William P. Kustas

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.

Use of remote sensing for evapotranspiration monitoring over land surfaces

Abstract Monitoring evapotranspiration (ET) at large scales is important for assessing climate and anthropogenic effects on natural and agricultural ecosystems. This paper describes techniques used in evaluating ET with remote sensing, which is the only technology that can efficiently and economically provide regional and global coverage. Some of the empirical/statistical techniques have been used operationally with satellite data for computing daily ET at regional scales. The more complex numerical simulation models require detailed input parameters that may limit their application to regions containing a large database of soils and vegetation properties. Current efforts are being directed towards simplifying the parameter requirements of these models. Essentially all energy balance models rely on an estimate of the available energy (net radiation less soil heat flux). Net radiation is not easily determined from space, although progress is being made. Simplified approaches for estimating soil heat flux a...

Remote sensing in hydrology

Remote sensing provides a means of observing hydrological state variables over large areas. The ones which we will consider in this paper are land surface temperature from thermal infrared data, surface soil moisture from passive microwave data, snow cover using both visible and microwave data, water quality using visible and near-infrared data and estimating landscape surface roughness using lidar. Methods for estimating the hydrometeorlogical fluxes, evapotranspiration and snowmelt runoff, using these state variables are also described. Published by Elsevier Science Ltd.

Estimating subpixel surface temperatures and energy fluxes from the vegetation index-radiometric temperature relationship

Routine (i.e., daily to weekly) monitoring of surface energy fluxes, particularly evapotranspiration (ET), using satellite observations of radiometric surface temperature has not been feasible at high pixel resolution (i.e., ∼101–102 m) because of the low frequency in satellite coverage over the region of interest (i.e., approximately every 2 weeks). Cloud cover further reduces the number of useable observations of surface conditions resulting in high-resolution satellite imagery of a region typically being available once a month, which is not very useful for routine ET monitoring. Radiometric surface temperature observations at ∼1- to 5-km pixel resolution are available multiple times per day from several weather satellites. However, this spatial resolution is too coarse for estimating ET from individual agricultural fields or for defining variations in ET due to land cover changes. Satellite data in the visible and near-infrared wavelengths, used for computing vegetation indices, are available at resolutions an order of magnitude smaller than in the thermal-infrared, and hence provide higher resolution information on vegetation cover conditions. A number of studies have exploited the relationship between vegetation indices and radiometric surface temperature for estimating model parameters used in computing spatially distributed fluxes and available moisture. In this paper, the vegetation index–radiometric surface temperature relationship is utilized in a disaggregation procedure for estimating subpixel variation in surface temperature with aircraft imagery collected over the US Southern Great Plains. The disaggregated surface temperatures estimated by this procedure are compared to actual observations at this subpixel resolution. In addition, a remote sensing-based energy balance model is used to compare output using actual versus estimated surface temperatures over a range of pixel resolutions. From these comparisons, the utility of the surface temperature disaggregation technique appears to be most useful for estimating subpixel surface temperatures at resolutions corresponding to length scales defining agricultural field boundaries across the landscape.

Estimation of the soil heat flux/net radiation ratio from spectral data

Reliable spatial averages of surface energy balance components are difficult to obtain without an extensive hydrological measurement system. Our objective was to develop a method using remote sensing for estimating soil heat flux, one component of the surface energy balance, for a range of canopy conditions that will be applicable to regional surface energy balance studies. Net radiation (Rn) and soil heat flux (G) were measured during several days in fields of bare soil, alfalfa, and cotton at the Maricopa Agricultural Center, near Phoenix, AZ. Ground-based measurements of reflectance factors were also obtained with a multiband radiometer. Midday values of the ratio of soil heat flux and net radiation (G/Rn) were linearly related to the simple ratio and normalized difference vegetation indices. Relative to measurement errors, the estimates of G/Rn for cotton were found to be practically insensitive to changes in the value of the vegetative indices caused by spectral data collected at significantly different solar zenith and azimuth angles. Thus, multispectral data may provide a means of computing a more accurate area-averaged soil heat flux for regional energy balance studies.

Determination of sensible heat flux over sparse canopy using thermal infrared data

Surface temperatures, Ts, were estimated for a natural vegetative surface in Owens Valley, California, with infrared thermometric observations collected from an aircraft. The region is quite arid and is composed primarily of bushes (∼30%) and bare soil (∼70%). Application of the bulk transfer equation for the estimation of sensible heat, H, gave unsatisfactory values when compared to Bowen ratio and eddy correlation methods over a particular site. This was attributed to the inability with existing data to properly evaluate the resistance to heat transfer, rah. To obtain appropriate rah-values the added resistance to heat transfer, kB−1, was allowed to vary although there is both theoretical and experimental evidence that kB−1 for vegetative surfaces can be treated as constant. The present data indicate that for partial canopy cover under arid conditions kB−1 may be a function of Ts measured radiometrically. The equation determining kB−1 was simplified and tested over another arid site with good results; however, this had a limited data set (i.e., 6 data points). The dimensionless kB−1 equation is simplified for use over full canopy cover and is shown to give satisfactory estimates of H over a fully-grown wheat crop.

Spectral estimates of absorbed radiation and phytomass production in corn and soybean canopies

Abstract Numerous studies have reported a linear relation between phytomass production and absorbed photosynthetically active radiation (APAR) for a wide range of plant species. Related work has shown that APAR may be estimated from multispectral (visible and near infrared) remotely sensed observations. The combination of these two concepts may provide the basis for development of physically-based agronomic monitoring systems. These concepts are subjected to examination for two primary, mid-latitude crops; corn (Zea mays L.) and soybeans (Glycine max Merr.). Phytomass, green leaf area index (LAI), absorbed PAR, and multispectral reflectance factors of corn and soybean were measured periodically from planting to mid-grain fill in two growing seasons. As green LAI increased, the fractional APAR asymptotically approached a maximum value between 0.95 and 0.97. Fractional APAR displayed a linear relation to the normalized difference vegetation index (NDVI), which is relatively independent of species, throughout the growing seasons. However, deviations in the relation were observed between pre- and post-onset of senescence. For both corn and soybean, a linear relation between cumulative APAR and cumulative aboveground phytomass production was found. However, the rate of accumulation per unit APAR was more than twice as great for corn as for soybean. This agrees with previous reports comparing C4 grasses and C3 legumes. These results indicate that remotely sensed measurements contribute valuable information concerning energy / mass accumulation in plant canopies. However, implementation of this approach in crop monitoring will clearly require a capability to discriminate between, at least, corn and soybean. The influence of stress events, such as drought, nutrient limitations, and disease, will also require further consideration.

Evaluation of Drought Indices Based on Thermal Remote Sensing of Evapotranspiration over the Continental United States

AbstractThe reliability of standard meteorological drought indices based on measurements of precipitation is limited by the spatial distribution and quality of currently available rainfall data. Furthermore, they reflect only one component of the surface hydrologic cycle, and they cannot readily capture nonprecipitation-based moisture inputs to the land surface system (e.g., irrigation) that may temper drought impacts or variable rates of water consumption across a landscape. This study assesses the value of a new drought index based on remote sensing of evapotranspiration (ET). The evaporative stress index (ESI) quantifies anomalies in the ratio of actual to potential ET (PET), mapped using thermal band imagery from geostationary satellites. The study investigates the behavior and response time scales of the ESI through a retrospective comparison with the standardized precipitation indices and Palmer drought index suite, and with drought classifications recorded in the U.S. Drought Monitor for the 2000–0...

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...

Estimates of Evapotranspiration with a One- and Two-Layer Model of Heat Transfer over Partial Canopy Cover

Abstract One of the applications of remotely sensed surface temperature is to determine the latent heat flux (LE) or evapotranspiration (ET) from held to regional scales. A common approach has been to use surface-air temperature differences in a bulk resistance equation for estimating sensible beat flux, H, and to subsequently solve for LE as a residual in the one-dimensional energy balance equation. This approach has been successfully applied over uniform terrain with nearly full, actively transpiring vegetative cover; however, serious discrepancies between estimated and measured ET have been observed when there is partial canopy cover. In an attempt to improve the estimates of H and as a result compute more accurate values of ET over partial canopy cover, one- and two-layer resistance models are developed to account for some of the factors causing the poor agreement between computed and measured ET. The utility of these two approaches for estimating ET at the field scale is tested with remotely sensed a...