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Soil Hydraulic Conductivity Data (FIFE)
The Soil Hydraulic Conductivity Data Set contains soil hydraulic conductivity, matric flux potential, and soil depth data collected during the 1989 FIFE soil properties investigation. The purpose of the 1989 FIFE soil properties investigation was to obtain more points on the soil moisture release curves for the soils at the FIFE stations, and provide values for the saturated hydraulic conductivity for the long-term water balance studies. In-situ measurements of field-saturated hydraulic conductivity were made using the constant well head permeameter method. These measurements were made at five sites, each representing a different soil series. The constant well head method for hydraulic conductivity involves augering a hole to the desired depth and measuring the steady state flow rate of water into the hole while maintaining a constant head of water inside the hole. Six measurements were made at each of the two soil depths at each site. The hydraulic conductivity measurements were made at the same depths and close to (less than 1 m away from) the location where samples for moisture release measurements were taken.
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Soil Thermal Conductivity Data (FIFE)
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The purpose of the 1989 FIFE soil properties investigation was to obtain a description of the thermal properties of the soils within the FIFE study area. Soil thermal conductivity measurements describe the soil properties which govern the flow of heat through the soil. The thermal conductivity is defined as the quantity of heat that flows through a unit area in a unit time under a unit temperature gradient. These measurements were made using a hot wire probe in situ at two depths at twenty six FIFE sites during October 1987. The measurements were taken using a long electrically heated wire enclosed in a cylindrical probe . The probe is placed in the soil, the wire is heated by running a current through it, and the temperature rise is measured with a thermocouple placed next to the wire. A plot of temperature versus the log of time can be used to derive the thermal conductivity. The results may require a correction factor to account for the dimensions of the probe.
Soil Water Prop. Derived Data (FIFE)
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During the 1989 FIFE field campaign, measurements were made of soil moisture release parameters and hydraulic conductivity. Bulk density and soil moisture release data were collected at five FIFE sites representing the major soil types in the FIFE study area. These data were used to model the porosity, saturated water potential, and the b-factor (the exponent of the power curve function) following the method of Clapp and Hormberger (1978). These soil moisture characteristics can be used to describe plant-available water and water movement through soils.
Soil Impedance Data (FIFE)
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The purpose of this research was to characterize the soil moisture distribution in the FIFE study area. Daily measurements of the soil dielectric properties were obtained at five locations throughout the FIFE study area during the 1987 Intensive Field Campaigns (IFC). Calculated soil volumetric water contents were compared with gravimetric soil moisture measurements collected at the same locations by the FIFE staff science team. Examination of the data revealed that the impedance probe is a more consistent source of time series information than traditional measurements, and is potentially more closely linked to the physical parameters. The dielectric constant of soil is a potentially sensitive indicator of soil moisture. Since, the magnetic permeability of all naturally occurring soils is near that of free space, dielectric measurements serve to fully characterize the electromagnetic response of soils. Many of the indirect methods of soil moisture measurement permit frequent or continuous measurements in the same place with only small expenditure of time. Thus, changes in water content with time can be approximated. The soil impedance is sensitive to the moisture content of the soil and can be used to calculate the volumetric water content of the soil. Soil impedence techniques using probes have been demonstrated to show small-scale diurnal variations that would be completely missed by small-scale spatial variations in the gravimetric sampling scheme. Furthermore, the basically non-destructive nature of the fixed probes minimize the impact of the sampling technique on the dynamic behavior of the region under study.
Soil Thermal Conductivity Data (FIFE)
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1989 FIFE staff science soil properties measurements
Soil Hydraulic Conductivity Data (FIFE)
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Field saturated hydraulic conductivity, using constant well head permeameter
Geospatial Measurements of Soil Electrical Conductivity, Soil Salinity, and Soil Saturation Percentage in Irrigated Farmland
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,These data are from soil salinity surveys conducted on California irrigated farmland between 1991 and 2017. The data consist of: (i.) geospatial field survey measurements of bulk soil electrical conductivity (ECa) and (ii.) laboratory determinations of soil salinity (ECe) and saturation percentage (SP) made on soil core sections extracted from the surveyed fields. The data consist of 277,624 ECa measurements and 8,575 ECe and SP determinations.,Soil bulk electrical conductivity (ECa) is relatively easy to measure in agricultural fields using electromagnetic induction (EMI) instrumentation. EMI instruments are readily mobilized and thus can be used to characterize in detail the spatial variability of ECa within fields (Corwin, 2005; 2008). ECa is a useful property because it often correlates with difficult-to-measure soil physical and chemical properties that affect crop production, including soil water content, clay percentage, bulk density, PH, and especially soil salinity. The standard quantitative measure of soil salinity is defined to be the electrical conductivity of the soil saturation paste extract, or ECe (U.S. Salinity Laboratory Staff, 1954). Saturation percentage (SP) is the dry-weight moisture percentage of the saturation paste.,The data can be used to test and explore model relationships between ECe, SP, and ECa (EMv and EMh), as well as their spatial variability. In particular, the data may be useful for comparing and testing modeling approaches that account for both deterministic and random components of soil spatial variability at single-field and multi-field scales, and to support high-resolution digital soil mapping studies across irrigated lands.,Data are stored column-wise in two comma-delimited text files, ECe_USDA_ARS_USSL_v01.csv and ECa_USDA_ARS_USSL_v01.csv. Joining the files on the 'ID' column returns data for geolocations at which field measurements of ECa and laboratory determinations of ECe and SP both exist. For example:,The DATASET label in each file indicates the survey or field campaign from which the data are taken.,DATASET_1. Survey of the Broadview Water District in California performed by Corwin and co-workers in 1991 (Corwin et al, 1999). Data include: (i.) ECe and SP determinations on 1,889 soil samples (depths) from 315 soil cores (locations) and (ii.) 2613 ECa (EMv and EMh) field measurements. Data from this survey have been used previously for interpreting the spatial variability of soil salinity at the regional scale (Corwin, 2005).,DATASET_2. Survey of Coachella Valley, California farmland conducted between 2005 and 2008 and led by the Coachella Water District. Data consist of: (i.) ECe and SP determinations on 2,088 samples from 476 soil cores and (ii.) 133,037 ECa (EMv and EMh) measurements across the Coachella Valley. This dataset has been used in previous work for validating linear approaches to regional-scale ECa and ECe calibration (Corwin and Lesch, 2014).,DATASET_3. Survey led by Singh and colleagues across four fields in western San Joaquin Valley for the purpose of assessing environmental risk associated with saline drainage (Singh et al,. 2020). Data include: (i.) ECe and SP determinations on 1,080 samples from 273 soil cores and (ii.) 36,236 ECa (EMv and EMh) field measurements.,DATASET_4. Soil salinity survey led by USDA-ARS U.S. Salinity Laboratory between 2012 and 2013. The survey covered 21 fields in San Joaquin Valley, California. Data consist of: (i.) ECe and SP determinations on 1,634 samples from 180 soil cores and (ii.) 63,225 ECa (EMv and EMh) field measurements. These data were used previously for large scale soil salinity assessments and is described in detail by Scudiero et al. (2014).,DATASET_5. Data from surveys of 6 miscellaneous fields in California led by the USDA-ARS U.S. Salinity Laboratory. Data consist of: (i.) 244 determinations of ECe and SP on samples taken from 62 soil cores and (ii.) 62 corresponding ECa (EMv and EMh) field
Soil Moisture Gravimetric Data (FIFE)
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The gravimetrical soil moisture data were collected from many stations spread over the FIFE study area. These data were collected to characterize the spatial and temporal patterns of moisture content of the soils over this area during and between the FIFE Intensive Field Campaigns. The aim of the FIFE soil moisture work was to characterize spatial and temporal patterns of soil moisture at the FIFE site, to validate and calibrate remote sensing measurements of soil water, and to evaluate alternative methods of measuring soil moisture both from the air and on the ground. A further goal was to develop techniques for comparing point and spatially continuous measurements of soil moisture. The FIFE soil moisture research was designed to advance the technology for characterizing soil moisture and contribute useful data to other FIFE investigations.
Soil Water Prop. Derived Data (FIFE)
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Soil hydraulic properties
Soil Moisture Transect Data (FIFE)
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The aim of the FIFE soil moisture transect work was to characterize spatial and temporal patterns of soil moisture along selected transects at the FIFE study area. Two levels of ground data were collected to support the passive microwave (PBMR) flights over the Konza experimental area. The water content measurements were collected using gravimetric methods. Soil moisture measured along a transect is necessary to calibrate airborne moisture instruments or compare data obtained from them. Soil units in a landscape are inherently heterogeneous, which leads to variations in moisture content along an aircraft flight path on the ground. In order to reduce errors, values on the flight path were sampled at close intervals.