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Chapter 4 Estimating spatially distributed surface fluxes in a semi-arid Great Basin desert using LandsatTM thermal data Charles A. Laymon and Dale A. Quattrochi 4.1 Introduction Ground-basedmeasurementsofhydrologicandmicrometeorologicprocesses arenowavailableformanypartsoftheworld, especiallyfortheUnitedStates and Europe, on a nearly routine basis. These measurements, however, are only representative of a very small area around the sensors, and, therefore, provide little information about regional hydrology. The variability of the land surface precludes using these measurements to make inferences about processes that occur over an area of a hectare, much less the size of an entire valley. Recent developments have demonstrated an increasing capability to estimate the spatial distribution of hydrologic surface fluxes for very large areas with remote sensing techniques. A number of studies have focused on the use of remote sensing to measure surface water and energy variables in attempts to derive latent heat flux or evapotranspiration (ET) over semi-arid regions (e.g. Kustas et al. 1989a,b, 1990, 1994a,b,d, 1995; Humes et al. 1994, 1995; Moranetal. 1994; OttléandVidal-madjar1994; Tueller1994). Alloftheseinvestigationshaveusedaircraft-basedinstrumentsandwerelim-ited to small areas. In only a few investigations has satellite-based remote sensing data been used to estimate ET. The synoptic and real-time attributes of remote sensing data from satellites offer the potential for measuring land-scape, hydrometeorological, and surface energy flux characteristics that can beusedinbothmonitoringandmodelingthestateanddynamicsofsemi-arid regions. Choudhury (1991) reviewed the current state of progress in utilizing satellite-based remote sensing data to estimate various surface energy bal-ance parameters. Kustas et al. (1994c) used Advanced Very High Resolution Radiometer (AVHRR) data to extrapolate ET estimates from one location containing near-surface meteorological data to other areas in a semi-arid basin in Arizona. Moran et al. (1989) and Moran and Jackson (1991) used Landsat Thematic Mapper (TM) data to estimate ET over a small agricul-turalarea. Inthispaper, wepresentamethodforscalingfrompointtospatial estimatesofinstantaneoussurfacefluxesforaGreatBasindesertvalleyusing Landsat TM data and for characterizing the partitioning of fluxes among the different soil and landcover types found in the study area. 134 Charles A. Laymon and Dale A. Quattrochi A field study was conducted from May 1993 through October 1994 to improve our understanding of the processes that govern the local energy and water fluxes in a Great Basin desert ecosystem. A survey of soils and vegeta-tion was conducted for the study area. Six surface water and energy balance flux stations were deployed in major plant ecosystems. These stations oper-ated nearly continuously throughout the study period, except for several of the winter months. Field work was conducted during special observ-ing periods at the peak “green-up” in the early summer of 1993 and 1994 and at “dry-down” during late summer of 1993. These periods included deployment of several eddy correlation systems, soil moisture measurements using the neutron probe and time domain reflectometry techniques, and radiosonde observations of the lower atmosphere. This research program provided an infrastructure to further study the use of remote sensing to measure surface properties and processes. 4.2 Setting The study was conducted in Goshute Valley of northeastern Nevada, a faulted graben valley of the Basin and Range Province of the western United States about 50km west of the Great Salt Lake Desert (Figure 4.1). Although the entire valley is about 75km long and 16km wide, our study was ID NV UT Great Salt Lake 1–80 Great 1–80 Goshute Valley Salt Lake Desert Salt Lake City Figure 4.1 Map showing the location of Goshute Valley (40◦44 N,114◦26 W) in northeastern Nevada in relation to state boundaries and Great Salt Lake Desert,Utah. Estimating spatially distributed surface fluxes 135 Figure 4.2 Landsat-5 TM image of the Goshute Valley, Nevada, study area showing the types and location of surface water and energy balance flux stations (BR = bowenratio,EC = eddycorrelation).Theboxdefinestheareaover which energy balance components were derived and cooresponds to the area shown in Figure 4.9(a)–(d). restricted to a 40km long central section (Figure 4.2). The valley floor, with an elevation of about 1700masl, is nearly flat with slopes of less than a few degrees. The valley is bordered by alluvial fans emanating from the mountains. A pluvial lake occupied the valley during the Late Pleistocene leaving strand lines and terraces on the alluvial fans and allowing for lacus-trine silt and clay to accumulate in the valley. Because outflow drainage was limited, dissolved weathering products from the surrounding moun-tains became concentrated in the lake producing significant amounts of soluble salts and carbonates in the lacustrine sediments. As a result, salt content and pH of the lacustrine soils in the central reaches of Goshute Valley are high. Vegetation of the valley is dominated by shrubs with some understory forbs and grasses. Land within the valley has not been heavily grazedordeveloped, althoughsmallportionsofthevalleyhavebeenchained for grazing and are easily identified by the regular geometric patterns in Figure 4.2. 136 Charles A. Laymon and Dale A. Quattrochi 4.3 Methods 4.3.1 Approach The general surface energy balance can be summarized as: Rn = H +LE +G (4.1) where Rn is net radiation absorbed at the surface, G the flux of heat into the soil, and H and LE are the sensible and latent heat fluxes into the atmo-sphere. We use the sign convention that all the radiative fluxes directed toward the surface are positive, while other (non-radiative) energy fluxes directed away from the surface are positive and vice versa. LE, a prod-uct of the rate of evaporation E and the latent heat of vaporization L, is the rate of energy utilization in ET and is often treated as a proxy for ET. Rn,G, and H can be estimated from micrometeorological measurements, or in some cases, using remote sensing techniques exclusively (Jackson et al. 1985; Clothieretal. 1986). Theremotesensingtechniques, however, usually require assumptions about surface conditions that are best measured on the ground. Remote sensing reflectance and emittance data used in conjunction with surface meteorological data can be used to estimate parameters needed to characterize Rn,G, and H, leaving LE to be defined mathematically. Our approach is to establish a one-to-one relationship between surface radiation and energy fluxes measured at points on the ground to correspond-ing reflectance and emittance values of a geolocated remote sensing image. The empirical relationships are then used to extrapolate from the point mea-surements to spatial estimates of surface fluxes. Our procedure is based on a Landsat-5 TM image of June 19, 1994. This date closely follows field observations that occurred between June 7 and June 14, 1994. Five surface energy balance flux stations were installed in Goshute Valley in May, 1993, and a sixth station was added in June, 1994 (Figure 4.2). The most northerly and southerly stations were separated by 35km. The stations were installed in different assemblages of dominant vegetation types present within the valley or in assemblages of vegetation with different plant density. Each station contained the same instrument configuration (Figure 4.3 and Table 4.1), with the exception that infrared thermometers were located at only four stations. Measurements were made every 5s and then output as 20-min averages. Malek et al. (1997) and Malek and Bingham (1997) have discussed the annual radiation and energy balance from these stations. The Bowen ratio method used to measure the surface energy balance in this experiment requires fetch. On the basis of instrument height and the wind speed measured during the hour that the TM scene was acquired, we assume that flux measurements are representative of an area within a 100m radius of each Bowen ratio station. The image was geometrically corrected to within one pixel of the true location. Thus, the station data were related Figure 4.3 Photo of a surface water and energy balance flux station deployed in Goshute Valley during the experiment. The letters correspond to the instrument descriptions inTable 4.1. Table 4.1 Instrument configuration at the surface energy balance stations Variablea Instrument Deployment Vendor a. Air temperature b. Dew point temperature c. Relative humidity d. Wind speed/direction e. Rainfall f. Net radiation g. Downwelling solar radiation h. Reflected solar radiation i. Surface temperature j. Soil temperature k. Ground heat flux Thermocouple Cooled mirror hygrometer RH Sensor Anemometer/Vane Tipping bucket Net radiometer Pyranometer Pyranometer IRThermometer Temperature probe Heat flux plate 1 and 2m above sfc Campbell Scientific 1 and 2m above sfc General Eastern Corp. 2m above sfc Campbell Scientific 10m above sfc RMYoung 6m above sfc Texas Electronics 4m above sfc REBS Fritschen 4m above sfc LI-COR 4m above sfc Epply Lab 4m above sfc Everest InterScience 2 and 6cm below Campbell Scientific sfc at three locations 2 and 8cm below Campbell Scientific sfc at three locations Note a Letters correspond to the letters in Figure 4.3. ... - tailieumienphi.vn
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