Yang, Zhengwei; Sherstha, Ranjay; Crow, Wade; Bolten, John; Mladenova, Iva; Yu, Genong; Di, Liping
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.
Mishra, Ashok; Vu, Tue; Veettil, Anoop Valiya; Entekhabi, Dara
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
Leone, Marco; Principe, Sofia; Consales, Marco; Parente, Roberto; Laudati, Armando; Caliro, Stefano; Cutolo, Antonello; Cusano, Andrea
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.
W. B. Anderson
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
Zhu, Wenbin; Lv, Aifeng; Jia, Shaofeng; Sun, Liang
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.
Merzouki, A.; McNairn, H.; Powers, J.; Friesen, M.
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.
H.-J. F. Benninga
Full Text Available We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2, and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2. Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m−3. The first set of measurements has been retrieved for the period 5 April 2016–4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data and information (elevation, soil physical characteristics, land cover and a geohydrological model available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.
Benninga, Harm-Jan F.; Carranza, Coleen D. U.; Pezij, Michiel; van Santen, Pim; van der Ploeg, Martine J.; Augustijn, Denie C. M.; van der Velde, Rogier
We have established a soil moisture profile monitoring network in the Raam region in the Netherlands. This region faces water shortages during summers and excess of water during winters and after extreme precipitation events. Water management can benefit from reliable information on the soil water availability and water storing capacity in the unsaturated zone. In situ measurements provide a direct source of information on which water managers can base their decisions. Moreover, these measurements are commonly used as a reference for the calibration and validation of soil moisture content products derived from earth observations or obtained by model simulations. Distributed over the Raam region, we have equipped 14 agricultural fields and 1 natural grass field with soil moisture and soil temperature monitoring instrumentation, consisting of Decagon 5TM sensors installed at depths of 5, 10, 20, 40 and 80 cm. In total, 12 stations are located within the Raam catchment (catchment area of 223 km2), and 5 of these stations are located within the closed sub-catchment Hooge Raam (catchment area of 41 km2). Soil-specific calibration functions that have been developed for the 5TM sensors under laboratory conditions lead to an accuracy of 0.02 m3 m-3. The first set of measurements has been retrieved for the period 5 April 2016-4 April 2017. In this paper, we describe the Raam monitoring network and instrumentation, the soil-specific calibration of the sensors, the first year of measurements, and additional measurements (soil temperature, phreatic groundwater levels and meteorological data) and information (elevation, soil physical characteristics, land cover and a geohydrological model) available for performing scientific research. The data are available at https://doi.org/10.4121/uuid:dc364e97-d44a-403f-82a7-121902deeb56.
Wigneron, J.P.; Schmugge, T.; Chanzy, A.; Calvet, J.C.; Kerr, Y.
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
Campana, C.; Gigante, V.; Iacobellis, V.
The signature of the hydrologic regime can be investigated, in principle, by recognizing the main mechanisms of runoff generation that take place in the basin and affect the seasonal behavior or the rainfall-driven events. In this framework, besides the implementation of hydrological models, a crucial role should be played by direct observation of key state variables such as soil moisture at different depths and different distances from the river network. In fact, understanding hydrological systems is often limited by the frequency and spatial distribution of observations. Experimental catchments, which are field laboratories with long-term measurements of hydrological variables, are not only sources of data but also sources of knowledge. Wireless distributed sensing platforms are a key technology to address the need for overcoming field limitations such as conflicts between soil use and cable connections. A stand-alone wireless network system has been installed for continuous monitoring of soil water contents at multiple depths along a transect located in Celone basin (sub-basin of Candelaro basin in Puglia, Southern Italy). The transect consists of five verticals, each one having three soil water content sensors at multiple depths: 0,05 m, 0,6 m and 1,2 m below the ground level. The total length of the transect is 307 m and the average distance between the verticals is 77 m. The main elements of the instrumental system installed are: fifteen Decagon 10HS Soil Moisture Sensors, five Decagon Em50R Wireless Radio Data Loggers, one Rain gauge, one Decagon Data Station and one Campbell CR1000 Data Logger. Main advantages of the system as described and presented in this work are that installation of the wireless network system is fast and easy to use, data retrieval and monitoring information over large spatial scales can be obtained in (near) real-time mode and finally other type of sensors can be connected to the system, also offering wide potentials for future
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.
Gibon, François; Pellarin, Thierry; Alhassane, Agali; Traoré, Seydou; Baron, Christian
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
Velpuri, Naga Manohar; Senay, Gabriel B.; Morisette, Jeffrey T.
Level 3 soil moisture datasets from the recently launched Soil Moisture Active Passive (SMAP) satellite are evaluated for drought monitoring in rangelands.Validation of SMAP soil moisture (SSM) with in situ and modeled estimates showed high level of agreement.SSM showed the highest correlation with surface soil moisture (0-5 cm) and a strong correlation to depths up to 20 cm.SSM showed a reliable and expected response of capturing seasonal dynamics in relation to precipitation, land surface temperature, and evapotranspiration.Further evaluation using multi-year SMAP datasets is necessary to quantify the full benefits and limitations for drought monitoring in rangelands.
Crop condition information is critical for public and private sector decision making that concerns agricultural policy, food production, food security, and food commodity prices. Crop conditions change quickly due to various growing condition events, such as temperature extremes, soil moisture defic...
Soil moisture condition is an important indicator for agricultural drought monitoring. Through the Land Parameter Retrieval Model (LPRM), vegetation optical depth (VOD) as well as surface soil moisture (SM) can be retrieved simultaneously from brightness temperature observations from the Advanced Mi...
Albergel, C.; Dorigo, W.; Balsamo, G.; Sabatar, J; de Rosnay, P.; Isaksen, I; Brocca, L; de Jeu, R.A.M.; Wagner, W.
Soil moisture from ERA-Land, a revised version of the land surface components of the European Centre for Medium-Range Weather Forecasts Interim reanalysis (ERA-Interim), is used to monitor at a global scale the consistency of a new microwave based multi-satellite surface soil moisture date set
A wireless sensor network (WSN) was developed and deployed in three fields to monitor soil water status and collect weather data for irrigation scheduling. The WSN consists of soil-water sensors, weather sensors, wireless data loggers, and a wireless modem. Soil-water sensors were installed at three...
Salve, R.; Cook, P.J.
To facilitate investigations of moisture dynamics inunsaturated soil, we have developed a technique to qualitatively monitorpatterns of saturation changes. Field results suggest that this device,the sensor array system (SAS), is suitable for determining changes inrelative wetness along vertical soil profiles. The performance of theseprobes was compared with that of the time domain reflectometry (TDR)technique under controlled and field conditions. Measurements from bothtechniques suggest that by obtaining data at high spatial and temporalresolution, the SAS technique was effective in determining patterns ofsaturation changes along a soil profile. In addition, hardware used inthe SAS technique was significantly cheaper than the TDR system, and thesensor arrays were much easier to install along a soilprofile.
Bolten, John D.; Crow, Wade T.; Zhan, Xiwu; Jackson, Thomas J.; Reynolds,Curt
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.
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
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.)
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
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
McNally, A.; Funk, C. C.; Yatheendradas, S.; Michaelsen, J.; Cappelarere, B.; Peters-Lidard, C. D.; Verdin, J. P.
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
Petropoulos, George P; McCalmont, Jon P
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.
Sayde, C.; Gregory, C.; Gil-Rodriguez, M.; Tufillaro, N.; Tyler, S.; Van de Giesen, N.C.; English, M.; Cuenca, R.; Selker, J.S.
Accurate methods are needed to measure changing soil water content from meter to kilometer scales. Laboratory results demonstrate the feasibility of the heat pulse method implemented with fiber optic temperature sensing to obtain accurate distributed measurements of soil water content. A fiber optic
Hun, Eunjin; Crow, Wade T.; Holmes, Thomas; Bolten, John
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.
L. L. Boersma; D. Kirkham; D. Norum; R. Ziemer; J. C. Guitjens; J. Davidson; J. N. Luthin
Infiltration continues to occupy the attention of soil physicists and engineers. A theoretical and experimental analysis of the effect of surface sealing on infiltration by Edwards and Larson  showed that raindrops reduced the infiltration rate by as much as 50% for a two-hour period of infiltration. The effect of raindrops on the surface infiltration rate of...
Sérgio Francisco Pichorim
Full Text Available Two solutions for UHF RFID tags for soil moisture sensing were designed and are described in this paper. In the first, two conventional tags (standard transponders are employed: one, placed close to the soil surface, is the sensor tag, while the other, separated from the soil, is the reference for system calibration. By transmission power ramps, the tag’s turn-on power levels are measured and correlated with soil condition (dry or wet. In the second solution, the SL900A chip, which supports up to two external sensors and an internal temperature sensor, is used. An interdigital capacitive sensor was connected to the transponder chip and used for soil moisture measurement. In a novel design for an UHF RFID tag the sensor is placed below the soil surface, while the transponder and antenna are above the soil to improve communication. Both solutions are evaluated practically and results show the presence of water in soil can be remotely detected allowing for their application in landslide monitoring.
Rosanno de Dios
Full Text Available This paper describes the design, implementation and characterization of a sensor network intended for monitoring of slope deformation and potential failures. The sensor network system consists of a tilt and moisture sensor column, a pore water pressure sensor column and a personal computer for data storage and processing. The tilt sensor column consists of several pipe segments containing tri-axial accelerometers and signal processing electronics. Each segment is joined together by flexible joints to allow for the column to deform and subsequently track underground movement. Capacitive-type sensors for soil moisture measurement are also included in the sensor column, which are used to measure the soil moisture at different depths. The measurements at each segment are transferred via a Controller Area Network (CAN bus, where the CAN master node is located at the top of the column above ground. The CAN master node transmits the collected data from the slave nodes via a wireless connection to a personal computer that performs data storage, processing and display via a Python-based graphical user interface (GUI. The entire system was deployed and characterized on a small-scale slope model. Slope failure was induced via water seepage and the system was demonstrated to ably measure the inclination and soil moisture content throughout the landslide event.
Schrön, Martin; Köhli, Markus; Zreda, Marek; Dietrich, Peter; Zacharias, Steffen
Cosmic-ray neutron sensing is a unique and an increasingly accepted method to monitor the effective soil water content at the field scale. The technology is famous for its low maintenance, non-invasiveness, continuous measurement, and most importantly, for its large footprint. Being more representative than point data and finer resolved than remote-sensing products, cosmic-ray neutron derived soil moisture products provide unrivaled advantage for mesoscale hydrologic and land surface models. The method takes advantage of neutrons induced by cosmic radiation which are extraordinarily sensitive to hydrogen and behave like a hot gas. Information about nearby water sources are quickly mixed in a domain of tens of hectares in air. Since experimental determination of the actual spatial extent is hardly possible, scientists have applied numerical models to address the footprint characteristics. We have revisited previous neutron transport simulations and present a modified conceptual design and refined physical assumptions. Our revised study reveals new insights into probing distance and water sensitivity of detected neutrons under various environmental conditions. These results sharpen the range of interpretation concerning the spatial extent of integral soil moisture products derived from cosmic-ray neutron counts. Our findings will have important impact on calibration strategies, on scales for data assimilation and on the interpolation of soil moisture data derived from mobile cosmic-ray neutron surveys.
Wagner, Wolfgang; Bauer-Marschallinger, Bernhard; Hochstöger, Simon
The Advanced Scatterometer (ASCAT) is a C-Band radar instrument flown on board of the series of three METOP satellites. Albeit not operating in one of the more favorable longer wavelength ranges (S, L or P-band) as the dedicated Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions, it is one of main microwave sensors used for monitoring of soil moisture on a global scale. Its attractiveness for soil moisture monitoring applications stems from its operational status, high radiometric accuracy and stability, short revisit time, multiple viewing directions and long heritage (Wagner et al. 2013). From an application perspective, its main limitation is its spatial resolution of about 25 km, which does not allow resolving soil moisture patterns driven by smaller-scale hydrometeorological processes (e.g. convective precipitation, runoff patterns, etc.) that are themselves related to highly variable land surface characteristics (soil characteristics, topography, vegetation cover, etc.). Fortunately, the technique of aperture synthesis allows to significantly improve the spatial resolution of spaceborne radar instruments up to the meter scale. Yet, past Synthetic Aperture Radar (SAR) missions had not yet been designed to achieve a short revisit time required for soil moisture monitoring. This has only changed recently with the development and launch of SMAP (Entekhabi et al. 2010) and Sentinel-1 (Hornacek et al. 2012). Unfortunately, the SMAP radar failed only after a few months of operations, which leaves Sentinel-1 as the only currently operational SAR mission capable of delivering high-resolution radar observations with a revisit time of about three days for Europe, about weekly for most crop growing regions worldwide, and about bi-weekly to monthly over the rest of the land surface area. Like ASCAT, Sentinel-1 acquires C-band backscatter data in VV polarization over land. Therefore, for the interpretation of both ASCAT and Sentinel-1
Full Text Available Comprehensive surface soil moisture (SM monitoring is a vital task in precision agriculture applications. SM monitoring includes remote sensing imagery monitoring and in situ sensor-based observational monitoring. Cloud computing can increase computational efficiency enormously. A geographical web service was developed to assist in agronomic decision making, and this tool can be scaled to any location and crop. By integrating cloud computing and the web service-enabled information infrastructure, this study uses the cloud computing-enabled spatio-temporal cyber-physical infrastructure (CESCI to provide an efficient solution for soil moisture monitoring in precision agriculture. On the server side of CESCI, diverse Open Geospatial Consortium web services work closely with each other. Hubei Province, located on the Jianghan Plain in central China, is selected as the remote sensing study area in the experiment. The Baoxie scientific experimental field in Wuhan City is selected as the in situ sensor study area. The results show that the proposed method enhances the efficiency of remote sensing imagery mapping and in situ soil moisture interpolation. In addition, the proposed method is compared to other existing precision agriculture infrastructures. In this comparison, the proposed infrastructure performs soil moisture mapping in Hubei Province in 1.4 min and near real-time in situ soil moisture interpolation in an efficient manner. Moreover, an enhanced performance monitoring method can help to reduce costs in precision agriculture monitoring, as well as increasing agricultural productivity and farmers’ net-income.
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.
Wang, Tiejun; Franz, Trenton E.; Yue, Weifeng; Szilagyi, Jozsef; Zlotnik, Vitaly A.; You, Jinsheng; Chen, Xunhong; Shulski, Martha D.; Young, Aaron
Despite the importance of groundwater recharge (GR), its accurate estimation still remains one of the most challenging tasks in the field of hydrology. In this study, with the help of inverse modeling, long-term (6 years) soil moisture data at 34 sites from the Automated Weather Data Network (AWDN) were used to estimate the spatial distribution of GR across Nebraska, USA, where significant spatial variability exists in soil properties and precipitation (P). To ensure the generality of this study and its potential broad applications, data from public domains and literature were used to parameterize the standard Hydrus-1D model. Although observed soil moisture differed significantly across the AWDN sites mainly due to the variations in P and soil properties, the simulations were able to capture the dynamics of observed soil moisture under different climatic and soil conditions. The inferred mean annual GR from the calibrated models varied over three orders of magnitude across the study area. To assess the uncertainties of the approach, estimates of GR and actual evapotranspiration (ETa) from the calibrated models were compared to the GR and ETa obtained from other techniques in the study area (e.g., remote sensing, tracers, and regional water balance). Comparison clearly demonstrated the feasibility of inverse modeling and large-scale (>104 km2) soil moisture monitoring networks for estimating GR. In addition, the model results were used to further examine the impacts of climate and soil on GR. The data showed that both P and soil properties had significant impacts on GR in the study area with coarser soils generating higher GR; however, different relationships between GR and P emerged at the AWDN sites, defined by local climatic and soil conditions. In general, positive correlations existed between annual GR and P for the sites with coarser-textured soils or under wetter climatic conditions. With the rapidly expanding soil moisture monitoring networks around the
Haux, E.; Busek, N.; Park, Y.; Estrin, D.; Harmon, T. C.
The use of reclaimed wastewater for irrigation in agriculture can be a significant source of nutrients, in particular nitrogen species, but its use raises concern for groundwater, riparian, and water quality. A 'smart' technology would have the ability to measure wastewater nutrients as they enter the irrigation system, monitor their transport in situ and optimally control inputs with little human intervention, all in real-time. Soil heterogeneity and economic issues require, however, a balance between cost and the spatial and temporal scales of the monitoring effort. Therefore, a wireless and embedded sensor network, deployed in the soil vertically across the horizon, is capable of collecting, processing, and transmitting sensor data. The network consists of several networked nodes or 'pylons', each outfitted with an array of sensors measuring humidity, temperature, precipitation, soil moisture, and aqueous nitrate concentrations. Individual sensor arrays are controlled by a MICA2 mote (Crossbow Technology Inc., San Jose, CA) programmed with TinyOS (University of California, Berkeley, CA) and a Stargate (Crossbow Technology Inc., San Jose, CA) base-station capable of GPRS for data transmission. Results are reported for the construction and testing of a prototypical pylon at the benchtop and in the field.
Full Text Available Chongqing mountain citrus orchard is one of the main origins of Chinese citrus. Its planting terrain is complex and soil parent material is diverse. Currently, the citrus fertilization, irrigation and other management processes still have great blindness. They usually use the same pattern and the same formula rather than considering the orchard terrain features, soil differences, species characteristics and the state of tree growth. With the help of the ZigBee technology, artificial intelligence and decision support technology, this paper has developed the research on the application technology of agricultural Internet of Things for real-time monitoring of citrus soil moisture and nutrients as well as the research on the integration of fertilization and irrigation decision support system. Some achievements were obtained including single-point multi-layer citrus soil temperature and humidity detection wireless sensor nodes and citrus precision fertilization and irrigation management decision support system. They were applied in citrus base in the Three Gorges Reservoir Area. The results showed that the system could help the grower to scientifically fertilize or irrigate, improve the precision operation level of citrus production, reduce the labor cost and reduce the pollution caused by chemical fertilizer.
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...
Timmermans, J.; Gokmen, M.; Eden, U.; Abou Ali, M.; Vekerdy, Z.; Su, Z.
The need to good drought monitoring and management for the Horn of Africa has never been greater. This ongoing drought is the largest in the past sixty years and is effecting the life of around 10 million people, according to the United Nations. The impact of drought is most apparent in food security and health. In addition secondary problems arise related to the drought such as large migration; more than 15000 Somalia have fled to neighboring countries to escape the problems caused by the drought. These problems will only grow in the future to larger areas due to increase in extreme weather patterns due to global climate change. Monitoring drought impact and managing the drought effects are therefore of critical importance. The impact of a drought is hard to characterize as drought depends on several parameters, like precipitation, land use, irrigation. Consequently the effects of the drought vary spatially and range from short-term to long-term. For this reason a drought event can be characterized into four categories: meteorological, agricultural, hydrological and socio-economical. In terms of food production the agricultural drought, or short term dryness near the surface layer, is most important. This drought is usually characterized by low soil moisture content in the root zone, decreased evapotranspiration, and changes in vegetation vigor. All of these parameters can be detected with good accuracy from space. The advantage of remote sensing in Drought monitoring is evident. Drought monitoring is usually performed using drought indices, like the Palmer Index (PDSI), Crop Moisture Index (CMI), Standard Precipitation Index (SPI). With the introduction of remote sensing several indices of these have shown great potential for large scale application. These indices however all incorporate precipitation as the main surface parameter neglecting the response of the surface to the dryness. More recently two agricultural drought indices, the EvapoTranspiration Deficit
Alvarez-Garreton, C. D.; Ryu, D.; Western, A. W.; Crow, W. T.; Su, C. H.; Robertson, D. E.
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
Full Text Available The launch of the European Remote sensing Satellite (ERS-1 in July 1991 represented an important turning point in the development of Earth observation as it was the first of a series of satellites which would carry high resolution active microwave (radar sensors which could operate through the thickest cloudeover and provide continuity of data for at least a decade. This was of particular relevance to hydrological applications, such as soil moisture monitoring, which generally require frequent satellite observations to monitor changes in state. ERS-1 and its successor ERS-2 carry the active microwave instrument (AMI which operates in 3 modes (synthetic aperture radar, wind scatterometer and wave seatterometer together with the radar altimeter which may all be useful for the observation of soil moisture. This paper assesses the utility of these sensors through a comprehensive review of work in this field. Two approaches to soil moisture retrieval are identified: 1 inversion modelling, where the physical effects of vegetation and soil roughness on radar backscatter are quantified through the use of multi-frequency and/or multi-polarization sensors and 2 change detection where these effects are normalized through frequent satellite observation, the residual effects being attributed to short-term changes in soil moisture. Both approaches will be better supported by the future European Envisat-l satellite which will provide both multi-polarization SAR and low resolution products which should facilitate more frequent temporal observation.
Chen, Hui; Fan, Li; Wu, Wei; Liu, Hong-Bin
Soil moisture data can reflect valuable information on soil properties, terrain features, and drought condition. The current study compared and assessed the performance of different interpolation methods for estimating soil moisture in an area with complex topography in southwest China. The approaches were inverse distance weighting, multifarious forms of kriging, regularized spline with tension, and thin plate spline. The 5-day soil moisture observed at 167 stations and daily temperature recorded at 33 stations during the period of 2010-2014 were used in the current work. Model performance was tested with accuracy indicators of determination coefficient (R 2 ), mean absolute percentage error (MAPE), root mean square error (RMSE), relative root mean square error (RRMSE), and modeling efficiency (ME). The results indicated that inverse distance weighting had the best performance with R 2 , MAPE, RMSE, RRMSE, and ME of 0.32, 14.37, 13.02%, 0.16, and 0.30, respectively. Based on the best method, a spatial database of soil moisture was developed and used to investigate drought condition over the study area. The results showed that the distribution of drought was characterized by evidently regional difference. Besides, drought mainly occurred in August and September in the 5 years and was prone to happening in the western and central parts rather than in the northeastern and southeastern areas.
Coopersmith, E. J.; Cosh, M. H.
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.
Wienhold, K. J.; Li, D.; Fang, N. Z.
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.
Extreme hydrological processes are often very dynamic and destructive.A better understanding of these processes requires an accurate mapping of key variables that control them. In this regard, soil moisture is perhaps the most important parameter that impacts the magnitude of flooding events as it c...
Yue, H.; Liu, Y.
to climate change and human activities, Hong Jiannao Lake located in the arid and semi-arid area of China, it played a very important role in the regulation of the local climate, the balance of water resources and the maintenance of biological diversity. Hongjiannao Lake area in recent years continues to shrink, it was urgent to get the Hongjiannao Lake area change trend. This article take Hongjiannao Lake as study object using MODIS image of NIR and Red wavelength reflectivity data, selected April to October of 2000-2014,consturcted scale of SMMI (S-SMMI) based on soil moisture monitoring index (SMMI). The result indicated that lake area reduced from 46.9 km2 in 2000 to 27.8 km2 in 2014, average decay rate is 1.3 km2/a. The lake's annual change showed a trend of periodic change. In general, the lake area began to increase slowly each year in April, and the area of the lake area reached the maximum, and then decreased gradually in June to July. Finally, we analysed the main driving factors included natural, man-made, and underground mining which lead to the lake area shrink.
Chen, Hui; Wu, Wei; Liu, Hong-Bin
Numerous drought indices have been developed to analyze and monitor drought condition, but they are region specific and limited by various climatic conditions. In southwest China, summer drought mainly occurs from June to September, causing destructive and profound impact on agriculture, society, and ecosystems. The current study assesses the availability of meteorological drought indices in monitoring summer drought in this area at 5-day scale. The drought indices include the relative moisture index ( M), the standardized precipitation index (SPI), the standardized precipitation evapotranspiration index (SPEI), the composite index of meteorological drought (CIspi), and the improved composite index of meteorological drought (CIwap). Long-term daily precipitation and temperature from 1970 to 2014 are used to calculate 30-day M ( M 30), SPI (SPI30), SPEI (SPEI30), 90-day SPEI (SPEI90), CIspi, and CIwap. The 5-day soil moisture observations from 2010 to 2013 are applied to assess the performance of these drought indices. Correlation analysis, overall accuracy, and kappa coefficient are utilized to investigate the relationships between soil moisture and drought indices. Correlation analysis indicates that soil moisture is well correlated with CIwap, SPEI30, M 30, SPI30, and CIspi except SPEI90. Moreover, drought classifications identified by M 30 are in agreement with that of the observed soil moisture. The results show that M 30 based on precipitation and potential evapotranspiration is an appropriate indicator for monitoring drought condition at a finer scale in the study area. According to M 30, summer drought during 1970-2014 happened in each year and showed a slightly upward tendency in recent years.
McJannet, David; Hawdon, Aaron; Baker, Brett; Renzullo, Luigi; Searle, Ross
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.
De Vleeschouwer, N.; Verhoest, N.; Pauwels, V. R. N.
The continuous monitoring of soil moisture in a permanent network can yield an interesting data product for use in hydrological data assimilation. Major advantages of in situ observations compared to remote sensing products are the potential vertical extent of the measurements, the finer temporal resolution of the observation time series, the smaller impact of land cover variability on the observation bias, etc. However, two major disadvantages are the typical small integration volume of in situ measurements and the often large spacing between monitoring locations. This causes only a small part of the modelling domain to be directly observed. Furthermore, the spatial configuration of the monitoring network is typically temporally non-dynamic. Therefore two questions can be raised. Do spatially sparse in situ soil moisture observations contain a sufficient data representativeness to successfully assimilate them into the largely unobserved spatial extent of a distributed hydrological model? And if so, how is this assimilation best performed? Consequently two important factors that can influence the success of assimilating in situ monitored soil moisture are the spatial configuration of the monitoring network and the applied assimilation algorithm. In this research the influence of those factors is examined by means of synthetic data-assimilation experiments. The study area is the ± 100 km² catchment of the Bellebeek in Flanders, Belgium. The influence of the spatial configuration is examined by varying the amount of locations and their position in the landscape. The latter is performed using several techniques including temporal stability analysis and clustering. Furthermore the observation depth is considered by comparing assimilation of surface layer (5 cm) and deeper layer (50 cm) observations. The impact of the assimilation algorithm is assessed by comparing the performance obtained with two well-known algorithms: Newtonian nudging and the Ensemble Kalman
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
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.
Bertoldi, Giacomo; Brenner, Johannes; Notarnicola, Claudia; Greifeneder, Felix; Nicolini, Irene; Della Chiesa, Stefano; Niedrist, Georg; Tappeiner, Ulrike
Soil moisture content (SMC) is a key factor for numerous processes, including runoff generation, groundwater recharge, evapotranspiration, soil respiration, and biological productivity. Understanding the controls on the spatial and temporal variability of SMC in mountain catchments is an essential step towards improving quantitative predictions of catchment hydrological processes and related ecosystem services. The interacting influences of precipitation, soil properties, vegetation, and topography on SMC and the influence of SMC patterns on runoff generation processes have been extensively investigated (Vereecken et al., 2014). However, in mountain areas, obtaining reliable SMC estimations is still challenging, because of the high variability in topography, soil and vegetation properties. In the last few years, there has been an increasing interest in the estimation of surface SMC at local scales. On the one hand, low cost wireless sensor networks provide high-resolution SMC time series. On the other hand, active remote sensing microwave techniques, such as Synthetic Aperture Radars (SARs), show promising results (Bertoldi et al. 2014). As these data provide continuous coverage of large spatial extents with high spatial resolution (10-20 m), they are particularly in demand for mountain areas. However, there are still limitations related to the fact that the SAR signal can penetrate only a few centimeters in the soil. Moreover, the signal is strongly influenced by vegetation, surface roughness and topography. In this contribution, we analyse the spatial and temporal dynamics of surface and root-zone SMC (2.5 - 5 - 25 cm depth) of alpine meadows and pastures in the Long Term Ecological Research (LTER) Area Mazia Valley (South Tyrol - Italy) with different techniques: (I) a network of 18 stations; (II) field campaigns with mobile ground sensors; (III) 20-m resolution RADARSAT2 SAR images; (IV) numerical simulations using the GEOtop hydrological model (Rigon et al
Jucicléia Soares da Silva
Knowledge of the factors related to the development of the vine is very important because it has implications for the production. Thus, the aim of this study was to determine the moisture, using the monitoring technique tensiometry fingerstick. The experiment was conducted in the agricultural area of the Federal Institute of Education, Science and Technology Pernambucano Hinterland on the campus located in Petrolina Rural Zone - PE and a privately owned table grape. They were carried out in the areas of collecting undisturbed soil samples to obtain the retention curve of water through the soil. Three batteries tensiometers were installed at depths of 0-0.3 and 0.3-0.6 m in the IF field and 0-0, 2, 0.2-0.4 and 0.4-0.6 m the privately owned area for table grapes and three batteries in the depth of 0-0.3 and 0.3-0.6 m in the IF area for wine grape. It was concluded that the moisture in the upper layers in the table grape and wine IF always stood above the field capacity, indicating problems of surface leaching. The moisture in the lower layers in the table grape on private property stood close and slightly above the field capacity, indicating deep leaching problems.
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 ...
temporal distributions of key variables in the hydrological cycle, such as soil moisture, evapotranspiration (ET) and precipitation. The multi-sensor platform may include not only in-situ sensor network, ground-based radar, air-borne aircraft, but also even space-borne satellites. The use of a decadal-scale historical record from 1998 to 2008 to support such a trend analysis via NEXRAD (Rainfall), GOES (ET), and MODIS (soil moisture) satellite images may uniquely support middle-term and long-term water resources management in the near future. This study confirms that the potential of using remotely sensed time-series biophysical and ecohydrological states of landscape to characterize soil moisture condition, ET, and other states should be further investigated based on the pros and cons of each type of satellite imageries so as to maximize the beneficial use of remote sensing.
Full Text Available Hydrologic processes, such as runoff production or evapotranspiration, largely depend on the variation of soil moisture and its spatial pattern. The interaction of electromagnetic waves with the land surface can be dependant on the water content of the uppermost soil layer. Especially in the microwave domain of the electromagnetic spectrum, this is the case. New sensors as e.g. ENVISAT ASAR, allow for frequent, synoptically and homogeneous image acquisitions over larger areas. Parameter inversion models are therefore developed to derive bio- and geophysical parameters from the image products. The paper presents a soil moisture inversion model for ENVISAT ASAR data for local and regional scale applications. The model is validated against in situ soil moisture measurements. The various sources of uncertainties, being related to the inversion process are assessed and quantified.
Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...
A method for calibrating an aluminum oxide hygrometer against an optical chilled mirror dew-point hygrometer has been established. A theoretical cross-point line of dew points from both hygrometers and a maximum moisture content of 10 ppM/sub v/ are used to define an area for calibrating the sensor probes of the aluminum oxide hygrometer
1973-01-01Established 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
Soil moisture estimates are valuable for hydrologic modeling and agricultural decision support. These estimates are typically produced via a combination of sparse ¬in situ networks and remotely-sensed products or where sensory grids and quality satellite estimates are unavailable, through derived h...
The results of both laboratory and field experiments indicate that the neutron moisture gauge traditionally used in soil physics experiments can be extended for use in large diameter (up to 15 cm) steel-cased boreholes with excellent results. This application will permit existing saturated zone monitoring wells to be used for unsaturated zone monitoring of recharge, redistribution and leak detection from waste disposal facilities. Its applicability to large diameter cased wells also gives the soil physicist and ground-water hydrologist and new set of monitoring points in the unsaturated zone to study recharge and aquifer properties. 6 refs., 6 figs., 2 tabs
project. The principal investigator for this study was Dr. Ernest S. Berney IV, Airfields and Pavements Branch (APB), Engineering Systems and Materials...measuring the deceleration of the weight as it impacts the soil. The CIV is the deceleration measured in micro gravities, with a well-defined proctor...American Society for Testing and Materials. _____ 2010. Standard test method for use of the dynamic cone penetrometer in shallow pavement applications
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...
Gou, S.; Miller, G. R.
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
McNally, Amy; Shukla, Shraddhanand; Arsenault, Kristi R.; Wang, Shugong; Peters-Lidard, Christa D.; Verdin, James P.
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.
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...
Full Text Available Sea surface salinity (SSS links various components of the Arctic freshwater system. SSS responds to freshwater inputs from river discharge, sea ice change, precipitation and evaporation, and oceanic transport through the open straits of the Pacific and Atlantic oceans. However, in situ SSS data in the Arctic Ocean are very sparse and insufficient to depict the large-scale variability to address the critical question of how climate variability and change affect the Arctic Ocean freshwater. The L-band microwave radiometer on board the NASA Soil Moisture Active Passive (SMAP mission has been providing SSS measurements since April 2015, at approximately 60 km resolution with Arctic Ocean coverage in 1–2 days. With improved land/ice correction, the SMAP SSS algorithm that was developed at the Jet Propulsion Laboratory (JPL is able to retrieve SSS in ice-free regions 35 km of the coast. SMAP observes a large-scale contrast in salinity between the Atlantic and Pacific sides of the Arctic Ocean, while retrievals within the Arctic Circle vary over time, depending on the sea ice coverage and river runoff. We assess the accuracy of SMAP SSS through comparative analysis with in situ salinity data collected by Argo floats, ships, gliders, and in field campaigns. Results derived from nearly 20,000 pairs of SMAP and in situ data North of 50°N collocated within a 12.5-km radius and daily time window indicate a Root Mean Square Difference (RMSD less than ~1 psu with a correlation coefficient of 0.82 and a near unity regression slope over the entire range of salinity. In contrast, the Hybrid Coordinate Ocean Model (HYCOM has a smaller RMSD with Argo. However, there are clear systematic biases in the HYCOM for salinity in the range of 25–30 psu, leading to a regression slope of about 0.5. In the region North of 65°N, the number of collocated samples drops more than 70%, resulting in an RMSD of about 1.2 psu. SMAP SSS in the Kara Sea shows a consistent
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...
Singh, Gurjeet; Panda, Rabindra K.; Mohanty, Binayak P.; Jana, Raghavendra Belur
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
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.
Robert R. Ziemer
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...
Bian, Zhengfu; Lei, Shaogang; Inyang, Hilary I.; Chang, Luqun; Zhang, Richen; Zhou, Chengjun; He, Xiao
Mining affects the environment in different ways depending on the physical context in which the mining occurs. In mining areas with an arid environment, mining affects plants’ growth by changing the amount of available water. This paper discusses the effects of mining on two important determinants of plant growth—soil moisture and groundwater table (GWT)—which were investigated using an integrated approach involving a field sampling investigation with remote sensing (RS) and ground-penetrating radar (GPR). To calculate and map the distribution of soil moisture for a target area, we initially analyzed four models for regression analysis between soil moisture and apparent thermal inertia and finally selected a linear model for modeling the soil moisture at a depth 10 cm; the relative error of the modeled soil moisture was about 6.3% and correlation coefficient 0.7794. A comparison of mined and unmined areas based on the results of limited field sampling tests or RS monitoring of Landsat 5-thermatic mapping (TM) data indicated that soil moisture did not undergo remarkable changes following mining. This result indicates that mining does not have an effect on soil moisture in the Shendong coal mining area. The coverage of vegetation in 2005 was compared with that in 1995 by means of the normalized difference vegetation index (NDVI) deduced from TM data, and the results showed that the coverage of vegetation in Shendong coal mining area has improved greatly since 1995 because of policy input RMB¥0.4 per ton coal production by Shendong Coal Mining Company. The factor most affected by coal mining was GWT, which dropped from a depth of 35.41 m before mining to a depth of 43.38 m after mining at the Bulianta Coal Mine based on water well measurements. Ground-penetrating radar at frequencies of 25 and 50 MHz revealed that the deepest GWT was at about 43.4 m. There was a weak water linkage between the unsaturated zone and groundwater, and the decline of water table
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...
Minions, C.; Natali, S.; Ludwig, S.; Risk, D.; Macintyre, C. M.
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.
Tan, Adrian Eng-Choon; Richards, Sean; Platt, Ian; Woodhead, Ian
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)
Zavodsky, B.; Case, J.; White, K.; Bell, J. R.
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
... 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 ...
McColl, Kaighin A.; Wang, Wei; Peng, Bin; Akbar, Ruzbeh; Short Gianotti, Daniel J.; Lu, Hui; Pan, Ming; Entekhabi, Dara
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.
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
Jackson, T.J.; Schmugge, T.J.
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
Kapilaratne, R. G. C. Jeewantinie; Lu, Minjiao
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
Chen, Zijuan; Mohanty, Binayak P.; Rodriguez-Iturbe, Ignacio
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.
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 ...
Moghaddam, Mahta; Moller, Delwyn; Rodriguez, Ernesto; Rahmat-Samii, Yahya
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.
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.
Isaacson, R.E.; Brownell, L.E.; Nelson, R.W.; Roetman, E.L.
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)
Drainage rates through the profile were established using time domain reflectometry probes while water drainage volumes were assessed using shallow plate lysimeters. Despite slow growth in the unfelled crop during the monitoring period (attributed to a pest infestation), soil moisture depletion remained rapid and ...
Carpenter, K.E.; Fadeff, J.G.
During the past 50 years, a wide variety of chemical compounds have been placed in the 149 single-shell tanks (SSTS) on the Hanford Site. A concern relating to chemical stability, chemical control, and safe storage of the waste is the potential for propagating reactions as a result of ferrocyanide-oxidizer and organic-oxidizer concentrations in the SSTS. Propagating reactions in fuel-nitrate mixtures are precluded if the amounts of fuel and moisture present in the waste are within specified limits. Because most credible ignition sources occur near the waste surface, the main emphasis of this study is toward monitoring and controlling moisture in the top 14 cm (5.5 in.) of waste. The purpose of this engineering study is to recommend a moisture monitoring and control system for use in SSTs containing sludge and saltcake. This study includes recommendations for: (1) monitoring and controlling moisture in SSTs; (2) the fundamental design criteria for a moisture monitoring and control system; and (3) criteria for the deployment of a moisture monitoring and control system in hanford Site SSTs. To support system recommendations, technical bases for selecting and using a moisture monitoring and control system are presented. Key functional requirements and a conceptual design are included to enhance system development and establish design criteria
Wang, J. X.; Yu, B. S.; Zhang, G. Z.; Zhao, G. C.; He, S. D.; Luo, W. R.; Zhang, C. C.
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.
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.
Zagyvainé Kiss, Katalin Anita; Vastag, Viktor; Gribovszki, Zoltán; Kalicz, Péter
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.
Abbaszadeh, P.; Moradkhani, H.; Yan, H.
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.
Gines, G. A.; Bea, J. G.; Palaoag, T. D.
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.
Zwick, T.C.; Leeson, A.; Hinchee, R.E.; Hoeppel, R.E.; Bowling, L.
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
Reichel, Rüdiger; Radl, Viviane; Rosendahl, Ingrid; Albert, Andreas; Amelung, Wulf; Schloter, Michael; Thiele-Bruhn, Sören
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.
Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.
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.
Zhang, Z. F.; Strickland, C. E.; Field, J. G.
A 6000 m2 interim surface barrier has been constructed over a portion of the T Tank Farm in the Depart of Energy’s Hanford site. The purpose of using a surface barrier was to reduce or eliminate the infiltration of meteoric precipitation into the contaminated soil zone due to past leaks from Tank T-106 and hence to reduce the rate of movement of the plume. As part of the demonstration effort, vadose zone moisture is being monitored to assess the effectiveness of the barrier on the reduction of soil moisture flow. A vadose zone monitoring system was installed to measure soil water conditions at four horizontal locations (i.e., instrument Nests A, B, C, and D) outside, near the edge of, and beneath the barrier. Each instrument nest consists of a capacitance probe with multiple sensors, multiple heat-dissipation units, and a neutron probe access tube used to measure soil-water content and soil-water pressure. Nest A serves as a control by providing subsurface conditions outside the influence of the surface barrier. Nest B provides subsurface measurements to assess barrier edge effects. Nests C and D are used to assess the impact of the surface barrier on soil-moisture conditions beneath it. Monitoring began in September 2006 and continues to the present. To date, the monitoring system has provided high-quality data. Results show that the soil beneath the barrier has been draining from the shallower depth. The lack of climate-caused seasonal variation of soil water condition beneath the barrier indicates that the surface barrier has minimized water exchange between the soil and the atmosphere.
Passive microwave remote sensing of soil moisture has matured over the past decade as a result of the Advanced Microwave Scanning Radiometer (AMSR) program of JAXA. This program has resulted in improved algorithms that have been supported by rigorous validation. Access to the products and the valida...
Todisco, F.; Brocca, L.; Termite, L. F.; Wagner, W.
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.
Aquarius is the first satellite to provide both passive and active L-band observations of the Earth. In addition, the instruments on Satelite de Aplicaciones Cientificas-D (SAC-D) provide complementary information for analysis and retrieval algorithms. Our research focuses on the retrieval of soil m...
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...
Pospisil, S.; Janout, Z.; Kovacik, M.
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
Medina, C.; Neely, H.; Desilets, D.; Mohanty, B.; Moore, G. W.
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.
Liu, Cheng; Qian, Hongzhou; Cao, Weixing; Ni, Jun
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
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...
Orth, R.; Seneviratne, S. I.
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
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...
Full Text Available Construction of modern timber bridges has greatly increased during the last 20 years in Sweden. Wood as a construction material has several advantageous properties, e.g., it is renewable, sustainable, and aesthetically pleasing, but it is also susceptible to deterioration. To protect wood from deterioration and ensure the service life, the wood is either treated or somehow covered. This work evaluates a technology to monitor the moisture content in wood constructions. Monitoring the moisture content is important both to verify the constructive protection and for finding areas with elevated levels of moisture which might lead to a microbiological attack of the wood. In this work, a timber bridge was studied. The structure was equipped with six wireless sensors that measured the moisture content of the wood and the relative humidity every hour. Data for 744 days of the bridge are presented in this paper. Results show that the technology used to monitor the bridge generally works; however, there were issues due to communication problems and malfunction of sensors. This technology is promising for monitoring the state of wood constructions, but a more reliable sensor technology is warranted continuous remote monitoring of wood bridges over long periods of time.
Rodriguez-Alvarez, N.; Bosch-Lluis, X.; Camps, A.; Aguasca, A.; Vall-Llossera, M.; Valencia, E.; Ramos-Perez, I.; Park, H.
Reflectometry using Global Navigation Satellite Systems signals (GNSSR) has been the focus of many studies during the past few years for a number of applications over different scenarios as land, ocean or snow and ice surfaces. In the past decade, its potential has increased yearly, with improved receivers and signal processors, from generic GNSS receivers whose signals were recorded in magnetic tapes to instruments that measure full Delay Doppler Maps (the power distribution of the reflected GNSS signal over the 2-D space of delay offsets and Doppler shifts) in real time. At present, these techniques are considered to be promising tools to retrieve geophysical parameters such as soil moisture, vegetation height, topography, altimetry, sea state and ice and snow thickness, among others. This paper focuses on the land geophysical retrievals (topography, vegetation height and soil moisture) performed from a ground-based instrument using the Interference Pattern Technique (IPT). This technique consists of the measurement of the power fluctuations of the interference signal resulting from the simultaneous reception of the direct and the reflected GNSS signals. The latest experiment performed using this technique over a maize field is shown in this paper. After a review of the previous results, this paper presents the latest experiment performed using this technique over a maize field. This new study provides a deeper analysis on the soil moisture retrieval by observing three irrigation-drying cycles and comparing them to different depths soil moisture probes. Furthermore, the height of the maize, almost 300 cm, has allowed testing the capabilities of the technique over dense and packed vegetation layers, with high vegetation water content.
Emmet-Booth, Jeremy; Forristal, Dermot; Fenton, Owen; Bondi, Giulia; Creamer, Rachel; Holden, Nick
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
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.
Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig
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
The neutron probe measures sub-surface moisture in soil and other materials by means of high energy neutrons and a slow (thermal) neutron detector. Exposure to radiation, including neutrons, especially at high doses, can cause detrimental health effects. In order to achieve operational radiation safety, there must be compliance with protection and safety standards. The design and manufacture of commercially available neutron moisture gauges are such that risks to the health of the user have been greatly reduced. The major concern is radiation escape from the soil during measurement, especially under dry conditions and when the radius of influence is large. With appropriate work practices as well as good design and manufacture of gauges, recorded occupational doses have been well below recommended annual limits. It can be concluded that the use of neutron gauges poses not only acceptable health and safety risks but, in fact, the risks are negligible. Neutron gauges should not be classified as posing high potential health hazards. (author)
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.
Wang, J. R.
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.
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
Orr, Barron; Moran, M. Susan; Escobar, Vanessa; Brown, Molly E.
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.
Attalla, Daniela; Tannfelt Wu, Jennifer
In this thesis an automated greenhouse was built with the purpose of investigating the watering system’s reliability and if a desired range of temperatures can be maintained. The microcontroller used to create the automated greenhouse was an Arduino UNO. This project utilizes two different sensors, a soil moisture sensor and a temperature sensor. The sensors are controlling the two actuators which are a heating fan and a pump. The heating fan is used to change the temperature and the pump is ...
Roshani, E.; Berg, A. A.; Lindsay, J.
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
Samaniego, L.; Thober, S.; Kumar, R.; Wanders, N.; Rakovec, O.; Pan, M.; Zink, M.; Sheffield, J.; Wood, E. F.; Marx, A.
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.
Chen, Xiang-Bi; Wang, Ai-Hua; Hu, Le-Ning; Huang, Yuan; Li, Yang; He, Xun-Yang; Su, Yi-Rong
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.
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
Rajasekaran, E.; Das, N. N.; Entekhabi, D.; Yueh, S. H.
Identification of the onset and the end of droughts are important for socioeconomic planning. Different datasets and tools are either available or being generated for drought analysis to recognize the status of drought. The aim of this study is to understand the potential of the SMAP soil moisture (SM) data for identification of onset, persistence and withdrawal of droughts over the Contiguous United States. We are using the SMAP-passive level 3 soil moisture observations and the United States Drought Monitor (http://droughtmonitor.unl.edu) data for understanding the relation between change in SM and drought severity. The daily observed SM data are temporally averaged to match the weekly drought monitor data and subsequently the weekly, monthly, 3 monthly and 6 monthly change in SM and drought severity were estimated. The analyses suggested that the change in SM and drought severity are correlated especially over the mid-west and west coast of USA at monthly and longer time scales. The spatial pattern of the SM change maps clearly indicated the regions that are moving between different levels of drought severity. Further, the time series of effective saturation [Se =(θ-θr)/(θs-θr)] indicated the temporal dynamics of drought conditions over California which is recovering from a long-term drought. Additional analyses are being carried out to develop statistics between drought severity and soil moisture level.
Mccoll, K. A.; Entekhabi, D.
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.
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.
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.
Brown, Molly E.; Escobar, Vanessa; Moran, Susan; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni G.; Doorn, Brad; Entin, Jared K.
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.
Ueno, Kohta [Building Science Corporation, Westford, MA (United States)
Adding insulation to the interior side of walls of masonry buildings in cold (and wet) climates may cause performance and durability problems. Some concerns, such as condensation and freeze-thaw, have known solutions, but wood members embedded in the masonry structure will be colder (and potentially wetter) after an interior insulation retrofit. Moisture content & relative humidity were monitored at joist ends in historic mass brick masonry walls retrofitted with interior insulation in a cold climate (Zone 5A); data were collected from 2012-2015. Eleven joist ends were monitored in all four orientations. One limitation of these results is that the renovation is still ongoing, with limited wintertime construction heating and no permanent occupancy to date. Measurements show that many joists ends remain at high moisture contents, especially at north- and east-facing orientations, with constant 100% RH conditions at the worst cases. These high moisture levels are not conducive for wood durability, but no evidence for actual structural damage has been observed. Insulated versus non-insulated joist pockets do not show large differences. South facing joists have safe (10-15%) moisture contents. Given the uncertainty pointed out by research, definitive guidance on the vulnerability of embedded wood members is difficult to formulate. In high-risk situations, or when a very conservative approach is warranted, the embedded wood member condition can be eliminated entirely, supporting the joist ends outside of the masonry pocket.
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.
Singh, M.; Ramola, R.C.; Singh, S.; Virk, H.S.
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)
Ju Hyoung Lee
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.
Orth, Rene; Koster, Randal Dean; Seneviratne, Sonia I.
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.
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.
Choi, J.; Metzl, R.; Aggarwal, M. D.; Belisle, W.; Coleman, T.
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.
Kim, Edward; Walker, Jeff; Rudiger, Christopher; Panciera, Rocco
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
Orth, R.; Seneviratne, S. I.
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 . 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.  Orth and Seneviratne: Analysis of soil moisture memory from observations in Europe; submitted to J. Geophysical Research.
Orth, R.; Seneviratne, S. I.
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.
Park, Seonyoung; Im, Jungho; Park, Sumin; Rhee, Jinyoung
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
Martini, Edoardo; Wollschläger, Ute; Kögler, Simon; Behrens, Thorsten; Dietrich, Peter; Reinstorf, Frido; Schmidt, Karsten; Weiler, Markus; Werban, Ulrike; Zacharias, Steffen
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
Ueno, Kohta [Building Science Corporation, Westford, MA (United States)
There are many existing buildings with load-bearing mass masonry walls, whose energy performance could be improved with the retrofit of insulation. However, adding insulation to the interior side of walls of such masonry buildings in cold (and wet) climates may cause performance and durability problems. Some concerns, such as condensation and freeze-thaw have known solutions. But wood members embedded in the masonry structure will be colder (and potentially wetter) after an interior insulation retrofit. Moisture content & relative humidity were monitored at joist ends in historic mass brick masonry walls retrofitted with interior insulation in a cold climate (Zone 5A); data were collected from 2012-2015. Eleven joist ends were monitored in all four orientations. One limitation of these results is that the renovation is still ongoing, with limited wintertime construction heating and no permanent occupancy to date. Measurements show that many joists ends remain at high moisture contents, especially at north- and east-facing orientations, with constant 100% RH conditions at the worst cases. These high moisture levels are not conducive for wood durability, but no evidence for actual structural damage has been observed. Insulated vs. non-insulated joist pockets do not show large differences. South facing joists have safe (10-15%) moisture contents. Given the uncertainty pointed out by research, definitive guidance on the vulnerability of embedded wood members is difficult to formulate. In high-risk situations, or when a very conservative approach is warranted, the embedded wood member condition can be eliminated entirely, supporting the joist ends outside of the masonry pocket.
Reichle, Rolf H.; Ardizzone, Joseph V.; Kim, Gi-Kong; Lucchesi, Robert A.; Smith, Edmond B.; Weiss, Barry H.
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.
Berg, Alexis; Sheffield, Justin; Milly, Paul C.D.
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.
Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang
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.
Monitoring drought affected crop yields based on ERS-scatterometer data : exploration of possibilities to integrate ERS-scatterometer derived soil moisture into the CGMS crop model for a Russian-Ukrainian study area
Boogaard, H.L.; Diepen, van C.A.; Savin, I.
In this study the possibilities of integrating ERS scatterometer-derived soil moisture into CGMS are explored. This remote sensed soil moisture is used to calculate drought stress in grains of barley for a Russian-Ukrainian study area. The results arecompared with drought stress based on the
Chambers, J. E.; Meldrum, P.; Gunn, D.; Wilkinson, P. B.; Uhlemann, S.; Swift, R. T.; Kuras, O.; Inauen, C.; Hutchinson, D.; Butler, S.
ERT monitoring has been demonstrated in numerous studies as an effective means of imaging near surface processes for applications as diverse as permafrost studies and contaminated land assessment. A limiting factor in applying time-lapse ERT for long-term studies in remote locations has been the availability of cost-effective ERT measurement systems designed specifically for monitoring applications. Typically, monitoring is undertaken using repeated manual data collection, or by building conventional survey instruments into a monitoring setup. The latter often requires high power and is therefore difficult to operate remotely without access to mains electricity. We describe the development of a low-power resistivity imaging system designed specifically for remote monitoring, taking advantage of, e.g., solar power and data telemetry. Here, we present the results of two field deployments. The system has been installed on an active railway cutting to provide insights into the effect of vegetation on the moisture dynamics in unstable infrastructure slopes and to gather subsurface information for pro-active remediation measures. The system, comprising 255 electrodes, acquires 4596 reciprocal measurement pairs twice daily during standard operation. In case of severe weather events, the measurement schedule is reactively changed, to gather high temporal resolution data to image rainfall infiltration processes. The system has also been installed along a leaking and marginally stable canal embankment; a less favourable location for remote monitoring, with limited solar power and poor mobile reception. Nevertheless, the acquired data indicated the effectiveness of remedial actions on the canal. The ERT results showed that one leak was caused by the canal and fixed during remediation, while two other "leaks" were shown to be effects of groundwater dynamics. The availability of cost-effective, low-power ERT monitoring instrumentation, combined with an automated workflow of
Khorasani, A.; Mousavi Shalmani, M. A.; Piervali Bieranvand, N.
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.
McColl, Kaighin A.; Alemohammad, Seyed Hamed; Akbar, Ruzbeh; Konings, Alexandra G.; Yueh, Simon; Entekhabi, Dara
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.
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.
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.
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...
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...
Loaiza Usuga, Juan Carlos; Jarauta Bragulat, Eusebio; Porta Casanellas, Jaume; Poch Claret, Rosa Maria
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.
Anderson, J.E.; Ratzlaff, T.D.
Shallow land burial is a common method of disposing of industrial, municipal, and low-level radioactive waste. The exclusion of water from buried wastes is a primary objective in designing and managing waste disposal sites. If wastes are not adequately isolated, water from precipitation may move through the landfill cover and into the wastes. The presence of water in the waste zone may promote the growth of plant roots to that depth and result in the transport of toxic materials to above-ground foliage. Furthermore, percolation of water through the waste zone may transport contaminants into ground water. This report presents results from a field study designed to assess the the potential for using vegetation to deplete soil moisture and prevent water from reaching buried wastes at the Idaho National Engineering Laboratory (INEL). Our results show that this approach may provide an economical means of limiting the intrusion of water on waste sites
Chan, S.; O'Neill, P.; Njoku, E.; Jackson, T.; Bindlish, R.
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.
James Reardon; Gary Curcio; Roberta Bartlette
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...
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.
Termite, Loris Francesco; Massari, Christian; Todisco, Francesca; Brocca, Luca; Ferro, Vito; Bagarello, Vincenzo; Pampalone, Vincenzo; Wagner, Wolfgang
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
Wagner, Wolfgang; Hahn, Sebastian; Kidd, Richard [Vienna Univ. of Technology (Austria). Dept. of Geodesy and Geoinformation] [and others
Many physical, chemical and biological processes taking place at the land surface are strongly influenced by the amount of water stored within the upper soil layers. Therefore, many scientific disciplines require soil moisture observations for developing, evaluating and improving their models. One of these disciplines is meteorology where soil moisture is important due to its control on the exchange of heat and water between the soil and the lower atmosphere. Soil moisture observations may thus help to improve the forecasts of air temperature, air humidity and precipitation. However, until recently, soil moisture observations had only been available over a limited number of regional soil moisture networks. This has hampered scientific progress as regards the characterisation of land surface processes not just in meteorology but many other scientific disciplines as well. Fortunately, in recent years, satellite soil moisture data have increasingly become available. One of the freely available global soil moisture data sets is derived from the backscatter measurements acquired by the Advanced Scatterometer (ASCAT) that is a C-band active microwave remote sensing instrument flown on board of the Meteorological Operational (METOP) satellite series. ASCAT was designed to observe wind speed and direction over the oceans and was initially not foreseen for monitoring soil moisture over land. Yet, as argued in this review paper, the characteristics of the ASCAT instrument, most importantly its wavelength (5.7 cm), its high radiometric accuracy, and its multiple-viewing capabilities make it an attractive sensor for measuring soil moisture. Moreover, given the operational status of ASCAT, and its promising long-term prospects, many geoscientific applications might benefit from using ASCAT soil moisture data. Nonetheless, the ASCAT soil moisture product is relatively complex, requiring a good understanding of its properties before it can be successfully used in applications. To
Full Text Available Many physical, chemical and biological processes taking place at the land surface are strongly influenced by the amount of water stored within the upper soil layers. Therefore, many scientific disciplines require soil moisture observations for developing, evaluating and improving their models. One of these disciplines is meteorology where soil moisture is important due to its control on the exchange of heat and water between the soil and the lower atmosphere. Soil moisture observations may thus help to improve the forecasts of air temperature, air humidity and precipitation. However, until recently, soil moisture observations had only been available over a limited number of regional soil moisture networks. This has hampered scientific progress as regards the characterisation of land surface processes not just in meteorology but many other scientific disciplines as well. Fortunately, in recent years, satellite soil moisture data have increasingly become available. One of the freely available global soil moisture data sets is derived from the backscatter measurements acquired by the Advanced Scatterometer (ASCAT that is a C-band active microwave remote sensing instrument flown on board of the Meteorological Operational (METOP satellite series. ASCAT was designed to observe wind speed and direction over the oceans and was initially not foreseen for monitoring soil moisture over land. Yet, as argued in this review paper, the characteristics of the ASCAT instrument, most importantly its wavelength (5.7 cm, its high radiometric accuracy, and its multiple-viewing capabilities make it an attractive sensor for measuring soil moisture. Moreover, given the operational status of ASCAT, and its promising long-term prospects, many geoscientific applications might benefit from using ASCAT soil moisture data. Nonetheless, the ASCAT soil moisture product is relatively complex, requiring a good understanding of its properties before it can be successfully used in
Dumedah, Gift; Walker, Jeffrey P.; Chik, Li
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.
Lakshmipathy, A.V.; Gangadharan, P.
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)
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.
Full Text Available Recently, we presented a steady-state analytical hillslope stability model to study rain-induced shallow landslides. This model is based on kinematic wave dynamics of saturated subsurface storage and the infinite slope stability assumption. Here we apply the model to investigate the effect of neglecting the unsaturated storage on the assessment of slope stability in the steady-state hydrology. For that purpose we extend the hydrological model to compute the soil pore pressure distribution over the entire flow domain. We also apply this model for hillslopes with non-constant soil depth to compare the stability of different hillslopes and to find the critical slip surface in hillslopes with different geometric characteristics. In order to do this, we incorporate more complex approaches to compute slope stability (Janbu's non-circular method and Bishop's simplified method in the steady-state analytical hillslope stability model. We compare the safety factor (FS derived from the infinite slope stability method and the more complex approach for two cases: with and without the soil moisture profile in the unsaturated zone. We apply this extended hillslope stability model to nine characteristic hillslope types with three different profile curvatures (concave, straight, convex and three different plan shapes (convergent, parallel, divergent. Overall, we find that unsaturated zone storage does not play a critical role in determining the factor of safety for shallow and deep landslides. As a result, the effect of the unsaturated zone storage on slope stability can be neglected in the steady-state hydrology and one can assume the same bulk specific weight below and above the water table. We find that steep slopes with concave profile and convergent plan shape have the least stability. We also demonstrate that in hillslopes with non-constant soil depth (possible deep landslides, the ones with convex profiles and convergent plan shapes have
Yuan, Q.; Xu, H.; Li, T.; Shen, H.; Zhang, L.
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
The Soil Moisture Active-Passive (SMAP) Mission is one of the first Earth observation satellites being formulated by NASA in response to the 2007 National Research Council s Decadal Survey. SMAP will make global measurements of soil moisture at the Earth's land surface and its freeze-thaw state. These measurements will allow significantly improved estimates of water, energy and carbon transfers between the land and atmosphere. Soil moisture measurements are also of great importance in assessing flooding and monitoring drought. Knowledge gained from SMAP observations can help mitigate these natural hazards, resulting in potentially great economic and social benefits. SMAP observations of soil moisture and freeze/thaw timing over the boreal latitudes will also reduce a major uncertainty in quantifying the global carbon balance and help to resolve an apparent missing carbon sink over land. The SMAP mission concept will utilize an L-band radar and radiometer sharing a rotating 6-meter mesh reflector antenna flying in a 680 km polar orbit with an 8-day exact ground track repeat aboard a 3-axis stabilized spacecraft to provide high-resolution and high-accuracy global maps of soil moisture and freeze/thaw state every two to three days. In addition, the SMAP project will use these surface observations with advanced modeling and data assimilation to provide estimates of deeper root-zone soil moisture and net ecosystem exchange of carbon. SMAP recently completed its Phase A Mission Concept Study Phase for NASA and transitioned into Phase B (Formulation and Detailed Design). A number of significant accomplishments occurred during this initial phase of mission development. The SMAP project held several open meetings to solicit community feedback on possible science algorithms, prepared preliminary draft Algorithm Theoretical Basis Documents (ATBDs) for each mission science product, and established a prototype algorithm testbed to enable testing and evaluation of the
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 ...
Crow, W. T.; Chen, F.; Reichle, R. H.; Xia, Y.; Liu, Q.
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.
Gruber, A.; Crow, W. T.; Dorigo, W. A.
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.
Abbaszadeh, Peyman; Yan, Hongxiang; Moradkhani, Hamid
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.
Stocker, Benjamin D; Zscheischler, Jakob; Keenan, Trevor F; Prentice, I Colin; Peñuelas, Josep; Seneviratne, Sonia I
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.
Irving Goldberg; Norman A. MacGillivray; Robert R. Ziemer
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.
Zhan, X.; Yin, J.; Liu, J.; Fang, L.; Hain, C.; Ferraro, R. R.; Weng, F.
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.
Jones, L. A.; Madani, N.; Kimball, J. S.; Reichle, R. H.; Colliander, A.
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
Salve, R.; Torn, M.S.
The primary objective of this study was to assess the impact of two grassland soils and precipitation regimes on soil-moisture dynamics. We set up an experiment in a greenhouse, and monitored soil moisture dynamics in mesocosms planted with Avena barbata, an annual species found in California grasslands. By repeating the precipitation input at regular intervals, we were able to observe plant manipulation of soil moisture during well-defined periods during the growing season. We found that the amount of water partitioned to evapotranspiration, seepage, and soil storage varied among different growth stages. Further, both soil type and precipitation regimes had a significant impact on redistributing soil moisture. Whereas in the low-precipitation treatments most water was released to the atmosphere as evapotranspiration, major losses from the high-precipitation treatment occurred as gravity drainage. Observations from this study emphasize the importance of understanding intra-seasonal relationships between vegetation, soil, and water.
Ek, M. B.; Xia, Y.; Ford, T.; Wu, Y.; Quiring, S. M.
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.
National Oceanic and Atmospheric Administration, Department of Commerce — This dataset, DSI-6411 is comprised of soil moisture data and the accompanying information for the agricultural regions of Western Russia (west of ~ 60E) and The...
Gaikwad, Pramod; Devendrachari, Mruthyunjayachari Chattanahalli; Thimmappa, Ravikumar; Paswan, Bhuneshwar; Raja Kottaichamy, Alagar; Makri Nimbegondi Kotresh, Harish; Thotiyl, Musthafa Ottakam
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.
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.
Stacke, Tobias; Hagemann, Stefan; Loew, Alexander
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
Bogena, Heye R.; Huisman, Johan A.; Rosenbaum, Ulrike; Weuthen, Ansgar; Vereecken, Harry
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 , . 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 . 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
Paloscia, S.; Pampaloni, P.; Chiarantini, L.; Coppo, P.; Gagliani, S.; Luzi, G.
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
Guimont, Sophie; Perrin-Ganier, Corinne; Real, Benoit; Schiavon, Michel
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...
Amazirh, Abdelhakim; Merlin, Olivier; Er-Raki, Salah; Gao, Qi; Rivalland, Vincent; Malbeteau, Yoann; Khabba, Said; Escorihuela, Maria José
Radar data have been used to retrieve and monitor the surface soil moisture (SM) changes in various conditions. However, the calibration of radar models whether empirically or physically-based, is still subject to large uncertainties especially
Hnatushenko, Volodymyr; Garkusha, Igor; Vasyliev, Volodymyr
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.
Koster, Randal D.; Brocca, Luca; Crow, Wade T.; Burgin, Mariko S.; De Lannoy, Gabrielle J. M.
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.
Xu-Li Tang; Guo-Yi Zhou; Shu-Guang Liu; De-Qiang Zhang; Shi-Zhong Liu; Jiong Li; Cun-Yu Zhou
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.
Tang, X.-L.; Zhou, G.-Y.; Liu, S.-G.; Zhang, D.-Q.; Liu, S.-Z.; Li, Ji; Zhou, C.-Y.
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.
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.
Time (s). A. Amplitude of the soil thermal wave at any depth (. ◦. C). A0. Amplitude of thermal ... system, soil moisture has a long memory (Pielke et al 1999; Wu et al .... measurements of the short wave radiation compo- nents as follows: α = Su.
Moyano, F E; Vasilyeva, N; Bouckaert, L
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...
Srivastava, Prashant K.; Han, Dawei; Rico-Ramirez, Miguel A.; O'Neill, Peggy; Islam, Tanvir; Gupta, Manika
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.
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
Bircher, Simone; Skou, N.; Jensen, Karsten Høgh
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...
C.R. Boardman; Samuel V. Glass
This case study presents measurements of radon and moisture infiltration from soil gases into the basement of an unoccupied research house in Madison, Wisconsin, over two full years. The basement floor and exterior walls were constructed with preservative-treated lumber and plywood. In addition to continuous radon monitoring, measurements included building air...
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
Caylor, K.; D'Odorico, P.; Rodriguez-Iturbe, I.
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
Robock, Alan; Vinnikov, Konstantin YA.; Schlosser, C. Adam; Speranskaya, Nina A.; Xue, Yongkang
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
Hauser, Mathias; Orth, René; Thiery, Wim; Seneviratne, Sonia
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
Akbar, Ruzbeh; Cosh, Michael H.; O'Neill, Peggy E.; Entekhabi, Dara; Moghaddam, Mahta
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.
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.
Koster, Randal D.; Suarez, Max J.; Houser, Paul (Technical Monitor)
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.
Coopersmith, E J; Bell, J E; Benedict, K; Shriber, J; McCotter, O; Cosh, M H
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.
The Los Alamos Scientific Laboratory (LASL) has an extensive program for the development of nondestructive assay instrumentation for the quantitative analysis of transuranic (TRU) materials found in bulk solid wastes generated by Department of Energy facilities and by the commercial nuclear power industry. Included are wastes generated in decontamination and decommissioning of outdated nuclear facilities as well as wastes from old waste burial ground exhumation programs. The assay instrumentation is designed to have detection limits below 10 nCi/g wherever practicable. Because of the topic of this workshop, only the assay instrumentation applied specifically to soil monitoring will be discussed here. Four types of soil monitors are described
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.
Lellei-Kovács, Eszter; Kovács-Láng, Edit; Botta-Dukát, Zoltán
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...
This report provides the basis for the US Department of Energy's (DOE) request to discontinue neutron moisture monitoring (NMM) at the Green River, Utah, Uranium Mill Tailings Remedial Action (UMTRA) disposal cell and decommission the neutron access holes. After 3 years of monitoring the disposal cell, the DOE has determined that the NMM method is not suitable for determining changes in moisture content in the disposal cell. Existing tailings moisture contents in the disposal cell result in a low seepage flux. The combination of a low seepage flux and geochemical retardation by foundation materials underneath the disposal cell ensures that the proposed US Environmental Protection Agency (EPA) groundwater protection standards will not be exceeded within the design life of the disposal cell. To assess the effectiveness of the NMM method for monitoring moisture contents In the disposal cell at Green River, the DOE subsequently conducted a field study and a review of historical and new literature. The literature review allowed the DOE to identify performance criteria for the NMM method. Findings of these studies suggest that: The NMM method is not sensitive to the low moisture contents found in the disposal cell.; there is an insufficient range of moisture contents in the disposal cell to develop a field calibration curve relating moisture content to neutron counts; it is not possible to collect NMM data from the disposal cell that meet data quality objectives for precision and accuracy developed from performance criteria described in the literature
Full Text Available Plant temperature is an indicator of stomatal conductance, which reflects soil moisture stresses. We explored the relationship between plant temperature and soil moisture to optimize irrigation schedules in a water-stress experiment using Firmiana platanifolia (L. f. Marsili in an incubator. Canopy temperature, leaf temperature, and stomatal conductance were measured using thermal imaging and a porometer. The results indicated that (1 stomatal conductance decreased with declines in soil moisture, and reflected average canopy temperature; (2 the variation of the leaf temperature distribution was a reliable indicator of soil moisture stress, and the temperature distribution in severely water-stressed leaves exhibited greater spatial variation than that in the presence of sufficient irrigation; (3 thermal indices (Ig and crop water stress index (CWSI were theoretically proportional to stomatal conductance (gs, Ig was certified to have linearity relationship with gs and CWSI have a logarithmic relationship with gs, and both of the two indices can be used to estimate soil moisture; and (4 thermal imaging data can reflect water status irrespective of long-term water scarcity or lack of sudden rainfall. This study applied thermal imaging methods to monitor plants and develop adaptable irrigation scheduling, which are important for the formulation of effective and economical agriculture and forestry policy.
Luft, G.; Morgenschweis, G.
The authors present a brief outline of the direct and indirect field methods used at present in soil moisture measurement; particularly the advantages and disadvantages of neutron diffusion measurement are illustrated by means of various types of instruments available. The recently developed Wellingford Neutron Moisture Probe IH II, used for hydrological and pedohydrological fieldwork respectively, is presented and the first test results concerning the handling, measuring time, measured volume and layer thickness are discussed. (orig.) [de
El Gendy, R.W.
The unsaturated hydraulic conductivity for soil can be estimated from o(t) function, and the dimensionless soil water content parameter (Se)Se (β - βr)/ (φ - θ)), where θ, is the soil water content at any time (from soil moisture depletion curve l; θ is the residual water content and θ, is the total soil porosity (equals saturation point). Se can be represented as a time function (Se = a t b ), where t, is the measurement time and (a and b) are the regression constants. The recommended equation in this method is given by
Mattikalli, N.M.; Engman, E.T.; Ahuja, L.R.; Jackson, T.J.
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)
He, Q.; Mccoll, K. A.; Li, C.; Lu, H.; Akbar, R.; Pan, M.; Entekhabi, D.
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
Tana Wood; M. Detto; W.L. Silver
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...
Hawdon, A. A.; McJannet, D. L.; Renzullo, L. J.; Baker, B.; Searle, R.
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.
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.
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.
Case, Jonathan L.; Zavodsky, Bradley T.; White, Kristopher D.; Bell, Jesse E.
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
Khakural, B.R.; Robert, P.C.; Hugins, D.R.
There is a growing interest in real-time estimation of soil moisture for site-specific crop management. Non-contacting electromagnetic inductive (EMI) methods have potentials to provide real-time estimate of soil profile water contents. Soil profile water contents were monitored with a neutron probe at selected sites. A Geonics LTD EM-38 terrain meter was used to record bulk soil electrical conductivity (EC(A)) readings across a soil-landscape in West central Minnesota with variable moisture regimes. The relationships among EC(A), selected soil and landscape properties were examined. Bulk soil electrical conductivity (0-1.0 and 0-0.5 m) was negatively correlated with relative elevation. It was positively correlated with soil profile (1.0 m) clay content and negatively correlated with soil profile coarse fragments (2 mm) and sand content. There was significant linear relationship between ECA (0-1.0 and 0-0.5) and soil profile water storage. Soil water storage estimated from ECA reflected changes in landscape and soil characteristics
Tromp-van Meerveld, I.; McDonnell, J.
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
Cook, David R. [Argonne National Lab. (ANL), Argonne, IL (United States)
The soil temperature and moisture profile system (STAMP) provides vertical profiles of soil temperature, soil water content (soil-type specific and loam type), plant water availability, soil conductivity, and real dielectric permittivity as a function of depth below the ground surface at half-hourly intervals, and precipitation at one-minute intervals. The profiles are measured directly by in situ probes at all extended facilities of the SGP climate research site. The profiles are derived from measurements of soil energy conductivity. Atmospheric scientists use the data in climate models to determine boundary conditions and to estimate the surface energy flux. The data are also useful to hydrologists, soil scientists, and agricultural scientists for determining the state of the soil. The STAMP system replaced the SWATS system in early 2016.
Niroula, Sundar; Halder, Subhadeep; Ghosh, Subimal
Real time hydrologic forecasting requires near accurate initial condition of soil moisture; however, continuous monitoring of soil moisture is not operational in many regions, such as, in Ganga basin, extended in Nepal, India and Bangladesh. Here, we examine the impacts of perturbation/error in the initial soil moisture conditions on simulated soil moisture and streamflow in Ganga basin and its propagation, during the summer monsoon season (June to September). This provides information regarding the required minimum duration of model simulation for attaining the model stability. We use the Variable Infiltration Capacity model for hydrological simulations after validation. Multiple hydrologic simulations are performed, each of 21 days, initialized on every 5th day of the monsoon season for deficit, surplus and normal monsoon years. Each of these simulations is performed with the initial soil moisture condition obtained from long term runs along with positive and negative perturbations. The time required for the convergence of initial errors is obtained for all the cases. We find a quick convergence for the year with high rainfall as well as for the wet spells within a season. We further find high spatial variations in the time required for convergence; the region with high precipitation such as Lower Ganga basin attains convergence at a faster rate. Furthermore, deeper soil layers need more time for convergence. Our analysis is the first attempt on understanding the sensitivity of hydrological simulations of Ganga basin on initial soil moisture conditions. The results obtained here may be useful in understanding the spin-up requirements for operational hydrologic forecasts.
Kim, S.; Kim, H.; Choi, M.; Kim, K.
Estimating spatiotemporal variation of soil moisture is crucial to hydrological applications such as flood, drought, and near real-time climate forecasting. Recent advances in space-based passive microwave measurements allow the frequent monitoring of the surface soil moisture at a global scale and downscaling approaches have been applied to improve the spatial resolution of passive microwave products available at local scale applications. However, most downscaling methods using optical and thermal dataset, are valid only in cloud-free conditions; thus renewed downscaling method under all sky condition is necessary for the establishment of spatiotemporal continuity of datasets at fine resolution. In present study Support Vector Machine (SVM) technique was utilized to downscale a satellite-based soil moisture retrievals. The 0.1 and 0.25-degree resolution of daily Land Parameter Retrieval Model (LPRM) L3 soil moisture datasets from Advanced Microwave Scanning Radiometer 2 (AMSR2) were disaggregated over Northeast Asia in 2015. Optically derived estimates of surface temperature (LST), normalized difference vegetation index (NDVI), and its cloud products were obtained from MODerate Resolution Imaging Spectroradiometer (MODIS) for the purpose of downscaling soil moisture in finer resolution under all sky condition. Furthermore, a comparison analysis between in situ and downscaled soil moisture products was also conducted for quantitatively assessing its accuracy. Results showed that downscaled soil moisture under all sky condition not only preserves the quality of AMSR2 LPRM soil moisture at 1km resolution, but also attains higher spatial data coverage. From this research we expect that time continuous monitoring of soil moisture at fine scale regardless of weather conditions would be available.
Charles A. Troendle
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.
Chaleeraktrakoon, Chavalit; Somsakun, Somrit
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.
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...
The U.S. Drought Monitor (USDM) classifies drought into five discrete dryness/drought categories based on expert synthesis of numerous data sources. In this study, an empirical methodology is presented for creating a non-discrete U.S. Drought Monitor (USDM) index that simultaneously 1) represents th...
Soil moisture was measured using the NZK 203 neutron probe manufactured by Tesla Premysleni. The individual measuring sites were spaced at a distance of 100 m. The NZK 203 set consists of a NPK 202 moisture gage and a NSK 301 scintillation detector and features the following specifications: moisture density measuring range 20 to 500 kg/m 3 , 241 Am-Be fast neutron source having a neutron flux of 7.5x10 4 n.sec -1 +-10%, operating temperature -10 to +45 degC. The measured counting rate was primarily affected by the statistical fluctuation of ionizing radiation and by instrument instability. In order that these effects should be limited each measurement was repeated 10 times with the optimum measurement time at an interval of 20 to 100 sec. The NZK 203 Tesla set was proven to be suitable for rapid and reproducible determination of moisture profiles. (J.P.)
Jadghuber, Thomas; Hajnsek, Irena; Weiß, Thomas; Papathanassiou, Konstantinos P.
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).
Pereira,Roseana Florentino da Costa; Oliveira,Edkarlla Sousa Dantas de; Lima,Maria Alice Gomes de Andrade; Brasil,Simone Louise Delarue Cezar
Galvanized steel has been widely applied in different applications and the industry significantly increased its production in recent years. Some galvanized structures can be completely or partially buried, such as transmission tower footings. The corrosion of these metallic structures is related to the soil chemical and physicochemical properties, which define the aggressiveness of the environment. To assess the effect of the soil moisture on galvanized steel corrosion, a comparative study wa...
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.
Yu. A. Savel'ev
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.
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.
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.
Quets, Jan; De Lannoy, Gabrielle; Reichle, Rolf; Cosh, Michael; van der Schalie, Robin; Wigneron, Jean-Pierre
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.
Kolassa, J.; Reichle, R. H.; Liu, Q.; Alemohammad, S. H.; Gentine, P.
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.
Yueh, Simon H.; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni; Entin, Jared K.
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.
Parinussa, R.M.; Holmes, T.R.H.; Wanders, N.; Dorigo, W.A.; de Jeu, R.A.M.
A preliminary study toward consistent soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2) is presented. Its predecessor, the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), has providedEarth scientists with a consistent and continuous global
Wilheit, T. T.
An electrically scanned pushbroom phased antenna array is described for a microwave radiometer which can provide agriculturally meaningful measurements of soil moisture. The antenna size of 100 meters at 1400 MHz or 230 meters at 611 MHz requires several shuttle launches and orbital assembly. Problems inherent to the size of the structure and specific instrument problems are discussed as well as the preliminary design.
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
Replicate field plots were used in experiments aimed at evaluating the yield potentials of maize and cucumber intercrop resulting from the control of soil moisture through irrigation and mulching, for a period of eleven weeks. Three irrigation depths, 2.5, 3.5 and 4.5 mm; and two mulch levels, zero mulch and 10 ton/ha of oil ...
Jiankang, Ji; Thomsen, A.; Skriver, Henning
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...
Passive microwave remote sensing of soil moisture has matured over the past decade as a result of the Advanced Microwave Scanning Radiometer (AMSR) program of JAXA. This program has resulted in improved algorithms that have been supported by rigorous validation. Access to the products and the valida...
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
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.
Ueno, K. [Building Science Corporation, Westford, MA (United States)
Double-stud walls insulated with cellulose or low-density spray foam can have R-values of 40 or higher. However, double stud walls have a higher risk of interior-sourced condensation moisture damage, when compared with high-R approaches using exterior insulating sheathing.; Moisture conditions in double stud walls were monitored in Zone 5A (Massachusetts); three double stud assemblies were compared.
A. R. Adesiji
Full Text Available The estimation of runoff and soil moisture deficit in Guinea Savannah region using semi arid model based on soil water balance technique (SAMBA was carried out. The input to the SAMBA model are daily rainfall, daily evapotranspiration, type and date of planting of crop, and soil parameters. The estimated runoff was validated with field measurement taken in a 67.23 ha catchment in the study area. The annual rainfall for the year under study (2009 is 1356.2 mm, the estimated annual evapotranspiration. runoff and recharge are 638mm, 132.93mm, and 447.8mm respectively. Recharge was experienced 23 days after a significant depth of rainfall was recorded. For the crop growth in the catchment, the soil was cropped with a pepper and the growth monitored from the planting to the harvesting. The crop enjoyed so much moisture throughout the growing period as Total Available Water in the soil is greater than Soil Moisture Deficit (TAW>SMD. The model results show that the larger percentage of the total annual rainfall was lost to evaporation and recharge during the growing season. The low runoff and high recharge are attributed to soil characteristics of the area and moderate terrain of the study area.
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...
Altaf, M. U.; Jana, Raghavendra Belur; Hoteit, Ibrahim; McCabe, Matthew
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
Full Text Available Glass fiber reinforced polymer (GFRP composites are widely used in infrastructure applications including water structures due to their relatively high durability, high strength to weight ratio, and non-corrosiveness. Here we demonstrate the potential use of carbon nanoparticles dispersed during GFRP composite fabrication to reduce water absorption of GFRP and to enable monitoring of moisture damage propagation in GFRP composites. GFRP coupons incorporating 2.0 wt % carbon nanofibers (CNFs and 2.0 wt % multi-wall carbon nanotubes (MWCNTs were fabricated in order to study the effect of moisture damage on mechanical properties of GFRP. Water absorption tests were carried out by immersing the GFRP coupons in a seawater bath at two temperatures for a time period of three months. Effects of water immersion on the mechanical properties and glass transition temperature of GFRP were investigated. Furthermore, moisture damage in GFRP was monitored by measuring the electrical conductivity of the GFRP coupons. It was shown that carbon nanoparticles can provide a means of self-sensing that enables the monitoring of moisture damage in GFRP. Despite the success of the proposed technique, it might not be able to efficiently describe moisture damage propagation in GFRP beyond a specific threshold because of the relatively high electrical conductivity of seawater. Microstructural investigations using Fourier Transform Infrared (FTIR explained the significance of seawater immersion time and temperature on the different levels of moisture damage in GFRP.
Dalla Valle, Nicolas; Wutzler, Thomas; Meyer, Stefanie; Potthast, Karin; Michalzik, Beate
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
Lyu, Jin Lin; He, Qiu Yue; Yan, Mei Jie; Li, Guo Qing; Du, Sheng
To examine the characteristics of sap flow in Quercus liaotungensis and their response to environmental factors under different soil moisture conditions, Granier-type thermal dissipation probes were used to measure xylem sap flow of trees with different sapwood area in a natural Q. liaotungensis forest in the loess hilly region. Solar radiation, air temperature, relative air humidity, precipitation, and soil moisture were monitored during the study period. The results showed that sap flux of Q. liaotungensis reached daily peaks earlier than solar radiation and vapor pressure deficit. The diurnal dynamics of sap flux showed a similar pattern to those of the environmental factors. Trees had larger sap flux during the period with higher soil moisture. Under the same soil moisture conditions, trees with larger diameter and sapwood areas had significantly higher sap flux than those with smaller diameter and sapwood areas. Sap flux could be fitted with vapor pressure deficit, solar radiation, and the integrated index of the two factors using exponential saturation function. Differences in the fitted curves and parameters suggested that sap flux tended to reach saturation faster under higher soil moisture. Furthermore, trees in the smaller diameter class were more sensitive to the changes of soil moisture. The ratio of daily sap flux per unit vapor pressure deficit under lower soil moisture condition to that under higher soil moisture condition was linearly correlated to sapwood area. The regressive slope in smaller diameter class was larger than that in bigger diameter class, which further indicated the higher sensitivity of trees with smaller diameter class to soil moisture. These results indicated that wider sapwood of larger diameter class provided a buffer against drought stress.
Christiansen, Jesper; Levy-Booth, David; Barker, Jason; Prescott, Cindy; Grayston, Sue
Soil moisture is a key driver of methane (CH4) fluxes in forest soils, both of the net uptake of atmospheric CH4 and emission from the soil. Climate and land use change will alter spatial patterns of soil moisture as well as temporal variability impacting the net CH4 exchange. The impact on the resultant net CH4 exchange however is linked to the underlying spatial and temporal distribution of the soil microbial communities involved in CH4 cycling as well as the response of the soil microbial community to environmental changes. Significant progress has been made to target specific CH4 consuming and producing soil organisms, which is invaluable in order to understand the microbial regulation of the CH4 cycle in forest soils. However, it is not clear as to which extent soil moisture shapes the structure, function and abundance of CH4 specific microorganisms and how this is linked to observed net CH4 exchange under contrasting soil moisture regimes. Here we report on the results from a research project aiming to understand how the CH4 net exchange is shaped by the interactive effects soil moisture and the spatial distribution CH4 consuming (methanotrophs) and producing (methanogens). We studied the growing season variations of in situ CH4 fluxes, microbial gene abundances of methanotrophs and methanogens, soil hydrology, and nutrient availability in three typical forest types across a soil moisture gradient in a temperate rainforest on the Canadian Pacific coast. Furthermore, we conducted laboratory experiments to determine whether the net CH4 exchange from hydrologically contrasting forest soils responded differently to changes in soil moisture. Lastly, we modelled the microbial mediation of net CH4 exchange along the soil moisture gradient using structural equation modeling. Our study shows that it is possible to link spatial patterns of in situ net exchange of CH4 to microbial abundance of CH4 consuming and producing organisms. We also show that the microbial
Zhou, Weiping; Hui, Dafeng; Shen, Weijun
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
Pannu, Ravinder; Siciliano, Steven D; O'Driscoll, Nelson J
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.
Hauser, Mathias; Orth, René; Seneviratne, Sonia I.
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).
Cassiani, Giorgio; Ursino, Nadia; Deiana, Rita
of possible climatic changes. We used long-term electromagnetic induction (EMI) time lapse monitoring and short-term irrigation experiments monitored using electrical resistivity tomography (ERT) and EMI, supported by time domain reflectometry (TDR) soil moisture measurements. Mapping of natural ?-ray...... emission, texture analysis, and laboratory calibration of an electrical constitutive relationship on soil samples complete the dataset. We observe that the growth of vegetation, with the associated below-ground allocation of biomass, has a significant impact on the soil moisture dynamics. It is well known...
Hursh, Andrew; Ballantyne, Ashley; Cooper, Leila; Maneta, Marco; Kimball, John; Watts, Jennifer
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
In arid lands, a major contribution to water loss is by soil water evaporation. Desert sand dunes in arid regions are devoid of runoff and have high rates of infiltration. Rainwater is commonly stored within them because of the low permeability soils in the underlying desert pavement. In such cases, moisture is confined in the sand dune below a depth, termed as the “extinction depth”, where it is protected from evaporation during long dry periods. Moreover, desert sand dunes have sparse vegetation, which results in low transpiration losses from the stored water. The water accumulated below the extinction depth of the sand dunes can be utilized for various purposes such as in irrigation to support desert agriculture. In this study, field experiments were conducted in Western Saudi Arabia to monitor the soil moisture gradients and determine the diffusive extinction depth of dune sand. The dune sand was saturated with water and was exposed to natural conditions (evaporation and precipitation). The decline of the water level in the sand column was continuously recorded using transducers and sensors installed at different depths monitored the temporal variation of temperature and moisture content within the sand. The hydrological simulator HYDRUS-1D was used to construct the vertical profiles of soil water content and temperature and the results obtained from HYDRUS-1D were compared to the gradients monitored by the sensors.
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...
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...
Draper, C.S.; Walker, J.P.; Steinle, P.J.; De Jeu, R.A.M.; Holmes, T.R.H.
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
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...
Schrön, M.; Fersch, B.; Jagdhuber, T.
The representative determination of soil moisture across different spatial ranges and scales is still an important challenge in hydrology. While in situ measurements are trusted methods at the profile- or point-scale, cosmic-ray neutron sensors (CRNS) are renowned for providing volume averages for several hectares and tens of decimeters depth. On the other hand, airborne remote-sensing enables the coverage of regional scales, however limited to the top few centimeters of the soil.Common to all of these methods is a challenging data processing part, often requiring calibration with independent data. We investigated the performance and potential of three complementary observational methods for the determination of soil moisture below grassland in an alpine front-range river catchment (Rott, 55 km2) of southern Germany.We employ the TERENO preAlpine soil moisture monitoring network, along with additional soil samples taken throughout the catchment. Spatial soil moisture products have been generated using surveys of a car-mounted mobile CRNS (rover), and an aerial acquisition of the polarimetric synthetic aperture radar (F-SAR) of DLR.The study assesses (1) the viability of the different methods to estimate soil moisture for their respective scales and extents, and (2) how either method could support an improvement of the others. We found that in situ data can provide valuable information to calibrate the CRNS rover and to train the vegetation removal part of the polarimetric SAR (PolSAR) retrieval algorithm. Vegetation correction is mandatory to obtain the sub-canopy soil moisture patterns. While CRNS rover surveys can be used to evaluate the F-SAR product across scales, vegetation-related PolSAR products in turn can support the spatial correction of CRNS products for biomass water. Despite the different physical principles, the synthesis of the methods can provide reasonable soil moisture information by integrating from the plot to the landscape scale. The
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.
Anderson, J.E.; Ratzlaff, T.D.; Nowak, R.S.; Markham, O.D.
In semiarid regions, where potential evapotranspiration greatly exceeds precipitation, it is theoretically possible to preclude water form reaching interred wastes by (i) providing a sufficient cap of soil to store precipitation that falls while plants are dormant and (ii) establishing sufficient plant cover to deplete soil moisture during the growing season, thereby emptying the water storage reservoir of the soil. Here the authors discuss the theory and rationale for such an approach and then present the results of a field study to test its efficacy at the Idaho National Engineering Laboratory (INEL). They examined the capacity of four species of perennial plants to deplete soil moisture on simulated waste trenches and determined the effective water storage capacity of the soil. Those data enabled them to estimate the minimum depth of fill soil required to prevent deep drainage. Any of the species studied can use all of the plant-available soil water, even during a very wet growing season. The water storage capacity of the soil studied is 17% by volume, so a trench cap of 1.6 m of soil should be adequate to store precipitation received at the INEL while plants are dormant. They recommend a fill soil depth of 2 m to provide a margin of safety in case water accumulates in local areas as a result of heavy snow accumulation, subsidence, or runoff. Fill soil requirements and choice of plant species will vary, but the concepts and general approach are applicable to other shallow land burial sites in arid or semiarid regions. 23 refs., 5 figs
TAUPE as a moisture sensor has been developed in cooperation with Technology Transfer Division in Forschungszentrum Karlsruhe since 1996. These sensors can be used to monitor moisture in a variety of materials, using time domain or frequency domain techniques. Major applications are large area supervision of landfill sealings, determination of the snow water equivalent, e.g. in the project SNOWPOWER for the forecasting of the amount of water for energy production in storage lakes and, as a new project, continuous monitoring of groundwater level in the flood plane of river Rhine. (orig.)
A.K.M. Azad Hossain
Full Text Available Soil moisture monitoring and characterization of the spatial and temporal variability of this hydrologic parameter at scales from small catchments to large river basins continues to receive much attention, reflecting its critical role in subsurface-land surface-atmospheric interactions and its importance to drought analysis, irrigation planning, crop yield forecasting, flood protection, and forest fire prevention. Synthetic Aperture Radar (SAR data acquired at different spatial resolutions have been successfully used to estimate soil moisture in different semi-arid areas of the world for many years. This research investigated the potential of linear multiple regressions and Artificial Neural Networks (ANN based models that incorporate different geophysical variables with Radarsat 1 SAR fine imagery and concurrently measured soil moisture measurements to estimate surface soil moisture in Nash Draw, NM. An artificial neural network based model with vegetation density, soil type, and elevation data as input in addition to radar backscatter values was found suitable to estimate surface soil moisture in this area with reasonable accuracy. This model was applied to a time series of SAR data acquired in 2006 to produce soil moisture data covering a normal wet season in the study site.
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
Tootle, G.; Anderson, S.; Grissino-Mayer, H.
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.
Gomez-Sanz, V.; Garcia-Vinas, J. I.
Pinus pinaster stands in the center of the Iberian Peninsula frequently grow in a unique hydrological system characterized by a variable groundwater table near the soil surface and highly permeable soils (arenosols). Over the last few decades, this superficial aquifer has been overused as a water resource, especially for irrigated crops. Overuse has reached a critical level and has caused various environmental impacts and a water sustainability crisis wherein rainfall variability does not allow for a sufficient level of aquifer recharge by natural means. Within this changing scenario, soil water significantly affects the spatio-temporal ecological response, necessitating more extensive characterization of the complex soil-tree water relationship. The primary goal of the present work was to evaluate the influence of root zone soil moisture on the observed spatial response of Pinus pinaster stands. Volumetric soil moisture content was measured at eleven forest sites, using time-domain reflectometry (TDR), over a two-year observation period. The results demonstrate that the combined effect of groundwater table proximity and dune morphology associated with this area are the main factors driving very different water availability conditions among the monitored hydrological response units, which modulate maritime pine installation and development. Topographically lower areas are more heterogeneous in terms of soil moisture behavior. In these areas, the conifer forests that are connected to the water table may be the most sensitive to land use changes within current environmental change scenarios. Consequently, in these pine ecosystems, the combined influences of geomorphology and water table proximity on variations in root zone soil moisture are essential and must be considered to develop adequate adaptive management models. (Author) 25 refs.
Marschmann, G.; Pagel, H.; Uksa, M.; Streck, T.; Milojevic, T.; Rezanezhad, F.; Van Cappellen, P.
The key processes of herbicide fate in agricultural soils are well-characterized. However, most of these studies are from batch experiments that were conducted under optimal aerobic conditions. In order to delineate the processes controlling herbicide (i.e., phenoxy herbicide 2-methyl-4-chlorophenoxyacetic acid, MCPA) turnover in soil under variable moisture conditions, we conducted a state-of-the-art soil column experiment, with a highly instrumented automated soil column system, under constant and oscillating water table regimes. In this system, the position of the water table was imposed using a computer-controlled, multi-channel pump connected to a hydrostatic equilibrium reservoir and a water storage reservoir. The soil samples were collected from a fertilized, arable and carbon-limited agricultural field site in Germany. The efflux of CO2 was determined from headspace gas measurements as an integrated signal of microbial respiration activity. Moisture and oxygen profiles along the soil column were monitored continuously using high-resolution moisture content probes and luminescence-based Multi Fiber Optode (MuFO) microsensors, respectively. Pore water and solid-phase samples were collected periodically at 8 depths and analyzed for MCPA, dissolved inorganic and organic carbon concentrations as well as the abundance of specific MCPA-degrading bacteria. The results indicated a clear effect of the water table fluctuations on CO2 fluxes, with lower fluxes during imbibition periods and enhanced CO2 fluxes after drainage. In this presentation, we focus on the results of temporal changes in the vertical distribution of herbicide, specific herbicide degraders, organic carbon concentration, moisture content and oxygen. We expect that the high spatial and temporal resolution of measurements from this experiment will allow robust calibration of a reactive transport model for the soil columns, with subsequent identification and quantification of rate limiting processes of
Reppucci, Antonio; Moreno, Laura
Information on Soil moisture spatial and temporal evolution is of great importance for managing the utilization of soils and vegetation, in particular in environments where the water resources are scarce. In-situ measurement of soil moisture are costly and not able to sample the spatial behaviour of a whole region. Thanks to their all weather capability and wide coverage, Synthetic Aperture Radar (SAR) images offer the opportunity to monitor large area with high resolution. This study presents the results of a project, partially founded by the Catalan government, to improve the monitoring of soil moisture using Earth Observation data. In particular the project is focused on the calibration of existing semi-empirical algorithm in the area of study. This will be done using co-located SAR and in-situ measurements acquired during several field campaigns. Observed deviations between SAR measurements and in-situ measurement are discussed.
The Los Alamos Scientific Laboratory (LASL) has an extensive program for the development of nondestructive assay instrumentation for the quantitative analysis of transuranic (TRU) materials found in bulk solid wastes generated by Department of Energy facilities and by the commercial nuclear power industry. Included are wastes generated in decontamination and decommissioning of outdated nuclear facilities, as well as from old waste-burial-ground exhumation programs. The assay instrumentation is designed to have detection limits below 10 nCi/g wherever practicable. The assay instrumentation that is applied specifically to soil monitoring is discussed
Cammalleri, Carmelo; Vogt, Jürgen V.; Bisselink, Bernard; de Roo, Ad
Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, eu/gdo/" target="_blank">http://edo.jrc.ec.europa.eu/gdo/), the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1) the soil moisture from the Lisflood distributed hydrological model (namely LIS), (2) the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST), and (3) the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI). Due to the independency of these three datasets, the triple collocation (TC) technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia) detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of
Full Text Available Agricultural drought events can affect large regions across the world, implying the need for a suitable global tool for an accurate monitoring of this phenomenon. Soil moisture anomalies are considered a good metric to capture the occurrence of agricultural drought events, and they have become an important component of several operational drought monitoring systems. In the framework of the JRC Global Drought Observatory (GDO, http://edo.jrc.ec.europa.eu/gdo/, the suitability of three datasets as possible representations of root zone soil moisture anomalies has been evaluated: (1 the soil moisture from the Lisflood distributed hydrological model (namely LIS, (2 the remotely sensed Land Surface Temperature data from the MODIS satellite (namely LST, and (3 the ESA Climate Change Initiative combined passive/active microwave skin soil moisture dataset (namely CCI. Due to the independency of these three datasets, the triple collocation (TC technique has been applied, aiming at quantifying the likely error associated with each dataset in comparison to the unknown true status of the system. TC analysis was performed on five macro-regions (namely North America, Europe, India, southern Africa and Australia detected as suitable for the experiment, providing insight into the mutual relationship between these datasets as well as an assessment of the accuracy of each method. Even if no definitive statement on the spatial distribution of errors can be provided, a clear outcome of the TC analysis is the good performance of the remote sensing datasets, especially CCI, over dry regions such as Australia and southern Africa, whereas the outputs of LIS seem to be more reliable over areas that are well monitored through meteorological ground station networks, such as North America and Europe. In a global drought monitoring system, the results of the error analysis are used to design a weighted-average ensemble system that exploits the advantages of each dataset.
Rao, K.S.; Chandra, G.; Rao, P.V.N.
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
Sure, A.; Dikshit, O.
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.
Nuclear and related techniques can help develop climate-smart agricultural practices by optimizing water use efficiency. The measurement of soil water content is essential to improve the use of this resource in agriculture. However, most sensors monitor small areas (less than 1m in radius), hence a large number of sensors are needed to obtain soil water content across a large area. This can be both costly and labour intensive and so larger scale measuring devices are needed as an alternative to traditional point-based soil moisture sensing techniques. The cosmic ray neutron sensor (CRNS) is such a device that monitors soil water content in a non-invasive and continuous way. This publication provides background information about this novel technique, and explains in detail the calibration and validation process.
Crow, W. T.; Kustas, W. P.
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.
O'Donnell, F. C.; Springer, A. E.; Sankey, T.; Masek Lopez, S.
Forest restoration projects are being planned for large areas of overgrown semi-arid ponderosa pine forests of the Southwestern US. Restoration involves the thinning of smaller trees and prescribed or managed fire to reduce tree density, restore a more natural fire regime, and decrease the risk of catastrophic wildfire. The stated goals of these projects generally reduced plant water stress and improvements in hydrologic function. However, little is known about how to design restoration treatments to best meet these goals. As part of a larger project on snow cover, soil moisture, and groundwater recharge, we measured soil moisture, an indicator of plant water status, in four pairs of control and restored sites near Flagstaff, Arizona. The restoration strategies used at the sites range in both amount of open space created and degree of clustering of the remaining trees. We measured soil moisture using 30 cm vertical time domain reflectometry probes installed on 100 m transects at 5 m intervals so it would be possible to analyze the spatial pattern of soil moisture. Soil moisture was higher and more spatially variable in the restored sites than the control sites with differences in spatial pattern among the restoration types. Soil moisture monitoring will continue until the first snow fall, at which point measurements of snow depth and snow water equivalent will be made at the same locations.
Kearney, Michael R.; Maino, James L.
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
Koster, R. D.; Walker, G. K.
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.
Knight, B P; Chaudri, A M; McGrath, S P; Giller, K E
A rapid method for extracting soil solutions using porous plastic soil-moisture samplers was combined with a cation resin equilibration based speciation technique to look at the chemical availability of metals in soil. Industrially polluted, metal sulphate amended and sewage sludge treated soils were used in our study. Cadmium sulphate amended and industrially contaminated soils all had > 65% of the total soil solution Cd present as free Cd2+. However, increasing total soil Cd concentrations by adding CdSO4 resulted in smaller total soil solution Cd. Consequently, the free Cd2+ concentrations in soil solutions extracted from these soils were smaller than in the same soil contaminated by sewage sludge addition. Amendment with ZnSO4 gave much greater concentrations of free Zn2+ in soil solutions compared with the same soil after long-term Zn contamination via sewage sludge additions. Our results demonstrate the difficulty in comparing total soil solution and free metal ion concentrations for soils from different areas with different physiochemical properties and sources of contamination. However, when comparing the same Woburn soil, Cd was much less available as Cd2+ in soil solution from the CdSO4 amended soils compared with soil contaminated by about 36 years of sewage sludge additions. In contrast, much more Zn was available in soil solution as free Zn2+ in the ZnSO4 amended soils compared with the sewage sludge treated soils.
Penna, Daniele; Gobbi, Alberto; Mantese, Nicola; Borga, Marco
Hydrological processes driving runoff generation in mountain basins depend on a wide number of factors which are often strictly interconnected. Among them, topography is widely recognized as one of the dominant controls influencing soil moisture distribution in the root zone, depth to water table and location and extent of saturated areas possibly prone to runoff production. Morphological properties of catchments are responsible for the alternation between steep slopes and relatively flat areas which have the potentials to control the storage/release of water and hence the hydrological response of the whole watershed. This work aims to: i) identify the role of topography as the main factor controlling the spatial distribution of near-surface soil moisture; ii) evaluate the possible switch in soil moisture spatial organization between wet and relatively dry periods and the stability of patterns during triggering of surface/subsurface runoff; iii) assess the possible connection between the develop of an ephemeral river network and the groundwater variations, examining the influence of the catchment topographical properties on the hydrological response. Hydro-meteorological data were collected in a small subcatchment (Larch Creek Catchment, 0.033 km²) of Rio Vauz basin (1.9 km²), in the eastern Italian Alps. Precipitation, discharge, water table level over a net of 14 piezometric wells and volumetric soil moisture at 0-30 cm depth were monitored continuously during the late spring-early autumn months in 2007 and 2008. Soil water content at 0-6 and 0-20 cm depth was measured manually during 22 field surveys in summer 2007 over a 44-sampling point experimental plot (approximately 3000 m²). In summer 2008 the sampling grid was extended to 64 points (approximately 4500 m²) and 28 field surveys were carried out. The length of the ephemeral stream network developed during rainfall events was assessed by a net of 24 Overland Flow Detectors (OFDs), which are able to
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.
Gherboudj, Imen; Beegum, S. Naseema; Marticorena, Beatrice; Ghedira, Hosni
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
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
Saxena, P.; Chaudhary, T.N.; Mookerji, P.
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
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.
Massoud, M.A.; El-Nennah, M.E.; El-Kholi, A.F.; Abd-Elmonem, M.A.
The purpose of this investigation was to study the effect of soil moisture on the radiosensitivity of soil bacteria and fungi. The percentages of survival of soil bacteria and fungi, after exposure to different doses of gamma radiation, were lower in the moistened soil samples than in the dry one, inspite of the observed encouragement of wetting the soil samples, before gamma radiation exposure, on the proliferation of soil micro-organisms. This effect was explained by the indirect action from the breakdown products of radiolysis of water rather than by the direct damage to the cell structure
Shuttleworth, W. J.; Zreda, M. G.; Zeng, X.; Zweck, C.; Franz, T. E.; Rosolem, R.
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
area is selected in the Mashhad plain in Khorasan Razavi province of I.R. Iran. Study area is about 1,200 square kilometers and is located around the Golmakan center of agricultural research. In this study, water deficit index (WDI was zoning by MODIS images in subset of Mashhad plain during water year of 2011-2012. Then, based on the close relationship between WDI and soil moisture parameter, a linear relationship between these two parameters were fitted. Soil moisture is measured by the TDR and every 7 days at 5 depths of 5, 10, 20, 30 and 50 cm from the surface. Remote Sensing (RS technology used as a tool for providing some of the data that is required. The moderate resolution imaging spectroradiometer (MODIS instrument is popular for monitoring soil moisture because of its high spectral (36 bands resolution, moderate spatial (250–1000 m resolution and various products for land surface properties. MODIS products used in the present study include: MOD09A1 land surface albedo data, MOD11A1 land surface temperature data, and MOD13A1 vegetation data. Using ArcMap 9.2 and ERDAS IMAGINE 2010 softwares, WDI was calculated pixel by pixel for 18 days (non-cloudy days and simultaneous with measurement of soil moisture at the station. Results and Discussion: The results showed that the northeastern region is predominantly rainfed and irrigated farmlands are under water stress. Conversely, the southwestern part of the area is mountainous with less water stress. Based on NDVI, there is also less crop cover in the southwestern part of the region during the year. The results showed that about 44% of the index values are in the range of 0.2-0.3. Then about 22% of the index values are in the range of 0.3-0.4. Thus it can be concluded that over 66% of the index values are in the range of 0.2-0.4. According to the maximum index value (WDI=0.59 on the 201th day of year and the minimum values (WDI=0.0004 on the 129th day of year during the time period of study, it seems that water
G. Geoff Wang; Shongming Huang; Robert A. Monserud; Ryan J. Klos
Lodgepole pine site index was examined in relation to synoptic measures of topography, soil moisture, and soil nutrients in Alberta. Data came from 214 lodgepole pine-dominated stands sampled as a part of the provincial permanent sample plot program. Spatial location (elevation, latitude, and longitude) and natural subregions (NSRs) were topographic variables that...
Bao, Xiaoying; Zhu, Xiaoxue; Chang, Xiaofeng; Wang, Shiping; Xu, Burenbayin; Luo, Caiyun; Zhang, Zhenhua; Wang, Qi; Rui, Yichao; Cui, Xiaoying
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.
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...
Šípek, Václav; Tesař, Miroslav
Roč. 31, č. 6 (2017), s. 1438-1452 ISSN 0885-6087 R&D Projects: GA ČR GA16-05665S Institutional support: RVO:67985874 Keywords : hydrological modelling * pore-size distribution * saturated hydraulic conductivity * seasonal variability * soil hydraulic parameters * soil moisture Subject RIV: DA - Hydrology ; Limnology OBOR OECD: Hydrology Impact factor: 3.014, year: 2016
Claire L. Phillips; Nick Nickerson; David Risk; Zachary E. Kayler; Chris Andersen; Alan Mix; Barbara J. Bond
The carbon isotopic composition (Î´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 Î´13C of soil respiration, which suggests indirectly that recently fixed photosynthates...
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.
Zhu, H.; Zhao, H. L.; Jiang, Y. Z.; Zang, W. B.
Soil moisture is one of the important hydrological elements. Obtaining soil moisture accurately and effectively is of great significance for water resource management in irrigation area. During the process of soil moisture content retrieval with multiremote sensing data, multi- remote sensing data always brings multi-spatial scale problems which results in inconformity of soil moisture content retrieved by remote sensing in different spatial scale. In addition, agricultural water use management has suitable spatial scale of soil moisture information so as to satisfy the demands of dynamic management of water use and water demand in certain unit. We have proposed to use land parcel unit as the minimum unit to do soil moisture content research in agricultural water using area, according to soil characteristics, vegetation coverage characteristics in underlying layer, and hydrological characteristic into the basis of study unit division. We have proposed division method of land parcel units. Based on multi thermal infrared and near infrared remote sensing data, we calculate the ndvi and tvdi index and make a statistical model between the tvdi index and soil moisture of ground monitoring station. Then we move forward to study soil moisture remote sensing retrieval method on land parcel unit scale. And the method has been applied in Hetao irrigation area. Results show that compared with pixel scale the soil moisture content in land parcel unit scale has displayed stronger correlation with true value. Hence, remote sensing retrieval method of soil moisture content in land parcel unit scale has shown good applicability in Hetao irrigation area. We converted the research unit into the scale of land parcel unit. Using the land parcel units with unified crops and soil attributes as the research units more complies with the characteristics of agricultural water areas, avoids the problems such as decomposition of mixed pixels and excessive dependence on high-resolution data
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.
Imamovic, Adel; Schlemmer, Linda; Schär, Christoph
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
Dumouchelle, Denise H.; Darner, Robert A.
Stormwater runoff in urban areas is increasingly being managed by means of a variety of treaments that reduce or delay runoff and promote more natural infiltration. One such treatment is a rain garden, which is built to detain runoff and allow for water infiltration and uptake by plants.Water flow into or out of a rain garden can be readily monitored with a variety of tools; however, observing the movement of water within the rain garden is less straightforward. Soil-moisture probes in combination with an automated interpolation procedure were used to document the infiltration of water into two rain gardens in Ohio. Animations show changes in soil moisture in the rain gardens during two precipitation events. At both sites, the animations demonstrate underutilization of the rain gardens.
Bloem, J.; Schouten, A.J.; Sørensen, S.J.; Rutgers, M.; Werf, van der A.K.; Breure, A.M.
This book provides a selection of microbiological methods that are already applied in regional or national soil quality monitoring programs. It is split into two parts: part one gives an overview of approaches to monitoring, evaluating and managing soil quality. Part two provides a selection of
Bispo, A.; Cluzeau, D.; Creamer, R.
is made for a set of suitable indicators for monitoring the decline in soil biodiversity (Bispo et al. 2007). These indicators were selected both from a literature review and an inventory of national monitoring programmes. Decline in soil biodiversity was defined as the reduction of forms of life living...... indicators are actually measured. For monitoring application it was considered in ENVASSO that only three key indicators per soil stress were practical. For indicating biodiversity decline it was difficult to arrive at a small set of indicators due to the complexity of soil biota and functions. Therefore...
landscape developed under tropical climate with alternate wet ... nical reasons. The sensing element for soil tem- ... The sensor associated with its signal conditioning, processed ...... formance over Europe, through remote-sensing of vegeta-.
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.
Raja Shekhar, S. S.; Chandrasekar, K.; Sesha Sai, M. V. R.; Diwakar, P. G.; Dadhwal, V. K.
Drought is a frequently occurring disaster affecting lives of millions of people across the world every year. Several parameters, indices and models are being used globally to forecast / early warning of drought and monitoring drought for its prevalence, persistence and severity. Since drought is a complex phenomenon, large number of parameter/index need to be evaluated to sufficiently address the problem. It is a challenge to generate input parameters from different sources like space based data, ground data and collateral data in short intervals of time, where there may be limitation in terms of processing power, availability of domain expertise, specialized models & tools. In this study, effort has been made to automate the derivation of one of the important parameter in the drought studies viz Soil Moisture. Soil water balance bucket model is in vogue to arrive at soil moisture products, which is widely popular for its sensitivity to soil conditions and rainfall parameters. This model has been encoded into "Fish-Bone" architecture using COM technologies and Open Source libraries for best possible automation to fulfill the needs for a standard procedure of preparing input parameters and processing routines. The main aim of the system is to provide operational environment for generation of soil moisture products by facilitating users to concentrate on further enhancements and implementation of these parameters in related areas of research, without re-discovering the established models. Emphasis of the architecture is mainly based on available open source libraries for GIS and Raster IO operations for different file formats to ensure that the products can be widely distributed without the burden of any commercial dependencies. Further the system is automated to the extent of user free operations if required with inbuilt chain processing for every day generation of products at specified intervals. Operational software has inbuilt capabilities to automatically
Xu, Wenfang; Yuan, Wenping; Dong, Wenjie; Xia, Jiangzhou; Liu, Dan; Chen, Yang
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)
Blanchard, M. B.; Greeley, R.; Goettelman, R.
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).
NDVI in soil moisture monitoring, even in extreme environments. To the best of our knowledge, this paper represents the first study of this kind using Sentinel-2.
Full Text Available Soil moisture (SM is a highly relevant variable for agriculture, the emergence of floods and a key variable in the global energy and water cycle. In the last years, several satellite missions have been launched especially to derive large-scale products of the SM dynamics on the Earth. However, in situ validation data are often scarce. We developed a new method to retrieve SM of bare soil from measurements of low-cost GPS (Global Positioning System sensors that receive the freely available GPS L1-band signals. The experimental setup of three GPS sensors was installed at a bare soil field at the German Weather Service (DWD in Munich for almost 1.5 years. Two GPS antennas were installed within the soil column at a depth of 10 cm and one above the soil. SM was successfully retrieved based on GPS signal strength losses through the integral soil volume. The results show high agreement with measured and modelled SM validation data. Due to its non-destructive, cheap and low power setup, GPS sensor networks could also be used for potential applications in remote areas, aiming to serve as satellite validation data and to support the fields of agriculture, water supply, flood forecasting and climate change.
Zhang, Yanjun; Guo, Shengli; Liu, Qingfang; Jiang, Jishao
Understanding the response mechanisms of litter respiration to soil moisture in water-limited semi-arid regions is of vital importance to better understanding the interplay between ecological processes and the local carbon cycle. In situ soil respiration was monitored during 2010–2012 under various conditions (normal litter, no litter, and double litter treatments) in a 30-year-old artificial black locust plantation (Robinia pseudoacacia L.) on the Loess Plateau. Litter respiration with normal and double litter treatments exhibited similar seasonal variation, with the maximum value obtained in summer (0.57 and 1.51 μmol m−2 s−1 under normal and double litter conditions, respectively) and the minimum in spring (0.27 and 0.69 μmol m−2 s−1 under normal and double litter conditions, respectively). On average, annual cumulative litter respiration was 115 and 300 g C m−2 y−1 under normal and double litter conditions, respectively. Using a soil temperature of 17°C as the critical point, the relationship between litter respiration and soil moisture was found to follow quadratic functions well, whereas the determination coefficient was much greater at high soil temperature than at low soil temperature (33–35% vs. 22–24%). Litter respiration was significantly higher in 2010 and 2012 than in 2011 under both normal litter (132–165 g C m−2 y−1 vs. 48 g C m−2 y−1) and double litter (389–418 g C m−2 y−1 vs. 93 g C m−2 y−1) conditions. Such significant interannual variations were largely ascribed to the differences in summer rainfall. Our study demonstrates that, apart from soil temperature, moisture also has significant influence on litter respiration in semi-arid regions. PMID:25474633
Orth, René; Seneviratne, Sonia I.
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
K. C. Kornelsen
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.
Bindlish, Rajat; Jackson, Thomas; Cosh, Michael; Zhao, Tianjie; O'Neil, Peggy
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.
Moradizadeh, Mina; Saradjian, Mohammad R.
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.
The SMAP (Soil Moisture Active Passive) mission provides global surface soil moisture product at 36 km resolution from its L-band radiometer. While the coarse resolution is satisfactory to many applications there are also a lot of applications which would benefit from a higher resolution soil moistu...
Jeremy Pinto; John D. Marshall; Kas Dumroese; Anthony S. Davis; Douglas R. Cobos
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...
In this thesis, the possibilities of using spaceborne remote sensing for large-scale groundwater modeling are explored. We focus on a soil moisture product called European Remote Sensing Soil Water Index (ERS SWI, Wagner et al., 1999) - representing the upper profile soil moisture. As a test-bed, we
Global-scale surface soil moisture (SSM) products retrieved from active and passive microwave remote sensing provide an effective method for monitoring near-real-time SSM content with nearly daily temporal resolution. In the present study, we first inter-compared global-scale error patterns and comb...
Mittelbach, H.; Orth, R.; Seneviratne, S. I.
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.
Bircher, Simone; Skou, Niels; Jensen, K. H.
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...
Deraedt, Deborah; Bernard, Julien; Bietlot, Louise; Clerbois, Laura; Rosière, Clément; Starren, Amandine; Colinet, Gilles; Mercatoris, Benoit; Degré, Aurore
. The evolution of the soil sample height was monitored as well. As first result, the stone content is a parameter that seems to influence soil water content. The stone size is no important. Because soil moisture deserves to be measured accurately in every soil and to confirm the first results the experiment is going on with more samples, different stone proportions, other sensor positioning and a natural air drying.
Coates, Victoria; Pattison, Ian; Sander, Graham
England's rural landscape is dominated by pastoral agriculture, with 40% of land cover classified as either improved or semi-natural grassland according to the Land Cover Map 2007. Since the Second World War the intensification of agriculture has resulted in greater levels of soil compaction, associated with higher stocking densities in fields. Locally compaction has led to loss of soil storage and an increased in levels of ponding in fields. At the catchment scale soil compaction has been hypothesised to contribute to increased flood risk. Previous research (Pattison, 2011) on a 40km2 catchment (Dacre Beck, Lake District, UK) has shown that when soil characteristics are homogeneously parameterised in a hydrological model, downstream peak discharges can be 65% higher for a heavy compacted soil than for a lightly compacted soil. However, at the catchment scale there is likely to be a significant amount of variability in compaction levels within and between fields, due to multiple controlling factors. This research focusses in on one specific type of land use (permanent pasture with cattle grazing) and areas of activity within the field (feeding area, field gate, tree shelter, open field area). The aim was to determine if the soil characteristics and soil compaction levels are homogeneous in the four areas of the field. Also, to determine if these levels stayed the same over the course of the year, or if there were differences at the end of the dry (October) and wet (April) periods. Field experiments were conducted in the River Skell catchment, in Yorkshire, UK, which has an area of 120km2. The dynamic cone penetrometer was used to determine the structural properties of the soil, soil samples were collected to assess the bulk density, organic matter content and permeability in the laboratory and the Hydrosense II was used to determine the soil moisture content in the topsoil. Penetration results show that the tree shelter is the most compacted and the open field area
Shao, Wei; Coenders-Gerrits, Miriam; Judge, Jasmeet; Zeng, Yijian; Su, Ye
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
Jarvi, Mickey P; Burton, Andrew J
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.
Al-Jeboori, M.A.; Ameen, I.A.
Water content in soil column was measured using NaI scintillation detector 5 mci Cs-137 as a gamma source. The measurements were done with a back scatter gauge, restricted with scattering angle less to than /2 overcome the effect of soil type. A 3 cm air gap was maintained between the front of the detector and the wall of the soil container in order to increase the counting rate. The distance between the center of the source and the center of the back scattering detector was 14 cm. The accuracy of the measurements was 0.63. For comparision, a direct rays method was used to measure the soil moisture. The results gave an error of 0.65. Results of the two methods were compared with the gravimetric method which gave an error of 0.18 g/g and 0.17 g/g for direct and back method respectively. The quick direct method was used to determine the gravimetric and volumetric percentage constants, and were found to be 1.62 and 0.865 respectively. The method then used to measure the water content in the layers of soil column.(6 tabs., 4 figs., 12 refs.)
Burgin, M. S.; van Zyl, J. J.
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.
The prevailing severe shortage of animal feed in most of the developing countries could, to a considerable extent, be overcome through improved range management, which includes introduction of high yielding drought-resistant forage crops, development of adequate water conservation measures, and as far as possible growing annual forage crops on part of the vast areas of arable land currently left fallow each year. Year round measurements are essential for a good understanding of soil water and nutrients dynamics, which allow for adequate evaluation of pasture management alternatives. The methods most commonly used for moisture measurements in soil profiles are discussed because such measurements are likely to form an essential part of any investigation aimed at increasing animal feed production through the development of adequate pasture management practices. (author)
Todisco, Francesca; Brocca, Luca; Termite, Loris Francesco; Wagner, Wolfgang
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
extracted using this model were also studied for their capability to monitor soil moisture variation. Finally, phenomena such as retrieval ambiguity and error sensitivity were stated and discussed.
Full Text Available The DO3SE (Deposition of O3 for Stomatal Exchange model is an established tool for estimating ozone (O3 deposition, stomatal flux and impacts to a variety of vegetation types across Europe. It has been embedded within the EMEP (European Monitoring and Evaluation Programme photochemical model to provide a policy tool capable of relating the flux-based risk of vegetation damage to O3 precursor emission scenarios for use in policy formulation. A key limitation of regional flux-based risk assessments has been the assumption that soil water deficits are not limiting O3 flux due to the unavailability of evaluated methods for modelling soil water deficits and their influence on stomatal conductance (gsto, and subsequent O3 flux. This paper describes the development and evaluation of a method to estimate soil moisture status and its influence on gsto for a variety of forest tree species. This DO3SE soil moisture module uses the Penman-Monteith energy balance method to drive water cycling through the soil-plant-atmosphere system and empirical data describing gsto relationships with pre-dawn leaf water status to estimate the biological control of transpiration. We trial four different methods to estimate this biological control of the transpiration stream, which vary from simple methods that relate soil water content or potential directly to gsto, to more complex methods that incorporate hydraulic resistance and plant capacitance that control water flow through the plant system. These methods are evaluated against field data describing a variety of soil water variables, gsto and transpiration data for Norway spruce (Picea abies, Scots pine (Pinus sylvestris, birch (Betula pendula, aspen (Populus tremuloides, beech (Fagus sylvatica and holm oak (Quercus ilex collected from ten sites across Europe and North America. Modelled estimates of these variables show consistency with observed data when applying the simple empirical methods, with the timing and
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
Seyyedi, H.; Anagnostou, E. N.
This study presents an in-depth analysis of the dependence of overland rainfall estimates from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) on the soil moisture conditions at the land surface. TMI retrievals are verified against rainfall fields derived from a high resolution rain-gauge network (MESONET) covering Oklahoma. Soil moisture (SOM) patterns are extracted based on recorded data from 2000-2007 with 30 minutes temporal resolution. The area is divided into wet and dry regions based on normalized SOM (Nsom) values. Statistical comparison between two groups is conducted based on recorded ground station measurements and the corresponding passive microwave retrievals from TMI overpasses at the respective MESONET station location and time. The zero order error statistics show that the Probability of Detection (POD) for the wet regions (higher Nsom values) is higher than the dry regions. The Falls Alarm Ratio (FAR) and volumetric FAR is lower for the wet regions. The volumetric missed rain for the wet region is lower than dry region. Analysis of the MESONET-to-TMI ratio values shows that TMI tends to overestimate for surface rainfall intensities less than 12 (mm/h), however the magnitude of the overestimation over the wet regions is lower than the dry regions.
Tuttle, Samuel E.; Salvucci, Guido D.
Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.
Brown, Molly E.; Moran, Susan; Escobar, Vanessa; Entekhabi, Dara; O'Neill, Peggy; Njoku, Eni
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.
Tang, Min; Zhao, Xi Ning; Gao, Xiao Dong; Zhang, Chao; Wu, Pu Te
Soil water availability is a key factor restricting the ecological construction and sustainable land use in the loess hilly region. It is of great theoretical and practical significance to understand the soil moisture status of different land use types for the vegetation restoration and the effective utilization of land resources in this area. In this study, EC-5 soil moisture sensors were used to continuously monitor the soil moisture content in the 0-160 cm soil profile in the slope cropland, terraced fields, jujube orchard, and grassland during the growing season (from May to October) in the Yuanzegou catchment on the Loess Plateau, to investigate soil moisture dynamics in these four typical land use types. The results showed that there were differences in seasonal variation, water storage characteristics, and vertical distribution of soil moisture under different land use types in both the normal precipitation (2014) and dry (2015) years. The terraced fields showed good water retention capacity in the dry year, with the average soil moisture content of 0-60 cm soil layer in the growing season being 2.6%, 4.2%, and 1.8% higher than that of the slope cropland, jujube orchard, and grassland (all Pmoisture content of 0-60 cm soil layer in jujube orchard in the growing season was 2.9%, 3.8%, and 4.5% lower than that of slope cropland, terraced fields, and grassland, respectively (all Pmoisture in the surface layer (0-20 cm) and soil moisture in the middle layer (20-100 cm) under different land use types was large, and the trend for the similarity degree of soil moisture variation followed terraced fields > grassland > slope cropland > jujube orchard. The slope cropland in this area could be transformed into terraced fields to improve the utilization of precipitation and promote the construction of ecological agriculture. Aiming at resolving the severe water shortage in the rain-fed jujube orchard for the sustainable development of jujube orchard in the loess hilly
Full Text Available Land-atmosphere interactions play an important role for hot temperature extremes in Europe. Dry soils may amplify such extremes through feedbacks with evapotranspiration. While previous observational studies generally focused on the relationship between precipitation deficits and the number of hot days, we investigate here the influence of soil moisture (SM on summer monthly maximum temperatures (TXx using water balance model-based SM estimates (driven with observations and temperature observations. Generalized extreme value distributions are fitted to TXx using SM as a covariate. We identify a negative relationship between SM and TXx, whereby a 100 mm decrease in model-based SM is associated with a 1.6 °C increase in TXx in Southern-Central and Southeastern Europe. Dry SM conditions result in a 2–4 °C increase in the 20-year return value of TXx compared to wet conditions in these two regions. In contrast with SM impacts on the number of hot days (NHD, where low and high surface-moisture conditions lead to different variability, we find a mostly linear dependency of the 20-year return value on surface-moisture conditions. We attribute this difference to the non-linear relationship between TXx and NHD that stems from the threshold-based calculation of NHD. Furthermore the employed SM data and the Standardized Precipitation Index (SPI are only weakly correlated in the investigated regions, highlighting the importance of evapotranspiration and runoff for resulting SM. Finally, in a case study for the hot 2003 summer we illustrate that if 2003 spring conditions in Southern-Central Europe had been as dry as in the more recent 2011 event, temperature extremes in summer would have been higher by about 1 °C, further enhancing the already extreme conditions which prevailed in that year.
Li, Bailing; Toll, David; Zhan, Xiwu; Cosgrove, Brian
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.
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.
Chitu, Zenaida; Bogaard, Thom; Adler, Mary-Jeanne; Steele-Dunne, Susan; Hrachowitz, Markus; Busuioc, Aristita; Sandric, Ionut; Istrate, Alexandru
Like in many parts of the world, landslides represent in Romania recurrent phenomena that produce numerous damages to the infrastructure every few years. The high frequency of landslide events over the world has resulted to the development of many early warning systems that are based on the definition of rainfall thresholds triggering landslides. In Romania in particular, recent studies exploring the temporal occurrence of landslides have revealed that rainfall represents the most important triggering factor for landslides. The presence of low permeability soils and gentle slope degrees in the Ialomita Subcarpathians of Romania makes that cumulated precipitation over variable time interval and the hydraulic response of the soil plays a key role in landslides triggering. In order to identify the slope responses to rainfall events in this particular area we investigate the variability of soil moisture and its relationship to landslide events in three Subcarpathians catchments (Cricovul Dulce, Bizididel and Vulcana) by combining in situ measurements, satellite-based radiometry and hydrological modelling. For the current study, hourly soil moisture measurements from six soil moisture monitoring stations that are fitted with volumetric soil moisture sensors, temperature soil sensors and rain gauges sensors are used. Pedotransfer functions will be applied in order to infer hydraulic soil properties from soil texture sampled from 50 soil profiles. The information about spatial and temporal variability of soil moisture content will be completed with the Level 2 soil moisture products from the Soil Moisture and Ocean Salinity (SMOS) mission. A time series analysis of soil moisture is planned to be integrated to landslide and rainfall time series in order to determine a preliminary rainfall threshold triggering landslides in Ialomita Subcarpathians.
Hübner, R.; Heller, K.; Günther, T.; Kleber, A.
Besides floodplains, hillslopes are basic units that mainly control water movement and flow pathways within catchments of subdued mountain ranges. The structure of their shallow subsurface affects water balance, e.g. infiltration, retention, and runoff. Nevertheless, there is still a gap in the knowledge of the hydrological dynamics on hillslopes, notably due to the lack of generalization and transferability. This study presents a robust multi-method framework of electrical resistivity tomography (ERT) in addition to hydrometric point measurements, transferring hydrometric data into higher spatial scales to obtain additional patterns of distribution and dynamics of soil moisture on a hillslope. A geoelectrical monitoring in a small catchment in the eastern Ore Mountains was carried out at weekly intervals from May to December 2008 to image seasonal moisture dynamics on the hillslope scale. To link water content and electrical resistivity, the parameters of Archie's law were determined using different core samples. To optimize inversion parameters and methods, the derived spatial and temporal water content distribution was compared to tensiometer data. The results from ERT measurements show a strong correlation with the hydrometric data. The response is congruent to the soil tension data. Water content calculated from the ERT profile shows similar variations as that of water content from soil moisture sensors. Consequently, soil moisture dynamics on the hillslope scale may be determined not only by expensive invasive punctual hydrometric measurements, but also by minimally invasive time-lapse ERT, provided that pedo-/petrophysical relationships are known. Since ERT integrates larger spatial scales, a combination with hydrometric point measurements improves the understanding of the ongoing hydrological processes and better suits identification of heterogeneities.
To support the operational use of Synthetic Aperture Radar (SAR) earth observation systems, the European Space Agency (ESA) is developing Sentinel-1 radar satellites operating in C-band. Much like its SAR predecessors (Earth Resource Satellite, ENVISAT, and RADARSAT), the Sentinel-1 will operate at a medium spatial resolution (ranging from 5 to 40 m), but with a greatly improved revisit period, especially over Europe (∼2 days). Given the planned high temporal sampling and the operational configuration Sentinel-1 is expected to be beneficial for operational monitoring of dynamic processes in hydrology and phenology. The benefit of a C-band SAR monitoring service in hydrology has already been demonstrated within the scope of the Soil Moisture for Hydrometeorologic Applications (SHARE) project using data from the Global Mode (GM) of the Advanced Synthetic Aperture Radar (ASAR). To fully exploit the potential of the SAR soil moisture products, well characterized error needs to be provided with the products. Understanding errors of remotely sensed surface soil moisture (SSM) datasets was indispensible for their application in models, for extractions of blended SSM products, as well as for their usage in evaluation of other soil moisture datasets. This thesis has several objectives. First, it provides the basics and state of the art methods for evaluating measures of SSM, including both the standard (e.g. Root Mean Square Error, Correlation coefficient) and the advanced (e.g. Error propagation, Triple collocation) evaluation measures. A summary of applications of soil moisture datasets is presented and evaluation measures are suggested for each application according to its requirement on the dataset quality. The evaluation of the Advanced Synthetic Aperture Radar (ASAR) Global Mode (GM) SSM using the standard and advanced evaluation measures comprises a second objective of the work. To achieve the second objective, the data from the Australian Water Assessment System
Water storage and flow in soils is usually complicated by the intricate nature of and changes in soil pore size distribution (PSD) due to modifications in soil structure following changes in agricultural management. The paper presents the Soil High Energy Moisture Characteristic (Soil-HEMC) method f...
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
Sally M Haase
Prescribed burning created a more favorable seedbed by exposing mineral soil and increasing soil moisture, resulting in a twenty-fold increase in the number of seeds germinating on burned compared to unburned sites.
Santanello, Joseph A., Jr.; Kumar, Sujay V.; Peters-Lidard, Christa D.; Lawston, P.
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.
Kumar, S.; Newman, M.; Lawrence, D. M.; Livneh, B.; Lombardozzi, D. L.
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.
Liu, Zhao; Zhou, Yan-Lian; Ju, Wei-Min; Gao, Ping
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.
Blankenship, C. B.; Case, J.; Zavodsky, B.; Crosson, W. L.
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.
Boisramé, Gabrielle; Thompson, Sally; Stephens, Scott
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.
Full Text Available Studies are warranted to evaluate head injury criterion (HIC on athletic fields to determine baseline numbers and compare those findings to current critical thresholds for impact attenuation. A two year (2016 and 2017 study was conducted on University of Tennessee athletic fields (Knoxville, TN, USA to determine the effect of soil type (cohesive soil, United States Golf Association sand specifications and grass species (Poa pratensis and Cynodon dactylon × C. transvaalensis on HIC. Additionally soil moisture conditions monitored were: dry (0.06–0.16 m3/m3, acceptable (0.17–0.29 m3/m3, and wet (0.30–0.40 m3/m3. A linear relationship (r = 0.91 was identified between drop height (0.5–2.9 M and HIC value (35-1423 HIC on granular root zones of both grass types. However, HIC on cohesive soil is a function of soil water content in addition to drop height. These results demonstrate to aid in head injury prevention on cohesive soil athletic fields the HIC can be lowered by managing soil water content.
Schmid, T.; Tallos, A.; Millan, R.; Vera, R.; Recreo, F.
This study forms part of the project Mercurio and Recuperation de Terrenos Afectados por Mercurio Ambiental (RETAMA) , which determines the behaviour of mercury in the soil-plant system within the area of Almaden. The objective of this work is to instrument lysimeters with a set of electronic sensors to monitor physical and chemical soil parameters (moisture content, soil temperature, soil water matrix potential, Eh and pH) over a period of a complete vegetation cycle for selected crops. Physical and chemical soil analyses have been carried out on samples two soil profiles marking the extreme perimeter where the lysimeters were extracted. The monitoring data obtained every half hour show that the physicochemical conditions of the soils in the lysimeter can be correlated with the type of cultivation in the lysimeters. The results for parameters such as soil water matrix potential and the soil temperature reflect the diurnal changes; and fluctuations of the Eh can be related to the biological activities in the soils and are within oxid and sub oxid conditions. Slight fluctuations have been observed for the pH and constant volumetric moisture content is maintained during the period of no hydric stress. (Author) 16 refs
Schmid, T.; Tallos, A.; Millan, R.; Vera, R.; Recreo, F.
This study forms part of the project Mercurio and Recuperation de Terrenos Afectados por Mercurio Ambiental (RETAMA), which determines the behaviour of mercury in the soil-plant system within the area of Almaden. The objective of this work is to instrument lysimeters with a set of electronic sensors to monitor physical and chemical soil parameters (moisture content, soil temperature, soil water matrix potential. Eh and pH) over a period of a complete vegetation cycle for selected crops. Physical and chemical soil analyses have been carried out on samples two soil profiles marking the extreme perimeter where the lysimeters were extracted. The monitoring data obtained every half hour show that the physicochemical conditions of the soils in the lysimeter can be correlated with the type of cultivation in the lysimeters. The results for parameters such as soil water matrix potential and the soil temperature reflect the diurnal changes; and fluctuations of the Eh can be related to the biological activities in the soils and are within oxid and suboxic conditions. Slight fluctuations have been observed for the pH and constant volumetric moisture content is maintained during the period of no hydric stress. (Author) 16 refs.
The Hanford Nuclear Reservation Tank Farms' underground waste tanks have been used to store liquid radioactive waste from defense materials production since the 1940's. Waste in certain of the tanks may contain material in the form of ferrocyanide or various organic compounds which could potentially be susceptible to condensed phase chemical reactions. Because of the presence of oxidizing materials (nitrate compounds) and heat sources (radioactive decay and chemical reactions), the ferrocyanide or organic material could potentially fuel a propagating exothermic reaction with undesirable consequences. Analysis and experiments indicate that the reaction propagation and/or initiation may be prevented by the presence of sufficient moisture in the waste. Because the reaction would probably be initiated at the surface of the waste, evidence of sufficient moisture concentration would help provide evidence that the tank waste can continue to be safely stored. The Surface Moisture Measurement System (SMMS) was developed to collect data on the surface moisture in the waste by inserting two types of probes (singly) into a waste tank-a neutron probe and an electromagnetic inductance (EMI) probe. The sensor probes will be placed on the surface of the waste utilizing a moveable deployment arm to lower them through an available riser. The movement of the SMMS within the tank will be monitored by a camera lowered through an adjacent riser. The SMMS equipment is the subject of this study. Hazards and Operability Analysis (HAZOP) is a systematic technique for assessing potential hazards and/or operability problems for a new activity. It utilizes a multidiscipline team of knowledgeable individuals in a systematic brainstorming effort. The results of this study will be used as input to an Unreviewed Safety Question determination
Tsegaye, T.; Coleman, T.; Senwo, Z.; Shaffer, D.; Zou, X.
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.
Jackson, R. D.; Cihlar, J.; Estes, J. E.; Heilman, J. L.; Kahle, A.; Kanemasu, E. T.; Millard, J.; Price, J. C.; Wiegand, C. L.
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.
Samaniego, L. E.; Warrach-Sagi, K.; Zink, M.; Wulfmeyer, V.
obtained by closing the water balance over major river basins in Germany. Simulated soil moisture and latent heat flux were also evaluated at several eddy covariance sites in Germany. Comparison of monthly soil moisture and latent heat fields obtained with both models over Germany exhibited significant differences, which are mainly attributed to the subgrid variability of key model parameters such as porosity and aerodynamic resistance. Comparison of soil moisture fields obtained with WRF/Noah-MP and mHM forced with grided metereological observations (German Meteorological Service) showed that the differences between both models are mainly due to a combination of precipitation bias and different soil texture resolution. However, EOF analyses indicate that CORDEX results start recovering structures due to soil and vegetation properties. This experiment clearly highlighted the importance of hyper resolution input data to address these challenge. High resolution mHM simulations also indicate that the parametric uncertainty of land surface models is significant, and should not be neglected if a model is to be employed for application at regional scales, e.g. for drought monitoring.
Pandey, Dharmendra K.; Maity, Saroj; Bhattacharya, Bimal; Misra, Arundhati
Accurate measurement of surface soil moisture of bare and vegetation covered soil over agricultural field and monitoring the changes in surface soil moisture is vital for estimation for managing and mitigating risk to agricultural crop, which requires information and knowledge to assess risk potential and implement risk reduction strategies and deliver essential responses. The empirical and semi-empirical model-based soil moisture inversion approach developed in the past are either sensor or region specific, vegetation type specific or have limited validity range, and have limited scope to explain physical scattering processes. Hence, there is need for more robust, physical polarimetric radar backscatter model-based retrieval methods, which are sensor and location independent and have wide range of validity over soil properties. In the present study, Integral Equation Model (IEM) and Vector Radiative Transfer (VRT) model were used to simulate averaged backscatter coefficients in various soil moisture (dry, moist and wet soil), soil roughness (smooth to very rough) and crop conditions (low to high vegetation water contents) over selected regions of Gujarat state of India and the results were compared with multi-temporal Radar Imaging Satellite-1 (RISAT-1) C-band Synthetic Aperture Radar (SAR) data in σ°HH and σ°HV polarizations, in sync with on field measured soil and crop conditions. High correlations were observed between RISAT-1 HH and HV with model simulated σ°HH & σ°HV based on field measured soil with the coefficient of determination R2 varying from 0.84 to 0.77 and RMSE varying from 0.94 dB to 2.1 dB for bare soil. Whereas in case of winter wheat crop, coefficient of determination R2 varying from 0.84 to 0.79 and RMSE varying from 0.87 dB to 1.34 dB, corresponding to with vegetation water content values up to 3.4 kg/m2. Artificial Neural Network (ANN) methods were adopted for model-based soil moisture inversion. The training datasets for the NNs were
Orth, Rene; Seneviratne, Sonia I.
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.
J.D. Helvey; J.N. Kochenderfer; J.N. Kochenderfer
Reports results of soil density and soil moisture measurements on two roads in the central Appalachians over a 30-month period. Density increased slightly during the measurement period at most locations. Almost all of the density changes occurred during the first few months after construction. Moisture content decreased during the first few months after construction,...
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...
Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...
L. Hao; Ge Sun; Yongqiang Liu; G. S. Zhou; J. H. Wan; L. B. Zhang; J. L. Niu; Y. H. Sang; J. J He
Precipitation, evapotranspiration (ET), and soil moisture are the key controls for the productivity and functioning of temperate grassland ecosystems in Inner Mongolia, northern China. Quantifying the soil moisture dynamics and water balances in the grasslands is essential to sustainable grassland management under global climate change. We...
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)
Wang, Jianghao; Ge, Yong; Heuvelink, Gerard B.M.; Zhou, Chenghu
Validation of satellite-based soil moisture products is necessary to provide users with an assessment of their accuracy and reliability and to ensure quality of information. A key step in the validation process is to upscale point-scale, ground-based soil moisture observations to satellite-scale
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.
Hector Ramirez; Alexander Fernald; Andres Cibils; Michelle Morris; Shad Cox; Michael Rubio
Clearing oneseed juniper (Juniperus monosperma) may make more water available for aquifer recharge or herbaceous vegetation growth, but the effects of tree treatment on soil moisture dynamics are not fully understood. This study investigated juniper treatment effects on understory herbaceous vegetation concurrently with soil moisture dynamics using vegetation sampling...
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 ...
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...
Moran, M. Susan; O'Neill, Peggy E.; Entekhabi, Dara; Njoku, Eni G.; Kellogg, Kent H.
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.
Roger C. Bales; Jan W. Hopmans; Anthony T. O’Geen; Matthew Meadows; Peter C. Hartsough; Peter Kirchner; Carolyn T. Hunsaker; Dylan. Beaudette
Using data from a water-balance instrument cluster with spatially distributed sensors we determined the magnitude and within-catchment variability of components of the catchment-scale water balance, focusing on the relationship of seasonal evapotranspiration to changes in snowpack and soil moisture storage. Co-located, continuous snow depth and soil moisture...
Blankenship, Clay; Zavodsky, Bradley; Case, Jonathan; Stano, Geoffrey
Goal: Accurate, high-resolution (approx.3 km) soil moisture in near-real time. Situational awareness (drought assessment, flood and fire threat). Local modeling applications (to improve sfc-PBL exchanges) Method: Assimilate satellite soil moisture retrievals into a land surface model. Combines high-resolution geophysical model data with latest satellite observations.
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...
Akbar, Ruzbeh; Short Gianotti, Daniel; McColl, Kaighin A.; Haghighi, Erfan; Salvucci, Guido D.; Entekhabi, Dara
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.
Bárcenas-Moreno, G., M. Gómez-Brandón, J. Rousk, and E. Bååth. 2009. Adaptation of soil microbial communities to temperature: Comparison of fungi and...ER D C/ CR RE L TR -1 5- 6 ERDC 6.2 Geospatial Research and Engineering (GRE) ARTEMIS TSP-SA Soil Temperature and Moisture Effects on... Soil Respiration and Microbial Community Abundance Co ld R eg io ns R es ea rc h an d En gi ne er in g La bo ra to ry Robyn A. Barbato
Su, Chun-Hsu; Ryu, Dongryeol; Dorigo, Wouter; Zwieback, Simon; Gruber, Alexander; Albergel, Clement; Reichle, Rolf H.; Wagner, Wolfgang
Climate Data Records (CDR) that blend multiple satellite products are invaluable for climate studies, trend analysis and risk assessments. Knowledge of any inhomogeneities in the CDR is therefore critical for making correct inferences. This work proposes a methodology to identify the spatiotemporal extent of the inhomogeneities in a 36-year, global multisatellite soil moisture CDR as the result of changing observing systems. Inhomogeneities are detected at up to 24 percent of the tested pixels with spatial extent varying with satellite changeover times. Nevertheless, the contiguous periods without inhomogeneities at changeover times are generally longer than 10 years. Although the inhomogeneities have measurable impact on the derived trends, these trends are similar to those observed in ground data and land surface reanalysis, with an average error less than 0.003 cubic meters per cubic meter per year. These results strengthen the basis of using the product for long-term studies and demonstrate the necessity of homogeneity testing of multisatellite CDRs in general.
Tramblay, Yves; Bouvier, Christophe; Martin, C.; Didon-Lescot, J. F.; Todorovik, D.; Domergue, J. M.
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,...
Bolten, J. D.; Crow, W.; Zhan, X.; Jackson, T.; Reynolds, C.
A crucial requirement of global crop yield forecasts by the U.S. Department of Agriculture (USDA) International Production Assessment Division (IPAD) is the regional characterization of surface and sub-surface soil moisture. However, due to the spatial heterogeneity and dynamic nature of precipitation events and resulting soil moisture, accurate estimation of regional land surface-atmosphere interactions based sparse ground measurements is difficult. IPAD estimates global soil moisture using daily estimates of minimum and maximum temperature and precipitation applied to a modified Palmer two-layer soil moisture model which calculates the daily amount of soil moisture withdrawn by evapotranspiration and replenished by precipitation. We attempt to improve upon the existing system by 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 soil moisture model. This work aims at evaluating the utility of merging satellite-retrieved soil moisture estimates with the IPAD two-layer soil moisture model used within the DBMS. We present a quantitative analysis of the assimilated soil moisture product over West Africa (9°N- 20°N; 20°W-20°E). This region contains many key agricultural areas and has a high agro- meteorological gradient from desert and semi-arid vegetation in the North, to grassland, trees and crops in the South, thus providing an ideal location for evaluating the assimilated soil moisture product over multiple land cover types and conditions. A data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing assimilated soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model
Martens, B.; Miralles, D.; Lievens, H.; Fernández-Prieto, D.; Verhoest, N. E. C.
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
Dick, Jonathan; Tetzlaff, Doerthe; Bradford, John; Soulsby, Chris
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
Hauser, Mathias; Orth, René; Seneviratne, Sonia I.
The severe 2010 heat wave in western Russia was found to be influenced by anthropogenic climate change. Additionally, soil moisture-temperature feedbacks were deemed important for the buildup of the exceptionally high temperatures. We quantify the relative role of both factors by applying the probabilistic event attribution framework and analyze ensemble simulations to distinguish the effect of climate change and the 2010 soil moisture conditions for annual maximum temperatures. The dry 2010 soil moisture alone has increased the risk of a severe heat wave in western Russia sixfold, while climate change from 1960 to 2000 has approximately tripled it. The combined effect of climate change and 2010 soil moisture yields a 13 times higher heat wave risk. We conclude that internal climate variability causing the dry 2010 soil moisture conditions formed a necessary basis for the extreme heat wave.
Vogel, M. M.; Orth, R.; Cheruy, F.; Hagemann, S.; Lorenz, R.; Hurk, B. J. J. M.; Seneviratne, S. I.
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 the role of soil moisture-temperature feedbacks for this response based on multimodel 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 processes leading to these changes. We find that soil moisture-temperature feedbacks significantly contribute to the amplified warming of the hottest days compared to that of global mean temperature. This contribution reaches more than 70% in Central Europe and Central North America. Soil moisture trends are more important for this response than short-term soil moisture variability. These results are relevant for reducing uncertainties in regional temperature projections.
Zhao, L.; Hu, G.; Wu, X.; Tian, L.
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.
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.
Huang, Gang; Zhao, Xue-yong; Huang, Ying-xin; Su, Yan-gui
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.
Orth, R.; Seneviratne, S. I.
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.
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.
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.
A.M. Weitza; E. Linderb; S. Frolkingc; P.M. Crillc; M. Keller
We studied soil moisture dynamics and nitrous oxide (N2O) Â¯uxes from agricultural soils in the humid tropics of Costa Rica. Using a splitplot design on two soils (clay, loam) we compared two crop types (annual, perennial) each unfertilized and fertilized. Both soils are of andic origin. Their properties include relatively low bulk density and high organic matter...
Wax apple (Syzygium samarngense Merr.et Perry) was one of the economically planted fruits in Taiwan. This research was conducted to evaluate the effects of different soil moisture management on increasing wax apple quality. It was preceded at two different soil properties (shallow soil and alluvial soil) in Pingtung, ...
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...
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
Blakenship, Clay; Zavodsky, Bradley; Cae, Jonathan
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.
Kalopesas, Charalampos; Galanis, George; Kalopesa, Eleni; Katsogiannos, Fotis; Kalafatis, Panagiotis; Bilas, George; Patakas, Aggelos; Zalidis, George
Mapping the spatial variation of soil moisture content is a vital parameter for precision agriculture techniques. The aim of this study was to examine the correlation of soil moisture and conductivity (EC) data obtained through scanning techniques with field telemetry data and to spatially separate the field into discrete irrigation management zones. Using the Veris MSP3 model, geo-referenced data for electrical conductivity and organic matter preliminary maps were produced in a pilot kiwifruit field in Chrysoupoli, Kavala. Data from 15 stratified sampling points was used in order to produce the corresponding soil maps. Fusion of the Veris produced maps (OM, pH, ECa) resulted on the delineation of the field into three zones of specific management interest. An appropriate pedotransfer function was used in order to estimate a capacity soil indicator, the saturated volumetric water content (θs) for each zone, while the relationship between ECs and ECa was established for each zone. Validation of the uniformity of the three management zones was achieved by measuring specific electrical conductivity (ECs) along a transect in each zone and corresponding semivariograms for ECs within each zone. Near real-time data produced by a telemetric network consisting of soil moisture and electrical conductivity sensors, were used in order to integrate the temporal component of the specific management zones, enabling the calculation of time specific volumetric water contents on a 10 minute interval, an intensity soil indicator necessary to be incorporated to differentiate spatially the irrigation strategies for each zone. This study emphasizes the benefits yielded by fusing near real time telemetric data with soil scanning data and spatial interpolation techniques, enhancing the precision and validity of the desired results. Furthermore the use of telemetric data in combination with modern database management and geospatial software leads to timely produced operational results
Carranza, Coleen D. U.; van der Ploeg, Martine J.; Torfs, Paul J. J. F.
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.
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.
Jung, S C; Kuk, Y I; Senseman, S A; Ahn, H G; Seong, C N; Lee, D J
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.
Li, L.; Ouellette, J. D.; Colliander, A.; Cosh, M. H.; Caldwell, T. G.; Walker, J. P.
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
Full Text Available Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale and binary indicator maps (for the long-term and hillslope scale. Annual dynamics of soil moisture and decimeter-scale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a data-scarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to
Increased use of prescribed fire by land managers and the increasing likelihood of wildfires due to climate change require an improved modeling capability of extreme heating of soils during fires. This issue is addressed here by developing and testing the soil (heat-moisture-vapor) HMVmodel, a 1-D (one-dimensional) non-equilibrium (liquid- vapor phase change)...
In frame of Soil monitoring system it is going about a lot of methods in advance as follows: methods of soil monitoring sites selection and soil monitoring network construction, as well; methods of soil survey and soil sampling; analytical methods (indicating of chemical, agrochemical and physical properties); soil database and methods of evaluation and interpretation of measured results. The monitoring network was constructed on the base of ecological principles - including the monitoring of all soil types and subtypes, various climatic and emission regions as well as relatively clean regions, lowland and highland. Soil monitoring network in forest land is regular (8 x 8 km) with regard to International monitoring system in Forestry. The soil monitoring network in Slovakia consist of 650 monitoring sites (312 sites in farming land and 338 sites in forest land). In addition soil monitoring network includes also 21 monitoring sites. All monitoring sites are geodesically located and reported on the map at a scale of 1:5000. There are the methods concerning the important soil parameters indication with regard to main soil degradation processes a s follows: soil contamination (heavy metals and organic contaminants); soil acidification; soil salinity; soil erosion (deluometrically by the Cs-137 and remote sensing methods); soil compaction; soil fertility and protection. Analytical control system was elaborated according to Good Laboratory Practice. Evaluation of soil monitoring network results is not simple because it depends on various monitored parameters, on aim of evaluation as well as on the scale of landscape which is object for evaluation. There are used the modern statistical methods in monitoring system which can be: universal; disjunctive; simulated. Used statistical methods are significant for interpretation of measured results as follows: trends in landscape; anisotropy; comparison. The evaluation and interpretation way is very significant with regard not
Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Vogt, Roland; Li, Lin; Seely, Mary K.
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.
M. R. Mobasheri
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.
Parinussa, R.M.; Meesters, A.G.C.A.; Liu, Y.Y.; Dorigo, W.; Wagner, W.; de Jeu, R.A.M.
A time-efficient solution to estimate the error of satellite surface soil moisture from the land parameter retrieval model is presented. The errors are estimated using an analytical solution for soil moisture retrievals from this radiative-transfer-based model that derives soil moisture from
Kaplan, D.; Muñoz-Carpena, R.
SummaryRestoration of degraded floodplain forests requires a robust understanding of surface water, groundwater, and vadose zone hydrology. Soil moisture is of particular importance for seed germination and seedling survival, but is difficult to monitor and often overlooked in wetland restoration studies. This research hypothesizes that the complex effects of surface water and shallow groundwater on the soil moisture dynamics of floodplain wetlands are spatially complementary. To test this hypothesis, 31 long-term (4-year) hydrological time series were collected in the floodplain of the Loxahatchee River (Florida, USA), where watershed modifications have led to reduced freshwater flow, altered hydroperiod and salinity, and a degraded ecosystem. Dynamic factor analysis (DFA), a time series dimension reduction technique, was applied to model temporal and spatial variation in 12 soil moisture time series as linear combinations of common trends (representing shared, but unexplained, variability) and explanatory variables (selected from 19 additional candidate hydrological time series). The resulting dynamic factor models yielded good predictions of observed soil moisture series (overall coefficient of efficiency = 0.90) by identifying surface water elevation, groundwater elevation, and net recharge (cumulative rainfall-cumulative evapotranspiration) as important explanatory variables. Strong and complementary linear relationships were found between floodplain elevation and surface water effects (slope = 0.72, R2 = 0.86, p < 0.001), and between elevation and groundwater effects (slope = -0.71, R2 = 0.71, p = 0.001), while the effect of net recharge was homogenous across the experimental transect (slope = 0.03, R2 = 0.05, p = 0.242). This study provides a quantitative insight into the spatial structure of groundwater and surface water effects on soil moisture that will be useful for refining monitoring plans and developing ecosystem restoration and management scenarios
Hain, C.; Crow, W. T.; Anderson, M. C.; Yilmaz, M. T.
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
Bertoldi, Giacomo; Claudia, Notarnicola; Brenner, Johannes; Castelli, Mariapina; Greifeneder, Felix; Niedrist, Georg; Seeber, Julia; Tappeiner, Ulrike
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
Ballesteros, M.; Mazon, M. P.
The effect of soil moisture, over field capacity, on growth and photosynthesis of three moisture levels (20,30 and 40 %) was studied.The first moisture level was near field capacity while the others exceeded. Weekly dry weight of different plant parts, chlorophyll content, net CO 2 exchange rate in light and darkness, 14 C O 2 assimilated rate and stomatal aperture were determined. Results show a positive effect of soil moisture over field capacity on growth, photosynthate and transpiration of beans during the first growing month. (Author) 76 refs
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
Virgawati, S.; Mawardi, M.; Sutiarso, L.; Shibusawa, S.; Segah, H.; Kodaira, M.
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.
El- Gendy, R.W.
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
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.
Akuraju, V. R.; Ryu, D.; George, B.; Ryu, Y.; Dassanayake, K. B.
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.
Abou-Assaf, N.; Coats, J.R.
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
Full Text Available The first five centimeters of soil form an interface where the main heat fluxes exchanges between the land surface and the atmosphere occur. Besides ground measurements, remote sensing has proven to be an excellent tool for the monitoring of spatial and temporal distributed data of the most relevant Earth surface parameters including soil’s parameters. Indeed, active microwave sensors (Synthetic Aperture Radar - SAR offer the opportunity to monitor soil moisture (HS at global, regional and local scales by monitoring involved processes. Several inversion algorithms, that derive geophysical information as HS from SAR data, were developed. Many of them use electromagnetic models for simulating the backscattering coefficient and are based on statistical techniques, such as neural networks, inversion methods and regression models. Recent studies have shown that simple multiple regression techniques yield satisfactory results. The involved geophysical variables in these methodologies are descriptive of the soil structure, microwave characteristics and land use. Therefore, in this paper we aim at developing a multiple linear regression model to estimate HS on flat agricultural regions using TerraSAR-X satellite data and data from a ground weather station. The results show that the backscatter, the precipitation and the relative humidity are the explanatory variables of HS. The results obtained presented a RMSE of 5.4 and a R2 of about 0.6
José Ricardo Macedo Pezzopane
Full Text Available In this study, the microclimate changes in silvopastoral systems are quantified at different time and spatial scales and compared with single-pasture systems. The study was conducted in a silvopastoral system in São Carlos, Brazil (22°01' South and 47°53' West. The silvopastoral system consisted of grass pastures [Urochloa (sin. Brachiaria decumbens cv. Basilik] lined with strips of native trees spaced at 17 m. Continuous microclimate measurements (air temperature, relative humidity, wind speed, and incident photosynthetically active radiation were carried out from September 2010 to September 2012 at two positions of the silvopastoral system (2.0 and 8.5 m from the rows of trees and at a pasture under full sunlight, located in an adjacent area. The soil moisture was monitored weekly from 24 March 2010 to 1 April 2012 at distances of 0.0, 2.0, 4.75, and 8.5 m from the rows of trees. The rows of native trees reduced wind speeds (46% reduction and changed the photosynthetically active radiation incidence pattern on the pasture (up to 40% reduction of incidence at the point nearest to the trees. The combined action of these factors promoted thermal and air humidity changes on the pasture at the different points measured. With respect to soil moisture, there was greater soil moisture removal at the sampling points near the rows of native trees under the silvopastoral system, mainly due to enhanced exploration by tree roots at greater depths in dry spells or early dry periods, when compared with the midpoints between the rows.
He, Liming; Chen, Jing M.; Liu, Jane; Bélair, Stéphane; Luo, Xiangzhong
In this study, high-quality soil moisture data derived from the Soil Moisture Active Passive (SMAP) satellite measurements are evaluated from a perspective of improving the estimation of the global gross primary production (GPP) using a process-based ecosystem model, namely, the Boreal Ecosystem Productivity Simulator (BEPS). The SMAP soil moisture data are assimilated into BEPS using an ensemble Kalman filter. The correlation coefficient (r) between simulated GPP from the sunlit leaves and Sun-induced chlorophyll fluorescence (SIF) measured by Global Ozone Monitoring Experiment-2 is used as an indicator to evaluate the performance of the GPP simulation. Areas with SMAP data in low quality (i.e., forests), or with SIF in low magnitude (e.g., deserts), or both are excluded from the analysis. With the assimilated SMAP data, the r value is enhanced for Africa, Asia, and North America by 0.016, 0.013, and 0.013, respectively (p r appears in single-cropping agricultural land where the irrigation is not considered in the model but well captured by SMAP (e.g., 0.09 in North America, p < 0.05). With the assimilation of SMAP, areas with weak model performances are identified in double or triple cropping cropland (e.g., part of North China Plain) and/or mountainous area (e.g., Spain and Turkey). The correlation coefficient is enhanced by 0.01 in global average for shrub, grass, and cropland. This enhancement is small and insignificant because nonwater-stressed areas are included.
Vogel, Martha Marie; Orth, René; Cheruy, Frederique; Hagemann, Stefan; Lorenz, Ruth; van den Hurk, Bart; Seneviratne, Sonia Isabelle
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.
Kumar, Sujay V.; Reichle, Rolf H.; Harrison, Kenneth W.; Peters-Lidard, Christa D.; Yatheendradas, Soni; Santanello, Joseph A.
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.
Hu, Z.; Xu, L.; Yu, B.
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.
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.
Bi, H Y; Ma, J W; Qin, S X; Zeng, J Y
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
Michel, Claude; Andréassian, Vazken; Perrin, Charles
This paper unveils major inconsistencies in the age-old and yet efficient Soil Conservation Service Curve Number (SCS-CN) procedure. Our findings are based on an analysis of the continuous soil moisture accounting procedure implied by the SCS-CN equation. It is shown that several flaws plague the original SCS-CN procedure, the most important one being a confusion between intrinsic parameter and initial condition. A change of parameterization and a more complete assessment of the initial condition lead to a renewed SCS-CN procedure, while keeping the acknowledged efficiency of the original method.
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 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
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
Chang, Ni-Bin; Xuan, Zhemin; Wimberly, Brent
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.
An empirical equation was deduced from studies of time variations of terrestrial gamma exposure rate and soil moisture content with depth distribution in the surface layer. It was definitely suggested that the variation of terrestrial gamma exposure rate is most strongly influenced by the change of soil moisture content at 5 cm depth. The seasonal variation with a relative maximum in early autumn and a relative minimum in early spring was clearly obtained in the consequence of long time measurements of terrestrial gamma exposure rate and degree of soil dryness. The diurnal change and phase difference due to the effect of depth were also obtained in the dynamic characteristics of soil moisture content at 3 different depths. From the comparison between measured terrestrial gamma exposure rate and that evaluated from soil moisture content using the empirical equation, it was seen that seasonal variations of the both agreed fairly well as a whole. (author)
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.
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
Jacobs, J. M.; Cho, E.; Jia, X.
In the past two decades, tile drainage installation has accelerated throughout the Red River of the North Basin (RRB) in parts of western Minnesota, eastern North Dakota, and a small area of northeastern South Dakota, because the flat topography and low-permeability soils in this region necessitated the removal of excess water to improve crop production. Interestingly, streamflow in the Red River has markedly increased and six of 13 major floods during the past century have occurred since the late 1990s. It has been suggested that the increase in RRB flooding could be due to change in agricultural practices, including extensive tile drainage installation. Reliable information on existing and future tile drainage installation is greatly needed to capture the rapid extension of tile drainage systems and to locate tile drainage systems in the north central U.S. including the RRB region. However, there are few reliable data of tile drainage installation records, except tile drainage permit records in the Bois de Sioux watershed (a sub-basin in southern part of the RRB where permits are required for tile drainage installation). This study presents a tile drainage expansion detection method based on a physical principle that the soil-drying rate may increase with increasing tile drainage for a given area. In order to capture the rate of change in soil drying rate with time over entire RRB (101,500 km2), two satellite-based microwave soil moisture records from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and AMSR2 were used during 2002 to 2016. In this study, a sub-watershed level (HUC10) potential tile drainage growth map was developed and the results show good agreement with tile drainage permit records of six sub-watersheds in the Bois de Sioux watershed. Future analyses will include improvement of the potential tile drainage map through additional information using optical- and thermal-based sensor products and evaluation of its
Shrivastava, Sourabh; Kar, Sarat C.; Sharma, Anu Rani
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.
Marimuthu, S.; Raj Kumar, R.
An experiment was conducted with pot-grown young tea plants to study N uptake under different soil moisture regime. Labelled urea nitrogen was found effectively utilized under rainfed conditions. However, N loss through percolation/leaching in response to saturated moisture was as high as 33.3%. Plants grown under controlled conditions utilized less amount of applied N and the rest was retained in the soil. Unaccounted loss, in both the cases, was approximately 9%. Fertilizer-use efficiency of young tea plants under rain fed conditions was about 35% while it was 15% under moisture deficient conditions. Results on N balance in tea soils are discussed. (author)
Moghaddam, M.; Silva, A. R. D.; Akbar, R.; Clewley, D.
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.
El Sebaï, Talaat; Devers, Marion; Lagacherie, Bernard; Rouard, Nadine; Soulas, Guy; Martin-Laurent, Fabrice
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.
Xingming, Zheng; Kai, Zhao; Yangyang, Li; Jianhua, Ren; Yanling, Ding
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.
Pellet, Cécile; Hilbich, Christin; Marmy, Antoine; Hauck, Christian
The use of geophysical methods in the field of permafrost research is well established and crucial since it is the only way to infer the composition of the subsurface material. Since geophysical measurements are indirect, ambiguities in the interpretation of the results can arise, hence the simultaneous use of several methods (e.g. electrical resistivity tomography and refraction seismics) is often necessary. The so-called four-phase model, 4PM (Hauck et al., 2011) constitutes a further step towards clarification of interpretation from geophysical measurements. It uses two well-known petrophysical relationships, namely Archie's law and an extension of Timur's time-averaged equation for seismic P-wave velocities, to quantitatively estimate the different phase contents (air, water and ice) in the ground from tomographic electric and seismic measurements. In this study, soil moisture measurements were used to calibrate the 4PM in order to assess the spatial distribution of water, ice and air content in the ground at three high elevation sites with different ground properties and thermal regimes. The datasets used here were collected as part of the SNF-project SOMOMOUNT. Within the framework of this project a network of six entirely automated soil moisture stations was installed in Switzerland along an altitudinal gradient ranging from 1'200 m. a.s.l. to 3'400 m. a.s.l. The standard instrumentation of each station comprises the installation of Frequency Domain Reflectometry (FDR) and Time Domain Reflectometry (TDR) sensors for long term monitoring coupled with repeated Electrical Resistivity Tomography (ERT) and Refraction Seismic Tomography (RST) as well as spatial FDR (S-FDR) measurements. The use of spatially distributed soil moisture data significantly improved the 4PM calibration process and a semi-automatic calibration scheme was developed. This procedure was then tested at three different locations, yielding satisfactory two dimensional distributions of water
A. Al Bitar
Full Text Available The objective of this paper is to present the multi-orbit (MO surface soil moisture (SM and angle-binned brightness temperature (TB products for the SMOS (Soil Moisture and Ocean Salinity mission based on a new multi-orbit algorithm. The Level 3 algorithm at CATDS (Centre Aval de Traitement des Données SMOS makes use of MO retrieval to enhance the robustness and quality of SM retrievals. The motivation of the approach is to make use of the longer temporal autocorrelation length of the vegetation optical depth (VOD compared to the corresponding SM autocorrelation in order to enhance the retrievals when an acquisition occurs at the border of the swath. The retrieval algorithm is implemented in a unique operational processor delivering multiple parameters (e.g. SM and VOD using multi-angular dual-polarisation TB from MO. A subsidiary angle-binned TB product is provided. In this study the Level 3 TB V310 product is showcased and compared to SMAP (Soil Moisture Active Passive TB. The Level 3 SM V300 product is compared to the single-orbit (SO retrievals from the Level 2 SM processor from ESA with aligned configuration. The advantages and drawbacks of the Level 3 SM product (L3SM are discussed. The comparison is done on a global scale between the two datasets and on the local scale with respect to in situ data from AMMA-CATCH and USDA ARS Watershed networks. The results obtained from the global analysis show that the MO implementation enhances the number of retrievals: up to 9 % over certain areas. The comparison with the in situ data shows that the increase in the number of retrievals does not come with a decrease in quality, but rather at the expense of an increased time lag in product availability from 6 h to 3.5 days, which can be a limiting factor for applications like flood forecast but reasonable for drought monitoring and climate change studies. The SMOS L3 soil moisture and L3 brightness temperature products are delivered using an
Full Text Available Observation on the seasonal variations of hydrological condition and turgidity of selected Robusta coffee clones has been carried out in Kaliwining Experimental Station, Indonesian Coffee and Cocoa Research Institute in Jember. The aim was to evaluate the effect of hydrological variation on the coffee plants and the degree of soil moisture effect on plant performance. Experimental site overlays on alluvial plain, + 45 m a.s.l., 8o 15’ South with D rainfall type. Observation was conducted by survey method at the experimental plots of organic fertilizer and nitogen treatments on selected Robusta coffee clones derived from rooted cuttings, i.e. BP 436, BP 42, BP 936 and BP 358. Observation was only conducted at the experimental blocks of organic matter trials of 20 l/tree/year at nitrogen (Urea application of locally recommanded rate during the subsequent years of 1999 to 2001. Parameters observed included plant turgidity and soil moisture content of three different depths, i.e. 0—20, 20—40 and 40—60 cm and the weather. Observation was carried out in five replicates designed as blocks of barn manure treatment and N-fertilizer of recommended rate as basal fertilizer. The results showed that meteorological condition and soil moisture of experimental site through the years have seasonal patterns following the seasonal pattern of rainfall. Compared to other meteorological characteristics, relative humidity dominantly determined evaporation and plant turgidity. Plant turgi-dity was not only determined by soil moisture condition, but also atmospheric demand. When relative humidity (RH was relatively high, plant turgidity was relatively stable although soil moisture of surface layers was very low, and the reversal when soil moisture content was high plant turgidity was controlled by atmospheric demand (relative humidity. With a 3—4 dry month period, relative turgidity of the coffee plants was relatively stable above 82%, except when soil
Jean FranÃƒÂ§ois Desprats
Full Text Available Soil moisture is a key parameter in different environmental applications, suchas hydrology and natural risk assessment. In this paper, surface soil moisture mappingwas carried out over a basin in France using satellite synthetic aperture radar (SARimages acquired in 2006 and 2007 by C-band (5.3 GHz sensors. The comparisonbetween soil moisture estimated from SAR data and in situ measurements shows goodagreement, with a mapping accuracy better than 3%. This result shows that themonitoring of soil moisture from SAR images is possible in operational phase. Moreover,moistures simulated by the operational MÃƒÂ©tÃƒÂ©o-France ISBA soil-vegetation-atmospheretransfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moistureestimates to validate its pertinence. The difference between ISBA simulations and radarestimates fluctuates between 0.4 and 10% (RMSE. The comparison between ISBA andgravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally,these results are very encouraging. Results show also that the soil moisture estimatedfrom SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones.
Martins Bento, Celia; Yang, Xiaomei; Gort, Gerrit; Xue, Sha; Dam, van Ruud; Zomer, Paul; Mol, Hans G.J.; Ritsema, Coen J.; Geissen, Violette
The dissipation kinetics of glyphosate and its metabolite aminomethylphosphonic acid (AMPA) were studied in loess soil, under biotic and abiotic conditions, as affected by temperature, soil moisture (SM) and light/darkness. Nonsterile and sterile soil samples were spiked with 16 mg kg−
Kreye, Phillip; Meon, Günter
Complex concepts for the physically correct depiction of dominant processes in the hydrosphere are increasingly at the forefront of hydrological modelling. Many scientific issues in hydrological modelling demand for additional system variables besides a simulation of runoff only, such as groundwater recharge or soil moisture conditions. Models that include soil water simulations are either very simplified or require a high number of parameters. Against this backdrop there is a heightened demand of observations to be used to calibrate the model. A reasonable integration of groundwater data or remote sensing data in calibration procedures as well as the identifiability of physically plausible sets of parameters is subject to research in the field of hydrology. Since this data is often combined with conceptual models, the given interfaces are not suitable for such demands. Furthermore, the application of automated optimisation procedures is generally associated with conceptual models, whose (fast) computing times allow many iterations of the optimisation in an acceptable time frame. One of the main aims of this study is to reduce the discrepancy between scientific and practical applications in the field of hydrological modelling. Therefore, the soil model DYVESOM (DYnamic VEgetation SOil Model) was developed as one of the primary components of the hydrological modelling system PANTA RHEI. DYVESOMs structure provides the required interfaces for the calibrations made at runoff, satellite based soil moisture and groundwater level. The model considers spatial and temporal differentiated feedback of the development of the vegetation on the soil system. In addition, small scale heterogeneities of soil properties (subgrid-variability) are parameterized by variation of van Genuchten parameters depending on distribution functions. Different sets of parameters are operated simultaneously while interacting with each other. The developed soil model is innovative regarding concept
2Atmospheric and Climate Sciences Group, Earth & Climate Science Area, National Remote Sensing Centre, ... soil moisture from India Meteorological Department (IMD) are used for the validation of the gridded soil .... the first generation satellite of Global Change ..... urban, inland water, bare soil and land ice) derived.
ter Heerdt, Gerard N. J.; Veen, Ciska G.F.; van der Putten, Wim H.; Bakker, Jan P.
Restoration of riparian plant communities on bare soil requires germination of seeds and establishment of seedlings. However, species that are present in the soil seed bank do not always establish in the vegetation. Temperature, moisture conditions and soil type could play a major role in the
Heerdt, ter Gerard N.J.; Veen, Ciska G.F.; Putten, van der Wim H.; Bakker, Jan P.
Restoration of riparian plant communities on bare soil requires germination of seeds and establishment of seedlings. However, species that are present in the soil seed bank do not always establish in the vegetation. Temperature, moisture conditions and soil type could play a major role in the
Ter Heerdt, Gerard N.J.; Veen, G.F.; Van der Putten, Wim H.; Bakker, Jan P.
Abstract Restoration of riparian plant communities on bare soil requires germination of seeds and establishment of seedlings. However, species that are present in the soil seed bank do not always establish in the vegetation. Temperature, moisture conditions and soil type could play a major role in
Shrub encroachment into grasslands creates a mosaic of different soil microsites ranging from open spaces to well-developed shrub canopies, and it is unclear how this affects the spatial variability in soil respiration characteristics, such as the sensitivity to soil temperature and moisture. This i...
James H. Patric; James H. Patric
Soil moisture, precipitation, and streamflow were measured on three watersheds in West Virginia, two deforested and one forested. Water content of barren soil always exceeded that of forest soil throughout the growing season and especially in dry weather. Streamflow increased 10 inches annually on the watersheds that were cleared, most of the increase occurring between...
Bird, M.I.; Veenendaal, E.M.; Lloyd, J.
We present a study of soil organic carbon (SOC) inventories and d 13C values for 625 soil cores collected from well-drained, coarse-textured soils in eight areas along a 1000 km moisture gradient from Southern Botswana, north into southern Zambia. The spatial distribution of trees and grass in the
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
Sreelash, K.; Sekhar, M.; Ruiz, L.; Tomer, S. K.; Guérif, M.; Buis, S.; Durand, P.; Gascuel-Odoux, C.
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 t