cone penetratio...

  17. Automated Quality Control of in Situ Soil Moisture from the North American Soil Moisture Database Using NLDAS-2 Products

    Science.gov (United States)

    Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.

    2015-12-01

    The North American Soil Moisture Database (NASMD) was initiated in 2011 to provide support for developing climate forecasting tools, calibrating land surface models and validating satellite-derived soil moisture algorithms. The NASMD has collected data from over 30 soil moisture observation networks providing millions of in situ soil moisture observations in all 50 states as well as Canada and Mexico. It is recognized that the quality of measured soil moisture in NASMD is highly variable due to the diversity of climatological conditions, land cover, soil texture, and topographies of the stations and differences in measurement devices (e.g., sensors) and installation. It is also recognized that error, inaccuracy and imprecision in the data set can have significant impacts on practical operations and scientific studies. Therefore, developing an appropriate quality control procedure is essential to ensure the data is of the best quality. In this study, an automated quality control approach is developed using the North American Land Data Assimilation System phase 2 (NLDAS-2) Noah soil porosity, soil temperature, and fraction of liquid and total soil moisture to flag erroneous and/or spurious measurements. Overall results show that this approach is able to flag unreasonable values when the soil is partially frozen. A validation example using NLDAS-2 multiple model soil moisture products at the 20 cm soil layer showed that the quality control procedure had a significant positive impact in Alabama, North Carolina, and West Texas. It had a greater impact in colder regions, particularly during spring and autumn. Over 433 NASMD stations have been quality controlled using the methodology proposed in this study, and the algorithm will be implemented to control data quality from the other ~1,200 NASMD stations in the near future.

  18. Can next-generation soil data products improve soil moisture modelling at the continental scale? An assessment using a new microclimate package for the R programming environment

    Science.gov (United States)

    Kearney, Michael R.; Maino, James L.

    2018-06-01

    Accurate models of soil moisture are vital for solving core problems in meteorology, hydrology, agriculture and ecology. The capacity for soil moisture modelling is growing rapidly with the development of high-resolution, continent-scale gridded weather and soil data together with advances in modelling methods. In particular, the GlobalSoilMap.net initiative represents next-generation, depth-specific gridded soil products that may substantially increase soil moisture modelling capacity. Here we present an implementation of Campbell's infiltration and redistribution model within the NicheMapR microclimate modelling package for the R environment, and use it to assess the predictive power provided by the GlobalSoilMap.net product Soil and Landscape Grid of Australia (SLGA, ∼100 m) as well as the coarser resolution global product SoilGrids (SG, ∼250 m). Predictions were tested in detail against 3 years of root-zone (3-75 cm) soil moisture observation data from 35 monitoring sites within the OzNet project in Australia, with additional tests of the finalised modelling approach against cosmic-ray neutron (CosmOz, 0-50 cm, 9 sites from 2011 to 2017) and satellite (ASCAT, 0-2 cm, continent-wide from 2007 to 2009) observations. The model was forced by daily 0.05° (∼5 km) gridded meteorological data. The NicheMapR system predicted soil moisture to within experimental error for all data sets. Using the SLGA or the SG soil database, the OzNet soil moisture could be predicted with a root mean square error (rmse) of ∼0.075 m3 m-3 and a correlation coefficient (r) of 0.65 consistently through the soil profile without any parameter tuning. Soil moisture predictions based on the SLGA and SG datasets were ≈ 17% closer to the observations than when using a chloropleth-derived soil data set (Digital Atlas of Australian Soils), with the greatest improvements occurring for deeper layers. The CosmOz observations were predicted with similar accuracy (r = 0.76 and rmse of ∼0

  19. Soil moisture content with global warming

    International Nuclear Information System (INIS)

    Vinnikov, K.Ya.

    1990-01-01

    The potential greenhouse-gas-induced changes in soil moisture, particularly the desiccation of the Northern Hemisphere contents in summer, are discussed. To check the conclusions based on climate models the authors have used long-term measurements of contemporary soil moisture in the USSR and reconstructions of soil moisture for the last two epochs that were warmer than the present, namely, the Holocene optimum, 5,000-6,000 years ago, and the last interglacial, about 125,000 years ago. The analysis shows that there is a considerable disagreement between the model results and the empirical data

  20. Propagation of soil moisture memory into the climate system

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2012-04-01

    Soil moisture is known for its integrative behaviour and resulting memory characteristics. Associated anomalies can persist for weeks or even months into the future, making initial soil moisture an important potential component in weather forecasting. This is particularly crucial given the role of soil moisture for land-atmosphere interactions and its impacts on the water and energy balances on continents. We present here an analysis of the characteristics of soil moisture memory and of its propagation into runoff and evapotranspiration in Europe, based on available measurements from several sites across the continent and expanding a previous analysis focused on soil moisture [1]. We identify the main drivers of soil moisture memory at the analysed sites, as well as their role for the propagation of soil moisture persistence into runoff and evapotranspiration memory characteristics. We focus on temporal and spatial variations in these relationships and identify seasonal and latitudinal differences in the persistence of soil moisture, evapotranspiration and runoff. Finally, we assess the role of these persistence characteristics for the development of agricultural and hydrological droughts. [1] Orth and Seneviratne: Analysis of soil moisture memory from observations in Europe; submitted to J. Geophysical Research.

  1. Climate Prediction Center (CPC) Global Monthly Leaky Bucket Soil Moisture Analysis

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Monthly global soil moisture, runoff, and evaporation data sets produced by the Leaky Bucket model at 0.5? ? 0.5? resolution for the period from 1948 to the present....

  2. DEVELOPMENT OF NEW HYPERSPECTRAL ANGLE INDEX FOR ESTIMATION OF SOIL MOISTURE USING IN SITU SPECTRAL MEASURMENTS

    Directory of Open Access Journals (Sweden)

    M. R. Mobasheri

    2013-10-01

    Full Text Available Near-surface soil moisture is one of the crucial variables in hydrological processes, which influences the exchange of water and energy fluxes at the land surface/atmosphere interface. Accurate estimate of the spatial and temporal variations of soil moisture is critical for numerous environmental studies. On the other hand, information of distributed soil moisture at large scale with reasonable spatial and temporal resolution is required for improving climatic and hydrologic modeling and prediction. The advent of hyperspectral imagery has allowed examination of continuous spectra not possible with isolated bands in multispectral imagery. In addition to high spectral resolution for individual band analyses, the contiguous narrow bands show characteristics of related absorption features, such as effects of strong absorptions on the band depths of adjacent absorptions. Our objective in this study was to develop a new spectral angle index to estimate soil moisture based on spectral region (350 and 2500 nm. In this paper, using spectral observations made by ASD Spectroradiometer for predicting soil moisture content, two soil indices were also investigated involving the Perpendicular Drought Index (PDI, NMDI (Normalized Multi-band Drought Index indices. Correlation and regression analysis showed a high relationship between PDI and the soil moisture percent (R2 = 0.9537 and NMDI (R2 = 0.9335. Furthermore, we also simulated these data according to the spectral range of some sensors such as MODIS, ASTER, ALI and ETM+. Indices relevant these sensors have high correlation with soil moisture data. Finally, we proposed a new angle index which shows significant relationship between new angle index and the soil moisture percentages (R2 = 0.9432.angle index relevant bands 3, 4, 5, 6, 7 MODIS also showing high accuracy in estimation of soil moisture (R2 = 0.719.

  3. A simple nudging scheme to assimilate ASCAT soil moisture data in the WRF model

    Science.gov (United States)

    Capecchi, V.; Gozzini, B.

    2012-04-01

    The present work shows results obtained in a numerical experiment using the WRF (Weather and Research Forecasting, www.wrf-model.org) model. A control run where soil moisture is constrained by GFS global analysis is compared with a test run where soil moisture analysis is obtained via a simple nudging scheme using ASCAT data. The basic idea of the assimilation scheme is to "nudge" the first level (0-10 cm below ground in NOAH model) of volumetric soil moisture of the first-guess (say θ(b,1) derived from global model) towards the ASCAT derived value (say ^θ A). The soil moisture analysis θ(a,1) is given by: { θ + K (^θA - θ ) l = 1 θ(a,1) = θ(b,l) (b,l) l > 1 (b,l) (1) where l is the model soil level. K is a constant scalar value that is user specified and in this study it is equal to 0.2 (same value as in similar studies). Soil moisture is critical for estimating latent and sensible heat fluxes as well as boundary layer structure. This parameter is, however, poorly assimilated in current global and regional numerical models since no extensive soil moisture observation network exists. Remote sensing technologies offer a synoptic view of the dynamics and spatial distribution of soil moisture with a frequent temporal coverage and with a horizontal resolution similar to mesoscale NWP model. Several studies have shown that measurements of normalized backscatter (surface soil wetness) from the Advanced Scatterometer (ASCAT) operating at microwave frequencies and boarded on the meteorological operational (Metop) satellite, offer quality information about surface soil moisture. Recently several studies deal with the implementation of simple assimilation procedures (nudging, Extended Kalman Filter, etc...) to integrate ASCAT data in NWP models. They found improvements in screen temperature predictions, particularly in areas such as North-America and in the Tropics, where it is strong the land-atmosphere coupling. The ECMWF (Newsletter No. 127) is currently

  4. Assessing the effect of soil use changes on soil moisture regimes in mountain regions. (Catalan Pre-Pyrenees NE Spain)

    International Nuclear Information System (INIS)

    Loaiza Usuga, Juan Carlos; Jarauta Bragulat, Eusebio; Porta Casanellas, Jaume; Poch Claret, Rosa Maria

    2010-01-01

    Soil moisture regimes under different land uses were observed and modeled in a representative forest basin in the Catalonian Pre-Pyrenees, more specifically in the Ribera Salada catchment (222.5 km2). The vegetation cover in the catchment consists of pasture, tillage and forest. A number of representative plots for each of these land cover types were intensely monitored during the study period. The annual precipitation fluctuates between 516 and 753 mm, while the soil moisture content oscillates between 14 and 26% in the middle and low lying areas of the basin, and between 21 and 48% in shady zones near the river bed, and in the higher parts of the basin. Soil moisture and rainfall are controlled firstly by altitude, with the existence of two climatic types in the basin (sub-Mediterranean and sub-alpine), and further, by land use. Two models were applied to the estimated water moisture regimes: the Jarauta Simulation Newhall model (JSM) and the Newhall simulation model (NSM) were found to be able to predict the soil moisture regimes in the basin in the different combinations of local abiotic and biotic factors. The JSM results are more precise than the results obtained using another frequently used method, more specifically the Newhall Simulation Model (NSM), which has been developed to simulate soil moisture regimes. NSM was found to overestimate wet soil moisture regimes. The results show the importance of the moisture control section size and Available Water Capacity (AWC) of the profile, in the moisture section control state and variability. The mountain soils are dominated by rustic and occasionally xeric regimes. Land use changes leading to an increase in forest areas would imply drier soil conditions and therefore drier soil water regimes. These effects are most evident in degraded shallow and stony soils with low AWC.

  5. Impacts of soil moisture content on visual soil evaluation

    Science.gov (United States)

    Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick

    2017-04-01

    Visual Soil Examination and Evaluation (VSE) techniques offer tools for soil quality assessment. They involve the visual and tactile assessment of soil properties such as aggregate size and shape, porosity, redox morphology, soil colour and smell. An increasing body of research has demonstrated the reliability and utility of VSE techniques. However a number of limitations have been identified, including the potential impact of soil moisture variation during sampling. As part of a national survey of grassland soil quality in Ireland, an evaluation of the impact of soil moisture on two widely used VSE techniques was conducted. The techniques were Visual Evaluation of Soil Structure (VESS) (Guimarães et al., 2011) and Visual Soil Assessment (VSA) (Shepherd, 2009). Both generate summarising numeric scores that indicate soil structural quality, though employ different scoring mechanisms. The former requires the assessment of properties concurrently and the latter separately. Both methods were deployed on 20 sites across Ireland representing a range of soils. Additional samples were taken for soil volumetric water (θ) determination at 5-10 and 10-20 cm depth. No significant correlation was observed between θ 5-10 cm and either VSE technique. However, VESS scores were significantly related to θ 10-20 cm (rs = 0.40, sig = 0.02) while VSA scores were not (rs = -0.33, sig = 0.06). VESS and VSA scores can be grouped into quality classifications (good, moderate and poor). No significant mean difference was observed between θ 5-10 cm or θ 10-20 cm according to quality classification by either method. It was concluded that VESS scores may be affected by soil moisture variation while VSA appear unaffected. The different scoring mechanisms, where the separate assessment and scoring of individual properties employed by VSA, may limit soil moisture effects. However, moisture content appears not to affect overall structural quality classification by either method. References

  6. Soil moisture in sessile oak forest gaps

    Science.gov (United States)

    Zagyvainé Kiss, Katalin Anita; Vastag, Viktor; Gribovszki, Zoltán; Kalicz, Péter

    2015-04-01

    By social demands are being promoted the aspects of the natural forest management. In forestry the concept of continuous forest has been an accepted principle also in Hungary since the last decades. The first step from even-aged stand to continuous forest can be the forest regeneration based on gap cutting, so small openings are formed in a forest due to forestry interventions. This new stand structure modifies the hydrological conditions for the regrowth. Without canopy and due to the decreasing amounts of forest litter the interception is less significant so higher amount of precipitation reaching the soil. This research focuses on soil moisture patterns caused by gaps. The spatio-temporal variability of soil water content is measured in gaps and in surrounding sessile oak (Quercus petraea) forest stand. Soil moisture was determined with manual soil moisture meter which use Time-Domain Reflectometry (TDR) technology. The three different sizes gaps (G1: 10m, G2: 20m, G3: 30m) was opened next to Sopron on the Dalos Hill in Hungary. First, it was determined that there is difference in soil moisture between forest stand and gaps. Second, it was defined that how the gap size influences the soil moisture content. To explore the short term variability of soil moisture, two 24-hour (in growing season) and a 48-hour (in dormant season) field campaign were also performed in case of the medium-sized G2 gap along two/four transects. Subdaily changes of soil moisture were performed. The measured soil moisture pattern was compared with the radiation pattern. It was found that the non-illuminated areas were wetter and in the dormant season the subdaily changes cease. According to our measurements, in the gap there is more available water than under the forest stand due to the less evaporation and interception loss. Acknowledgements: The research was supported by TÁMOP-4.2.2.A-11/1/KONV-2012-0004 and AGRARKLIMA.2 VKSZ_12-1-2013-0034.

  7. Modeling and Mapping Soil Moisture of Plateau Pasture Using RADARSAT-2 Imagery

    Directory of Open Access Journals (Sweden)

    Xun Chai

    2015-01-01

    Full Text Available Accurate soil moisture retrieval of a large area in high resolution is significant for plateau pasture. The object of this paper is to investigate the estimation of volumetric soil moisture in vegetated areas of plateau pasture using fully polarimetric C-band RADARSAT-2 SAR (Synthetic Aperture Radar images. Based on the water cloud model, Chen model, and Dubois model, we proposed two developed algorithms for soil moisture retrieval and validated their performance using experimental data. We eliminated the effect of vegetation cover by using the water cloud model and minimized the effect of soil surface roughness by solving the Dubois equations. Two experimental campaigns were conducted in the Qinghai Lake watershed, northeastern Tibetan Plateau in September 2012 and May 2013, respectively, with simultaneous satellite overpass. Compared with the developed Chen model, the predicted soil moisture given by the developed Dubois model agreed better with field measurements in terms of accuracy and stability. The RMSE, R2, and RPD value of the developed Dubois model were (5.4, 0.8, 1.6 and (3.05, 0.78, 1.74 for the two experiments, respectively. Validation results indicated that the developed Dubois model, needing a minimum of prior information, satisfied the requirement for soil moisture inversion in the study region.

  8. A Polarimetric First-Order Model of Soil Moisture Effects on the DInSAR Coherence

    Directory of Open Access Journals (Sweden)

    Simon Zwieback

    2015-06-01

    Full Text Available Changes in soil moisture between two radar acquisitions can impact the observed coherence in differential interferometry: both coherence magnitude |Υ| and phase Φ are affected. The influence on the latter potentially biases the estimation of deformations. These effects have been found to be variable in magnitude and sign, as well as dependent on polarization, as opposed to predictions by existing models. Such diversity can be explained when the soil is modelled as a half-space with spatially varying dielectric properties and a rough interface. The first-order perturbative solution achieves–upon calibration with airborne L band data–median correlations ρ at HH polarization of 0.77 for the phase Φ, of 0.50 for |Υ|, and for the phase triplets ≡ of 0.56. The predictions are sensitive to the choice of dielectric mixing model, in particular the absorptive properties; the differences between the mixing models are found to be partially compensatable by varying the relative importance of surface and volume scattering. However, for half of the agricultural fields the Hallikainen mixing model cannot reproduce the observed sensitivities of the phase to soil moisture. In addition, the first-order expansion does not predict any impact on the HV coherence, which is however empirically found to display similar sensitivities to soil moisture as the co-pol channels HH and VV. These results indicate that the first-order solution, while not able to reproduce all observed phenomena, can capture some of the more salient patterns of the effect of soil moisture changes on the HH and VV DInSAR signals. Hence it may prove useful in separating the deformations from the moisture signals, thus yielding improved displacement estimates or new ways for inferring soil moisture.

  9. Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

    Science.gov (United States)

    Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt

    2010-01-01

    Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

  10. Improving Flood Prediction By the Assimilation of Satellite Soil Moisture in Poorly Monitored Catchments.

    Science.gov (United States)

    Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.

    2014-12-01

    Flood prediction in poorly monitored catchments is among the greatest challenges faced by hydrologists. To address this challenge, an increasing number of studies in the last decade have explored methods to integrate various existing observations from ground and satellites. One approach in particular, is the assimilation of satellite soil moisture (SM-DA) into rainfall-runoff models. The rationale is that satellite soil moisture (SSM) can be used to correct model soil water states, enabling more accurate prediction of catchment response to precipitation and thus better streamflow. However, there is still no consensus on the most effective SM-DA scheme and how this might depend on catchment scale, climate characteristics, runoff mechanisms, model and SSM products used, etc. In this work, an operational SM-DA scheme was set up in the poorly monitored, large (>40,000 km2), semi-arid Warrego catchment situated in eastern Australia. We assimilated passive and active SSM products into the probability distributed model (PDM) using an ensemble Kalman filter. We explored factors influencing the SM-DA framework, including relatively new techniques to remove model-observation bias, estimate observation errors and represent model errors. Furthermore, we explored the advantages of accounting for the spatial distribution of forcing and channel routing processes within the catchment by implementing and comparing lumped and semi-distributed model setups. Flood prediction is improved by SM-DA (Figure), with a 30% reduction of the average root-mean-squared difference of the ensemble prediction, a 20% reduction of the false alarm ratio and a 40% increase of the ensemble mean Nash-Sutcliffe efficiency. SM-DA skill does not significantly change with different observation error assumptions, but the skill strongly depends on the observational bias correction technique used, and more importantly, on the performance of the open-loop model before assimilation. Our findings imply that proper

  11. Calibration of neutron moisture gauges and their ability to spatially determine soil water content in environmental studies

    International Nuclear Information System (INIS)

    Nyhan, J.W.; Martinez, J.L.; Langhorst, G.J.

    1994-10-01

    Several neutron moisture gauges were calibrated, and their ability to spatially determine soil water content was evaluated. In 1982, the midpoint of sensitivity of each neutron probe to the detection of hydrogen was determined, as well as the radius of investigation of each probe in crushed Bandelier Tuff with varying water contents. After determining the response of one of the moisture gauges to changes in soil water at the soil-air interface, a neutron transport model was successfully calibrated to predict spatial variations in soil water content. The model was then used to predict various shapes and volumes of crushed Bandelier Tuff interrogated by the neutron moisture gauge. From 1991 through 1994, six neutron moisture gauges were calibrated for soil water determinations in a local topsoil and crushed Bandelier Tuff, as well as for a sample of fine sand and soils from a field experiment at Hill Air Force Base. Statistical analysis of the calibration results is presented and summarized, and a final summary of practical implications for future neutron moisture gauge studies at Los Alamos is included

  12. Theoretical study of soil water balance and process of soil moisture evaporation

    Directory of Open Access Journals (Sweden)

    Yu. A. Savel'ev

    2017-01-01

    Full Text Available Nearly a half of all grain production in the Russian Federation is grown in dry regions. But crop production efficiency there depends on amount of moisture, available to plants. However deficit of soil moisture is caused not only by a lack of an atmospheric precipitation, but also inefficient water saving: losses reach 70 percent. With respect thereto it is important to reveal the factors influencing intensity of soil moisture evaporation and to develop methods of decrease in unproductive moisture losses due to evaporation. The authors researched soil water balance theoretically and determined the functional dependences of moisture loss on evaporation. Intensity of moisture evaporation depends on physicomechanical characteristics of the soil, a consistence of its surface and weather conditions. To decrease losses of moisture for evaporation it is necessary, first, to improve quality of crumbling of the soil and therefore to reduce the evaporating surface of the soil. Secondly - to create the protective mulching layer which will allow to enhance albedo of the soil and to reduce its temperature that together will reduce unproductive evaporative water losses and will increase its inflow in case of condensation from air vapors. The most widespread types of soil cultivation are considered: disk plowing and stubble mulch plowing. Agricultural background «no tillage» was chosen as a control. Subsoil mulching tillage has an essential advantage in a storage of soil moisture. So, storage of soil moisture after a disking and in control (without tillage decreased respectively by 24.9 and 19.8 mm while at the mulching tillage this indicator revised down by only 15.6 mm. The mulching layer has lower heat conductivity that provides decrease in unproductive evaporative water losses.

  13. State of the Art in Large-Scale Soil Moisture Monitoring

    Science.gov (United States)

    Ochsner, Tyson E.; Cosh, Michael Harold; Cuenca, Richard H.; Dorigo, Wouter; Draper, Clara S.; Hagimoto, Yutaka; Kerr, Yan H.; Larson, Kristine M.; Njoku, Eni Gerald; Small, Eric E.; hide

    2013-01-01

    Soil moisture is an essential climate variable influencing land atmosphere interactions, an essential hydrologic variable impacting rainfall runoff processes, an essential ecological variable regulating net ecosystem exchange, and an essential agricultural variable constraining food security. Large-scale soil moisture monitoring has advanced in recent years creating opportunities to transform scientific understanding of soil moisture and related processes. These advances are being driven by researchers from a broad range of disciplines, but this complicates collaboration and communication. For some applications, the science required to utilize large-scale soil moisture data is poorly developed. In this review, we describe the state of the art in large-scale soil moisture monitoring and identify some critical needs for research to optimize the use of increasingly available soil moisture data. We review representative examples of 1) emerging in situ and proximal sensing techniques, 2) dedicated soil moisture remote sensing missions, 3) soil moisture monitoring networks, and 4) applications of large-scale soil moisture measurements. Significant near-term progress seems possible in the use of large-scale soil moisture data for drought monitoring. Assimilation of soil moisture data for meteorological or hydrologic forecasting also shows promise, but significant challenges related to model structures and model errors remain. Little progress has been made yet in the use of large-scale soil moisture observations within the context of ecological or agricultural modeling. Opportunities abound to advance the science and practice of large-scale soil moisture monitoring for the sake of improved Earth system monitoring, modeling, and forecasting.

  14. An evaluation of the potential of Sentinel 1 for improving flash flood predictions via soil moisture-data assimilation

    Science.gov (United States)

    Cenci, Luca; Pulvirenti, Luca; Boni, Giorgio; Chini, Marco; Matgen, Patrick; Gabellani, Simone; Squicciarino, Giuseppe; Pierdicca, Nazzareno

    2017-11-01

    The assimilation of satellite-derived soil moisture estimates (soil moisture-data assimilation, SM-DA) into hydrological models has the potential to reduce the uncertainty of streamflow simulations. The improved capacity to monitor the closeness to saturation of small catchments, such as those characterizing the Mediterranean region, can be exploited to enhance flash flood predictions. When compared to other microwave sensors that have been exploited for SM-DA in recent years (e.g. the Advanced SCATterometer - ASCAT), characterized by low spatial/high temporal resolution, the Sentinel 1 (S1) mission provides an excellent opportunity to monitor systematically soil moisture (SM) at high spatial resolution and moderate temporal resolution. The aim of this research was thus to evaluate the impact of S1-based SM-DA for enhancing flash flood predictions of a hydrological model (Continuum) that is currently exploited for civil protection applications in Italy. The analysis was carried out in a representative Mediterranean catchment prone to flash floods, located in north-western Italy, during the time period October 2014-February 2015. It provided some important findings: (i) revealing the potential provided by S1-based SM-DA for improving discharge predictions, especially for higher flows; (ii) suggesting a more appropriate pre-processing technique to be applied to S1 data before the assimilation; and (iii) highlighting that even though high spatial resolution does provide an important contribution in a SM-DA system, the temporal resolution has the most crucial role. S1-derived SM maps are still a relatively new product and, to our knowledge, this is the first work published in an international journal dealing with their assimilation within a hydrological model to improve continuous streamflow simulations and flash flood predictions. Even though the reported results were obtained by analysing a relatively short time period, and thus should be supported by further

  15. Evaluating ESA CCI Soil Moisture in East Africa

    Science.gov (United States)

    McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R.; Wang, Shugong; Peters-Lidard, Christa D.; Verdin, James P.

    2016-01-01

    To assess growing season conditions where ground based observations are limited or unavailable, food security and agricultural drought monitoring analysts rely on publicly available remotely sensed rainfall and vegetation greenness. There are also remotely sensed soil moisture observations from missions like the European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) and NASAs Soil Moisture Active Passive (SMAP), however these time series are still too short to conduct studies that demonstrate the utility of these data for operational applications, or to provide historical context for extreme wet or dry events. To promote the use of remotely sensed soil moisture in agricultural drought and food security monitoring, we use East Africa as a case study to evaluate the quality of a 30+ year time series of merged active-passive microwave soil moisture from the ESA Climate Change Initiative (CCI-SM). Compared to the Normalized Difference Vegetation index (NDVI) and modeled soil moisture products, we found substantial spatial and temporal gaps in the early part of the CCI-SM record, with adequate data coverage beginning in 1992. From this point forward, growing season CCI-SM anomalies were well correlated (R greater than 0.5) with modeled, seasonal soil moisture, and in some regions, NDVI. We use correlation analysis and qualitative comparisons at seasonal time scales to show that remotely sensed soil moisture can add information to a convergence of evidence framework that traditionally relies on rainfall and NDVI in moderately vegetated regions.

  16. Acclimation and soil moisture constrain sugar maple root respiration in experimentally warmed soil.

    Science.gov (United States)

    Jarvi, Mickey P; Burton, Andrew J

    2013-09-01

    The response of root respiration to warmer soil can affect ecosystem carbon (C) allocation and the strength of positive feedbacks between climatic warming and soil CO2 efflux. This study sought to determine whether fine-root (maple (Acer saccharum Marsh.)-dominated northern hardwood forest would adjust to experimentally warmed soil, reducing C return to the atmosphere at the ecosystem scale to levels lower than that would be expected using an exponential temperature response function. Infrared heating lamps were used to warm the soil (+4 to +5 °C) in a mature sugar maple forest in a fully factorial design, including water additions used to offset the effects of warming-induced dry soil. Fine-root-specific respiration rates, root biomass, root nitrogen (N) concentration, soil temperature and soil moisture were measured from 2009 to 2011, with experimental treatments conducted from late 2010 to 2011. Partial acclimation of fine-root respiration to soil warming occurred, with soil moisture deficit further constraining specific respiration rates in heated plots. Fine-root biomass and N concentration remained unchanged. Over the 2011 growing season, ecosystem root respiration was not significantly greater in warmed soil. This result would not be predicted by models that allow respiration to increase exponentially with temperature and do not directly reduce root respiration in drier soil.

  17. NOAA Soil Moisture Products System (SMOPS) Daily Blended Products

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Soil Moisture Operational Products System (SMOPS) combines soil moisture retrievals from multiple satellite sensors to provide a global soil moisture map with...

  18. Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

    Science.gov (United States)

    Koster, R. D.; Walker, G. K.

    2015-01-01

    The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

  19. NASA Soil Moisture Active Passive (SMAP) Applications

    Science.gov (United States)

    Orr, Barron; Moran, M. Susan; Escobar, Vanessa; Brown, Molly E.

    2014-05-01

    The launch of the NASA Soil Moisture Active Passive (SMAP) mission in 2014 will provide global soil moisture and freeze-thaw measurements at moderate resolution (9 km) with latency as short as 24 hours. The resolution, latency and global coverage of SMAP products will enable new applications in the fields of weather, climate, drought, flood, agricultural production, human health and national security. To prepare for launch, the SMAP mission has engaged more than 25 Early Adopters. Early Adopters are users who have a need for SMAP-like soil moisture or freeze-thaw data, and who agreed to apply their own resources to demonstrate the utility of SMAP data for their particular system or model. In turn, the SMAP mission agreed to provide Early Adopters with simulated SMAP data products and pre-launch calibration and validation data from SMAP field campaigns, modeling, and synergistic studies. The applied research underway by Early Adopters has provided fundamental knowledge of how SMAP data products can be scaled and integrated into users' policy, business and management activities to improve decision-making efforts. This presentation will cover SMAP applications including weather and climate forecasting, vehicle mobility estimation, quantification of greenhouse gas emissions, management of urban potable water supply, and prediction of crop yield. The presentation will end with a discussion of potential international applications with focus on the ESA/CEOS TIGER Initiative entitled "looking for water in Africa", the United Nations (UN) Convention to Combat Desertification (UNCCD) which carries a specific mandate focused on Africa, the UN Framework Convention on Climate Change (UNFCCC) which lists soil moisture as an Essential Climate Variable (ECV), and the UN Food and Agriculture Organization (FAO) which reported a food and nutrition crisis in the Sahel.

  20. [Bare Soil Moisture Inversion Model Based on Visible-Shortwave Infrared Reflectance].

    Science.gov (United States)

    Zheng, Xiao-po; Sun, Yue-jun; Qin, Qi-ming; Ren, Hua-zhong; Gao, Zhong-ling; Wu, Ling; Meng, Qing-ye; Wang, Jin-liang; Wang, Jian-hua

    2015-08-01

    Soil is the loose solum of land surface that can support plants. It consists of minerals, organics, atmosphere, moisture, microbes, et al. Among its complex compositions, soil moisture varies greatly. Therefore, the fast and accurate inversion of soil moisture by using remote sensing is very crucial. In order to reduce the influence of soil type on the retrieval of soil moisture, this paper proposed a normalized spectral slope and absorption index named NSSAI to estimate soil moisture. The modeling of the new index contains several key steps: Firstly, soil samples with different moisture level were artificially prepared, and soil reflectance spectra was consequently measured using spectroradiometer produced by ASD Company. Secondly, the moisture absorption spectral feature located at shortwave wavelengths and the spectral slope of visible wavelengths were calculated after analyzing the regular spectral feature change patterns of different soil at different moisture conditions. Then advantages of the two features at reducing soil types' effects was synthesized to build the NSSAI. Thirdly, a linear relationship between NSSAI and soil moisture was established. The result showed that NSSAI worked better (correlation coefficient is 0.93) than most of other traditional methods in soil moisture extraction. It can weaken the influences caused by soil types at different moisture levels and improve the bare soil moisture inversion accuracy.

  1. Drought monitoring with soil moisture active passive (SMAP) measurements

    Science.gov (United States)

    Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara

    2017-09-01

    Recent launch of space-borne systems to estimate surface soil moisture may expand the capability to map soil moisture deficit and drought with global coverage. In this study, we use Soil Moisture Active Passive (SMAP) soil moisture geophysical retrieval products from passive L-band radiometer to evaluate its applicability to forming agricultural drought indices. Agricultural drought is quantified using the Soil Water Deficit Index (SWDI) based on SMAP and soil properties (field capacity and available water content) information. The soil properties are computed using pedo-transfer function with soil characteristics derived from Harmonized World Soil Database. The SMAP soil moisture product needs to be rescaled to be compatible with the soil parameters derived from the in situ stations. In most locations, the rescaled SMAP information captured the dynamics of in situ soil moisture well and shows the expected lag between accumulations of precipitation and delayed increased in surface soil moisture. However, the SMAP soil moisture itself does not reveal the drought information. Therefore, the SMAP based SWDI (SMAP_SWDI) was computed to improve agriculture drought monitoring by using the latest soil moisture retrieval satellite technology. The formulation of SWDI does not depend on longer data and it will overcome the limited (short) length of SMAP data for agricultural drought studies. The SMAP_SWDI is further compared with in situ Atmospheric Water Deficit (AWD) Index. The comparison shows close agreement between SMAP_SWDI and AWD in drought monitoring over Contiguous United States (CONUS), especially in terms of drought characteristics. The SMAP_SWDI was used to construct drought maps for CONUS and compared with well-known drought indices, such as, AWD, Palmer Z-Index, sc-PDSI and SPEI. Overall the SMAP_SWDI is an effective agricultural drought indicator and it provides continuity and introduces new spatial mapping capability for drought monitoring. As an

  2. Measuring Soil Moisture in Skeletal Soils Using a COSMOS Rover

    Science.gov (United States)

    Medina, C.; Neely, H.; Desilets, D.; Mohanty, B.; Moore, G. W.

    2017-12-01

    The presence of coarse fragments directly influences the volumetric water content of the soil. Current surface soil moisture sensors often do not account for the presence of coarse fragments, and little research has been done to calibrate these sensors under such conditions. The cosmic-ray soil moisture observation system (COSMOS) rover is a passive, non-invasive surface soil moisture sensor with a footprint greater than 100 m. Despite its potential, the COSMOS rover has yet to be validated in skeletal soils. The goal of this study was to validate measurements of surface soil moisture as taken by a COSMOS rover on a Texas skeletal soil. Data was collected for two soils, a Marfla clay loam and Chinati-Boracho-Berrend association, in West Texas. Three levels of data were collected: 1) COSMOS surveys at three different soil moistures, 2) electrical conductivity surveys within those COSMOS surveys, and 3) ground-truth measurements. Surveys with the COSMOS rover covered an 8000-h area and were taken both after large rain events (>2") and a long dry period. Within the COSMOS surveys, the EM38-MK2 was used to estimate the spatial distribution of coarse fragments in the soil around two COSMOS points. Ground truth measurements included coarse fragment mass and volume, bulk density, and water content at 3 locations within each EM38 survey. Ground-truth measurements were weighted using EM38 data, and COSMOS measurements were validated by their distance from the samples. There was a decrease in water content as the percent volume of coarse fragment increased. COSMOS estimations responded to both changes in coarse fragment percent volume and the ground-truth volumetric water content. Further research will focus on creating digital soil maps using landform data and water content estimations from the COSMOS rover.

  3. Global characterization of surface soil moisture drydowns

    Science.gov (United States)

    McColl, Kaighin A.; Wang, Wei; Peng, Bin; Akbar, Ruzbeh; Short Gianotti, Daniel J.; Lu, Hui; Pan, Ming; Entekhabi, Dara

    2017-04-01

    Loss terms in the land water budget (including drainage, runoff, and evapotranspiration) are encoded in the shape of soil moisture "drydowns": the soil moisture time series directly following a precipitation event, during which the infiltration input is zero. The rate at which drydowns occur—here characterized by the exponential decay time scale τ—is directly related to the shape of the loss function and is a key characteristic of global weather and climate models. In this study, we use 1 year of surface soil moisture observations from NASA's Soil Moisture Active Passive mission to characterize τ globally. Consistent with physical reasoning, the observations show that τ is lower in regions with sandier soils, and in regions that are more arid. To our knowledge, these are the first global estimates of τ—based on observations alone—at scales relevant to weather and climate models.

  4. The global distribution and dynamics of surface soil moisture

    Science.gov (United States)

    McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara

    2017-01-01

    Surface soil moisture has a direct impact on food security, human health and ecosystem function. It also plays a key role in the climate system, and the development and persistence of extreme weather events such as droughts, floods and heatwaves. However, sparse and uneven observations have made it difficult to quantify the global distribution and dynamics of surface soil moisture. Here we introduce a metric of soil moisture memory and use a full year of global observations from NASA's Soil Moisture Active Passive mission to show that surface soil moisture--a storage believed to make up less than 0.001% of the global freshwater budget by volume, and equivalent to an, on average, 8-mm thin layer of water covering all land surfaces--plays a significant role in the water cycle. Specifically, we find that surface soil moisture retains a median 14% of precipitation falling on land after three days. Furthermore, the retained fraction of the surface soil moisture storage after three days is highest over arid regions, and in regions where drainage to groundwater storage is lowest. We conclude that lower groundwater storage in these regions is due not only to lower precipitation, but also to the complex partitioning of the water cycle by the surface soil moisture storage layer at the land surface.

  5. Regional vegetation water effects on satellite soil moisture estimations for West Africa

    NARCIS (Netherlands)

    Friesen, J.C.

    2008-01-01

    Soil moisture information is a vital parameter for water resources planning and food production. In particular for West Africa, where income largely depends on rainfed agriculture, reliable information on available soil water is required for modeling and prediction. Over large areas and,

  6. Crop yield monitoring in the Sahel using root zone soil moisture anomalies derived from SMOS soil moisture data assimilation

    Science.gov (United States)

    Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian

    2017-04-01

    West Africa is greatly vulnerable, especially in terms of food sustainability. Mainly based on rainfed agriculture, the high variability of the rainy season strongly impacts the crop production driven by the soil water availability in the soil. To monitor this water availability, classical methods are based on daily precipitation measurements. However, the raingauge network suffers from the poor network density in Africa (1/10000km2). Alternatively, real-time satellite-derived precipitations can be used, but they are known to suffer from large uncertainties which produce significant error on crop yield estimations. The present study proposes to use root soil moisture rather than precipitation to evaluate crop yield variations. First, a local analysis of the spatiotemporal impact of water deficit on millet crop production in Niger was done, from in-situ soil moisture measurements (AMMA-CATCH/OZCAR (French Critical Zone exploration network)) and in-situ millet yield survey. Crop yield measurements were obtained for 10 villages located in the Niamey region from 2005 to 2012. The mean production (over 8 years) is 690 kg/ha, and ranges from 381 to 872 kg/ha during this period. Various statistical relationships based on soil moisture estimates were tested, and the most promising one (R>0.9) linked the 30-cm soil moisture anomalies from mid-August to mid-September (grain filling period) to the crop yield anomalies. Based on this local study, it was proposed to derive regional statistical relationships using 30-cm soil moisture maps over West Africa. The selected approach was to use a simple hydrological model, the Antecedent Precipitation Index (API), forced by real-time satellite-based precipitation (CMORPH, PERSIANN, TRMM3B42). To reduce uncertainties related to the quality of real-time rainfall satellite products, SMOS soil moisture measurements were assimilated into the API model through a Particular Filter algorithm. Then, obtained soil moisture anomalies were

  7. Microwave radiometric measurements of soil moisture in Italy

    Directory of Open Access Journals (Sweden)

    G. Macelloni

    2003-01-01

    Full Text Available Within the framework of the MAP and RAPHAEL projects, airborne experimental campaigns were carried out by the IFAC group in 1999 and 2000, using a multifrequency microwave radiometer at L, C and X bands (1.4, 6.8 and 10 GHz. The aim of the experiments was to collect soil moisture and vegetation biomass information on agricultural areas to give reliable inputs to the hydrological models. It is well known that microwave emission from soil, mainly at L-band (1.4 GHz, is very well correlated to its moisture content. Two experimental areas in Italy were selected for this project: one was the Toce Valley, Domodossola, in 1999, and the other, the agricultural area of Cerbaia, close to Florence, where flights were performed in 2000. Measurements were carried out on bare soils, corn and wheat fields in different growth stages and on meadows. Ground data of soil moisture (SMC were collected by other research teams involved in the experiments. From the analysis of the data sets, it has been confirmed that L-band is well related to the SMC of a rather deep soil layer, whereas C-band is sensitive to the surface SMC and is more affected by the presence of surface roughness and vegetation, especially at high incidence angles. An algorithm for the retrieval of soil moisture, based on the sensitivity to moisture of the brightness temperature at C-band, has been tested using the collected data set. The results of the algorithm, which is able to correct for the effect of vegetation by means of the polarisation index at X-band, have been compared with soil moisture data measured on the ground. Finally, the sensitivity of emission at different frequencies to the soil moisture profile was investigated. Experimental data sets were interpreted by using the Integral Equation Model (IEM and the outputs of the model were used to train an artificial neural network to reproduce the soil moisture content at different depths. Keywords: microwave radiometry, soil moisture

  8. An overview of the measurements of soil moisture and modeling of moisture flux in FIFE

    Science.gov (United States)

    Wang, J. R.

    1992-01-01

    Measurements of soil moisture and calculations of moisture transfer in the soil medium and at the air-soil interface were performed over a 15-km by 15-km test site during FIFE in 1987 and 1989. The measurements included intensive soil moisture sampling at the ground level and surveys at aircraft altitudes by several passive and active microwave sensors as well as a gamma radiation device.

  9. A Time Series Analysis of Global Soil Moisture Data Products for Water Cycle Studies

    Science.gov (United States)

    Zhan, X.; Yin, J.; Liu, J.; Fang, L.; Hain, C.; Ferraro, R. R.; Weng, F.

    2017-12-01

    Water is essential for sustaining life on our planet Earth and water cycle is one of the most important processes of out weather and climate system. As one of the major components of the water cycle, soil moisture impacts significantly the other water cycle components (e.g. evapotranspiration, runoff, etc) and the carbon cycle (e.g. plant/crop photosynthesis and respiration). Understanding of soil moisture status and dynamics is crucial for monitoring and predicting the weather, climate, hydrology and ecological processes. Satellite remote sensing has been used for soil moisture observation since the launch of the Scanning Multi-channel Microwave Radiometer (SMMR) on NASA's Nimbus-7 satellite in 1978. Many satellite soil moisture data products have been made available to the science communities and general public. The soil moisture operational product system (SMOPS) of NOAA NESDIS has been operationally providing global soil moisture data products from each of the currently available microwave satellite sensors and their blends. This presentation will provide an update of SMOPS products. The time series of each of these soil moisture data products are analyzed against other data products, such as precipitation and evapotranspiration from other independent data sources such as the North America Land Data Assimilation System (NLDAS). Temporal characteristics of these water cycle components are explored against some historical events, such as the 2010 Russian, 2010 China and 2012 United States droughts, 2015 South Carolina floods, etc. Finally whether a merged global soil moisture data product can be used as a climate data record is evaluated based on the above analyses.

  10. Reducing the Influence of Soil Moisture on the Estimation of Clay from Hyperspectral Data: A Case Study Using Simulated PRISMA Data

    Directory of Open Access Journals (Sweden)

    Fabio Castaldi

    2015-11-01

    Full Text Available Soil moisture hampers the estimation of soil variables such as clay content from remote and proximal sensing data, reducing the strength of the relevant spectral absorption features. In the present study, two different strategies have been evaluated for their ability to minimize the influence of soil moisture on clay estimation by using soil spectra acquired in a laboratory and by simulating satellite hyperspectral data. Simulated satellite data were obtained according to the spectral characteristics of the forthcoming hyperspectral imager on board of the Italian PRISMA satellite mission. The soil datasets were split into four groups according to the water content. For each soil moisture level a prediction model was applied, using either spectral indices or partial least squares regression (PLSR. Prediction models were either specifically developed for the soil moisture level or calibrated using synthetically dry soil spectra, generated from wet soil data. Synthetically dry spectra were obtained using a new technique based on the effects caused by soil moisture on the optical spectrum from 400 to 2400 nm. The estimation of soil clay content, when using different prediction models according to soil moisture, was slightly more accurate as compared to the use of synthetically dry soil spectra, both employing clay indices and PLSR models. The results obtained in this study demonstrate that the a priori knowledge of the soil moisture class can reduce the error of clay estimation when using hyperspectral remote sensing data, such as those that will be provided by the PRISMA satellite mission in the near future.

  11. Collective impacts of soil moisture and orography on deep convective thunderstorms

    Science.gov (United States)

    Imamovic, Adel; Schlemmer, Linda; Schär, Christoph

    2017-04-01

    Thunderstorm activity in many land regions peaks in summer, when surface heat fluxes and the atmospheric moisture content reach an annual maximum. Studies using satellite and ground-based observations have shown that the timing and vigor of summer thunderstorms are influenced by the presence of triggering mechanisms such as soil-moisture heterogeneity or orography. In the current process-based study we aim to dissect the combined impact of soil-moisture and orography on moist convection by using convection-resolving climate simulations with idealized landsurface and orographic conditions. First we systematically investigate the sensitivity of moist convection in absence of orography to a mesoscale soil-moisture anomaly, i.e. a region with drier or moister soil. Consistent with previous studies, a high sensitivity of total rain to soil-moisture anomalies over flat terrain is found. The total rain in the presence of a dry soil-moisture anomaly increases linearly if the soil-moisture anomaly is dried: an anomaly that is 50 % dryer than the reference case with a homogeneous soil-moisture distribution produces up to 40 % more rain. The amplitude of this negative response to the dry soil-moisture anomaly cannot be reproduced by either drying or moistening the soil in the whole domain, even when using unrealistic soil-moisture values. A moist soil anomaly showed little impact on total rain. The triggering effects of the soil-moisture anomalies can be reproduced by an isolated mountain of 250 m height. In order to test to what extent the impact of the soil-moisture anomaly and the mountain are additive, the soil-moisture perturbation method is applied to soil-moisture over the isolated mountain. A 250 m high mountain with drier (moister) soil than its surrounding is found to enhance (suppress) rain amounts. However, the sensitivity of rain amount to the soil-moisture anomaly decreases with the mountain height: A 500 m high mountain is already sufficient to eliminate the

  12. Errors in the calculation of sub-soil moisture probe by equivalent moisture content technique

    International Nuclear Information System (INIS)

    Lakshmipathy, A.V.; Gangadharan, P.

    1982-01-01

    The size of the soil sample required to obtain the saturation response, with a neutron moisture probe is quite large and this poses practical problems of handling and mixing large amounts of samples for absolute laboratory calibration. Hydrogenous materials are used as a substitute for water in the equivalent moisture content technique, for calibration of soil moisture probes. In this it is assumed that only hydrogen of the bulk sample is responsible for the slowing down of fast neutrons and the slow neutron countrate is correlated to equivalent water content by considering the hydrogen density of sample. It is observed that the higher atomic number elements present in water equivalent media also affect the response of the soil moisture probe. Hence calculations, as well as experiments, were undertaken to know the order of error introduced by this technique. The thermal and slow neutron flux distribution around the BF 3 counter of a sub-soil moisture probe is calculated using three group diffusion theory. The response of the probe corresponding to different equivalent moisture content of hydrogenous media, is calculated taking into consideration the effective length of BF 3 counter. Soil with hydrogenous media such as polyethylene, sugar and water are considered for calculation, to verify the suitability of these materials as substitute for water during calibration of soil moisture probe. Experiments were conducted, to verify the theoretically calculated values. (author)

  13. Impact of different satellite soil moisture products on the predictions of a continuous distributed hydrological model

    Science.gov (United States)

    Laiolo, P.; Gabellani, S.; Campo, L.; Silvestro, F.; Delogu, F.; Rudari, R.; Pulvirenti, L.; Boni, G.; Fascetti, F.; Pierdicca, N.; Crapolicchio, R.; Hasenauer, S.; Puca, S.

    2016-06-01

    The reliable estimation of hydrological variables in space and time is of fundamental importance in operational hydrology to improve the flood predictions and hydrological cycle description. Nowadays remotely sensed data can offer a chance to improve hydrological models especially in environments with scarce ground based data. The aim of this work is to update the state variables of a physically based, distributed and continuous hydrological model using four different satellite-derived data (three soil moisture products and a land surface temperature measurement) and one soil moisture analysis to evaluate, even with a non optimal technique, the impact on the hydrological cycle. The experiments were carried out for a small catchment, in the northern part of Italy, for the period July 2012-June 2013. The products were pre-processed according to their own characteristics and then they were assimilated into the model using a simple nudging technique. The benefits on the model predictions of discharge were tested against observations. The analysis showed a general improvement of the model discharge predictions, even with a simple assimilation technique, for all the assimilation experiments; the Nash-Sutcliffe model efficiency coefficient was increased from 0.6 (relative to the model without assimilation) to 0.7, moreover, errors on discharge were reduced up to the 10%. An added value to the model was found in the rainfall season (autumn): all the assimilation experiments reduced the errors up to the 20%. This demonstrated that discharge prediction of a distributed hydrological model, which works at fine scale resolution in a small basin, can be improved with the assimilation of coarse-scale satellite-derived data.

  14. Logging effects on soil moisture losses

    Science.gov (United States)

    Robert R. Ziemer

    1978-01-01

    Abstract - The depletion of soil moisture within the surface 15 feet by an isolated mature sugar pine and an adjacent uncut forest in the California Sierra Nevada was measured by the neutron method every 2 weeks for 5 consecutive summers. Soil moisture recharge was measured periodically during the intervening winters. Groundwater fluctuations within the surface 50...

  15. Propagation of soil moisture memory to runoff and evapotranspiration

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2012-10-01

    As a key variable of the land-climate system soil moisture is a main driver of runoff and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Also for runoff many studies report distinct low frequency variations that represent a memory. Using data from over 100 near-natural catchments located across Europe we investigate in this study the connection between soil moisture memory and the respective memory of runoff and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalized by precipitation) and evapotranspiration (normalized by radiation) on soil moisture are fitted using runoff observations. The model therefore allows to compute memory of soil moisture, runoff and evapotranspiration on catchment scale. We find considerable memory in soil moisture and runoff in many parts of the continent, and evapotranspiration also displays some memory on a monthly time scale in some catchments. We show that the memory of runoff and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of runoff and evapotranspiration to soil moisture. Furthermore we find that the coupling strengths of runoff and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  16. CPC Soil Moisture

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The monthly data set consists of a file containing 1/2 degree monthly averaged soil moisture water height equivalents for the globe from 1948 onwards. Values are...

  17. Assimilation of SMOS Soil Moisture Retrievals in the Land Information System

    Science.gov (United States)

    Blakenship, Clay; Zavodsky, Bradley; Cae, Jonathan

    2014-01-01

    Soil moisture is a crucial variable for weather prediction because of its influence on evaporation. It is of critical importance for drought and flood monitoring and prediction and for public health applications. The NASA Short-term Prediction Research and Transition Center (SPoRT) has implemented a new module in the NASA Land Information System (LIS) to assimilate observations from the ESA's Soil Moisture and Ocean Salinity (SMOS) satellite. SMOS Level 2 retrievals from the Microwave Imaging Radiometer using Aperture Synthesis (MIRAS) instrument are assimilated into the Noah LSM within LIS via an Ensemble Kalman Filter. The retrievals have a target volumetric accuracy of 4% at a resolution of 35-50 km. Parallel runs with and without SMOS assimilation are performed with precipitation forcing from intentionally degraded observations, and then validated against a model run using the best available precipitation data, as well as against selected station observations. The goal is to demonstrate how SMOS data assimilation can improve modeled soil states in the absence of dense rain gauge and radar networks.

  18. A soil moisture-rainfall feedback mechanism. 1. Theory and observations

    International Nuclear Information System (INIS)

    Eltahir, E.A.B.

    1998-01-01

    This paper presents a hypothesis regarding the fundamental role of soil moisture conditions in land-atmosphere interactions. We propose that wet soil moisture conditions over any large region should be associated with relatively large boundary layer moist static energy, which favors the occurrence of more rainfall. Since soil moisture conditions themselves reflect past occurrence of rainfall, the proposed hypothesis implies a positive feedback mechanism between soil moisture and rainfall. This mechanism is based on considerations of the energy balance at the land-atmosphere boundary, in contrast to similar mechanisms that were proposed in the past and that were based on the concepts of water balance and precipitation recycling. The control of soil moisture on surface albedo and Bowen ratio is the fundamental basis of the proposed soil moisture-rainfall feedback mechanism. The water content in the upper soil layer affects these two important properties of the land surface such that both variables decrease with any increase in the water content of the top soil layer. The direct effect of soil moisture on surface albedo implies that wet soil moisture conditions enhance net solar radiation. The direct effect of soil moisture on Bowen ratio dictates that wet soil moisture conditions would tend to enhance net terrestrial radiation at the surface through cooling of surface temperature, reduction of upwards emissions of terrestrial radiation, and simultaneous increase in atmospheric water vapor content and downwards flux of terrestrial radiation. Thus, under wet soil moisture conditions, both components of net radiation are enhanced, resulting in a larger total flux of heat from the surface into the boundary layer. This total flux represents the sum of the corresponding sensible and latent heat fluxes. Simultaneously, cooling of surface temperature should be associated with a smaller sensible heat flux and a smaller depth of the boundary layer

  19. Development of an Integrated Moisture Index for predicting species composition

    Science.gov (United States)

    Louis R. Iverson; Charles T. Scott; Martin E. Dale; Anantha Prasad

    1996-01-01

    A geographic information system (GIS) approach was used to develop an Integrated Moisture Index (IMI), which was used to predict species composition for Ohio forests. Several landscape features (a slope-aspect shading index, cumulative flow of water downslope, curvature of the landscape, and the water-holding capacity of the soil) were derived from elevation and soils...

  20. The Impact of Model and Rainfall Forcing Errors on Characterizing Soil Moisture Uncertainty in Land Surface Modeling

    Science.gov (United States)

    Maggioni, V.; Anagnostou, E. N.; Reichle, R. H.

    2013-01-01

    The contribution of rainfall forcing errors relative to model (structural and parameter) uncertainty in the prediction of soil moisture is investigated by integrating the NASA Catchment Land Surface Model (CLSM), forced with hydro-meteorological data, in the Oklahoma region. Rainfall-forcing uncertainty is introduced using a stochastic error model that generates ensemble rainfall fields from satellite rainfall products. The ensemble satellite rain fields are propagated through CLSM to produce soil moisture ensembles. Errors in CLSM are modeled with two different approaches: either by perturbing model parameters (representing model parameter uncertainty) or by adding randomly generated noise (representing model structure and parameter uncertainty) to the model prognostic variables. Our findings highlight that the method currently used in the NASA GEOS-5 Land Data Assimilation System to perturb CLSM variables poorly describes the uncertainty in the predicted soil moisture, even when combined with rainfall model perturbations. On the other hand, by adding model parameter perturbations to rainfall forcing perturbations, a better characterization of uncertainty in soil moisture simulations is observed. Specifically, an analysis of the rank histograms shows that the most consistent ensemble of soil moisture is obtained by combining rainfall and model parameter perturbations. When rainfall forcing and model prognostic perturbations are added, the rank histogram shows a U-shape at the domain average scale, which corresponds to a lack of variability in the forecast ensemble. The more accurate estimation of the soil moisture prediction uncertainty obtained by combining rainfall and parameter perturbations is encouraging for the application of this approach in ensemble data assimilation systems.

  1. Soil-moisture transport in arid site vadose zones

    International Nuclear Information System (INIS)

    Isaacson, R.E.; Brownell, L.E.; Nelson, R.W.; Roetman, E.L.

    1974-01-01

    Soil-moisture transport processes in the arid soils of the United States Atomic Energy Commission's Hanford site are being evaluated. The depth of penetration of meteoric precipitation has been determined by profiling fall-out tritium at two locations where the water table is about 90 m below ground surface. In situ temperatures and water potentials were measured with temperature transducers and thermocouple psychrometers at the same location to obtain thermodynamic data for identifying the factors influencing soil-moisture transport. Neutron probes are being used to monitor soil-moisture changes in two lysimeters, three metres in diameter by 20 metres deep. The lysimeters are also equipped to measure pressure, temperature and relative humidity as a function of depth and time. Theoretical models based on conservation of momentum expressions are being developed to analyse non-isothermal soil-moisture transport processes. Future work will be concerned with combining the theoretical and experimental work and determining the amount of rainfall required to cause migration of soil-moisture to the water table. (author)

  2. A Novel Bias Correction Method for Soil Moisture and Ocean Salinity (SMOS Soil Moisture: Retrieval Ensembles

    Directory of Open Access Journals (Sweden)

    Ju Hyoung Lee

    2015-12-01

    Full Text Available Bias correction is a very important pre-processing step in satellite data assimilation analysis, as data assimilation itself cannot circumvent satellite biases. We introduce a retrieval algorithm-specific and spatially heterogeneous Instantaneous Field of View (IFOV bias correction method for Soil Moisture and Ocean Salinity (SMOS soil moisture. To the best of our knowledge, this is the first paper to present the probabilistic presentation of SMOS soil moisture using retrieval ensembles. We illustrate that retrieval ensembles effectively mitigated the overestimation problem of SMOS soil moisture arising from brightness temperature errors over West Africa in a computationally efficient way (ensemble size: 12, no time-integration. In contrast, the existing method of Cumulative Distribution Function (CDF matching considerably increased the SMOS biases, due to the limitations of relying on the imperfect reference data. From the validation at two semi-arid sites, Benin (moderately wet and vegetated area and Niger (dry and sandy bare soils, it was shown that the SMOS errors arising from rain and vegetation attenuation were appropriately corrected by ensemble approaches. In Benin, the Root Mean Square Errors (RMSEs decreased from 0.1248 m3/m3 for CDF matching to 0.0678 m3/m3 for the proposed ensemble approach. In Niger, the RMSEs decreased from 0.14 m3/m3 for CDF matching to 0.045 m3/m3 for the ensemble approach.

  3. Influence of moisture content on radon diffusion in soil

    International Nuclear Information System (INIS)

    Singh, M.; Ramola, R.C.; Singh, S.; Virk, H.S.

    1990-01-01

    Radon diffusion from soil has been studied as a function of the moisture content of the soil. A few simple experiments showed that up to a certain moisture content the radon diffusion increased with increasing moisture. A sharp rise in radon concentration occurred as the moisture was increased from the completely dry state to 13% water by weight. The radon flux was measured for columns of dry, moist and water saturated soil. The highest flux came from the column filled with moist soil. Water saturated soil gave the lowest flux because of the much lower diffusion coefficient of radon through water. (author)

  4. Comparisons of Satellite Soil Moisture, an Energy Balance Model Driven by LST Data and Point Measurements

    Science.gov (United States)

    Laiolo, Paola; Gabellani, Simone; Rudari, Roberto; Boni, Giorgio; Puca, Silvia

    2013-04-01

    Soil moisture plays a fundamental role in the partitioning of mass and energy fluxes between land surface and atmosphere, thereby influencing climate and weather, and it is important in determining the rainfall-runoff response of catchments; moreover, in hydrological modelling and flood forecasting, a correct definition of moisture conditions is a key factor for accurate predictions. Different sources of information for the estimation of the soil moisture state are currently available: satellite data, point measurements and model predictions. All are affected by intrinsic uncertainty. Among different satellite sensors that can be used for soil moisture estimation three major groups can be distinguished: passive microwave sensors (e.g., SSMI), active sensors (e.g. SAR, Scatterometers), and optical sensors (e.g. Spectroradiometers). The last two families, mainly because of their temporal and spatial resolution seem the most suitable for hydrological applications In this work soil moisture point measurements from 10 sensors in the Italian territory are compared of with the satellite products both from the HSAF project SM-OBS-2, derived from the ASCAT scatterometer, and from ACHAB, an operative energy balance model that assimilate LST data derived from MSG and furnishes daily an evaporative fraction index related to soil moisture content for all the Italian region. Distributed comparison of the ACHAB and SM-OBS-2 on the whole Italian territory are performed too.

  5. The ASCAT soil moisture product. A Review of its specifications, validation results, and emerging applications

    Energy Technology Data Exchange (ETDEWEB)

    Wagner, Wolfgang; Hahn, Sebastian; Kidd, Richard [Vienna Univ. of Technology (Austria). Dept. of Geodesy and Geoinformation] [and others

    2013-02-15

    provide a comprehensive overview of the major characteristics and caveats of the ASCAT soil moisture product, this paper describes the ASCAT instrument and the soil moisture processor and near-real-time distribution service implemented by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT). A review of the most recent validation studies shows that the quality of ASCAT soil moisture product is - with the exception of arid environments -comparable to, and over some regions (e.g. Europe) even better than currently available soil moisture data derived from passive microwave sensors. Further, a review of applications studies shows that the use of the ASCAT soil moisture product is particularly advanced in the fields of numerical weather prediction and hydrologic modelling. But also in other application areas such as yield monitoring, epidemiologic modelling, or societal risks assessment some first progress can be noted. Considering the generally positive evaluation results, it is expected that the ASCAT soil moisture product will increasingly be used by a growing number of rather diverse land applications. (orig.)

  6. The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications

    Directory of Open Access Journals (Sweden)

    Wolfgang Wagner

    2013-02-01

    applications. To provide a comprehensive overview of the major characteristics and caveats of the ASCAT soil moisture product, this paper describes the ASCAT instrument and the soil moisture processor and near-real-time distribution service implemented by the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT. A review of the most recent validation studies shows that the quality of ASCAT soil moisture product is - with the exception of arid environments -comparable to, and over some regions (e.g. Europe even better than currently available soil moisture data derived from passive microwave sensors. Further, a review of applications studies shows that the use of the ASCAT soil moisture product is particularly advanced in the fields of numerical weather prediction and hydrologic modelling. But also in other application areas such as yield monitoring, epidemiologic modelling, or societal risks assessment some first progress can be noted. Considering the generally positive evaluation results, it is expected that the ASCAT soil moisture product will increasingly be used by a growing number of rather diverse land applications.

  7. Mapping The Temporal and Spatial Variability of Soil Moisture Content Using Proximal Soil Sensing

    Science.gov (United States)

    Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.

    2018-05-01

    In studies related to soil optical properties, it has been proven that visual and NIR soil spectral response can predict soil moisture content (SMC) using proper data analysis techniques. SMC is one of the most important soil properties influencing most physical, chemical, and biological soil processes. The problem is how to provide reliable, fast and inexpensive information of SMC in the subsurface from numerous soil samples and repeated measurement. The use of spectroscopy technology has emerged as a rapid and low-cost tool for extensive investigation of soil properties. The objective of this research was to develop calibration models based on laboratory Vis-NIR spectroscopy to estimate the SMC at four different growth stages of the soybean crop in Yogyakarta Province. An ASD Field-spectrophotoradiometer was used to measure the reflectance of soil samples. The partial least square regression (PLSR) was performed to establish the relationship between the SMC with Vis-NIR soil reflectance spectra. The selected calibration model was used to predict the new samples of SMC. The temporal and spatial variability of SMC was performed in digital maps. The results revealed that the calibration model was excellent for SMC prediction. Vis-NIR spectroscopy was a reliable tool for the prediction of SMC.

  8. The sensitivity of US wildfire occurrence to pre-season soil moisture conditions across ecosystems

    Science.gov (United States)

    Jensen, Daniel; Reager, John T.; Zajic, Brittany; Rousseau, Nick; Rodell, Matthew; Hinkley, Everett

    2018-01-01

    It is generally accepted that year-to-year variability in moisture conditions and drought are linked with increased wildfire occurrence. However, quantifying the sensitivity of wildfire to surface moisture state at seasonal lead-times has been challenging due to the absence of a long soil moisture record with the appropriate coverage and spatial resolution for continental-scale analysis. Here we apply model simulations of surface soil moisture that numerically assimilate observations from NASA’s Gravity Recovery and Climate Experiment (GRACE) mission with the USDA Forest Service’s historical Fire-Occurrence Database over the contiguous United States. We quantify the relationships between pre-fire-season soil moisture and subsequent-year wildfire occurrence by land-cover type and produce annual probable wildfire occurrence and burned area maps at 0.25 degree resolution. Cross-validated results generally indicate a higher occurrence of smaller fires when months preceding fire season are wet, while larger fires are more frequent when soils are dry. This is consistent with the concept of increased fuel accumulation under wet conditions in the pre-season. These results demonstrate the fundamental strength of the relationship between soil moisture and fire activity at long lead-times and are indicative of that relationship’s utility for the future development of national-scale predictive capability.

  9. Detection of soil moisture impact in convective initiation in the central region of Mexico

    Science.gov (United States)

    Dolores, Edgar; Caetano, Ernesto

    2017-04-01

    Soil moisture is important for understanding hydrological cycle variability in many regions. Local surface heat and moisture fluxes represent a major source of convective rainfall in Mexico during the summer, driven by positive evaporation-precipitation feedback. The effects of soil moisture are directly reflected in the limitation of evapotranspiration, affecting the development of the planetary boundary layer and, therefore, the initiation and intensity of convective precipitation. This study presents preliminary analysis of the role of soil moisture in convective initiations in central Mexico, for which a methodology for the detection of convective initiations similar to Taylor (2015) has been considered. The results show that the moisture fluxes from the surface influence the development of convection favored by mesoscale circulations at low levels. Initiations are more frequent in regions less humid than their surroundings with the very strong signal during the month of September. The knowledge of the soil predisposition to allow the development of deep convection suggests an alternative tool for the prediction of convective rains in Mexico.

  10. Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

    NARCIS (Netherlands)

    Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

    Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture

  11. Soil moisture effects on seasonal temperature and precipitation forecast scores in Europe

    Energy Technology Data Exchange (ETDEWEB)

    Hurk, Bart van den; Camargo, Helio [Royal Netherlands Meteorological Institute, KNMI, PO Box 201, AE De Bilt (Netherlands); Doblas-Reyes, Francisco [Catalan Institute of Climate Sciences (IC3), Barcelona (Spain); European Centre for Medium-range Weather Forecasts (ECMWF), Reading (United Kingdom); Balsamo, Gianpaolo [European Centre for Medium-range Weather Forecasts (ECMWF), Reading (United Kingdom); Koster, Randal D. [NASA/Goddard Space Flight Center, Global Modeling and Assimilation Office, Greenbelt, MD (United States); Seneviratne, Sonia I. [Institute for Atmospheric and Climate Science, Zurich (Switzerland)

    2012-01-15

    The Second Global Land Atmosphere Coupling Experiment (GLACE2) is designed to explore the improvement of forecast skill of summertime temperature and precipitation up to 8 weeks ahead by using realistic soil moisture initialization. For the European continent, we show in this study that for temperature the skill does indeed increase up to 6 weeks, but areas with (statistically significant) lower skill also exist at longer lead times. The skill improvement is smaller than shown earlier for the US, partly because of a lower potential predictability of the European climate at seasonal time scales. Selection of extreme soil moisture conditions or a subset of models with similar initial soil moisture conditions does improve the forecast skill, and sporadic positive effects are also demonstrated for precipitation. Using realistic initial soil moisture data increases the interannual variability of temperature compared to the control simulations in the South-Central European area at longer lead times. This leads to better temperature forecasts in a remote area in Western Europe. However, the covered range of forecast dates (1986-1995) is too short to isolate a clear physical mechanism for this remote correlation. (orig.)

  12. Use of Ultrasonic Technology for Soil Moisture Measurement

    Science.gov (United States)

    Choi, J.; Metzl, R.; Aggarwal, M. D.; Belisle, W.; Coleman, T.

    1997-01-01

    In an effort to improve existing soil moisture measurement techniques or find new techniques using physics principles, a new technique is presented in this paper using ultrasonic techniques. It has been found that ultrasonic velocity changes as the moisture content changes. Preliminary values of velocities are 676.1 m/s in dry soil and 356.8 m/s in 100% moist soils. Intermediate values can be calibrated to give exact values for the moisture content in an unknown sample.

  13. Design and Test of a Soil Profile Moisture Sensor Based on Sensitive Soil Layers

    Science.gov (United States)

    Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun

    2018-01-01

    To meet the demand of intelligent irrigation for accurate moisture sensing in the soil vertical profile, a soil profile moisture sensor was designed based on the principle of high-frequency capacitance. The sensor consists of five groups of sensing probes, a data processor, and some accessory components. Low-resistivity copper rings were used as components of the sensing probes. Composable simulation of the sensor’s sensing probes was carried out using a high-frequency structure simulator. According to the effective radiation range of electric field intensity, width and spacing of copper ring were set to 30 mm and 40 mm, respectively. A parallel resonance circuit of voltage-controlled oscillator and high-frequency inductance-capacitance (LC) was designed for signal frequency division and conditioning. A data processor was used to process moisture-related frequency signals for soil profile moisture sensing. The sensor was able to detect real-time soil moisture at the depths of 20, 30, and 50 cm and conduct online inversion of moisture in the soil layer between 0–100 cm. According to the calibration results, the degree of fitting (R2) between the sensor’s measuring frequency and the volumetric moisture content of soil sample was 0.99 and the relative error of the sensor consistency test was 0–1.17%. Field tests in different loam soils showed that measured soil moisture from our sensor reproduced the observed soil moisture dynamic well, with an R2 of 0.96 and a root mean square error of 0.04. In a sensor accuracy test, the R2 between the measured value of the proposed sensor and that of the Diviner2000 portable soil moisture monitoring system was higher than 0.85, with a relative error smaller than 5%. The R2 between measured values and inversed soil moisture values for other soil layers were consistently higher than 0.8. According to calibration test and field test, this sensor, which features low cost, good operability, and high integration, is qualified for

  14. Effect of soil moisture and treatment volume on bentazone mobility in soil

    OpenAIRE

    Guimont, Sophie; Perrin-Ganier, Corinne; Real, Benoit; Schiavon, Michel

    2005-01-01

    Soil moisture affects the leaching behaviour of pesticides by inducing their physical entrapment in the soil structure. Columns containing soil aggregates were dampened to specific initial moisture levels. Bentazon was dripped onto surface aggregates in different volumes. The columns were then percolated after an equilibration period. Soil water from the columns was divided arbitrarily among mobile and immobile regions in order to describe the herbicide redistribution processes in the soil. W...

  15. Analytical analysis of soil-moisture and trace-contaminant transport

    International Nuclear Information System (INIS)

    Larson, N.M.; Reeves, M.

    1976-03-01

    A transport model is presented which predicts the coupled movement of both water and trace contaminants through a layered and unsaturated soil-moisture zone. In order to achieve computation speeds suitable for watershed implementations, moisture properties are approximated as exponential functions of pressure head, and lateral flows are treated as sinks in a basically vertical one-dimensional analysis. In addition, only advection by the Darcy-flow velocities and linear adsorption by the soil matrix are considered in depicting movement of the trace contaminant. Formal solution of the resulting transport equations is obtained through use of both eigenfunction-expansion and coordinate-transformation methods. Numerical solution is effected by means of a program written in FORTRAN IV and implemented on an IBM 360/91 computer. Two example calculations illustrate both strengths and weaknesses of our model

  16. Comparing soil moisture memory in satellite observations and models

    Science.gov (United States)

    Stacke, Tobias; Hagemann, Stefan; Loew, Alexander

    2013-04-01

    A major obstacle to a correct parametrization of soil processes in large scale global land surface models is the lack of long term soil moisture observations for large parts of the globe. Currently, a compilation of soil moisture data derived from a range of satellites is released by the ESA Climate Change Initiative (ECV_SM). Comprising the period from 1978 until 2010, it provides the opportunity to compute climatological relevant statistics on a quasi-global scale and to compare these to the output of climate models. Our study is focused on the investigation of soil moisture memory in satellite observations and models. As a proxy for memory we compute the autocorrelation length (ACL) of the available satellite data and the uppermost soil layer of the models. Additional to the ECV_SM data, AMSR-E soil moisture is used as observational estimate. Simulated soil moisture fields are taken from ERA-Interim reanalysis and generated with the land surface model JSBACH, which was driven with quasi-observational meteorological forcing data. The satellite data show ACLs between one week and one month for the greater part of the land surface while the models simulate a longer memory of up to two months. Some pattern are similar in models and observations, e.g. a longer memory in the Sahel Zone and the Arabian Peninsula, but the models are not able to reproduce regions with a very short ACL of just a few days. If the long term seasonality is subtracted from the data the memory is strongly shortened, indicating the importance of seasonal variations for the memory in most regions. Furthermore, we analyze the change of soil moisture memory in the different soil layers of the models to investigate to which extent the surface soil moisture includes information about the whole soil column. A first analysis reveals that the ACL is increasing for deeper layers. However, its increase is stronger in the soil moisture anomaly than in its absolute values and the first even exceeds the

  17. Use of passive microwave remote sensing to monitor soil moisture

    International Nuclear Information System (INIS)

    Wigneron, J.P.; Schmugge, T.; Chanzy, A.; Calvet, J.C.; Kerr, Y.

    1998-01-01

    Surface soil moisture is a key variable to describe the water and energy exchanges at the land surface/atmosphere interface. However, soil moisture is highly variable both spatially and temporally. Passive microwave remotely sensed data have great potential for providing estimates of soil moisture with good temporal repetition (on a daily basis) and at regional scale (∼ 10 km). This paper reviews the various methods for remote sensing of soil moisture from microwave radiometric systems. Potential applications from both airborne and spatial observations are discussed in the fields of agronomy, hydrology and meteorology. Emphasis in this paper is given to relatively new aspects of microwave techniques and of temporal soil moisture information analysis. In particular, the aperture synthesis technique allows us now to a address the soil moisture information needs on a global basis, from space instruments. (author) [fr

  18. Implementing a physical soil water flow model with minimal soil characteristics and added value offered by surface soil moisture measurements assimilation.

    Science.gov (United States)

    Chanzy, André

    2010-05-01

    Soil moisture is a key variable for many soil physical and biogeochemical processes. Its dynamic results from water fluxes in soil and at its boundaries, as well as soil water storage properties. If the water flows are dominated by diffusive processes, modelling approaches based on the Richard's equation or the Philip and de Vries coupled heat and water flow equations lead to a satisfactory representation of the soil moisture dynamic. However, It requires the characterization of soil hydraulic functions, the initialisation and the boundary conditions, which are expensive to obtain. The major problem to assess soil moisture for decision making or for representing its spatiotemporal evolution over complex landscape is therefore the lack of information to run the models. The aim of the presentation is to analyse how a soil moisture model can be implemented when only climatic data and basic soil information are available (soil texture, organic matter) and what would be the added of making a few soil moisture measurements. We considered the field scale, which is the key scale for decision making application (the field being the management unit for farming system) and landscape modelling (field size being comparable to the computation unit of distributed hydrological models). The presentation is limited to the bare soil case in order to limit the complexity of the system and the TEC model based on Philip and De Vries equations is used in this study. The following points are addressed: o the within field spatial variability. This spatial variability can be induced by the soil hydraulic properties and/or by the amount of infiltrated water induced by water rooting towards infiltration areas. We analyse how an effective parameterization of soil properties and boundary conditions can be used to simulate the field average moisture. o The model implementation with limited information. We propose strategies that can be implemented when information are limited to soil texture and

  19. A Technical Design Approach to Soil Moisture Content Measurement

    African Journals Online (AJOL)

    Soil moisture is an important type of data in many fields; ranging from agriculture to environmental monitoring. Three soil samples were collected at definite proportions to represent the three basic soil types (sandy, loamy and clay soils). The moisture contents of these soil samples were analyzed using the thermogravimetric ...

  20. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    user

    soil moisture meter using the NE555 timer and micro controller as a major electronic component ... relationship between the moisture content process and the digital soil moisture meter. ..... the moisture contents showing that the infiltration of.

  1. Soil moisture dynamics and smoldering combustion limits of pocosin soils in North Carolina, USA

    Science.gov (United States)

    James Reardon; Gary Curcio; Roberta Bartlette

    2009-01-01

    Smoldering combustion of wetland organic soils in the south-eastern USA is a serious management concern. Previous studies have reported smoldering was sensitive to a wide range of moisture contents, but studies of soil moisture dynamics and changing smoldering combustion potential in wetland communities are limited. Linking soil moisture measurements with estimates of...

  2. Development and Assessment of the Sand Dust Prediction Model by Utilizing Microwave-Based Satellite Soil Moisture and Reanalysis Datasets in East Asian Desert Areas

    Directory of Open Access Journals (Sweden)

    Hyunglok Kim

    2017-01-01

    Full Text Available For several decades, satellite-based microwave sensors have provided valuable soil moisture monitoring in various surface conditions. We have first developed a modeled aerosol optical depth (AOD dataset by utilizing Soil Moisture and Ocean Salinity (SMOS, Advanced Microwave Scanning Radiometer 2 (AMSR2, and the Global Land Data Assimilation System (GLDAS soil moisture datasets in order to estimate dust outbreaks over desert areas of East Asia. Moderate Resolution Imaging Spectroradiometer- (MODIS- based AOD products were used as reference datasets to validate the modeled AOD (MA. The SMOS-based MA (SMOS-MA dataset showed good correspondence with observed AOD (R-value: 0.56 compared to AMSR2- and GLDAS-based MA datasets, and it overestimated AOD compared to observed AOD. The AMSR2-based MA dataset was found to underestimate AOD, and it showed a relatively low R-value (0.35 with respect to observed AOD. Furthermore, SMOS-MA products were able to simulate the short-term AOD trends, having a high R-value (0.65. The results of this study may allow us to acknowledge the utilization of microwave-based soil moisture datasets for investigation of near-real time dust outbreak predictions and short-term dust outbreak trend analysis.

  3. Pore-scale investigation on the response of heterotrophic respiration to moisture conditions in heterogeneous soils

    Energy Technology Data Exchange (ETDEWEB)

    Yan, Zhifeng; Liu, Chongxuan; Todd-Brown, Katherine E.; Liu, Yuanyuan; Bond-Lamberty, Ben; Bailey, Vanessa L.

    2016-11-15

    The relationship between microbial respiration rate and soil moisture content is an important property for understanding and predicting soil organic carbon degradation, CO2 production and emission, and their subsequent effects on climate change. This paper reports a pore-scale modeling study to investigate the response of heterotrophic respiration to moisture conditions in soils and to evaluate various factors that affect this response. X-ray computed tomography was used to derive soil pore structures, which were then used for pore-scale model investigation. The pore-scale results were then averaged to calculate the effective respiration rates as a function of water content in soils. The calculated effective respiration rate first increases and then decreases with increasing soil water content, showing a maximum respiration rate at water saturation degree of 0.75 that is consistent with field and laboratory observations. The relationship between the respiration rate and moisture content is affected by various factors, including pore-scale organic carbon bioavailability, the rate of oxygen delivery, soil pore structure and physical heterogeneity, soil clay content, and microbial drought resistivity. Simulations also illustrates that a larger fraction of CO2 produced from microbial respiration can be accumulated inside soil cores under higher saturation conditions, implying that CO2 flux measured on the top of soil cores may underestimate or overestimate true soil respiration rates under dynamic moisture conditions. Overall, this study provides mechanistic insights into the soil respiration response to the change in moisture conditions, and reveals a complex relationship between heterotrophic microbial respiration rate and moisture content in soils that is affected by various hydrological, geochemical, and biophysical factors.

  4. An integrated GIS application system for soil moisture data assimilation

    Science.gov (United States)

    Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

    2014-11-01

    The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

  5. Soil microbial community responses to antibiotic-contaminated manure under different soil moisture regimes.

    Science.gov (United States)

    Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören

    2014-01-01

    Sulfadiazine (SDZ) is an antibiotic frequently administered to livestock, and it alters microbial communities when entering soils with animal manure, but understanding the interactions of these effects to the prevailing climatic regime has eluded researchers. A climatic factor that strongly controls microbial activity is soil moisture. Here, we hypothesized that the effects of SDZ on soil microbial communities will be modulated depending on the soil moisture conditions. To test this hypothesis, we performed a 49-day fully controlled climate chamber pot experiments with soil grown with Dactylis glomerata (L.). Manure-amended pots without or with SDZ contamination were incubated under a dynamic moisture regime (DMR) with repeated drying and rewetting changes of >20 % maximum water holding capacity (WHCmax) in comparison to a control moisture regime (CMR) at an average soil moisture of 38 % WHCmax. We then monitored changes in SDZ concentration as well as in the phenotypic phospholipid fatty acid and genotypic 16S rRNA gene fragment patterns of the microbial community after 7, 20, 27, 34, and 49 days of incubation. The results showed that strongly changing water supply made SDZ accessible to mild extraction in the short term. As a result, and despite rather small SDZ effects on community structures, the PLFA-derived microbial biomass was suppressed in the SDZ-contaminated DMR soils relative to the CMR ones, indicating that dynamic moisture changes accelerate the susceptibility of the soil microbial community to antibiotics.

  6. Assessment of the SMAP Passive Soil Moisture Product

    Science.gov (United States)

    Chan, Steven K.; Bindlish, Rajat; O'Neill, Peggy E.; Njoku, Eni; Jackson, Tom; Colliander, Andreas; Chen, Fan; Burgin, Mariko; Dunbar, Scott; Piepmeier, Jeffrey; hide

    2016-01-01

    The National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) satellite mission was launched on January 31, 2015. The observatory was developed to provide global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using an L-band (active) radar and an L-band (passive) radiometer. After an irrecoverable hardware failure of the radar on July 7, 2015, the radiometer-only soil moisture product became the only operational Level 2 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 kilometer Earth-fixed grid produced using brightness temperature observations from descending passes. Within months after the commissioning of the SMAP radiometer, the product was assessed to have attained preliminary (beta) science quality, and data were released to the public for evaluation in September 2015. The product is available from the NASA Distributed Active Archive Center at the National Snow and Ice Data Center. This paper provides a summary of the Level 2 Passive Soil Moisture Product (L2_SM_P) and its validation against in situ ground measurements collected from different data sources. Initial in situ comparisons conducted between March 31, 2015 and October 26, 2015, at a limited number of core validation sites (CVSs) and several hundred sparse network points, indicate that the V-pol Single Channel Algorithm (SCA-V) currently delivers the best performance among algorithms considered for L2_SM_P, based on several metrics. The accuracy of the soil moisture retrievals averaged over the CVSs was 0.038 cubic meter per cubic meter unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 cubic meter per cubic meter.

  7. Thresholds and interactive effects of soil moisture on the temperature response of soil respiration

    DEFF Research Database (Denmark)

    Lellei-Kovács, Eszter; Kovács-Láng, Edit; Botta-Dukát, Zoltán

    2011-01-01

    efflux is soil temperature, while soil moisture has less, although significant effect on soil respiration. Clear thresholds for moisture effects on temperature sensitivity were identified at 0.6, 4.0 and 7.0vol% by almost each model, which relate well to other known limits for biological activity......Ecosystem carbon exchange is poorly understood in low-productivity, semiarid habitats. Here we studied the controls of soil temperature and moisture on soil respiration in climate change field experiment in a sandy forest-steppe. Soil CO2 efflux was measured monthly from April to November in 2003......–2008 on plots receiving either rain exclusion or nocturnal warming, or serving as ambient control. Based on this dataset, we developed and compared empirical models of temperature and moisture effects on soil respiration. Results suggest that in this semiarid ecosystem the main controlling factor for soil CO2...

  8. Integration of GIS, Geostatistics, and 3-D Technology to Assess the Spatial Distribution of Soil Moisture

    Science.gov (United States)

    Betts, M.; Tsegaye, T.; Tadesse, W.; Coleman, T. L.; Fahsi, A.

    1998-01-01

    The spatial and temporal distribution of near surface soil moisture is of fundamental importance to many physical, biological, biogeochemical, and hydrological processes. However, knowledge of these space-time dynamics and the processes which control them remains unclear. The integration of geographic information systems (GIS) and geostatistics together promise a simple mechanism to evaluate and display the spatial and temporal distribution of this vital hydrologic and physical variable. Therefore, this research demonstrates the use of geostatistics and GIS to predict and display soil moisture distribution under vegetated and non-vegetated plots. The research was conducted at the Winfred Thomas Agricultural Experiment Station (WTAES), Hazel Green, Alabama. Soil moisture measurement were done on a 10 by 10 m grid from tall fescue grass (GR), alfalfa (AA), bare rough (BR), and bare smooth (BS) plots. Results indicated that variance associated with soil moisture was higher for vegetated plots than non-vegetated plots. The presence of vegetation in general contributed to the spatial variability of soil moisture. Integration of geostatistics and GIS can improve the productivity of farm lands and the precision of farming.

  9. Relationship between Depth of Soil Moisture Assessment and Turgidity of Coffee Plant in Selected Agroclimates

    Directory of Open Access Journals (Sweden)

    Rudy Erwiyono

    2008-05-01

    Full Text Available Observation on the relationship between the depth of soil moisture assessment and turgidity of coffee plant has been carried out at 3 different agroclimates by survey method, i.e. Andungsari experimental station (Andosol soil type, >1.000 m asl. high, and rainfall type of C, Sumberasin experimental station (yellowish-red Mediterranean soil type, 450-500 m asl. high, and rainfall type of C, and Kaliwining experimental station (low humic glei soil type, 45 m asl. high, and rainfall type of D in order to assess the depth of soil moisture through soil profile influencing turgidity of coffee plants at three different agroclimates. The method of assessment is by fitting the relationship between the depth of soil moisture assessment and turgidity of coffee plant and their determination coefficients through the period of dry season up to early rainy season. Plant turgidity is evaluated from its relative water contents of the leaves sampled periodically at the same time as observation of soil moisture content. Plant turgidity is affected by soil moisture condition up to a certain depth which looks to be typical of the agroclimates. At Andungsari experimental station (high land it is necessary to assess soil moisture through the soil profile up to 100 cm deep in order to evaluate water stress of the plants; inversely, at Kaliwining experimental station in order to evaluate water stress of the plants it is just justified from the soil moisture condition of the soil surface layers (0-25 cm. Whereas at Sumberasin experimental station water stress of the plants could be predicted from soil moisture assessment of the surface layer depth or through the deeper layers of the soil profile either. Andungsari-1 and Lini S-795 clones are more resistant to drought than Kartika-2 clone at Andisol soil type with C rainfall type and elevation > 1000 m asl. BP-308 clone showed its response as relatively resistant to drought at yellowish red Mediterranean soil type with C

  10. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Science.gov (United States)

    Orth, R.; Seneviratne, S. I.

    2013-10-01

    As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence) characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation) and evapotranspiration (normalised by radiation) on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  11. Propagation of soil moisture memory to streamflow and evapotranspiration in Europe

    Directory of Open Access Journals (Sweden)

    R. Orth

    2013-10-01

    Full Text Available As a key variable of the land-climate system soil moisture is a main driver of streamflow and evapotranspiration under certain conditions. Soil moisture furthermore exhibits outstanding memory (persistence characteristics. Many studies also report distinct low frequency variations for streamflow, which are likely related to soil moisture memory. Using data from over 100 near-natural catchments located across Europe, we investigate in this study the connection between soil moisture memory and the respective memory of streamflow and evapotranspiration on different time scales. For this purpose we use a simple water balance model in which dependencies of runoff (normalised by precipitation and evapotranspiration (normalised by radiation on soil moisture are fitted using streamflow observations. The model therefore allows us to compute the memory characteristics of soil moisture, streamflow and evapotranspiration on the catchment scale. We find considerable memory in soil moisture and streamflow in many parts of the continent, and evapotranspiration also displays some memory at monthly time scale in some catchments. We show that the memory of streamflow and evapotranspiration jointly depend on soil moisture memory and on the strength of the coupling of streamflow and evapotranspiration to soil moisture. Furthermore, we find that the coupling strengths of streamflow and evapotranspiration to soil moisture depend on the shape of the fitted dependencies and on the variance of the meteorological forcing. To better interpret the magnitude of the respective memories across Europe, we finally provide a new perspective on hydrological memory by relating it to the mean duration required to recover from anomalies exceeding a certain threshold.

  12. Galvanic Cell Type Sensor for Soil Moisture Analysis.

    Science.gov (United States)

    Gaikwad, Pramod; Devendrachari, Mruthyunjayachari Chattanahalli; Thimmappa, Ravikumar; Paswan, Bhuneshwar; Raja Kottaichamy, Alagar; Makri Nimbegondi Kotresh, Harish; Thotiyl, Musthafa Ottakam

    2015-07-21

    Here we report the first potentiometric sensor for soil moisture analysis by bringing in the concept of Galvanic cells wherein the redox energies of Al and conducting polyaniline are exploited to design a battery type sensor. The sensor consists of only simple architectural components, and as such they are inexpensive and lightweight, making it suitable for on-site analysis. The sensing mechanism is proved to be identical to a battery type discharge reaction wherein polyaniline redox energy changes from the conducting to the nonconducting state with a resulting voltage shift in the presence of soil moisture. Unlike the state of the art soil moisture sensors, a signal derived from the proposed moisture sensor is probe size independent, as it is potentiometric in nature and, hence, can be fabricated in any shape or size and can provide a consistent output signal under the strong aberration conditions often encountered in soil moisture analysis. The sensor is regenerable by treating with 1 M HCl and can be used for multiple analysis with little read out hysteresis. Further, a portable sensor is fabricated which can provide warning signals to the end user when the moisture levels in the soil go below critically low levels, thereby functioning as a smart device. As the sensor is inexpensive, portable, and potentiometric, it opens up avenues for developing effective and energy efficient irrigation strategies, understanding the heat and water transfer at the atmosphere-land interface, understanding soil mechanics, forecasting the risk of natural calamities, and so on.

  13. Time series modeling of soil moisture dynamics on a steep mountainous hillside

    Science.gov (United States)

    Kim, Sanghyun

    2016-05-01

    The response of soil moisture to rainfall events along hillslope transects is an important hydrologic process and a critical component of interactions between soil vegetation and the atmosphere. In this context, the research described in this article addresses the spatial distribution of soil moisture as a function of topography. In order to characterize the temporal variation in soil moisture on a steep mountainous hillside, a transfer function, including a model for noise, was introduced. Soil moisture time series with similar rainfall amounts, but different wetness gradients were measured in the spring and fall. Water flux near the soil moisture sensors was modeled and mathematical expressions were developed to provide a basis for input-output modeling of rainfall and soil moisture using hydrological processes such as infiltration, exfiltration and downslope lateral flow. The characteristics of soil moisture response can be expressed in terms of model structure. A seasonal comparison of models reveals differences in soil moisture response to rainfall, possibly associated with eco-hydrological process and evapotranspiration. Modeling results along the hillslope indicate that the spatial structure of the soil moisture response patterns mainly appears in deeper layers. Similarities between topographic attributes and stochastic model structures are spatially organized. The impact of temporal and spatial discretization scales on parameter expression is addressed in the context of modeling results that link rainfall events and soil moisture.

  14. Improving Simulated Soil Moisture Fields Through Assimilation of AMSR-E Soil Moisture Retrievals with an Ensemble Kalman Filter and a Mass Conservation Constraint

    Science.gov (United States)

    Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian

    2011-01-01

    Model simulated soil moisture fields are often biased due to errors in input parameters and deficiencies in model physics. Satellite derived soil moisture estimates, if retrieved appropriately, represent the spatial mean of soil moisture in a footprint area, and can be used to reduce model bias (at locations near the surface) through data assimilation techniques. While assimilating the retrievals can reduce model bias, it can also destroy the mass balance enforced by the model governing equation because water is removed from or added to the soil by the assimilation algorithm. In addition, studies have shown that assimilation of surface observations can adversely impact soil moisture estimates in the lower soil layers due to imperfect model physics, even though the bias near the surface is decreased. In this study, an ensemble Kalman filter (EnKF) with a mass conservation updating scheme was developed to assimilate the actual value of Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture retrievals to improve the mean of simulated soil moisture fields by the Noah land surface model. Assimilation results using the conventional and the mass conservation updating scheme in the Little Washita watershed of Oklahoma showed that, while both updating schemes reduced the bias in the shallow root zone, the mass conservation scheme provided better estimates in the deeper profile. The mass conservation scheme also yielded physically consistent estimates of fluxes and maintained the water budget. Impacts of model physics on the assimilation results are discussed.

  15. Use of soil moisture sensors for irrigation scheduling

    Science.gov (United States)

    Various types of soil moisture sensing devices have been developed and are commercially available for water management applications. Each type of soil moisture sensors has its advantages and shortcomings in terms of accuracy, reliability, and cost. Resistive and capacitive based sensors, and time-d...

  16. New era of satellite chlorophyll fluorescence and soil moisture observations leads to advances in the predictive understanding of global terrestrial coupled carbon-water cycles

    Science.gov (United States)

    Qiu, B.; Xue, Y.; Fisher, J.; Guo, W.

    2017-12-01

    The terrestrial carbon cycle and water cycle are coupled through a multitude of connected processes among soil, roots, leaves, and the atmosphere. The strength and sensitivity of these couplings are not yet well known at the global scale, which contributes to uncertainty in predicting the terrestrial water and carbon budgets. For the first time, we now have synchronous, high fidelity, global-scale satellite observations of critical terrestrial carbon and water cycle components: sun-induced chlorophyll fluorescence (SIF) and soil moisture. We used these observations within the framework of a well-established global terrestrial biosphere model (Simplified Simple Biosphere Model version 2.0, SSiB2) to investigate carbon-water coupling processes. We updated SSiB2 to include a mechanistic representation of SIF and tested the sensitivity of model parameters to improve the simulation of both SIF and soil moisture with the ultimate objective of improving the first-order terrestrial carbon component, gross primary production (GPP). Although several vegetation parameters, such as leaf area index (LAI) and green leaf fraction, improved the simulated SIF, and several soil parameters, such as hydraulic conductivity, improved simulated soil moisture, their effects were mainly limited to their respective cycles. One parameter emerged as the key coupler between the carbon and water cycles: the wilting point. Updates to the wilting point significantly improved the simulations for both soil moisture and SIF, as well as GPP. This study demonstrates the value of synchronous global measurements of the terrestrial carbon and water cycles in improving the understanding of coupled carbon-water cycles.

  17. Evaporational losses under different soil moisture regimes and atmospheric evaporativities using tritium

    International Nuclear Information System (INIS)

    Saxena, P.; Chaudhary, T.N.; Mookerji, P.

    1991-01-01

    Tritium as tracer was used in a laboratory study to estimate the contribution of moisture from different soil depths towards actual soil water evaporation. Results indicated that for comparable amounts of free water evaporation (5 cm), contribution of moisture from 70-80 cm soil layer towards total soil moisture loss through evaporation increased nearly 1.5 to 3 folds for soils with water table at 90 cm than without water table. Identical initial soil moistures were exposed to different atmospheric evaporativities. Similarly, for a given initial soil moisture status, upward movement of moisture from 70-80 cm soil layer under low evaporativity was nearly 8 to 12 times that of under high evaporativity at 5 cm free water evaporation value. (author). 6 refs., 4 tabs., 2 figs

  18. Evapotranspiration Estimates for a Stochastic Soil-Moisture Model

    Science.gov (United States)

    Chaleeraktrakoon, Chavalit; Somsakun, Somrit

    2009-03-01

    Potential evapotranspiration is information that is necessary for applying a widely used stochastic model of soil moisture (I. Rodriguez Iturbe, A. Porporato, L. Ridolfi, V. Isham and D. R. Cox, Probabilistic modelling of water balance at a point: The role of climate, soil and vegetation, Proc. Roy. Soc. London A455 (1999) 3789-3805). An objective of the present paper is thus to find a proper estimate of the evapotranspiration for the stochastic model. This estimate is obtained by comparing the calculated soil-moisture distribution resulting from various techniques, such as Thornthwaite, Makkink, Jensen-Haise, FAO Modified Penman, and Blaney-Criddle, with an observed one. The comparison results using five sequences of daily soil-moisture for a dry season from November 2003 to April 2004 (Udornthani Province, Thailand) have indicated that all methods can be used if the weather information required is available. This is because their soil-moisture distributions are alike. In addition, the model is shown to have its ability in approximately describing the phenomenon at a weekly or biweekly time scale which is desirable for agricultural engineering applications.

  19. Physically plausible prescription of land surface model soil moisture

    Science.gov (United States)

    Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia

    2016-04-01

    Land surface hydrology is an important control of surface weather and climate, especially under extreme dry or wet conditions where it can amplify heat waves or floods, respectively. Prescribing soil moisture in land surface models is a valuable technique to investigate this link between hydrology and climate. It has been used for example to assess the influence of soil moisture on temperature variability, mean and extremes (Seneviratne et al. 2006, 2013, Lorenz et al., 2015). However, perturbing the soil moisture content artificially can lead to a violation of the energy and water balances. Here we present a new method for prescribing soil moisture which ensures water and energy balance closure by using only water from runoff and a reservoir term. If water is available, the method prevents soil moisture decrease below climatological values. Results from simulations with the Community Land Model (CLM) indicate that our new method allows to avoid soil moisture deficits in many regions of the world. We show the influence of the irrigation-supported soil moisture content on mean and extreme temperatures and contrast our findings with that of earlier studies. Additionally, we will assess how long into the 21st century the new method will be able to maintain present-day climatological soil moisture levels for different regions. Lorenz, R., Argüeso, D., Donat, M.G., Pitman, A.J., den Hurk, B.V., Berg, A., Lawrence, D.M., Chéruy, F., Ducharne, A., Hagemann, S. and Meier, A., 2015. Influence of land-atmosphere feedbacks on temperature and precipitation extremes in the GLACE-CMIP5 ensemble. Journal of Geophysical Research: Atmospheres. Seneviratne, S.I., Lüthi, D., Litschi, M. and Schär, C., 2006. Land-atmosphere coupling and climate change in Europe. Nature, 443(7108), pp.205-209. Seneviratne, S.I., Wilhelm, M., Stanelle, T., Hurk, B., Hagemann, S., Berg, A., Cheruy, F., Higgins, M.E., Meier, A., Brovkin, V. and Claussen, M., 2013. Impact of soil moisture

  20. Complex terrain alters temperature and moisture limitations of forest soil respiration across a semiarid to subalpine gradient

    Science.gov (United States)

    Berryman, Erin Michele; Barnard, H.R.; Adams, H.R.; Burns, M.A.; Gallo, E.; Brooks, P.D.

    2015-01-01

    Forest soil respiration is a major carbon (C) flux that is characterized by significant variability in space and time. We quantified growing season soil respiration during both a drought year and a nondrought year across a complex landscape to identify how landscape and climate interact to control soil respiration. We asked the following questions: (1) How does soil respiration vary across the catchments due to terrain-induced variability in moisture availability and temperature? (2) Does the relative importance of moisture versus temperature limitation of respiration vary across space and time? And (3) what terrain elements are important for dictating the pattern of soil respiration and its controls? Moisture superseded temperature in explaining watershed respiration patterns, with wetter yet cooler areas higher up and on north facing slopes yielding greater soil respiration than lower and south facing areas. Wetter subalpine forests had reduced moisture limitation in favor of greater seasonal temperature limitation, and the reverse was true for low-elevation semiarid forests. Coincident climate poorly predicted soil respiration in the montane transition zone; however, antecedent precipitation from the prior 10 days provided additional explanatory power. A seasonal trend in respiration remained after accounting for microclimate effects, suggesting that local climate alone may not adequately predict seasonal variability in soil respiration in montane forests. Soil respiration climate controls were more strongly related to topography during the drought year highlighting the importance of landscape complexity in ecosystem response to drought.

  1. McMaster Mesonet soil moisture dataset: description and spatio-temporal variability analysis

    Directory of Open Access Journals (Sweden)

    K. C. Kornelsen

    2013-04-01

    Full Text Available This paper introduces and describes the hourly, high-resolution soil moisture dataset continuously recorded by the McMaster Mesonet located in the Hamilton-Halton Watershed in Southern Ontario, Canada. The McMaster Mesonet consists of a network of time domain reflectometer (TDR probes collecting hourly soil moisture data at six depths between 10 cm and 100 cm at nine locations per site, spread across four sites in the 1250 km2 watershed. The sites for the soil moisture arrays are designed to further improve understanding of soil moisture dynamics in a seasonal climate and to capture soil moisture transitions in areas that have different topography, soil and land cover. The McMaster Mesonet soil moisture constitutes a unique database in Canada because of its high spatio-temporal resolution. In order to provide some insight into the dominant processes at the McMaster Mesonet sites, a spatio-temporal and temporal stability analysis were conducted to identify spatio-temporal patterns in the data and to suggest some physical interpretation of soil moisture variability. It was found that the seasonal climate of the Great Lakes Basin causes a transition in soil moisture patterns at seasonal timescales. During winter and early spring months, and at the meadow sites, soil moisture distribution is governed by topographic redistribution, whereas following efflorescence in the spring and summer, soil moisture spatial distribution at the forested site was also controlled by vegetation canopy. Analysis of short-term temporal stability revealed that the relative difference between sites was maintained unless there was significant rainfall (> 20 mm or wet conditions a priori. Following a disturbance in the spatial soil moisture distribution due to wetting, the relative soil moisture pattern re-emerged in 18 to 24 h. Access to the McMaster Mesonet data can be provided by visiting www.hydrology.mcmaster.ca/mesonet.

  2. Benchmarking NLDAS-2 Soil Moisture and Evapotranspiration to Separate Uncertainty Contributions

    Science.gov (United States)

    Nearing, Grey S.; Mocko, David M.; Peters-Lidard, Christa D.; Kumar, Sujay V.; Xia, Youlong

    2016-01-01

    Model benchmarking allows us to separate uncertainty in model predictions caused 1 by model inputs from uncertainty due to model structural error. We extend this method with a large-sample approach (using data from multiple field sites) to measure prediction uncertainty caused by errors in (i) forcing data, (ii) model parameters, and (iii) model structure, and use it to compare the efficiency of soil moisture state and evapotranspiration flux predictions made by the four land surface models in the North American Land Data Assimilation System Phase 2 (NLDAS-2). Parameters dominated uncertainty in soil moisture estimates and forcing data dominated uncertainty in evapotranspiration estimates; however, the models themselves used only a fraction of the information available to them. This means that there is significant potential to improve all three components of the NLDAS-2 system. In particular, continued work toward refining the parameter maps and look-up tables, the forcing data measurement and processing, and also the land surface models themselves, has potential to result in improved estimates of surface mass and energy balances.

  3. Antecedent moisture content and soil texture effects on infiltration and erosion

    Science.gov (United States)

    Mamedov, A. I.; Huang, C.; Levy, G. J.

    2006-12-01

    erosion modeling. In order to improve the prediction capabilities of erosion models, temporal and spatial variation of soil moisture content (AMC, wetting and aging) prior to erosive rainstorms should be considered and or incorporated. In addition, management practices could be adapted to diminish the severe soil moisture variation, where ever possible, (minimum till or no-till with known residue) to maintain the soil surface at a desired AMC level prior to expected rainstorms in order to decrease soil susceptibility to seal formation, runoff and soil loss.

  4. Verification of High Resolution Soil Moisture and Latent Heat in Germany

    Science.gov (United States)

    Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.

    2012-12-01

    Improving our understanding of soil-land-surface-atmosphere feedbacks is fundamental to make reliable predictions of water and energy fluxes on land systems influenced by anthropogenic activities. Estimating, for instance, which would be the likely consequences of changing climatic regimes on water availability and crop yield, requires of high resolution soil moisture. Modeling it at large-scales, however, is difficult and uncertain because of the interplay between state variables and fluxes and the significant parameter uncertainty of the predicting models. At larger scales, the sub-grid variability of the variables involved and the nonlinearity of the processes complicate the modeling exercise even further because parametrization schemes might be scale dependent. Two contrasting modeling paradigms (WRF/Noah-MP and mHM) were employed to quantify the effects of model and data complexity on soil moisture and latent heat over Germany. WRF/Noah-MP was forced ERA-interim on the boundaries of the rotated CORDEX-Grid (www.meteo.unican.es/wiki/cordexwrf) with a spatial resolution of 0.11o covering Europe during the period from 1989 to 2009. Land cover and soil texture were represented in WRF/Noah-MP with 1×1~km MODIS images and a single horizon, coarse resolution European-wide soil map with 16 soil texture classes, respectively. To ease comparison, the process-based hydrological model mHM was forced with daily precipitation and temperature fields generated by WRF during the same period. The spatial resolution of mHM was fixed at 4×4~km. The multiscale parameter regionalization technique (MPR, Samaniego et al. 2010) was embedded in mHM to be able to estimate effective model parameters using hyper-resolution input data (100×100~km) obtained from Corine land cover and detailed soil texture fields for various horizons comprising 72 soil texture classes for Germany, among other physiographical variables. mHM global parameters, in contrast with those of Noah-MP, were

  5. Combined Radar-Radiometer Surface Soil Moisture and Roughness Estimation

    Science.gov (United States)

    Akbar, Ruzbeh; Cosh, Michael H.; O'Neill, Peggy E.; Entekhabi, Dara; Moghaddam, Mahta

    2017-01-01

    A robust physics-based combined radar-radiometer, or Active-Passive, surface soil moisture and roughness estimation methodology is presented. Soil moisture and roughness retrieval is performed via optimization, i.e., minimization, of a joint objective function which constrains similar resolution radar and radiometer observations simultaneously. A data-driven and noise-dependent regularization term has also been developed to automatically regularize and balance corresponding radar and radiometer contributions to achieve optimal soil moisture retrievals. It is shown that in order to compensate for measurement and observation noise, as well as forward model inaccuracies, in combined radar-radiometer estimation surface roughness can be considered a free parameter. Extensive Monte-Carlo numerical simulations and assessment using field data have been performed to both evaluate the algorithms performance and to demonstrate soil moisture estimation. Unbiased root mean squared errors (RMSE) range from 0.18 to 0.03 cm3cm3 for two different land cover types of corn and soybean. In summary, in the context of soil moisture retrieval, the importance of consistent forward emission and scattering development is discussed and presented.

  6. Improving agricultural drought monitoring in West Africa using root zone soil moisture estimates derived from NDVI

    Science.gov (United States)

    McNally, A.; Funk, C. C.; Yatheendradas, S.; Michaelsen, J.; Cappelarere, B.; Peters-Lidard, C. D.; Verdin, J. P.

    2012-12-01

    The Famine Early Warning Systems Network (FEWS NET) relies heavily on remotely sensed rainfall and vegetation data to monitor agricultural drought in Sub-Saharan Africa and other places around the world. Analysts use satellite rainfall to calculate rainy season statistics and force crop water accounting models that show how the magnitude and timing of rainfall might lead to above or below average harvest. The Normalized Difference Vegetation Index (NDVI) is also an important indicator of growing season progress and is given more weight over regions where, for example, lack of rain gauges increases error in satellite rainfall estimates. Currently, however, near-real time NDVI is not integrated into a modeling framework that informs growing season predictions. To meet this need for our drought monitoring system a land surface model (LSM) is a critical component. We are currently enhancing the FEWS NET monitoring activities by configuring a custom instance of NASA's Land Information System (LIS) called the FEWS NET Land Data Assimilation System. Using the LIS Noah LSM, in-situ measurements, and remotely sensed data, we focus on the following questions: What is the relationship between NDVI and in-situ soil moisture measurements over the West Africa Sahel? How can we use this relationship to improve modeled water and energy fluxes over the West Africa Sahel? We investigate soil moisture and NDVI cross-correlation in the time and frequency domain to develop a transfer function model to predict soil moisture from NDVI. This work compares sites in southwest Niger, Benin, Burkina Faso, and Mali to test the generality of the transfer function. For several sites with fallow and millet vegetation in the Wankama catchment in southwest Niger we developed a non-parametric frequency response model, using NDVI inputs and soil moisture outputs, that accurately estimates root zone soil moisture (40-70cm). We extend this analysis by developing a low order parametric transfer function

  7. SMOS/SMAP Synergy for SMAP Level 2 Soil Moisture Algorithm Evaluation

    Science.gov (United States)

    Bindlish, Rajat; Jackson, Thomas J.; Zhao, Tianjie; Cosh, Michael; Chan, Steven; O'Neill, Peggy; Njoku, Eni; Colliander, Andreas; Kerr, Yann

    2011-01-01

    Soil Moisture Active Passive (SMAP) satellite has been proposed to provide global measurements of soil moisture and land freeze/thaw state at 10 km and 3 km resolutions, respectively. SMAP would also provide a radiometer-only soil moisture product at 40-km spatial resolution. This product and the supporting brightness temperature observations are common to both SMAP and European Space Agency's Soil Moisture and Ocean Salinity (SMOS) mission. As a result, there are opportunities for synergies between the two missions. These include exploiting the data for calibration and validation and establishing longer term L-band brightness temperature and derived soil moisture products. In this investigation we will be using SMOS brightness temperature, ancillary data, and soil moisture products to develop and evaluate a candidate SMAP L2 passive soil moisture retrieval algorithm. This work will begin with evaluations based on the SMOS product grids and ancillary data sets and transition to those that will be used by SMAP. An important step in this analysis is reprocessing the multiple incidence angle observations provided by SMOS to a global brightness temperature product that simulates the constant 40 degree incidence angle observations that SMAP will provide. The reprocessed brightness temperature data provide a basis for evaluating different SMAP algorithm alternatives. Several algorithms are being considered for the SMAP radiometer-only soil moisture retrieval. In this first phase, we utilized only the Single Channel Algorithm (SCA), which is based on the radiative transfer equation and uses the channel that is most sensitive to soil moisture (H-pol). Brightness temperature is corrected sequentially for the effects of temperature, vegetation, roughness (dynamic ancillary data sets) and soil texture (static ancillary data set). European Centre for Medium-Range Weather Forecasts (ECMWF) estimates of soil temperature for the top layer (as provided as part of the SMOS

  8. Effects of natural and synthetic soil conditioners on soil moisture ...

    African Journals Online (AJOL)

    The efficacy of a natural soil conditioner, Coco-Peat (C-P), and synthetic soil conditioners, Terawet (T-200) and Teraflow (T-F), in improving soil moisture content were examined on five Ghanaian soil series (Akroso, Akuse, Amo, Hake and Oyarifa). In general, the water retention of T-200 and C-P treated soils were similar ...

  9. Radar for Measuring Soil Moisture Under Vegetation

    Science.gov (United States)

    Moghaddam, Mahta; Moller, Delwyn; Rodriguez, Ernesto; Rahmat-Samii, Yahya

    2004-01-01

    A two-frequency, polarimetric, spaceborne synthetic-aperture radar (SAR) system has been proposed for measuring the moisture content of soil as a function of depth, even in the presence of overlying vegetation. These measurements are needed because data on soil moisture under vegetation canopies are not available now and are necessary for completing mathematical models of global energy and water balance with major implications for global variations in weather and climate.

  10. Multi-Scale Soil Moisture Monitoring and Modeling at ARS Watersheds for NASA's Soil Moisture Active Passive (SMAP) Calibration/Validation Mission

    Science.gov (United States)

    Coopersmith, E. J.; Cosh, M. H.

    2014-12-01

    NASA's SMAP satellite, launched in November of 2014, produces estimates of average volumetric soil moisture at 3, 9, and 36-kilometer scales. The calibration and validation process of these estimates requires the generation of an identically-scaled soil moisture product from existing in-situ networks. This can be achieved via the integration of NLDAS precipitation data to perform calibration of models at each ­in-situ gauge. In turn, these models and the gauges' volumetric estimations are used to generate soil moisture estimates at a 500m scale throughout a given test watershed by leveraging, at each location, the gauge-calibrated models deemed most appropriate in terms of proximity, calibration efficacy, soil-textural similarity, and topography. Four ARS watersheds, located in Iowa, Oklahoma, Georgia, and Arizona are employed to demonstrate the utility of this approach. The South Fork watershed in Iowa represents the simplest case - the soil textures and topography are relative constants and the variability of soil moisture is simply tied to the spatial variability of precipitation. The Little Washita watershed in Oklahoma adds soil textural variability (but remains topographically simple), while the Little River watershed in Georgia incorporates topographic classification. Finally, the Walnut Gulch watershed in Arizona adds a dense precipitation network to be employed for even finer-scale modeling estimates. Results suggest RMSE values at or below the 4% volumetric standard adopted for the SMAP mission are attainable over the desired spatial scales via this integration of modeling efforts and existing in-situ networks.

  11. Fiber Optic Thermo-Hygrometers for Soil Moisture Monitoring.

    Science.gov (United States)

    Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea

    2017-06-20

    This work deals with the fabrication, prototyping, and experimental validation of a fiber optic thermo-hygrometer-based soil moisture sensor, useful for rainfall-induced landslide prevention applications. In particular, we recently proposed a new generation of fiber Bragg grating (FBGs)-based soil moisture sensors for irrigation purposes. This device was realized by integrating, inside a customized aluminum protection package, a FBG thermo-hygrometer with a polymer micro-porous membrane. Here, we first verify the limitations, in terms of the volumetric water content (VWC) measuring range, of this first version of the soil moisture sensor for its exploitation in landslide prevention applications. Successively, we present the development, prototyping, and experimental validation of a novel, optimized version of a soil VWC sensor, still based on a FBG thermo-hygrometer, but able to reliably monitor, continuously and in real-time, VWC values up to 37% when buried in the soil.

  12. Creating soil moisture maps based on radar satellite imagery

    Science.gov (United States)

    Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr

    2017-10-01

    The presented work is related to a study of mapping soil moisture basing on radar data from Sentinel-1 and a test of adequacy of the models constructed on the basis of data obtained from alternative sources. Radar signals are reflected from the ground differently, depending on its properties. In radar images obtained, for example, in the C band of the electromagnetic spectrum, soils saturated with moisture usually appear in dark tones. Although, at first glance, the problem of constructing moisture maps basing on radar data seems intuitively clear, its implementation on the basis of the Sentinel-1 data on an industrial scale and in the public domain is not yet available. In the process of mapping, for verification of the results, measurements of soil moisture obtained from logs of the network of climate stations NOAA US Climate Reference Network (USCRN) were used. This network covers almost the entire territory of the United States. The passive microwave radiometers of Aqua and SMAP satellites data are used for comparing processing. In addition, other supplementary cartographic materials were used, such as maps of soil types and ready moisture maps. The paper presents a comparison of the effect of the use of certain methods of roughening the quality of radar data on the result of mapping moisture. Regression models were constructed showing dependence of backscatter coefficient values Sigma0 for calibrated radar data of different spatial resolution obtained at different times on soil moisture values. The obtained soil moisture maps of the territories of research, as well as the conceptual solutions about automation of operations of constructing such digital maps, are presented. The comparative assessment of the time required for processing a given set of radar scenes with the developed tools and with the ESA SNAP product was carried out.

  13. Soil Moisture Anomaly as Predictor of Crop Yield Deviation in Germany

    Science.gov (United States)

    Peichl, Michael; Thober, Stephan; Schwarze, Reimund; Meyer, Volker; Samaniego, Luis

    2016-04-01

    Natural hazards, such as droughts, have the potential to drastically diminish crop yield in rain-fed agriculture. For example, the drought in 2003 caused direct losses of 1.5 billion EUR only in Germany (COPA-COGECA 2003). Predicting crop yields allows to economize the mitigation of risks of weather extremes. Economic approaches for quantifying agricultural impacts of natural hazards mainly rely on temperature and related concepts. For instance extreme heat over the growing season is considered as best predictor of corn yield (Auffhammer and Schlenker 2014). However, those measures are only able to provide a proxy for the available water content in the root zone that ultimately determines plant growth and eventually crop yield. The aim of this paper is to analyse whether soil moisture has a causal effect on crop yield that can be exploited in improving adaptation measures. For this purpose, reduced form fixed effect panel models are developed with yield as dependent variable for both winter wheat and silo maize crops. The explanatory variables used are soil moisture anomalies, precipitation and temperature. The latter two are included to estimate the current state of the water balance. On the contrary, soil moisture provides an integrated signal over several months. It is also the primary source of water supply for plant growth. For each crop a single model is estimated for every month within the growing period to study the variation of the effects over time. Yield data is available for Germany as a whole on the level of administrative districts from 1990 to 2010. Station data by the German Weather Service are obtained for precipitation and temperature and are aggregated to the same spatial units. Simulated soil moisture computed by the mesoscale Hydrologic Model (mHM, www.ufz.de/mhm) is transformed into Soil Moisture Index (SMI), which represents the monthly soil water quantile and hence accounts directly for the water content available to plants. The results

  14. Estimating Regional Scale Hydroclimatic Risk Conditions from the Soil Moisture Active-Passive (SMAP Satellite

    Directory of Open Access Journals (Sweden)

    Catherine Champagne

    2018-04-01

    Full Text Available Satellite soil moisture is a critical variable for identifying susceptibility to hydroclimatic risks such as drought, dryness, and excess moisture. Satellite soil moisture data from the Soil Moisture Active/Passive (SMAP mission was used to evaluate the sensitivity to hydroclimatic risk events in Canada. The SMAP soil moisture data sets in general capture relative moisture trends with the best estimates from the passive-only derived soil moisture and little difference between the data at different spatial resolutions. In general, SMAP data sets overestimated the magnitude of moisture at the wet extremes of wetting events. A soil moisture difference from average (SMDA was calculated from SMAP and historical Soil Moisture and Ocean Salinity (SMOS data showed a relatively good delineation of hydroclimatic risk events, although caution must be taken due to the large variability in the data within risk categories. Satellite soil moisture data sets are more sensitive to short term water shortages than longer term water deficits. This was not improved by adding “memory” to satellite soil moisture indices to improve the sensitivity of the data to drought, and there is a large variability in satellite soil moisture values with the same drought severity rating.

  15. Soil moisture remote sensing: State of the science

    Science.gov (United States)

    Satellites (e.g., SMAP, SMOS) using passive microwave techniques, in particular at L band frequency, have shown good promise for global mapping of near-surface (0-5 cm) soil moisture at a spatial resolution of 25-40 km and temporal resolution of 2-3 days. C- and X-band soil moisture records date bac...

  16. Estimating soil moisture using the Danish polarimetric SAR

    DEFF Research Database (Denmark)

    Jiankang, Ji; Thomsen, A.; Skriver, Henning

    1995-01-01

    The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness a...... of surface parameters with the bilinear model, the correlation coefficient between the estimated and measured soil moisture, as well as rms height, is about 0.77. To improve the result, the local incidence angles need to be taken into account......The results of applying data from the Danish polarimetric SAR (EMISAR) to estimate soil moisture for bare fields are presented. Fully calibrated C-band SAR images for hh, vv and cross polarizations have been used in this study. The measured surface roughness data showed that classical roughness...... autocorrelation functions (Gaussian and Exponential) were not able to fit natural surfaces well. A Gauss-Exp hybrid model which agreed better with the measured data has been proposed. Theoretical surface scattering models (POM, IEM), as well as an empirical model for retrieval of soil moisture and surface rms...

  17. A Physically-based Model for Predicting Soil Moisture Dynamics in Wetlands

    Science.gov (United States)

    Kalin, L.; Rezaeianzadeh, M.; Hantush, M. M.

    2017-12-01

    Wetlands are promoted as green infrastructures because of their characteristics in retaining and filtering water. In wetlands going through wetting/drying cycles, simulation of nutrient processes and biogeochemical reactions in both ponded and unsaturated wetland zones are needed for an improved understanding of wetland functioning for water quality improvement. The physically-based WetQual model can simulate the hydrology and nutrient and sediment cycles in natural and constructed wetlands. WetQual can be used in continuously flooded environments or in wetlands going through wetting/drying cycles. Currently, WetQual relies on 1-D Richards' Equation (RE) to simulate soil moisture dynamics in unponded parts of the wetlands. This is unnecessarily complex because as a lumped model, WetQual only requires average moisture contents. In this paper, we present a depth-averaged solution to the 1-D RE, called DARE, to simulate the average moisture content of the root zone and the layer below it in unsaturated parts of wetlands. DARE converts the PDE of the RE into ODEs; thus it is computationally more efficient. This method takes into account the plant uptake and groundwater table fluctuations, which are commonly overlooked in hydrologic models dealing with wetlands undergoing wetting and drying cycles. For verification purposes, DARE solutions were compared to Hydrus-1D model, which uses full RE, under gravity drainage only assumption and full-term equations. Model verifications were carried out under various top boundary conditions: no ponding at all, ponding at some point, and no rain. Through hypothetical scenarios and actual atmospheric data, the utility of DARE was demonstrated. Gravity drainage version of DARE worked well in comparison to Hydrus-1D, under all the assigned atmospheric boundary conditions of varying fluxes for all examined soil types (sandy loam, loam, sandy clay loam, and sand). The full-term version of DARE offers reasonable accuracy compared to the

  18. Use of a combined penetrometer-TDR moisture probe for soil compaction studies

    International Nuclear Information System (INIS)

    Pedro Vaz, C.M.

    2004-01-01

    Soil mechanical strength is an important soil parameter that affects root growth and water movement, and controls nutrient and contaminant transport below the rooting zone. The most common way to assess soil strength is by using a soil penetrometer, which characterizes the force needed to drive a cone of specific size into the soil. The measured penetration resistance (PR) depends on such soil properties as bulk density, water content and potential, texture, aggregation, cementation and mineralogy. Soil scientists have related changes in PR as caused by tillage, traffic or soil genetic pans to root growth, crop yields and soil physical properties. For example, correlation between PR and crop root growth and water and nutrient exploration have been obtained, and cone penetrometers have been used extensively in soil science studies to identify natural and induced compacted layers or to predict related soil properties. Many studies have been conducted to understand the influence of bulk density and water content on PR in the laboratory and, from which both empirical and theoretical relationships were obtained. From the many different models that have been introduced to test these relationships (polynomial, exponential, power and linear equations), it is suggested that either the power or exponential equations are the most adequate. Using dimensional analysis techniques, it was suggested a power exponential equation for prediction of the PR for a silt loam soil, but also suggested additional experimental work for its validation. However, many referenced studies lack accurate and representative data, because PR is a highly variable soil property, whereas it is usually determined from local small-scale measurements. Hence, difficulties in relating PR with other soil parameters can be attributed mostly to soil spatial variability, because available measurement techniques prevent determination of the different soil attributes at the same spatial location. To improve on the

  19. Quantifying soil moisture impacts on light use efficiency across biomes.

    Science.gov (United States)

    Stocker, Benjamin D; Zscheischler, Jakob; Keenan, Trevor F; Prentice, I Colin; Peñuelas, Josep; Seneviratne, Sonia I

    2018-06-01

    Terrestrial primary productivity and carbon cycle impacts of droughts are commonly quantified using vapour pressure deficit (VPD) data and remotely sensed greenness, without accounting for soil moisture. However, soil moisture limitation is known to strongly affect plant physiology. Here, we investigate light use efficiency, the ratio of gross primary productivity (GPP) to absorbed light. We derive its fractional reduction due to soil moisture (fLUE), separated from VPD and greenness changes, using artificial neural networks trained on eddy covariance data, multiple soil moisture datasets and remotely sensed greenness. This reveals substantial impacts of soil moisture alone that reduce GPP by up to 40% at sites located in sub-humid, semi-arid or arid regions. For sites in relatively moist climates, we find, paradoxically, a muted fLUE response to drying soil, but reduced fLUE under wet conditions. fLUE identifies substantial drought impacts that are not captured when relying solely on VPD and greenness changes and, when seasonally recurring, are missed by traditional, anomaly-based drought indices. Counter to common assumptions, fLUE reductions are largest in drought-deciduous vegetation, including grasslands. Our results highlight the necessity to account for soil moisture limitation in terrestrial primary productivity data products, especially for drought-related assessments. © 2018 The Authors. New Phytologist © 2018 New Phytologist Trust.

  20. Ecosystem-scale plant hydraulic strategies inferred from remotely-sensed soil moisture

    Science.gov (United States)

    Bassiouni, M.; Good, S. P.; Higgins, C. W.

    2017-12-01

    Characterizing plant hydraulic strategies at the ecosystem scale is important to improve estimates of evapotranspiration and to understand ecosystem productivity and resilience. However, quantifying plant hydraulic traits beyond the species level is a challenge. The probability density function of soil moisture observations provides key information about the soil moisture states at which evapotranspiration is reduced by water stress. Here, an inverse Bayesian approach is applied to a standard bucket model of soil column hydrology forced with stochastic precipitation inputs. Through this approach, we are able to determine the soil moisture thresholds at which stomata are open or closed that are most consistent with observed soil moisture probability density functions. This research utilizes remotely-sensed soil moisture data to explore global patterns of ecosystem-scale plant hydraulic strategies. Results are complementary to literature values of measured hydraulic traits of various species in different climates and previous estimates of ecosystem-scale plant isohydricity. The presented approach provides a novel relation between plant physiological behavior and soil-water dynamics.

  1. Assimilating satellite soil moisture into rainfall-runoff modelling: towards a systematic study

    Science.gov (United States)

    Massari, Christian; Tarpanelli, Angelica; Brocca, Luca; Moramarco, Tommaso

    2015-04-01

    Soil moisture is the main factor for the repartition of the mass and energy fluxes between the land surface and the atmosphere thus playing a fundamental role in the hydrological cycle. Indeed, soil moisture represents the initial condition of rainfall-runoff modelling that determines the flood response of a catchment. Different initial soil moisture conditions can discriminate between catastrophic and minor effects of a given rainfall event. Therefore, improving the estimation of initial soil moisture conditions will reduce uncertainties in early warning flood forecasting models addressing the mitigation of flood hazard. In recent years, satellite soil moisture products have become available with fine spatial-temporal resolution and a good accuracy. Therefore, a number of studies have been published in which the impact of the assimilation of satellite soil moisture data into rainfall-runoff modelling is investigated. Unfortunately, data assimilation involves a series of assumptions and choices that significantly affect the final result. Given a satellite soil moisture observation, a rainfall-runoff model and a data assimilation technique, an improvement or a deterioration of discharge predictions can be obtained depending on the choices made in the data assimilation procedure. Consequently, large discrepancies have been obtained in the studies published so far likely due to the differences in the implementation of the data assimilation technique. On this basis, a comprehensive and robust procedure for the assimilation of satellite soil moisture data into rainfall-runoff modelling is developed here and applied to six subcatchment of the Upper Tiber River Basin for which high-quality hydrometeorological hourly observations are available in the period 1989-2013. The satellite soil moisture product used in this study is obtained from the Advanced SCATterometer (ASCAT) onboard Metop-A satellite and it is available since 2007. The MISDc ("Modello Idrologico Semi

  2. Reconstructions of Soil Moisture for the Upper Colorado River Basin Using Tree-Ring Chronologies

    Science.gov (United States)

    Tootle, G.; Anderson, S.; Grissino-Mayer, H.

    2012-12-01

    Soil moisture is an important factor in the global hydrologic cycle, but existing reconstructions of historic soil moisture are limited. Tree-ring chronologies (TRCs) were used to reconstruct annual soil moisture in the Upper Colorado River Basin (UCRB). Gridded soil moisture data were spatially regionalized using principal components analysis and k-nearest neighbor techniques. Moisture sensitive tree-ring chronologies in and adjacent to the UCRB were correlated with regional soil moisture and tested for temporal stability. TRCs that were positively correlated and stable for the calibration period were retained. Stepwise linear regression was applied to identify the best predictor combinations for each soil moisture region. The regressions explained 42-78% of the variability in soil moisture data. We performed reconstructions for individual soil moisture grid cells to enhance understanding of the disparity in reconstructive skill across the regions. Reconstructions that used chronologies based on ponderosa pines (Pinus ponderosa) and pinyon pines (Pinus edulis) explained increased variance in the datasets. Reconstructed soil moisture was standardized and compared with standardized reconstructed streamflow and snow water equivalent from the same region. Soil moisture reconstructions were highly correlated with streamflow and snow water equivalent reconstructions, indicating reconstructions of soil moisture in the UCRB using TRCs successfully represent hydrologic trends, including the identification of periods of prolonged drought.

  3. Using high-resolution soil moisture modelling to assess the uncertainty of microwave remotely sensed soil moisture products at the correct spatial and temporal support

    Science.gov (United States)

    Wanders, N.; Karssenberg, D.; Bierkens, M. F. P.; Van Dam, J. C.; De Jong, S. M.

    2012-04-01

    Soil moisture is a key variable in the hydrological cycle and important in hydrological modelling. When assimilating soil moisture into flood forecasting models, the improvement of forecasting skills depends on the ability to accurately estimate the spatial and temporal patterns of soil moisture content throughout the river basin. Space-borne remote sensing may provide this information with a high temporal and spatial resolution and with a global coverage. Currently three microwave soil moisture products are available: AMSR-E, ASCAT and SMOS. The quality of these satellite-based products is often assessed by comparing them with in-situ observations of soil moisture. This comparison is however hampered by the difference in spatial and temporal support (i.e., resolution, scale), because the spatial resolution of microwave satellites is rather low compared to in-situ field measurements. Thus, the aim of this study is to derive a method to assess the uncertainty of microwave satellite soil moisture products at the correct spatial support. To overcome the difference in support size between in-situ soil moisture observations and remote sensed soil moisture, we used a stochastic, distributed unsaturated zone model (SWAP, van Dam (2000)) that is upscaled to the support of different satellite products. A detailed assessment of the SWAP model uncertainty is included to ensure that the uncertainty in satellite soil moisture is not overestimated due to an underestimation of the model uncertainty. We simulated unsaturated water flow up to a depth of 1.5m with a vertical resolution of 1 to 10 cm and on a horizontal grid of 1 km2 for the period Jan 2010 - Jun 2011. The SWAP model was first calibrated and validated on in-situ data of the REMEDHUS soil moisture network (Spain). Next, to evaluate the satellite products, the model was run for areas in the proximity of 79 meteorological stations in Spain, where model results were aggregated to the correct support of the satellite

  4. Assimilation of SMOS Retrieved Soil Moisture into the Land Information System

    Science.gov (United States)

    Blankenship, Clay; Case, Jonathan; Zavodsky, Bradley; Jedlovec, Gary

    2014-01-01

    Soil moisture retrievals from the Soil Moisture and Ocean Salinity (SMOS) instrument are assimilated into the Noah land surface model (LSM) within the NASA Land Information System (LIS). Before assimilation, SMOS retrievals are bias-corrected to match the model climatological distribution using a Cumulative Distribution Function (CDF) matching approach. Data assimilation is done via the Ensemble Kalman Filter. The goal is to improve the representation of soil moisture within the LSM, and ultimately to improve numerical weather forecasts through better land surface initialization. We present a case study showing a large area of irrigation in the lower Mississippi River Valley, in an area with extensive rice agriculture. High soil moisture value in this region are observed by SMOS, but not captured in the forcing data. After assimilation, the model fields reflect the observed geographic patterns of soil moisture. Plans for a modeling experiment and operational use of the data are given. This work helps prepare for the assimilation of Soil Moisture Active/Passive (SMAP) retrievals in the near future.

  5. A soil moisture and temperature network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, Niels; Jensen, K. H.

    2011-01-01

    The Soil Moisture and Ocean Salinity Mission (SMOS) acquires surface soil moisture data globally, and thus product validation for a range of climate and environmental conditions across continents is a crucial step. For this purpose, a soil moisture and temperature network of Decagon ECH2O 5TE...... SMOS pixel (44 × 44 km), which is representative of the land surface conditions of the catchment and with minimal impact from open water (2) arrangement of three network clusters along the precipitation gradient, and (3) distribution of the stations according to respective fractions of classes...... representing the prevailing environmental conditions. Overall, measured moisture and temperature patterns could be related to the respective land cover and soil conditions. Texture-dependency of the 0–5 cm soil moisture measurements was demonstrated. Regional differences in 0–5 cm soil moisture, temperature...

  6. Surface Soil Moisture Memory Estimated from Models and SMAP Observations

    Science.gov (United States)

    He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D.

    2017-12-01

    Soil moisture memory(SMM), which is loosely defined as the time taken by soil to forget an anomaly, has been proved to be important in land-atmosphere interaction. There are many metrics to calculate the SMM timescale, for example, the timescale based on the time-series autocorrelation, the timescale ignoring the soil moisture time series and the timescale which only considers soil moisture increment. Recently, a new timescale based on `Water Cycle Fraction' (Kaighin et al., 2017), in which the impact of precipitation on soil moisture memory is considered, has been put up but not been fully evaluated in global. In this study, we compared the surface SMM derived from SMAP observations with that from land surface model simulations (i.e., the SMAP Nature Run (NR) provided by the Goddard Earth Observing System, version 5) (Rolf et al., 2014). Three timescale metrics were used to quantify the surface SMM as: T0 based on the soil moisture time series autocorrelation, deT0 based on the detrending soil moisture time series autocorrelation, and tHalf based on the Water Cycle Fraction. The comparisons indicate that: (1) there are big gaps between the T0 derived from SMAP and that from NR (2) the gaps get small for deT0 case, in which the seasonality of surface soil moisture was removed with a moving average filter; (3) the tHalf estimated from SMAP is much closer to that from NR. The results demonstrate that surface SMM can vary dramatically among different metrics, while the memory derived from land surface model differs from the one from SMAP observation. tHalf, with considering the impact of precipitation, may be a good choice to quantify surface SMM and have high potential in studies related to land atmosphere interactions. References McColl. K.A., S.H. Alemohammad, R. Akbar, A.G. Konings, S. Yueh, D. Entekhabi. The Global Distribution and Dynamics of Surface Soil Moisture, Nature Geoscience, 2017 Reichle. R., L. Qing, D.L. Gabrielle, A. Joe. The "SMAP_Nature_v03" Data

  7. Design and Fabrication of a Soil Moisture Meter Using Thermal Conductivity Properties of Soil

    Directory of Open Access Journals (Sweden)

    Subir DAS

    2011-09-01

    Full Text Available Study of soil for agricultural purposes is one of the main focuses of research since the beginning of civilization as food related requirements is closely linked with the soil. The study of soil has generated an interest among the researchers for very similar other reasons including understanding of soil water dynamics, evolution of agricultural water stress and validation of soil moisture modeling. In this present work design of a soil moisture measurement meter using thermal conductivity properties of soil has been proposed and experimental results are reported.

  8. A meta-analysis of the response of soil moisture to experimental warming

    International Nuclear Information System (INIS)

    Xu, Wenfang; Yuan, Wenping; Dong, Wenjie; Xia, Jiangzhou; Liu, Dan; Chen, Yang

    2013-01-01

    Soil moisture is an important variable for regulating carbon, water and energy cycles of terrestrial ecosystems. However, numerous inconsistent conclusions have been reported regarding the responses of soil moisture to warming. In this study, we conducted a meta-analysis for examination of the response of soil moisture to experimental warming across global warming sites including several ecosystem types. The results showed that soil moisture decreased in response to warming treatments when compared with control treatments in most ecosystem types. The largest reduction of soil moisture was observed in forests, while intermediate reductions were observed in grassland and cropland, and they were both larger than the reductions observed in shrubland and tundra ecosystems. Increases (or no change) in soil moisture also occurred in some ecosystems. Taken together, these results showed a trend of soil drying in most ecosystems, which may have exerted profound impacts on a variety of terrestrial ecosystem processes as well as feedbacks to the climate system. (letter)

  9. Relating coccidioidomycosis (valley fever) incidence to soil moisture conditions.

    Science.gov (United States)

    Coopersmith, E J; Bell, J E; Benedict, K; Shriber, J; McCotter, O; Cosh, M H

    2017-04-17

    Coccidioidomycosis (also called Valley fever) is caused by a soilborne fungus, Coccidioides spp. , in arid regions of the southwestern United States. Though some who develop infections from this fungus remain asymptomatic, others develop respiratory disease as a consequence. Less commonly, severe illness and death can occur when the infection spreads to other regions of the body. Previous analyses have attempted to connect the incidence of coccidioidomycosis to broadly available climatic measurements, such as precipitation or temperature. However, with the limited availability of long-term, in situ soil moisture data sets, it has not been feasible to perform a direct analysis of the relationships between soil moisture levels and coccidioidomycosis incidence on a larger temporal and spatial scale. Utilizing in situ soil moisture gauges throughout the southwest from the U.S. Climate Reference Network and a model with which to extend those estimates, this work connects periods of higher and lower soil moisture in Arizona and California between 2002 and 2014 to the reported incidence of coccidioidomycosis. The results indicate that in both states, coccidioidomycosis incidence is related to soil moisture levels from previous summers and falls. Stated differently, a higher number of coccidioidomycosis cases are likely to be reported if previous bands of months have been atypically wet or dry, depending on the location.

  10. Continuous data assimilation for downscaling large-footprint soil moisture retrievals

    KAUST Repository

    Altaf, M. U.; Jana, Raghavendra Belur; Hoteit, Ibrahim; McCabe, Matthew

    2016-01-01

    Soil moisture is a crucial component of the hydrologic cycle, significantly influencing runoff, infiltration, recharge, evaporation and transpiration processes. Models characterizing these processes require soil moisture as an input, either directly

  11. Using Remotely Sensed Fluorescence and Soil Moisture to Better Understand the Seasonal Cycle of Tropical Grasslands

    Science.gov (United States)

    Smith, Dakota Carlysle

    Seasonal grasslands account for a large area of Earth's land cover. Annual and seasonal changes in these grasslands have profound impacts on Earth's carbon, energy, and water cycles. In tropical grasslands, growth is commonly water-limited and the landscape oscillates between highly productive and unproductive. As the monsoon begins, soils moisten providing dry grasses the water necessary to photosynthesize. However, along with the rain come clouds that obscure satellite products that are commonly used to study productivity in these areas. To navigate this issue, we used solar induced fluorescence (SIF) products from OCO-2 along with soil moisture products from the Soil Moisture Active Passive satellite (SMAP) to "see through" the clouds to monitor grassland productivity. To get a broader understanding of the vegetation dynamics, we used the Simple Biosphere Model (SiB4) to simulate the seasonal cycles of vegetation. In conjunction with SiB4, the remotely sensed SIF and soil moisture observations were utilized to paint a clearer picture of seasonal productivity in tropical grasslands. The remotely sensed data is not available for every place at one time or at every time for one place. Thus, the study was focused on a large area from 15° E to 35° W and from 8°S to 20°N in the African Sahel. Instead of studying productivity relative to time, we studied it relative to soil moisture. Through this investigation we found soil moisture thresholds for the emergence of grassland growth, near linear grassland growth, and maturity of grassland growth. We also found that SiB4 overestimates SIF by about a factor of two for nearly every value of soil moisture. On the whole, SiB4 does a surprisingly good job of predicting the response of seasonal growth in tropical grasslands to soil moisture. Future work will continue to integrate remotely sensed SIF & soil moisture with SiB4 to add to our growing knowledge of carbon, water, and energy cycling in tropical grasslands.

  12. Detecting Trends in Wetland Extent from MODIS Derived Soil Moisture Estimates

    Directory of Open Access Journals (Sweden)

    Thomas Gumbricht

    2018-04-01

    Full Text Available A soil wetness index for optical satellite images, the Transformed Wetness Index (TWI is defined and evaluated against ground sampled soil moisture. Conceptually, TWI is formulated as a non-linear normalized difference index from orthogonalized vectors representing soil and water conditions, with the vegetation signal removed. Compared to 745 ground sites with in situ measured soil moisture, TWI has a globally estimated Random Mean Square Error of 14.0 (v/v expressed as percentage, which reduces to 8.5 for unbiased data. The temporal variation in soil moisture is significantly captured at 4 out of 10 stations, but also fails for 2 to 3 out of 10 stations. TWI is biased by different soil mineral compositions, dense vegetation and shadows, with the latter two most likely also causing the failure of TWI to capture soil moisture dynamics. Compared to soil moisture products from microwave brightness temperature data, TWI performs slightly worse, but has the advantages of not requiring ancillary data, higher spatial resolution and a relatively simple application. TWI has been used for wetland and peatland mapping in previously published studies but is presented in detail in this article, and then applied for detecting changes in soil moisture for selected tropical regions between 2001 and 2016. Sites with significant changes are compared to a published map of global tropical wetlands and peatlands.

  13. [Simulation of cropland soil moisture based on an ensemble Kalman filter].

    Science.gov (United States)

    Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping

    2011-11-01

    By using an ensemble Kalman filter (EnKF) to assimilate the observed soil moisture data, the modified boreal ecosystem productivity simulator (BEPS) model was adopted to simulate the dynamics of soil moisture in winter wheat root zones at Xuzhou Agro-meteorological Station, Jiangsu Province of China during the growth seasons in 2000-2004. After the assimilation of observed data, the determination coefficient, root mean square error, and average absolute error of simulated soil moisture were in the ranges of 0.626-0.943, 0.018-0.042, and 0.021-0.041, respectively, with the simulation precision improved significantly, as compared with that before assimilation, indicating the applicability of data assimilation in improving the simulation of soil moisture. The experimental results at single point showed that the errors in the forcing data and observations and the frequency and soil depth of the assimilation of observed data all had obvious effects on the simulated soil moisture.

  14. Use of Neutron Probe to Quantify the Soil Moisture Flux in Layers of Cultivated Soil by Chickpea

    International Nuclear Information System (INIS)

    El- Gendy, R.W.

    2008-01-01

    This work aims to use the neutron moisture meter and the soil moisture retention curve to quantify the soil moisture flux in the soil profile of Nubarria soil in Egypt at 15, 30, 45, and 60-cm depths during the growth season of Chickpea. This method depends on the use of in situ θ measurements via neutron moisture meter and soil matric suction using model of the soil moisture retention curve at different soil depths, which can be determined in situ. Total hydraulic potential values at the different soil depths were calculated as a function (θ) using the derivative model. The gradient of hydraulic potential at any soil depth can be obtained by detecting of the hydraulic potential within the soil profile. The soil water fluxes at the different soil depths were calculated using In situ measured unsaturated hydraulic conductivity and the gradient of hydraulic potential, which correlated with soil moisture contents as measured by neutron probe. Values of hydraulic potentials after and before irrigation indicate that the direction of soil moisture movement was downward after irrigation and was different before next irrigation. Collecting active roots for water absorption of chickpea were defined from direction of soil water movement from up and down to a certain soil depth was 19 cm depth from the soil surface. Active rooting depth was 53 cm depth, which separates between evapotranspiration and gravity effects The soil water fluxes after and before the next irrigation of chickpea were 1.2453, 0.8613, 0.8197 and 0.6588 cm/hr and 0.0037, - 0.0270,- 0.1341, and 0.2545 cm/hr at 15, 30, 45 and 60 cm depths, respectively. The negative values at 30 and 45 cm depth before the next irrigation indicates there were up ward movement for soil water flux, where finding collecting active roots for water absorption of chickpea at 19 cm depth. Direction of soil water movement, soil water flux, collecting active roots for water absorption and active rooting depth can be determined using

  15. Effects of Soil Moisture on the Temperature Sensitivity of Soil Heterotrophic Respiration: A Laboratory Incubation Study

    Science.gov (United States)

    Zhou, Weiping; Hui, Dafeng; Shen, Weijun

    2014-01-01

    The temperature sensitivity (Q10) of soil heterotrophic respiration (Rh) is an important ecological model parameter and may vary with temperature and moisture. While Q10 generally decreases with increasing temperature, the moisture effects on Q10 have been controversial. To address this, we conducted a 90-day laboratory incubation experiment using a subtropical forest soil with a full factorial combination of five moisture levels (20%, 40%, 60%, 80%, and 100% water holding capacity - WHC) and five temperature levels (10, 17, 24, 31, and 38°C). Under each moisture treatment, Rh was measured several times for each temperature treatment to derive Q10 based on the exponential relationships between Rh and temperature. Microbial biomass carbon (MBC), microbial community structure and soil nutrients were also measured several times to detect their potential contributions to the moisture-induced Q10 variation. We found that Q10 was significantly lower at lower moisture levels (60%, 40% and 20% WHC) than at higher moisture level (80% WHC) during the early stage of the incubation, but became significantly higher at 20%WHC than at 60% WHC and not significantly different from the other three moisture levels during the late stage of incubation. In contrast, soil Rh had the highest value at 60% WHC and the lowest at 20% WHC throughout the whole incubation period. Variations of Q10 were significantly associated with MBC during the early stages of incubation, but with the fungi-to-bacteria ratio during the later stages, suggesting that changes in microbial biomass and community structure are related to the moisture-induced Q10 changes. This study implies that global warming’s impacts on soil CO2 emission may depend upon soil moisture conditions. With the same temperature rise, wetter soils may emit more CO2 into the atmosphere via heterotrophic respiration. PMID:24647610

  16. Soil moisture estimation using reflected solar and emitted thermal infrared radiation

    Science.gov (United States)

    Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.

    1978-01-01

    Classical methods of measuring soil moisture such as gravimetric sampling and the use of neutron moisture probes are useful for cases where a point measurement is sufficient to approximate the water content of a small surrounding area. However, there is an increasing need for rapid and repetitive estimations of soil moisture over large areas. Remote sensing techniques potentially have the capability of meeting this need. The use of reflected-solar and emitted thermal-infrared radiation, measured remotely, to estimate soil moisture is examined.

  17. PRELIMINARY RESULTS OF ESTIMATING SOIL MOISTURE OVER BARE SOIL USING FULL-POLARIMETRIC ALOS-2 DATA

    Directory of Open Access Journals (Sweden)

    A. Sekertekin

    2016-10-01

    Full Text Available Synthetic Aperture Radar (SAR imaging system is one of the most effective way for Earth observation. The aim of this study is to present the preliminary results about estimating soil moisture using L-band Synthetic Aperture Radar (SAR data. Full-polarimetric (HH, HV, VV, VH ALOS-2 data, acquired on 22.04.2016 with the incidence angle of 30.4o, were used in the study. Simultaneously with the SAR acquisition, in-situ soil moisture samples over bare agricultural lands were collected and evaluated using gravimetric method. Backscattering coefficients for all polarizations were obtained and linear regression analysis was carried out with in situ moisture measurements. The best correlation coefficient was observed with VV polarization. Cross-polarized backscattering coefficients were not so sensitive to soil moisture content. In the study, it was observed that soil moisture maps can be retrieved with the accuracy about 14% (RMSE.

  18. Anthropogenic warming exacerbates European soil moisture droughts

    Science.gov (United States)

    Samaniego, L.; Thober, S.; Kumar, R.; Wanders, N.; Rakovec, O.; Pan, M.; Zink, M.; Sheffield, J.; Wood, E. F.; Marx, A.

    2018-05-01

    Anthropogenic warming is anticipated to increase soil moisture drought in the future. However, projections are accompanied by large uncertainty due to varying estimates of future warming. Here, using an ensemble of hydrological and land-surface models, forced with bias-corrected downscaled general circulation model output, we estimate the impacts of 1-3 K global mean temperature increases on soil moisture droughts in Europe. Compared to the 1.5 K Paris target, an increase of 3 K—which represents current projected temperature change—is found to increase drought area by 40% (±24%), affecting up to 42% (±22%) more of the population. Furthermore, an event similar to the 2003 drought is shown to become twice as frequent; thus, due to their increased occurrence, events of this magnitude will no longer be classified as extreme. In the absence of effective mitigation, Europe will therefore face unprecedented increases in soil moisture drought, presenting new challenges for adaptation across the continent.

  19. Potential of bias correction for downscaling passive microwave and soil moisture data

    Science.gov (United States)

    Passive microwave satellites such as SMOS (Soil Moisture and Ocean Salinity) or SMAP (Soil Moisture Active Passive) observe brightness temperature (TB) and retrieve soil moisture at a spatial resolution greater than most hydrological processes. Bias correction is proposed as a simple method to disag...

  20. Dust emission parameterization scheme over the MENA region: Sensitivity analysis to soil moisture and soil texture

    Science.gov (United States)

    Gherboudj, Imen; Beegum, S. Naseema; Marticorena, Beatrice; Ghedira, Hosni

    2015-10-01

    The mineral dust emissions from arid/semiarid soils were simulated over the MENA (Middle East and North Africa) region using the dust parameterization scheme proposed by Alfaro and Gomes (2001), to quantify the effect of the soil moisture and clay fraction in the emissions. For this purpose, an extensive data set of Soil Moisture and Ocean Salinity soil moisture, European Centre for Medium-Range Weather Forecasting wind speed at 10 m height, Food Agricultural Organization soil texture maps, MODIS (Moderate Resolution Imaging Spectroradiometer) Normalized Difference Vegetation Index, and erodibility of the soil surface were collected for the a period of 3 years, from 2010 to 2013. Though the considered data sets have different temporal and spatial resolution, efforts have been made to make them consistent in time and space. At first, the simulated sandblasting flux over the region were validated qualitatively using MODIS Deep Blue aerosol optical depth and EUMETSAT MSG (Meteosat Seciond Generation) dust product from SEVIRI (Meteosat Spinning Enhanced Visible and Infrared Imager) and quantitatively based on the available ground-based measurements of near-surface particulate mass concentrations (PM10) collected over four stations in the MENA region. Sensitivity analyses were performed to investigate the effect of soil moisture and clay fraction on the emissions flux. The results showed that soil moisture and soil texture have significant roles in the dust emissions over the MENA region, particularly over the Arabian Peninsula. An inversely proportional dependency is observed between the soil moisture and the sandblasting flux, where a steep reduction in flux is observed at low friction velocity and a gradual reduction is observed at high friction velocity. Conversely, a directly proportional dependency is observed between the soil clay fraction and the sandblasting flux where a steep increase in flux is observed at low friction velocity and a gradual increase is

  1. Hydrological real-time modelling in the Zambezi river basin using satellite-based soil moisture and rainfall data

    Directory of Open Access Journals (Sweden)

    P. Meier

    2011-03-01

    Full Text Available Reliable real-time forecasts of the discharge can provide valuable information for the management of a river basin system. For the management of ecological releases even discharge forecasts with moderate accuracy can be beneficial. Sequential data assimilation using the Ensemble Kalman Filter provides a tool that is both efficient and robust for a real-time modelling framework. One key parameter in a hydrological system is the soil moisture, which recently can be characterized by satellite based measurements. A forecasting framework for the prediction of discharges is developed and applied to three different sub-basins of the Zambezi River Basin. The model is solely based on remote sensing data providing soil moisture and rainfall estimates. The soil moisture product used is based on the back-scattering intensity of a radar signal measured by a radar scatterometer. These soil moisture data correlate well with the measured discharge of the corresponding watershed if the data are shifted by a time lag which is dependent on the size and the dominant runoff process in the catchment. This time lag is the basis for the applicability of the soil moisture data for hydrological forecasts. The conceptual model developed is based on two storage compartments. The processes modeled include evaporation losses, infiltration and percolation. The application of this model in a real-time modelling framework yields good results in watersheds where soil storage is an important factor. The lead time of the forecast is dependent on the size and the retention capacity of the watershed. For the largest watershed a forecast over 40 days can be provided. However, the quality of the forecast increases significantly with decreasing prediction time. In a watershed with little soil storage and a quick response to rainfall events, the performance is relatively poor and the lead time is as short as 10 days only.

  2. Changes in soil moisture drive soil methane uptake along a fire regeneration chronosequence in a eucalypt forest landscape.

    Science.gov (United States)

    Fest, Benedikt; Wardlaw, Tim; Livesley, Stephen J; Duff, Thomas J; Arndt, Stefan K

    2015-11-01

    Disturbance associated with severe wildfires (WF) and WF simulating harvest operations can potentially alter soil methane (CH4 ) oxidation in well-aerated forest soils due to the effect on soil properties linked to diffusivity, methanotrophic activity or changes in methanotrophic bacterial community structure. However, changes in soil CH4 flux related to such disturbances are still rarely studied even though WF frequency is predicted to increase as a consequence of global climate change. We measured in-situ soil-atmosphere CH4 exchange along a wet sclerophyll eucalypt forest regeneration chronosequence in Tasmania, Australia, where the time since the last severe fire or harvesting disturbance ranged from 9 to >200 years. On all sampling occasions, mean CH4 uptake increased from most recently disturbed sites (9 year) to sites at stand 'maturity' (44 and 76 years). In stands >76 years since disturbance, we observed a decrease in soil CH4 uptake. A similar age dependency of potential CH4 oxidation for three soil layers (0.0-0.05, 0.05-0.10, 0.10-0.15 m) could be observed on incubated soils under controlled laboratory conditions. The differences in soil CH4 uptake between forest stands of different age were predominantly driven by differences in soil moisture status, which affected the diffusion of atmospheric CH4 into the soil. The observed soil moisture pattern was likely driven by changes in interception or evapotranspiration with forest age, which have been well described for similar eucalypt forest systems in south-eastern Australia. Our results imply that there is a large amount of variability in CH4 uptake at a landscape scale that can be attributed to stand age and soil moisture differences. An increase in severe WF frequency in response to climate change could potentially increase overall forest soil CH4 sinks. © 2015 John Wiley & Sons Ltd.

  3. Hydrologic responses to restored wildfire regimes revealed by soil moisture-vegetation relationships

    Science.gov (United States)

    Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott

    2018-02-01

    Many forested mountain watersheds worldwide evolved with frequent fire, which Twentieth Century fire suppression activities eliminated, resulting in unnaturally dense forests with high water demand. Restoration of pre-suppression forest composition and structure through a variety of management activities could improve forest resilience and water yields. This study explores the potential for "managed wildfire", whereby naturally ignited fires are allowed to burn, to alter the water balance. Interest in this type of managed wildfire is increasing, yet its long-term effects on water balance are uncertain. We use soil moisture as a spatially-distributed hydrologic indicator to assess the influence of vegetation, fire history and landscape position on water availability in the Illilouette Creek Basin in Yosemite National Park. Over 6000 manual surface soil moisture measurements were made over a period of three years, and supplemented with continuous soil moisture measurements over the top 1m of soil in three sites. Random forest and linear mixed effects models showed a dominant effect of vegetation type and history of vegetation change on measured soil moisture. Contemporary and historical vegetation maps were used to upscale the soil moisture observations to the basin and infer soil moisture under fire-suppressed conditions. Little change in basin-averaged soil moisture was inferred due to managed wildfire, but the results indicated that large localized increases in soil moisture had occurred, which could have important impacts on local ecology or downstream flows.

  4. Assimilation of microwave brightness temperatures for soil moisture estimation using particle filter

    International Nuclear Information System (INIS)

    Bi, H Y; Ma, J W; Qin, S X; Zeng, J Y

    2014-01-01

    Soil moisture plays a significant role in global water cycles. Both model simulations and remote sensing observations have their limitations when estimating soil moisture on a large spatial scale. Data assimilation (DA) is a promising tool which can combine model dynamics and remote sensing observations to obtain more precise ground soil moisture distribution. Among various DA methods, the particle filter (PF) can be applied to non-linear and non-Gaussian systems, thus holding great potential for DA. In this study, a data assimilation scheme based on the residual resampling particle filter (RR-PF) was developed to assimilate microwave brightness temperatures into the macro-scale semi-distributed Variance Infiltration Capacity (VIC) Model to estimate surface soil moisture. A radiative transfer model (RTM) was used to link brightness temperatures with surface soil moisture. Finally, the data assimilation scheme was validated by experimental data obtained at Arizona during the Soil Moisture Experiment 2004 (SMEX04). The results show that the estimation accuracy of soil moisture can be improved significantly by RR-PF through assimilating microwave brightness temperatures into VIC model. Both the overall trends and specific values of the assimilation results are more consistent with ground observations compared with model simulation results

  5. A Smart Irrigation Approach Aided by Monitoring Surface Soil Moisture using Unmanned Aerial Vehicles

    Science.gov (United States)

    Wienhold, K. J.; Li, D.; Fang, N. Z.

    2017-12-01

    Soil moisture is a critical component in the optimization of irrigation scheduling in water resources management. Unmanned Aerial Vehicles (UAV) equipped with multispectral sensors represent an emerging technology capable of detecting and estimating soil moisture for irrigation and crop management. This study demonstrates a method of using a UAV as an optical and thermal remote sensing platform combined with genetic programming to derive high-resolution, surface soil moisture (SSM) estimates. The objective is to evaluate the feasibility of spatially-variable irrigation management for a golf course (about 50 acres) in North Central Texas. Multispectral data is collected over the course of one month in the visible, near infrared and longwave infrared spectrums using a UAV capable of rapid and safe deployment for daily estimates. The accuracy of the model predictions is quantified using a time domain reflectometry (TDR) soil moisture sensor and a holdout validation test set. The model produces reasonable estimates for SSM with an average coefficient of correlation (r) = 0.87 and coefficient of determination of (R2) = 0.76. The study suggests that the derived SSM estimates be used to better inform irrigation scheduling decisions for lightly vegetated areas such as the turf or native roughs found on golf courses.

  6. Sensitivity Analysis of b-factor in Microwave Emission Model for Soil Moisture Retrieval: A Case Study for SMAP Mission

    Directory of Open Access Journals (Sweden)

    Dugwon Seo

    2010-05-01

    Full Text Available Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS and measured field soil moisture from Southern Great Plains experiment (SGP99. The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated condition compared to the sensitivity of the soil moisture. Apparently, the b-factor is found to be more sensitive than the vegetation water content, surface roughness and surface temperature; therefore, the effect of the b-factor is fairly large to the microwave emission in certain conditions. Understanding the dependence of the b-factor on the soil and vegetation is important in studying the soil moisture retrieval algorithm, which can lead to potential improvements in model development for the Soil Moisture Active-Passive (SMAP mission.

  7. Soil Moisture Data Assimilation in the NASA Land Information System for Local Modeling Applications and Improved Situational Awareness

    Science.gov (United States)

    Case, Jonathan L.; Blakenship, Clay B.; Zavodsky, Bradley T.

    2014-01-01

    As part of the NASA Soil Moisture Active Passive (SMAP) Early Adopter (EA) program, the NASA Shortterm Prediction Research and Transition (SPoRT) Center has implemented a data assimilation (DA) routine into the NASA Land Information System (LIS) for soil moisture retrievals from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) satellite. The SMAP EA program promotes application-driven research to provide a fundamental understanding of how SMAP data products will be used to improve decision-making at operational agencies. SPoRT has partnered with select NOAA/NWS Weather Forecast Offices (WFOs) that use output from a real-time regional configuration of LIS, without soil moisture DA, to initialize local numerical weather prediction (NWP) models and enhance situational awareness. Improvements to local NWP with the current LIS have been demonstrated; however, a better representation of the land surface through assimilation of SMOS (and eventually SMAP) retrievals is expected to lead to further model improvement, particularly during warm-season months. SPoRT will collaborate with select WFOs to assess the impact of soil moisture DA on operational forecast situations. Assimilation of the legacy SMOS instrument data provides an opportunity to develop expertise in preparation for using SMAP data products shortly after the scheduled launch on 5 November 2014. SMOS contains a passive L-band radiometer that is used to retrieve surface soil moisture at 35-km resolution with an accuracy of 0.04 cu cm cm (exp -3). SMAP will feature a comparable passive L-band instrument in conjunction with a 3-km resolution active radar component of slightly degraded accuracy. A combined radar-radiometer product will offer unprecedented global coverage of soil moisture at high spatial resolution (9 km) for hydrometeorological applications, balancing the resolution and accuracy of the active and passive instruments, respectively. The LIS software framework manages land surface model

  8. Dependence of Soil Respiration on Soil Temperature and Soil Moisture in Successional Forests in Southern China

    Institute of Scientific and Technical Information of China (English)

    Xu-Li Tang; Guo-Yi Zhou; Shu-Guang Liu; De-Qiang Zhang; Shi-Zhong Liu; Jiong Li; Cun-Yu Zhou

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (± SD) soil respiration rate in the DNR forests was (9.0±4.6) Mg CO2-C/hm2 per year, ranging from (6.1±3.2) Mg CO2-C/hm2 per year in early successional forests to (10.7±4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities.

  9. Dependence of soil respiration on soil temperature and soil moisture in successional forests in Southern China

    Science.gov (United States)

    Tang, X.-L.; Zhou, G.-Y.; Liu, S.-G.; Zhang, D.-Q.; Liu, S.-Z.; Li, Ji; Zhou, C.-Y.

    2006-01-01

    The spatial and temporal variations in soil respiration and its relationship with biophysical factors in forests near the Tropic of Cancer remain highly uncertain. To contribute towards an improvement of actual estimates, soil respiration rates, soil temperature, and soil moisture were measured in three successional subtropical forests at the Dinghushan Nature Reserve (DNR) in southern China from March 2003 to February 2005. The overall objective of the present study was to analyze the temporal variations of soil respiration and its biophysical dependence in these forests. The relationships between biophysical factors and soil respiration rates were compared in successional forests to test the hypothesis that these forests responded similarly to biophysical factors. The seasonality of soil respiration coincided with the seasonal climate pattern, with high respiration rates in the hot humid season (April-September) and with low rates in the cool dry season (October-March). Soil respiration measured at these forests showed a clear increasing trend with the progressive succession. Annual mean (±SD) soil respiration rate in the DNR forests was (9.0 ± 4.6) Mg CO2-C/hm2per year, ranging from (6.1 ± 3.2) Mg CO2-C/hm2per year in early successional forests to (10.7 ± 4.9) Mg CO2-C/hm2 per year in advanced successional forests. Soil respiration was correlated with both soil temperature and moisture. The T/M model, where the two biophysical variables are driving factors, accounted for 74%-82% of soil respiration variation in DNR forests. Temperature sensitivity decreased along progressive succession stages, suggesting that advanced-successional forests have a good ability to adjust to temperature. In contrast, moisture increased with progressive succession processes. This increase is caused, in part, by abundant respirators in advanced-successional forest, where more soil moisture is needed to maintain their activities.

  10. Inference of soil hydrologic parameters from electronic soil moisture records

    Science.gov (United States)

    Soil moisture is an important control on hydrologic function, as it governs vertical fluxes from and to the atmosphere, groundwater recharge, and lateral fluxes through the soil. Historically, the traditional model parameters of saturation, field capacity, and permanent wilting point have been deter...

  11. Impacts of Soil Moisture on Typical Frontal Rainstorm in Yangtze River Basin

    Directory of Open Access Journals (Sweden)

    Jinzhong Min

    2016-03-01

    Full Text Available By using a coupled land surface-atmosphere model with initial conditions of varying resolution and ensembles of systematically changed soil moisture, convective-scale simulations of a typical frontal rainstorm in the Yangtze River Basin are collected to investigate: (1 effects of different datasets on the simulated frontal mesoscale convective systems (MCSs; (2 possible linkages between soil moisture, planetary boundary layer (PBL, MCSs and precipitation in this modeled rainstorm. Firstly, initial soil moisture differences can affect the PBL, MCSs and precipitation of this frontal rainstorm. Specially, for a 90 mm precipitation forecast, the Threat score (TS can increase 6.61% by using the Global Land Data Assimilation System (GLDAS soil moisture. Secondly, sensitivity experiment results show that the near-surface thermodynamic conditions are more sensitive to dry soil than wet due to the initial moist surface; atmosphere conditions have suppressed the relations between soil and atmosphere; and decreased precipitation can be found over both wet and dry surfaces. Generally, a positive feedback between soil moisture and the near-surface thermodynamic conditions is identified, while the relations between soil moisture and precipitation are quite complicated. This relationship shows a daytime mixing of warm surface soil over dry surfaces and a daytime evaporation of adequate moisture over wet surfaces. The large-scale forcing can affect these relations and finally cause decreased precipitation over both wet and dry surfaces.

  12. Effect of land-use practice on soil moisture variability for soils covered with dense forest vegetation of Puerto Rico

    Science.gov (United States)

    Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.

    1998-01-01

    Little is known about the landuse management effect on soil moisture and soil pH distribution on a landscape covered with dense tropical forest vegetation. This study was conducted at three locations where the history of the landuse management is different. Soil moisture was measured using a 6-cm three-rod Time Domain Reflectometery (TDR) probe. Disturbed soil samples were taken from the top 5-cm at the up, mid, and foothill landscape position from the same spots where soil moisture was measured. The results showed that soil moisture varies with landscape position and depth at all three locations. Soil pH and moisture variability were found to be affected by the change in landuse management and landscape position. Soil moisture distribution usually expected to be relatively higher in the foothill (P3) area of these forests than the uphill (P1) position. However, our results indicated that in the Luquillo and Guanica site the surface soil moisture was significantly higher for P1 than P3 position. These suggest that the surface and subsurface drainage in these two sites may have been poor due to the nature of soil formation and type.

  13. Remote Sensing of Surface Soil Moisture using Semi-Concurrent Radar and Radiometer Observations

    Science.gov (United States)

    Li, L.; Ouellette, J. D.; Colliander, A.; Cosh, M. H.; Caldwell, T. G.; Walker, J. P.

    2017-12-01

    Radar backscatter and radiometer brightness temperature both have well-documented sensitivity to surface soil moisture, particularly in the microwave regime. While radiometer-derived soil moisture retrievals have been shown to be stable and accurate, they are only available at coarse spatial resolutions on the order of tens of kilometers. Backscatter from Synthetic Aperture Radar (SAR) is similarly sensitive to soil moisture but can yield higher spatial resolutions, with pixel sizes about an order of magnitude smaller. Soil moisture retrieval from radar backscatter is more difficult, however, due to the combined sensitivity of radar scattering to surface roughness, vegetation structure, and soil moisture. The algorithm uses a time-series of SAR data to retrieval soil moisture information, constraining the SAR-derived soil moisture estimates with radiometer observations. This effectively combines the high spatial resolution offered by SAR with the precision offered by passive radiometry. The algorithm is a change detection approach which maps changes in the radar backscatter to changes in surface soil moisture. This new algorithm differs from existing retrieval techniques in that it does not require ancillary vegetation information, but assumes vegetation and surface roughness are stable between pairs of consecutive radar overpasses. Furthermore, this method does not require a radar scattering model for the vegetation canopy, nor the use of a training data set. The algorithm works over a long time series, and is constrained by hard bounds which are defined using a coarse-resolution radiometer soil moisture product. The presentation will include soil moisture retrievals from Soil Moisture Active/Passive (SMAP) SAR data. Two sets of optimization bounds will constrain the radar change detection algorithm: one defined by SMAP radiometer retrievals and one defined by WindSat radiometer retrievals. Retrieved soil moisture values will be presented on a world map and will

  14. Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture

    Science.gov (United States)

    Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.

    2016-06-01

    Terrestrial evaporation is an essential variable in the climate system that links the water, energy and carbon cycles over land. Despite this crucial importance, it remains one of the most uncertain components of the hydrological cycle, mainly due to known difficulties to model the constraints imposed by land water availability on terrestrial evaporation. The main objective of this study is to assimilate satellite soil moisture observations from the Soil Moisture and Ocean Salinity (SMOS) mission into an existing evaporation model. Our over-arching goal is to find an optimal use of satellite soil moisture that can help to improve our understanding of evaporation at continental scales. To this end, the Global Land Evaporation Amsterdam Model (GLEAM) is used to simulate evaporation fields over continental Australia for the period September 2010-December 2013. SMOS soil moisture observations are assimilated using a Newtonian Nudging algorithm in a series of experiments. Model estimates of surface soil moisture and evaporation are validated against soil moisture probe and eddy-covariance measurements, respectively. Finally, an analogous experiment in which Advanced Microwave Scanning Radiometer (AMSR-E) soil moisture is assimilated (instead of SMOS) allows to perform a relative assessment of the quality of both satellite soil moisture products. Results indicate that the modelled soil moisture from GLEAM can be improved through the assimilation of SMOS soil moisture: the average correlation coefficient between in situ measurements and the modelled soil moisture over the complete sample of stations increased from 0.68 to 0.71 and a statistical significant increase in the correlations is achieved for 17 out of the 25 individual stations. Our results also suggest a higher accuracy of the ascending SMOS data compared to the descending data, and overall higher quality of SMOS compared to AMSR-E retrievals over Australia. On the other hand, the effect of soil moisture data

  15. Comparison of Soil Moisture in Switzerland Using In-Situ Measurements and Model Output

    Science.gov (United States)

    Mittelbach, H.; Orth, R.; Seneviratne, S. I.

    2011-01-01

    Soil moisture is an essential contributor to land surface- atmosphere interactions. In this study we evaluate the two Land surface models CLM3.5 and SIB3 regarding their performance in simulating soil moisture and its anomalies for the one year period 01.09.2009 to 31.08.2010. Four grassland sites from the SwissSMEX/- Veg project were used as reference soil moisture data. In general, both models represent the soil moisture anomalies and their distribution better than the absolute soil moisture. Furthermore, both models show a seasonal dependence of the correlation and root mean square error. In contrast to the SIB3 model, the CLM3.5 model shows stronger seasonal variation of the root mean square error and a larger interquantile range for soil moisture anomalies.

  16. Continuous data assimilation for downscaling large-footprint soil moisture retrievals

    KAUST Repository

    Altaf, Muhammad

    2016-01-01

    Soil moisture is a key component of the hydrologic cycle, influencing processes leading to runoff generation, infiltration and groundwater recharge, evaporation and transpiration. Generally, the measurement scale for soil moisture is found to be different from the modeling scales for these processes. Reducing this mismatch between observation and model scales in necessary for improved hydrological modeling. An innovative approach to downscaling coarse resolution soil moisture data by combining continuous data assimilation and physically based modeling is presented. In this approach, we exploit the features of Continuous Data Assimilation (CDA) which was initially designed for general dissipative dynamical systems and later tested numerically on the incompressible Navier-Stokes equation, and the Benard equation. A nudging term, estimated as the misfit between interpolants of the assimilated coarse grid measurements and the fine grid model solution, is added to the model equations to constrain the model\\'s large scale variability by available measurements. Soil moisture fields generated at a fine resolution by a physically-based vadose zone model (HYDRUS) are subjected to data assimilation conditioned upon coarse resolution observations. This enables nudging of the model outputs towards values that honor the coarse resolution dynamics while still being generated at the fine scale. Results show that the approach is feasible to generate fine scale soil moisture fields across large extents, based on coarse scale observations. Application of this approach is likely in generating fine and intermediate resolution soil moisture fields conditioned on the radiometerbased, coarse resolution products from remote sensing satellites.

  17. Precipitation Estimation Using L-Band and C-Band Soil Moisture Retrievals

    Science.gov (United States)

    Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.

    2016-01-01

    An established methodology for estimating precipitation amounts from satellite-based soil moisture retrievals is applied to L-band products from the Soil Moisture Active Passive (SMAP) and Soil Moisture and Ocean Salinity (SMOS) satellite missions and to a C-band product from the Advanced Scatterometer (ASCAT) mission. The precipitation estimates so obtained are evaluated against in situ (gauge-based) precipitation observations from across the globe. The precipitation estimation skill achieved using the L-band SMAP and SMOS data sets is higher than that obtained with the C-band product, as might be expected given that L-band is sensitive to a thicker layer of soil and thereby provides more information on the response of soil moisture to precipitation. The square of the correlation coefficient between the SMAP-based precipitation estimates and the observations (for aggregations to approximately100 km and 5 days) is on average about 0.6 in areas of high rain gauge density. Satellite missions specifically designed to monitor soil moisture thus do provide significant information on precipitation variability, information that could contribute to efforts in global precipitation estimation.

  18. Impacts of twenty years of experimental warming on soil carbon, nitrogen, moisture and soil across alpine/subarctic tundra communities

    DEFF Research Database (Denmark)

    M. Alatalo, Juha; K. Jägerbrand, Annika; Juhanson, Jaanis

    2017-01-01

    High-altitude and alpine areas are predicted to experience rapid and substantial increases in future temperature, which may have serious impacts on soil carbon, nutrient and soil fauna. Here we report the impact of 20 years of experimental warming on soil properties and soil mites in three...... contrasting plant communities in alpine/subarctic Sweden. Long-term warming decreased juvenile oribatid mite density, but had no effect on adult oribatids density, total mite density, any major mite group or the most common species. Long-term warming also caused loss of nitrogen, carbon and moisture from...

  19. Improving Landslide Forecasting Using ASCAT-Derived Soil Moisture Data: A Case Study of the Torgiovannetto Landslide in Central Italy

    Directory of Open Access Journals (Sweden)

    Wolfgang Wagner

    2012-05-01

    Full Text Available Predicting the spatial and temporal occurrence of rainfall triggered landslides represents an important scientific and operational issue due to the high threat that they pose to human life and property. This study investigates the relationship between rainfall, soil moisture conditions and landslide movement by using recorded movements of a rock slope located in central Italy, the Torgiovannetto landslide. This landslide is a very large rock slide, threatening county and state roads. Data acquired by a network of extensometers and a meteorological station clearly indicate that the movements of the unstable wedge, first detected in 2003, are still proceeding and the alternate phases of quiescence and reactivation are associated with rainfall patterns. By using a multiple linear regression approach, the opening of the tension cracks (as recorded by the extensometers as a function of rainfall and soil moisture conditions prior the occurrence of rainfall, are predicted for the period 2007–2009. Specifically, soil moisture indicators are obtained through the Soil Water Index, SWI, a product derived by the Advanced SCATterometer (ASCAT on board the MetOp (Meteorological Operational satellite and by an Antecedent Precipitation Index, API. Results indicate that the regression performance (in terms of correlation coefficient, r significantly enhances if an indicator of the soil moisture conditions is included. Specifically, r is equal to 0.40 when only rainfall is used as a predictor variable and increases to r = 0.68 and r = 0.85 if the API and the SWI are used respectively. Therefore, the coarse spatial resolution (25 km of satellite data notwithstanding, the ASCAT SWI is found to be very useful for the prediction of landslide movements on a local scale. These findings, although valid for a specific area, present new opportunities for the effective use of satellite-derived soil moisture estimates to improve landslide forecasting.

  20. SOIL moisture data intercomparison

    Science.gov (United States)

    Kerr, Yann; Rodriguez-Frenandez, Nemesio; Al-Yaari, Amen; Parens, Marie; Molero, Beatriz; Mahmoodi, Ali; Mialon, Arnaud; Richaume, Philippe; Bindlish, Rajat; Mecklenburg, Susanne; Wigneron, Jean-Pierre

    2016-04-01

    The Soil Moisture and Ocean Salinity satellite (SMOS) was launched in November 2009 and started delivering data in January 2010. Subsequently, the satellite has been in operation for over 6 years while the retrieval algorithms from Level 1 to Level 2 underwent significant evolutions as knowledge improved. Other approaches for retrieval at Level 2 over land were also investigated while Level 3 and 4 were initiated. In this présentation these improvements are assessed by inter-comparisons of the current Level 2 (V620) against the previous version (V551) and new products either using neural networks or Level 3. In addition a global evaluation of different SMOS soil moisture (SM) products is performed comparing products with those of model simulations and other satellites (AMSR E/ AMSR2 and ASCAT). Finally, all products were evaluated against in situ measurements of soil moisture (SM). The study demonstrated that the V620 shows a significant improvement (including those at level1 improving level2)) with respect to the earlier version V551. Results also show that neural network based approaches can yield excellent results over areas where other products are poor. Finally, global comparison indicates that SMOS behaves very well when compared to other sensors/approaches and gives consistent results over all surfaces from very dry (African Sahel, Arizona), to wet (tropical rain forests). RFI (Radio Frequency Interference) is still an issue even though detection has been greatly improved while RFI sources in several areas of the world are significantly reduced. When compared to other satellite products, the analysis shows that SMOS achieves its expected goals and is globally consistent over different eco climate regions from low to high latitudes and throughout the seasons.

  1. Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

    Science.gov (United States)

    Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

    2008-08-01

    SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar

  2. Upscaling of Surface Soil Moisture Using a Deep Learning Model with VIIRS RDR

    Directory of Open Access Journals (Sweden)

    Dongying Zhang

    2017-04-01

    Full Text Available In current upscaling of in situ surface soil moisture practices, commonly used novel statistical or machine learning-based regression models combined with remote sensing data show some advantages in accurately capturing the satellite footprint scale of specific local or regional surface soil moisture. However, the performance of most models is largely determined by the size of the training data and the limited generalization ability to accomplish correlation extraction in regression models, which are unsuitable for larger scale practices. In this paper, a deep learning model was proposed to estimate soil moisture on a national scale. The deep learning model has the advantage of representing nonlinearities and modeling complex relationships from large-scale data. To illustrate the deep learning model for soil moisture estimation, the croplands of China were selected as the study area, and four years of Visible Infrared Imaging Radiometer Suite (VIIRS raw data records (RDR were used as input parameters, then the models were trained and soil moisture estimates were obtained. Results demonstrate that the estimated models captured the complex relationship between the remote sensing variables and in situ surface soil moisture with an adjusted coefficient of determination of R ¯ 2 = 0.9875 and a root mean square error (RMSE of 0.0084 in China. These results were more accurate than the Soil Moisture Active Passive (SMAP active radar soil moisture products and the Global Land data assimilation system (GLDAS 0–10 cm depth soil moisture data. Our study suggests that deep learning model have potential for operational applications of upscaling in situ surface soil moisture data at the national scale.

  3. Inferring Soil Moisture Memory from Streamflow Observations Using a Simple Water Balance Model

    Science.gov (United States)

    Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.

    2013-01-01

    Soil moisture is known for its integrative behavior and resulting memory characteristics. Soil moisture anomalies can persist for weeks or even months into the future, making initial soil moisture a potentially important contributor to skill in weather forecasting. A major difficulty when investigating soil moisture and its memory using observations is the sparse availability of long-term measurements and their limited spatial representativeness. In contrast, there is an abundance of long-term streamflow measurements for catchments of various sizes across the world. We investigate in this study whether such streamflow measurements can be used to infer and characterize soil moisture memory in respective catchments. Our approach uses a simple water balance model in which evapotranspiration and runoff ratios are expressed as simple functions of soil moisture; optimized functions for the model are determined using streamflow observations, and the optimized model in turn provides information on soil moisture memory on the catchment scale. The validity of the approach is demonstrated with data from three heavily monitored catchments. The approach is then applied to streamflow data in several small catchments across Switzerland to obtain a spatially distributed description of soil moisture memory and to show how memory varies, for example, with altitude and topography.

  4. Influence of soil moisture content on surface albedo and soil thermal ...

    Indian Academy of Sciences (India)

    Half hourly data of soil moisture content, soil temperature, solar irradiance, and reflectance are measured ... and the influence of solar elevation angle and cloud cover are also investigated. .... ters are important factors in climate modelling and.

  5. A New Approach in Downscaling Microwave Soil Moisture Product using Machine Learning

    Science.gov (United States)

    Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid

    2016-04-01

    Understating the soil moisture pattern has significant impact on flood modeling, drought monitoring, and irrigation management. Although satellite retrievals can provide an unprecedented spatial and temporal resolution of soil moisture at a global-scale, their soil moisture products (with a spatial resolution of 25-50 km) are inadequate for regional study, where a resolution of 1-10 km is needed. In this study, a downscaling approach using Genetic Programming (GP), a specialized version of Genetic Algorithm (GA), is proposed to improve the spatial resolution of satellite soil moisture products. The GP approach was applied over a test watershed in United States using the coarse resolution satellite data (25 km) from Advanced Microwave Scanning Radiometer - EOS (AMSR-E) soil moisture products, the fine resolution data (1 km) from Moderate Resolution Imaging Spectroradiometer (MODIS) vegetation index, and ground based data including land surface temperature, vegetation and other potential physical variables. The results indicated the great potential of this approach to derive the fine resolution soil moisture information applicable for data assimilation and other regional studies.

  6. L-band HIgh Spatial Resolution Soil Moisture Mapping using SMALL UnManned Aerial Systems

    Science.gov (United States)

    Dai, E.; Venkitasubramony, A.; Gasiewski, A. J.; Stachura, M.; Elston, J. S.; Walter, B.; Lankford, D.; Corey, C.

    2017-12-01

    Soil moisture is of fundamental importance to many hydrological, biological and biogeochemical processes, plays an important role in the development and evolution of convective weather and precipitation, water resource management, agriculture, and flood runoff prediction. The launch of NASA's Soil Moisture Active/Passive (SMAP) mission in 2015 provided new passive global measurements of soil moisture and surface freeze/thaw state at fixed crossing times and spatial resolutions of 36 km. However, there exists a need for measurements of soil moisture on much smaller spatial scales and arbitrary diurnal times for SMAP validation, precision agriculture and evaporation and transpiration studies of boundary layer heat transport. The Lobe Differencing Correlation Radiometer (LDCR) provides a means of mapping soil moisture on spatial scales as small as several meters. Compared with other methods of validation based on either in-situ measurements [1,2] or existing airborne sensors suitable for manned aircraft deployment [3], the integrated design of the LDCR on a lightweight small UAS (sUAS) is capable of providing sub-watershed ( km scale) coverage at very high spatial resolution ( 15 m) suitable for scaling studies, and at comparatively low operator cost. To demonstrate the LDCR several flights had been performed during field experiments at the Canton Oklahoma Soilscape site and Yuma Colorado Irrigation Research Foundation (IRF) site in 2015 and 2016, respectively, using LDCR Revision A and Tempest sUAS. The scientific intercomparisons of LDCR retrieved soil moisture and in-situ measurements will be presented. LDCR Revision B has been built and integrated into SuperSwift sUAS and additional field experiments will be performed at IRF in 2017. In Revision B the IF signal is sampled at 80 MS/s to enable digital correlation and RFI mitigation capabilities, in addition to analog correlation. [1] McIntyre, E.M., A.J. Gasiewski, and D. Manda D, "Near Real-Time Passive C

  7. Neutron moisture gaging of agricultural soil

    International Nuclear Information System (INIS)

    Pospisil, S.; Janout, Z.; Kovacik, M.

    1987-01-01

    The design is described of a neutron moisture gage which consists of a measuring probe, neutron detector, small electronic recording device and a 241 Am-Be radionuclide source. The neutron detector consists of a surface barrier semiconductor silicon detector and a conversion layer of lithium fluoride. The detection of triton which is the reaction product of lithium with neutrons by the silicon detector is manifested as a voltage pulse. The detector has low sensitivity for fast neutrons and for gamma radiation and is suitable for determining moisture values in large volume samples. Verification and calibration measurements were carried out of chernozem, brown soil and podzolic soils in four series. The results are tabulated. Errors of measurement range between 0.8 to 1.0%. The precision of measurement could be improved by the calibration of the device for any type of soil. (E.S.). 4 tabs., 6 refs., 5 figs

  8. Using lagged dependence to identify (de)coupled surface and subsurface soil moisture values

    Science.gov (United States)

    Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.

    2018-04-01

    Recent advances in radar remote sensing popularized the mapping of surface soil moisture at different spatial scales. Surface soil moisture measurements are used in combination with hydrological models to determine subsurface soil moisture values. However, variability of soil moisture across the soil column is important for estimating depth-integrated values, as decoupling between surface and subsurface can occur. In this study, we employ new methods to investigate the occurrence of (de)coupling between surface and subsurface soil moisture. Using time series datasets, lagged dependence was incorporated in assessing (de)coupling with the idea that surface soil moisture conditions will be reflected at the subsurface after a certain delay. The main approach involves the application of a distributed-lag nonlinear model (DLNM) to simultaneously represent both the functional relation and the lag structure in the time series. The results of an exploratory analysis using residuals from a fitted loess function serve as a posteriori information to determine (de)coupled values. Both methods allow for a range of (de)coupled soil moisture values to be quantified. Results provide new insights into the decoupled range as its occurrence among the sites investigated is not limited to dry conditions.

  9. Soil surface moisture estimation over a semi-arid region using ENVISAT ASAR radar data for soil evaporation evaluation

    Directory of Open Access Journals (Sweden)

    M. Zribi

    2011-01-01

    Full Text Available The present paper proposes a method for the evaluation of soil evaporation, using soil moisture estimations based on radar satellite measurements. We present firstly an approach for the estimation and monitoring of soil moisture in a semi-arid region in North Africa, using ENVISAT ASAR images, over two types of vegetation covers. The first mapping process is dedicated solely to the monitoring of moisture variability related to rainfall events, over areas in the "non-irrigated olive tree" class of land use. The developed approach is based on a simple linear relationship between soil moisture and the backscattered radar signal normalised at a reference incidence angle. The second process is proposed over wheat fields, using an analysis of moisture variability due to both rainfall and irrigation. A semi-empirical model, based on the water-cloud model for vegetation correction, is used to retrieve soil moisture from the radar signal. Moisture mapping is carried out over wheat fields, showing high variability between irrigated and non-irrigated wheat covers. This analysis is based on a large database, including both ENVISAT ASAR and simultaneously acquired ground-truth measurements (moisture, vegetation, roughness, during the 2008–2009 vegetation cycle. Finally, a semi-empirical approach is proposed in order to relate surface moisture to the difference between soil evaporation and the climate demand, as defined by the potential evaporation. Mapping of the soil evaporation is proposed.

  10. Cross-evaluation of modelled and remotely sensed surface soil moisture with in situ data in southwestern France

    Directory of Open Access Journals (Sweden)

    C. Albergel

    2010-11-01

    Full Text Available 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 ASCAT SSM, improves the SSM and the root-zone soil moisture analyses.

  11. Degradation of [14C]isofenphos in soil in the laboratory under different soil pH's, temperatures, and moistures

    International Nuclear Information System (INIS)

    Abou-Assaf, N.; Coats, J.R.

    1987-01-01

    The effects of three soil pH's, three soil temperatures, and three soil moistures on [ 14 C]isofenphos degradation were investigated. All three factors interacted strongly and significantly affected the persistence of isofenphos as well as the formation of the degradation products (p less than 1%). Isofenphos degradation was greatest at the higher temperatures 35 0 C greater than 25 0 C greater than 15 0 C (except under alkaline pH's), medium moisture 25% greater than 30% greater than 15%, and in both alkaline (pH = 8) and acidic soils (pH = 6) compared with neutral soil (pH = 7). Isofenphos oxon formation was greatest at higher temperatures 35 0 C compared with 25 0 C and 15 0 C, in acidic soil greater than neutral soil greater than alkaline soil, and under high moisture (30%) compared with the 15% and 22.5% moistures. The formation of soil-bound residues was greatest at higher temperatures 35 0 C greater than 25 0 C greater than 15 0 C, higher moisture 30% compared with 15% and 22.5%, and in alkaline soil compared with neutral and acidic soils

  12. Effect of soil-moisture stress on nitrogen uptake and fixation by plants

    International Nuclear Information System (INIS)

    Mitrosuhardjo, M.M.

    1983-01-01

    The effect of four levels of soil moisture, namely 25, 30, 35, and 40% (g/g) on nitrogen uptake and fixation by plants was studied in a greenhouse experiment. Soybean and wheat were used in this experiment. Both crops were grown in pots containing 7 kg loamy alluvial soil. Rhizobium japonicum was used as an inoculant for soybean, one week after planting. Nitrogen-15 labelled urea with 10% atom excess was applied to each pot with a dose rate of 70 mg N/pot (20 kg N/ha) two weeks after planting. Soil moisture was regularly controlled with porous-cup mercury tensiometers, and the amount of water consumed by plants was always recorded. Water was applied to each pot with a distribution pipe which was laid down in the centre of the soil depth, horizontally in a circular form, and was connected with a smaller pipe to the soil surface. The result obtained showed that the amount of water consumed by plants grown in a higher level of soil moisture was increased until soil aeration problems arose. A different amount of water consumption between soybean and wheat was observed at least until a certain period of growing time. Fertilizer nitrogen taken up by both crops varied with the different levels of soil moisture. Generally, greater fertilizer nitrogen was taken up by both crops grown in a higher level of soil moisture. The symbiotic fixation of nitrogen was reasonable, although no clarification has been found about the role of the four levels of soil-moisture treatment on it. A similar effect of soil-moisture stress on nodule dry matter and acetylene reduction was found. (author)

  13. Temporal changes of spatial soil moisture patterns: controlling factors explained with a multidisciplinary approach

    Science.gov (United States)

    Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen

    2016-04-01

    Characterizing the spatial patterns of soil moisture is critical for hydrological and meteorological models, as soil moisture is a key variable that controls matter and energy fluxes and soil-vegetation-atmosphere exchange processes. Deriving detailed process understanding at the hillslope scale is not trivial, because of the temporal variability of local soil moisture dynamics. Nevertheless, it remains a challenge to provide adequate information on the temporal variability of soil moisture and its controlling factors. Recent advances in wireless sensor technology allow monitoring of soil moisture dynamics with high temporal resolution at varying scales. In addition, mobile geophysical methods such as electromagnetic induction (EMI) have been widely used for mapping soil water content at the field scale with high spatial resolution, as being related to soil apparent electrical conductivity (ECa). The objective of this study was to characterize the spatial and temporal pattern of soil moisture at the hillslope scale and to infer the controlling hydrological processes, integrating well established and innovative sensing techniques, as well as new statistical methods. We combined soil hydrological and pedological expertise with geophysical measurements and methods from digital soil mapping for designing a wireless soil moisture monitoring network. For a hillslope site within the Schäfertal catchment (Central Germany), soil water dynamics were observed during 14 months, and soil ECa was mapped on seven occasions whithin this period of time using an EM38-DD device. Using the Spearman rank correlation coefficient, we described the temporal persistence of a dry and a wet characteristic state of soil moisture as well as the switching mechanisms, inferring the local properties that control the observed spatial patterns and the hydrological processes driving the transitions. Based on this, we evaluated the use of EMI for mapping the spatial pattern of soil moisture under

  14. Multifrequency passive microwave remote sensing of soil moisture and roughness

    International Nuclear Information System (INIS)

    Paloscia, S.; Pampaloni, P.; Chiarantini, L.; Coppo, P.; Gagliani, S.; Luzi, G.

    1993-01-01

    The accuracy achievable in the surface soil moisture measurement of rough bare and vegetated soils, typical of the Italian landscape, has been investigated by using microwave experimental data collected by means of a multi-band sensor package (L, X, Ka and infrared bands). The thickness of soil that mainly affects the emission at the three microwave frequencies has been assessed. The sensitivity of L band emission to the moisture content of a soil layer about 5 cm thick has been confirmed, as well as the attenuation effect due to the surface roughness and presence of vegetation. A correction criterion based on the sensitivity to roughness and crop parameters of the highest frequencies (X and Ka bands) is proposed in order to increase the precision in soil moisture measurements

  15. Evaluation of AMSR-E derived soil moisture over Australia, /Remote Sensing of Environment

    NARCIS (Netherlands)

    Draper, C.S.; Walker, J.P.; Steinle, P.J.; De Jeu, R.A.M.; Holmes, T.R.H.

    2009-01-01

    This paper assesses remotely sensed near-surface soil moisture over Australia, derived from the passive microwave Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) instrument. Soil moisture fields generated by the AMSR-E soil moisture retrieval algorithm developed at the Vrije

  16. Experimental evidence and modelling of drought induced alternative stable soil moisture states

    Science.gov (United States)

    Robinson, David; Jones, Scott; Lebron, Inma; Reinsch, Sabine; Dominguez, Maria; Smith, Andrew; Marshal, Miles; Emmett, Bridget

    2017-04-01

    The theory of alternative stable states in ecosystems is well established in ecology; however, evidence from manipulation experiments supporting the theory is limited. Developing the evidence base is important because it has profound implications for ecosystem management. Here we show evidence of the existence of alternative stable soil moisture states induced by drought in an upland wet heath. We used a long-term (15 yrs) climate change manipulation experiment with moderate sustained drought, which reduced the ability of the soil to retain soil moisture by degrading the soil structure, reducing moisture retention. Moreover, natural intense droughts superimposed themselves on the experiment, causing an unexpected additional alternative soil moisture state to develop, both for the drought manipulation and control plots; this impaired the soil from rewetting in winter. Our results show the coexistence of three stable states. Using modelling with the Hydrus 1D software package we are able to show the circumstances under which shifts in soil moisture states are likely to occur. Given the new understanding it presents a challenge of how to incorporate feedbacks, particularly related to soil structure, into soil flow and transport models?

  17. Numerical and experimental determination of surface temperature and moisture evolution in a field soil

    Science.gov (United States)

    Akinyemi, Olukayode D.; Mendes, Nathan

    2007-03-01

    Knowledge about the dynamics of soil moisture and heat, especially at the surface, provides important insights into the physical processes governing their interactions with the atmosphere, thereby improving the understanding of patterns of climate dynamics. In this context the paper presents the numerical and field experimental results of temperature and moisture evolution, which were measured on the surface of a sandy soil at Abeokuta, south-western Nigeria. An unconditionally stable numerical method was used, which linearizes the vapour concentration driving-potential term giving the moisture exchanged at the boundaries in terms of temperature and moisture content, and simultaneously solves the governing equations for each time step. The model avoids stability problems and limitations to low moisture contents and the usual assumption of constant thermal conductivity. Instantaneous temperature measurements were made at the surface using a thermocouple, while the gravimetric method was employed to determine the volumetric water contents at some specific hours of the experimental period. The observed experimental data compared fairly well with the predicted values, with both having correlation coefficients greater than 0.9 and consequently following a common diurnal trend. The sensitivity of the model was very high to the choice of simulation parameters, especially grid size refinement and time step. While the model underestimated the soil moisture content at 6 a.m. and 10 p.m., the measured temperatures were however overestimated. When compared to moisture content, average errors for temperature were low resulting in a minimal absolute difference in amplitude of 0.81 °C.

  18. Plasticity and density-moisture-resistance relations of soils amended with fly ash

    Energy Technology Data Exchange (ETDEWEB)

    Mapfuno, E.; Chanasyk, D.S. [University of Alberta, Edmonton, AB (Canada). Dept. of Renewable Resources

    1998-06-01

    The objective of this study was to investigate the impact of fly ash amendments on the plasticity, water retention and penetration resistance-density-moisture relationships of three soils of sandy loam, loam and clay loam textures in order to determine the potential compaction of these soil/fly ash mixtures if they were worked at different moisture ranges. For all three soils the addition of fly ash decreased the plasticity index, but slightly increased the Proctor maximum density. This implies that fly ash amendments reduce the range of moisture within which soils are most susceptible to compaction. However, for the sandy loam and loam textured soils amended with fly ash, cultivation must be avoided at moisture contents close to field capacity since maximum densification occurs at these moisture contents. In all three soils the addition of fly ash increased water retention, especially in the sandy loam. Fly ash amendments increased penetration resistance of the clay loam, but increased penetration resistance of the sandy loam.

  19. Compact polarimetric synthetic aperture radar for monitoring soil moisture condition

    Science.gov (United States)

    Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.

    2017-12-01

    Coarse resolution soil moisture maps are currently operationally delivered by ESA's SMOS and NASA's SMAP passive microwaves sensors. Despite this evolution, operational soil moisture monitoring at the field scale remains challenging. A number of factors contribute to this challenge including the complexity of the retrieval that requires advanced SAR systems with enhanced temporal revisit capabilities. Since the launch of RADARSAT-2 in 2007, Agriculture and Agri-Food Canada (AAFC) has been evaluating the accuracy of these data for estimating surface soil moisture. Thus, a hybrid (multi-angle/multi-polarization) retrieval approach was found well suited for the planned RADARSAT Constellation Mission (RCM) considering the more frequent relook expected with the three satellite configuration. The purpose of this study is to evaluate the capability of C-band CP data to estimate soil moisture over agricultural fields, in anticipation of the launch of RCM. In this research we introduce a new CP approach based on the IEM and simulated RCM CP mode intensities from RADARSAT-2 images acquired at different dates. The accuracy of soil moisture retrieval from the proposed multi-polarization and hybrid methods will be contrasted with that from a more conventional quad-pol approach, and validated against in situ measurements by pooling data collected over AAFC test sites in Ontario, Manitoba and Saskatchewan, Canada.

  20. Negative soil moisture-precipitation feedback in dry and wet regions.

    Science.gov (United States)

    Yang, Lingbin; Sun, Guoqing; Zhi, Lu; Zhao, Jianjun

    2018-03-05

    Soil moisture-precipitation (SM-P) feedback significantly influences the terrestrial water and energy cycles. However, the sign of the feedback and the associated physical mechanism have been debated, leaving a research gap regarding global water and climate changes. Based on Koster's framework, we estimate SM-P feedback using satellite remote sensing and ground observation data sets. Methodologically, the sign of the feedback is identified by the correlation between monthly soil moisture and next-month precipitation. The physical mechanism is investigated through coupling precipitation and soil moisture (P-SM), soil moisture ad evapotranspiration (SM-E) and evapotranspiration and precipitation (E-P) correlations. Our results demonstrate that although positive SM-P feedback is predominant over land, non-negligible negative feedback occurs in dry and wet regions. Specifically, 43.75% and 40.16% of the negative feedback occurs in the arid and humid climate zones. Physically, negative SM-P feedback depends on the SM-E correlation. In dry regions, evapotranspiration change is soil moisture limited. In wet regions, evapotranspiration change is energy limited. We conclude that the complex SM-E correlation results in negative SM-P feedback in dry and wet regions, and the cause varies based on the environmental and climatic conditions.

  1. Evaluation of SMOS soil moisture products over the CanEx-SM10 area

    Science.gov (United States)

    The Soil Moisture and Ocean Salinity (SMOS) Earth observation satellite was launched in November 2009 to provide global soil moisture and ocean salinity measurements based on L-Band passive microwave measurements. Since its launch, different versions of SMOS soil moisture products processors have be...

  2. MAPPING SPATIAL MOISTURE CONTENT OF UNSATURATED AGRICULTURAL SOILS WITH GROUND-PENETRATING RADAR

    Directory of Open Access Journals (Sweden)

    O. Shamir

    2016-06-01

    Full Text Available Soil subsurface moisture content, especially in the root zone, is important for evaluation the influence of soil moisture to agricultural crops. Conservative monitoring by point-measurement methods is time-consuming and expensive. In this paper we represent an active remote-sensing tool for subsurface spatial imaging and analysis of electromagnetic physical properties, mostly water content, by ground-penetrating radar (GPR reflection. Combined with laboratory methods, this technique enables real-time and highly accurate evaluations of soils' physical qualities in the field. To calculate subsurface moisture content, a model based on the soil texture, porosity, saturation, organic matter and effective electrical conductivity is required. We developed an innovative method that make it possible measures spatial subsurface moisture content up to a depth of 1.5 m in agricultural soils and applied it to two different unsaturated soil types from agricultural fields in Israel: loess soil type (Calcic haploxeralf, common in rural areas of southern Israel with about 30% clay, 30% silt and 40% sand, and hamra soil type (Typic rhodoxeralf, common in rural areas of central Israel with about 10% clay, 5% silt and 85% sand. Combined field and laboratory measurements and model development gave efficient determinations of spatial moisture content in these fields. The environmentally friendly GPR system enabled non-destructive testing. The developed method for measuring moisture content in the laboratory enabled highly accurate interpretation and physical computing. Spatial soil moisture content to 1.5 m depth was determined with 1–5% accuracy, making our method useful for the design of irrigation plans for different interfaces.

  3. Soil Moisture Estimations Based on Airborne CAROLS L-Band Microwave Data

    Directory of Open Access Journals (Sweden)

    Arnaud Mialon

    2011-12-01

    Full Text Available The SMOS satellite mission, launched in 2009, allows global soil moisture estimations to be made using the L-band Microwave Emission of the Biosphere (L-MEB model, which simulates the L-band microwave emissions produced by the soil–vegetation layer. This model was calibrated using various sources of in situ and airborne data. In the present study, we propose to evaluate the L-MEB model on the basis of a large set of airborne data, recorded by the CAROLS radiometer during the course of 20 flights made over South West France (the SMOSMANIA site, and supported by simultaneous soil moisture measurements, made in 2009 and 2010. In terms of volumetric soil moisture, the retrieval accuracy achieved with the L-MEB model, with two default roughness parameters, ranges between 8% and 13%. Local calibrations of the roughness parameter, using data from the 2009 flights for different areas of the site, allowed an accuracy of approximately 5.3% to be achieved with the 2010 CAROLS data. Simultaneously we estimated the vegetation optical thickness (t and we showed that, when roughness is locally adjusted, MODIS NDVI values are correlated (R2 = 0.36 to t. Finally, as a consequence of the significant influence of the roughness parameter on the estimated absolute values of soil moisture, we propose to evaluate the relative variability of the soil moisture, using a default soil roughness parameter. The soil moisture variations are estimated with an uncertainty of approximately 6%.

  4. Error characterisation of global active and passive microwave soil moisture datasets

    Directory of Open Access Journals (Sweden)

    W. A. Dorigo

    2010-12-01

    Full Text Available Understanding the error structures of remotely sensed soil moisture observations is essential for correctly interpreting observed variations and trends in the data or assimilating them in hydrological or numerical weather prediction models. Nevertheless, a spatially coherent assessment of the quality of the various globally available datasets is often hampered by the limited availability over space and time of reliable in-situ measurements. As an alternative, this study explores the triple collocation error estimation technique for assessing the relative quality of several globally available soil moisture products from active (ASCAT and passive (AMSR-E and SSM/I microwave sensors. The triple collocation is a powerful statistical tool to estimate the root mean square error while simultaneously solving for systematic differences in the climatologies of a set of three linearly related data sources with independent error structures. Prerequisite for this technique is the availability of a sufficiently large number of timely corresponding observations. In addition to the active and passive satellite-based datasets, we used the ERA-Interim and GLDAS-NOAH reanalysis soil moisture datasets as a third, independent reference. The prime objective is to reveal trends in uncertainty related to different observation principles (passive versus active, the use of different frequencies (C-, X-, and Ku-band for passive microwave observations, and the choice of the independent reference dataset (ERA-Interim versus GLDAS-NOAH. The results suggest that the triple collocation method provides realistic error estimates. Observed spatial trends agree well with the existing theory and studies on the performance of different observation principles and frequencies with respect to land cover and vegetation density. In addition, if all theoretical prerequisites are fulfilled (e.g. a sufficiently large number of common observations is available and errors of the different

  5. The SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) Product

    Science.gov (United States)

    Reichle, Rolf; Crow, Wade; Koster, Randal; Kimball, John

    2010-01-01

    The Soil Moisture Active and Passive (SMAP) mission is being developed by NASA for launch in 2013 as one of four first-tier missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space in 2007. The primary science objectives of SMAP are to enhance understanding of land surface controls on the water, energy and carbon cycles, and to determine their linkages. Moreover, the high resolution soil moisture mapping provided by SMAP has practical applications in weather and seasonal climate prediction, agriculture, human health, drought and flood decision support. In this paper we describe the assimilation of SMAP observations for the generation of the planned SMAP Level 4 Surface and Root-zone Soil Moisture (L4_SM) product. The SMAP mission makes simultaneous active (radar) and passive (radiometer) measurements in the 1.26-1.43 GHz range (L-band) from a sun-synchronous low-earth orbit. Measurements will be obtained across a 1000 km wide swath using conical scanning at a constant incidence angle (40 deg). The radar resolution varies from 1-3 km over the outer 70% of the swath to about 30 km near the center of the swath. The radiometer resolution is 40 km across the entire swath. The radiometer measurements will allow high-accuracy but coarse resolution (40 km) measurements. The radar measurements will add significantly higher resolution information. The radar is however very sensitive to surface roughness and vegetation structure. The combination of the two measurements allows optimal blending of the advantages of each instrument. SMAP directly observes only surface soil moisture (in the top 5 cm of the soil column). Several of the key applications targeted by SMAP, however, require knowledge of root zone soil moisture (approximately top 1 m of the soil column), which is not directly measured by SMAP. The foremost objective of the SMAP L4_SM product is to fill this gap and provide estimates of root zone soil moisture

  6. An Operational In Situ Soil Moisture & Soil Temperature Monitoring Network for West Wales, UK: The WSMN Network.

    Science.gov (United States)

    Petropoulos, George P; McCalmont, Jon P

    2017-06-23

    This paper describes a soil moisture dataset that has been collecting ground measurements of soil moisture, soil temperature and related parameters for west Wales, United Kingdom. Already acquired in situ data have been archived to the autonomous Wales Soil Moisture Network (WSMN) since its foundation in July 2011. The sites from which measurements are being collected represent a range of conditions typical of the Welsh environment, with climate ranging from oceanic to temperate and a range of the most typical land use/cover types found in Wales. At present, WSMN consists of a total of nine monitoring sites across the area with a concentration of sites in three sub-areas around the region of Aberystwyth located in Mid-Wales. The dataset of composed of 0-5 (or 0-10) cm soil moisture, soil temperature, precipitation, and other ancillary data. WSMN data are provided openly to the public via the International Soil Moisture Network (ISMN) platform. At present, WSMN is also rapidly expanding thanks to funding obtained recently which allows more monitoring sites to be added to the network to the wider community interested in using its data.

  7. Evaluating soil moisture and hydraulic conductivity in semi-arid rangeland soils

    International Nuclear Information System (INIS)

    Whitaker, M.P.L.

    1993-01-01

    The US DOE's Office of Civilian Radioactive Waste Management (DOE-OCRWM) Fellowship Program supports various disciplines of academic research related to the isolation of radionuclides from the biosphere. The purpose of this paper is to provide an example of a university research application in the specific discipline of hydrology and water resources (a multi-disciplinary field encompassing engineering and the earth sciences), and to discuss how this research pertains to the objectives of the DOE-OCRWM Fellowship Program. The university research application is twofold: One portion focuses on the spatial variability of soil moisture (θ) and the other section compares point measurements with small watershed estimates of hydraulic conductivity (K) in a semi-arid rangeland soil in Arizona. For soil moisture measurements collected over a range of horizontal sampling intervals, no spatial correlation was evident. This outcome is reassuring to computer modelers who have assumed no spatial correlation for soil moisture over smaller scales. In regard to hydraulic conductivity, point measurements differed significantly from small watershed estimates of hydraulic conductivity which were derived from a calibrated and verified rainfall-runoff computer model. The estimates of saturated hydraulic conductivity (Ks) were obtained from previous computer simulations in which measured data was collected in the same research location as the present study

  8. Assessing the uncertainty of soil moisture impacts on convective precipitation using a new ensemble approach

    Directory of Open Access Journals (Sweden)

    O. Henneberg

    2018-05-01

    Full Text Available Soil moisture amount and distribution control evapotranspiration and thus impact the occurrence of convective precipitation. Many recent model studies demonstrate that changes in initial soil moisture content result in modified convective precipitation. However, to quantify the resulting precipitation changes, the chaotic behavior of the atmospheric system needs to be considered. Slight changes in the simulation setup, such as the chosen model domain, also result in modifications to the simulated precipitation field. This causes an uncertainty due to stochastic variability, which can be large compared to effects caused by soil moisture variations. By shifting the model domain, we estimate the uncertainty of the model results. Our novel uncertainty estimate includes 10 simulations with shifted model boundaries and is compared to the effects on precipitation caused by variations in soil moisture amount and local distribution. With this approach, the influence of soil moisture amount and distribution on convective precipitation is quantified. Deviations in simulated precipitation can only be attributed to soil moisture impacts if the systematic effects of soil moisture modifications are larger than the inherent simulation uncertainty at the convection-resolving scale.We performed seven experiments with modified soil moisture amount or distribution to address the effect of soil moisture on precipitation. Each of the experiments consists of 10 ensemble members using the deep convection-resolving COSMO model with a grid spacing of 2.8 km. Only in experiments with very strong modification in soil moisture do precipitation changes exceed the model spread in amplitude, location or structure. These changes are caused by a 50 % soil moisture increase in either the whole or part of the model domain or by drying the whole model domain. Increasing or decreasing soil moisture both predominantly results in reduced precipitation rates. Replacing the soil

  9. Impact of soil moisture initialization on boreal summer subseasonal forecasts: mid-latitude surface air temperature and heat wave events

    Science.gov (United States)

    Seo, Eunkyo; Lee, Myong-In; Jeong, Jee-Hoon; Koster, Randal D.; Schubert, Siegfried D.; Kim, Hye-Mi; Kim, Daehyun; Kang, Hyun-Suk; Kim, Hyun-Kyung; MacLachlan, Craig; Scaife, Adam A.

    2018-05-01

    This study uses a global land-atmosphere coupled model, the land-atmosphere component of the Global Seasonal Forecast System version 5, to quantify the degree to which soil moisture initialization could potentially enhance boreal summer surface air temperature forecast skill. Two sets of hindcast experiments are performed by prescribing the observed sea surface temperature as the boundary condition for a 15-year period (1996-2010). In one set of the hindcast experiments (noINIT), the initial soil moisture conditions are randomly taken from a long-term simulation. In the other set (INIT), the initial soil moisture conditions are taken from an observation-driven offline Land Surface Model (LSM) simulation. The soil moisture conditions from the offline LSM simulation are calibrated using the forecast model statistics to minimize the inconsistency between the LSM and the land-atmosphere coupled model in their mean and variability. Results show a higher boreal summer surface air temperature prediction skill in INIT than in noINIT, demonstrating the potential benefit from an accurate soil moisture initialization. The forecast skill enhancement appears especially in the areas in which the evaporative fraction—the ratio of surface latent heat flux to net surface incoming radiation—is sensitive to soil moisture amount. These areas lie in the transitional regime between humid and arid climates. Examination of the extreme 2003 European and 2010 Russian heat wave events reveal that the regionally anomalous soil moisture conditions during the events played an important role in maintaining the stationary circulation anomalies, especially those near the surface.

  10. Inter-Annual Variability of Soil Moisture Stress Function in the Wheat Field

    Science.gov (United States)

    Akuraju, V. R.; Ryu, D.; George, B.; Ryu, Y.; Dassanayake, K. B.

    2014-12-01

    Root-zone soil moisture content is a key variable that controls the exchange of water and energy fluxes between land and atmosphere. In the soil-vegetation-atmosphere transfer (SVAT) schemes, the influence of root-zone soil moisture on evapotranspiration (ET) is parameterized by the soil moisture stress function (SSF). Dependence of actual ET: potential ET (fPET) or evaporative fraction to the root-zone soil moisture via SSF can also be used inversely to estimate root-zone soil moisture when fPET is estimated by remotely sensed land surface states. In this work we present fPET versus available soil water (ASW) in the root zone observed in the experimental farm sites in Victoria, Australia in 2012-2013. In the wheat field site, fPET vs ASW exhibited distinct features for different soil depth, net radiation, and crop growth stages. Interestingly, SSF in the wheat field presented contrasting shapes for two cropping years of 2012 and 2013. We argue that different temporal patterns of rainfall (and resulting soil moisture) during the growing seasons in 2012 and 2013 are responsible for the distinctive SSFs. SSF of the wheat field was simulated by the Agricultural Production Systems sIMulator (APSIM). The APSIM was able to reproduce the observed fPET vs. ASW. We discuss implications of our findings for existing modeling and (inverse) remote sensing approaches relying on SSF and alternative growth-stage-dependent SSFs.

  11. Automated general temperature correction method for dielectric soil moisture sensors

    Science.gov (United States)

    Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao

    2017-08-01

    An effective temperature correction method for dielectric sensors is important to ensure the accuracy of soil water content (SWC) measurements of local to regional-scale soil moisture monitoring networks. These networks are extensively using highly temperature sensitive dielectric sensors due to their low cost, ease of use and less power consumption. Yet there is no general temperature correction method for dielectric sensors, instead sensor or site dependent correction algorithms are employed. Such methods become ineffective at soil moisture monitoring networks with different sensor setups and those that cover diverse climatic conditions and soil types. This study attempted to develop a general temperature correction method for dielectric sensors which can be commonly used regardless of the differences in sensor type, climatic conditions and soil type without rainfall data. In this work an automated general temperature correction method was developed by adopting previously developed temperature correction algorithms using time domain reflectometry (TDR) measurements to ThetaProbe ML2X, Stevens Hydra probe II and Decagon Devices EC-TM sensor measurements. The rainy day effects removal procedure from SWC data was automated by incorporating a statistical inference technique with temperature correction algorithms. The temperature correction method was evaluated using 34 stations from the International Soil Moisture Monitoring Network and another nine stations from a local soil moisture monitoring network in Mongolia. Soil moisture monitoring networks used in this study cover four major climates and six major soil types. Results indicated that the automated temperature correction algorithms developed in this study can eliminate temperature effects from dielectric sensor measurements successfully even without on-site rainfall data. Furthermore, it has been found that actual daily average of SWC has been changed due to temperature effects of dielectric sensors with a

  12. The Soil Moisture Active Passive (SMAP) Applications Activity

    Science.gov (United States)

    Brown, Molly E.; Moran, Susan; Escobar, Vanessa; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni

    2011-01-01

    The Soil Moisture Active Passive (SMAP) mission is one of the first-tier satellite missions recommended by the U.S. National Research Council Committee on Earth Science and Applications from Space. The SMAP mission 1 is under development by NASA and is scheduled for launch late in 2014. The SMAP measurements will allow global and high-resolution mapping of soil moisture and its freeze/thaw state at resolutions from 3-40 km. These measurements will have high value for a wide range of environmental applications that underpin many weather-related decisions including drought and flood guidance, agricultural productivity estimation, weather forecasting, climate predictions, and human health risk. In 2007, NASA was tasked by The National Academies to ensure that emerging scientific knowledge is actively applied to obtain societal benefits by broadening community participation and improving means for use of information. SMAP is one of the first missions to come out of this new charge, and its Applications Plan forms the basis for ensuring its commitment to its users. The purpose of this paper is to outline the methods and approaches of the SMAP applications activity, which is designed to increase and sustain the interaction between users and scientists involved in mission development.

  13. Downscaling soil moisture over East Asia through multi-sensor data fusion and optimization of regression trees

    Science.gov (United States)

    Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung

    2017-04-01

    Soil moisture is one of the most important keys for understanding regional and global climate systems. Soil moisture is directly related to agricultural processes as well as hydrological processes because soil moisture highly influences vegetation growth and determines water supply in the agroecosystem. Accurate monitoring of the spatiotemporal pattern of soil moisture is important. Soil moisture has been generally provided through in situ measurements at stations. Although field survey from in situ measurements provides accurate soil moisture with high temporal resolution, it requires high cost and does not provide the spatial distribution of soil moisture over large areas. Microwave satellite (e.g., advanced Microwave Scanning Radiometer on the Earth Observing System (AMSR2), the Advanced Scatterometer (ASCAT), and Soil Moisture Active Passive (SMAP)) -based approaches and numerical models such as Global Land Data Assimilation System (GLDAS) and Modern- Era Retrospective Analysis for Research and Applications (MERRA) provide spatial-temporalspatiotemporally continuous soil moisture products at global scale. However, since those global soil moisture products have coarse spatial resolution ( 25-40 km), their applications for agriculture and water resources at local and regional scales are very limited. Thus, soil moisture downscaling is needed to overcome the limitation of the spatial resolution of soil moisture products. In this study, GLDAS soil moisture data were downscaled up to 1 km spatial resolution through the integration of AMSR2 and ASCAT soil moisture data, Shuttle Radar Topography Mission (SRTM) Digital Elevation Model (DEM), and Moderate Resolution Imaging Spectroradiometer (MODIS) data—Land Surface Temperature, Normalized Difference Vegetation Index, and Land cover—using modified regression trees over East Asia from 2013 to 2015. Modified regression trees were implemented using Cubist, a commercial software tool based on machine learning. An

  14. Assessing artificial neural networks and statistical methods for infilling missing soil moisture records

    Science.gov (United States)

    Dumedah, Gift; Walker, Jeffrey P.; Chik, Li

    2014-07-01

    Soil moisture information is critically important for water management operations including flood forecasting, drought monitoring, and groundwater recharge estimation. While an accurate and continuous record of soil moisture is required for these applications, the available soil moisture data, in practice, is typically fraught with missing values. There are a wide range of methods available to infilling hydrologic variables, but a thorough inter-comparison between statistical methods and artificial neural networks has not been made. This study examines 5 statistical methods including monthly averages, weighted Pearson correlation coefficient, a method based on temporal stability of soil moisture, and a weighted merging of the three methods, together with a method based on the concept of rough sets. Additionally, 9 artificial neural networks are examined, broadly categorized into feedforward, dynamic, and radial basis networks. These 14 infilling methods were used to estimate missing soil moisture records and subsequently validated against known values for 13 soil moisture monitoring stations for three different soil layer depths in the Yanco region in southeast Australia. The evaluation results show that the top three highest performing methods are the nonlinear autoregressive neural network, rough sets method, and monthly replacement. A high estimation accuracy (root mean square error (RMSE) of about 0.03 m/m) was found in the nonlinear autoregressive network, due to its regression based dynamic network which allows feedback connections through discrete-time estimation. An equally high accuracy (0.05 m/m RMSE) in the rough sets procedure illustrates the important role of temporal persistence of soil moisture, with the capability to account for different soil moisture conditions.

  15. A comparison of soil-moisture loss from forested and clearcut areas in West Virginia

    Science.gov (United States)

    Charles A. Troendle

    1970-01-01

    Soil-moisture losses from forested and clearcut areas were compared on the Fernow Experimental Forest. As expected, hardwood forest soils lost most moisture while revegetated clearcuttings, clearcuttings, and barren areas lost less, in that order. Soil-moisture losses from forested soils also correlated well with evapotranspiration and streamflow.

  16. APPRAISAL OF THE SNAP MODEL FOR PREDICTING NITROGEN MINERALIZATION IN TROPICAL SOILS UNDER EUCALYPTUS

    Directory of Open Access Journals (Sweden)

    Philip James Smethurst

    2015-04-01

    Full Text Available The Soil Nitrogen Availability Predictor (SNAP model predicts daily and annual rates of net N mineralization (NNM based on daily weather measurements, daily predictions of soil water and soil temperature, and on temperature and moisture modifiers obtained during aerobic incubation (basal rate. The model was based on in situ measurements of NNM in Australian soils under temperate climate. The purpose of this study was to assess this model for use in tropical soils under eucalyptus plantations in São Paulo State, Brazil. Based on field incubations for one month in three, NNM rates were measured at 11 sites (0-20 cm layer for 21 months. The basal rate was determined in in situ incubations during moist and warm periods (January to March. Annual rates of 150-350 kg ha-1 yr-1 NNM predicted by the SNAP model were reasonably accurate (R2 = 0.84. In other periods, at lower moisture and temperature, NNM rates were overestimated. Therefore, if used carefully, the model can provide adequate predictions of annual NNM and may be useful in practical applications. For NNM predictions for shorter periods than a year or under suboptimal incubation conditions, the temperature and moisture modifiers need to be recalibrated for tropical conditions.

  17. Soil moisture and temperature profile effects on microwave emission at low frequencies

    International Nuclear Information System (INIS)

    Raju, S.; Chanzy, A.; Wigneron, J.P.; Calvet, J.C.; Kerr, Y.; Laguerre, L.

    1995-01-01

    Soil moisture and temperature vertical profiles vary quickly during the day and may have a significant influence on the soil microwave emission. The objective of this work is to quantify such an influence and the consequences in soil moisture estimation from microwave radiometric information. The analysis is based on experimental data collected by the ground-based PORTOS radiometer at 1.4, 5.05, and 10.65 GHz and data simulated by a coherent model of microwave emission from layered media [Wilheit model (1978)]. In order to simulate diurnal variations of the brightness temperature (TB), the Wilheit model is coupled to a mechanistic model of heat and water flows in the soil. The Wilheit model is validated on experimental data and its performances for estimating TB are compared to those of a simpler approach based on a description of the soil media as a single layer (Fresnel model). When the depth of this single layer (hereafter referred to as the sampling depth) is determined to fit the experimental data, similar accuracy in TB estimation is found with both the Wilheit and Fresnel models. The soil microwave emission is found to be strongly affected by the diurnal variations of soil moisture and temperature profiles. Consequently, the TB sensitivity to soil moisture and temperature profiles has an influence on the estimation, from microwave observations, of the surface soil moisture in a surface layer with a fixed depth (05): the accuracy of θs retrievals and the optimal sampling depth depends both on the variation in soil moisture and temperature profile shape. (author)

  18. Event-scale soil moisture dynamics in open evergreen woodlands of southwest Spain

    Science.gov (United States)

    Lozano-Parra, F. J.; Schnabel, S.; Gómez-Gutiérrez, Á.

    2012-04-01

    Rangelands with a disperse tree cover occupy large areas in the southwestern part of the Iberian Pensinsula and are also found in other parts of the Mediterranean. In these grazed, savannah-like ecosystems water constitutes an important limiting factor for vegetation growth because of the strong summer dry period, being annual potential evapotranspiration nearly twice the annual rainfall amount. Previous studies by other authors have found lower values of soil water content below the tree canopy as compared to the open spaces, covered only by herbaceous vegetation. The differences of soil moisture between tree covered and open areas vary along the year, commonly being highest during autumn, low when water content is close to saturation and the inverse during summer. Our studies indicate that the spatial variation of soil moisture is more complex. The main objective of this study is to analyze soil moisture dynamics at the event scale below tree canopies (Quercus ilex) and in the open spaces. Because soils are commonly very shallow (Cambisols) and a high concentration of grass roots is found in the upper five centimetres, soil moisture measurements were carried out at 5, 10, 15 and 30 cm depth. The study area is located in Extremadura. Soil moisture is measured continuously with a time resolution of 30 minutes using capacitive sensors and rainfall is registered in 5-minute intervals. Data from the hydrological year 2010-11 are presented here. The main factors which produced variations in soil moisture in the upper 5 cm were amount and duration of the rainfall event. Rainfall intensity was also significantly related with an increase of the water content. At greater depth (30 cm) soil moisture was more related with antecedent rainfall, as for example the amount of precipitation registered 30 and 45 days prior to the event. Maximum increases produced by a rainstorm were approximately 0.20 m3m-3 in grasslands and 0.17 m3m-3 below tree canopy. However, in the uppermost

  19. Horizontal and vertical variability of soil moisture in savanna ecosystems

    Science.gov (United States)

    Caylor, K.; D'Odorico, P.; Rodriguez-Iturbe, I.

    2004-12-01

    Soil moisture is a key hydrological variable that mediates the interactions between climate, soil, and vegetation dynamics in water-limited ecosystems. Because of the importance of water limitation in savannas, a number of theoretical models of tree-grass coexistence have been developed which differ in their underlying assumptions about the ways in which trees and grasses access and use soil moisture. However, clarification of the mechanisms that allow savanna vegetation to persist as a mixture of grasses and trees remains a vexing problem in both hydrological and vegetation science. A particular challenge is the fact that the spatial pattern of vegetation is both a cause and effect of variation in water availability in semiarid ecosystems. At landscape to regional scales, climatic and geologic constraints on soil moisture availability are primary determinants of vegetation structural pattern. However, at local to landscape scales the patchy vegetation structural mosaic serves to redistribute the availability of soil moisture in ways that have important consequences for structural dynamics and community composition. In this regard, the emerging field of ecohydrology is well suited to investigate questions concerning couplings between the patchy structural mosaic of savanna vegetation and the kinds self-organizing dynamics known to exist in other light and nutrient-limited vegetation systems. Here we address the role of patchy vegetation structure through the use of a lumped model of soil moisture dynamics that accounts for the effect of tree canopy on the lateral and vertical distribution of soil moisture. The model includes mechanisms for the drying of the ground surface due to soil evaporation in the sites with no tree cover, and for the lateral water uptake due to root invading areas with no canopy cover located in the proximity of trees. The model, when applied to a series of sites along a rainfall gradient in southern Africa, is able to explain the cover

  20. Hydropedological parameters limiting soil moisture regime floodplain ecosystems of south Moravia

    Directory of Open Access Journals (Sweden)

    Ladislav Kubík

    2005-01-01

    Full Text Available Soil moisture regime of floodplain ecosystems in southern Moravia is considerably influenced and greatly changed by human activities. It can be changed negatively by water management engineering or positively by landscape revitalizations. The paper deals with problems of hydropedological characteristics (hydrolimits limiting soil moisture regime and solves effect of hydrological factors on soil moisture regime in the floodplain ecosystems. Attention is paid especially to water retention curves and to hydrolimits – wilting point and field capacity. They can be acquired either directly by slow laboratory assessment, derivation from the water retention curves or indirectly by calculation using pedotransfer functions (PTF. This indirect assessment uses hydrolimit dependency on better available soil physical parameters namely soil granularity, bulk density and humus content. The aim is to calculate PTF for wilting point and field capacity and to compare them with measured values. The paper documents suitableness utilization of PTF for the region of interest. The results of correlation and regression analysis for soil moisture and groundwater table are furthermore presented.

  1. Parameter estimation of a two-horizon soil profile by combining crop canopy and surface soil moisture observations using GLUE

    Science.gov (United States)

    Sreelash, K.; Sekhar, M.; Ruiz, L.; Tomer, S. K.; Guérif, M.; Buis, S.; Durand, P.; Gascuel-Odoux, C.

    2012-08-01

    SummaryEstimation of soil parameters by inverse modeling using observations on either surface soil moisture or crop variables has been successfully attempted in many studies, but difficulties to estimate root zone properties arise when heterogeneous layered soils are considered. The objective of this study was to explore the potential of combining observations on surface soil moisture and crop variables - leaf area index (LAI) and above-ground biomass for estimating soil parameters (water holding capacity and soil depth) in a two-layered soil system using inversion of the crop model STICS. This was performed using GLUE method on a synthetic data set on varying soil types and on a data set from a field experiment carried out in two maize plots in South India. The main results were (i) combination of surface soil moisture and above-ground biomass provided consistently good estimates with small uncertainity of soil properties for the two soil layers, for a wide range of soil paramater values, both in the synthetic and the field experiment, (ii) above-ground biomass was found to give relatively better estimates and lower uncertainty than LAI when combined with surface soil moisture, especially for estimation of soil depth, (iii) surface soil moisture data, either alone or combined with crop variables, provided a very good estimate of the water holding capacity of the upper soil layer with very small uncertainty whereas using the surface soil moisture alone gave very poor estimates of the soil properties of the deeper layer, and (iv) using crop variables alone (else above-ground biomass or LAI) provided reasonable estimates of the deeper layer properties depending on the soil type but provided poor estimates of the first layer properties. The robustness of combining observations of the surface soil moisture and the above-ground biomass for estimating two layer soil properties, which was demonstrated using both synthetic and field experiments in this study, needs now to

  2. NASAs Soil Moisture Active Passive (SMAP) Mission and Opportunities For Applications Users

    Science.gov (United States)

    Brown, Molly E.; Escobar, Vanessa; Moran, Susan; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni G.; Doorn, Brad; Entin, Jared K.

    2013-01-01

    Water in the soil, both its amount (soil moisture) and its state (freeze/thaw), plays a key role in water and energy cycles, in weather and climate, and in the carbon cycle. Additionally, soil moisture touches upon human lives in a number of ways from the ravages of flooding to the needs for monitoring agricultural and hydrologic droughts. Because of their relevance to weather, climate, science, and society, accurate and timely measurements of soil moisture and freeze/thaw state with global coverage are critically important.

  3. Use of modeled and satelite soil moisture to estimate soil erosion in central and southern Italy.

    Science.gov (United States)

    Termite, Loris Francesco; Massari, Christian; Todisco, Francesca; Brocca, Luca; Ferro, Vito; Bagarello, Vincenzo; Pampalone, Vincenzo; Wagner, Wolfgang

    2016-04-01

    This study presents an accurate comparison between two different approaches aimed to enhance accuracy of the Universal Soil Loss Equation (USLE) in estimating the soil loss at the single event time scale. Indeed it is well known that including the observed event runoff in the USLE improves its soil loss estimation ability at the event scale. In particular, the USLE-M and USLE-MM models use the observed runoff coefficient to correct the rainfall erosivity factor. In the first case, the soil loss is linearly dependent on rainfall erosivity, in the second case soil loss and erosivity are related by a power law. However, the measurement of the event runoff is not straightforward or, in some cases, possible. For this reason, the first approach used in this study is the use of Soil Moisture For Erosion (SM4E), a recent USLE-derived model in which the event runoff is replaced by the antecedent soil moisture. Three kinds of soil moisture datasets have been separately used: the ERA-Interim/Land reanalysis data of the European Centre for Medium-range Weather Forecasts (ECMWF); satellite retrievals from the European Space Agency - Climate Change Initiative (ESA-CCI); modeled data using a Soil Water Balance Model (SWBM). The second approach is the use of an estimated runoff rather than the observed. Specifically, the Simplified Continuous Rainfall-Runoff Model (SCRRM) is used to derive the runoff estimates. SCRMM requires soil moisture data as input and at this aim the same three soil moisture datasets used for the SM4E have been separately used. All the examined models have been calibrated and tested at the plot scale, using data from the experimental stations for the monitoring of the erosive processes "Masse" (Central Italy) and "Sparacia" (Southern Italy). Climatic data and runoff and soil loss measures at the event time scale are available for the period 2008-2013 at Masse and for the period 2002-2013 at Sparacia. The results show that both the approaches can provide

  4. Multifractal and Singularity Maps of soil surface moisture distribution derived from 2D image analysis.

    Science.gov (United States)

    Cumbrera, Ramiro; Millán, Humberto; Martín-Sotoca, Juan Jose; Pérez Soto, Luis; Sanchez, Maria Elena; Tarquis, Ana Maria

    2016-04-01

    methods for mapping geochemical anomalies caused by buried sources and for predicting undiscovered mineral deposits in covered areas. Journal of Geochemical Exploration, 122, 55-70. Cumbrera, R., Ana M. Tarquis, Gabriel Gascó, Humberto Millán (2012) Fractal scaling of apparent soil moisture estimated from vertical planes of Vertisol pit images. Journal of Hydrology (452-453), 205-212. Martin Sotoca; J.J. Antonio Saa-Requejo, Juan Grau and Ana M. Tarquis (2016). Segmentation of singularity maps in the context of soil porosity. Geophysical Research Abstracts, 18, EGU2016-11402. Millán, H., Cumbrera, R. and Ana M. Tarquis (2016) Multifractal and Levy-stable statistics of soil surface moisture distribution derived from 2D image analysis. Applied Mathematical Modelling, 40(3), 2384-2395.

  5. Radon emanation and soil moisture effects on airborne gamma-ray measurements

    International Nuclear Information System (INIS)

    Grasty, R.L.

    1997-01-01

    A theoretical model is developed to explain variations in airborne gamma-ray measurements over a calibration range near Ottawa, Ontario. The gamma-ray flux from potassium and the thorium decay series showed an expected decrease with increasing soil moisture. However, the gamma-ray flux from the uranium decay series was highest in the spring when the ground was water-saturated and even covered with snow. These results are explained through the build-up of radon and its associated gamma-ray-emitting decay products in the clay soil of the calibration range with increasing soil moisture. Similar results were found from airborne measurements over other clay soils. However, measurements over sandy soils showed that the count rates from all three radio elements increased with decreasing soil moisture. This difference between soil types was attributed to the lower radon emanation of the more coarse-grained sandy soils compared to finer-grained clay soils. The theoretical and experimental results demonstrate that any estimate of the natural gamma-ray field caused by radium in the ground must take into consideration the radon emanation coefficient of the soil. The radon diffusion coefficient of the soil must also be considered since it depends strongly on soil moisture. This has significant implications for the assessment of outdoor radiation doses using laboratory analyses of soil samples and the use of ground and airborne gamma-ray measurements for radon potential mapping

  6. Variability of soil moisture and its relationship with surface albedo

    Indian Academy of Sciences (India)

    Continuous observation data collected over the year 2008 at Astronomical Observatory, Thiruvananthapuram in south Kerala (76° 59′E longitude and 8° 30′N latitude) are used to study the diurnal, monthly and seasonal soil moisture variations. The effect of rainfall on diurnal and seasonal soil moisture is discussed.

  7. Empirical Soil Moisture Estimation with Spaceborne L-band Polarimetric Radars: Aquarius, SMAP, and PALSAR-2

    Science.gov (United States)

    Burgin, M. S.; van Zyl, J. J.

    2017-12-01

    Traditionally, substantial ancillary data is needed to parametrize complex electromagnetic models to estimate soil moisture from polarimetric radar data. The Soil Moisture Active Passive (SMAP) baseline radar soil moisture retrieval algorithm uses a data cube approach, where a cube of radar backscatter values is calculated using sophisticated models. In this work, we utilize the empirical approach by Kim and van Zyl (2009) which is an optional SMAP radar soil moisture retrieval algorithm; it expresses radar backscatter of a vegetated scene as a linear function of soil moisture, hence eliminating the need for ancillary data. We use 2.5 years of L-band Aquarius radar and radiometer derived soil moisture data to determine two coefficients of a linear model function on a global scale. These coefficients are used to estimate soil moisture with 2.5 months of L-band SMAP and L-band PALSAR-2 data. The estimated soil moisture is compared with the SMAP Level 2 radiometer-only soil moisture product; the global unbiased RMSE of the SMAP derived soil moisture corresponds to 0.06-0.07 cm3/cm3. In this study, we leverage the three diverse L-band radar data sets to investigate the impact of pixel size and pixel heterogeneity on soil moisture estimation performance. Pixel sizes range from 100 km for Aquarius, over 3, 9, 36 km for SMAP, to 10m for PALSAR-2. Furthermore, we observe seasonal variation in the radar sensitivity to soil moisture which allows the identification and quantification of seasonally changing vegetation. Utilizing this information, we further improve the estimation performance. The research described in this paper is supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. Copyright 2017. All rights reserved.

  8. Preliminary Evaluation of the SMAP Radiometer Soil Moisture Product over China Using In Situ Data

    Directory of Open Access Journals (Sweden)

    Yayong Sun

    2017-03-01

    Full Text Available The Soil Moisture Active Passive (SMAP satellite makes coincident global measurements of soil moisture using an L-band radar instrument and an L-band radiometer. It is crucial to evaluate the errors in the newest L-band SMAP satellite-derived soil moisture products, before they are routinely used in scientific research and applications. This study represents the first evaluation of the SMAP radiometer soil moisture product over China. In this paper, a preliminary evaluation was performed using sparse in situ measurements from 655 China Meteorological Administration (CMA monitoring stations between 1 April 2015 and 31 August 2016. The SMAP radiometer-derived soil moisture product was evaluated against two schemes of original soil moisture and the soil moisture anomaly in different geographical zones and land cover types. Four performance metrics, i.e., bias, root mean square error (RMSE, unbiased root mean square error (ubRMSE, and the correlation coefficient (R, were used in the accuracy evaluation. The results indicated that the SMAP radiometer-derived soil moisture product agreed relatively well with the in situ measurements, with ubRMSE values of 0.058 cm3·cm−3 and 0.039 cm3·cm−3 based on original data and anomaly data, respectively. The values of the SMAP radiometer-based soil moisture product were overestimated in wet areas, especially in the Southwest China, South China, Southeast China, East China, and Central China zones. The accuracies over croplands and in Northeast China were the worst. Soil moisture, surface roughness, and vegetation are crucial factors contributing to the error in the soil moisture product. Moreover, radio frequency interference contributes to the overestimation over the northern portion of the East China zone. This study provides guidelines for the application of the SMAP-derived soil moisture product in China and acts as a reference for improving the retrieval algorithm.

  9. Quantifying the effects of soil temperature, moisture and sterilization on elemental mercury formation in boreal soils.

    Science.gov (United States)

    Pannu, Ravinder; Siciliano, Steven D; O'Driscoll, Nelson J

    2014-10-01

    Soils are a source of elemental mercury (Hg(0)) to the atmosphere, however the effects of soil temperature and moisture on Hg(0) formation is not well defined. This research quantifies the effect of varying soil temperature (278-303 K), moisture (15-80% water filled pore space (WFPS)) and sterilization on the kinetics of Hg(0) formation in forested soils of Nova Scotia, Canada. Both, the logarithm of cumulative mass of Hg(0) formed in soils and the reduction rate constants (k values) increased with temperature and moisture respectively. Sterilizing soils significantly (p soils and our results highlight two key processes: (i) a fast abiotic process that peaks at 45% WFPS and depletes a small pool of Hg(0) and; (ii) a slower, rate limiting biotic process that generates a large pool of reducible Hg(II). Copyright © 2014 Elsevier Ltd. All rights reserved.

  10. NASA Giovanni: A Tool for Visualizing, Analyzing, and Inter-comparing Soil Moisture Data

    Science.gov (United States)

    Teng, William; Rui, Hualan; Vollmer, Bruce; deJeu, Richard; Fang, Fan; Lei, Guang-Dih; Parinussa, Robert

    2014-01-01

    There are many existing satellite soil moisture algorithms and their derived data products, but there is no simple way for a user to inter-compare the products or analyze them together with other related data. An environment that facilitates such inter-comparison and analysis would be useful for validation of satellite soil moisture retrievals against in situ data and for determining the relationships between different soil moisture products. As part of the NASA Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) family of portals, which has provided users worldwide with a simple but powerful way to explore NASA data, a beta prototype Giovanni Inter-comparison of Soil Moisture Products portal has been developed. A number of soil moisture data products are currently included in the prototype portal. More will be added, based on user requirements and feedback and as resources become available. Two application examples for the portal are provided. The NASA Giovanni Soil Moisture portal is versatile and extensible, with many possible uses, for research and applications, as well as for the education community.

  11. Use of visible, near-infrared, and thermal infrared remote sensing to study soil moisture

    Science.gov (United States)

    Blanchard, M. B.; Greeley, R.; Goettelman, R.

    1974-01-01

    Two methods are described which are used to estimate soil moisture remotely using the 0.4- to 14.0 micron wavelength region: (1) measurement of spectral reflectance, and (2) measurement of soil temperature. The reflectance method is based on observations which show that directional reflectance decreases as soil moisture increases for a given material. The soil temperature method is based on observations which show that differences between daytime and nighttime soil temperatures decrease as moisture content increases for a given material. In some circumstances, separate reflectance or temperature measurements yield ambiguous data, in which case these two methods may be combined to obtain a valid soil moisture determination. In this combined approach, reflectance is used to estimate low moisture levels; and thermal inertia (or thermal diffusivity) is used to estimate higher levels. The reflectance method appears promising for surface estimates of soil moisture, whereas the temperature method appears promising for estimates of near-subsurface (0 to 10 cm).

  12. Soil Organic Matter Accumulation and Carbon Fractions along a Moisture Gradient of Forest Soils

    Directory of Open Access Journals (Sweden)

    Ewa Błońska

    2017-11-01

    Full Text Available The aim of the study was to present effects of soil properties, especially moisture, on the quantity and quality of soil organic matter. The investigation was performed in the Czarna Rózga Reserve in Central Poland. Forty circular test areas were located in a regular grid of points (100 × 300 m. Each plot was represented by one soil profile located at the plot’s center. Sample plots were located in the area with Gleysols, Cambisols and Podzols with the water table from 0 to 100 cm. In each soil sample, particle size, total carbon and nitrogen content, acidity, base cations content and fractions of soil organic matter were determined. The organic carbon stock (SOCs was calculated based on its total content at particular genetic soil horizons. A Carbon Distribution Index (CDI was calculated from the ratio of the carbon accumulation in organic horizons and the amount of organic carbon accumulation in the mineral horizons, up to 60 cm. In the soils under study, in the temperate zone, moisture is an important factor in the accumulation of organic carbon in the soil. The highest accumulation of carbon was observed in soils of swampy variant, while the lowest was in the soils of moist variant. Large accumulation of C in the soils with water table 80–100 cm results from the thick organic horizons that are characterized by lower organic matter decomposition and higher acidity. The proportion of carbon accumulation in the organic horizons to the total accumulation in the mineral horizons expresses the distribution of carbon accumulated in the soil profile, and is a measure of quality of the organic matter accumulated. Studies have confirmed the importance of moisture content in the formation of the fractional organic matter. With greater soil moisture, the ratio of humic to fulvic acids (HA/FA decreases, which may suggest an increase in carbon mobility in soils.

  13. [Effects of Soil Moisture on Phytoremediation of As-Containinated Soils Using As-Hyperaccumulator Pteris vittata L].

    Science.gov (United States)

    Liu, Qiu-xin; Yan, Xiu-lan; Liao, Xiao-yong; Lin, Long-yong; Yang, Jing

    2015-08-01

    A pot experiment was carried out to study the effects of soil moisture on the growth and arsenic uptake of As-hyperaccumulator Pteris vittata L. The results showed that the remediation efficiency of As was the highest when the soil moisture was between 35%-45%. P. vittata grew best under 45% water content, and its aboveground and underground plant dry weights were 2.95 g x plant(-1) and 11.95 g x plant(-1), respectively; the arsenic concentration in aboveground and roots was the highest under 35% water content, and 40% content was the best for accumulation of arsenic in P. vittata. Moreover, controlling the soil moisture to 35%-45% enhanced the conversion of As(V) to As(III) in aboveground plant, and promoted arsenic detoxification in P. vittata. These above results showed that soil moisture played an important role in the absorption and transport of arsenic by P. vittata. The results of this study can provide important guidance for the large-scale planting of P. vittata and the moisture management measures in engineering application.

  14. Soil moisture effects on the carbon isotopic composition of soil respiration

    Science.gov (United States)

    The carbon isotopic composition ( 13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low soil moisture or by low atmospheric humidity. Air humidity has also been shown to correlate with the 13C of soil respiration, which suggests indir...

  15. Variation in soil moisture and N availability modulates carbon and water exchange in a California grassland experiment

    Energy Technology Data Exchange (ETDEWEB)

    St. Clair, S.B.; Sudderth, E.; Fischer, M.L.; Torn, M.S.; Stuart, S.; Salve, R.; Eggett, D.; Ackerly, D.

    2009-03-15

    Variability in the magnitude and timing of precipitation is predicted to change under future climate scenarios. The primary objective of this study was to understand how variation in precipitation patterns consisting of soil moisture pulses mixed with intermittent dry down events influence ecosystem gas fluxes. We characterized the effects of precipitation amount and timing, N availability, and plant community composition on whole ecosystem and leaf gas exchange in a California annual grassland mesocosm study system that allowed precise control of soil moisture conditions. Ecosystem CO2 and fluxes increased significantly with greater precipitation and were positively correlated with soil moisture. A repeated 10 day dry down period following 11 days of variable precipitation inputs strongly depressed net ecosystem CO2 exchange (NEE) across a range of season precipitation totals, and plant community types. Ecosystem respiration (Re), evapotranspiration (ET) and leaf level photosynthesis (Amax) showed greatest sensitivity to dry down periods in low precipitation plots. Nitrogen additions significantly increased NEE, Re and Amax, particularly as water availability was increased. These results demonstrate that N availability and intermittent periods of soil moisture deficit (across a wide range of cumulative season precipitation totals) strongly modulate ecosystem gas exchange.

  16. Relative Roles of Soil Moisture, Nutrient Supply, Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies.

    Science.gov (United States)

    Wernerehl, Robert W; Givnish, Thomas J

    2015-01-01

    Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis' continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward "drier" sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500-1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward "wetter" sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This study is the

  17. Relative Roles of Soil Moisture, Nutrient Supply, Depth, and Mechanical Impedance in Determining Composition and Structure of Wisconsin Prairies

    Science.gov (United States)

    Wernerehl, Robert W.; Givnish, Thomas J.

    2015-01-01

    Ecologists have long classified Midwestern prairies based on compositional variation assumed to reflect local gradients in moisture availability. The best known classification is based on Curtis’ continuum index (CI), calculated using the presence of indicator species thought centered on different portions of an underlying moisture gradient. Direct evidence of the extent to which CI reflects differences in moisture availability has been lacking, however. Many factors that increase moisture availability (e.g., soil depth, silt content) also increase nutrient supply and decrease soil mechanical impedance; the ecological effects of the last have rarely been considered in any ecosystem. Decreased soil mechanical impedance should increase the availability of soil moisture and nutrients by reducing the root costs of retrieving both. Here we assess the relative importance of soil moisture, nutrient supply, and mechanical impedance in determining prairie composition and structure. We used leaf δ13C of C3 plants as a measure of growing-season moisture availability, cation exchange capacity (CEC) x soil depth as a measure of mineral nutrient availability, and penetrometer data as a measure of soil mechanical impedance. Community composition and structure were assessed in 17 remnant prairies in Wisconsin which vary little in annual precipitation. Ordination and regression analyses showed that δ13C increased with CI toward “drier” sites, and decreased with soil depth and % silt content. Variation in δ13C among remnants was 2.0‰, comparable to that along continental gradients from ca. 500–1500 mm annual rainfall. As predicted, LAI and average leaf height increased significantly toward “wetter” sites. CI accounted for 54% of compositional variance but δ13C accounted for only 6.2%, despite the strong relationships of δ13C to CI and CI to composition. Compositional variation reflects soil fertility and mechanical impedance more than moisture availability. This

  18. NASA Soil Moisture Active Passive Mission Status and Science Performance

    Science.gov (United States)

    Yueh, Simon H.; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni; Entin, Jared K.

    2016-01-01

    The Soil Moisture Active Passive (SMAP) observatory was launched January 31, 2015, and its L-band radiometer and radar instruments became operational since mid-April 2015. The SMAP radiometer has been operating flawlessly, but the radar transmitter ceased operation on July 7. This paper provides a status summary of the calibration and validation of the SMAP instruments and the quality assessment of its soil moisture and freeze/thaw products. Since the loss of the radar in July, the SMAP project has been conducting two parallel activities to enhance the resolution of soil moisture products. One of them explores the Backus Gilbert optimum interpolation and de-convolution techniques based on the oversampling characteristics of the SMAP radiometer. The other investigates the disaggregation of the SMAP radiometer data using the European Space Agency's Sentinel-1 C-band synthetic radar data to obtain soil moisture products at about 1 to 3 kilometers resolution. In addition, SMAP's L-band data have found many new applications, including vegetation opacity, ocean surface salinity and hurricane ocean surface wind mapping. Highlights of these new applications will be provided.

  19. The role of soil moisture on the coevolution of soil and vegetation in mountain grasslands

    Science.gov (United States)

    Bertoldi, Giacomo; Claudia, Notarnicola; Brenner, Johannes; Castelli, Mariapina; Greifeneder, Felix; Niedrist, Georg; Seeber, Julia; Tappeiner, Ulrike

    2016-04-01

    One of the key variables controlling the organization of vegetation and the coevolution of soils and landforms is soil moisture content (SMC). For this reason, understanding the controls on the spatial and temporal patterns of SMC is essential to predict how perturbations in vegetation and climate will affect mountain ecosystem functioning. In this contribution, we focus on the dynamic of surface SMC of water-limited alpine grasslands in the Long Term Ecological Research area Mazia Valley in the European Alps. We analyze the impacts of different land managements (meadows versus pastures) and its relationships with climate and topography. The area has been equipped since 2009 with a network of more than 20 stations, measuring SMC and climatic variables and with two eddy-covariance stations, measuring surface fluxes over meadows and pastures. Monthly biomass production data have been collected and detailed soil and spatial soil moisture surveys are available. Moreover, high spatial resolution SMC maps have been derived from satellites Synthetic Aperture Radar Radar (SAR) images (Sentinel 1 and RADARSAT2 images). Both ground surveys and remote sensing observations show persistent landscape-level patterns. Meadows, in general located in flatter areas, tend to be wetter. This leads to higher vegetation productivity and to the development of soils with higher water holding capacity, thus to a positive feedback on SMC. In contrast, pastures, located on steeper slopes with lower vegetation density and higher soil erosion, tend to be drier, leading to a negative feedback on SMC and soil development. This co-evolution of land cover and SMC leads therefore to persistent spatial patterns. In order to understand quantitatively such linked interactions, a sensitivity analysis has been performed with the GEOtop hydrological model. Results show how both abiotic (mainly slope and elevation) and anthropogenic (irrigation and soil management) factors exert a significant control on

  20. Development and evaluation of the MTVDI for soil moisture monitoring

    Science.gov (United States)

    Zhu, Wenbin; Lv, Aifeng; Jia, Shaofeng; Sun, Liang

    2017-06-01

    Several parameterization schemes have been developed to retrieve the soil moisture information involved in the remotely sensed surface temperature-vegetation index (Ts - VI) space. However, most of them are performed with the constraint of the dry edge of the Ts - VI space to define the maximum water stressed conditions. In view of the subjectivity and uncertainty involved in the determination of the dry edge, a new index termed as the Modified Temperature-Vegetation Dryness Index (MTVDI) was developed in this paper to reduce the reliance of the parameterization scheme on the dry edge. In the parameterization scheme of MTVDI, isopleth lines of soil moisture involved in the feature space were retrieved by the temperature-vegetation index method, and only the maximum surface temperature of bare soil (Tsmax) was indispensable in the definition of maximum water stressed conditions. For evaluation purpose, the MTVDI was demonstrated in the Southern Great Plains region of the U.S. and was compared with two other traditional soil moisture indexes developed under the constraint of dry edge. The comparison confirmed the effectivity of the MTVDI in monitoring the spatial pattern and seasonal variation of soil moisture. Our analyses also suggest that Tsmax, the only parameter needed in the definition of maximum water stressed conditions, can be retrieved directly from the parameterization scheme itself. Therefore, the retrieval of MTVDI can be performed independent of the dry edge, which is a significant improvement to the traditional parameterization schemes of soil moisture from the Ts - VI feature space.

  1. Spatiotemporal Distribution of Soil Moisture and Salinity in the Taklimakan Desert Highway Shelterbelt

    Directory of Open Access Journals (Sweden)

    Yuan Huang

    2015-08-01

    Full Text Available Salinization and secondary salinization often appear after irrigation with saline water. The Taklimakan Desert Highway Shelterbelt has been irrigated with saline ground water for more than ten years; however, soil salinity in the shelterbelt has not been evaluated. The objective of this study was to analyze the spatial and temporal distribution of soil moisture and salinity in the shelterbelt system. Using a non-uniform grid method, soil samples were collected every two days during one ten-day irrigation cycle in July 2014 and one day in spring, summer, and autumn. The results indicated that soil moisture declined linearly with time during the irrigation cycle. Soil moisture was greatest in the southern and eastern sections of the study area. In contrast to soil moisture, soil electrical conductivity increased from 2 to 6 days after irrigation, and then gradually decreased from 6 to 8 days after irrigation. Soil moisture was the greatest in spring and the least in summer. In contrast, soil salinity increased from spring to autumn. Long time drip-irrigation with saline groundwater increased soil salinity slightly. The soil salt content was closely associated with soil texture. The current soil salt content did not affect plant growth, however, the soil in the shelterbelt should be continuously monitored to prevent salinization in the future.

  2. development and testing of a capacitive digital soil moisture metre

    African Journals Online (AJOL)

    This paper presents a low cost, simple digital soil moisture meter, working on the principle of dielectric. A digital soil moisture meter using the NE555 timer and micro controller as a major electronic component was developed and tested, which display its output in a range of 0.0 to 99% on the 7-segment displayed unit.

  3. Land-atmosphere coupling and soil moisture memory contribute to long-term agricultural drought

    Science.gov (United States)

    Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.

    2017-12-01

    We assessed the contribution of land-atmosphere coupling and soil moisture memory on long-term agricultural droughts in the US. We performed an ensemble of climate model simulations to study soil moisture dynamics under two atmospheric forcing scenarios: active and muted land-atmosphere coupling. Land-atmosphere coupling contributes to a 12% increase and 36% decrease in the decorrelation time scale of soil moisture anomalies in the US Great Plains and the Southwest, respectively. These differences in soil moisture memory affect the length and severity of modeled drought. Consequently, long-term droughts are 10% longer and 3% more severe in the Great Plains, and 15% shorter and 21% less severe in the Southwest. An analysis of Coupled Model Intercomparsion Project phase 5 data shows four fold uncertainty in soil moisture memory across models that strongly affects simulated long-term droughts and is potentially attributable to the differences in soil water storage capacity across models.

  4. Landscape-scale soil moisture heterogeneity and its influence on surface fluxes at the Jornada LTER site: Evaluating a new model parameterization for subgrid-scale soil moisture variability

    Science.gov (United States)

    Baker, I. T.; Prihodko, L.; Vivoni, E. R.; Denning, A. S.

    2017-12-01

    Arid and semiarid regions represent a large fraction of global land, with attendant importance of surface energy and trace gas flux to global totals. These regions are characterized by strong seasonality, especially in precipitation, that defines the level of ecosystem stress. Individual plants have been observed to respond non-linearly to increasing soil moisture stress, where plant function is generally maintained as soils dry down to a threshold at which rapid closure of stomates occurs. Incorporating this nonlinear mechanism into landscape-scale models can result in unrealistic binary "on-off" behavior that is especially problematic in arid landscapes. Subsequently, models have `relaxed' their simulation of soil moisture stress on evapotranspiration (ET). Unfortunately, these relaxations are not physically based, but are imposed upon model physics as a means to force a more realistic response. Previously, we have introduced a new method to represent soil moisture regulation of ET, whereby the landscape is partitioned into `BINS' of soil moisture wetness, each associated with a fractional area of the landscape or grid cell. A physically- and observationally-based nonlinear soil moisture stress function is applied, but when convolved with the relative area distribution represented by wetness BINS the system has the emergent property of `smoothing' the landscape-scale response without the need for non-physical impositions on model physics. In this research we confront BINS simulations of Bowen ratio, soil moisture variability and trace gas flux with soil moisture and eddy covariance observations taken at the Jornada LTER dryland site in southern New Mexico. We calculate the mean annual wetting cycle and associated variability about the mean state and evaluate model performance against this variability and time series of land surface fluxes from the highly instrumented Tromble Weir watershed. The BINS simulations capture the relatively rapid reaction to wetting

  5. A soil moisture network for SMOS validation in Western Denmark

    DEFF Research Database (Denmark)

    Bircher, Simone; Skou, N.; Jensen, Karsten Høgh

    2012-01-01

    network was established in the Skjern River Catchment, Denmark. The objectives of this article are to describe a method to implement a network suited for SMOS validation, and to present sample data collected by the network to verify the approach. The design phase included (1) selection of a single SMOS...... between the north-east and south-west were found to be small. A first comparison between the 0–5 cm network averages and the SMOS soil moisture (level 2) product is in range with worldwide validation results, showing comparable trends for SMOS retrieved soil moisture (R2 of 0.49) as well as initial soil......). Based on these findings, the network performs according to expectations and proves to be well-suited for its purpose. The discrepancies between network and SMOS soil moisture will be subject of subsequent studies...

  6. Potential and limitations of multidecadal satellite soil moisture observations for selected climate model evaluation studies

    Directory of Open Access Journals (Sweden)

    A. Loew

    2013-09-01

    Full Text Available Soil moisture is an essential climate variable (ECV of major importance for land–atmosphere interactions and global hydrology. An appropriate representation of soil moisture dynamics in global climate models is therefore important. Recently, a first multidecadal, observation-based soil moisture dataset has become available that provides information on soil moisture dynamics from satellite observations (ECVSM, essential climate variable soil moisture. The present study investigates the potential and limitations of this new dataset for several applications in climate model evaluation. We compare soil moisture data from satellite observations, reanalysis and simulations from a state-of-the-art land surface model and analyze relationships between soil moisture and precipitation anomalies in the different dataset. Other potential applications like model parameter optimization or model initialization are not investigated in the present study. In a detailed regional study, we show that ECVSM is capable to capture well the interannual and intraannual soil moisture and precipitation dynamics in the Sahelian region. Current deficits of the new dataset are critically discussed and summarized at the end of the paper to provide guidance for an appropriate usage of the ECVSM dataset for climate studies.

  7. The impact of non-isothermal soil moisture transport on evaporation fluxes in a maize cropland

    Science.gov (United States)

    Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye

    2018-06-01

    The process of evaporation interacts with the soil, which has various comprehensive mechanisms. Multiphase flow models solve air, vapour, water, and heat transport equations to simulate non-isothermal soil moisture transport of both liquid water and vapor flow, but are only applied in non-vegetated soils. For (sparsely) vegetated soils often energy balance models are used, however these lack the detailed information on non-isothermal soil moisture transport. In this study we coupled a multiphase flow model with a two-layer energy balance model to study the impact of non-isothermal soil moisture transport on evaporation fluxes (i.e., interception, transpiration, and soil evaporation) for vegetated soils. The proposed model was implemented at an experimental agricultural site in Florida, US, covering an entire maize-growing season (67 days). As the crops grew, transpiration and interception became gradually dominated, while the fraction of soil evaporation dropped from 100% to less than 20%. The mechanisms of soil evaporation vary depending on the soil moisture content. After precipitation the soil moisture content increased, exfiltration of the liquid water flow could transport sufficient water to sustain evaporation from soil, and the soil vapor transport was not significant. However, after a sufficient dry-down period, the soil moisture content significantly reduced, and the soil vapour flow significantly contributed to the upward moisture transport in topmost soil. A sensitivity analysis found that the simulations of moisture content and temperature at the soil surface varied substantially when including the advective (i.e., advection and mechanical dispersion) vapour transport in simulation, including the mechanism of advective vapour transport decreased soil evaporation rate under wet condition, while vice versa under dry condition. The results showed that the formulation of advective soil vapor transport in a soil-vegetation-atmosphere transfer continuum can

  8. Using repeat electrical resistivity surveys to assess heterogeneity in soil moisture dynamics under contrasting vegetation types

    Science.gov (United States)

    Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris

    2018-04-01

    As the relationship between vegetation and soil moisture is complex and reciprocal, there is a need to understand how spatial patterns in soil moisture influence the distribution of vegetation, and how the structure of vegetation canopies and root networks regulates the partitioning of precipitation. Spatial patterns of soil moisture are often difficult to visualise as usually, soil moisture is measured at point scales, and often difficult to extrapolate. Here, we address the difficulties in collecting large amounts of spatial soil moisture data through a study combining plot- and transect-scale electrical resistivity tomography (ERT) surveys to estimate soil moisture in a 3.2 km2 upland catchment in the Scottish Highlands. The aim was to assess the spatio-temporal variability in soil moisture under Scots pine forest (Pinus sylvestris) and heather moorland shrubs (Calluna vulgaris); the two dominant vegetation types in the Scottish Highlands. The study focussed on one year of fortnightly ERT surveys. The surveyed resistivity data was inverted and Archie's law was used to calculate volumetric soil moisture by estimating parameters and comparing against field measured data. Results showed that spatial soil moisture patterns were more heterogeneous in the forest site, as were patterns of wetting and drying, which can be linked to vegetation distribution and canopy structure. The heather site showed a less heterogeneous response to wetting and drying, reflecting the more uniform vegetation cover of the shrubs. Comparing soil moisture temporal variability during growing and non-growing seasons revealed further contrasts: under the heather there was little change in soil moisture during the growing season. Greatest changes in the forest were in areas where the trees were concentrated reflecting water uptake and canopy partitioning. Such differences have implications for climate and land use changes; increased forest cover can lead to greater spatial variability, greater

  9. Estimation of improved resolution soil moisture in vegetated areas using passive AMSR-E data

    Science.gov (United States)

    Moradizadeh, Mina; Saradjian, Mohammad R.

    2018-03-01

    Microwave remote sensing provides a unique capability for soil parameter retrievals. Therefore, various soil parameters estimation models have been developed using brightness temperature (BT) measured by passive microwave sensors. Due to the low resolution of satellite microwave radiometer data, the main goal of this study is to develop a downscaling approach to improve the spatial resolution of soil moisture estimates with the use of higher resolution visible/infrared sensor data. Accordingly, after the soil parameters have been obtained using Simultaneous Land Parameters Retrieval Model algorithm, the downscaling method has been applied to the soil moisture estimations that have been validated against in situ soil moisture data. Advance Microwave Scanning Radiometer-EOS BT data in Soil Moisture Experiment 2003 region in the south and north of Oklahoma have been used to this end. Results illustrated that the soil moisture variability is effectively captured at 5 km spatial scales without a significant degradation of the accuracy.

  10. Quality Improvement of the Satellite Soil Moisture Products by Fusing In Situ and GNSS-R Observation

    Science.gov (United States)

    Yuan, Q.; Xu, H.; Li, T.; Shen, H.; Zhang, L.

    2017-12-01

    Soil moisture plays a fundamental role in the hydrological cycle as well as in the energy partitioning. On this basis, it is of great concern to derive a long-term soil moisture time series on a global scale and monitor its temporal and spatial variations for practical applications. Although passive and active microwave satellites have been shown to provide useful retrievals of near-surface soil moisture at regional and global scales, the limitations in retrieval accuracy prevent them from high-quality applications in specific areas. On the other hand, measuring soil moisture straightly through in situdevices, such as soil moisture probes, is high accuracy, but is not able to derive global soil moisture maps. Recently, the ground-based GNSS-R method is emerging in monitoring near-surface soil moisture variations but still over limited spatial scales. In this paper, a multi-source data fusion method was applied to synthesize regional high-quality soil moisture products from 2015 to 2017 in western parts of the continental United States. Firstly, we put all the three soil moisture datasets into the generalized regression neural network (GRNN) model. The input signals of the model are SMOS and SMAP satellite-derived passive level 3 soil moisture daily products combined with date and latitude and longitude information, while the in situ measured and GNSS-R retrieved soil moisture are used as target. Finally, we apply the model to all the soil moisture time series in the experiment area and obtain two high-quality regional soil moisture products for SMOS and SMAP, respectively. The results before fusion show that the correlation coefficients between site-specific soil moisture and satellite-derived soil moisture are 0.39 for SMOS and 0.27 for SMAP and that unbiased root-mean-square errors (ubRMSE) are 0.113 for SMOS and 0.128 for SMAP, respectively. After applying the GRNN-R, the model fitted correlation coefficients have reached 0.72 for SMOS and 0.75 for SMAP and the

  11. Response of deep soil moisture to land use and afforestation in the semi-arid Loess Plateau, China

    Science.gov (United States)

    Yang, Lei; Wei, Wei; Chen, Liding; Mo, Baoru

    2012-12-01

    SummarySoil moisture is an effective water source for plant growth in the semi-arid Loess Plateau of China. Characterizing the response of deep soil moisture to land use and afforestation is important for the sustainability of vegetation restoration in this region. In this paper, the dynamics of soil moisture were quantified to evaluate the effect of land use on soil moisture at a depth of 2 m. Specifically, the gravimetric soil moisture content was measured in the soil layer between 0 and 8 m for five land use types in the Longtan catchment of the western Loess Plateau. The land use types included traditional farmland, native grassland, and lands converted from traditional farmland (pasture grassland, shrubland and forestland). Results indicate that the deep soil moisture content decreased more than 35% after land use conversion, and a soil moisture deficit appeared in all types of land with introduced vegetation. The introduced vegetation decreased the soil moisture content to levels lower than the reference value representing no human impact in the entire 0-8 m soil profile. No significant differences appeared between different land use types and introduced vegetation covers, especially in deeper soil layers, regardless of which plant species were introduced. High planting density was found to be the main reason for the severe deficit of soil moisture. Landscape management activities such as tillage activities, micro-topography reconstruction, and fallowed farmland affected soil moisture in both shallow and deep soil layers. Tillage and micro-topography reconstruction can be used as effective countermeasures to reduce the soil moisture deficit due to their ability to increase soil moisture content. For sustainable vegetation restoration in a vulnerable semi-arid region, the plant density should be optimized with local soil moisture conditions and appropriate landscape management practices.

  12. The neutronic method for measuring soil moisture

    International Nuclear Information System (INIS)

    Couchat, Ph.

    1967-01-01

    The three group diffusion theory being chosen as the most adequate method for determining the response of the neutron soil moisture probe, a mathematical model is worked out using a numerical calculation programme with Fortran IV coding. This model is fitted to the experimental conditions by determining the effect of different parameters of measuring device: channel, fast neutron source, detector, as also the soil behaviour under neutron irradiation: absorbers, chemical binding of elements. The adequacy of the model is tested by fitting a line through the image points corresponding to the couples of experimental and theoretical values, for seven media having different chemical composition: sand, alumina, line stone, dolomite, kaolin, sandy loam, calcareous clay. The model chosen gives a good expression of the dry density influence and allows α, β, γ and δ constants to be calculated for a definite soil according to the following relation which gives the count rate of the soil moisture probe: N = (α ρ s +β) H v +γ ρ s + δ. (author) [fr

  13. Seedling establishment and physiological responses to temporal and spatial soil moisture changes

    Science.gov (United States)

    Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos

    2016-01-01

    In many forests of the world, the summer season (temporal element) brings drought conditions causing low soil moisture in the upper soil profile (spatial element) - a potentially large barrier to seedling establishment. We evaluated the relationship between initial seedling root depth, temporal and spatial changes in soil moisture during drought after...

  14. Estimation of Soil Moisture Under Vegetation Cover at Multiple Frequencies

    Science.gov (United States)

    Jadghuber, Thomas; Hajnsek, Irena; Weiß, Thomas; Papathanassiou, Konstantinos P.

    2015-04-01

    Soil moisture under vegetation cover was estimated by a polarimetric, iterative, generalized, hybrid decomposition and inversion approach at multiple frequencies (X-, C- and L-band). Therefore the algorithm, originally designed for longer wavelength (L-band), was adapted to deal with the short wavelength scattering scenarios of X- and C-band. The Integral Equation Method (IEM) was incorporated together with a pedo-transfer function of Dobson et al. to account for the peculiarities of short wavelength scattering at X- and C-band. DLR's F-SAR system acquired fully polarimetric SAR data in X-, C- and L-band over the Wallerfing test site in Lower Bavaria, Germany in 2014. Simultaneously, soil and vegetation measurements were conducted on different agricultural test fields. The results indicate a spatially continuous inversion of soil moisture in all three frequencies (inversion rates >92%), mainly due to the careful adaption of the vegetation volume removal including a physical constraining of the decomposition algorithm. However, for X- and C-band the inversion results reveal moisture pattern inconsistencies and in some cases an incorrectly high inversion of soil moisture at X-band. The validation with in situ measurements states a stable performance of 2.1- 7.6vol.% at L-band for the entire growing period. At C- and X-band a reliable performance of 3.7-13.4vol.% in RMSE can only be achieved after distinct filtering (X- band) leading to a loss of almost 60% in spatial inversion rate. Hence, a robust inversion for soil moisture estimation under vegetation cover can only be conducted at L-band due to a constant availability of the soil signal in contrast to higher frequencies (X- and C-band).

  15. Validation and Scaling of Soil Moisture in a Semi-Arid Environment: SMAP Validation Experiment 2015 (SMAPVEX15)

    Science.gov (United States)

    Colliander, Andreas; Cosh, Michael H.; Misra, Sidharth; Jackson, Thomas J.; Crow, Wade T.; Chan, Steven; Bindlish, Rajat; Chae, Chun; Holifield Collins, Chandra; Yueh, Simon H.

    2017-01-01

    The NASA SMAP (Soil Moisture Active Passive) mission conducted the SMAP Validation Experiment 2015 (SMAPVEX15) in order to support the calibration and validation activities of SMAP soil moisture data products. The main goals of the experiment were to address issues regarding the spatial disaggregation methodologies for improvement of soil moisture products and validation of the in situ measurement upscaling techniques. To support these objectives high-resolution soil moisture maps were acquired with the airborne PALS (Passive Active L-band Sensor) instrument over an area in southeast Arizona that includes the Walnut Gulch Experimental Watershed (WGEW), and intensive ground sampling was carried out to augment the permanent in situ instrumentation. The objective of the paper was to establish the correspondence and relationship between the highly heterogeneous spatial distribution of soil moisture on the ground and the coarse resolution radiometer-based soil moisture retrievals of SMAP. The high-resolution mapping conducted with PALS provided the required connection between the in situ measurements and SMAP retrievals. The in situ measurements were used to validate the PALS soil moisture acquired at 1-km resolution. Based on the information from a dense network of rain gauges in the study area, the in situ soil moisture measurements did not capture all the precipitation events accurately. That is, the PALS and SMAP soil moisture estimates responded to precipitation events detected by rain gauges, which were in some cases not detected by the in situ soil moisture sensors. It was also concluded that the spatial distribution of the soil moisture resulted from the relatively small spatial extents of the typical convective storms in this region was not completely captured with the in situ stations. After removing those cases (approximately10 of the observations) the following metrics were obtained: RMSD (root mean square difference) of0.016m3m3 and correlation of 0.83. The

  16. Multifrequency passive microwave observations of soil moisture in an arid rangeland environment

    Science.gov (United States)

    Jackson, T. J.; Schmugge, T. J.; Parry, R.; Kustas, W. P.; Ritchie, J. C.; Shutko, A. M.; Khaldin, A.; Reutov, E.; Novichikhin, E.; Liberman, B.

    1992-01-01

    A cooperative experiment was conducted by teams from the U.S. and U.S.S.R. to evaluate passive microwave instruments and algorithms used to estimate surface soil moisture. Experiments were conducted as part of an interdisciplinary experiment in an arid rangeland watershed located in the southwest United States. Soviet microwave radiometers operating at wavelengths of 2.25, 21 and 27 cm were flown on a U.S. aircraft. Radio frequency interference limited usable data to the 2.25 and 21 cm systems. Data have been calibrated and compared to ground observations of soil moisture. These analyses showed that the 21 cm system could produce reliable and useful soil moisture information and that the 2.25 cm system was of no value for soil moisture estimation in this experiment.

  17. The effect of soil moisture on the 37 GHz microwave polarization difference index (MPDI)

    International Nuclear Information System (INIS)

    Felde, G.W.

    1998-01-01

    Previous studies have shown that the 37 GHz microwave polarization difference index (MPDI) has an inverse nonlinear relationship to the normalized difference vegetation index (NDVI) with the MPDI (NDVI) being more sensitive to vegetation density under sparse (moderate) vegetation conditions. It has also been noted that soil moisture can have a significant influence on the MPDI. This study quantifies the effect of soil moisture on the MPDI using the RADTRAN model and comparison with measurements from a few geographically restricted (eastern USA) study sites. Model results show the MPDI increases with soil moisture but its sensitivity approaches zero when soil moisture values or vegetation densities are large. Results based on special sensor microwave/imager (SSM/I) measured values of MPDI, using the NDVI as a surrogate for vegetation density and an antecedent precipitation index (API) as a surrogate for soil moisture, were consistent with those based on the model. Linear equations, one for each of three categories of vegetation density, expressing MPDI as a function of API were derived based on SSM/I measurements. These equations demonstrate that soil moisture information can be extracted from the MPDI when the NDVI is used to account for the effect of vegetation and that the effect of soil moisture on the MPDI should be taken into account if it is to be used as a vegetation index. The potential to normalize MPDI values for variations in soil moisture is discussed. (author)

  18. Effects of neutron source type on soil moisture measurement

    Science.gov (United States)

    Irving Goldberg; Norman A. MacGillivray; Robert R. Ziemer

    1967-01-01

    A number of radioisotopes have recently become commercially available as alternatives to radium-225 in moisture gauging devices using alpha-neutron sources for determining soil moisture, for well logging, and for other industrial applications in which hydrogenous materials are measured.

  19. Uncertainty Assessment of Space-Borne Passive Soil Moisture Retrievals

    Science.gov (United States)

    Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre

    2017-01-01

    The uncertainty associated with passive soil moisture retrieval is hard to quantify, and known to be underlain by various, diverse, and complex causes. Factors affecting space-borne retrieved soil moisture estimation include: (i) the optimization or inversion method applied to the radiative transfer model (RTM), such as e.g. the Single Channel Algorithm (SCA), or the Land Parameter Retrieval Model (LPRM), (ii) the selection of the observed brightness temperatures (Tbs), e.g. polarization and incidence angle, (iii) the definition of the cost function and the impact of prior information in it, and (iv) the RTM parameterization (e.g. parameterizations officially used by the SMOS L2 and SMAP L2 retrieval products, ECMWF-based SMOS assimilation product, SMAP L4 assimilation product, and perturbations from those configurations). This study aims at disentangling the relative importance of the above-mentioned sources of uncertainty, by carrying out soil moisture retrieval experiments, using SMOS Tb observations in different settings, of which some are mentioned above. The ensemble uncertainties are evaluated at 11 reference CalVal sites, over a time period of more than 5 years. These experimental retrievals were inter-compared, and further confronted with in situ soil moisture measurements and operational SMOS L2 retrievals, using commonly used skill metrics to quantify the temporal uncertainty in the retrievals.

  20. Evaluating lysimeter drainage against soil deep percolation modeled with profile soil moisture, field tracer propagation, and lab measured soil hydraulic properties

    DEFF Research Database (Denmark)

    Vasquez, Vicente; Thomsen, Anton Gårde; Iversen, Bo Vangsø

    them have been reported. To compare among methods, one year of four large-scale lysimeters drainage (D) was evaluated against modeled soil deep percolation using either profile soil moisture, bromide breakthrough curves from suction cups, or measured soil hydraulic properties in the laboratory....... Measured volumetric soil water content (q) was 3-4% higher inside lysimeters than in the field probably due to a zero tension lower boundary condition inside lysimeters. D from soil hydraulic properties measured in the laboratory resulted in a 15% higher evapotranspiration and 12% lower drainage...... predictions than the model calibrated with field measured q. Bromide (Br) breakthrough curves indicated high variability between lysimeters and field suction cups with mean Br velocities at first arrival time of 110 and 33 mm/d, respectively. D was 520 mm/yr with lysimeters, 613 mm/yr with the calibrated...

  1. Soil moisture effects on the carbon isotope composition of soil respiration

    Science.gov (United States)

    Claire L. Phillips; Nick Nickerson; David Risk; Zachary E. Kayler; Chris Andersen; Alan Mix; Barbara J. Bond

    2010-01-01

    The carbon isotopic composition (δ13C) of recently assimilated plant carbon is known to depend on water-stress, caused either by low soil moisture or by low atmospheric humidity. Air humidity has also been shown to correlate with the δ13C of soil respiration, which suggests indirectly that recently fixed photosynthates...

  2. Smap Soil Moisture Data Assimilation for the Continental United States and Eastern Africa

    Science.gov (United States)

    Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.

    2016-12-01

    The NASA Short-Term Prediction Research and Transition (SPoRT) Center at Marshall Space Flight Center manages near-real-time runs of the Noah Land Surface Model within the NASA Land Information System (LIS) over Continental U.S. (CONUS) and Eastern Africa domains. Soil moisture products from the CONUS model run are used by several NOAA/National Weather Service Weather Forecast Offices for flood and drought situational awareness. The baseline LIS configuration is the Noah model driven by atmospheric and combined radar/gauge precipitation analyses, and input satellite-derived real-time green vegetation fraction on a 3-km grid for the CONUS. This configuration is being enhanced by adding the assimilation of Level 2 Soil Moisture Active/Passive (SMAP) soil moisture retrievals in a parallel run beginning on 1 April 2015. Our implementation of SMAP assimilation includes a cumulative distribution function (CDF) matching approach that aggregates points with similar soil types. This method allows creation of robust CDFs with a short data record, and also permits the correction of local anomalies that may arise from poor forcing data (e.g., quality-control problems with rain gauges). Validation results using in situ soil monitoring networks in the CONUS are shown, with comparisons to the baseline SPoRT-LIS run. Initial results are also presented from a modeling run in eastern Africa, forced by Integrated Multi-satellitE Retrievals for GPM (IMERG) precipitation data. Strategies for spatial downscaling and for dealing with effective depth of the retrieval product are also discussed.

  3. Soil moisture dynamics and their effect on bioretention performance in Northeast Ohio

    Science.gov (United States)

    Bush, S. A.; Jefferson, A.; Jarden, K.; Kinsman-Costello, L. E.; Grieser, J.

    2014-12-01

    Urban impervious surfaces lead to increases in stormwater runoff. Green infrastructure, like bioretention cells, is being used to mitigate negative impacts of runoff by disconnecting impervious surfaces from storm water systems and redirecting flow to decentralized treatment areas. While bioretention soil characteristics are carefully designed, little research is available on soil moisture dynamics within the cells and how these might relate to inter-storm variability in performance. Bioretentions have been installed along a residential street in Parma, Ohio to determine the impact of green infrastructure on the West Creek watershed, a 36 km2 subwatershed of the Cuyahoga River. Bioretentions were installed in two phases (Phase I in 2013 and Phase II in 2014); design and vegetation density vary slightly between the two phases. Our research focuses on characterizing soil moisture dynamics of multiple bioretentions and assessing their impact on stormwater runoff at the street scale. Soil moisture measurements were collected in transects for eight bioretentions over the course of one summer. Vegetation indices of canopy height, percent vegetative cover, species richness and NDVI were also measured. A flow meter in the storm drain at the end of the street measured storm sewer discharge. Precipitation was recorded from a meteorological station 2 km from the research site. Soil moisture increased in response to precipitation and decreased to relatively stable conditions within 3 days following a rain event. Phase II bioretentions exhibited greater soil moisture and less vegetation than Phase I bioretentions, though the relationship between soil moisture and vegetative cover is inconclusive for bioretentions constructed in the same phase. Data from five storms suggest that pre-event soil moisture does not control the runoff-to-rainfall ratio, which we use as a measure of bioretention performance. However, discharge data indicate that hydrograph characteristics, such as lag

  4. Diuron mineralisation in a Mediterranean vineyard soil: impact of moisture content and temperature.

    Science.gov (United States)

    El Sebaï, Talaat; Devers, Marion; Lagacherie, Bernard; Rouard, Nadine; Soulas, Guy; Martin-Laurent, Fabrice

    2010-09-01

    The diuron-mineralising ability of the microbiota of a Mediterranean vineyard soil exposed each year to this herbicide was measured. The impact of soil moisture and temperature on this microbial activity was assessed. The soil microbiota was shown to mineralise diuron. This mineralising activity was positively correlated with soil moisture content, being negligible at 5% and more than 30% at 20% soil moisture content. According to a double Gaussian model applied to fit the dataset, the optimum temperature/soil moisture conditions were 27.9 degrees C/19.3% for maximum mineralisation rate and 21.9 degrees C/18.3% for maximum percentage mineralisation. The impact of temperature and soil moisture content variations on diuron mineralisation was estimated. A simulated drought period had a suppressive effect on subsequent diuron mineralisation. This drought effect was more marked when higher temperatures were used to dry (40 degrees C versus 28 degrees C) or incubate (28 degrees C versus 20 degrees C) the soil. The diuron kinetic parameters measured after drought conditions were no longer in accordance with those estimated by the Gaussian model. Although soil microbiota can adapt to diuron mineralisation, its activity is strongly dependent on climatic conditions. It suggests that diuron is not rapidly degraded under Mediterranean climate, and that arable Mediterranean soils are likely to accumulate diuron residues. (c) 2010 Society of Chemical Industry.

  5. Diagnosing Soil Moisture Anomalies and Neglected Soil Moisture Source/Sink Processes via a Thermal Infrared-based Two-Source Energy Balance Model

    Science.gov (United States)

    Hain, C.; Crow, W. T.; Anderson, M. C.; Yilmaz, M. T.

    2014-12-01

    Atmospheric processes, especially those that occur in the surface and boundary layer, are significantly impacted by soil moisture (SM). Due to the observational gaps in the ground-based monitoring of SM, methodologies have been developed to monitor SM from satellite platforms. While many have focused on microwave methods, observations of thermal infrared land surface temperature (LST) also provides a means of providing SM information. One particular TIR SM method exploits surface flux predictions retrieved from the Atmosphere Land Exchange Inverse (ALEXI) model. ALEXI uses a time-differential measurement of morning LST rise to diagnose the partitioning of net radiation into surface energy fluxes. Here an analysis will be presented to study relationships between three SM products during a multi-year period (2000-2013) from an active/passive microwave dataset (ECV), a TIR-based model (ALEXI), and a land surface model (Noah) over the CONUS. Additionally, all three will be compared against in-situ SM observations from the North American Soil Moisture Database. The second analysis will focus on the use of ALEXI towards diagnosing SM source/sink processes. Traditional soil water balance modeling is based on one-dimensional (vertical-only) water flow, free drainage at the bottom of the soil column, and neglecting ancillary inputs due to processes such as irrigation. However, recent work has highlighted the importance of secondary water source (e.g., irrigation, groundwater extraction, inland wetlands, lateral flows) and sink (e.g., tile drainage in agricultural areas) processes on the partitioning of evaporative and sensible heat fluxes. ALEXI offers a top-down approach for mapping areas where SM source/sink processes have a significant impact on the surface energy balance. Here we present an index, ASSET, that is based on comparisons between ALEXI latent heat flux (LE) estimates and LE predicted by a free-drainage prognostic LSM lacking irrigation, groundwater and tile

  6. Estimation of Soil Moisture in an Alpine Catchment with RADARSAT2 Images

    Directory of Open Access Journals (Sweden)

    L. Pasolli

    2011-01-01

    Full Text Available Soil moisture retrieval is one of the most challenging problems in the context of biophysical parameter estimation from remotely sensed data. Typically, microwave signals are used thanks to their sensitivity to variations in the water content of soil. However, especially in the Alps, the presence of vegetation and the heterogeneity of topography may significantly affect the microwave signal, thus increasing the complexity of the retrieval. In this paper, the effectiveness of RADARSAT2 SAR images for the estimation of soil moisture in an alpine catchment is investigated. We first carry out a sensitivity analysis of the SAR signal to the moisture content of soil and other target properties (e.g., topography and vegetation. Then we propose a technique for estimating soil moisture based on the Support Vector Regression algorithm and the integration of ancillary data. Preliminary results are discussed both in terms of accuracy over point measurements and effectiveness in handling spatially distributed data.

  7. Monitoring soil moisture dynamics via ground-penetrating radar survey of agriculture fields after irrigation

    Science.gov (United States)

    Muro, G.

    2015-12-01

    It is possible to examine the quality of ground-penetrating radar (GPR) as a measure of soil moisture content in the shallow vadose zone, where roots are most abundant and water conservation best management practices are critical in active agricultural fields. By analyzing temporal samplings of 100 Mhz reflection profiles and common-midpoint (CMP) soundings over a full growing season, the variability of vertical soil moisture distribution directly after irrigation events are characterized throughout the lifecycle of a production crop. Reflection profiles produce high-resolution travel time data and summed results of CMP sounding data provide sampling depth estimates for the weak, but coherent reflections amid strong point scatterers. The high ratio of clay in the soil limits the resolution of downward propagation of infiltrating moisture after irrigation; synthetic data analysis compared against soil moisture lysimeter logs throughout the profile allow identification of the discrete soil moisture content variation in the measured GPR data. The nature of short duration irrigation events, evapotranspiration, and drainage behavior in relation to root depths observed in the GPR temporal data allow further examination and comparison with the variable saturation model HYDRUS-1D. After retrieving soil hydraulic properties derived from laboratory measured soil samples and simplified assumptions about boundary conditions, the project aims to achieve good agreement between simulated and measured soil moisture profiles without the need for excessive model calibration for GPR-derived soil moisture estimates in an agricultural setting.

  8. Global retrieval of soil moisture and vegetation properties using data-driven methods

    Science.gov (United States)

    Rodriguez-Fernandez, Nemesio; Richaume, Philippe; Kerr, Yann

    2017-04-01

    Data-driven methods such as neural networks (NNs) are a powerful tool to retrieve soil moisture from multi-wavelength remote sensing observations at global scale. In this presentation we will review a number of recent results regarding the retrieval of soil moisture with the Soil Moisture and Ocean Salinity (SMOS) satellite, either using SMOS brightness temperatures as input data for the retrieval or using SMOS soil moisture retrievals as reference dataset for the training. The presentation will discuss several possibilities for both the input datasets and the datasets to be used as reference for the supervised learning phase. Regarding the input datasets, it will be shown that NNs take advantage of the synergy of SMOS data and data from other sensors such as the Advanced Scatterometer (ASCAT, active microwaves) and MODIS (visible and infra red). NNs have also been successfully used to construct long time series of soil moisture from the Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) and SMOS. A NN with input data from ASMR-E observations and SMOS soil moisture as reference for the training was used to construct a dataset sharing a similar climatology and without a significant bias with respect to SMOS soil moisture. Regarding the reference data to train the data-driven retrievals, we will show different possibilities depending on the application. Using actual in situ measurements is challenging at global scale due to the scarce distribution of sensors. In contrast, in situ measurements have been successfully used to retrieve SM at continental scale in North America, where the density of in situ measurement stations is high. Using global land surface models to train the NN constitute an interesting alternative to implement new remote sensing surface datasets. In addition, these datasets can be used to perform data assimilation into the model used as reference for the training. This approach has recently been tested at the European Centre

  9. Optimizing Soil Moisture Sampling Locations for Validation Networks for SMAP

    Science.gov (United States)

    Roshani, E.; Berg, A. A.; Lindsay, J.

    2013-12-01

    Soil Moisture Active Passive satellite (SMAP) is scheduled for launch on Oct 2014. Global efforts are underway for establishment of soil moisture monitoring networks for both the pre- and post-launch validation and calibration of the SMAP products. In 2012 the SMAP Validation Experiment, SMAPVEX12, took place near Carman Manitoba, Canada where nearly 60 fields were sampled continuously over a 6 week period for soil moisture and several other parameters simultaneous to remotely sensed images of the sampling region. The locations of these sampling sites were mainly selected on the basis of accessibility, soil texture, and vegetation cover. Although these criteria are necessary to consider during sampling site selection, they do not guarantee optimal site placement to provide the most efficient representation of the studied area. In this analysis a method for optimization of sampling locations is presented which combines the state-of-art multi-objective optimization engine (non-dominated sorting genetic algorithm, NSGA-II), with the kriging interpolation technique to minimize the number of sampling sites while simultaneously minimizing the differences between the soil moisture map resulted from the kriging interpolation and soil moisture map from radar imaging. The algorithm is implemented in Whitebox Geospatial Analysis Tools, which is a multi-platform open-source GIS. The optimization framework is subject to the following three constraints:. A) sampling sites should be accessible to the crew on the ground, B) the number of sites located in a specific soil texture should be greater than or equal to a minimum value, and finally C) the number of sampling sites with a specific vegetation cover should be greater than or equal to a minimum constraint. The first constraint is implemented into the proposed model to keep the practicality of the approach. The second and third constraints are considered to guarantee that the collected samples from each soil texture categories

  10. Relationships between some soil physical and chemical properties with magnetic properties in different soil moisture regimes in Golestan province

    Directory of Open Access Journals (Sweden)

    M. Valaee

    2016-09-01

    Full Text Available Introduction: Soil moisture regime refers to the presence or absence either of ground water or of water held at a tension of less than 1500 kPa in the soil or in specific horizons during periods of the year. It is the most important factor in soil formation, soil evolution and fertility affecting on crop production and management. Also, it widely is practical in soil classification and soil mapping. The soil moisture regime depends on the soil properties, climatic and weather conditions, characteristics of natural plant formations and, in cultivated soils, is affected by the characteristics of crops grown, as well as the cultivation practices. Determination of soil moisture regime within a landscape scale requires high information and data about moisture balance of soil profile during some years according to Soil Survey Manual (2010. This approach is very expensive, labor, time and cost consuming. Therefore, achievement to an alternative approach is seems essential to overcome these problems. The main hypothesis of this study was to use capability of magnetic susceptibility as a cheap and rapid technique could determine the soil moisture regimes. Magnetic properties of soils reflect the impacts of soil mineral composition, particularly the quantity of ferrimagnetic minerals such as maghemite and magnetite. Magnetic susceptibility measurements can serve a variety of applications including the changes in soil forming processes and ecological services, understanding of lithological effects, insight of sedimentation processes and soil drainage. Materials and Methods: This study was conducted in an area located between 36°46َ 10˝ and 37° 2’ 28˝ N latitudes, and 54° 29’ 31˝ and 55° 12’ 47˝ E longitudes in Golestan province, northern Iran. In the study region mean annual temperature varies from 12.4 to 19.4 °C. The average annual rainfall and evapotranspiration varies from 230 mm and 2335 mm in Inchebrun district (Aridic regime, to 732

  11. Towards an integrated soil moisture drought monitor for East Africa

    Directory of Open Access Journals (Sweden)

    W. B. Anderson

    2012-08-01

    Full Text Available Drought in East Africa is a recurring phenomenon with significant humanitarian impacts. Given the steep climatic gradients, topographic contrasts, general data scarcity, and, in places, political instability that characterize the region, there is a need for spatially distributed, remotely derived monitoring systems to inform national and international drought response. At the same time, the very diversity and data scarcity that necessitate remote monitoring also make it difficult to evaluate the reliability of these systems. Here we apply a suite of remote monitoring techniques to characterize the temporal and spatial evolution of the 2010–2011 Horn of Africa drought. Diverse satellite observations allow for evaluation of meteorological, agricultural, and hydrological aspects of drought, each of which is of interest to different stakeholders. Focusing on soil moisture, we apply triple collocation analysis (TCA to three independent methods for estimating soil moisture anomalies to characterize relative error between products and to provide a basis for objective data merging. The three soil moisture methods evaluated include microwave remote sensing using the Advanced Microwave Scanning Radiometer – Earth Observing System (AMSR-E sensor, thermal remote sensing using the Atmosphere-Land Exchange Inverse (ALEXI surface energy balance algorithm, and physically based land surface modeling using the Noah land surface model. It was found that the three soil moisture monitoring methods yield similar drought anomaly estimates in areas characterized by extremely low or by moderate vegetation cover, particularly during the below-average 2011 long rainy season. Systematic discrepancies were found, however, in regions of moderately low vegetation cover and high vegetation cover, especially during the failed 2010 short rains. The merged, TCA-weighted soil moisture composite product takes advantage of the relative strengths of each method, as judged by the

  12. Data Assimilation to Extract Soil Moisture Information from SMAP Observations

    Directory of Open Access Journals (Sweden)

    Jana Kolassa

    2017-11-01

    Full Text Available This study compares different methods to extract soil moisture information through the assimilation of Soil Moisture Active Passive (SMAP observations. Neural network (NN and physically-based SMAP soil moisture retrievals were assimilated into the National Aeronautics and Space Administration (NASA Catchment model over the contiguous United States for April 2015 to March 2017. By construction, the NN retrievals are consistent with the global climatology of the Catchment model soil moisture. Assimilating the NN retrievals without further bias correction improved the surface and root zone correlations against in situ measurements from 14 SMAP core validation sites (CVS by 0.12 and 0.16, respectively, over the model-only skill, and reduced the surface and root zone unbiased root-mean-square error (ubRMSE by 0.005 m 3 m − 3 and 0.001 m 3 m − 3 , respectively. The assimilation reduced the average absolute surface bias against the CVS measurements by 0.009 m 3 m − 3 , but increased the root zone bias by 0.014 m 3 m − 3 . Assimilating the NN retrievals after a localized bias correction yielded slightly lower surface correlation and ubRMSE improvements, but generally the skill differences were small. The assimilation of the physically-based SMAP Level-2 passive soil moisture retrievals using a global bias correction yielded similar skill improvements, as did the direct assimilation of locally bias-corrected SMAP brightness temperatures within the SMAP Level-4 soil moisture algorithm. The results show that global bias correction methods may be able to extract more independent information from SMAP observations compared to local bias correction methods, but without accurate quality control and observation error characterization they are also more vulnerable to adverse effects from retrieval errors related to uncertainties in the retrieval inputs and algorithm. Furthermore, the results show that using global bias correction approaches without a

  13. Finally It Is Possible To Measure Area-Average Soil Moisture!

    Science.gov (United States)

    Shuttleworth, W. J.; Zreda, M. G.; Zeng, X.; Zweck, C.; Franz, T. E.; Rosolem, R.

    2011-12-01

    When a hitherto impossible measurement becomes possible, there are transformational changes in understanding. Measuring soil moisture using cosmic rays sounds like 1950s science fiction. But the non-invasive measurement of soil moisture at a horizontal scale of ~700m and depths of 15-70 cm is now feasible, by counting cosmic-ray neutrons that are generated within soil, moderated mainly by the hydrogen atoms, and emitted back to the atmosphere. The number of neutrons counted is sensitive to water content changes, only weakly sensitive to soil chemistry, and their intensity is inversely correlated with the hydrogen (i.e., water) content of the soil. Neither the basis of this measurement method nor the sensor technology used is new, they have been around for decades. However, the systematic understanding of cosmic-ray interactions at the ground-atmosphere interface and resulting knowledge of the source "footprint" of above ground neutron detectors and recognition of their limited of sensitivity to soil type in selected neutron energy bands is new, as is the low power electronics used for remote signal conditioning, counting and data capture. The measurement with a portable neutron detector placed above the ground takes minutes to hours, permitting high-resolution, long-term monitoring of undisturbed soil moisture. The large footprint makes the method suitable for weather and short-term climate forecast initialization and satellite validation, while the measurement depth makes the probe ideal for studying plant/soil/atmosphere interactions. Inclusion of a second detector that is sensitive to neutrons with lower energy shows promise as a means for detecting snow cover. This talk briefly overviews evidence that soil moisture status can potentially influence weather and seasonal climate and describe the COsmic-ray Soil Moisture Observing System (COSMOS), which observing program will install initially a network of 50 probes (to provide a proof of concept) and subsequently

  14. Spatial Variability of Soil-Water Storage in the Southern Sierra Critical Zone Observatory: Measurement and Prediction

    Science.gov (United States)

    Oroza, C.; Bales, R. C.; Zheng, Z.; Glaser, S. D.

    2017-12-01

    Predicting the spatial distribution of soil moisture in mountain environments is confounded by multiple factors, including complex topography, spatial variably of soil texture, sub-surface flow paths, and snow-soil interactions. While remote-sensing tools such as passive-microwave monitoring can measure spatial variability of soil moisture, they only capture near-surface soil layers. Large-scale sensor networks are increasingly providing soil-moisture measurements at high temporal resolution across a broader range of depths than are accessible from remote sensing. It may be possible to combine these in-situ measurements with high-resolution LIDAR topography and canopy cover to estimate the spatial distribution of soil moisture at high spatial resolution at multiple depths. We study the feasibility of this approach using six years (2009-2014) of daily volumetric water content measurements at 10-, 30-, and 60-cm depths from the Southern Sierra Critical Zone Observatory. A non-parametric, multivariate regression algorithm, Random Forest, was used to predict the spatial distribution of depth-integrated soil-water storage, based on the in-situ measurements and a combination of node attributes (topographic wetness, northness, elevation, soil texture, and location with respect to canopy cover). We observe predictable patterns of predictor accuracy and independent variable ranking during the six-year study period. Predictor accuracy is highest during the snow-cover and early recession periods but declines during the dry period. Soil texture has consistently high feature importance. Other landscape attributes exhibit seasonal trends: northness peaks during the wet-up period, and elevation and topographic-wetness index peak during the recession and dry period, respectively.

  15. Characterization of Soil Moisture Level for Rice and Maize Crops using GSM Shield and Arduino Microcontroller

    Science.gov (United States)

    Gines, G. A.; Bea, J. G.; Palaoag, T. D.

    2018-03-01

    Soil serves a medium for plants growth. One factor that affects soil moisture is drought. Drought has been a major cause of agricultural disaster. Agricultural drought is said to occur when soil moisture is insufficient to meet crop water requirements, resulting in yield losses. In this research, it aimed to characterize soil moisture level for Rice and Maize Crops using Arduino and applying fuzzy logic. System architecture for soil moisture sensor and water pump were the basis in developing the equipment. The data gathered was characterized by applying fuzzy logic. Based on the results, applying fuzzy logic in validating the characterization of soil moisture level for Rice and Maize crops is accurate as attested by the experts. This will help the farmers in monitoring the soil moisture level of the Rice and Maize crops.

  16. Bioactivity of Several Herbicides on the Nanogram Level Under Different Soil Moisture Conditions.

    Science.gov (United States)

    Jung, S C; Kuk, Y I; Senseman, S A; Ahn, H G; Seong, C N; Lee, D J

    2015-01-01

    In this study, a double-tube centrifuge method was employed to determine the effects of soil moisture on the bioactivity of cafenstrole, pretilachlor, benfuresate, oxyfluorfen and simetryn. In general, the available herbicide concentration in soil solution (ACSS) showed little change as soil moisture increased for herbicides. The total available herbicide in soil solution (TASS) typically increased as soil moisture increased for all herbicides. The relationship between TASS and % growth rate based on dry weight showed strong linear relationships for both cafenstrole and pretilachlor, with r2 values of 0.95 and 0.84, respectively. Increasing TASS values were consistent with increasing herbicide water solubility, with the exception of the ionizable herbicide simetryn. Plant absorption and % growth rate exhibited a strong linear relationship with TASS. According to the results suggested that TASS was a better predictor of herbicidal bioactivity than ACSS for all herbicides under unsaturated soil moisture conditions.

  17. Spatio-temporal soil moisture variability in Southwest Germany observed with a new monitoring network within the COPS domain

    Energy Technology Data Exchange (ETDEWEB)

    Krauss, Liane; Kottmeier, Christoph [Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany). Inst. for Meteorology and Climate Research; Hauck, Christian [Karlsruhe Institute of Technology (KIT), Karlsruhe (Germany). Inst. for Meteorology and Climate Research; Fribourg Univ. (Switzerland). Dept. of Geosciences

    2010-12-15

    Within the 'Convective and Orographically-induced Precipitation Study' (COPS) 2007 in Southwest Germany and Northeast France a soil moisture monitoring network was installed. The aim of the network is to identify the interaction between the temporal and spatial variability of the soil moisture field and its influence on the energy balance and the moisture availability in the planetary boundary layer. The network is comprised of a large number of newly developed low-cost soil moisture sensors based on the frequency-domain reflectometry method (FDR). In total 47 soil moisture stations within the COPS domain were each equipped with two to four sensors simultaneously measuring vertical profiles of soil moisture and soil temperature down to 50 cm depth. This contribution describes the soil moisture network, its installation procedure and the calibration of the sensor output signal. Furthermore we discuss the soil texture distribution within the study area and present first analyses of the spatio-temporal soil moisture variability during a 13 month period from June 2007 till June 2008 based on regional differences and site specific properties (altitude and soil texture). Results show that the altitude plays a key role for the overall soil moisture pattern relative to the area mean due to the direct linkage to precipitation patterns. Soil texture controls the vertical soil moisture gradient relative to the near surface soil moisture, as their properties control water storage and drainage characteristics. Both factors significantly influence regional soil moisture patterns in Southwest Germany. (orig.)

  18. Numerical Investigations of Moisture Distribution in a Selected Anisotropic Soil Medium

    Science.gov (United States)

    Iwanek, M.

    2018-01-01

    The moisture of soil profile changes both in time and space and depends on many factors. Changes of the quantity of water in soil can be determined on the basis of in situ measurements, but numerical methods are increasingly used for this purpose. The quality of the results obtained using pertinent software packages depends on appropriate description and parameterization of soil medium. Thus, the issue of providing for the soil anisotropy phenomenon gains a big importance. Although anisotropy can be taken into account in many numerical models, isotopic soil is often assumed in the research process. However, this assumption can be a reason for incorrect results in the simulations of water changes in soil medium. In this article, results of numerical simulations of moisture distribution in the selected soil profile were presented. The calculations were conducted assuming isotropic and anisotropic conditions. Empirical verification of the results obtained in the numerical investigations indicated statistical essential discrepancies for the both analyzed conditions. However, better fitting measured and calculated moisture values was obtained for the case of providing for anisotropy in the simulation model.

  19. Large-area Soil Moisture Surveys Using a Cosmic-ray Rover: Approaches and Results from Australia

    Science.gov (United States)

    Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.

    2017-12-01

    Recent improvements in satellite instrumentation has increased the resolution and frequency of soil moisture observations, and this in turn has supported the development of higher resolution land surface process models. Calibration and validation of these products is restricted by the mismatch of scales between remotely sensed and contemporary ground based observations. Although the cosmic ray neutron soil moisture probe can provide estimates soil moisture at a scale useful for the calibration and validation purposes, it is spatially limited to a single, fixed location. This scaling issue has been addressed with the development of mobile soil moisture monitoring systems that utilizes the cosmic ray neutron method, typically referred to as a `rover'. This manuscript describes a project designed to develop approaches for undertaking rover surveys to produce soil moisture estimates at scales comparable to satellite observations and land surface process models. A custom designed, trailer-mounted rover was used to conduct repeat surveys at two scales in the Mallee region of Victoria, Australia. A broad scale survey was conducted at 36 x 36 km covering an area of a standard SMAP pixel and an intensive scale survey was conducted over a 10 x 10 km portion of the broad scale survey, which is at a scale equivalent to that used for national water balance modelling. We will describe the design of the rover, the methods used for converting neutron counts into soil moisture and discuss factors controlling soil moisture variability. We found that the intensive scale rover surveys produced reliable soil moisture estimates at 1 km resolution and the broad scale at 9 km resolution. We conclude that these products are well suited for future analysis of satellite soil moisture retrievals and finer scale soil moisture models.

  20. Prediction of snowmelt infiltration into frozen soils

    International Nuclear Information System (INIS)

    Tao, Y.X.; Gray, D.M.

    1994-01-01

    A numerical model is presented, based on the local volume averaging formulation of transport phenomena in porous media, for simulating meltwater infiltration into unsaturated, frozen soil. With the defined flow and freezing boundary conditions at the snow-soil interface, using the concept of a surface local averaging volume, the time variation in profiles of temperature, liquid/ice content, infiltration/percolation rates, and rate of phase change in upper soil layers are predicted. In addition to a parametric analysis, model estimates of infiltration are compared with quantities calculated from field measurements of soil moisture changes and temperature during snow cover ablation, showing a reasonable agreement

  1. A study of soil moisture variability for landmine detection by the neutron technique

    OpenAIRE

    Avdić Senada

    2007-01-01

    This paper is focused on the space and temporal variability of soil moisture experimental data acquired at a few locations near landmine fields in the Tuzla Canton, as well as on the quantification of the statistical nature of soil moisture data on a small spatial scale. Measurements of soil water content at the surface were performed by an electro-magnetic sensor over 1 25, and 100 m2 grids, at intervals of 0.2, 0.5, and 1 m, respectively. The sampling of soil moisture at different spatial r...

  2. Soil hydraulic parameters and surface soil moisture of a tilled bare soil plot inversely derived from l-band brightness temperatures

    KAUST Repository

    Dimitrov, Marin

    2014-01-01

    We coupled a radiative transfer model and a soil hydrologic model (HYDRUS 1D) with an optimization routine to derive soil hydraulic parameters, surface roughness, and soil moisture of a tilled bare soil plot using measured brightness temperatures at 1.4 GHz (L-band), rainfall, and potential soil evaporation. The robustness of the approach was evaluated using five 28-d data sets representing different meteorological conditions. We considered two soil hydraulic property models: the unimodal Mualem-van Genuchten and the bimodal model of Durner. Microwave radiative transfer was modeled by three different approaches: the Fresnel equation with depth-averaged dielectric permittivity of either 2-or 5-cm-thick surface layers and a coherent radiative transfer model (CRTM) that accounts for vertical gradients in dielectric permittivity. Brightness temperatures simulated by the CRTM and the 2-cm-layer Fresnel model fitted well to the measured ones. L-band brightness temperatures are therefore related to the dielectric permittivity and soil moisture in a 2-cm-thick surface layer. The surface roughness parameter that was derived from brightness temperatures using inverse modeling was similar to direct estimates from laser profiler measurements. The laboratory-derived water retention curve was bimodal and could be retrieved consistently for the different periods from brightness temperatures using inverse modeling. A unimodal soil hydraulic property function underestimated the hydraulic conductivity near saturation. Surface soil moisture contents simulated using retrieved soil hydraulic parameters were compared with in situ measurements. Depth-specific calibration relations were essential to derive soil moisture from near-surface installed sensors. © Soil Science Society of America 5585 Guilford Rd., Madison, WI 53711 USA.

  3. Global Assessment of the SMAP Level-4 Soil Moisture Product Using Assimilation Diagnostics

    Science.gov (United States)

    Reichle, Rolf; Liu, Qing; De Lannoy, Gabrielle; Crow, Wade; Kimball, John; Koster, Randy; Ardizzone, Joe

    2018-01-01

    The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx. 2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

  4. Using Data Assimilation Diagnostics to Assess the SMAP Level-4 Soil Moisture Product

    Science.gov (United States)

    Reichle, Rolf; Liu, Qing; De Lannoy, Gabrielle; Crow, Wade; Kimball, John; Koster, Randy; Ardizzone, Joe

    2018-01-01

    The Soil Moisture Active Passive (SMAP) mission Level-4 Soil Moisture (L4_SM) product provides 3-hourly, 9-km resolution, global estimates of surface (0-5 cm) and root-zone (0-100 cm) soil moisture and related land surface variables from 31 March 2015 to present with approx.2.5-day latency. The ensemble-based L4_SM algorithm assimilates SMAP brightness temperature (Tb) observations into the Catchment land surface model. This study describes the spatially distributed L4_SM analysis and assesses the observation-minus-forecast (O-F) Tb residuals and the soil moisture and temperature analysis increments. Owing to the climatological rescaling of the Tb observations prior to assimilation, the analysis is essentially unbiased, with global mean values of approx. 0.37 K for the O-F Tb residuals and practically zero for the soil moisture and temperature increments. There are, however, modest regional (absolute) biases in the O-F residuals (under approx. 3 K), the soil moisture increments (under approx. 0.01 cu m/cu m), and the surface soil temperature increments (under approx. 1 K). Typical instantaneous values are approx. 6 K for O-F residuals, approx. 0.01 (approx. 0.003) cu m/cu m for surface (root-zone) soil moisture increments, and approx. 0.6 K for surface soil temperature increments. The O-F diagnostics indicate that the actual errors in the system are overestimated in deserts and densely vegetated regions and underestimated in agricultural regions and transition zones between dry and wet climates. The O-F auto-correlations suggest that the SMAP observations are used efficiently in western North America, the Sahel, and Australia, but not in many forested regions and the high northern latitudes. A case study in Australia demonstrates that assimilating SMAP observations successfully corrects short-term errors in the L4_SM rainfall forcing.

  5. Sensitivity of soil respiration to variability in soil moisture and temperature in a humid tropical forest

    Science.gov (United States)

    Tana Wood; M. Detto; W.L. Silver

    2013-01-01

    Precipitation and temperature are important drivers of soil respiration. The role of moisture and temperature are generally explored at seasonal or inter-annual timescales; however, significant variability also occurs on hourly to daily time-scales. We used small (1.54 m2), throughfall exclusion shelters to evaluate the role soil moisture and temperature as temporal...

  6. Soil Moisture Retrieval and Spatiotemporal Pattern Analysis Using Sentinel-1 Data of Dahra, Senegal

    Directory of Open Access Journals (Sweden)

    Zhiqu Liu

    2017-11-01

    Full Text Available The spatiotemporal pattern of soil moisture is of great significance for the understanding of the water exchange between the land surface and the atmosphere. The two-satellite constellation of the Sentinel-1 mission provides C-band synthetic aperture radar (SAR observations with high spatial and temporal resolutions, which are suitable for soil moisture monitoring. In this paper, we aim to assess the capability of pattern analysis based on the soil moisture retrieved from Sentinel-1 time-series data of Dahra in Senegal. The look-up table (LUT method is used in the retrieval with the backscattering coefficients that are simulated by the advanced integrated equation Model (AIEM for the soil layer and the Michigan microwave canopy scattering (MIMICS model for the vegetation layer. The temporal trend of Sentinel-1A soil moisture is evaluated by the ground measurements from the site at Dahra, with an unbiased root-mean-squared deviation (ubRMSD of 0.053 m3/m3, a mean average deviation (MAD of 0.034 m3/m3, and an R value of 0.62. The spatial variation is also compared with the existing microwave products at a coarse scale, which confirms the reliability of the Sentinel-1A soil moisture. The spatiotemporal patterns are analyzed by empirical orthogonal functions (EOF, and the geophysical factors that are affecting soil moisture are discussed. The first four EOFs of soil moisture explain 77.2% of the variance in total and the primary EOF explains 66.2%, which shows the dominant pattern at the study site. Soil texture and the normalized difference vegetation index are more closely correlated with the primary pattern than the topography and temperature in the study area. The investigation confirms the potential for soil moisture retrieval and spatiotemporal pattern analysis using Sentinel-1 images.

  7. An Arduino Based Citizen Science Soil Moisture Sensor in Support of SMAP and GLOBE

    Science.gov (United States)

    Podest, E.; Das, N. N.; Rajasekaran, E.; Jeyaram, R.; Lohrli, C.; Hovhannesian, H.; Fairbanks, G.

    2017-12-01

    Citizen science allows individuals anywhere in the world to engage in science by collecting environmental variables. One of the longest running platforms for the collection of in situ variables is the GLOBE program, which is international in scope and encourages students and citizen scientists alike to collect in situ measurements. NASA's Soil Moisture Active Passive (SMAP) satellite mission, which has been acquiring global soil moisture measurements every 3 days of the top 5 cm of the soil since 2015, has partnered with the GLOBE program to engage students from around the world to collect in situ soil moisture and help validate SMAP measurements. The current GLOBE SMAP soil moisture protocol consists in collecting a soil sample, weighing, drying and weighing it again in order to determine the amount of water in the soil. Preparation and soil sample collection can take up to 20 minutes and drying can take up to 3 days. We have hence developed a soil moisture measurement device based on Arduino- microcontrollers along with off-the-shelf and homemade sensors that are accurate, robust, inexpensive and quick and easy to use so that they can be implemented by the GLOBE community and citizen scientists alike. In addition, we have developed a phone app, which interfaces with the Arduino, displays the soil moisture value and send the measurement to the GLOBE database. This talk will discuss building, calibration and validation of the soil moisture measuring device and assessing the quality of the measurements collected. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under contract with the National Aeronautics and Space Administration.

  8. Seasonal soil moisture patterns in contrasting habitats in the Willamette Valley, Oregon

    Science.gov (United States)

    Changing seasonal soil moisture regimes caused by global warming may alter plant community composition in sensitive habitats such as wetlands and oak savannas. To evaluate such changes, an understanding of typical seasonal soil moisture regimes is necessary. The primary objective...

  9. Interaction between Soil Moisture and Air Temperature in the Mississippi River Basin

    Science.gov (United States)

    Increasing air temperatures are expected to continue in the future. The relation between soil moisture and near surface air temperature is significant for climate change and climate extremes. Evaluation of the relations between soil moisture and temperature was performed by devel...

  10. New technique of insitu soil moisture sampling for environmental isotope analysis applied at 'Pilat-dune' near Bordeaux

    International Nuclear Information System (INIS)

    Thoma, G.; Esser, N.; Sonntag, C.; Weiss, W.; Rudolph, J.; Leveque, P.

    1978-01-01

    A new soil-air suction method with soil water vapor adsorption by 4 A-molecular sieve provides soil moisture samples from various depths for environmental isotope analysis and yields soil temperature profiles. A field tritium tracer experiment shows that this insitu sampling method has an isotope profile resolution of about 5-10 cm only. Application of this method in the Pilat sand dune (Bordeaux/France) yielded deuterium and tritium profiles down to 25 meters depth. Bomb tritium measurements of monthly lysimeter percolate samples available since 1961 show that the tritium response has a mean delay of 5 months in case of a sand lysimeter and of 2.5 years for a loess loam lysimeter. A simple HETP model simulates the layered downward movement of soil water and the longitudinal dispersion in the lysimeters. Field capacity and evapotranspiration taken as open parameters yield tritium concentration values of the lysimeters' percolate which are in close agreement with the experimental results. Based on local meteorological data the HETP model applied to tritium tracer experiments in the unsaturated zone further yiels an individual prediction of the momentary tracer position and of the soil moisture distribution. This prediction can be checked experimentally at selected intervals by coring. (orig.) [de

  11. Analysis of spatiotemporal soil moisture patterns at the catchment scale using a wireless sensor network

    Science.gov (United States)

    Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry

    2010-05-01

    Soil water content plays a key role in partitioning water and energy fluxes and controlling the pattern of groundwater recharge. Despite the importance of soil water content, it is not yet measured in an operational way at larger scales. The aim of this paper is to present the potential of real-time monitoring for the analysis of soil moisture patterns at the catchment scale using the recently developed wireless sensor network SoilNet [1], [2]. SoilNet is designed to measure soil moisture, salinity and temperature in several depths (e.g. 5, 20 and 50 cm). Recently, a small forest catchment Wüstebach (~27 ha) has been instrumented with 150 sensor nodes and more than 1200 soil sensors in the framework of the Transregio32 and the Helmholtz initiative TERENO (Terrestrial Environmental Observatories). From August to November 2009, more than 6 million soil moisture measurements have been performed. We will present first results from a statistical and geostatistical analysis of the data. The observed spatial variability of soil moisture corresponds well with the 800-m scale variability described in [3]. The very low scattering of the standard deviation versus mean soil moisture plots indicates that sensor network data shows less artificial soil moisture variations than soil moisture data originated from measurement campaigns. The variograms showed more or less the same nugget effect, which indicates that the sum of the sub-scale variability and the measurement error is rather time-invariant. Wet situations showed smaller spatial variability, which is attributed to saturated soil water content, which poses an upper limit and is typically not strongly variable in headwater catchments with relatively homogeneous soil. The spatiotemporal variability in soil moisture at 50 cm depth was significantly lower than at 5 and 20 cm. This finding indicates that the considerable variability of the top soil is buffered deeper in the soil due to lateral and vertical water fluxes

  12. Examining the relationship between intermediate scale soil moisture and terrestrial evaporation within a semi-arid grassland

    KAUST Repository

    Jana, Raghavendra Belur

    2016-05-17

    Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale-mismatch when compared to coarser-resolution satellite-based soil moisture or evaporation estimates. The Cosmic Ray Soil Moisture Observing System (COSMOS) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here we present an examination of the links observed between COSMOS soil moisture retrievals and evaporation estimates over a pasture in the semi-arid central-west region of New South Wales, Australia. The COSMOS soil moisture product was compared to evaporation derived from three distinct approaches, including the Priestley-Taylor (PT-JPL), Penman-Monteith (PM-Mu) and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson’s Correlations, Quantile-Quantile (Q-Q) plots, and Analysis of Variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly two years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q-Q plots and ANOVA illustrate that the root-zone soil moisture represented by the COSMOS measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold

  13. The effect of row structure on soil moisture retrieval accuracy from passive microwave data.

    Science.gov (United States)

    Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding

    2014-01-01

    Row structure causes the anisotropy of microwave brightness temperature (TB) of soil surface, and it also can affect soil moisture retrieval accuracy when its influence is ignored in the inversion model. To study the effect of typical row structure on the retrieved soil moisture and evaluate if there is a need to introduce this effect into the inversion model, two ground-based experiments were carried out in 2011. Based on the observed C-band TB, field soil and vegetation parameters, row structure rough surface assumption (Q p model and discrete model), including the effect of row structure, and flat rough surface assumption (Q p model), ignoring the effect of row structure, are used to model microwave TB of soil surface. Then, soil moisture can be retrieved, respectively, by minimizing the difference of the measured and modeled TB. The results show that soil moisture retrieval accuracy based on the row structure rough surface assumption is approximately 0.02 cm(3)/cm(3) better than the flat rough surface assumption for vegetated soil, as well as 0.015 cm(3)/cm(3) better for bare and wet soil. This result indicates that the effect of row structure cannot be ignored for accurately retrieving soil moisture of farmland surface when C-band is used.

  14. Statistical techniques to extract information during SMAP soil moisture assimilation

    Science.gov (United States)

    Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.

    2017-12-01

    Statistical techniques permit the retrieval of soil moisture estimates in a model climatology while retaining the spatial and temporal signatures of the satellite observations. As a consequence, the need for bias correction prior to an assimilation of these estimates is reduced, which could result in a more effective use of the independent information provided by the satellite observations. In this study, a statistical neural network (NN) retrieval algorithm is calibrated using SMAP brightness temperature observations and modeled soil moisture estimates (similar to those used to calibrate the SMAP Level 4 DA system). Daily values of surface soil moisture are estimated using the NN and then assimilated into the NASA Catchment model. The skill of the assimilation estimates is assessed based on a comprehensive comparison to in situ measurements from the SMAP core and sparse network sites as well as the International Soil Moisture Network. The NN retrieval assimilation is found to significantly improve the model skill, particularly in areas where the model does not represent processes related to agricultural practices. Additionally, the NN method is compared to assimilation experiments using traditional bias correction techniques. The NN retrieval assimilation is found to more effectively use the independent information provided by SMAP resulting in larger model skill improvements than assimilation experiments using traditional bias correction techniques.

  15. Dynamics and characteristics of soil temperature and moisture of active layer in central Tibetan Plateau

    Science.gov (United States)

    Zhao, L.; Hu, G.; Wu, X.; Tian, L.

    2017-12-01

    Research on the hydrothermal properties of active layer during the thawing and freezing processes was considered as a key question to revealing the heat and moisture exchanges between permafrost and atmosphere. The characteristics of freezing and thawing processes at Tanggula (TGL) site in permafrost regions on the Tibetan Plateau, the results revealed that the depth of daily soil temperature transmission was about 40 cm shallower during thawing period than that during the freezing period. Soil warming process at the depth above 140 cm was slower than the cooling process, whereas they were close below 140 cm depth. Moreover, the hydro-thermal properties differed significantly among different stages. Precipitation caused an obviously increase in soil moisture at 0-20 cm depth. The vertical distribution of soil moisture could be divided into two main zones: less than 12% in the freeze state and greater than 12% in the thaw state. In addition, coupling of moisture and heat during the freezing and thawing processes also showed that soil temperature decreased faster than soil moisture during the freezing process. At the freezing stage, soil moisture exhibited an exponential relationship with the absolute soil temperature. Energy consumed for water-ice conversion during the freezing process was 149.83 MJ/m2 and 141.22 MJ/m2 in 2011 and 2012, respectively, which was estimated by the soil moisture variation.

  16. AirMOSS P-Band Radar Retrieval of Subcanopy Soil Moisture Profile

    Science.gov (United States)

    Tabatabaeenejad, A.; Burgin, M. S.; Duan, X.; Moghaddam, M.

    2013-12-01

    Knowledge of soil moisture, as a key variable of the Earth system, plays an important role in our under-standing of the global water, energy, and carbon cycles. The importance of such knowledge has led NASA to fund missions such as Soil Moisture Active and Passive (SMAP) and Airborne Microwave Observatory of Subcanopy and Subsurface (AirMOSS). The AirMOSS mission seeks to improve the estimates of the North American Net Ecosystem Exchange (NEE) by providing high-resolution observations of the root zone soil moisture (RZSM) over regions representative of the major North American biomes. AirMOSS flies a P-band SAR to penetrate vegetation and into the root zone to provide estimates of RZSM. The flights cover areas containing flux tower sites in regions from the boreal forests in Saskatchewan, Canada, to the tropical forests in La Selva, Costa Rica. The radar snapshots are used to generate estimates of RZSM via inversion of a scattering model of vegetation overlying soils with variable moisture profiles. These retrievals will be used to generate a time record of RZSM, which will be integrated with an ecosystem demography model in order to estimate the respiration and photosynthesis carbon fluxes. The aim of this work is the retrieval of the moisture profile over AirMOSS sites using the collected P-band radar data. We have integrated layered-soil scattering models into a forest scattering model; for the backscattering from ground and for the trunk-ground double-bounce mechanism, we have used a layered small perturbation method and a coherent scattering model of layered soil, respectively. To estimate the soil moisture profile, we represent it as a second-order polynomial in the form of az2 + bz + c, where z is the depth and a, b, and c are the coefficients to be retrieved from radar measurements. When retrieved, these coefficients give us the soil moisture up to a prescribed depth of validity. To estimate the unknown coefficients of the polynomial, we use simulated

  17. Analysis of surface soil moisture patterns in agricultural landscapes using Empirical Orthogonal Functions

    Directory of Open Access Journals (Sweden)

    W. Korres

    2010-05-01

    Full Text Available Soil moisture is one of the fundamental variables in hydrology, meteorology and agriculture. Nevertheless, its spatio-temporal patterns in agriculturally used landscapes that are affected by multiple natural (rainfall, soil, topography etc. and agronomic (fertilisation, soil management etc. factors are often not well known. The aim of this study is to determine the dominant factors governing the spatio-temporal patterns of surface soil moisture in a grassland and an arable test site that are located within the Rur catchment in Western Germany. Surface soil moisture (0–6 cm was measured in an approx. 50×50 m grid during 14 and 17 measurement campaigns (May 2007 to November 2008 in both test sites. To analyse the spatio-temporal patterns of surface soil moisture, an Empirical Orthogonal Function (EOF analysis was applied and the results were correlated with parameters derived from topography, soil, vegetation and land management to link the patterns to related factors and processes. For the grassland test site, the analysis resulted in one significant spatial structure (first EOF, which explained 57.5% of the spatial variability connected to soil properties and topography. The statistical weight of the first spatial EOF is stronger on wet days. The highest temporal variability can be found in locations with a high percentage of soil organic carbon (SOC. For the arable test site, the analysis resulted in two significant spatial structures, the first EOF, which explained 38.4% of the spatial variability, and showed a highly significant correlation to soil properties, namely soil texture and soil stone content. The second EOF, which explained 28.3% of the spatial variability, is linked to differences in land management. The soil moisture in the arable test site varied more strongly during dry and wet periods at locations with low porosity. The method applied is capable of identifying the dominant parameters controlling spatio-temporal patterns of

  18. Fostering Application Opportunites for the NASA Soil Moisture Active Passive (SMAP) Mission

    Science.gov (United States)

    Moran, M. Susan; O'Neill, Peggy E.; Entekhabi, Dara; Njoku, Eni G.; Kellogg, Kent H.

    2010-01-01

    The NASA Soil Moisture Active Passive (SMAP) Mission will provide global observations of soil moisture and freeze/thaw state from space. We outline how priority applications contributed to the SMAP mission measurement requirements and how the SMAP mission plans to foster applications and applied science.

  19. The potentiation of zinc toxicity by soil moisture in a boreal forest ecosystem.

    Science.gov (United States)

    Owojori, Olugbenga J; Siciliano, Steven D

    2015-03-01

    Northern boreal forests often experience forest dieback as a result of metal ore mining and smelting. The common solution is to lime the soil, which increases pH, reducing metal toxicity and encouraging recovery. In certain situations, however, such as in Flin Flon, Manitoba, Canada, liming has yielded only moderate benefits, with some locations responding well to liming and other locations not at all. In an effort to increase the effectiveness of the ecorestoration strategy, the authors investigated if these differences in liming responsiveness were linked to differences in toxicity. Toxicity of metal-impacted Flin Flon soils on the oribatid mite Oppia nitens and the collembolan Folsomia candida was assessed, with a view toward identifying the metal of concern in the area. The effects of moisture content on metal sorption, uptake, and toxicity to the invertebrates were also investigated. Toxicity tests with the invertebrates were conducted using either Flin Flon soils or artificial soils with moisture content adjusted to 30%, 45%, 60%, or 75% of the maximum water-holding capacity of the soil samples. The Relative to Cd Toxicity Model identified Zn as the metal of concern in the area, and this was confirmed using validation tests with field contaminated soils. Furthermore, increasing the moisture content in soils increased the amount of mobile Zn available for uptake with the ion exchange resin. Survival and reproduction of both invertebrates were reduced under Zn exposure as moisture level increased. Thus, moisture-collecting landforms, which are often also associated with high Zn concentrations at Flin Flon, have, as a result, higher Zn toxicity to the soil ecosystem because of increases in soil moisture. © 2014 SETAC.

  20. Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

    Science.gov (United States)

    Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John

    2014-01-01

    Despite considerable interest in the application of land surface data assimilation systems (LDAS) for agricultural drought applications, relatively little is known about the large-scale performance of such systems and, thus, the optimal methodological approach for implementing them. To address this need, this paper evaluates an LDAS for agricultural drought monitoring by benchmarking individual components of the system (i.e., a satellite soil moisture retrieval algorithm, a soil water balance model and a sequential data assimilation filter) against a series of linear models which perform the same function (i.e., have the same basic inputoutput structure) as the full system component. Benchmarking is based on the calculation of the lagged rank cross-correlation between the normalized difference vegetation index (NDVI) and soil moisture estimates acquired for various components of the system. Lagged soil moistureNDVI correlations obtained using individual LDAS components versus their linear analogs reveal the degree to which non-linearities andor complexities contained within each component actually contribute to the performance of the LDAS system as a whole. Here, a particular system based on surface soil moisture retrievals from the Land Parameter Retrieval Model (LPRM), a two-layer Palmer soil water balance model and an Ensemble Kalman filter (EnKF) is benchmarked. Results suggest significant room for improvement in each component of the system.

  1. Use of neutron scattering meter to detect soil moisture distribution under trickle irrigation system in sandy soil of inshas, Egypt

    International Nuclear Information System (INIS)

    Abd El-moniem, M.; El-gendy, R.W.; Gadalla, A.M.; Hamdy, A.; Zeedan, A.

    2006-01-01

    This study aims to investigate the soil moisture distribution under different quantities of irrigation water in cultivated sandy soil with squash, using drip irrigation system. This study was carried out in Inshas sandy soil at the farm of Soil and Water Research Department, Nuclear Research Centre, Atomic Energy Authority, Egypt. Three rates of applied irrigation water (100, 75 and 50 % ETc) were used. Three sites (0, 12.5 and 25 cm distances from the emitter between drippers and laterals lines) were chosen to measure soil moisture contents (horizontal and vertical directions within the soil depths). The obtained data pointed out that the maximum width, in onion shape of water distribution under drip irrigation system, was at 45 cm depth at 0 site. From the study of soil moisture distribution, the overlapping between each two neighbor drippers played a good role in increasing soil moisture content at the 25 site rather than the rest sites. Water distribution was affected with plant location within the wet area as well as the used irrigation water quantities. Water distribution between drippers and laterals did not differ much approximately. The highest soil moisture depletion was at 12.5 site (between drippers) for 100 and 75 % ETc rather than the rest treatments. 100 % ETc treatment introduced the highest soil moisture depletion in the first stage of plant growth season for the three sites (between drippers and laterals). In the last stage of plant growth season, water re-distribution phenomena resulted from the changeable total hydraulic potential, which played important role for interpretation of results

  2. Effects of Natural and Synthetic Soil Conditioners on Soil Moisture ...

    African Journals Online (AJOL)

    USER

    The field investigation was a 4 × 5 factorial pot-experiment with maize as the test crop. ... The soil samples were air-dried to about 20% (v v–1) moisture content, pounded and passed through a 2- ..... properties of gel-amended container media.

  3. The benefits of using remotely sensed soil moisture in parameter identification of large-scale hydrological models

    Science.gov (United States)

    Wanders, N.; Bierkens, M. F. P.; de Jong, S. M.; de Roo, A.; Karssenberg, D.

    2014-08-01

    Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10-30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas. This article was corrected on 15 SEP 2014. See the end of the full text for details.

  4. [Soil moisture dynamics of artificial Caragana microphylla shrubs at different topographical sites in Horqin sandy land].

    Science.gov (United States)

    Huang, Gang; Zhao, Xue-yong; Huang, Ying-xin; Su, Yan-gui

    2009-03-01

    Based on the investigation data of vegetation and soil moisture regime of Caragana microphylla shrubs widely distributed in Horqin sandy land, the spatiotemporal variations of soil moisture regime and soil water storage of artificial sand-fixing C. microphylla shrubs at different topographical sites in the sandy land were studied, and the evapotranspiration was measured by water balance method. The results showed that the soil moisture content of the shrubs was the highest in the lowland of dunes, followed by in the middle, and in the crest of the dunes, and increased with increasing depth. No water stress occurred during the growth season of the shrubs. Soil moisture content of the shrubs was highly related to precipitation event, and the relationship of soil moisture content with precipitation was higher in deep soil layer (50-180 cm) than in shallow soil layer (0-50 cm). The variation coefficient of soil moisture content was also higher in deep layer than in shallow layer. Soil water storage was increasing in the whole growth season of the shrubs, which meant that the accumulation of soil water occurred in this area. The evapotranspiriation of the shrubs occupied above 64% of the precipitation.

  5. Effect of soil moisture on trace elements concentrations using ...

    African Journals Online (AJOL)

    Portable X-ray fluorescence (PXRF) technology can offer rapid and cost-effective determination of the trace elements concentrations in soils. The aim of this study was to assess the influence of soil moisture content under different condition on PXRF measurement quality. For this purpose, PXRF was used to evaluate the soil ...

  6. Effects of climate change on soil moisture over China from 1960-2006

    Science.gov (United States)

    Zhu, Q.; Jiang, H.; Liu, J.

    2009-01-01

    Soil moisture is an important variable in the climate system and it has sensitive impact on the global climate. Obviously it is one of essential components in the climate change study. The Integrated Biosphere Simulator (IBIS) is used to evaluate the spatial and temporal patterns of soil moisture across China under the climate change conditions for the period 1960-2006. Results show that the model performed better in warm season than in cold season. Mean errors (ME) are within 10% for all the months and root mean squared errors (RMSE) are within 10% except winter season. The model captured the spatial variability higher than 50% in warm seasons. Trend analysis based on the Mann-Kendall method indicated that soil moisture in most area of China is decreased especially in the northern China. The areas with significant increasing trends in soil moisture mainly locate at northwestern China and small areas in southeastern China and eastern Tibet plateau. ?? 2009 IEEE.

  7. To the vibrational over wetting and liquefaction effects in moistured soils

    International Nuclear Information System (INIS)

    Karimov, F.H.; Oripov, G.O.; Saidov, R.M.; Tojibekov, M.

    2003-01-01

    There is a lot of evidence of the dynamical effects in soils when they become wetted or during or after the earthquakes or explosions. There are some quantitative estimates for the vibrational wetting and liquefaction of soils under consideration. For the models in the present research the moistured sands and weak soils like losses are accepted. The first model is focusing on soil fractures sliding down under the action of vibrations, tightening of a hard phase, squeezing water phase out and thus bringing to soil liquefaction. The second is based on soil fractures plunging at the action of vibrations into the aquatic background. This mechanism seems to be more effective for the high degree moistured soils. The third mechanism is based on capillary phenomena in moistured porous medium. When inertia forces are large enough the resultant force, consisting of sliding down gravity component and inertia forces, overcomes friction and fracture becomes unstable. Both vibrations amplitude and frequency are the stability controlling factors, playing an important role in the vibrational wetting and liquefaction effects through porous water phase squeezing out or capillary lifting phenomena leading to the wetting or liquefaction of the medium. (author)

  8. The relationship between brightness temperature and soil moisture. Selection of frequency range for microwave remote sensing

    International Nuclear Information System (INIS)

    Rao, K.S.; Chandra, G.; Rao, P.V.N.

    1987-01-01

    The analysis of brightness temperature data acquired from field and aircraft experiments demonstrates a linear relationship between soil moisture and brightness temperature. However, the analysis of brightness temperature data acquired by the Skylab radiometer demonstrates a non-linear relationship between soil moisture and brightness temperature. In view of the above and also because of recent theoretical developments for the calculation of the dielectric constant and brightness temperature under varying soil moisture profile conditions, an attempt is made to study the theoretical relationship between brightness temperature and soil moisture as a function of frequency. Through the above analysis, the appropriate microwave frequency range for soil moisture studies is recommended

  9. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks

    Science.gov (United States)

    Vogel, Martha Marie; Orth, René; Cheruy, Frederique; Hagemann, Stefan; Lorenz, Ruth; van den Hurk, Bart; Seneviratne, Sonia Isabelle

    2017-04-01

    Regional hot extremes are projected to increase more strongly than global mean temperature, with substantially larger changes than 2°C even if global warming is limited to this level. We investigate here the role of soil moisture-temperature feedbacks for this response based on multi-model experiments for the 21st century with either interactive or fixed (late 20th century mean seasonal cycle) soil moisture. We analyze changes in the hottest days in each year in both sets of experiments, relate them to the global mean temperature increase, and investigate physical processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America and between 42%-52% in Amazonia, Northern Australia and Southern Africa. Soil moisture trends (multi-decadal soil moisture variability) are more important for this response than short-term (e.g. seasonal, interannual) soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections. Vogel, M.M. et al.,2017. Regional amplification of projected changes in extreme temperatures strongly controlled by soil moisture-temperature feedbacks. Geophysical Research Letters, accepted.

  10. Estimating surface soil moisture from SMAP observations using a Neural Network technique.

    Science.gov (United States)

    Kolassa, J; Reichle, R H; Liu, Q; Alemohammad, S H; Gentine, P; Aida, K; Asanuma, J; Bircher, S; Caldwell, T; Colliander, A; Cosh, M; Collins, C Holifield; Jackson, T J; Martínez-Fernández, J; McNairn, H; Pacheco, A; Thibeault, M; Walker, J P

    2018-01-01

    A Neural Network (NN) algorithm was developed to estimate global surface soil moisture for April 2015 to March 2017 with a 2-3 day repeat frequency using passive microwave observations from the Soil Moisture Active Passive (SMAP) satellite, surface soil temperatures from the NASA Goddard Earth Observing System Model version 5 (GEOS-5) land modeling system, and Moderate Resolution Imaging Spectroradiometer-based vegetation water content. The NN was trained on GEOS-5 soil moisture target data, making the NN estimates consistent with the GEOS-5 climatology, such that they may ultimately be assimilated into this model without further bias correction. Evaluated against in situ soil moisture measurements, the average unbiased root mean square error (ubRMSE), correlation and anomaly correlation of the NN retrievals were 0.037 m 3 m -3 , 0.70 and 0.66, respectively, against SMAP core validation site measurements and 0.026 m 3 m -3 , 0.58 and 0.48, respectively, against International Soil Moisture Network (ISMN) measurements. At the core validation sites, the NN retrievals have a significantly higher skill than the GEOS-5 model estimates and a slightly lower correlation skill than the SMAP Level-2 Passive (L2P) product. The feasibility of the NN method was reflected by a lower ubRMSE compared to the L2P retrievals as well as a higher skill when ancillary parameters in physically-based retrievals were uncertain. Against ISMN measurements, the skill of the two retrieval products was more comparable. A triple collocation analysis against Advanced Microwave Scanning Radiometer 2 (AMSR2) and Advanced Scatterometer (ASCAT) soil moisture retrievals showed that the NN and L2P retrieval errors have a similar spatial distribution, but the NN retrieval errors are generally lower in densely vegetated regions and transition zones.

  11. A simulation test of the impact on soil moisture by agricultural ...

    African Journals Online (AJOL)

    use

    2011-11-21

    Nov 21, 2011 ... 500 cm2 separately by calculating the length and width of its tires in case of tires' variant for pressure (Chen 1981), and thus their respective ground pressure ratios are 201.9 kPa and 121.5 ... cm depth, which is for the measure error and the low impaction by load on soil moisture. The loss of soil moisture ...

  12. Low-Cost Soil Moisture Profile Probe Using Thin-Film Capacitors and a Capacitive Touch Sensor

    Directory of Open Access Journals (Sweden)

    Yuki Kojima

    2016-08-01

    Full Text Available Soil moisture is an important property for agriculture, but currently commercialized soil moisture sensors are too expensive for many farmers. The objective of this study is to develop a low-cost soil moisture sensor using capacitors on a film substrate and a capacitive touch integrated circuit. The performance of the sensor was evaluated in two field experiments: a grape field and a mizuna greenhouse field. The developed sensor captured dynamic changes in soil moisture at 10, 20, and 30 cm depth, with a period of 10–14 days required after sensor installation for the contact between capacitors and soil to settle down. The measured soil moisture showed the influence of individual sensor differences, and the influence masked minor differences of less than 0.05 m3·m−3 in the soil moisture at different locations. However, the developed sensor could detect large differences of more than 0.05 m3·m−3, as well as the different magnitude of changes, in soil moisture. The price of the developed sensor was reduced to 300 U.S. dollars and can be reduced even more by further improvements suggested in this study and by mass production. Therefore, the developed sensor will be made more affordable to farmers as it requires low financial investment, and it can be utilized for decision-making in irrigation.

  13. [Response of mineralization of dissolved organic carbon to soil moisture in paddy and upland soils in hilly red soil region].

    Science.gov (United States)

    Chen, Xiang-Bi; Wang, Ai-Hua; Hu, Le-Ning; Huang, Yuan; Li, Yang; He, Xun-Yang; Su, Yi-Rong

    2014-03-01

    Typical paddy and upland soils were collected from a hilly subtropical red-soil region. 14C-labeled dissolved organic carbon (14C-DOC) was extracted from the paddy and upland soils incorporated with 14C-labeled straw after a 30-day (d) incubation period under simulated field conditions. A 100-d incubation experiment (25 degrees C) with the addition of 14C-DOC to paddy and upland soils was conducted to monitor the dynamics of 14C-DOC mineralization under different soil moisture conditions [45%, 60%, 75%, 90%, and 105% of the field water holding capacity (WHC)]. The results showed that after 100 days, 28.7%-61.4% of the labeled DOC in the two types of soils was mineralized to CO2. The mineralization rates of DOC in the paddy soils were significantly higher than in the upland soils under all soil moisture conditions, owing to the less complex composition of DOC in the paddy soils. The aerobic condition was beneficial for DOC mineralization in both soils, and the anaerobic condition was beneficial for DOC accumulation. The biodegradability and the proportion of the labile fraction of the added DOC increased with the increase of soil moisture (45% -90% WHC). Within 100 days, the labile DOC fraction accounted for 80.5%-91.1% (paddy soil) and 66.3%-72.4% (upland soil) of the cumulative mineralization of DOC, implying that the biodegradation rate of DOC was controlled by the percentage of labile DOC fraction.

  14. Effects of Recent Regional Soil Moisture Variability on Global Net Ecosystem CO2 Exchange

    Science.gov (United States)

    Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.

    2017-12-01

    Soil moisture exerts a major regional control on the inter-annual variability of the global land sink for atmospheric CO2. In semi-arid regions, annual biomass production is closely coupled to variability in soil moisture availability, while in cold-season-affected regions, summer drought offsets the effects of advancing spring phenology. Availability of satellite solar-induced fluorescence (SIF) observations and improvements in atmospheric inversions has led to unprecedented ability to monitor atmospheric sink strength. However, discrepancies still exist between such top-down estimates as atmospheric inversion and bottom-up process and satellite driven models, indicating that relative strength, mechanisms, and interaction of driving factors remain poorly understood. We use soil moisture fields informed by Soil Moisture Active Passive Mission (SMAP) observations to compare recent (2015-2017) and historic (2000-2014) variability in net ecosystem land-atmosphere CO2 exchange (NEE). The operational SMAP Level 4 Carbon (L4C) product relates ground-based flux tower measurements to other bottom-up and global top-down estimates to underlying soil moisture and other driving conditions using data-assimilation-based SMAP Level 4 Soil Moisture (L4SM). Droughts in coastal Brazil, South Africa, Eastern Africa, and an anomalous wet period in Eastern Australia were observed by L4C. A seasonal seesaw pattern of below-normal sink strength at high latitudes relative to slightly above-normal sink strength for mid-latitudes was also observed. Whereas SMAP-based soil moisture is relatively informative for short-term temporal variability, soil moisture biases that vary in space and with season constrain the ability of the L4C estimates to accurately resolve NEE. Such biases might be caused by irrigation and plant-accessible ground-water. Nevertheless, SMAP L4C daily NEE estimates connect top-down estimates to variability of effective driving factors for accurate estimates of regional

  15. Seasonality in ENSO-related precipitation, river discharges, soil moisture, and vegetation index in Colombia

    Science.gov (United States)

    Poveda, GermáN.; Jaramillo, Alvaro; Gil, Marta MaríA.; Quiceno, Natalia; Mantilla, Ricardo I.

    2001-08-01

    An analysis of hydrologic variability in Colombia shows different seasonal effects associated with El Niño/Southern Oscillation (ENSO) phenomenon. Spectral and cross-correlation analyses are developed between climatic indices of the tropical Pacific Ocean and the annual cycle of Colombia's hydrology: precipitation, river flows, soil moisture, and the Normalized Difference Vegetation Index (NDVI). Our findings indicate stronger anomalies during December-February and weaker during March-May. The effects of ENSO are stronger for streamflow than for precipitation, owing to concomitant effects on soil moisture and evapotranspiration. We studied time variability of 10-day average volumetric soil moisture, collected at the tropical Andes of central Colombia at depths of 20 and 40 cm, in coffee growing areas characterized by shading vegetation ("shaded coffee"), forest, and sunlit coffee. The annual and interannual variability of soil moisture are highly intertwined for the period 1997-1999, during strong El Niño and La Niña events. Soil moisture exhibited greater negative anomalies during 1997-1998 El Niño, being strongest during the two dry seasons that normally occur in central Colombia. Soil moisture deficits were more drastic at zones covered by sunlit coffee than at those covered by forest and shaded coffee. Soil moisture responds to wetter than normal precipitation conditions during La Niña 1998-1999, reaching maximum levels throughout that period. The probability density function of soil moisture records is highly skewed and exhibits different kinds of multimodality depending upon land cover type. NDVI exhibits strong negative anomalies throughout the year during El Niños, in particular during September-November (year 0) and June-August (year 0). The strong negative relation between NDVI and El Niño has enormous implications for carbon, water, and energy budgets over the region, including the tropical Andes and Amazon River basin.

  16. Soil sample moisture content as a function of time during oven drying for gamma-ray spectroscopic measurements

    International Nuclear Information System (INIS)

    Benke, R.R.; Kearfott, K.J.

    1999-01-01

    In routine gamma-ray spectroscopic analysis of collected soil samples, procedure often calls to remove soil moisture by oven drying overnight at a temperature of 100 deg. C . Oven drying not only minimizes the gamma-ray self-attenuation of soil samples due to the absence of water during the gamma-ray spectroscopic analysis, but also allows for a straightforward calculation of the specific activity of radionuclides in soil, historically based on the sample dry weight. Because radon exhalation is strongly dependent on moisture , knowledge of the oven-drying time dependence of the soil moisture content, combined with radon exhalation measurements during oven drying and at room temperature for varying soil moisture contents, would allow conclusions to be made on how the oven-drying radon exhalation rate depends on soil moisture content. Determinations of the oven-drying radon exhalation from soil samples allow corrections to be made for the immediate laboratory gamma-ray spectroscopy of radionuclides in the natural uranium decay chain. This paper presents the results of soil moisture content measurements during oven drying and suggests useful empirical fits to the moisture data

  17. MODIS-based spatiotemporal patterns of soil moisture and evapotranspiration interactions in Tampa Bay urban watershed

    Science.gov (United States)

    Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent

    2011-09-01

    Soil moisture and evapotranspiration (ET) is affected by both water and energy balances in the soilvegetation- atmosphere system, it involves many complex processes in the nexus of water and thermal cycles at the surface of the Earth. These impacts may affect the recharge of the upper Floridian aquifer. The advent of urban hydrology and remote sensing technologies opens new and innovative means to undertake eventbased assessment of ecohydrological effects in urban regions. For assessing these landfalls, the multispectral Moderate Resolution Imaging Spectroradiometer (MODIS) remote sensing images can be used for the estimation of such soil moisture change in connection with two other MODIS products - Enhanced Vegetation Index (EVI), Land Surface Temperature (LST). Supervised classification for soil moisture retrieval was performed for Tampa Bay area on the 2 kmx2km grid with MODIS images. Machine learning with genetic programming model for soil moisture estimation shows advances in image processing, feature extraction, and change detection of soil moisture. ET data that were derived by Geostationary Operational Environmental Satellite (GOES) data and hydrologic models can be retrieved from the USGS web site directly. Overall, the derived soil moisture in comparison with ET time series changes on a seasonal basis shows that spatial and temporal variations of soil moisture and ET that are confined within a defined region for each type of surfaces, showing clustered patterns and featuring space scatter plot in association with the land use and cover map. These concomitant soil moisture patterns and ET fluctuations vary among patches, plant species, and, especially, location on the urban gradient. Time series plots of LST in association with ET, soil moisture and EVI reveals unique ecohydrological trends. Such ecohydrological assessment can be applied for supporting the urban landscape management in hurricane-stricken regions.

  18. Data Assimilation using observed streamflow and remotely-sensed soil moisture for improving sub-seasonal-to-seasonal forecasting

    Science.gov (United States)

    Arumugam, S.; Mazrooei, A.; Lakshmi, V.; Wood, A.

    2017-12-01

    Subseasonal-to-seasonal (S2S) forecasts of soil moisture and streamflow provides critical information for water and agricultural systems to support short-term planning and mangement. This study evaluates the role of observed streamflow and remotely-sensed soil moisture from SMAP (Soil Moisture Active Passive) mission in improving S2S streamflow and soil moisture forecasting using data assimilation (DA). We first show the ability to forecast soil moisture at monthly-to-seaasonal time scale by forcing climate forecasts with NASA's Land Information System and then compares the developed soil moisture forecast with the SMAP data over the Southeast US. Our analyses show significant skill in forecasting real-time soil moisture over 1-3 months using climate information. We also show that the developed soil moisture forecasts capture the observed severe drought conditions (2007-2008) over the Southeast US. Following that, we consider both SMAP data and observed streamflow for improving S2S streamflow and soil moisture forecasts for a pilot study area, Tar River basin, in NC. Towards this, we consider variational assimilation (VAR) of gauge-measured daily streamflow data in improving initial hydrologic conditions of Variable Infiltration Capacity (VIC) model. The utility of data assimilation is then assessed in improving S2S forecasts of streamflow and soil moisture through a retrospective analyses. Furthermore, the optimal frequency of data assimilation and optimal analysis window (number of past observations to use) are also assessed in order to achieve the maximum improvement in S2S forecasts of streamflow and soil moisture. Potential utility of updating initial conditions using DA and providing skillful forcings are also discussed.

  19. Joint Sentinel-1 and SMAP data assimilation to improve soil moisture estimates

    Science.gov (United States)

    Lievens, H.; Reichle, R. H.; Liu, Q.; De Lannoy, G.; Dunbar, R. S.; Kim, S.; Das, N. N.; Cosh, M. H.; Walker, J. P.; Wagner, W.

    2017-12-01

    SMAP (Soil Moisture Active and Passive) radiometer observations at 40 km resolution are routinely assimilated into the NASA Catchment Land Surface Model (CLSM) to generate the SMAP Level 4 Soil Moisture product. The use of C-band radar backscatter observations from Sentinel-1 has the potential to add value to the radiance assimilation by increasing the level of spatial detail. The specifications of Sentinel-1 are appealing, particularly its high spatial resolution (5 by 20 m in interferometric wide swath mode) and frequent revisit time (6 day repeat cycle for the Sentinel-1A and Sentinel-1B constellation). However, the shorter wavelength of Sentinel-1 observations implies less sensitivity to soil moisture. This study investigates the value of Sentinel-1 data for hydrologic simulations by assimilating the radar observations into CLSM, either separately from or simultaneously with SMAP radiometer observations. To facilitate the assimilation of the radar observations, CLSM is coupled to the water cloud model, simulating the radar backscatter as observed by Sentinel-1. The innovations, i.e. differences between observations and simulations, are converted into increments to the model soil moisture state through an Ensemble Kalman Filter. The assimilation impact is assessed by comparing 3-hourly, 9 km surface and root-zone soil moisture simulations with in situ measurements from 9 km SMAP core validation sites and sparse networks, from May 2015 to 2017. The Sentinel-1 assimilation consistently improves surface soil moisture, whereas root-zone impacts are mostly neutral. Relatively larger improvements are obtained from SMAP assimilation. The joint assimilation of SMAP and Sentinel-1 observations performs best, demonstrating the complementary value of radar and radiometer observations.

  20. Soil Moisture Estimate under Forest using a Semi-empirical Model at P-Band

    Science.gov (United States)

    Truong-Loi, M.; Saatchi, S.; Jaruwatanadilok, S.

    2013-12-01

    In this paper we show the potential of a semi-empirical algorithm to retrieve soil moisture under forests using P-band polarimetric SAR data. In past decades, several remote sensing techniques have been developed to estimate the surface soil moisture. In most studies associated with radar sensing of soil moisture, the proposed algorithms are focused on bare or sparsely vegetated surfaces where the effect of vegetation can be ignored. At long wavelengths such as L-band, empirical or physical models such as the Small Perturbation Model (SPM) provide reasonable estimates of surface soil moisture at depths of 0-5cm. However for densely covered vegetated surfaces such as forests, the problem becomes more challenging because the vegetation canopy is a complex scattering environment. For this reason there have been only few studies focusing on retrieving soil moisture under vegetation canopy in the literature. Moghaddam et al. developed an algorithm to estimate soil moisture under a boreal forest using L- and P-band SAR data. For their studied area, double-bounce between trunks and ground appear to be the most important scattering mechanism. Thereby, they implemented parametric models of radar backscatter for double-bounce using simulations of a numerical forest scattering model. Hajnsek et al. showed the potential of estimating the soil moisture under agricultural vegetation using L-band polarimetric SAR data and using polarimetric-decomposition techniques to remove the vegetation layer. Here we use an approach based on physical formulation of dominant scattering mechanisms and three parameters that integrates the vegetation and soil effects at long wavelengths. The algorithm is a simplification of a 3-D coherent model of forest canopy based on the Distorted Born Approximation (DBA). The simplified model has three equations and three unknowns, preserving the three dominant scattering mechanisms of volume, double-bounce and surface for three polarized backscattering

  1. Examining the relationship between intermediate-scale soil moisture and terrestrial evaporation within a semi-arid grassland

    KAUST Repository

    Jana, Raghavendra B.

    2016-09-30

    Interactions between soil moisture and terrestrial evaporation affect water cycle behaviour and responses between the land surface and the atmosphere across scales. With strong heterogeneities at the land surface, the inherent spatial variability in soil moisture makes its representation via point-scale measurements challenging, resulting in scale mismatch when compared to coarser-resolution satellite based soil moisture or evaporation estimates. The Cosmic Ray Neutron Probe (CRNP) was developed to address such issues in the measurement and representation of soil moisture at intermediate scales. Here, we present a study to assess the utility of CRNP soil moisture observations in validating model evaporation estimates. The CRNP soil moisture product from a pasture in the semi-arid central west region of New South Wales, Australia, was compared to evaporation derived from three distinct approaches, including the Priestley–Taylor (PT-JPL), Penman–Monteith (PM-Mu), and Surface Energy Balance System (SEBS) models, driven by forcing data from local meteorological station data and remote sensing retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. Pearson’s correlations, quantile–quantile (Q–Q) plots, and analysis of variance (ANOVA) were used to qualitatively and quantitatively evaluate the temporal distributions of soil moisture and evaporation over the study site. The relationships were examined against nearly 2 years of observation data, as well as for different seasons and for defined periods of analysis. Results highlight that while direct correlations of raw data were not particularly instructive, the Q–Q plots and ANOVA illustrate that the root-zone soil moisture represented by the CRNP measurements and the modelled evaporation estimates reflect similar distributions under most meteorological conditions. The PT-JPL and PM-Mu model estimates performed contrary to expectation when high soil moisture and cold temperatures were

  2. Soil moisture variations in remotely sensed and reanalysis datasets during weak monsoon conditions over central India and central Myanmar

    Science.gov (United States)

    Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani

    2017-07-01

    Variation of soil moisture during active and weak phases of summer monsoon JJAS (June, July, August, and September) is very important for sustenance of the crop and subsequent crop yield. As in situ observations of soil moisture are few or not available, researchers use data derived from remote sensing satellites or global reanalysis. This study documents the intercomparison of soil moisture from remotely sensed and reanalyses during dry spells within monsoon seasons in central India and central Myanmar. Soil moisture data from the European Space Agency (ESA)—Climate Change Initiative (CCI) has been treated as observed data and was compared against soil moisture data from the ECMWF reanalysis-Interim (ERA-I) and the climate forecast system reanalysis (CFSR) for the period of 2002-2011. The ESA soil moisture correlates rather well with observed gridded rainfall. The ESA data indicates that soil moisture increases over India from west to east and from north to south during monsoon season. The ERA-I overestimates the soil moisture over India, while the CFSR soil moisture agrees well with the remotely sensed observation (ESA). Over Myanmar, both the reanalysis overestimate soil moisture values and the ERA-I soil moisture does not show much variability from year to year. Day-to-day variations of soil moisture in central India and central Myanmar during weak monsoon conditions indicate that, because of the rainfall deficiency, the observed (ESA) and the CFSR soil moisture values are reduced up to 0.1 m3/m3 compared to climatological values of more than 0.35 m3/m3. This reduction is not seen in the ERA-I data. Therefore, soil moisture from the CFSR is closer to the ESA observed soil moisture than that from the ERA-I during weak phases of monsoon in the study region.

  3. Soil Moisture Estimation Using MODIS Images (Case Study: Mashhad Plain Area

    Directory of Open Access Journals (Sweden)

    M. Fashaee

    2016-09-01

    Full Text Available Introduction: Numerous studies have been undertaken based on satellite imagery in order to estimate soil moisture using vegetation indices such as NDVI. Previous studies suffer from a restriction; these indices are not able to estimate where the vegetative coverage is low or where no vegetation exists. Hence, it is essential to develop a model which can overcome this restriction. Focus of this research is on estimation of soil moisture for low or scattered vegetative land covers. Trapezoidal temperature-vegetation (Ts~VI model is able to consider the status of soil moisture and vegetation condition. It can estimate plant water deficit for weak or no vegetation land cover. Materials and Methods: Moran proposed Water Deficit Index (WDI for evaluating field evapotranspiration rates and relative field water deficit for both full-cover and partially vegetated sites. The theoretical basis of this method is based on the energy balance equation. Penman-Monteith equation of energy balance was used to calculate the coordinates of the four vertices of the temperature-vegetation trapezoid also for four different extreme combinations of temperature and vegetation. For the (Ts−Ta~Vc trapezoid, four vertices correspond to 1 well-watered full-cover vegetation, 2 water-stressed full-cover vegetation, 3 saturated bare soil, and 4 dry bare soil. WDI is equal to 0 for well-watered conditions and equals to 1 for maximum stress conditions. As suggested by Moran et al. to draw a trapezoidal shape, some field measurements are required such as wind speed at the height of 2 meters, air pressure, mean daily temperature, vapor pressure-temperature curve slope, Psychrometrics constant, vapor pressure at mean temperature, vapor pressure deficit, external radiation, solar radiation of short wavelength, longwave radiation, net radiation, soil heat flux and air aerodynamic resistance is included. Crop vegetation and canopy resistance should be measured or estimated. The study

  4. A study of soil moisture variability for landmine detection by the neutron technique

    Directory of Open Access Journals (Sweden)

    Avdić Senada

    2007-01-01

    Full Text Available This paper is focused on the space and temporal variability of soil moisture experimental data acquired at a few locations near landmine fields in the Tuzla Canton, as well as on the quantification of the statistical nature of soil moisture data on a small spatial scale. Measurements of soil water content at the surface were performed by an electro-magnetic sensor over 1 25, and 100 m2 grids, at intervals of 0.2, 0.5, and 1 m, respectively. The sampling of soil moisture at different spatial resolutions and over different grid sizes has been investigated in order to achieve the quantification of the statistical nature of soil moisture distribution. The statistical characterization of spatial variability was performed through variogram and correlogram analysis of measurement results. The temporal variability of the said samples was examined over a two-season period. For both sampling periods, the spatial correlation length is about 1 to 2 m, respectively, or less. Thus, sampling should be done on a larger spatial scale, in order to capture the variability of the investigated areas. Since the characteristics of many landmine sensors depend on soil moisture, the results of this study could form a useful data base for multisensor landmine detection systems with a promising performance.

  5. Comparison of time domain reflectometry, capacitance methods and neutron scattering in soil moisture measurements

    International Nuclear Information System (INIS)

    Khorasani, A.; Mousavi Shalmani, M. A.; Piervali Bieranvand, N.

    2011-01-01

    An accurate, precise, fast and ease as well as the ability for measurements in depth are the characteristics that are desirable in measuring soil moisture methods. To compare methods (time domain reflectometry and capacitance) with neutron scattering for soil water monitoring, an experiment was carried out in a randomized complete block design (Split Split plot) on tomato with three replications on the experimental field of International Atomic Energy Agency (Seibersdorf-Austria). The treatment instruments for the soil moisture monitoring (main factor) consist of neutron gauge, Diviner 2000, time domain reflectometer and an EnviroScan and different irrigation systems (first sub factor) consist of trickle and furrow irrigations and different depths of soil (second sub factor) consist of 0-20, 20-40 and 40-60 cm. The results showed that for the neutron gauge and time domain reflectometer the amount of soil moisture in both of trickle and furrow irrigations were the same, but the significant differences were recorded in Diviner 2000 and EnviroScan measurements. The results of this study showed that the neutron gauge is an acceptable and reliable means with the modern technology, with a precision of ±2 mm in 450 mm soil water to a depth of 1.5 meter and can be considered as the most practical method for measuring soil moisture profiles and irrigation planning program. The time domain reflectometer method in most mineral soils, without the need for calibration, with an accuracy ±0.01m 3 m -3 has a good performance in soil moisture and electrical conductivity measurements. The Diviner 2000 and EnviroScan are not well suitable for the above conditions for several reasons such as much higher soil moisture and a large error measurement and also its sensitivity to the soil gap and to the small change in the soil moisture in comparison with the neutron gauge and the time domain reflectometer methods.

  6. Unsaturated soil moisture drying and wetting diffusion coefficient measurements in the laboratory.

    Science.gov (United States)

    2009-09-01

    ABSTRACTTransient moisture flow in an unsaturated soil in response to suction changes is controlled by the unsaturated moisture diffusion coefficient. The moisture diffusion coefficient can be determined by measuring suction profiles over time. The l...

  7. Assimilation of Spatially Sparse In Situ Soil Moisture Networks into a Continuous Model Domain

    Science.gov (United States)

    Gruber, A.; Crow, W. T.; Dorigo, W. A.

    2018-02-01

    Growth in the availability of near-real-time soil moisture observations from ground-based networks has spurred interest in the assimilation of these observations into land surface models via a two-dimensional data assimilation system. However, the design of such systems is currently hampered by our ignorance concerning the spatial structure of error afflicting ground and model-based soil moisture estimates. Here we apply newly developed triple collocation techniques to provide the spatial error information required to fully parameterize a two-dimensional (2-D) data assimilation system designed to assimilate spatially sparse observations acquired from existing ground-based soil moisture networks into a spatially continuous Antecedent Precipitation Index (API) model for operational agricultural drought monitoring. Over the contiguous United States (CONUS), the posterior uncertainty of surface soil moisture estimates associated with this 2-D system is compared to that obtained from the 1-D assimilation of remote sensing retrievals to assess the value of ground-based observations to constrain a surface soil moisture analysis. Results demonstrate that a fourfold increase in existing CONUS ground station density is needed for ground network observations to provide a level of skill comparable to that provided by existing satellite-based surface soil moisture retrievals.

  8. Calculating crop water requirement satisfaction in the West Africa Sahel with remotely sensed soil moisture

    Science.gov (United States)

    McNally, Amy; Gregory J. Husak,; Molly Brown,; Carroll, Mark L.; Funk, Christopher C.; Soni Yatheendradas,; Kristi Arsenault,; Christa Peters-Lidard,; Verdin, James

    2015-01-01

    The Soil Moisture Active Passive (SMAP) mission will provide soil moisture data with unprecedented accuracy, resolution, and coverage, enabling models to better track agricultural drought and estimate yields. In turn, this information can be used to shape policy related to food and water from commodity markets to humanitarian relief efforts. New data alone, however, do not translate to improvements in drought and yield forecasts. New tools will be needed to transform SMAP data into agriculturally meaningful products. The objective of this study is to evaluate the possibility and efficiency of replacing the rainfall-derived soil moisture component of a crop water stress index with SMAP data. The approach is demonstrated with 0.1°-resolution, ~10-day microwave soil moisture from the European Space Agency and simulated soil moisture from the Famine Early Warning Systems Network Land Data Assimilation System. Over a West Africa domain, the approach is evaluated by comparing the different soil moisture estimates and their resulting Water Requirement Satisfaction Index values from 2000 to 2010. This study highlights how the ensemble of indices performs during wet versus dry years, over different land-cover types, and the correlation with national-level millet yields. The new approach is a feasible and useful way to quantitatively assess how satellite-derived rainfall and soil moisture track agricultural water deficits. Given the importance of soil moisture in many applications, ranging from agriculture to public health to fire, this study should inspire other modeling communities to reformulate existing tools to take advantage of SMAP data.

  9. Advanced Soil Moisture Network Technologies; Developments in Collecting in situ Measurements for Remote Sensing Missions

    Science.gov (United States)

    Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.

    2015-12-01

    The Soil moisture Sensing Controller And oPtimal Estimator (SoilSCAPE) wireless sensor network has been developed to support Calibration and Validation activities (Cal/Val) for large scale soil moisture remote sensing missions (SMAP and AirMOSS). The technology developed here also readily supports small scale hydrological studies by providing sub-kilometer widespread soil moisture observations. An extensive collection of semi-sparse sensor clusters deployed throughout north-central California and southern Arizona provide near real time soil moisture measurements. Such a wireless network architecture, compared to conventional single points measurement profiles, allows for significant and expanded soil moisture sampling. The work presented here aims at discussing and highlighting novel and new technology developments which increase in situ soil moisture measurements' accuracy, reliability, and robustness with reduced data delivery latency. High efficiency and low maintenance custom hardware have been developed and in-field performance has been demonstrated for a period of three years. The SoilSCAPE technology incorporates (a) intelligent sensing to prevent erroneous measurement reporting, (b) on-board short term memory for data redundancy, (c) adaptive scheduling and sampling capabilities to enhance energy efficiency. A rapid streamlined data delivery architecture openly provides distribution of in situ measurements to SMAP and AirMOSS cal/val activities and other interested parties.

  10. Uncertainty of Deardorff’s soil moisture model based on continuous TDR measurements for sandy loam soil

    Directory of Open Access Journals (Sweden)

    Brandyk Andrzej

    2016-03-01

    Full Text Available Knowledge on soil moisture is indispensable for a range of hydrological models, since it exerts a considerable influence on runoff conditions. Proper tools are nowadays applied in order to gain in-sight into soil moisture status, especially of uppermost soil layers, which are prone to weather changes and land use practices. In order to establish relationships between meteorological conditions and topsoil moisture, a simple model would be required, characterized by low computational effort, simple structure and low number of identified and calibrated parameters. We demonstrated, that existing model for shallow soils, considering mass exchange between two layers (the upper and the lower, as well as with the atmosphere and subsoil, worked well for sandy loam with deep ground water table in Warsaw conurbation. GLUE (Generalized Likelihood Uncertainty Estimation linked with GSA (Global Sensitivity Analysis provided for final determination of parameter values and model confidence ranges. Including the uncertainty in a model structure, caused that the median soil moisture solution of the GLUE was shifted from the one optimal in deterministic sense. From the point of view of practical model application, the main shortcoming were the underestimated water exchange rates between the lower soil layer (ranging from the depth of 0.1 to 0.2 m below ground level and subsoil. General model quality was found to be satisfactory and promising for its utilization for establishing measures to regain retention in urbanized conditions.

  11. A missing piece of the puzzle in climate change hotspots: Near-surface turbulent interactions controlling ET-soil moisture coupling in semiarid areas

    Science.gov (United States)

    Haghighi, Erfan; Gianotti, Daniel J.; Rigden, Angela J.; Salvucci, Guido D.; Kirchner, James W.; Entekhabi, Dara

    2017-04-01

    Being located in the transitional zone between dry and wet climate areas, semiarid ecosystems (and their associated ecohydrological processes) play a critical role in controlling climate change and global warming. Land evapotranspiration (ET), which is a central process in the climate system and a nexus of the water, energy and carbon cycles, typically accounts for up to 95% of the water budget in semiarid areas. Thus, the manner in which ET is partitioned into soil evaporation and plant transpiration in these settings is of practical importance for water and carbon cycling and their feedbacks to the climate system. ET (and its partitioning) in these regions is primarily controlled by surface soil moisture which varies episodically under stochastic precipitation inputs. Important as the ET-soil moisture relationship is, it remains empirical, and physical mechanisms governing its nature and dynamics are underexplored. Thus, the objective of this study is twofold: (1) to provide observational evidence for the influence of surface cover conditions on ET-soil moisture coupling in semiarid regions using soil moisture data from NASA's SMAP satellite mission combined with independent observationally based ET estimates, and (2) to develop a relatively simple mechanistic modeling platform improving our physical understanding of interactions between micro and macroscale processes controlling ET and its partitioning in partially vegetated areas. To this end, we invoked concepts from recent progress in mechanistic modeling of turbulent energy flux exchange in bluff-rough regions, and developed a physically based ET model that explicitly accounts for how vegetation-induced turbulence in the near-surface region influences soil drying and thus ET rates and dynamics. Model predictions revealed nonlinearities in the strength of the ET-soil moisture relationship (i.e., ∂ET/∂θ) as vegetation cover fraction increases, accounted for by the nonlinearity of surface

  12. The use of remotely sensed soil moisture data in large-scale models of the hydrological cycle

    Science.gov (United States)

    Salomonson, V. V.; Gurney, R. J.; Schmugge, T. J.

    1985-01-01

    Manabe (1982) has reviewed numerical simulations of the atmosphere which provided a framework within which an examination of the dynamics of the hydrological cycle could be conducted. It was found that the climate is sensitive to soil moisture variability in space and time. The challenge arises now to improve the observations of soil moisture so as to provide up-dated boundary condition inputs to large scale models including the hydrological cycle. Attention is given to details regarding the significance of understanding soil moisture variations, soil moisture estimation using remote sensing, and energy and moisture balance modeling.

  13. Implementation of a multiangle soil moisture retrieval model using RADARSAT-2 imagery over arid Juyanze, northwest China

    Science.gov (United States)

    Yang, Liping; Li, Yanfei; Li, Qi; Sun, Xiaohui; Kong, Jinling; Wang, Le

    2017-07-01

    Accurate retrieval of soil moisture is important for understanding regional environmental changes and sustainable development in arid regions. Through numerical simulation and regression analysis based on advanced integral equation model (AIEM), the study aims to establish a multiangle soil moisture retrieval model based on RADARSAT-2 image in arid Juyanze. A combined roughness parameter Rs was established, and then the influences of roughness and soil moisture on the backscattering simulations were discussed. Finally, the empirical multiangle soil moisture retrieval model was implemented and validated in Juyanze. Inversion results show that the model has favorable validity. The coefficient of determination R2 between the inferred and measured soil moisture is 0.775 with a root-mean-square error (rmse) of 0.626%, implying better retrieval accuracy. Soil moisture varies from about 0.1% to 25% and is no more than 10% in most parts of this region, which is in reasonable agreement with the factual circumstances. The model directly relates the Fresnel reflection coefficient and soil moisture and is independent of ground roughness measurements. With a wider angular range, it has great potential for soil moisture evaluation in arid regions.

  14. Simultaneous heat and moisture transfer in soils combined with building simulation

    Energy Technology Data Exchange (ETDEWEB)

    Santos, G. H. dos; Mendes, N. [Pontifical Catholic University of Parana, PUCPR/CCET, Thermal Systems Laboratory (LST), Curitiba (Brazil)

    2006-07-01

    In order to precisely predict ground heat transfer, room air temperature and humidity, a combined model has been developed and conceived to calculate both the coupled heat and moisture transfer in soil and floor and the psychrometrics condition of indoor air. The present methodology for the soil is based on the theory of Philip and De Vries, using variable thermophysical properties for different materials. The governing equations were discretized using the finite-volume method and a three-dimensional model for describing the physical phenomena of heat and mass transfer in unsaturated moist porous soils and floor. Additionally, a lumped transient approach for a building room and a finite-volume multi-layer model for the building envelope have been developed to integrate with the soil model. Results are presented in terms of temperature, humidity and heat flux at the interface between room air and the floor, showing the importance of the approach presented and the model robustness for long-term simulations with a high time step. (author)

  15. A simple model for retrieving bare soil moisture from radar-scattering coefficients

    International Nuclear Information System (INIS)

    Chen, K.S.; Yen, S.K.; Huang, W.P.

    1995-01-01

    A simple algorithm based on a rough surface scattering model was developed to invert the bare soil moisture content from active microwave remote sensing data. In the algorithm development, a frequency mixing model was used to relate soil moisture to the dielectric constant. In particular, the Integral Equation Model (IEM) was used over a wide range of surface roughness and radar frequencies. To derive the algorithm, a sensitivity analysis was performed using a Monte Carlo simulation to study the effects of surface parameters, including height variance, correlation length, and dielectric constant. Because radar return is inherently dependent on both moisture content and surface roughness, the purpose of the sensitivity testing was to select the proper radar parameters so as to optimally decouple these two factors, in an attempt to minimize the effects of one while the other was observed. As a result, the optimal radar parameter ranges can be chosen for the purpose of soil moisture content inversion. One thousand samples were then generated with the IEM model followed by multivariate linear regression analysis to obtain an empirical soil moisture model. Numerical comparisons were made to illustrate the inversion performance using experimental measurements. Results indicate that the present algorithm is simple and accurate, and can be a useful tool for the remote sensing of bare soil surfaces. (author)

  16. A wireless soil moisture sensor powered by solar energy.

    Directory of Open Access Journals (Sweden)

    Mingliang Jiang

    Full Text Available In a variety of agricultural activities, such as irrigation scheduling and nutrient management, soil water content is regarded as an essential parameter. Either power supply or long-distance cable is hardly available within field scale. For the necessity of monitoring soil water dynamics at field scale, this study presents a wireless soil moisture sensor based on the impedance transform of the frequency domain. The sensor system is powered by solar energy, and the data can be instantly transmitted by wireless communication. The sensor electrodes are embedded into the bottom of a supporting rod so that the sensor can measure soil water contents at different depths. An optimal design with time executing sequence is considered to reduce the energy consumption. The experimental results showed that the sensor is a promising tool for monitoring moisture in large-scale farmland using solar power and wireless communication.

  17. Toxicity interaction between chlorpyrifos, mancozeb and soil moisture to the terrestrial isopod Porcellionides pruinosus.

    Science.gov (United States)

    Morgado, Rui G; Gomes, Pedro A D; Ferreira, Nuno G C; Cardoso, Diogo N; Santos, Miguel J G; Soares, Amadeu M V M; Loureiro, Susana

    2016-02-01

    A main source of uncertainty currently associated with environmental risk assessment of chemicals is the poor understanding of the influence of environmental factors on the toxicity of xenobiotics. Aiming to reduce this uncertainty, here we evaluate the joint-effects of two pesticides (chlorpyrifos and mancozeb) on the terrestrial isopod Porcellionides pruinosus under different soil moisture regimes. A full factorial design, including three treatments of each pesticide and an untreated control, were performed under different soil moisture regimes: 25%, 50%, and 75% WHC. Our results showed that soil moisture had no effects on isopods survival, at the levels assessed in this experiment, neither regarding single pesticides nor mixture treatments. Additivity was always the most parsimonious result when both pesticides were present. Oppositely, both feeding activity and biomass change showed a higher sensitivity to soil moisture, with isopods generally showing worse performance when exposed to pesticides and dry or moist conditions. Most of the significant differences between soil moisture regimes were found in single pesticide treatments, yet different responses to mixtures could still be distinguished depending on the soil moisture assessed. This study shows that while soil moisture has the potential to influence the effects of the pesticide mixture itself, such effects might become less important in a context of complex combinations of stressors, as the major contribution comes from its individual interaction with each pesticide. Finally, the implications of our results are discussed in light of the current state of environmental risk assessment procedures and some future perspectives are advanced. Copyright © 2015 Elsevier Ltd. All rights reserved.

  18. 4.4 Development of a 30-Year Soil Moisture Climatology for Situational Awareness and Public Health Applications

    Science.gov (United States)

    Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.

    2015-01-01

    This paper provided a brief background on the work being done at NASA SPoRT and the CDC to create a soil moisture climatology over the CONUS at high spatial resolution, and to provide a valuable source of soil moisture information to the CDC for monitoring conditions that could favor the development of Valley Fever. The soil moisture climatology has multi-faceted applications for both the NOAA/NWS situational awareness in the areas of drought and flooding, and for the Public Health community. SPoRT plans to increase its interaction with the drought monitoring and Public Health communities by enhancing this testbed soil moisture anomaly product. This soil moisture climatology run will also serve as a foundation for upgrading the real-time (currently southeastern CONUS) SPoRT-LIS to a full CONUS domain based on LIS version 7 and incorporating real-time GVF data from the Suomi-NPP Visible Infrared Imaging Radiometer Suite (Vargas et al. 2013) into LIS-Noah. The upgraded SPoRT-LIS run will serve as a testbed proof-of-concept of a higher-resolution NLDAS-2 modeling member. The climatology run will be extended to near real-time using the NLDAS-2 meteorological forcing from 2011 to present. The fixed 1981-2010 climatology shall provide the soil moisture "normals" for the production of real-time soil moisture anomalies. SPoRT also envisions a web-mapping type of service in which an end-user could put in a request for either an historical or real-time soil moisture anomaly graph for a specified county (as exemplified by Figure 2) and/or for local and regional maps of soil moisture proxy percentiles. Finally, SPoRT seeks to assimilate satellite soil moisture data from the current Soil Moisture Ocean Salinity (SMOS; Blankenship et al. 2014) and the recently-launched NASA Soil Moisture Active Passive (SMAP; Entekhabi et al. 2010) missions, using the EnKF capability within LIS. The 9-km combined active radar and passive microwave retrieval product from SMAP (Das et al. 2011

  19. Rainfall events and soil moisture deviations as detected by operational ASCAT soil moisture data: case study in semi-arid regions of Somalia

    Science.gov (United States)

    Doubkova, M.; Bartsch, A.; Wagner, W.

    2009-04-01

    Large and widely dispersed populations in Somalia depend on pastoralism and on rainfed and irrigated farming. Droughts and floods that have plagued the country in the course of its history were critical for the herders and farmers and have often initiated long-lasting food crises. Recently, the Somalia Water and Land Information Management (SWALIM) has initiated collaborative activities to identify and quantify the physical causes of drought for better understanding of this phenomenon and better addressing the humanitarian aid in Somalia. The soil moisture was identified as one of the parameter that may improve the drought assessment studies in Somalia. The poor accessibility and long-lasting conflicts in Somalia region caused periods of missing values in the meteorological networks that complicate or disable further weather analyses. In this study, a comparison of operational available spatial soil moisture dataset from active microwave sensor with 50 km spatial resolution - ASCAT scatterometer - with existing in-situ rainfall data is performed. The ASCAT data are processed at the Vienna University of Technology (TU WIEN), and recently became operationally available via EUMETCAST. Together with its predecessor - ERS 1/2 - the ASCAT/ERS scatterometers embrace period of 1992 until recent with existing gap over Somalia (2001-2007). The rainfall data were provided by the SWALIM organization. The focus is brought on the ability of the ASCAT scatterometer to detect first rains in the season that dictate the schedule of agricultural activities from land preparation, crop variety to selection to planting. Further, the ability to detect moisture deviations with coarse resolution soil moisture data is studied. The remote sensing data are especially important for countries like Somalia with the poor field accessibility. The improved understanding of the soil moisture data from active microwave sensor may help in interpolating data from existing in-situ networks both

  20. Influence of physical and chemical properties of different soil types on optimal soil moisture for tillage

    Directory of Open Access Journals (Sweden)

    Vladimir Zebec

    2017-01-01

    Full Text Available Soil plasticity is the area of soil consistency, i.e. it represents a change in soil condition due to different soil moisture influenced by external forces activity. Consistency determines soil resistance in tillage, therefore, the aim of the research was to determine the optimum soil moisture condition for tillage and the influence of the chemical and physical properties of the arable land horizons on the soil plasticity on three different types of soil (fluvisol, luvisol and humic glaysol. Statistically significant differences were found between all examined soil types, such as the content of clay particles, the density of packaging and the actual and substitution acidity, the cation exchange capacity and the content of calcium. There were also statistically significant differences between the examined types of soil for the plasticity limit, liquid limit and the plasticity index. The average established value of plasticity limit as an important element for determining the optimal moment of soil tillage was 18.9% mass on fluvisol, 24.0% mass on luvisol and 28.6% mass on humic glaysol. Very significant positive direction correlation with plasticity limits was shown by organic matter, clay, fine silt, magnesium, sodium and calcium, while very significant negative direction correlation was shown by hydrolytic acidity, coarse sand, fine sand and coarse silt. Created regression models can estimate the optimal soil moisture condition for soil cultivation based on the basic soil properties. The model precision is significantly increased by introducing a greater number of agrochemical and agrophysical soil properties, and the additional precision of the model can be increased by soil type data.

  1. Spatial and temporal variability of soil moisture in a restored reach of an Alpine river

    Science.gov (United States)

    Luster, Jörg

    2010-05-01

    replicates for each FPZ and depth. At all monitoring locations the occurrence of water saturation in a given soil layer could be related to river discharge and additional soil moisture peaks in topsoil to rain events. However, absolute soil moisture levels during unsatured conditions exhibited strong spatial variability in all FPZ, probably mainly due to variability in soil texture and plant cover. In addition, in the grass zone the major summer floodings changed conditions at least temporarily. On one hand, the soil's field capacity apparently increased stepwise with each flooding, which may be explained either by fresh input of fine sediments or by retarded wetting of hydrophobic microsites rich in soil organic matter. On the other hand, the dominant canary reed grass was irreversibly flattened by each flood and replaced by a new generation of small seedlings. Processes and events as those described before complicate predictions of soil moisture in highly dynamic and biologically active systems like colonized gravel bars. In addition, it has consequences for the rate of sensitive biogeochemical processes such as denitrification which is strongly affected by soil moisture.

  2. Linking the distribution of carbon isotope ratios in soil carbonates and speleothems to climate conditions in the past: A model for the dependence of respiration rate on soil moisture

    Science.gov (United States)

    Liu, Y.; Ibarra, D. E.; Winnick, M.; Caves Rugenstein, J. K.; Oster, J. L.; Druhan, J. L.

    2017-12-01

    The carbon isotope compositions (δ13C) of atmospheric CO2, C3-origin organic carbon, and limestone epikarst differ substantially, resulting in variable δ13C signatures recorded in secondary soil carbonates and speleothems which represent a mixture of these sources. Even though this signal has been widely used in paleoclimate studies, the extent to which carbonate δ13C is influenced by the dynamic response of organic carbon respiration rates to soil moisture variations has yet to be fully evaluated [1]. Soils that are rewetted after a prolonged drought commonly display a peak in respiration rate followed by relaxation to a lower steady state in both lab incubation experiments and field observations. This transient behavior, known as the Birch effect, has been extensively observed across a broad range of locations and soil types, and may generate more than 50% of the total respired CO2 in some ecosystems [2]. Here, we seek to identify the influence of the Birch effect on carbonate δ13C records based on a moisture-dependent modeling approach. We report compiled respiration rates of soils from the literature and fit these data as a function of soil moisture, before imposing exponential dampening with depth and applying the resulting function in a production-diffusion equation [3]. We then implement a mass balance calculation for the δ13C value of carbonate precipitated from a mixture of atmospheric and respired CO2, including mass-dependent fractionation associated with diffusive transport. Our results offer a novel prediction for depth-resolved carbonate δ13C as a function of soil moisture, and suggest that Birch effect signals may be recorded in soil carbonates and influence the magnitude of carbonate δ13C variations in speleothems. Thus, we illustrate a prediction for the range of carbonate δ13C recorded in terrestrial carbonates and suggest that differences in the range of carbonate δ13C may indicate changes in soil moisture variability, providing a new

  3. Spatial and temporal monitoring of soil moisture using surface electrical resistivity tomography in Mediterranean soils

    NARCIS (Netherlands)

    Alamry, Abdulmohsen S.; van der Meijde, Mark; Noomen, Marleen; Addink, Elisabeth A.|info:eu-repo/dai/nl/224281216; van Benthem, Rik; de Jong, Steven M.|info:eu-repo/dai/nl/120221306

    2017-01-01

    ERT techniques are especially promising in (semi-arid) areas with shallow and rocky soils where other methods fail to produce soil moisture maps and to obtain soil profile information. Electrical Resistivity Tomography (ERT) was performed in the Peyne catchment in southern France at four sites

  4. Extending the soil moisture record of the climate reference network with machine learning

    Science.gov (United States)

    Soil moisture estimation is crucial for agricultural decision-support and a key component of hydrological and climatic research. Unfortunately, quality-controlled soil moisture time series data are uncommon before the most recent decade. However, time series data for precipitation are accessible at ...

  5. The Development of Terrestrial Water Cycle Applications for SMAP Soil Moisture Data Products

    Science.gov (United States)

    Soil moisture storage sits at the locus of the terrestrial water cycle and governs the relative partitioning of precipitation into various land surface flux components. Consequently, improved observational constraint of soil moisture variations should improve our ability to globally monitor the te...

  6. A practical approach for deriving all-weather soil moisture content using combined satellite and meteorological data

    Science.gov (United States)

    Leng, Pei; Li, Zhao-Liang; Duan, Si-Bo; Gao, Mao-Fang; Huo, Hong-Yuan

    2017-09-01

    Soil moisture has long been recognized as one of the essential variables in the water cycle and energy budget between Earth's surface and atmosphere. The present study develops a practical approach for deriving all-weather soil moisture using combined satellite images