Remote Sensing in Hydrological Modeling

Dubayah, Ralph; Wood, Eric F.; Engman, Edwin T.; Czajkowski, Kevin; Zion, Mark S.; Rhoads, Joshua

doi:10.1007/978-3-642-59583-7_5

Cited by 5 publications

(9 citation statements)

References 51 publications

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“…Hydrological models use meteorological data derived from either ground observations or satellite data. In an initial study, Dubayah et al (1997b) used remotely sensed estimates of air temperature (from AVHRR), humidity (from AVHRR) and solar radiation (from GOES) to drive a land surface model and compared results with model uxes derived using traditional methodology based on ground data alone. The model was run on a hourly time step over a period of a month over the Red River -Arkansas River basin.…”

Section: Discussionmentioning

confidence: 99%

“…The actual diOE erence in time between the satellite observations and the corresponding ground observations is at most 30 min given hourly ground observations. The interpolated surface airways data have been used in various modelling activities (Abdulla 1995, Liang et al 1997, Dubayah et al 1997b . The list of the surface airways stations in the Red River-Arkansas River basin is given in table 1.…”

Section: Ground Observations (Surface Airways)mentioning

confidence: 99%

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Land surface air temperature mapping using TOVS and AVHRR

Lakshmi

Czajkowski

Dubayah

et al. 2001

International Journal of Remote Sensing

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Surface air temperature is an important variable in land surface hydrological studies. This paper evaluates the ability of satellites to map air temperature across large land surface areas. Algorithms recently have been developed that derive surface air temperature using observations from the TOVS (TIROS Operational Vertical Sounder) suite of instruments and also from the AVHRR (Advanced Very High Resolution Radiometer), which have own on the NOAA operational sun synchronous satellites TIROS-N NOAA-14. In this study we evaluate TOVS soundings from NOAA-10 (nominal local time of overpass 7:30 a.m./p.m.) and data from AVHRR aboard NOAA-9 (nominal local time 2:30 a.m./p.m.). Instantaneous estimates from the AVHRR and TOVS were compared with the hourly ground observations collected from 26 meteorological stations in the Red River-Arkansas River basin for a 3-month period from May to July 1987. Detailed comparisons between the satellite and ground estimates of surface air temperatures are reported and the feasibility of estimating the diurnal variation is explored. The comparisons are interpreted in the geographical context, i.e. land cover and topography, and in the seasonal context, i.e. early and midsummer. The results show that the average bias over the 3-month period compared with ground-based observations is approximately 2ß C or less for the three times of day with TOVS having lower biases than AVHRR. Knowledge of these error estimates will greatly bene t use of satellite data in hydrological modelling.

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Section: Discussionmentioning

confidence: 99%

Section: Ground Observations (Surface Airways)mentioning

confidence: 99%

Land surface air temperature mapping using TOVS and AVHRR

Lakshmi

Czajkowski

Dubayah

et al. 2001

International Journal of Remote Sensing

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“…here have been considerable advances in the estimation of land surface environmental conditions from satellite observations, particularly from thermal infrared remote sensing data (Running and Nemani 1988;Carlson et al 1994;Norman et al 1995;Prince and Goward 1995;Sun and Mahrt 1995;Andersen 1996;Susskind et al 1997). Near surface temperature and water vapor are of critical importance to the study of terrestrial hydrology (Dubayah et al 2000), biospheric processes (Prince and Goward 1995) and other Earth System Science objectives (Ehrlich et al 1994). For instance, determining the energy and water balances for hydrological modeling is dependent upon both the difference in temperature between the surface and some level in the atmosphere and the amount of water vapor in the atmosphere.…”

Section: Introductionmentioning

confidence: 99%

“…For instance, determining the energy and water balances for hydrological modeling is dependent upon both the difference in temperature between the surface and some level in the atmosphere and the amount of water vapor in the atmosphere. Remote sensing estimations of temperature and humidity can be used as input to drive models (Dubayah et al 2000) or as validation data sets of model output (Lakshmi and Susskind 1998). In comparison to ground based meteorological observations which have traditionally been used, satellites provide high spatial resolution data over large areas of the Earth.…”

Section: Introductionmentioning

confidence: 99%

Thermal Remote Sensing of Near Surface Environmental Variables: Application Over the Oklahoma Mesonet

Czajkowski

Goward

Stadler

et al. 2000

The Professional Geographer

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Many recent studies have applied satellite remote sensing data to large-scale hydrologic and biospheric modeling. It is widely accepted that the thermal infrared observations from the Advanced Very High Resolution Radiometer (AVHRR) have the potential to estimate land surface conditions, such as surface temperature, near surface air temperature, and near surface water vapor. In this study, algorithms to estimate all three variables are presented and applied to an area covering the state of Oklahoma for a six day period in August, 1994. The results were validated using ground observations from the 111 station Oklahoma Mesonet. Validation of the remote sensing algorithms with Mesonet observations produced comparable results to previous validation studies. In addition, the validation process revealed inadequacies in thermal modeling that had not been detected in previous validation studies leading to the development of a new approach to estimate atmospheric water vapor.

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“…Previous comparisons of satellite-derived surface temperatures with model predictions have shown good agreement of monthly mean temperatures [Jin et al, 1997]. However, the need and potential for satellite data, e.g., for model validation and data assimilation, is at much shorter time intervals [Dubayah et al, 2000]. This paper examines the variability in space and time of remotely sensed surface temperature from two sources, TOVS (TIROS Operational Vertical Sounder) and GOES (Geostationary Operational Environmental Satellite), as compared to modeled predictions, with emphasis on short timescales.…”

confidence: 99%

Validation of land surface models using satellite‐derived surface temperature

Rhoads¹,

Dubayah²,

Lettenmaier³

et al. 2001

J. Geophys. Res.

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Abstract. This research examines the feasibility of using remotely sensed surface temperature for validation and updating of land surface hydrologic models. Surface temperature simulated by the Variable Infiltration Capacity (VIC) hydrologic model is compared over the Arkansas-Red River basin with surface temperature retrievals from TOVS and GOES. The results show that modeled and satellite-derived surface temperatures agree well when aggregated in space or time. In particular, monthly mean temperatures agree on the pixel scale, and basin mean temperatures agree instantaneously. At the pixel scale, however, surface temperatures from both satellites were found to have higher spatial and temporal variabilities than the modeled temperatures, although the model and satellites display similar patterns of variability through space and time. The largest differences between modeled and remotely sensed surface temperature variability occur at times of maximum net radiation both diurnally and seasonally, i.e., afternoon and summer. Comparison of temporal and spatial patterns of VIC-predicted surface temperature variability with similar predictions by nine other models involved in the PILPS-2c experiment show that the VIC patterns are similar to those of the other models. Observed surface temperature and air temperature from FII•'E are used to identify possible errors in satellite-retrieved surface temperatures. The lql•E comparisons show that satellite retrieved surface temperatures likely contain errors that increase variability.

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Remote Sensing in Hydrological Modeling

Cited by 5 publications

References 51 publications

Land surface air temperature mapping using TOVS and AVHRR

Land surface air temperature mapping using TOVS and AVHRR

Thermal Remote Sensing of Near Surface Environmental Variables: Application Over the Oklahoma Mesonet

Validation of land surface models using satellite‐derived surface temperature

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