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Observing system simulation experiments were used to investigate ensemble Bayesian state-updating data assimilation of observations of leaf area index (LAI) and soil moisture (&thgr;) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kaiman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and &thgr; observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth. [ABSTRACT FROM AUTHOR]

Observations of the temporal and spatial distribution of poststorm soil moisture in open shrublands and savannas are limited, yet they are critical to understanding the interaction and feedback between moisture distribution and canopies. The objective of this analysis was to study the hydrologic impacts of precipitation pulses on the upper layer of soils under and between shrubs. The study was based on measurements of precipitation, runoff, and under- and between-shrub soil moisture over a period of 20 years (1990-2009) at a shrub-dominated site in the Walnut Gulch Experimental Watershed (WGEW) near Tombstone, Arizona. Within much of the root zone (to 30 cm depth), infiltration was not significantly different under versus between shrubs, and the under:between infiltration ratio was not related to pulse size or intensity. However, root-zone soil moisture was significantly higher between shrubs than under shrubs. The soil moisture measured at the surface (at 5 cm depth) was not consistently different under and between shrubs, but the soil moisture measured at depths of 15 and 30 cm were both significantly higher between shrubs than under shrubs. Considering mechanisms that explain the interaction between plants and soil moisture, we found no differences in infiltration, evaporative losses, and surface soil moisture in locations under and between shrubs. This led to the conclusion that lower root-zone soil moisture under shrubs was due largely to greater root density under shrubs than between shrubs. This study adds to the understanding of the impact of precipitation patterns on infiltration and soil moisture in shrub-dominated sites and the potential for vegetation change in arid and semiarid lands. [ABSTRACT FROM AUTHOR]

A multiyear comparison of two types of automated-recording, weighing bucket rain gauges was conducted using precipitation data collected at the United States Department of Agriculture, Agricultural Research Service's Walnut Gulch Experimental Watershed in southeastern Arizona. The comparison was part of the conversion of all rain gauges on the watershed from an analog-recording, mechanical-weighing rain gauge to a data logger controlled, digital-recording, electronic-weighing rain gauge with radiotelemetry. This comparison applied to nine pairs of analog and digital rain gauges that were in coincident operation during a 5-year period, 1 January 2000 to 31 December 2004. This study found that (1) high errors in event intensities may be produced when analog charts are digitized at short time intervals; (2) dual digital rain gauges recorded precipitation equivalently; (3) for several different measures of precipitation, the analog and digital data were equivalent; and (4) implications for the rainfall-runoff model, Kinematic and Erosion Runoff model (KINEROS), showed a limited but significant effect in modeled runoff due to differences between analog and digital rain gauge input precipitation intensities. This study provided a useful analysis for long-term rain gauge networks that have recently converted, or will soon convert, from analog to digital technology. Understanding these differences and similarities will benefit interpretation of the combined long-term precipitation record and provide insights into the impacts on hydrologic modeling. [ABSTRACT FROM AUTHOR]

Vegetation species cover and photographic data have been collected at multiple grass- and shrub-dominated sites in 1967, 1994, 1999, and 2005 at the U.S. Department of Agriculture Agricultural Research Service Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona. This study combines these measurements with meteorological and edaphic information, as well as historic repeat photography from the late 1880s onward and recent satellite imagery to assess vegetation change at WGEW. The results of classification and ordination of repeated transect data showed that WGEW had two main vegetation structural types, shrub dominated and grass dominated. Spatial distribution was closely linked to soil type and variations in annual and August precipitation. Other than the recent appearance of Eragrostis lehmanniana (Lehmann lovegrass) at limited sites in WGEW, little recruitment has taken place in either shrub or grass vegetation types. Effects of recent drought on both vegetation types were apparent in both transect data and enhanced vegetation index data derived from satellite imagery. Historic photos and a better understanding of WGEW geology and geomorphology supported the hypothesis that the shift from grass- to shrub-dominated vegetation occurred substantially before 1967, with considerable spatial variability. This work reaffirmed the value of maintaining long-term data sets for use in assessments of vegetation change. [ABSTRACT FROM AUTHOR]

Semiarid systems compose a significant portion of the world's terrestrial area and may play an important role in the global carbon cycle. A model was developed using the relation between surface reflectance and temperature obtained from satellite imagery to determine a Water Deficit Index (WDI) that estimated distributed plant transpiration, and by extension carbon dioxide (CO2) flux, for a point in time. Relationships were developed to scale these instantaneous flux measurements up to daytime estimates, which were then used to obtain measures of nighttime flux. Satellite images were acquired for a 5-year period (1996-2000) during which transpiration and net CO2 flux were measured for a semiarid grassland site in southeastern Arizona. Manual and automatic chamber data were also collected at the same site during the monsoon growing seasons of 2005 and 2006 and used to develop the relationship between and daytime and nighttime CO2 flux. Strong linear relationships were found between WDI-derived instantaneous and daytime net CO2 flux estimates (R2 = 0.97), and between daytime and nighttime fluxes (R2 = 0.88). These relations were used to generate maps of distributed total daily net CO2 flux. The error for the model was within the range of error inherent in the data sets used to create it and remained reasonable when used with WDI values less than 0.9. This study demonstrated that remote sensing can offer a physically based means of obtaining daily net CO2 flux in semiarid grasslands. [ABSTRACT FROM AUTHOR]

A 17 year (1990-2006) meteorological and soil hydrology database has been developed for the Walnut Gulch Experimental Watershed in southeastern Arizona. Data have been acquired at three automated weather stations, 5 soil profile trench sites, and 19 locations dispersed across the watershed colocated with recording rain gauges. Meteorological elements measured at the weather stations include air temperature, relative humidity, wind speed, wind direction, barometric pressure, solar radiation, photosynthetically active radiation, and net radiation. Soil hydrology properties measured at the weather stations, trench sites, and rain gauges include soil moisture, soil temperature, soil heat flux, and soil surface temperature. Data are available at http://www.tucson.ars.ag.gov/dap. [ABSTRACT FROM AUTHOR]

The USDA Agricultural Research Service, Southwest Watershed Research Center, Walnut Gulch Experimental Watershed (WGEW), is located in the San Pedro Valley of southeastern Arizona. It is one of the most highly instrumented semiarid experimental watersheds in the world and has one of the largest published collections of spectral imagery with coordinated ground observations. The WGEW Image and Ground Data Archive produced in 2006 (WIDGA06) is a collection of images from satellite- and aircraft-based sensors dating back to 1990 with ancillary ground-based measurements archived with each image. This report provides background information on the collection and archiving of this data set and contact information for obtaining copies of the image and data files. Many images are available in the University of Arizona, Arizona Regional Image Archive (ARIA) (http://aria.arizona.edu). Metadata are available via the U.S. Department of Agriculture, Agricultural Research Service, Southwest Watershed Research Center (SWRC) (http://www.tucson.ars.ag.gov/dap/). [ABSTRACT FROM AUTHOR]

Four approaches for deriving estimates of near-surface soil moisture from radar imagery in a semiarid, sparsely vegetated rangeland were evaluated against in situ measurements of soil moisture. The approaches were based on empirical, physical, semiempirical, and image difference techniques. The empirical approach involved simple linear regression of radar backscatter on soil moisture, while the integral equation method (IEM) model was used in both the physical and semiempirical approaches. The image difference or delta index approach is a new technique presented here for the first time. In all cases, spatial averaging to the watershed scale improved agreement with observed soil moisture. In the empirical approach, variation in radar backscatter explained 85% of the variation in observed soil moisture at the watershed scale. For the physical and best semiempirical adjustment to the physical model, the root-mean-square errors (RMSE) between modeled and observed soil moisture were 0.13 and 0.04, respectively. Practical limitations to obtaining surface roughness measurements limit IEM utility for large areas. The purely image-based delta index has significant operational advantage in soil moisture estimates for broad areas. Additionally, satellite observations of backscatter used in the delta index indicated an approximate 1:1 relationship with soil moisture that explained 91% of the variability, with RMSE = 0.03. Results showed that the delta index is scaled to the range in observed soil moisture and may provide a purely image based model. It should be tested in other watersheds to determine if it implicitly accounts for surface roughness, topography, and vegetation. These are parameters that are difficult to measure over large areas, and may influence the delta index. [ABSTRACT FROM AUTHOR]

Radiometric surface temperatures obtained from remote sensing measurements are a function of both the physical surface temperature and the effective emissivity of the surface within the band pass of the radiometric measurement. For sparsely vegetated areas, however, a sensor views significant fractions of both bare soil and various vegetation types. In this case the radiometric response of a sensor is a function of the emissivities and kinetic temperatures of various surface elements, the proportion of those surface elements within the field of view of the sensor, and the interaction of radiation emitted from the various surface components. In order to effectively utilize thermal remote sensing data to quantify energy balance components for a sparsely vegetated area, it is important to examine the typical magnitude and degree of variability of emissivity and surface temperature for such surfaces. Surface emissivity measurements and ground and low-altitude-aircraft-based surface temperature measurements (8-13 μm band pass) made in conjunction with the Monsoon '90 field experiment were used to evaluate the typical variability of those quantities during the summer rainy season in a semiarid watershed. The average value for thermal band emissivity of the exposed bare soil portions of the surface was found to be approximately 0.96; the average value measured for most of the varieties of desert shrubs present was approximately 0.99. Surface composite emissivity was estimated to be approximately 0.98 for both the grass-dominated and shrub-dominated portions of the watershed. The spatial variability of surface temperature was found to be highly dependent on the spatial scale of integration for the instantaneous field of view (IFOV) of the instrument, the spatial scale of the total area under evaluation, and the time of day. For the conditions which existed during most of the Monsoon '90 experiment, the differences in kinetic (physical) temperature between the vegetation and soil background were typically between 10° and 25°C at midday. These differences gave rise to large variations in radiometric composite surface temperatures observed with a ground-based instrument configuration which allowed a ground IFOV of approximately 0.5 m. An evaluation of the frequency distribution for these observations indicated that the variance in surface temperature observed over an intensively sampled target area (approximately 500 m×120 m) increased significantly in the early to late morning hours of a typical diurnal heating cycle. For aircraft-based composite radiometric temperature measurements at the watershed scale (with ground IFOV of approximately 40 m for each observation), much of the variability in surface temperature due to differences in soil and vegetation temperature was integrated into a single measurement; consequently, the variance between observations over the watershed was not significantly larger than those observed at length scales of 100 m. [ABSTRACT FROM AUTHOR]

A study was conducted to determine the relation between remotely sensed spectral data and measurements of vegetation-related hydrologic parameters in a semiarid rangeland in southeast Arizona. Throughout the measurement periods, ranging from June to September 1990, eight sites in the U.S. Department of Agriculture's Agricultural Research Service Walnut Gulch experimental watershed were monitored for water and energy fluxes and other meteorological and biological parameters. Corresponding spectral data were acquired with ground-based radiometers, low-altitude aircraft-mounted instruments, and Landsat thematic mapper sensors. Spectral indices were derived from measurements of surface reflectance, based on their response to variations in hydrologic parameters and sensitivity to unrelated variables, such as solar zenith angle and soil differences. A soil-adjusted vegetation index, SAVI (derived from red and NIR reflectance factors), was found to be highly correlated with the temporal changes in vegetation cover and biomass, but less successful in discriminating spatial differences in cover and biomass across the watershed. Significant relations were found between the surface-air temperature ( T s- T a) difference and measurements of soil moisture content, though the shape differed from that previously published for bare soil. The relation between daily evaporation rate and measurements of ( T s- T a) and daily net radiation was similar to that derived previously for irrigated pasture and dryland shortgrass in France but differed from that derived for irrigated wheat. These results emphasized the strengths and limitations of the use of spectral data for estimation of hydrologic characteristics of sparsely vegetated sites and suggested a need for reevaluation of common empirical relations between remotely sensed measurements and surface characteristics for application to rangeland areas. [ABSTRACT FROM AUTHOR]

An interdisciplinary field experiment was conducted to study the water and energy balance of a semiarid rangeland watershed in southeast Arizona during the summer of 1990. Two subwatersheds, one grass dominated and the other shrub dominated, were selected for intensive study with ground-based remote sensing systems and hydrometeorological instrumentation. Surface energy balance was evaluated at both sites using direct and indirect measurements of the turbulent fluxes (eddy correlation, variance, and Bowen ratio methods) and using an aerodynamic approach based on remote measurements of surface reflectance and temperature and conventional meteorological information. Estimates of net radiant flux density ( R n), derived from measurements of air temperature, incoming solar radiation, and surface temperature and radiance compared well with values measured using a net radiometer (mean absolute difference (MAD) ≃ 50 W/m2 over a range from 115 to 670 W/m2). Soil heat flux density ( G) was estimated using a relation between G/ Rn and a spectral vegetation index computed from the red and near-infrared surface reflectance. These G estimates compared well with conventional measurements of G using buried soil heat flux plates (MAD ≃ 20 W/m2 over a range from −13 to 213 W/m2). In order to account for the effects of sparse vegetation, semiempirical adjustments to the single-layer bulk aerodynamic resistance approach were required for evaluation of sensible heat flux density ( H). This yielded differences between measurements and remote estimates of H of approximately 33 W/m2 over a range from 13 to 303 W/m2. The resulting estimates of latent heat flux density, LE, were of the same magnitude and trend as measured values; however, a significant scatter was still observed: MAD ≃ 40 W/m2 over a range from 0 to 340 W/m2. Because LE was solved as a residual, there was a cumulative effect of errors associated with remote estimates of R n, G, and H. [ABSTRACT FROM AUTHOR]

A primary motivation for using remotely sensed data to estimate components of the surface energy balance is to quantify surface energy fluxes in a spatially distributed manner over various spatial scales. However, all models which utilize remotely sensed data to estimate surface fluxes also require input variables and parameters which cannot be estimated on a spatially distributed basis with remotely sensed data. In this analysis, data from the Monsoon '90 experiment were used to evaluate the limitations in spatially extending a relatively simple energy balance model with remotely sensed data over a semiarid rangeland watershed. Using one ground-based meteorological and flux station as a reference site, aircraft-based remotely sensed data (surface temperatures and reflectances) were used to compute energy balance components for seven other locations within the watershed. The results indicated that for clear sky conditions, all components of the surface energy balance could be estimated to within approximately the same level of uncertainty with which the fluxes were measured with ground-based flux instrumentation. However, under partly cloudy conditions the variability in incoming solar radiation across the watershed significantly degraded the estimation of distributed values of net radiation ( Rnet). If ground-based estimates of incoming solar radiation are used to calculate Rnet from remotely sensed data, then the spatial extent over which that measurement is valid limits the area over which accurate spatially distributed values of Rnet can be estimated. Additionally, the results of sensitivity analyses indicate that the level of uncertainty to which the roughness length for momentum, or z0 m, is typically known for spatially distributed values in an area of naturally variable vegetation can give rise to significant uncertainties in the estimation of sensible heat flux. For areas where the spatial variation in roughness parameters is of the order of several centimeters, the error associated with assuming constant values for the roughness length for momentum is similar in size to the errors associated with temperature variations of the order of several degrees. In order to utilize radiometric temperatures to reliably estimate spatially distributed values of sensible heat flux, techniques such as those explored by Menenti and Ritchie (this issue) are needed to provide spatially distributed information on surface roughness parameters. [ABSTRACT FROM AUTHOR]

Remotely sensed data in the visible, near-infrared, and thermal-infrared wave bands were collected from a low-flying aircraft during the Monsoon '90 field experiment. Monsoon '90 was a multidisciplinary experiment conducted in a semiarid watershed. It had as one of its objectives the quantification of hydrometeorological fluxes during the 'monsoon' or wet season. The remote sensing observations along with micrometeprological and atmospheric boundary layer (ABL) data were used to compute the surface energy balance over a range of spatial scales. The procedure involved averaging multiple pixels along transects flown over the meteorological and flux (METFLUX) stations. Average values of the spectral reflectance and thermal-infrared temperatures were computed for pixels of order 10−1 to 101 km in length and were used with atmospheric data for evaluating net radiation ( R n), soil heat flux ( G), and sensible ( H) and latent ( LE) heat fluxes at these same length scales. The model employs a single-layer resistance approach for estimating H that requires wind speed and air temperature in the ABL and a remotely sensed surface temperature. The values of R n and G are estimated from remote sensing information together with near-surface observations of air temperature, relative humidity, and solar radiation. Finally, LE is solved as the residual term in the surface energy balance equation. Model calculations were compared to measurements from the METFLUX network for three days having different environmental conditions. Average percent differences for the three days between model and the METFLUX estimates of the local fluxes were about 5% for R n, 20% for G and H, and 15% for LE. Larger differences occurred during partly cloudy conditions because of errors in interpreting the remote sensing data and the higher spatial and temporal variation in the energy fluxes. Minor variations in modeled energy fluxes were observed when the pixel size representing the remote sensing inputs changed from 0.2 to 2 km. Regional scale estimates of the surface energy balance using bulk ABL properties for the model parameters and input variables and the 10-km pixel data differed from the METFLUX network averages by about 4% for Rn, 10% for G and H, and 15% for LE. Model sensitivity in calculating the turbulent fluxes H and LE to possible variations in key model parameters (i.e., the roughness lengths for heat and momentum) was found to be fairly significant. Therefore the reliability of the methods for estimating key model parameters and potential errors needs further testing over different ecosystems and environmental conditions. [ABSTRACT FROM AUTHOR]