Geology topics

William P. Kustas

Publications and source records attributed to William P. Kustas.

13 recordsLinked to original sources

USGS2024

A comparative analysis of OpenET for evaluating evapotranspiration in California almond orchards

The almond industry in California faces water management challenges that are being exacerbated by droughts, climate change, and groundwater sustainability legislation. The Tree-crop Remote sensing of Evapotranspiration eXperiment (T-REX) aims to explore opportunities to improve precision irrigation management for woody perennial cropping systems. Almond orchards in the California Central Valley were equipped with eddy covariance flux measurements to evaluate satellite remote sensing-based evapotranspiration (RSET) models. OpenET provides high-resolution (30-m spatial and daily temporal) RSET data, synthesizing decades of research for practical water management. This study provides an evaluation of OpenET performance at six almond sites covering a large range in soils, age, and variety. It also compares OpenET ensemble evapotranspiration (ET) data with applied irrigation and precipitation records over an additional 148 almond orchards located in the Central Valley of California. Results show OpenET models, including the ensemble ET value, produced reasonable and actionable ET values, with overall coefficient of determination (R 2 ) and mean absolute error values of 0.73- and 0.95-mm d −1 at the daily time step, respectively. However, given the temporal sampling of Landsat (8-day revisit) and the interpolation methods used, the assessed ET models had difficulty in capturing short-term variability in almond ET; for example, the rapid decline in measured ET observed as a response to lack of irrigation preceding and during almond harvest. The study also drew attention to the spatial complexity in scenarios where irrigated orchards are surrounded by hot/dry areas, causing discrepancies between measured and modeled ET values. In comparison with irrigation records, OpenET ensemble ET was capable of quantifying water input (applied irrigation + precipitation) in almond orchards to within 13 % when evaluating monthly data. Initial results presented here reinforce the idea that RSET models, such as in OpenET, are powerful tools, yet their application requires nuanced understanding and careful consideration of local conditions.

California↗

USGS2023

Development of a benchmark eddy flux evapotranspiration dataset for evaluation of satellite-driven evapotranspiration models over the CONUS

A large sample of ground-based evapotranspiration (ET) measurements made in the United States, primarily from eddy covariance systems, were post-processed to produce a benchmark ET dataset. The dataset was produced primarily to support the intercomparison and evaluation of the OpenET satellite-based remote sensing ET (RSET) models and could also be used to evaluate ET data from other models and approaches. OpenET is a web-based service that makes field-delineated and pixel-level ET estimates from well-established RSET models readily available to water managers, agricultural producers, and the public. The benchmark dataset is composed of flux and meteorological data from a variety of providers covering native vegetation and agricultural settings. Flux footprint predictions were developed for each station and included static flux footprints developed based on average wind direction and speed, as well as dynamic hourly footprints that were generated with a physically based model of upwind source area. The two footprint prediction methods were rigorously compared to evaluate their relative spatial coverage. Data from all sources were post-processed in a consistent and reproducible manner including data handling, gap-filling, temporal aggregation, and energy balance closure correction. The resulting dataset included 243,048 daily and 5,284 monthly ET values from 194 stations, with all data falling between 1995 and 2021. We assessed average daily energy imbalance using 172 flux sites with a total of 193,021 days of data, finding that overall turbulent fluxes were understated by about 12% on average relative to available energy. Multiple linear regression analyses indicated that daily average latent energy flux may be typically understated slightly more than sensible heat flux. This dataset was developed to provide a consistent reference to support evaluation of RSET data being developed for a wide range of applications related to water accounting and water resources management at field to watershed scales.

continental United States↗

USGS2020

A within-season approach for detecting early crop stage of corn and soybean using high temporal and spatial resolution imagery

Crop emergence is a critical stage for crop development and crop growth modeling. Mapping crop emergence using remote sensing data is challenging. Previous remote sensing phenology algorithms showed that crop stages could be detected around the V3-V4 (3 to 4 established leaves) vegetative stage. Traditional approaches have a strong assumption regarding the temporal evolution of plant growth and normally require a complete growth period of observations to define seasonal changes. Most approaches were not designed for the within-season mapping in the early growing season. In the current paper, we developed a new within-season emergence (WISE) approach to mapping crop green-up date using satellite observations during early growth stages. The approach was first optimized using high spatiotemporal resolution (10 m, 2 day revisit) imagery from the Vegetation and Environment monitoring New MicroSatellite (VENµS) research mission, and assessed using ground observations of early crop growth stages (emergence VE and one leaf V1 stages for corn, and emergence VE and unifoliolate VC stages for soybeans) collected over the Beltsville Agricultural Research Center (BARC) experimental fields in Beltsville, MD during the 2019 growing season. Results show that early crop growth stages can be reliably detected at sub-field scale about two weeks after crop emergence. The remote sensing green-up dates were about 4-5 days after crop emergence on average. Coefficients of determination (R2) between green-up dates and the mid-point dates of the early growth stages were above 0.90. The mean absolute differences, standard deviations, and root mean square errors comparing to the early growth stage mid-point dates were within six days. The maximum differences were within ±10 days across all fields. The WISE approach was assessed using operational Sentinel-2 data (10 m, 5 day revisit) in BARC. The detected green-up dates from Sentinel-2 were found close to VENµS results. Some fields were not detected due to the lack of observations during emergence dates. For independent evaluation, the WISE approach was applied over an agricultural watershed on the Maryland Eastern Shore using both VENµS and the harmonized Landsat and Sentinel-2 (HLS) data (30 m, 3-4 day revisit). The green-up dates were compared with crop progress reports of crop emergence dates from the National Agricultural Statistics Service (NASS) at the state-level. The WISE -detected green-up dates at the regional scale are within VE stage ranges but slightly earlier than NASS crop progress reports at the state-level. The WISE approach uses remote sensing observations during the early crop growth stages and has potential for operational application within the season using Sentinel-2 and HLS data.

Maryland↗

USGS2017

Impact of tile drainage on evapotranspiration in South Dakota, USA, based on high spatiotemporal resolution evapotranspiration time series from a multi-satellite data fusion system

Soil drainage is a widely used agricultural practice in the midwest USA to remove excess soil water to potentially improve the crop yield. Research shows an increasing trend in baseflow and streamflow in the midwest over the last 60 years, which may be related to artificial drainage. Subsurface drainage (i.e., tile) in particular may have strongly contributed to the increase in these flows, because of its extensive use and recent gain in the popularity as a yield-enhancement practice. However, how evapotranspiration (ET) is impacted by tile drainage on a regional level is not well-documented. To explore spatial and temporal ET patterns and their relationship to tile drainage, we applied an energy balance-based multisensor data fusion method to estimate daily 30-m ET over an intensively tile-drained area in South Dakota, USA, from 2005 to 2013. Results suggest that tile drainage slightly decreases the annual cumulative ET, particularly during the early growing season. However, higher mid-season crop water use suppresses the extent of the decrease of the annual cumulative ET that might be anticipated from widespread drainage. The regional water balance analysis during the growing season demonstrates good closure, with the average residual from 2005 to 2012 as low as -3 mm. As an independent check of the simulated ET at the regional scale, the water balance analysis lends additional confidence to the study. The results of this study improve our understanding of the influence of agricultural drainage practices on regional ET, and can affect future decision making regarding tile drainage systems.

IEEE Journal of Selected Topics in Applied Earth O↗

USGS2012

Remote sensing of evapotranspiration for operational drought monitoring using principles of water and energy balance

Evapotranspiration (ET) is an important component of the hydrologic budget because it režects the exchange of mass and energy between the soil-water-vegetation system and the atmosphere. Prevailing weather conditions inžuence potential or reference ET through variables such as radiation, temperature, wind, and relativity humidity. In addition to these weather variables, actual ET (ETa) is also affected by land cover type and condition, as well as soil moisture. The dependence of ETa on land cover and soil moisture, and its direct relationship with carbon dioxide assimilation in plants, makes it an important variable for monitoring drought, crop yield, and biomass-a critical capability for decision makers interested in food security, grain markets, water allocation, and carbon sequestration (Bastiaanssen et al., 2005).

Book chapter↗

USGS2010

Interpretation of surface flux measurements in heterogeneous terrain during the Monsoon '90 experiment

A network of 9-m-tall surface flux measurement stations were deployed at eight sparsely vegetated sites during the Monsoon '90 experiment to measure net radiation, Q , soil heat flux, G , sensible heat flux, H (using eddy correlation), and latent heat flux, λ E (using the energy balance equation). At four of these sites, 2-m-tall eddy correlation systems were used to measure all four fluxes directly. Also a 2-m-tall Bowen ratio system was deployed at one site. Magnitudes of the energy balance closure ( Q + G + H + λ E ) increased as the complexity of terrain increased. The daytime Bowen ratio decreased from about 10 before the monsoon season to about 0.3 during the monsoons. Source areas of the measurements are developed and compared to scales of heterogeneity arising from the sparse vegetation and the topography. There was very good agreement among simultaneous measurements of Q with the same model sensor at different heights (representing different source areas), but poor agreement among different brands of sensors. Comparisons of simultaneous measurements of G suggest that because of the extremely small source area, extreme care in sensor deployment is necessary for accurate measurement in sparse canopies. A recently published model to estimate fetch is used to interpret measurements of H at the 2 m and 9 m heights. Three sites were characterized by undulating topography, with ridgetops separated by about 200–600 m. At these sites, sensors were located on ridgetops, and the 9-m fetch included the adjacent valley, whereas the 2-m fetch was limited to the immediate ridgetop and hillside. Before the monsoons began, vegetation was mostly dormant, the watershed was uniformly hot and dry, and the two measurements of H were in close agreement. After the monsoons began and vegetation fully matured, the 2-m measurements of H were significantly greater than the 9-m measurements, presumably because the vegetation in the valleys was denser and cooler than on the ridgetops and hillsides. At one lowland site with little topographic relief, the vegetation was more uniform, and the two measurements of H were in close agreement during peak vegetation. Values of λ E could only be compared at two sites, but the 9-m values were greater than the 2-m values, suggesting λ E from the dense vegetation in the valleys was greater than elsewhere.

Water Environment Research↗

USGS2010

Surface energy balance estimates at local and regional scales using optical remote sensing from an aircraft platform and atmospheric data collected over semiarid rangelands

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 10 1 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 R n , 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.

Water Resources Research↗

USGS2010

Use of ground-based remotely sensed data for surface energy balance evaluation of a semiarid rangeland

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/m 2 over a range from 115 to 670 W/m 2 ). Soil heat flux density ( G ) was estimated using a relation between G / R n 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/m 2 over a range from −13 to 213 W/m 2 ). 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/m 2 over a range from 13 to 303 W/m 2 . 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/m 2 over a range from 0 to 340 W/m 2 . Because LE was solved as a residual, there was a cumulative effect of errors associated with remote estimates of R n , G , and H .

Water Resources Research↗

USGS2010

Local energy flux estimates for unstable conditions using variance data in semiarid rangelands

A network of meteorological stations was installed during the Monsoon '90 field campaign in the Walnut Gulch experimental watershed. The study area has a fairly complex surface. The vegetation cover is heterogeneous and sparse, and the terrain is mildly hilly, but dissected by ephemeral channels. Besides measurement of some of the standard weather data such as wind speed, air temperature, and solar radiation, these sites also contained instruments for estimating the local surface energy balance. The approach utilized measurements of net radiation ( R n ), soil heat flux ( G ) and Monin-Obukhov similarity theory applied to first- and second-order turbulent statistics of wind speed and temperature for determining the sensible heat flux ( H ). The latent heat flux ( LE ) was solved as a residual in the surface energy balance equation, namely, LE = −( R n + G + H ). This procedure (VAR-RESID) for estimating the energy fluxes satisfied monetary constraints and the requirement for low maintenance and continued operation through the harsh environmental conditions experienced in semiarid regions. Comparison of energy fluxes using this approach with more traditional eddy correlation techniques showed differences were within 20% under unstable conditions. Similar variability in flux estimates over the study area was present in the eddy correlation data. Hence, estimates of H and LE using the VAR-RESID approach under unstable conditions were considered satisfactory. Also, with second-order statistics of vertical velocity collected at several sites, the local momentum roughness length was estimated. This is an important parameter used in modeling the turbulent transfer of momentum and sensible heat fluxes across the surface-atmosphere interface.

Water Resources Research↗

USGS1996

Variability in surface energy flux partitioning during Washita '92: Resulting effects on Penman-Monteith and Priestley-Taylor parameters

During the Washita '92 field experiment, the local surface energy balance was evaluated at four locations in the USDA-ARS Little Washita River Watershed near Chickasha, OK, using the Bowen ratio-energy balance (BREB) approach. For any given day, differences in the partitioning of the available energy appeared to be mostly a function of the type of vegetation at the site, while the actual magnitude of the fluxes was mostly affected by cloud cover. The soil surface was initially wet, and gradually dried during the field experiment. However, there was not a corresponding decrease in the evaporative fraction, which would have indicated a decreasing contribution of soil evaporation to the total latent heat flux. Ground weather data indicated a large shift in the direction and magnitude of the surface winds, and a significant increase in air temperature and vapor pressure deficit. During this period, the evaporative fraction actually increased at two of the four sites. The response of the different sites to the changing near-surface atmospheric conditions was studied in more detail by evaluating the canopy resistance ( r c ) to evaporation using the Penman-Monteith equation and the Priestley-Taylor parameter (α). Midday averages of ( r c ) and (α) tended to decrease (increase) with increasing vapor pressure deficit for two of the sites while such a trend was not evident for the other two sites. Estimates of stomatal resistances indicated that significant plant physiological differences existed between the sites containing weedy vegetation versus the grasses at the pasture/rangeland sites. Even though soil moisture conditions were relatively wet, a was less than 1 at all sites and there was no trend in α as a function of surface soil moisture conditions. These findings suggest that vegetation types C in mixed agricultural /rangeland ecosystems can have significantly different responses to similar atmospheric forcing conditions.

Agricultural and Forest Meteorology↗

USGS1990

Spectral estimates of net radiation and soil heat flux

Conventional methods of measuring surface energy balance are point measurements and represent only a small area. Remote sensing offers a potential means of measuring outgoing fluxes over large areas at the spatial resolution of the sensor. The objective of this study was to estimate net radiation (R n ) and soil heat flux (G) using remotely sensed multispectral data acquired from an aircraft over large agricultural fields. Ground-based instruments measured R n and G at nine locations along the flight lines. Incoming fluxes were also measured by ground-based instruments. Outgoing fluxes were estimated using remotely sensed data. Remote R n , estimated as the algebraic sum of incoming and outgoing fluxes, slightly underestimated R n measured by the ground-based net radiometers. The mean absolute errors for remote R n minus measured R n were less than 7%. Remote G, estimated as a function of a spectral vegetation index and remote R n , slightly overestimated measured G; however, the mean absolute error for remote G was 13%. Some of the differences between measured and remote values of R n and G are associated with differences in instrument designs and measurement techniques. The root mean square error for available energy (R n - G) was 12%. Thus, methods using both ground-based and remotely sensed data can provide reliable estimates of the available energy which can be partitioned into sensible and latent heat under nonadvective conditions.

Remote Sensing of Environment↗

USGS1990

Instantaneous and daily values of the surface energy balance over agricultural fields using remote sensing and a reference field in an arid environment

Remotely sensed surface temperature and reflectance in the visible and near infrared wavebands along with ancilliary meteorological data provide the capability of computing three of the four surface energy balance components (i.e., net radiation, soil heat flux, and sensible heat flux) at different spatial and temporal scales. As a result, under nonadvective conditions, this enables the estimation of the remaining term (i.e., the latent heat flux). One of the practical applications with this approach is to produce evapotranspiration (ET) maps for agricultural regions which consist of an array of fields containing different crops at varying stages of growth and soil moisture conditions. Such a situation exists in the semiarid southwest at the University of Arizona Maricopa Agricultural Center, south of Phoenix. For one day (14 June 1987), surface temperature and reflectance measurements from an aircraft 150 m above ground level (agl) were acquired over fields from zero to nearly full cover at four times between 1000 MST and 1130 MST. The diurnal pattern of the surface energy balance was measured over four fields, which included alfalfa at 60% cover, furrowed cotton at 20% and 30% cover, and partially plowed what stubble. Instantaneous and daily values of ET were estimated for a representative area around each flux site with an energy balance model that relies on a reference ET. This reference value was determined with remotely sensed data and several meteorological inputs. The reference ET was adjusted to account for the different surface conditions in the other fields using only remotely sensed variables. A comparison with the flux measurements suggests the model has difficulties with partial canopy conditions, especially related to the estimation of the sensible heat flux. The resulting errors for instantaneous ET were on the order of 100 W m −2 and for daily values of order 2 mm day −1 . These findings suggest future research should involve development of methods to account for the variability of meteorological parameters brought about by changes in surface conditions and improvements in the modeling of sensible heat transfer across the surface—atmosphere interface for partial canopy conditions using remote sensing information.

Remote Sensing of Environment↗

USGS1989

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

Surface temperatures, T s , 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, r ah . To obtain appropriate r ah -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 T s 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.

Agricultural and Forest Meteorology↗