John H. Prueger

Correcting eddy-covariance flux underestimates over a grassland

Independent measurements of the major energy balance flux components are not often consistent with the principle of conservation of energy. This is referred to as a lack of closure of the surface energy balance. Most results in the literature have shown the sum of sensible and latent heat fluxes measured by eddy covariance to be less than the difference between net radiation and soil heat fluxes. This under-measurement of sensible and latent heat fluxes by eddy-covariance instruments has occurred in numerous field experiments and among many different manufacturers of instruments. Four eddy-covariance systems consisting of the same models of instruments were set up side-by-side during the Southern Great Plains 1997 Hydrology Experiment and all systems under-measured fluxes by similar amounts. One of these eddy-covariance systems was collocated with three other types of eddy-covariance systems at different sites; all of these systems under-measured the sensible and latent-heat fluxes. The net radiometers and soil heat flux plates used in conjunction with the eddy-covariance systems were calibrated independently and measurements of net radiation and soil heat flux showed little scatter for various sites. The 10% absolute uncertainty in available energy measurements was considerably smaller than the systematic closure problem in the surface energy budget, which varied from 10 to 30%. When available-energy measurement errors are known and modest, eddy-covariance measurements of sensible and latent heat fluxes should be adjusted for closure. Although the preferred method of energy balance closure is to maintain the Bowen‐ratio, the method for obtaining closure appears to be less important than assuring that eddy-covariance measurements are consistent with conservation of energy. Based on numerous measurements over a sorghum canopy, carbon dioxide fluxes, which are measured by eddy covariance, are underestimated by the same factor as eddy covariance evaporation measurements when energy balance closure is not achieved. Published by Elsevier Science B.V.

Managing Soils to Achieve Greater Water Use Efficiency

Water use efficiency (WUE) represents a given level of biomass or grain yield per unit of water used by the crop. With increasing concern about the availability of water resources in both irrigated and rainfed agriculture, there is renewed interest in trying to develop an understanding of how WUE can be improved and how farming systems can be modified to be more efficient in water use. This review and synthesis of the literature is directed toward understanding the role of soil management practices for WUE. Soil management practices affect the processes of evapotranspiration by modifying the available energy, the available water in the soil profile, or the exchange rate between the soil and the atmosphere. Plant management practices, e.g., the addition of N and P, have an indirect effect on water use through the physiological efficiency of the plant. A survey of the literature reveals a large variation in measured WUE across a range of climates, crops, and soil management practices. It is possible to increase WUE by 25 to 40% through soil management practices that involve tillage. Overall, precipitation use efficiency can be enhanced through adoption of more intensive cropping systems in semiarid environments and increased plant populations in more temperate and humid environments. Modifying nutrient management practices can increase WUE by 15 to 25%. Water use efficiency can be increased through proper management, and field-scale experiences show that these changes positively affect crop yield.

Utility of Remote Sensing-Based Two-Source Energy Balance Model under Low- and High-Vegetation Cover Conditions

Abstract Two resistance network formulations that are used in a two-source model for parameterizing soil and canopy energy exchanges are evaluated for a wide range of soybean and corn crop cover and soil moisture conditions during the Soil Moisture–Atmosphere Coupling Experiment (SMACEX). The parallel resistance formulation does not consider interaction between the soil and canopy fluxes, whereas the series resistance algorithms provide interaction via the computation of a within-air canopy temperature. Land surface temperatures were derived from high-resolution Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM) scenes and aircraft imagery. These data, along with tower-based meteorological data, provided inputs for the two-source energy balance model. Comparison of the local model output with tower-based flux observations indicated that both the parallel and series resistance formulations produced basically similar estimates with root-mean-square difference (RMSD) values ranging from approximatel...

Surface flux estimation using radiometric temperature: A dual‐temperature‐difference method to minimize measurement errors

Surface temperature serves as a key boundary condition that defines the partitioning of surface radiation into sensible and latent heat fluxes. Surface brightness temperature measurements from satellites offer the unique possibility of mapping surface heat fluxes at regional scales. Because uncertainties in satellite measurements of surface radiometric temperature arise from atmospheric corrections, surface emissivity, and instrument calibrations, a number of studies have found significant discrepancies between modeled and measured heat fluxes when using radiometric temperature. Recent research efforts have overcome these uncertainties and in addition have accounted for the difference between radiometric and aerodynamic temperature by considering soil and vegetative-canopy aerodynamic resistances. The major remaining obstacle to using satellite data for regional heat flux estimation is inadequate density of near-surface air temperature observations. In this paper we describe a simple, operational, double-difference approach for relating surface sensible heat flux to remote observations of surface brightness temperature, vegetative cover and type, and measurements of near-surface wind speed and air temperature from the synoptic weather network. A double difference of the time rate of change in radiometric and air temperature observations is related to heat flux. This double-difference approach reduces both the errors associated with deriving a radiometric temperature and with defining meteorological quantities at large scales. The scheme is simpler than other recent approaches because it requires minimal ground-based data and does not require modeling boundary layer development. The utility of this scheme is tested with ground-based radiometric temperature observations from several arid and subhumid climates with a wide range of vegetative cover and meteorological conditions.

Effects of Vegetation Clumping on Two–Source Model Estimates of Surface Energy Fluxes from an Agricultural Landscape during SMACEX

Abstract The effects of nonrandom leaf area distributions on surface flux predictions from a two-source thermal remote sensing model are investigated. The modeling framework is applied at local and regional scales over the Soil Moisture–Atmosphere Coupling Experiment (SMACEX) study area in central Iowa, an agricultural landscape that exhibits foliage organization at a variety of levels. Row-scale clumping in area corn- and soybean fields is quantified as a function of view zenith and azimuth angles using ground-based measurements of canopy architecture. The derived clumping indices are used to represent subpixel clumping in Landsat cover estimates at 30-m resolution, which are then aggregated to the 5-km scale of the regional model, reflecting field-to-field variations in vegetation amount. Consideration of vegetation clumping within the thermal model, which affects the relationship between surface temperature and leaf area inputs, significantly improves model estimates of sensible heating at both local a...

Assessment of the SMAP Passive Soil Moisture Product

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 soil moisture product for SMAP. The product provides soil moisture estimates posted on a 36 km 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 m3/m3 unbiased root-mean-square difference (ubRMSD), which approaches the SMAP mission requirement of 0.040 m3/m3.

The Soil Moisture–Atmosphere Coupling Experiment (SMACEX): Background, Hydrometeorological Conditions, and Preliminary Findings

Abstract The Soil Moisture–Atmosphere Coupling Experiment (SMACEX) was conducted in conjunction with the Soil Moisture Experiment 2002 (SMEX02) during June and July 2002 near Ames, Iowa—a corn and soybean production region. The primary objective of SMEX02 was the validation of microwave soil moisture retrieval algorithms for existing and new prototype satellite microwave sensor systems under rapidly changing crop biomass conditions. The SMACEX study was designed to provide direct measurement/remote sensing/modeling approaches for understanding the impact of spatial and temporal variability in vegetation cover, soil moisture, and other land surface states on turbulent flux exchange with the atmosphere. The unique dataset consisting of in situ and aircraft measurements of atmospheric, vegetation, and soil properties and fluxes allows for a detailed and rigorous analysis, and the validation of surface states and fluxes being diagnosed using remote sensing methods at various scales. Research results presented...

Value of Using Different Vegetative Indices to Quantify Agricultural Crop Characteristics at Different Growth Stages under Varying Management Practices

The paper investigates the value of using distinct vegetation indices to quantify and characterize agricultural crop characteristics at different growth stages. Research was conducted on four crops (corn, soybean, wheat, and canola) over eight years grown under different tillage practices and nitrogen management practices that varied rate and timing. Six different vegetation indices were found most useful, depending on crop phenology and management practices: (a) simple ratio for biomass, (b) NDVI for intercepted PAR, (c) SAVI for early stages of LAI, (d) EVI for later stages of LAI, (e) CIgreen for leaf chlorophyll, (f) NPCI for chlorophyll during later stages, and (g) PSRI to quantify plant senescence. There were differences among varieties of corn and soybean for the vegetation indices during the growing season and these differences were a function of growth stage and vegetative index. These results clearly imply the need to use multiple vegetation indices to best capture agricultural crop characteristics.

Variability in soil heat flux from a mesquite dune site

For many natural and agricultural landscapes, vegetation partially covers the ground surface, resulting in significant variations in soil heat flux between interspace areas and underneath vegetation. This is particularly apparent in arid and semiarid regions where vegetation cover is low and clustered or ‘clumped’ with large areas of exposed soil. Surface heterogeneity presents significant challenges to the use of standard micro-meteorological measurement techniques for estimating surface energy balance components. The objective of this study was to use an array of 20 soil heat flux plates and soil temperature sensors to characterize the spatial and temporal variability in soil heat flux as affected by vegetation and micro-topographic effects of mesquite dunes in the Jornada Experimental Range in southern New Mexico. Maximum differences in soil heat flux among sensors were nearly 300 W m 2 . Maximum differences among individual sensors under similar cover conditions (i.e. no cover or interdune, partial or open canopy cover and full canopy cover) were significant, reaching values of 200‐250 W m 2 . The ‘area-average’ soil heat flux from the array was compared with an estimate using three sensors from a nearby micro-meteorological station. These sensors were positioned to obtain soil heat flux estimates representative of the three main cover conditions: namely, no cover or interdune, partial or open canopy cover, and full canopy cover. Comparisons between the array-average soil heat flux and the three-sensor system indicate that maximum differences on the order of 50 to nearly 100 W m 2 are obtained in the early morning and mid-afternoon periods, respectively. These discrepancies are caused by shading from the vegetation and micro-topography. The array-derived soil heat flux also produced a significantly higher temporal varying soil heat flux/net radiation ratio than what has been observed in other studies under more uniform cover conditions. Results from this study suggest that, to determine the number and location of sensors needed for estimating area-average soil heat flux in this type of landscape, one needs to account not only for the clustering of the vegetation cover but also micro-topography. Published by Elsevier Science B.V.

Comparing Aircraft-Based Remotely Sensed Energy Balance Fluxes with Eddy Covariance Tower Data Using Heat Flux Source Area Functions

Abstract In an effort to better evaluate distributed airborne remotely sensed sensible and latent heat flux estimates, two heat flux source area (footprint) models were applied to the imagery, and their pixel weighting/integrating functionality was investigated through statistical analysis. Soil heat flux and sensible heat flux models were calibrated. The latent heat flux was determined as a residual from the energy balance equation. The resulting raster images were integrated using the 2D footprints and were compared to eddy covariance energy balance flux measurements. The results show latent heat flux estimates (adjusted for closure) with errors of (mean ± std dev) −9.2 ± 39.4 W m−2, sensible heat flux estimate errors of 9.4 ± 28.3 W m−2, net radiation error of −4.8 ± 20.7 W m−2, and soil heat flux error of −0.5 ± 24.5 W m−2. This good agreement with measured values indicates that the adopted methodology for estimating the energy balance components, using high-resolution airborne multispectral imagery, ...