WORLD METEOROLOGICAL ORGANIZATION OPERATIONAL HYDROLOGY REPORT No. 39
APPLICATIONS OF REMOTE SENSING BY SATELLITE, RADAR AND OTHER METHODS TO HYDROLOGY
ByA.Rango
I WMO-No. 804 1
Secretariat ofthe World Meteorological Organization - Geneva - Switzerland 1994 © 1994, World Meteorological Organization
ISBN: 92-63-10804-8
NOTE
The designations employed and the presentation of material in this publication do not imply the expression of any opinion whatsoever on the part of the Secretariat of the World Meteorological Organization concerning the legal status of any country, territory, city or area, or ofits authorities, or concerning the delimitation of its frontiers or boundaries. CONTENTS
Page
Foreword ", ...... vii
Acknowledgements ...... viii
Summary (English, French, Russian and Spanish) ...... ix
List of acronyms .•...... ,...... x
1. INTRODUCTION . 1 References . 1
2. TECHNICAL AND ECONOMfC ASPECTS . 2 2.1 Requirements and capabilities . 2 2.2 Future satellite capabilities ...... •...... 2 2.3 Economic considerations , . 2 References , . 2
3. PRECIPITATION . 3 3.1 Ground-based radars . 3 3.2 Visibie and thermal infrared satellite imagery . 3 3.3 Satellite microwave radiometry , . 3 3.4 Satellite radar techniques . 3 References , , . 4
4. SOIL MOISTURE AND GROUNDWATER ,. S 4.1 Soil moisture , ,. 5 4.2 ·Groundwater , . 7 References , , . 7
S. EVAPOTRANSPIRATION . 9 S.l Overview of remote sensing models for evaluating ET . 9 S.U Semi~empirical methods ,, . 9 S.1.2 Anaiytic approach . 10 S.l.3 Numerical models ,.. 10 S.2 Unresolved issues for evaluating ET with remote sensing , . 10 S.2.1 Atmospheric corrections , . 10 S.2.2 Non-uniform studies ,, . 10 S.2.3 Regional ET . 10 References , , , . 10
6. SNOW . 13 6.1 Hydrological applications of using remote sensfng to map snow covered areas . 13 6.2 Remote sensing methods for estimates of snow accumulation , . 14 6.2.1 Aeriai gamma ray spectrometry .. 14 6.2.2 Visible and near infrared radiation , , ,. 14 6.2.3 Combination of visible satellite and aerial gamma ray data .. " , .. 14 6.2.4 Microwave radiation , ,.. , ,.. , . 14 References ,.. , ' . 15
7. ICE ON LAND 17 7.1 Remote sensing of glaciers 17 7.1.1 Glacier mass balance assessment ., ,,, ,... 17 7.1.1.1 Glacier facies studies using TM data ...... 17 7.1.2 Globai alias of giaciers 17 7.2 Lake and river Ice . 18 7.2.1 Lake ice 18 7.2.2 River ice 18 References ,, ,.... 19 z CONTENTS
Page
8. SURFACE WATER 20 8.1 Measurements...... 20 8.1.1 Water surface area...... 20 8.1.2 Water stage/level 20 8.1.3 Water depth 20 8.1.4 Temperature ,' ...... 20 8.1.5 Salinity and mineralization 20 8.1.6 Pollutants 20 8.1.6.1 Suspended sediments 21 8.1.6.2 Chlorophyll 21 8.1.6.3 Other pollutants ,...... 21 8.1.6.4 Vegetation above water surface , ,...... 21 References 21
9. BASIN CHARACTERISTICS . 23 9.1 Basin characteristics and inventory methods . 23 9.2 Land use information , , . 24 9.3 Other spectral applications , '. 25 9.3.1 Thermal infrared data . 25 9.3.2 Microwave data , , . 25 9.4 Geographic information systems ...... •...... 25 References . 25
10, REMOTE SENSING INPUTS FOR HYDROLOGICAL MODELS .. 27 10.1 Basin characteristics , , . 27 10.1.1 Watershed geometry . 27 10.1.2 Empirical relationships . 27 10.2 Land cover . 27 10.3 Rainfall . 27 10.4 Snowmelt runoff ...... •.. 27 References . 28
11. OPERATIONAL APPLICATIONS . 29 References ~ . 29
12. GAPS IN KNOWLEDGE BASE ...... •...... 30 References . 30
13. FUTURE TRENDS . 32 13.1 Forthcoming sensors and systems . 32 13.2 Planned Earth observing systems into the 21st century . 32 13.2.1 New· sensors . 32 13.2.2 Employment of new remote sensing data .. 32 13.2.3 Model approaches to use real-time areal data .. 32 13.3 Development of hydrological models . 32 13.3.1 New model structure to use remote sensing data .. 33 13.4 Science development related to remote sensing and hydrology advances . 33 13.4.1 Global atmospheric modelling .. 33 References . 33 FOREWORD
Remote sensing methods are steadily making the transition from research to operational applications in the science of hydrology. The WMO Commission for Hydrology, at its eighth session in 1988, recognizing the need to keep Members abreast of the new developments in this field, appointed Mr A. Rango, USA, as its Rapporteur on Remote Sensing for Hydrological Purposes. The Commission entrusted him with the task of preparing a report on "applications of remote sensing by satellite, radar and other methods to hydrology in the light of recent developments". To complete this task, Mr Rango formed a Rapporteur Advisory Group of experts to assist him in putting the report together. Members of this group who contributed spedfic parts ofthe report were: Messrs T. Engman, J. Foster, T. Jackson, W. Kuslas, J. Ritchie, and Ms D. Hall (USA); Messrs R. Kuittinen (Finland), J. Martinec (Switzerland) and A. Shutko (Russian Federation). The report was recommended for publication by the Commission at its ninth session in 1993. It is with great pleasure that I express WMO's gratitude to Mr Rango and to each of the experts in his Rapporteur Advisory Group for the time and effort they have devoted to the preparation of this valuable publication.
.~..-:::.-I--- G.O.P. Obasi Secretary-Generai ACKNOWLEDGEMENTS
The author truly appreciates the efforts of the Rapporteur Advisory Group (RAG) that was formed to assist in putting this report together. Each member of RAG submitted sections of the report and reviewed parts of the entire report. The RAG consisted of Dr. Ted Engman (NASA), Mr. James Foster (NASA), Dr. Dorothy Hall (NASA), Dr. Thomas Jackson (USDA), Dr. Risto Kuittinen (Finnish Geodetic Institute), Dr. William Kustas (USDA), Dr. Jaroslav Martinec (Davos, Switzerland), Dr. Jerry Ritchie (USDA), and Dr. Anatolij Shutko (Academy of Sciences, Russian Federation). Without their dedicated help, the report would not have been possible. SUMMARY
This report provides information on the most recent on land, and surface water. Physiographic drainage basin advances in applications of remote sensing to hydrology parameters which are measurable from space and basin and water resources management. land use inventories are discussed in Chapter 9, while It consists of 13 chapters. The flrst chapter intro remote sensing inputs for hydrological models are covered duces the report and makes reference to existing in Chapter 10. For a remote sensing application to be documentation in this field. Chapter 2 is devoted to tech considered operational! several conditions must be met. nical and economic aspects of remote sensing, including These are discussed in Chapter 11. The two flnal chapters satellite capabilities for meeting hydrological requirements. provide information on topics requiring additional Chapters 3 to 8 discuss, respectively, applications for esti research and on relevant planned satellite sensors and mating amounts of precipitation, soil moisture and Earth observing systems into the 21st century. The report groundwater, evapotranspiration, snow accumulation, ice also provides extensive references for each of the chapters.
RESUME
Ce rapport naus renseigne sur les applications les plus recentes de des parametres physiographiques des bassins versants la teIedetection al'hydrologie et ala gestion des ressources en eau. mesurables 11 partir de l!espace et de II affectation des sols 11 nest divise en 13 chapitres. RedigI' sous forme differentes utiUsation dans les bassins, tandis que Ie chapitre 10 d'introductioll, Ie premier chapitre renvoie ala documentation recense les donnees de teledetection necessaires a retablisse~ existant dans ce domaine. Le chapitre 2 est consaere aUK ment de modeles hydrologiques. Le chapi!re 11 precise ies aspects techniques et economiques de la teledetection par satel conditions qui doivent etre remplies pour qu'une application lite/ notamment ala fal;on dont elle peut fl2pondre aux besoins de Ia teledetection soit consideree comme operationnelle. Les de I'hydrologie. Les chapitres 3 a8 portent sur les applications deux derniers chapitres, quant 11 eux, abordent des sujets qui de la teledetection al'estimation/ dans I'ordre/ du volume des necessitent des recherches supplementaires ainsi que la ques precipitations, de l'humidite du sol et des eaux souterraines/ de tion des detecteurs et les systemes d!observation de la Terre par l'evapotranspiratian/ de Ia hauteur de neige, de la cauche de satellite du vingt et unieme siecIe. Chacun des chapitres glace continentale et des eaux de surface. Le chapitre 9 traite renvoit 11 de nombreux ouvrages de reference.
PEillOME
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RESUMEN
Este informe proporciona informacion sobre los avances mas fide. En el Capitulo 9 se analizan los parametros de las cuencas recientes en las aplicaciones de la detecd6n a la gesti6n de Ia hidrograticas mensurables dcsde el espacia e inventarios sobre hidrolagia y los recursos hidricos. la utilizaci6n de la tierra en las cuencas, en tanto que en el Consta de 13 capitulos. En el primero se presenta el Capitulo 10 se examinan las aportaciones de la teledetecci6n informe y se hace referenda a la docnmentaci6n existente en para modelos hidrol6gicos. Para que pueda considerarse oper este campo. El Capitulo 2 se consagra a los aspectos tecnicos ativa una aplicaci6n de teledetecci6n han de darse varias y econ6micos de la teledetecci6n/ incluidas las capacidades de condiciones, que se describen en el Capitulo 11. En los dos satelite para atender necesidades hidrol6gicas. En los ultimos capitulos se facilita informaci6n sobre temas que Capitulos 3 a 8 se trata, respectivamente/ de las aplicaciones requieren investigaci6n adicional y sabre sensores y sistemas de para estimar la importancia de las precipitaciones, la humedad observaci6n de Ia tierra par satelite previstos hasta en el del suelo y el agua subterranea, la evapotranspiraci6n, la siglo XXI. El informe ofrece ademas amplias referencias sabre acumulaci6n de nieve, el hiclo sobre la tierra, y agua de super- cada uno de los capitulos. LIST OF ACRONYMS
ALMAZ Newest Russian remote sensing satellite, means {'diamond" ARS USDA Agricultural Research Service ASVT Applications Systems Verification Test AVHRR Advanced Very High Resolution Radiometer BATS Biosphere-Atmosphere Transfer Scheme CRREL US Army Cold Regions Research and Engineering Laboratory CZCS Coastal Zone Colour Scanner DMSP Defense Meteorological Satellite Program £OS Earth Observing System ERS-l First ESA Remote Sensing Satellite ESA European Space Agency ESMR Electrically Scanned Microwave Radiometer FIFE First ISLSCP Field Experiment GIS Geographic Information System GMS Geostationary Meteorological Satellite GOES Geostationary Operational Environmental Satellites GPS Global Positioning System HAPEX-MOBILIHY Hydrologic Atmospheric Pilot Experiment - Modelisation du Bilan Hydrique IAHS International Association of Hydrological Sciences IEEE Institute -of Electrical and Electronics Engineers IGARSS International Geoscience and Remote Sensing Symposium IHP International Hydrological Programme ISLSCP International Satellite Land Surface Climatology Project JERS-l First Japan Earth Resources Satellite MET£OSAT £SA Meteorology Satellite MIR Russian orbital space station capable of supporting Earth observation remote sensing modules MODIS Moderate Resolution Imaging Spectrometer MOS Marine Observation Satellite MSS Multispectral Scanner Subsystem NASA National Aeronautics and Space Administration NCAR National Center for Atmospheric Research NOAA National Oceanographic and Atmospheric AdmInistration RBV Return Beam Vision SAR Synthetic Aperture Radar SCS USDA Soil Conservation Service SMMR Scanning Multispectral Microwave Radiometer SMR Satellite Microwave Radiometry SPOT Satellite Probatoire d'Observation de Ia Terre SRM Snowmelt Runoff Model SSM/I Special Sensor Microwave/!mager TM Thematic Mapper TRMM Tropical Rainfall Measuring Mission USGS United States Geological Survey UNESCO United Nations Educational, Scientific and Cultural Organization US United States USA United States of America USDA United States Department of Agriculture VHRR Very High Resolution Radiometer WMO World Meteorological OrganIzation CHAPTER 1
INTRODUCTION
The purpose of this report is to provide information on the some of the advances will not be mentioned. It is a posi most recent advances in the applications ofremote sensing to tive sign that there are now enough remote sensing hydrology. In recent years, a number of reports and books applications that some had to be left out. The number of have been published that provide excellent documentation of applications continues to grow. how remote sensing can be used effectively in hydrology and water resources. These documents include the WMO reports References Remote sensing for hydrology - Progress and prospects Engman, E. and Gurney, R., 1991. Remote Sensing in (Kuittinen, 1992), and Application of Satellite Data for Hydrology, Chapman and Hall, London, 225 pp. Estimation of Precipitation (Kuittinen, 1989), UNESCO Kuittinen, R., 1992. Remote sensing for hydrology, Progress Technical Document on Advances in Remote Sensing for and prospects, Operational Hydrology Report No. 36, Hydrology and Water Resources Management (Schultz and WMO-No. 773, World Meteorological Organization, Barrett, 1989), and textbooks like Remote Sensing in Geneva! Switzerland. Hydroiogy (Engman and Gurney, 1991) and Microwave Kuiltinen, R., 1989. Application of satellite data for estimation Radiometry of Water Surface and Grounds (Shutko, 1986). of precipitation} Technical Report to the Commission This document is not intended to duplicate the existing infor for Hydrology No. 26, WMO/TD - No. 300, World mation. It will attempt to update or add to the available Meteorological Organization} Geneva, Switzerland. information, especially that in the above WMO reports, and Schultz, G.A. and Barrett, E.C.) 1989. Advances in remote sens~ includes some new sections, such as information on recent ing for hydrology and water resources management) operational applications ofnote and an assessment of gaps in UNESCO, Technical Documents in Hydrology, IHP-lll our knowledge base. Project 5.1, Paris, 102 pp. In assembling the information for this document, Shutko, A.M., 1986. Microwave Radiometry of Water Surface numerous research accomplishments and operational and Grounds, Nauka/Science PublishingHollse, applications were considered. Because of space constraints} Moscow, 190 pp. CHAPTER 2
TECHNICAL AND ECONOMIC ASPECTS
2.1 Requirements and capabilities icant amount of conventional ground information to duplicate the spatial detail available in the remote sensing The suitability of remote sensing to satisfy certain hydro data. For example, Cooley and Rango (1991) found that in logical needs can be assessed by comparing observational order to define the snowpack area mapped in a simple requirements with remote sensing capabilities. The reports aerial photograph, conventional point measurements had by Kuittinen (1992) and Schultz and Barrett (1989) include to be made every 90m in rugged terrain. Although ground very detailed tables covering these topics. The observa measurements can define the area of the snowpack, it is tional hydrological requirements have not changed since very costly, and sometimes dangerous, to acquire them. In their publication, so Table IB (Appendix 1) of Kuittinen addition to the cost savings, remote sensing may be the (1992) and Table 8 of Schultz and Barrett (1989) can be only way to acquire needed information, especially over used as is. Because of a lull in new .spacecraft launches large and remote areas. since 1989, the details of the relevant remote sensors Kuittinen (1992) presents the relative costs of presented in Appendix 2 of Kuitlinen (1992) and Table 1 of remote sensing digital data for currently available acquisi Schultz and Barrett (1989) are also still relevant. tion techniques in his Table- 2. Because conventional existing measurement networks are very sparse, as shown 2.2 Future satellite capabilities by Kuittinen (1992) in his Table 3, the potential for the In the planning for future satellite sensors that will be cost effective use of remote sensing data is high. In available. in the next decade and early part of the 21st Kuittinen's (1992) Table 3, it is interesting to note that the century, there appears to be a commitment to both long most sparse data networks are in arid and polar zones. Not term and concurrent multisensor observations. Much of only would remote sensing cost savings be greatest in these this emphasis has resulted from the realization that global areas, but research results have also shown that remote environmental change problems are-no longer in the sensing techniques are most effective in them because of distant future but are rather immediate problems. minimal vegetation cover. Tables 9 and 11 and Appendices I-III in Schultz and Barretl (1989) and Table 1 in NPO Energija (1990) References provide detailed information about future satellite sensors. Castruccio, P., Loats, H., Lloyd, D., and Newman, P. 1981. In the final section of this report on future trends, the Cost/benefit analysis for the ASVT on operational most recent information regarding satellites and large-scale applications of satellite snow-cover observations, programmes with relevance to hydrology is discussed. Applications Systems Verification and Transfer Project, Volume VII, NASA Technicai Paper 1828, 2.3 Economic considerations Greenbelt, Maryland, 240 pp. The expense associated with purchasing satellite data Cooley, K.R. and Rango, A., 1991. Effects of sampling density seems at first glance to be high. Upon close inspection, on estimations of snowpack characteristics, the cost is very low compared with acquiring the same Proceedings of the S9th Annual Western Snow spatial information using conventional means. Several Conference, Juneau, Aiaska, pp. 109-118. demonstration projects that ended in the 1980s attempted Kuittinen, R., 1992. Remote sensing for hydrology, Progress to assess cost effectiveness and in some cases benefit/cost and prospects, Operational Hydrology Report No. ratios. Landsat land cover data were used as input to 36, WMO-No. 773, World Meteorological hydrological models for generation of discharge frequency Organization, Geneva, Switzerland. curves for planning purposes and produced the same NPO Energija, 1990. Orbital station MIR, complex of remote results as conventional data (Rango et aI., 1983). The sensing of the Earth "Priroda", IRE AS USSR, studies, done on several basins, showed that the Landsat Interkosmos, Glavkosmos, Moscow, 14 pp. costs of obtaining the land cover data were about 3S per Rango, A., Feldman, A., George, T., and Ragan, R., 1983. cent of the conventional methods costs (Rango et aI., Effective use of Landsat data in hydrologic models, 1983). In a similar project involving remote sensing input Water Resources Bulletin, 19(2), pp. 165-174. to snowmelt runoff forecasting, a benefit/cost ratio of 75:1 Schultz, G.A. and Barrett, E.C., 1989. Advances in remote was estimated (Castruccio et aI., 1981). sensing for hydrology and water resources manage The reason for the significant cost savings and ment, UNESCO, Technical Documents in Hydrology, high benefit/cost ratio involve the need to acquire a signif- IHP-III Project S.I, Paris, 102 pp. CHAPTER 3 PRECIPITATION
Because it is a major driving force in the hydrological cycle, tering. In the absorption regime} one observes rainfall precipitation is a prime candidate variable for remote sensing through the enhanced emission associated with liquid measurement. There are many remote sensing possibilities raindrops against a cold background. The technique is including ground-based radar, visible and thermal Infrared only applicable over the highly reflective surface of the satellite imagery, and microwave satellite data. ocean. For hydrology, this would have application only in coastal areas where storms move in over nearby drainage 3.1 Ground-based radars basins. This rather direct physical reiationship between Ground-based radar is conceptually similar to spaceborne the rainfall rate and observed microwave radiances can radar except that the radar is stationary and its area of actually be derived from basic physical properties. Wilheit measurement is limited to a circle with a radius up to et al. (1977) reported such a relationship between the about 130 km (Kuittinen, 1992). A recording rain gauge is microwave radiances and the rainfall information over the desirable for calibration. Thus, the rain rate, R} can be esti oceans. Rao et al. (1976) used the Nimbus-S ESMR data to mated according to: produce a global rain atlas. In the scattering regime, on the other hand, rainfall Z=aRb (1) is observed through enhanced microwave scattering within where Z is the measured radar reflectivity and a and bare the rain column. This process proVides a rainfall signal over calibration parameters. any background surface. Because the scattering is primarily With ground-based radar there are two basic due to frozen hydrometers} the relationship to rainfall rate is approaches used quantitatively to estimate precipitation less direct than in the absorption regime and must be estab (Dalstrom 1985): lished empirically or through the use of cloud models. 1. Single-parameter measurement - this uses either Spencer et al. (1988) have described the utility of the scattering the backscattered radiation which is related to signai in Identifying rain areas using SSM!1 data. Adler et al. precipit~tion intensity or the attenuation rate (1989) reported a cloud model based algorithm to retrieve which is related to the precipitation rate} and rainfall rates from SSM!1 86 and 37 GHz data. 2. Multiparameter measurement - here multiwave Microwave radiometry provides a measurement of length radar backscatter is related to the the instantaneous rainfall rate whereas the quantity precipitation rate with the dual-polarization desired for climatological purposes is an integrated rainfall capabilities being used to give information on the over some time period. Therefore} it is necessary for any drop size distribution (DSD). remote LaWall measurement schem_e to -deal with the The use of ground-based radars has been success sampling problem and associated uncertainties. This can ful} especially when used with an integrated raingauge be approached statistically with a properly designed network and in areas with low relief. It is esti-mated that measurement strategy. Several investigators have devel the radar rainfall measurements are accurate to within oped procedures for obtaining precipitation amounts over about IS per cent of actual raingauge network totals land and ocean from the SMMR instrument. Utilizing the (Goldhirsh et aI., 1987). However, much research is still newly collected SSM/! data, Chang and Wilheit (1988) required to determine optimal merging techniques to reported a preliminary monthly rainfall index over oceans combine the radar and raingauge data. More difficulties retrieved by a statistical method. Over land, several algo are experienced in basins with mountainous terrain. rithms are now being developed. Adler et al. (1989) reported a preliminary algorithm to retrieve precipitation 3.2 Visible and thermal infrared satellite over land and ocean using the scattering signal. The indi imagery rect nature of this approach and the need to estimate the Visible and thermal infrared techniques using measure effect of environmental conditions requires careful testing ments of cloud top reflectance and temperatures have been before finalizing the scattering~basedalgorithms. used in a variety of ways by meteorologists and other The utilization of radiometry data from space for scientists to estimate monthly, daily, and storm precipita precipitation estimation is still very much in the research tion totals (Barrett, 1970; Follansbee, 1973; Griffith et aI., stage, but the idea that the microwave signal is attenuated 1978; Griffith, 1987; Scofield and Oliver, 1977; Scofield, by the precipitation particles seems to have an advantage 1987; and Shih, 1989). The greatest success so far has been over the more indirect visible and thermal infrared tech in the tropics and in countries not possessing detailed niques. In addition to actually measuring the rain falling} ground raingauge networks. Kuittinen (1989) provides a the microwave radiometry approach can be used to basic documentation of how various visible and thermal monitor radiation emitted by the soil to infer rainfall totals infrared methods are used. (Camillo and Schmugge, 1984), 3.3 Satellite microwave radiometry 3.4 Satellite radar techniques Visible and thermal infrared data provide only an indirect This approach is in its infancy even more so than satellite estimate of rain ratej however, microwave observations are microwave radiometry. Spaceborne radar differs from directly related to the hydrometers} and therefore represent ground-based radar approaches primarily by power and a great potential for improving satellite precipitation deter antenna size restrictions. mination. The physics of passive microwave rain The reflectivity to rainfall (Z-R) relations generally measurements fall into two regimes: absorption and scat- require non-attenuating wavelengths (>5 em), although at 4 CHAPTER 3 shorter wavelengths} lighter rain rates can be detected. Goldhirsh, J., Rowland, J., and Musiani, B., 1987. Rain Because the longer wavelengths require antenna dimensions measurement results derived from a two-polariza larger than currently possible to achieve adequate resolution tion frequency-diversity S-band radar at Wallops from space, a compromise wavelength of about 2.16 em is Island, Virginia, IEEE Transactions on Geoscience being proposed for the TRMM radar. At the moment much and Remote Sensing, GE-25(6), pp. 654-661. effort is directed toward algorithm development. Griffith, e.G., 1987. Comparison of gauge and satellite rain One problem we have had in this area of applica estimates for the central United States during August tion is that most of the investigators have been 1979, JOllmal of Geophysical Research, 92(D8), pp. meteorologists. With the exception of a few hydrologists 9551-9566. (e.g., Schuitz, 1989), we have waited for the meteorologists Griffith, e.G., Woodiey, W.E., and Grubb, P.G., 1978. Rain to solve this problem. It is time for more hydrologists to estimation from geosynchronous satellite imagery take an active role in this research so that the solutions visible and infrared studYI Monthly Weather Review, provide meaningful answers to hydrological questions. 106, pp. 1153-1171. Rao, M.S.V., Abbott, W.V., and Theon, J.s., 1976. Satellite References derived global oceanic rainfall atlas (1973-1974), Adler, R.E, Negri, A.J., Prasad, N., and Tao, W.K., 1989. Cloud NASA Special Publication 410, National Aeronautics model-based simulations of satellite microwave data and Space Administration, Washington, D.C., 31 pp.
and their application to an SSM/! algorithm, Schultzl G.A., 1989. Remote sensing of watershed character Proceedings of the Fourth Conference on Satellite istics and rainfall input} in Unsaturated Flow in Meteorology and Oceanography, American Hydrologic Modelling Theory and Practice, H.J. Meteorological Society, San Diego, CA, pp. JI2-JI5. Morel-Seytoux (ed.), KlilIver Academia Publishers, Barrett, E.C., 1970. The estimation of monthly rainfall from pp.301-323. satellite data, Monthly Weather Review, 98, pp. 322 Scofield, R.A., 1987. The NESDIS operational convective 327. precipitation esthnation technique, Monthly Weather Camillo, P.J. and Schmugge, T.J., 1984. Correlating rainfall Review, 115, pp. 1773-1792. with remotely sensed microwave radiation using Scofield, R.A. and Oliver, V.J., 1977. A scheme for estimating physically based models, IEEE Transactions on convective rain from satellite imagery, NOAA
Geoscience and Remote Sensing, GE·22 t pp. 415 Technical Memo. NESS 86, Washington, D.C., 47 pp. 423. Shih, S.p., 1989. Potential application of satellite data for rain Chang, A.T.C. and Wilheit, T.T., 1988. Rainfall index over fall estimation, Remote Sensing and Large-Scale oceans derived from 5SM/I data, Proceedings of the Global Processes (Proceedings of the IAHS Third lGARSS '88 Symposium, ESA SP-284, Edinburgh, International Assembly, Baltimore), IAHS Scotland, pp. 251-252. Publication No. 186, pp. 97-104. Dahlstrom, B., 1985. Estimation of precipitation by remote Spencer, R.W., Goodman, H.M., and Wood, R.E., 1988. sensing techniques, in Remote Sensing Applications Precipitation retrieval over land and ocean with the to Hydrology and Water Resources) Proceedings of SSM/I, part 1: Identification and characteristics of an International Seminar in Bratislava! the scattering signal, JOllmal of Atmospheric and Czechoslovakia, UNESCO Technical Documents in Oceanic Technology, 2, pp. 254-263. Hydrology, pp. 46-56. Wilheit, T.T., Rao, M.S.V., Chang, A.T.e., Rogers, E.B., and Follansbee, WA., 1973. Estimation of average daily rainfall Theon, T.S., 1977. A satellite technique for quanti from satellite cloud photographs, NOAA Technical tative mapping rainfall rates over the ocean/Journal Memorandum, NESS 44, Washington, D.e., 34 pp. ofApplied Meteorology, 16, pp. 551-560. CHAPTER 4
SOIL MOISTURE AND GROUNDWATER
Studies of subsurface water distinguish two zones; the zone of In addition, vegetation obscures the surface. The accuracy aeration and the zone of saturation. The zone of aeration is of this method is poor and absolute vaiues of soil moisture comprised of three sub~-zonesJ namelYI soil water} intermediate, cannot be obtained. There are, however, many remote and capillary. Water in this entire zone is called soil moisture. sensing instruments available for obtaining data in this The amount of water in the zone of aeration varies in time and special region and several operational satellites that can space. The saturated zone is the groundwater which tends to be obtain data at high resolution. less variable than soil moisture. Thermal techniques utilize the diurnal variation Information on soil moisture is important to agri of surface temperature or the difference in temperature cultural water management and hydrological runoff between the vegetation canopy and the air to estimate soil forecasts. Information on groundwater is needed primarily moisture. Thermal infrared observations of surface temper for water supply purposes and agricultural water manage ature are dependent on soil moisture for bare soils. ment. The importance of groundwater wiil increase in the However, the surface temperature also depends on other future due to the demands for better quality drinking factors such as incoming solar radiation, air temperature, water. humidity and wind speed. To normalize for these atmo In the literature, the measurement of subsurface spheric effects, -the diurnal variations are used. Diurnal water by remote sensing techniques is divided into soil approaches rely on the thermal inertia of the soil which is moisture measurement and the mapping of areas of a function of the thermal conductivity and heat capacity of groundwater. Most of the information that can be the soil (Schmugge et ai., 1980; Mulders, 1987). These obtained by remote sensing applies to the surface layers of factors are dependent on the soil type and soil moisture. the soil, however, there are situations and techniques that As the soil moisture increases, the thermal inertia increases can provide information on greater depths. and the diurnal variation in surface temperature decreases. For vegetated soils the difference between the 4.1 Soil moisture canopy radiation temperature and the ambient air temper Based upon the literature (Schmugge et aI., 1980 and ature can be used as an indicator of crop stress. Well Mulders, 1987) there are a variety of remote sensing tech watered plants wili be in thermal equilibrium with the air niques that can be used to estimate soil moisture. while stressed plants may be warmer than the air. Characteristics of these techniques are listed in Table 1. A major probiem with sensing in the visible and The reflection of bare soil in the visible and near infrared regions is the atmosphere. Atmospheric variations infrared parts of the electromagnetIc spectrum can only be make the absolute calibrations of these observations very used under limited conditions. In this case the indicator of difficult, especiaily from space platforms. Without an soil moisture is the colour of the soil. Reflectance is also absolute calibration, analyses are typicaily limited to quali dependent on chemical composition, texture, structure, tative indicators that can only be extracted after extensive and roughness (Mulders, 1987; Baumgartner et ai., 1985). analysis by trained personnel. In addition, clouds will obstruct observation of the surface in these spectral bands. In humid regions it is very difficult to obtain frequent TABLE 1 observations from a space platform which are cloud free. Soil moisture remote sensing techniques A unique advantage of using the microwave region of the electromagnetic spectrum for soil moisture Region ofthe Order of sensing is that at long wavelengths the observations can be electromagnetic magnitude made through clouds. Property observed spectrum Platfoml* depth Microwave remote sensing can be performed Albedol Visible and A, S Micrometers using either active (radar) or passive instruments. index of refraction near lnfrared Active microwave instruments send out a pulse and measure the returned signal. From these data, a Surface Thermal infrared A, S Millimeters backscattering coefficient is computed. Backscattering temperature depends on the dielectric properties of the soli, the surface roughness, and the topography (Viaby et aI., 1986). Backscattering coef./ Active A, S Centimeters dielectric constant microwave Dielectric properties or the dielectric constant depend on the soil water and soil texture (Schmugge, 1980; Dobson et Microwave emissivityl Passive A, S Centimeters aI., 1985). The thickness of the sensed iayer depends on dielectric constant microwave Decimeters the wavelength of the sensor and the wetness of the soil. Longer wavelengths sense a deeper layer. The effects of Reflection Active, nadir- Decimeters vegetation decrease as the wavelength increases. Extensive coefficient viewing pulse A,G Meters studies by Ulaby et ai. (1986) have shown that the optimal radar wavelength for radar soil moisture sensing independent of Attenuation of Gamma A Centimeters surface roughness is approximately 5 em and at an inci terrestrial gamma radiation Decimeters dence angle between 10 and 20 degrees, based upon radiation sensitivity studies. At this wavelength the contributing depth will be to the order of 2 em and small amounts of * S=Space, A=Aircraft, and G=Ground (mobile) platform. vegetation will not obscure observation. 6 CHAPTER 4
There are several aircraft systemsavaHable for Current aircraft systems are capable of both obtaining radar data, primarily for research. There have spatial and temporal observation of surface soil moisture. also been several short-term satellite and Space Shuttle Recent large~scale experiments have focused on how such radar missions. One reason for the interest in this data might be integrated Into hydrologic models. An approach for Earth observation is the fact that hIgh spatial example of this temporal-spatial data is presented in resolution data can be obtained from space platform alti Figure 1. In this figure the spatially variable antecedent tudes using SAR techniques (Ulaby, et aI., 1986). At rainfall and evapotranspiration are clearly reflected in the present, these synthetic aperture radar (SAR) instruments soil moisture estimates derived from L band radiometer on the ERS-l, ALMAZ, and JERS-l satellites, respectively, data Oackson et aI., 1991). are providing quasi-operational radar data at resolutions of The long-standing, basic problem with passive 15-30 m. microwave radiometry has been poor ground resolution Another approach that utilizes centimeter and from space platform altitudes. Using conventional decimeter wavelengths is passive microwave radiometry. antenna technology, ground resolution is increased by one In this approach, the natural microwave emission is of the following: shorter wavelengths, larger antennas, or measured in terms of its equivalent brightness temperature. lower altitudes. The desired resolution for large-scale The emissivity is dependent on the dielectric properties of studies is probably 10 km, which is on the order of the the soil and the surface roughness Oackson and Schmugge, scale of rainfall variability. New antenna technologies are 1989; Schmugge et aI., 1986; Shutko, 1982). The physical now emerging that can be used to overcome these limita basis of passive microwave sensing is more straightforward tions. Because space-based methods are the only ones than active sensing using radars. This makes calibration suitable for frequent monitoring of large areas, the devel easier and allows the mOTe direct observation of physical opment of these technologies should be promoted. parameters. However, the resolution of the passive Soil moisture information at a depth of several microwave sensors is much poorer than that of active meters can be obtained from short pulse radar techniques. microwave sensors. Reflected radiation at nadir angle of observation is received Longer microwave wavelengths are optimal for by the radar mounted on ground or aircraft platforms passive microwave remote sensing of soil moisture. (Finkelstein, et aI., 1987). In Russia, this aircraft-based However, radio frequency interference causes problems method is used for soH moisture measurements in forested beyond 1. band (21 em or 1.4 GHz). The soil depth areas and for detecting zones of saturation down to a depth contributing to L-band measurements is primarily the top of 5-10 m. Dielectric properties of soil at radio wave 5 em Oackson and Schmugge, 1989; Reutov and Shutko, lengths are mainly affected by free water content (in a 1986). However, it is possible to determine the soil mois range from wilting point to saturation). Thus radiophysi ture through a depth of one meter if two microwave cal sensors are capable of measuring volumetric free water wavelengths are used in conjunction with a priori informa content in soil (Shutko, 1982; 1985; 1987). A drawback of tion on local soil properties (Reutov and Shutko, 1986). this method is that it reqUires detailed calibration by an Under ideal conditions the accuracy of estimating surface experienced technician in each study area chosen. moisture can be 1 to 2.5 per cent (Pampaloni et aI., 1986; The variation of natural terrestriai gamma radia Jackson et aI., 1991), however, the error is typically 5 to 7 tion can be used to measure soil moisture because gamma per cent (Schmugge et aI., 1986; Shutko, 1982). Vegetation affects the microwave measurement I" 20 through its biomass (wet) and structure. The significance of .... •...... ·AUGUST 2 these effects is large at short (centimeter) wavelengths, ••• -_ •• AUGUST 3 however, at 21 and 30 em a deterministic correction can be ---AUGUST4 applied for canopies with wet biomass up to 5 kg/m>. This ._.._ .. -. AUGUST 5 would allow accurate estimates for almost all grasslands and cultivated crops with the exception ofthe peak biomass period Oackson et aI., 1982; Shutko and Chukhlantsev, 1982). Biomass corrections may be made using indices based on visi ble/near infrared data or a crop calendar. At present, microwave radiometers capable of measuring soil moisture are only available on aircraft. These are being used in both research and a few operational applica tions. Example research applications include preplanting soil moisture condition assessment, irrigation management, water management, and water balance studies Gackson and Schmugge, 1989; Shutko, 1985; Shutko, 1987). The first oper 5ol---...,2.....---4'----6~--...,6~--...,,~O ational programme utilizing these sensors were initiated in Russia in the early 1980s. Small aircraft laboratories equipped DISTANCE (m) (Thousands) with microwave radiometers have been used for agricultural, hydrometeorological, and land reclamation applications. The Figure 1 - Surface soil moisture estimated using an L band feasibility of these capabilities has been widely demonstrated microwave radiometer in the Walnut Gulch Watershed. Prior to 2 in many countries (Bulgaria, Poland, Hungary, Germany, August there was rainfall over the entire area. This was followed Vietnam, and Cuba) (Shutko, 1985). in recent years, the by a day of drying, 3 August. Prior to 4 August observations, Russian radiometers have been tested in the United States in another rainfall event occurred but this time only over the area the large scale hydrology experiment called Monsoon 90 represented by the left side of the figure. Finally, there was Oackson et aI., 1991). another day of drying,S August Uackson et al., 1991). SOIL MOISTURE AND GROUNDWATER 7 radiation is strongly attenuated by water. Most of the Nadir~viewing short pulse radars installed on gamma radiation which can be measured over the ground mobile ground or aircraft platforms and operating at originates from the top 90 em. Thus attenuation of frequencies from several hundred KHz to several hundred gamma radiation can be used to determine changes in soil MHz provide information on the depth to a shallow water moisture in the top 20-30 em of the ground. This tech table down to 5-50 m (Finkelstein et aI., 1987). nique requires that some ground measurements of soil All the other remote sensing methods of observ moisture be made during the measurement flights because ing groundwater are indirect. Aerial and satellite imagery it does not give absolute values of soil moisture. This is in the visible and infrared part of the electromagnetic spec potentialiy the most accurate of the remote sensing trum can give valuable information concerning the methods developed for soil moisture measure-ment. The topography, morphology and vegetation of the area. 50il error averages 5 per cent (Jones and Carroli, 1983). types can also be interpreted to some extent using these Air strongly attenuates gamma radiation which data. Good spatial resolution and the possibility of using reqUires that the measurements be made from aititudes of 50 stereoscopic images give the best results in inventories. 150 m. The equipment itself, the gamma ray spectrometer, is Infrared images are especially useful for vegetation and soil expensive and needs complicated calibration. It is in opera type mapping. Springs can best be detected using infrared tional use mainly for geological purposes, and thus gamma and thermal imagery. Even underwater springs can be spectrometers are available to some extent. The measure detected by this method (Guglielminetti et aI., 1982). ments must be made over the same routes every time because Radar images are useful for studying topography and the spatial variation of the gamma radiation can be strong. geomorphology, and it is also possible to detect water Measurements are not possible over saturated soils (mainly which is some decimeters below the ground surface in arid swamps) because in this case the attenuation by the water is areas, due to the increase in soil moisture near the surface. too strong. In addition, a rapidly changing amount of radon Because variation in both amount and flow of gas in the air can cause severe errors in the measurements if groundwater takes place slowly, there is no need for real~ the calibration is not made carefully. time data dissemination or proceSSing. Thus, there is time to select the best images and to interpret these carefully, in 4.2 Groundwater most cases by manual methods. The presence, depth and amount of groundwater are extremely Aerial photography, Landsat data and SPOT data are important in hydrology. The topography and morphology of widely used for groundwater inventories, primarily for locat an area are important in the location of groundwater, and, in ing potential sources of groundwater. These methods are some areas, the vegetation can yield information. inexpensive and easy to adOpt. A good summary of these Remote sensing techniques can provide some approaches is presented in Farnsworth et al. (1984). These information for groundwater hydrology; however, it is techniques are especially applicable in arid regions as shown usually indirect. This is d-q.e tQ the intervening unsatu~ by ZevenbergenandRango (1992). The application of passive rated zone of soil. microwave data for detecting shallow groundwaterJevels is Shallow groundwater tables can be measured using being used in the Russian Federation and is dependent on the passive microwave radiometry. Adual frequency radiometer availability of the instruments (Shutko, 1987). has been used on an aircraft to measure water table depths of two meters in humid areas and four meters in arid areas References
(Shntko, 1982; 1985; 1987). An example of the type of data Baumgartner, M. F' 1 Silva, L. F., Biehl, L. L., and Stoner, E. R., that this system produces is shown in Figure 2. 1985. Reflectance properties of soils, in Advances in Agronomy, Academic Press Inc., Orlando, Florida, ,------~~~ 38, pp. 1-44. I Carroll, T., 1985. Airborne Gamma Radiation Snow Water Equivalent and Soil Moisture Measurements, A I User's Guide} Version 2.0, Office of Hydrology} ! la) 0- National Weather SerVice, NOAA, 27 pp. Dobson, M. C., Vlaby, F. T., Hallikainen, M. T., and EI-Rayes, (A) ! M. A., 1985. Microwave dielectric behavior of wet soil-Part II: dielectric mixing models. IEEE Transactions on Geoscience and Remote Sensing/ GE-23(1), pp. 35-46. Farnsworth, R. K., Barrett, E. c., Dhanju, M. S., 1984. mm- 0-0.5 Applications of remote sensing to hydrology includ ~- 0.5-1.5 ing groundwater, IHP-II Project A.1.5, UNESCO, D- >1.5 Paris} France. Finkelstein} M. L, Mendelson, V. L., and Kutev, V. A., 1987. Radar sensing ofstratified Earth's covers (in Russian), Soviet Radio Publishing House, Moscow, 174 pp. Guglielminetti, M. R., Boltri, R,} Morino} C. M.} and Lorenzo, S., 1975. Remote sensing techniques applied to the Figure 2 - Retrieved radiometric data of shallow water tables on study of freshwater springs in coastal areas of south an area of about 2 000 hectares (A) and the results of a compari ern Italy, Proceedings of the 10th Symposium on son (B) between radiometric (solid line) and ground truth data Remote Sensing of the EnVironment, Environmental (vertical lines) of the depths of shallow water tables along the Research Institute of Michigan, Ann Arbor, pp. 1297 aircraft track (a) (Shutko, 1987) 1309. 8 CHAPTER 4
Jackson, T. J., Schmugge, T. ]., and Wang,]. R., 1982. Passive Reutov, E. A. and Shutko, A. M., 1986. Prior knowledge microwave remote sensing of soil moisture under based soil moisture determination by microwave vegetation canopies, Water Resources Research, 18(4), radiometry, Soviet Journal of Remote Sensing, 5(1), pp. 1137-1142. pp. 100·125. Jackson, T. J. and Schmugge, T. J., 1989. Passive microwave Schmugge, T. J., 1980. Effect of texture on microwave emis remote sensing system for soil moisture: some sion from soils, IEEE Transactions on Geoscience and supporting research, IEEE Transactions on Remote Sensing, GE-18, pp. 353-361. Geoscience and Remote Sensing, GE-27(2), pp. 225 Schmugge, T.J. ,Jackson, T.J., and McKim, H. L., 1980. Survey 235. of methods for soil moisture determination, Water Jackson, T.]., Shutko, A. M" Shiue,J. C., Scllll1ugge, T.]., Davis, Resources Research, 16(6), pp. 961-979.
D. K, Parry, R., HaldiTI, A' I Reutov, E., Novichikhin, Schmugge, T. J., O'Neill, P. E., and Wang, J. R., 1986.
E., Liberman, B., Kustas, W. P' I Goodrich, D. c., Passive microwave soil moisture research, IEEE Bach, L., and Ritchie, J. C., 1991. Soil moisture Transactions on Geoscience and Remote Sensing, observations using multifrequem:y passive GE-24(1), pp. 12-22. microwave sensors in an arid rangeland environ Shutko, A. M., 1982. Microwave radiometry of lands under ment: a cooperative US - USSR experiment, natural and artificial moistening, IEEE Transactions Proceedings of the AmericarrMeteorological Society . on Geoscience and Remote.Sensing, GE-20(1), pp. Special Session on Hydrometeorology, Salt Lake City, 18-23. pp.174-177. Shutko, A. M., 1985. Radiometry for farmers, Science in the Jones, K. J. andCarroll, T. R., 1983. Euor analysis of airborne USSR, No.6, pp. 97-113. gamma radiation soil moisture measurements, . Shutko, A. M., 1987. Remote ·sensing of the waters and . Agricultl/ral Meteorology, 28, pp. 19-30. lands via microwave radiometry (the principles of Mkrtchjan, F. A~I Reutov, E.A., Shutko, A. M-., Kostov, K. G., method, problems feasible- for solving, economic
MichalevJ M. A" Nedeltchev, N. M" Spasov, A. Y., use), in: Remote Sensing and Its Impact on and Vichev, B. I., 1988. Microcomputer-based Developing Countries" Pontificia Academia radiometer data acquisition and processing system Scientiarum, Scripta Varia-68,' Vatican City, pp. for large-area mapping of soil moisture in the top of 413-441. one meter layer, Proceedings of the IGARSS '88 Shutko, A. M., and A. A Chukhlantsev, 1982. Microwave radic Symposium, ESA SP-284, Edinburgh, Scotland, pp. ation peculiarities of vegetation covers, IEEE 1563-1564. Transactions on Geoscience and Remote Sensing,
Mulders, Mo AO l 1987. Remote sensing in soil science, GE-20(1), pp. 27·30. Developments in Soil Science, 15, Elsevier} Ulaby, F. T., Moore, R. K., and Fung, A. K., 1986. Microwave Amsterdam, The Netherlands. remote-sensing: active and passive, Vol. III, Artech Pampaloni, Po, Paloscia, SO} and Chiaranti, L., 1986. House, Dedham, MA. -Contribution of passive microwave remote sensing Zevenbergen, A. W. and Rango, A., 1992. Applying Landsat in soil moisture and evaporation measurements} ESA imagery for groundwater development in Egypt, SP-248, pp. 327-332. Geocarto International, 7(3). CHAPTERS EVAPOTRANSPIRATION
Remote sensing observations in the optical wavebands estimating incoming shortwave and longwave radiation (visible to thermal-IR wavelengths) combined with ancil and remotely sensed data for determining the outgoing lary meteorological data have been used in evaluating components 0ackson, 1985). evapotranspiration (ET) over a range of temporal and The soil heat flux, G, can be solved as a function spatial scales (Kustas et ai., 1989a; Choudhury, 1989), of the thermal conductivity of the soil and the vertical Remote sensing in the optical regions has been shown to temperature gradient. This temperature gradient cannot be provide information useful in estimating surface tempera measured remotely, but models using routine weather data ture} albedo} incident solar radiation, and vegetation may provide satisfactory calculations (e,g" Camillo, 1989), biomass. As of yeti no remote sensing system can provide An alternative approach assumes G/Rn is a constant which near-surface atmospheric parameters. mainly varies as a function of vegetation cover (Clothier et The approaches for determining ET can be ai., 1986; Kustas and Daughtry, 1990), This allows G to be divided into three basic groups: semi~empiricalJ analytical, determined essentially with remote sensing data. However, and numerical (Carlson, 1986). For each method, attempts the applicability of such a simple parameterlzation may be have been made to incorporate remote sensing data which limited due to temporal hysteresis and the effects of soil are normally available once or twice a day for estimating moisture on the G/Rn relationship (Brutsaert, 1982). daily ET, The rationale for computing daily values is that The sensible and latent heat fluxes are commonly flinstantaneous" remotely-sensed information that can solved using bulk resistance or single-layer expressions yield an Ilinstantaneous'J ET flux has no real practical together with surface-air temperature and surface-air application in hydrological modelling, A daily time step vapour pressure differences, respectively (Monteith, 1973), probably proVides the most useful information for most Studies suggest H and I.E estimated by such a technique are hydrological modelling applications. Therefore this accurate for uniform, full cover vegetated surfaces as long overview will discuss methods which attempt to estimate as aerodynamic and canopy resistances can be properly daily ET using remotely sensed data collected once or twice estimated. Difficulties arise in the application of these a day combined with numerical, analytical, and semi equations over partial canopy cover because the remotely empirical techniques for estimating a daily value. sensed data are affected by both the soil and vegetation; It should be pointed out that all of these methods and energy fluxes across the soi1~vegetation-atmosphere require cloud-free conditions, to some degree, over the area interface can no longer be easily .parameterized by single of interest. Also} correction for atmospheric effects on the layer models (Kustas, 1990; Choudhury, 1989). radiance received at satellite altitudes is not trivial. Even after corrections are made, there can be significant errors 5,1.1 Semi-empirical methods for some critical remotely-sensed parameters such as For integration of equation (2) over a 24-hour period, it is surface temperature. commonly assumed that G is negligible. Furthermore} Finally, there is the issue of estimating ET over large observations by Itier and Riou (1982) and more recently by areas which are usually heterogeneous. Studies which evalu BruneI (1989) suggest the daily ratio of H/Rn can be ate regional ET cannot easily verify the results with approximated by H/Rn estimated near midday under clear conventional ground-truth data. Instead, comparisons are sky conditions. With some further approximations, made with other model results or by extrapolating point equation (2) can be recast as: measurements ofhydrological data such as rainfall, pan-evap (2) oration values} or lysimeter data. However, recent large-scale field studies such as HAPEX-MOBILIHY (Andre et aI., 1986) where Ts is. the surface temperature estimated remotely, say and FIFE (Sellers et al.; 1988) are proViding the appropriate from a satellite-based sensor} T a is the near-surface air ground-truth data for evaluating regional-scale model output temperature obtained from a nearby weather station} and (e,g" Mahfouf, 1990). the subscript j represents the f1instantaneous!l observation by the satellite over the area of interest. This equation was 5.1 Overview ofremote sensing models for first proposed by Jackson et al. (1977) and later evaluated evaluating ET using empirical and theoretical results by Seguin and Hier (1983), This expression and derivatives of it have been In computing ET, the surface energy balance equation is tested and shown to produce reasonable estimates of daily the primary boundary condition to be satisfied: ET (Brunei, 1989; Kerr et aI., 1987; Niewenhuis et aI., 1985; Rambal et ai., 1985; Thunnissen and Niewenhuis, 1990), Rn+G+H+LE=O (2) Recent experimental and theoretical studies relating to the where Rn is the net radiation, G the soil heat flux, H the variation in the coefficient B as a function of surface sensible heat flux, and LE the latent heat flux, For this conditions and the reference height (Carlson and Buffum, discussion ET and IE are synonymous. Net radiation can 1989; Vidal and Perrier, 1989) have shown that B may be a be divided into incoming and outgoing shortwave and relatively stable parameter. The effects of cloudy condi Iongwave components. tions on the remote sensing data and the approximation A number of approaches have been developed for leading to equation (3) may limit its application, evaluating all the components of Rn with geostationary In another related approach 0ackson et aI., 1983), satellites (Pinker, 1990; Sellers et ai., 1990). Other BY was assumed to follow the temporal trend in solar techniques combine local meteorological observations for radiation throughout the daylight period, In addition, 10 CHAPTER 1
they showed that the ratio of daily to midday solar model sensitivity to such errors should be assessed in order radiation could be approximated by an analytical to give some idea of the reliability of flux estimates for expression involving the sine function, time of sunrise, and different meteorological and surface conditions (Kustas et length of day. Thus with an estimate of midday ET, and aI., 1989a; 1990). the assumption that ratios of midday to daily ET and solar radiation are equal, daily total BT can be computed. 5.2.2 Non-uniform studies Jackson et ai. (1987) showed the techniques worked Under many conditions the surface is not fuily vegetated but reasonably well with remote sensing data from an aircraft. contains some percentage of soil and vegetation cover. Hence the remotely sensed data is influenced by the spectral proper 5.1.2 Analytic approach ties of the soil and vegetation. Attempts to evaluate ET More physically-based approaches than discussed above without separating the contributions from the soil and vege in equation (2) over a 24-hour period are shown to tation to the composite spectral and thermal-IR data and the produce an analytical solution (Pratt et aI., 1980; Price, energy fluxes (i.e., a single-layer approach) have not always 1980). The 24-hour value of G is also assumed to be yielded satisfactory results (Kustas et aI., 1989b; Kustas, 1990). negligible. To further simplify the expression, Price Remote sensing models which treat the soil and vegetation (1980) used the Fourier expansion of the angle of solar separately have been developed (e.g., van de Griend and van incidence and linearized the Stefan-Boltzmann equations Boxel, 1989); however, the feaSibility of using them over large for the incoming and outgoing longwave and the bulk areas has not been treated quantitatively (Carlson etaI., 1990). resistance equation for H. The result is a 24-hour average Other approaches have related surface temperature to the estimate of ET which requires as primary input a 24-hour amount of vegetation cover and employed this in estimating max-min difference in surface temperature. This model critical ET-model parameters (e:g., Nemani and Running} readily lends itself to the NOAA-AVHRR series of satellites 1989; Price, 1990). which provide day-night pairs of surface temperatures. A synergistic approach with remote sensing data The method has been evaluated by Price (1982) and shows real promise in dealing with the problem of partial appears to give appropriate ET values when compared to cover (van de Griend and Glumey, 1988). It involves combin local estimates using standard meteorological and pan ing optical remote sensing with microwave observations evaporation data. More recent applications of this model which provide information on near surface soil moisture with ground-truth data from detailed field studies have conditions Oackson and Schmugge, 1989). The ability to not been performed. extract satisfactory estimates of soil hydraulic properties has been shown by van de Griend and O'Neill (1986) and Camillo 5.1.3 Numerical models et ai. (1986). However, a study of the spatial and temporal A significant number of models using remotely sensed data relationships between surface temperature and active have been developed over the past decade, which simulate microwave data (Perry and Carlson, 1988) suggests they are the flow of heat and water in the soil and use the surface rather complicated. Further work in this area is needed. energy balance as the boundary condition (Camillo et aI., 1983; Carlson et aI., 1981; Raffy and Becker, 1985; Rosema 5.2.3 Regional ET et aI., 1978; Soer, 1980; Taconet et aI., 1986). The Problems associated with ET modelling at regional scales advantage of using this approach is that only initial are twofold. First is the method used to aggregate pixel conditions are needed to determine model parameters. data and second is the technique for extrapolating near Then, the temporal trace of the evaporative flux can be surface meteorological data. Analytical and experimental simulated and periodically updated with remote sensing investigations by Gash (1987) and Kustas et a1. (1990) have observations whenever they are available. Tacanet et a1. revealed some of the potential errors in attempting tb eval (1986) show the feasibility of using this type of an uate the variation of ET over non-homogeneous (both in approach with AVHRR data and more recently included moisture and vegetation) surfaces. Others utilize the inte geostationary satellite data (METEOSAT) to increase the grating properties of the atmospheric boundary layer stability of model inversion and atmospheric correction to (Brutsaert, 1988) together with relatively coarse resolution the satellite observations (Taconet and Vidal-Madjar, 1988). satellite sensors to determine large areal ET fluxes (Carlson However, it may be difficult to evaluate ET over large areas et aI., 1984; Klassen and van de Berg, 1985; Wetzel and with a model requiring a significant number of input Woodward, 1987). As pointed out earlier, verification of parameters which relate to the soil and vegetation because model calculations of regional ET with more extensive this information is not readily available. This obstacle has ground-truth observations are beginning to appear in the been considered in model formulations (Gurney and literature (Shuttleworth, 1991). Camillo, 1984; Kustas, 1990; Noilhan and Pianton, 1989). References 5.2 Unresolved issues for evaluating ET with Andre, J. C., Boutorbe, J. P. and Perrier, A., 1986. HAPEX remote sensing MOBiLHY: A Hydrologic Atmospheric Experiment for the study of water budget and evaporation flux at 5.2.1. Atmospheric correction the climatic scale, Bulletin of the American Accounting for the attenuation of the radiances received Meteorological Society, 67, pp. 138-144. by satellite-based sensors in the optical wavebands is often Becker, F. and Li, Z. L., 1990. Towards a local spilt window not a trivial matter (Kaufman, 1989; Price, 1989). In method over land surfaces, International Journal of correcting thermal-lR data whether using radiative transfer Remote Sensing, 11, pp. 369-393. models (e.g., Kniezy et aI., 1988) or split-window tech Brutsaert, w., 1988. The parameterization of regional evapo niques (Becker and Li, 1990; Price, 1984), errors on the ration· some directions and strategies, Journal of order of I" to 3" C over land are not uncommon. Therefore Hydrology, 102, pp. 409-426. EVAPOTRANSPIRATION 11
Brutsaert, W. H" 1982. Evaporation into the atmosphere, Jackson, R. D" Hatfield, J. L., Reginato, R. J., Idso, S. B. and Reidel, Dordrecht, The Netherlands, 299 pp. Pinter, Jr" P. J., 1983. Estimates of daily evapo BruneI, J. P., 1989. Estimation of sensible heat flux from transpiration from one time of day measurements of surface radiative temperature measurements, Agricultural Water Management, and air temperature at two meters: application to 7, pp. 351-362. determine actual evaporation rate, Agricultural Jackson, R. D., Moran, M. 5" Gay, L. W. and Raymond, L. H" and Forest Meteorology, 46, pp. 179-191. 1987. Evaluating evaporation from field crops using Camillo, P., 1989. Estimating soil surface temperatures airborne radiometry and ground-based meteorolog from profile temperature and flux measurements, ical data, Irrigation Science, 8, pp. 81-90. Soil Science, 148, pp. 233-243. Jackson, R. D., Reginato, R. J. and Idso, S. B. 1977. Wheat Camillo, P. J., Gurney, R. J. and Schmugge, T. J., 1983. A canopy temperature: A practical tool for evaluat soil and atmospheric boundary layer model for ing water requirements, Water Resources evapotranspiration and soil moisture studies/ Research, 13, pp. 651-656. Water Resources Research, 19, pp. 371-380. Jackson, T. J. and Schmugge, T. J., 1989. Passive microwave Camillo, P.J., O'Neill, P. J., and Gurney, R. J., 1986. remote sensing system for soil moisture: some Estimating the hydraulic parameters using passive supporting research, IEEE Transactions on microwave datal IEEE Transactions on Geoscience Geoscience and Remote Sensing, 27, pp. 225-23S. and Remote Sensing, GE-24, pp. 930-936. Kaufman, Y. J., 1989. The atmospheriC effect on remote Carlson, T. N., 1986. Regional-scale estimates of surface sensing and its corrections, in Theory and moisture availability and thermal inertia using Applications of Optical Remote Sensing (G. Asrar, remote thermal measurements, Remote Sensing Editor), John Wiley and Sons, New York, 734 pp. Reviews, 1, pp. 197-247. Kerr, Y. H" Assad, E.} Freleaud, J. P., Lagourde, J. P. and Carlson, T. N. and Buffum, M. J., 1989. On estimating Seguin, B., 1987. Estimation of evapotranspira total daily evapotranspiration from remote tion in the SaheIian zone by lise of METEOSAT surface temperature measurements, Remote and NOAA AVHRR data, Advances in Space Sensing of Environment, 29, pp. 197-207. Research, 7, pp. 161-164. Carlson, T. N., Dodd, J. K., Benjamin, S. G. and Cooper, J. Klassen, W. and van den Berg, W., 1985. Evapo N., 1981. Satellite estimation of the surface transpiration derived from satellite observed energy balance, moisture availability and thermal surface temperature, Journal of Climate and inertial, JOllrnal ofApplied Meteorology, 20, pp. 67 Applled Meteorology, 24, pp. 412-424. 87. Kneizys, F. X" Shettle} E. P" Abreu, L. W., Chetwnde, J. H., Carlson, T. N., Perry, E. M. and Schmugge, T. J., 1990. Anderson, G. P., GaIIery, W. 0" Selby, J. E. A. and Remote estimation of soil moisture availability Clough, S, A., 1988. Users Guide to LOWTRAN 7, and fractional vegetation cover for agricultural Report AFGL-TR-88-0177, AFRCL, Bedford, Mass., fields, Agricultural and Forest Meteorology, 52, pp. 137 pp. 45-69. Kustas, W. P.} 1990. Estimates of evapotranspiration with a Carlson, T. N., Rose, F. G. and Perry, E. M., 1984. Regional one-and two-layer model of heat transfer over scale estimates of surface moisture availability partial canopy cover, Journal of Applied from GOES infrared satellite measurements, Meteorology, 29, pp. 704-71S. Agronomy Journal, 76, pp. 972-979. Kustas, W. P., Choudhury} B. J., Moran} M.S., Reginato, R. Choudhury, B.]., 1989. Estimating evaporation and carbon J., Jackson, R.D., Gay, 1. W. and Weaver, H. 1., assimilation using infrared temperature data: 1989a. Determination of sensible heat flux over vistas in modelling, in Theory and Applications sparse canopy using thermal infrared data, of Optical Remote Sensing (G. Asrar, Editor), John Agricultural and Forest Meteorology, 44, pp. 197 Wiley and Sons, New York, 734 pp. 216. Clothier, B. E., Clawson, K. L., Pinter, Jr., P. ] OJ Moran, Kustas, W. P., Jackson} R. D. and Asrar, G.} 1989b. M. S., Reginato, R. J. and Jackson, R. D., 1986. Estimating surface energy-balance components Estimation of soil heat flux from net radiation from remotely sensed data} in Theory and during the growth of alfalfa, Agricultural and Applications of Optical Remote Sensing (G. Asrar, Forest Meteorology, 37, pp. 319-329. Editor), John Wiley and Sons, New York, 734 pp. Gash, J. H. c., 1987. An analytical framework for extrapo Kustas, W. P. and Daughtry, C. S. T., 1990. Estimation of lating evaporation measurements by femote the soil heat flux/net radiation ratio from spectral sensing surface temperature} International Journal data, Agriwltural and Forest Meteorology, 49, pp. ofRemote Sensing, 8, pp. 124S-1249. 205-223. Gurney, R. J. and Camillo, P. J., 1984. Modelling daily Kustas, W. P.} Moran} M. S., Jackson} R. D.} Gay, 1. W., evapotranspiration using remotely sensed data, DueII, 1. F. W., Kunkle, K. E., and Matthias, A. D., Journal ofHydrology, 69, pp. 305-324. 1990. Instantaneous and daily values of the Ilier, B. and Riou, C. H., 1982. Une nouvelle methode de surface energy balance over agricultural fields determination de l'evapotranspiration n~elle par using remote sensing and a reference field in an thermographie IR, Journal de Recherches arid environment} Remote Sensing of Atmosp'u,riques, 14, pp. 113-125. Environment, 32, pp. 125-141. Jackson, R. D., 1985. Evaluating evapotranspiration at Mahfouf, J-F, 1990. A numerical simulation of the surface local and regional scales, Proceedings of the IEEE, water budget during HAPEX-MOBILHY, 73(6), pp. 1086-1095. Boundary-Layer Meteorology, 53, pp. 201-222. 12 CHAPTERS
Monteith, J. L., 1973. Principles of Environmental Physics. mapping approach, Proceedings of the 12th Elsevier, New York, 241 pp. International Symposium on Remote Sensing of Nemani, R. R. and Running, S. W., 1989. Estimation of Environment, Ann Arbor, Michigan, pp. 2267-2276. regional surface resistance to evapotranspiration Seguin, B. and Iller, B., 1983. Using midday surface tempera from NDVI and thermal-IR AVHRR data, Journal of ture to estimate daily evaporation from satellite Applied Meteorology, 28, pp. 276-284. thermal IR data, International Journal of Remote Nieuwenhuis, G']'I Smidt, E. H. and Thunnisseo/ H. A. M" SensIng, 4, pp. 371-383. 1985. Estimation of regional evapotranspiration of Sellers, P.J., Hall, F. G., Asrar, G., Strebel, D. E. and Murphy, R. arable crops from thermal infrared images] E., 1988. The first ISLSCP field experiment (FIFE), International Journal otRemote Sensing, 6, pp. 1319 Bulletin ofthe American Meteorological Society, 69, pp. 1334. 22-27.
Noilhanj ].} and Plantoll, S./ 1989. A simple parameterization Sellers, P.J., Rasool, S. I. and Bolle, H-J, 1990. Areview of satel of land surface processes for meteorological models, lite data algorithms for studies of the land surface, Monthly Weather Review, 117, pp. 536-549. Bulletin ofthe American Meteorological Society, 71, pp. Perry, E. M. and Carlson, T. N., 1988. Comparison of active 1429-1447. microwave soil water content with infrared surface Shuttleworth, W. J., 1991. Insight from large-scale observa temperatures and surface moisture availability! tional studies of land/atmosphere interactions, Water Resources Research, 24, pp. 1818-1824. Surveys in Geophysics, 12, pp. 3-30. Pinker, R. T., 1990. Satellites and our understanding of the Soer, G.J. R., 1980. Estimation of regional evapotranspiration surface energy balance} Paleogeography, and soil moisture condi~ions using remotely sensed Paleoclimatology, and Paleociology (Global and crop surface temperatures, Remote Sensing of Planet Change Section) 82, pp. 321-342. Environment, 9, pp. 27-45. Pratt, D. A., Foster, S.]. and Ellyet, C. D., 1980. A calibration Taconet, O. Bernard, R. and Vidal-Madjar, D., 1986. procedure for fourier series thermal inertia models] Evapotranspiration over an agricultural region using Photogrammetric Engineering and Remote Sensing, a surface flux/temperature model based on NOAA 46, pp. 529-538. AVHRR data, Journal of Climate and Applied Price,]. c., 1980. The potential of remotely sensed thermal Meteorology, 25, pp. 284-307. infrared data to infer surface soil moisture and evap Taconet, O. and Vidal-Madjar, D., 1988. Applications of a flux oration, Water Resources Research, 16, pp. 787-795. algorithm to a field-satellite campaign over vege Price, J. c., 1982. Estimation of regional scale evapotranspi tated area, Remote Sensing of Environment, 26, pp. ration through analysis of satellite thermal-infrared 227-239. data, IEEE Transactions on Geoscience and Remote Thunnissen, H. A. M. and Nieuwenhuis, G. J. A., 1990. A Sensing, GE-20, pp. 286-292. simplified method to estimate regional 24-h evapo Price, j.c.} 1984. Land surface temperature measurements transpiration from thermal infrared data, Remote from the split window channels of the NOAA 7 Sensing of Environment, 31, pp. 211-225.
advanced very high resolution radiometerl Journal of van de Griend, A. A. and Gurney, R. J., 1988. Satellite remote Geophysical Research, 89, pp. 7231-7237. sensing and energy balance modelling for water Price}]. c., 1989. Quantitative aspects of remote sensing in balance assessment in (semi-) arid regions, in the thermal infrared, in Theory and Applications of Estimation of Natural Groundwater Recharge (I Optical Remote Sensing (G. Asrar, Editor), John Simmers, editor) D. Reidel Pub. Co., Boston. Wiley and Sons, New York, 734 pp. van de Griend, A. A. and O'Neill, P. E., 1986. Discrimination Price,]. c., 1990. Using spatial context in satellite data to infer of soil hydraulic properties by combined thermal regional scale evapotranspiration, IEEE Transactions infrared and microwave remote sensing, Proceedings on Geoscience and Remote Sensing, 28, pp. 940-948. of IGARSS '86 Symposium, Zurich, ESA SP-254, pp. Rafly, M., and Becker, F., 1985. An inverse problem for remote 839-845. sensing in the thermal infrared bands and its solu van de Griend, A. A. and Van Boxel, J. H., 1989. Water and tion, Journal of Geophysical Research, 90, pp. surface energy balance model ""ith a multilayer S809-5819. canopy representation for remote sensing purposes, Rambal} 501 Lacaze, B., Mazurek} H. and Debussche, G., 1985. Water Resources Research, 25, pp. 949-971. Comparison of hydrologically simulated and Vidal, A. and Perrier, A., 1989. Analysis of a simplified relation remotely sensed actual evapotranspiration from for estimating daily evapotranspiration from satellite some Mediterranean vegetation formulations} thermal IR data, International JOl/mal of Remote International JOllrnal atRemote Sensing, 6, pp. 1475 Sensing, 10, pp. 1327-1337. 1481. Wetzel, P.J. and Woodward, R., 1987. Soil moisture and esti Rosema, A., Bijleveld,]. H" Reiniger, P.,Tassone, G.} Blyth} K. mation from geosynchronous satellite infrared data: and Gurney, R. J., 1978. TELL-US, a combined Afeaslbillty study, Journal ofApplied Meteorology, 23, surface temperature} soil moisture and evaporation pp.375-391. CHAPTER 6
SNOW
6.1 Hydrological applications ofusing remote sensing to map snow-covered areas 100 N~ Ifltltl~1 Among the applications of remote sensing in hydrology, MEL1WATER snow cover mapping is reaching the operational stage « 20 em (NASA, 1975, NASA, 1979). Due to its importance for snow w 2 0: km hydrology, in particular for river flow forecasts in moun « 1M tainous areas, attempts to evaluate the changing areal 0w 0: V = If(X)dx extent of the seasonal snow cover by terrestrial observa W > 50 o tions and photography took place long before the advent 0 of satellite remote sensing (Potts, 1937; 1944; Gartska et U ;': aI., 1958). It is evident that only satellites enable the 0 seasonal snow cover to be monitored periodically, effi Z
stream length, basin area, basin shape, drainage density, watershed. Divides between adjacent watersheds demar drainage pattern, and stream sinuosity or meander wave cate differences in drainage direction which can be readily length. Additional drainage basin parameters such as the observed from most Earth resources-type satellites. percentage of the basin in forests, swamps, surface water, Drainage density, which is the number of stream open area, and urban or impervious area can also be delin channels per unit area, can be extracted adequately in eated from high resolution sateilite imagery and are those areas where the landscape is sufficiently dissected to valuable in characterizing the hydrologic response of a permit detailed drainage mapping. Dissected areas provide basin. The physiographic and associated land use informa better contrast and thus better detail than non-dissected tion thus extracted is suitable for use in mean annual areas. For the most part these areas are characterized by sireamflow and/or mean annual flood regression models moderate or high -relief, non-glaciated landscapes, and and can also be used to calculate basic information neces resistant, impermeable lithologies. l.ocal relief of approXi sary for the calibration of watershed models which mately 90 m or more between basin divide and valley simulate daily discharge (Rango et a!., 1975). bottom in watersheds less than 2600 kmz usually provides Mapping of basin characteristics using satellite enough contrast to accurately map the drainage network data has been accomplished since the early 1970s. Using from high resolution satellite imagery. An exception to satellite based electro-optical systems, scales of up to this was found in ridge and valley topography where 1:50,000 may be obtained (Doyle, 1984). Due to the adequate local relief existed, but where most stream devel· stereoscopic capabilities of the SPOT satellite and the high opment has occurred on the flat, Wide valley floor. spatial resolution of its sensors (10 m), the smallest errors Drainage areas which were once covered by glacial ice achieved are now 5-20 ill in both the vertical and horizon often exhibit a lack of structural and bedrock control as tal planes. For economic reasons, however, the'most well as a lack of drainage patterns with a significant degree suitable scales are those of 1:100,000 to 1:250,000. It of integration or dissection. Streams which encounter should be stressed that increasing spatial resolution means resistant rocks tend to form valleys with steep slopes increased amounts of data and processing costs, and so for regardless of the climate, and landscapes of this type are each task the spatial resolution must be selected <:arefully. conducive to physiographic mapping from high resolution For watersheds larger than 10,000 km2, data from polar space sensors (Rango et aI., 1975). orbiting satellites having reduced resolution capabilities are The inspection of seasonal data over a given more practical (Tarpley, 1984). watershed greatly increases the chances that detailed Perhaps the most Widely used type of remotely drainage network information can be extracted. For sensed data for land cover in water-resources studies is that example, during times of minimum leaf coverage, snow obtained within the visible and near infrared region of the often enhances tributaries which may be difficult to spectrum. One reason for choosing this type of data is that discern during the summer season. it is relatively easy to interpret since the energy that is Drainage patterns can provide useful information sensed is reflected energy (5alomonson, 1983). concerning rock and soil relationships and landform asso The spectral resolution attainable with scanners ciations. For instance, radial drainage patterns are usually make their data more suitable than cameras for various indicative of resistant rocks and are associated with volca~ mapping and inventory purposes. Scanning sensors with noes and other domelike structures (see Table 4). wavelengths ranging from shortwave visible data to long Additionally, bifurcation ratios and drainage textures can wave microwave data are either currently in orbit or be useful in assessing permeability of the soil and bedrock. planned for launch in the 1990s. The all-weather, day For example, coarse drainage textures suggest resistant, night capability of microwave data is especially permeable bedrock materials. In coarse drainage systems advantageous and results of experimental inventories using the first-order streams are farther apart than they are for radar (active microwave) data are quite favorable (Brisco et medium and fine drainage textures (Travaglia, 1989). aI., 1983; Foster and Hall, 1981). But a better understand Of the Earth resources satellites which are ing of how microwaves respond and react to different currently operating, the SPOT satellite system with its kinds of media is needed before the'e data can be utilized stereoscopic viewing capabilities and superior resolution in an operational way. (10m) provides excellent mapping detail of drainage area Drainage network information is generally and density. The I.andsat TM has greater spectral range obtained from topographic maps which are usually out-of than the SPOT system which compensates for its coarser date. Remote sensing, due to its more current nature, can resolution (30 111). often provide better and more reliable information than these maps. Rango et a!. (1975) reported on a study in 9.2 Land Use Information which they compared conventionai methods with several Basin land use inventories are needed to improve surface types of remotely sensed data on a number of watersheds runoff and streamflow estimates. Some of the most impor in the United States. They found that watershed area, tant land use types are listed below. shape, and channel sinuosity estimates from Landsat 1. Floodplains and wetlands. Identification and images at a 1:100,000 scale were comparable to data mapping of flood-prone areas or floodplains are obtained from 1:62,500 scale topographic maps, particu critical for emergency preparedness and for flood larly in well-dissected terrain with moderate vegetation. In insurance evaluation. Flood-inundation mapping flat terrain or heavily forested areas, results were compara using remotely sensed imagery has been success· ble to 1:250,000 scale maps (5alomonson, 1983). ful on many rivers and in different regions using
The drainage system is controlled by the slope of visible data andl to a limited degree, thermal the surface and the type of underlying rock (Travaglia, infrared and radar data. Distinctive changes 1989). One of the easiest physiographic features to iden induced by additional water in an area facilitate tify using satellite imagery is the drainage area of a the mapping of floods. These include increased SNOW 15 water equivalent. It is possible to include the use of Geographic currently several drawbacks to using this technique. First, Information Systems (GIS) which makes it possible to estimate resolution from space is at present a limiting factor, the SWE for each pixel of the satellite image. although the use of aircraft platforms is a viable alternative until spacecraft resolutions improve. Second, mean snow 6.2.4 Microwave radiation grain size is not yet easy to obtain. Until some remote One of the largest problems for obtaining adequate visible measurement of the grain size is perfected} perhaps with observations for snow hydrology purposes is the presence visible satellite data (DOZier, 1989), ground-based measure of cloud cover over a basin. Although there are still several ments, meteorological data} and historical information problems with using microwave sensing for mapping snow must be relied upon (Armstrong and Rango, 1992). Finally, coverl one major advantage the microwave approach has is the presence of any liquid water in the snowpack causes the ability to penetrate cloud cover and map snow extent. the use of this modelling approach to be invalid. Despite Because of this cloud penetration or all-weather capability, these drawbacks, the method shows much promise and the microwave potential for snow mapping at about 1.0 em will become much more important as projected satellite wavelength has been of considerable interest to scientists. resolution improvements are realized in the 1990s. In The current major drawback is poor passive microwave addition} empirical relationships! similar to those of snow resolutions from space (about 25 km) so that only very depth, are a valid alternative approach to determine snow large areas of snow cover can be detected. It has been water eqUivalent from microwave data. shown, however, that the passive microwave data can be Although most success in analysing microwave used for determining snow-covered area over continents data for estimating snow water equivalent has been in flat (Rango et ai., 1979) and large river basins (Roll and Kunzi, areas} there are some possibilities for mountainous basins 1985; Josberger and Beauvillain, 1989) without interference as well. Analysis of the Nimbus-7 SMMR data over moun of clouds. The accuracy of the microwave snow mapping is tainous terrain was successful to the extent that an similar to visible snow mapping over the same area (Rango empirical relationship between 18 and 37 GHz brightness et ai., 1979). temperature difference and April 1 snow water equivalent Differences in interpretation arise from was derived for the 3419 km2 Rio Grande basin in microwave resolution problems and from the fact that Colorado. The average snow water eqUivalent for the basin microwaves penetrate very thin layers of snow with little was predicted to within 15 per cent of the actual value for absorption. As a result, the edge of the snowpack} which both 1986 and 1987 (Rango et ai., 1989). can be thin} is missed by microwave sensing and detected by the visible wavelengths. As resolutions of passive References microwave sensors improve} the all-weather capability will Armstrong, R. and Rango, A., 1992. Monitoring snow grain increasingly be exploited. The final advantage of the size for passive microwave studies, Proceedings of microwave spectrum is that nighttime measurements are the 60th Annual Western Snow Conference, Jackson, easily made because of the reliance on emitted microwave WY,10pp. radiation as opposed to reflected visible radiation. Baumgartner, M. E, 1987. Snowmelt runoff simulations based The resolution probiem can potentially be solved on snow cover mapping using digital Landsat-MSS with the use of high resolution active microwave sensors. and NOAA-AVHRR data, Technical Report HL-16, Unfortunately, few} if any! experiments with the short USDA/ARS Hydrology Laboratory, Beltsvllle, wavelength portion of the microwave spectrum (around 1 Maryland. em wavelength) that is sensitive to snow have been Carroll, T. R, 1986. Cost-benefit analysis of airborne gamma reported. Some interesting studies with 3 cm radar over radiation snow water equivalent data used in snow have been conducted (Rott, 1986), but applications snowmelt flood forecasting, Proceedings of the 59th are limited to a wet snowpack at this wavelength. If and Annual Western Snow Conference! PhoeniX, AZ, pp. when suitable instruments are built, the microwave 1-11. mapping capability should be possible on small drainage Carroll} T. R.! 1990. Operational remote sensing of snow cover basins as well as large basins and continental areas. in the U.s. and Canada, Proceedings of the 1990 Passive microwave attempts at estimating snow National Conference on Hydraulic Engineering, depth have also been limited to flat areas because the poor American Society of Civil Engineers, San Diego, resolution of the sensors prevents easy application in steep California. terrain. The studies that have been reported (Rango et ai., Chang, A.T.c', Foster,J. L., Hall! D. K.} Rango} A.! and Hartline} 1979; Foster et ai., 1980; Hall et ai., 1984; 1987) employ an B. K., 1982. Snow water equivalent estimation by empirical relationship between snow depth and microwave microwave radiometry! Cold Regions Research and brightness temperature. The positive results in these large Technology, 5, pp. 259-267. flat areas show much promise for estimating potential Dozier! ]'! 1989. Spectral Signature of alpine snow cover from winter kill of wheat which is affected strongly by the depth the Landsat Thematic Mapper, Remote Sensing of of snow cover in these areas. Environment, 28, pp. 9-22. Whereas an empirical model is necessary to make Foster, J. L, Rango, A., Hall, D. K., Chang, A.T.C., Allison, L. J., a passive microwave estimate of snow depth, a theoretical and Diesen, B. c., 1980. Snowpack monitoring in model of the passive microwave emission dependence on North America and Eurasia using passive microwave physical snowpack parameters such as snow water equiva satellite data, Remote Sensing of Environment, 10, lent has been derived by Chang et ai., 1982. When using pp.28S-298. the microscopic scattering model by Chang et ai., 1982, to Gartska, W. U., Lowe, 1. D.} Goodell! B. C., and BertIe, F. calculate the snow water equivalent of a dry snowpack, in A., 1958. Factors affecting snowmelt and stream addition to the microwave brightness temperature, it is flow! Bureau of Reclamation and U.S. Forest necessary to know the mean snow grain size. There are Service, 189 pp. 16 CHAPTER 6
Glynn,]. E., Carroll, T. R., Holman, P. B., andGrasty, R. L., 1988. McGinnis, D. F., Pritchard,]. A., and Wiesnet, D. R., 1975. An airborne gamma ray snow survey of a forest Determination ofsnow depth and snow extent from covered area with a deep snowpack, Remote Sensing NOAA 2 satelllte very high resolution radiometer ofEnvironment, 26, pp. 149-160. data, Water Resources Research, 11(2), pp. 897-902. Hall, D. K., Chang, A.T.e., and Foster,]. L., 1987. Seasonal and NASA, 1975. Operationai applications of satellite snowcover interannual observations and modelling of the snow observations (Editor, A. Rango), NASA Special pack on the arctic coastal plain of Alaska using Publication, SP-391, Washington, D.C., 430 pp. sate!liie data, Proceedings of the Cold Regions NASA, 1979. Operational applications of satellite snoweaver Hydrology Symposium, American Water Resources observations (Editors} A. Rango, and R. Peterson)] Association, Fairbanks, Alaska, pp. 521-529. NASA Conference Publication CP-2116, Washington, Hall, D. K., Foster, J. L., and Chang, A.T.C., 1984. Nimbus-7 D.e., 301 pp. SMMR polarization responses to snow depth in the 0degaard, H. A. and 0strem, G., 1977, Application of Landsat mid-western U.S., Nordic Hydrology, 15, pp. 1-8. imaging for snow mapping in Norway, Final report] Hall, D. K. and Martinec, ]., 1985. Remote Sensing of Ice and Landsat-2 Contract 29020, Norwegian Water Snow, Chapman & Hall, London - New York, 189 pp. Resources and Electricity Board, 20 pp.
Jones, E. B., P'iC', D. M" and Barkerl P. R., 1984. Application of Potts, H. L., 1937. Snow-surveys and runoff forecasting from a snowmelt runoff modei for flood prediction. photographs, Transactions of American Geophysical Unpublished report presented at the Symposium on Union, South Continental Divide Snow-survey a Critical Assessment of Forecasting, American Water Conference, pp. 658-660.
Resources Association! Seattlel Washington, 11 pp. Potts, H. L., 1944. Aphotographic snow survey method of fore ]osberger, E. G. and Beauvillain, E.} 1989. Snow cover of the casting runoff, Transactions ofAmerican Geophysical upper Colorado River basin from passive microwave Union, Part 1, pp. 149-153. and visual imagery, Nordic Hydrology, 20, pp. 73-84. Rango, A., Chang, A.T.C., and Foster,]. L., 1979. The utilization Kawata, Y. Kusaka, T. and Ueno, S., 1988. Snowmeit runoff esti of spaceborne radiometers for monitoring snowpack mation using snow-cover extent data and its properties, Nordic Hydrology, 10, pp. 25-40. application to optimum control of dam water level, Rango] A.] Martinec, J.} Chang] A.T.C.] Foster] J. L., and van Proceedings of the IGARSS '88 Symposium, Katwijk, V. E, 1989. Average areal water equivalent of Edinburgh, U. K., ESA SP-284, pp. 439-442. snow in a mountain basin using microwave and visi Keller, M., 1987. Ausaperungskartierung mit Landsat - MSS be satellite data, IEEE Transactions on Geoscience Daten zur Erfassung oekologischer Einflussgroessen and Remote Sensing, 27(6), pp. 740-745.
im Gebirge, (Mapping of snow cover ablation by Rango, A.] Salomonsonl V. V,] and Foster]]. L., 1977} Seasonal Landsat-MSS for evaluation of ecological effects), streamflow estimation in the Himalayan region Remote Sensing Series, Vol. 10, Dept. Geography, employing meteorological satellite snow cover obser Universlty of Zurich, pp. 209-220. vations, Water Resources Research, 13, pp. 109-112. Kuittinen, R., 1989. Determination of snow water equivalents Rango, A., van Katwijk, V., and Martinec, J., 1990; Snowmelt
by using NOAA-satellite images, gamma ray spec runoff forecasts in Colorado with remote sensingl trometry and field measurements} Remote Sensing Hydrology in Mountainous Regions (Proceedings of and Large-Scale Global Processes (Proceedings of the the Lausanne Symposium), IAHS Publication No. Baitimore Symposium), IAHS Publication No. 186, 193, pp. 627-634. pp.151-159. Rott, H.} 1986. Prospects of microwave remote sensing for Martinec}].} 1980. Limitations in hydrological interpretations snow hydrology, Hydrologic Applications of Space of the snow coverage, Nordic Hydrology, 11, pp. 209 Technology (Proceedings of the Cocoa Beach 220. Workshop), IAHS Publicati.on No. 160, pp. 215-233. Martinec, J., 1987. Importance and effects of seasonal snow Rott} H. and Kunzi, K. F., 1985. Remote sensing of snow cover cover, in Large Scale Effects of Seasonal Snow Cover with passive and active microwave sensors, (Proceedings of the Vancouver Symposium, 1987), Hydrological Applications of Remote Sensing and lAHS Publication No. 166, pp. 107-120. Remote Data Transmission (Proceedings of the Martinec,]. and Rango, A., 1987. Interpretation and utlllzation Hamburg Symposium), IAHS Publication No. 145, of areal snow-cover data from satellites] Annals of pp.361-369.
Glaclology, 9, pp. 166-169. Seidel] K.} U, Burkart} R. Baumamn,J, Martinec, H. Haefnerl and Martinec,]. and Rango, A., 1989. Effects of climate change on K. I. Itten, 1989. Satellite data for evaluation of snow snowmeit runoff patterns, Remote Sensing and Large reserves and runoff forecasts, Proceedings of the Scale Global Processes, (Proceedings of the Baltimore Hydrology and Water Resources Symposium, Symposium) lAHS Publication No. 186, pp. 31-38. Christchurch, New Zealand, The Institution of
Martinec} L Rango] A.} and Major, E., 1983, The Snowmelt Engineers, Australial National Conference Runoff-Model (SRM) User's Manual, NASA Reference Publication No. 89/19, pp. 24-27. Publication 1100, Washington, D.C., 118 pp. Vershinina, L. K., 1985. The use of aerial gamma surveys of Martinec, ]., Rango, A., and van Katwijk, V., 1990. snowpack for spring snowmelt runoff forecasts, Representativity ofsnow courses assessed from satel Hydrological Applications of Remote SensIng and lite monitoringof the snow cover} Proceedings of the Remote Data Transmission (Proceedings of the International Symposium on Remote Sensing and Hamburg Symposium), IAHS Publication No. 145,
Water Resources l International Association of pp. 411-420. Hydrogeoiogists, Enschede, The Netherlands, World Meteorological Organization, 1986. Intercomparison of pp.171-180. models of snowmelt runoff, Operational Hydrology Report No. 23, WMO-No. 646, Geneva. CHAPTER 7
ICE ON LAND
Ice on land may exist in the form of glacIers, lake and river seasonal and interanriual changes in the position of the ice, and permafrost as well as other more transitory forms boundaries of the snow line on glaciers may be detected of ice like hoarfrost and rime ice. Land ice, a key compo using Landsat and possibly even synthetic aperture radar nent of the global hydrologic cycle, represents both short (SAR) data. Long-term .analysis of the highest elevation of and long-term storage of freshwater. Lake and river ice the snow line each year may provide useful information on forms in winter and usually melts in the spring. Similarly, glacier mass balance. Global and long-term glacier area seasonal snow cover endures for only part of the year and, studIes are important for detection and monitoring of upon melting, contributes to runoff and groundwater. climate change. However, in mountainous areas, long-term storage of water Landsat Multispectral Scanner (MSS) and may result when the snow does not melt completely over a Thematic Mapper (TM) data have been available for about number of years] and turns to firll, and] with further two decades. These data are useful for measuring the posi compaction and movement, to glacier ice. tion of a glacier's terminus, thus permitting decadal-scale Long-term storage of water may occur in change~assessment studies. permafrost regions if the permafrost contains water in the SAR data of selected glaciers has been shown to form of ice. However, permafrost may be comprised of any be useful in measuring glacier area and terminus position material (e.g., rock, soil) that remains below DOC for two (Roti, 1980). However, there are not enough SAR data consecutive years or longer. available as yet for long-term studies of glacier area change. Remote sensing provides a regional and global At present, ERS-1 C-band SAR data are being acquired on a view for analysis of snow cover, glaciersj and lake and river regular basis and are useful for glacier studies (Jet ice. This chapter consists of a brief overview of remote PropulsIon Laboratory, 1989) as are the data currently sensing of land ice including glaciers, lake ice, and river being obtained from ]ERS-1 and ALMAZ. ice. The utility of remote sensing for permafrost studies is more obscure; however, some work has been done, espe 7.1.1.1 Glacierfacies studies using TM data cially in classification of vegetation in permafrost terrain The Landsat MSS and TM data have been useful for analy (Morrissey and Strong, 1986). sis of the glacier facies (Benson, 1962; Benson and Motyka, 1979) which may be interpreted to be indicative of glacier 7.1 Remote sensing of glaciers mass balance if studied over a period of years. The snow A glacier isanaccumu-lation of icea-nd snow -tha-thas line shows eleadyon a glacier using both the MSS and TM shown evidence of moving on land over a long-term data, and, when the snowline is visible at the end of the period. Glaciers cover about 10.8 per cent of the Earth's melt season, it corresponds to the glacier's equilibrium line land surface but only contain about 2.15 per cent of the which is the line above which the glacier has a net gain of Earth's water. However, glacier ice contains about 99 per mass over the year and below which there is a net mass cent of the Earth's surface freshwater (Baumgartner and loss (Paterson, 1981). Thus, the accumulation area ratio Reichel, 1975). The Earth's small glaciers (i.e., all glaciers (AAR) may be determined (Hall et aI., 1987). Other facies except the Greenland and Antarctic ice sheets), if melted/ boundaries may be detected in some cases (Williams et aI./ would raise sea level by 0.3 to 0.6 m (National Research 1991). Council, 1985), whereas most of the projected 70-80 m SAR data should be useful for detection of the potential sea-level rise due to melting of glacier ice is snowline and, because of its ability to penetrate the upper contained within the ice sheets. layers of snow and ice, may prove useful for locatingaddi A glacier/s annual mass balance is positive when tional facies boundaries Oet Propulsion Laboratory, 1989). the amount of snow that falls on the glacier exceeds the amount of ice that is lost through various ablation 7.1.2 Global atlas ofglaciers processes. A negative mass balance represents a situation The United States Geological Survey has initiated a long where less snow falls than melts, causing glacier thinning term project designed to proVide an inventory of available and ultimately terminus retreat. For small glaciers} even a images of present-day glaciers. This inventory of glaciers small change in mass balance may be noticeable/ whereas will consist of 11 chapters, eath published separately. mass balance changes in the ice sheets covering Greenland Internationally, more than 50 scientists are chapter co and Antarctica may not be apparent In the human lifes authors. Landsat data fram the mid-1970s represent the pan. The mass balance of glaciers has a direct effect on sea basic data source. When completed, this atlas will be a level, and the melting of the small glaciers of the world benchmark for future glacier studies. may have contributed up to 50 per cent of the water to the Three of the eleven chapters in Tize Satellite Image 10-15 em observed rise in sea level over the last century Atlas of Glaclers o{tlze World (Williams and Ferrigno, 1988; (Meier, 1984). 1989; 1991) have been published: Antarctica, Irian Jaya, Indonesia and New Zealand, and Glaclers of tlze Middle East 7.1.1 Glacier mass balance assessment and Africa. The Antarctic Ice Sheet contains an estimated Mass balance of glaciers may be studied using remote 13.9 x 106 km2 of ice or 91 per cent of the glacier ice on sensing. While glacier area change (including terminus our planet. Thus/ measurement and long-term monitoring movementL if large enough, may be assessed remotely, of the Antarctic lee Sheet is crucial to understanding global change in thickness of small glaciers cannot be measured climatology. The data shown in this chapter will function using remote sensing techniques at this time. However} as a standard reference of the Antarctic Ice Sheet's areal 18 CHAPTER 7 extent during the mid-1970s that can be compared with or thaw lakes of northern Alaska and thus \0 infer lake future satellite image maps and data of Antarctica. This depth on a regional basis. SAR data also proved useful for type of information is essential for global change stt;dies. distinguishing between those lakes that were frozen to the The second published Chapter of the Atlas details bottom and those lakes that were not frozen to the bottom some of the lesser known glaciers of the world in Irian at the time of maximum ice thickness, (Sellmann et aI., Jaya! Indonesia, and New Zealand. In New Zealand about 1975a; 1975b; Weeks et a1., 1978; 1981; Mellor, 1982). 3,155 glaciers are present along the crest of the Southern Lake ice thickness may also be assessed using passive Alps, South Island and six glaciers are present on Mt. microwave data (at a coarser resolution) (Hall et a1., 1981) Ruapehu, North Island. The total area covered is about and pulse radar techniques (Finklestein et a1., 1987). 1,159 km 2 (Williams and Ferrigno, 1989). Of three ice Thermal infrared imagery (Poulin, 1972) may also fields in Irian Jaya, all have experienced rapid retreat be useful in some cases to determine whether or not a lake during the 20th century. is frozen to the bottom. Lake ice underlain by water is The third chapter deals with glaciers in the Middle warmer than ice that is in contact with bottom sediments East and Africa. In Turkey, present-day glaciers are found in (Poulin, 1972). Wiesnet et a!. (1974) used NOAA-2 VHRR the hIgher elevations of the Eastern Black Sea Coastal Range, infrared digital data to develop a thermal map of Lake Erie in the Middle and South-eastern Taurus Mountains, and On ice conditions for 17 February 1973. The surface tempera Mounts Etciyas, Suphan and Agri. In Iran} glaciers are found ture of the ice is influenced by air and water temperature, in the Elburz Mountains} the Zagros Mountains, and Kuhha thermal conductivity of ice, and ice thickness and emissiv ye Sabalan. The glaciers in Iran are small and thus Landsat ity. In addition, in non-frozen lakes, surface water data are of limited utility for the detailed study of these temperature variations may correspond to different lake glaciers. In Africa, glaciers are found on two volcanoes, Mount depths (Strong, 1974). This information, acqUired in the Kenya in Kenya and Kilimanjaro in Tanzania, and one massif, summer, may be useful for lake bathymetry and ice thick the Ruwenzori, on the border between Uganda and Zaire. ness determination. While many of these glaciers are small, their presence and Other work on large lakes and estuaries shows the mass balance is important in terms of monitoring the health utility of Landsat data for classification of ice types and in of glaciers worldwide. The documentation of these glaciers, some cases to infer relative ice thickness (Foster et al., provided in the Satellite Image Atlas ofGlaciers ofthe World, is 1978; Leshkevich, 1982). especially important for these lesser known and poorly studied glaciers. Their documentation is especially important if rapid 7.2.2 River ice retreat in the future should cause them to melt completely. Landsat MSS and TM data provide adequate resolution for The other eight chapters will be published over analysis of river ice and riparian vegetation, but the repeat the next few years. There will be an introductory chapter cycle of the sensors is not suitable for imaging river ice that discusses the physical characteristics of glacier ice! the break-up regularly. Because river ice may break up rapidly, classification and global distribution of glaciers, and a a one-to-two day repeat cycle is required to monitor break chapter that presents information on related glaciological up patterns. Dey et a!. (1977) measured break-up patterns topics like global snOw cover. The remaining chapters will of the Mackenzie River in the Northwest Territories in discuss the glaciers of Greenland, Iceland, continental Canada using both NOAA-and Landsat-derived observa Europe, Asia, South America and North America. tions of break-up dates which compared quite favorably with field observations. Gatto (1990) used photo-interpre 7.2 Lake and river ice tation of Landsat-MSS, -TM, and -RBV images to produce ice conditions on the Allegheny, Monongahela, and Ohio 7.2.1. Lake ice Rivers in the central USA for the period 1972'1985. Lake ice in high latitudes may be of particular interest as Landsat-derived ice observations compared favorably with an indicator of regional and even global ciimate because it available ground and aerial observations 64~80 per cent of can be monitored for date of formation and melt each year. the time. The dates of freeze-up and break-up of lakes and lee jams may form during the break-up period lake ice thickness are very sensitive to air temperature when river waters rise beneath the ice cover thus breaking (Barry, 1984; Palecki and Barry, 1986). While the image the river ice into large ice floes. As the ice floes drift down resolution of Landsat TM and SPOT data is well suited for stream, they may become grounded on gravel bars or analysis of lake ice conditions, the repeat cycles of the meanders of the main river channel and block the flow of satellites are not adequate for determining the precise water, thus causing flooding upstream and on both sides of dates of lake ice build-up and dissipation (Hall, 1988). the river. Identification of ice jams in Alaskan rivers has However, Landsat data have been used for qualitative been accomplished using Landsat quick-look data (Miller determination of lake depth based on length of time that a and Osterkamp, 1978). lake ice cover remains intact. This, in turn! is related to Aufeis or overflow ice forms from water that has the maximum thickness of ice (Sellmann et a1., 1975a). flowed from a spring beneath a river in permafrost or Well timed aerial photography or daily acquisition of satel seasonally frozen ground. As the river ice freezes down~ lite data (I.e., SAR or even Moderate Resolution Imaging ward forcing the water in the bottom of the stream Spectrometer (MODIS») should permit such studies to be channel to the surface, an icing or aufeis may form on top accomplished from space. of the existing river ice. Aufeis may build extensively and In general, remote sensing of lake and river ice often forms in the same part of a river or stream each year, can be accomplished using relatively high resolution thus creating hazardous conditions if flooding results from sensors such as Landsat MSS and TM or SAR sensors. aufeis melting (Carey, 1973). Aufeis distribution may be Sellmann et a!. (1975a and 1975b) used Landsat and SAR studied using Landsat data (Harden et a1., 1977; Hall and imagery to analyse sequential melt of ice on the oriented Roswell, 1981). ICE ON LAND 19
References National Research Council, 1985. Glaciers, ice sheets, and sea Barry, R. G., 1984. Possible CO2-induced warming effects on level: effects of a CO2-induced climatic change, the cryosphere, in Climate Changes on a Yearly to report of a workshop held in Seattle, Washington, Millennial Basis, Edited by N. A. Morner and W. September 13-15, 1984, Ad Hoc Committee on the Karlen, D. Reidel, Hingham, Mass., pp. 571-604. Relationship between land Ice and sea level, Baumgartner, A. and Reichel, E., 1975. Die Weltwasserbilanz Committee on Glaciology, Polar Research Board, (World water balance), Oldenbourg, Munich. Commission on Physical Sciences} Mathematics, and Benson, C. S., 1962. Stratigraphic studies in the snow and lim of Resources, National Academy Press, Wash., D.C., 330 the Greenland Ice Sheet, Research Report 70, U. S. pp. Army Cold Regions Research and Engineering Palecld, M. A. and Barry, R. G., 1986. Freeze-up and break-up of Laboratory, Hanover} N. H. lakes as an index of temperature changes during the Benson, C. S. and Motyka, R. ]., 1979. Glacier-volcano interac transition seasons: A case study for Finland, IOllmal tions onMt. Wrangell, Alaska, in Geophysical Institute o(Climate and Applied Meteoroiogy, 25, pp. 893-902. Annual Report, 1977-1978, University of Alaska, Paterson, W. S. B., 1981, The Physics of Glaciers, Second Fairbanks, pp. 1-25. Edition, Pergamon Press, 380 pp. Carey, K. L., 1973. Icings developed from surface water and Poulin, A. 0., 1972. On the thermal nature and sensing of ground water, inCRREL Monograph 111-D3, 65 pp. snow-covered Arctic terrain, Ph.D dissertation/ McGill Dey, B., Moore, H. and Gregory, A. F., 1977. The use of satellite University! Montreal, Quebec. imagery for monitoring Ice break-up along the Rott, H., 1980. Synthetic aperture radar capabilities for glacier Mackenzie River, N. W. T., Arctic, 30, pp. 234-242. monitoring demonstrated with Seasat SAR data, Finkelstein, M.I., Mendelson} V.L., and Kutev, V.A., 1987. Radar Zeltschrift fur Gletscherkllnde llnd Glazlalgeoiogie, 16, sensing of stratified Earth's covers (in Russian), Soviet pp. 255-266. Radio Publishing House, Moscow, 174 pp. Sellmann, P, V,} Brown, L Lewellen, R. I., McKim} H. and Merry, Foster,]., Schultz, D. and Dallam, W. c., 1978. Ice conditions on c., 1975a. The classification and geomorphic Impli the Chesapeake Bay as observed from Landsat during cations of thaw lakes on the Arctic Coastal Plain, the winter of 1977, Proceedings of the 1978 Eastern Alaska, CRREL Research Report 334, U.S. Army Cold Snow Conference, Hanover, NH, pp. 89-104. Regions Research and Engineering Laboratory, Gatto, L. W., 1990. Monitoring river ice with Landsat images, Hanover/ NH. Remote Sensing of Environment, 32, pp. 1-16. Sellmann, P. V., Weeks, W. E Weeks, and Campbell, W. J., 1975b. Hall, D. K. and Roswell, c., 1981. The origin of water feeding Use of side looking airborne radar to determine lake icings on the eastern North Slope of Alaska, Polar depth on the Alaskan North Slope, U.s. Army Cold Record, 20,pp. 433-438. Regions Research and Engineering Laboratory! Hall, D. K., Foster,]. L., Chang, A. T. c., and Rango, A., 1981. Hanover, NH, CRREL Special Report 230, 6 pp. Freshwater ice thickness observations using passive Strong, A. E., 1974. Great Lakes temperature maps by satellite, microwave sensors, IEEE Transactions on Geoscience Proceedings of the 17th Conference on Great Lakes and Remote Sensing, GE.19, pp. 189-193. Research} International Association -for Great Lakes Hall, D. K., Bindschadler, R. A., Ormsby,]. P., and Siddaligaiah, Research, Ann Arbor, Michigan, pp. 321-333. H" 1987. Characterization of snow and ice reflectance Weeks, W. E, Fountain, A. G., Bryan, M. L., and Elachi, c., 1978. zones ofglaciers using Landsat Thematic Mapper data, Differences in radar return from ice-covered North Annals of Glaciology, 9, pp. 104-108. Slope lakes, IOllmal o(Geophysical Research, 83(C8), pp. Hall, D. K., 1988. Assessment ofpolar climate change using satel 4069-4073. lite technology, Reviews o(Geophysics, 26, pp. 26-39. Weeks, W. F., Gow, A.]., and Schertler, R.]., 1981. Ground-truth Harden, D., Barnes, P. and Reimnitz, E., 1977. Distribution and observations of ice-covered North Slope lakes imaged
character of naleds in northeastern Alaska, Arctic l 3D} by radar, U. S. Army Cold Regions Research and pp. 28-40. Jet Propulsion Laboratory, 1989. Science Engineering Laboratory, Hanover, NH, Report 81-19.
plan for the Alaska SAR Facility, ]PL Publications 89-14, Wiesnet! D. R.} McGinnis, D. F.} and Forsyth, D. G. t 1974. 87pp. Selected satellite data on snow and ice in the Great Leshkevich, G. A., 1981. Categorization of northern Green Bay Lakes Basin, 1972-73, Proceedings of the 17th ice cover using Landsat-1 digitai data - a case study, Conference on Great Lakes Research! International NOAA Technical Memo. ERL GLERL-33. Association for Great Lakes Research, Ann Arbor! Meier, M. E, 1984. Contributions of small glaciers to global sea Michigan, pp. 334-347. level, Science, 226, pp. 1418-1421. Wiliiams, R. S., Jr., Hall, D. K. and Benson, C. S., 1991. Analysis Mellor,]. C., 1982. Bathymetry of Alaskan Arctic lakes: Akey to of glacier facies using satellite techniques, Journal of resource inventory with remote sensing methods} Glaciology, 37(125), pp. 120-128. Ph.D dissertation, University of Alaska, Fairbanks, AK. Williams, R. S., ]r., and Ferrigno, J. G. (ed.) 1988. Satellite Image Miller, J. M. and Osterkamp, T. E., 1978. The use of Landsat data Atlas of Glaciers of the World: Antarctica, USGS to minimize flooding risks caused by ice jams in Professional Paper 1386- B, 278 pp. Alaskan rivers, in Proceedings of the Twelfth Williams, R. S., ]r., and Ferrigno,]. G., 1989. Satelllte Image International Symposium on Remote Sensing of Atlas of Glaciers of the World: Irian]aya, Indonesia, Environment, Vol. III, Ann Arbor, MI, pp. 2255-2266. and New Zealand, USGS Professional Paper 1386-H, Morrissey, LA. and Strong, L. L., 1986. Mapping permafrost in 48pp. the boreal forest with Thematic Mapper satellite data, Williams, R. S., ]r., and Ferrigno,]. G., 1991. Satelllte Image Photogrammetric Engineering and Remote Sensing! Atlas of Glaciers of the World: Middle East and 52, pp. 1513-1520. Africa, USGS Professional Paper 1386-G, 70 pp. CHAPTER 8
SURFACE WATER
The surface area of freshwater streams, rivers, lakes, and sediments. Sateiiite scanner data and aerial photography reservoirs constitutes a relatively small portion of the in the 0.4-0.6 pm spectral range can be used (Ibrahim and Earth's surface in comparison to the area of marine and Cracknell, 1990). Aerial dual-laser systems have also been terrestrial resources. Yet the importance of freshwater to used to measure water depth. For the dual-laser system, mankind for consumption, commerce, recreation} and wavelengths are chosen so that one wavelength (usually aesthetics is far greater than just area. Freshwater may in between 0.6 and 1.0 pm) is reflected by the surface water the future become a key limiting factor to economic while the second wavelength (usually between 0.4 and 0.6 growth worldwide as it already is now in certain localities. pm) penetrates the water and is reflected by the bottom Surface waters are subject to wide variations due to sediments. The difference between the two laser measure episodic events in hydrological, biological, and chemical ments is water depth. Water depths up to 50 m can be cycles. The size and distribution of surface water across the measured with a dual-laser system (Penny et aI., 1989). landscape is not uniform, making monitoring of these Water clarity (colour, turbidity, suspended sediments, and waters for quantity and quality difficult, time consuming, chlorophyll) will limit the application of optical tech and expensive using field methods. Remote sensing tech niques for measuring water depth. niques offer the potential to monitor the landscape effectively and efficiently to locate surface water and to 8.1.4 Temperature measure parameters related to surface water location! quan Remote sensing measurements of emitted thermal infrared tity, and quality. and microwave radiation can be used to estimate surface water temperatures. Aircraft measurements of thermal 8.1 Measurements infrared and microwave radiation data have been used to measure surface water temperature and to map thermal 8.1.1 Water surface area flows from dams and power plants. Thermal infrared radia The measurement of surface water area is an operational tion measurements from sateiiites such as Landsat TM and technique with image! scanner, or radar data. Wavelengths the NOAA-AVHRR have also been used to measure surface in the near infrared provide the best data for delineating water temperature (Gibbons et aI., 1989). Highly accurate the land-water interface. Flood waters can be mapped temperature measurements are possible when the effect of with the same techniques (McKim et aI., 1972; Rango and atmospheric attenuation can be corrected. Microwave esti Anderson, 1974; Barton and Bathols, 1989; Blasco et aI., mates of water surface temperature are less dependent on 1992). However, windows of opportunity during flood atmospheric conditions but provide coarser resolution periods may be limited due to clouds, rain, or other than thermal infrared data (Shutko, 1985; 1986). inclement conditions which would limit remote sensing techniques for Viewing the Earth!s surface. Opportunity 8.1.5 Salinity and mineralization for flood monitoring will also be limited by the time of the It has been shown by theoretical studies and demonstrated satellite overpass. SAR data has the potential for estimat by experiments in laboratories and on aircraft platforms ing flood extent during cloudy weather. With an available that microwave radiometry can be used to measure salinity spatial resolution of 20 m and up from different satellites, and general mineralization of water (Shulko, 1985; 1986; choice of satellite data will depend on the minimum size of 1987). This application makes use of sensitivity of surface water area that needs to be mapped to meet project microwave emissivity to water conductivity variations needs. Smaller surface areas can be mapped with aircraft caused by changes in concentrations of salts, acids, and data (Hilton, 1984). other chemicals including waste water outflows. In addi tion to measurements of microwave brightness 8.1.2 Water stageflevel temperature measurements, actual physical water tempera The measurement of ocean water level has been studied tures must be estimated by thermal infrared techniques. using radar altimeter data from satellites (Ridley, 1989; For obtaining quantitative estimates of salinity and miner Minster et aI., 1991). Such measurements from sateiiites alization} measurements have to be conducted at require accurate information on the satellite position and microwave wavelengths of 10 cm or longer (Shutko, 1985; atmospheric conditions. These satellite measurements are 1986; 1987). This approach works best where there is a only applicable for large water surfaces due to spatiai reso strong contrast in the salinity, such as in coastal regions. lution. Laser profiling techniques from airplanes can be used to measure water stage accurately. With accurate 8.1.6 Pollutants knowledge of the altitude of the airplane using Global A wide variety of natural and manmade pollutants can Positioning System (GPS) navigation, accurate water stage affect the quality of surface water. It is important to can be measured. If GPS navigation is not available, then acquire data about these pollutants so that knowledgeable water stage can be determined with laser profiling by actions can be taken that will improve the quality of measuring a site of known elevation and relating water surface water. Remote sensing methods can be used to stage elevation to the known elevation. measure surface water quality parameters (Ritchie et aI., 1990) which change the amount of reflected solar radia 8.1.3 Water depth tion. Suspended sediments and chlorophyll are the major Water depth has been measured by remote sensing using pollutants that affect water quality and also affect the measurements of visible radiation reflected from bottom amount of reflected solar radiation. Colour and oil are SURFACE WATER 21 other pollutants that may affect reflectance. Other pollu 8.1.6.4 Vegetation above water surface tants affecting water quality such as nutrients and Airborne microwave radiometers, operating at centimeter and pesticides do not directly affect reflected solar radiation. decimeter wavelengths, may be used to detennine some char They may indirectly affect reflected solar radiation from acteristics of vegetation above the surface of various water surface water by their interactions with chlorophyll bodies. Biomass and density of the vegetation can be deter producing organisms. mined in river deltas, marshy wetland areas} and rice fields (Shutko, 1986; 1990; Gross et aI., 1987). 8.1.6.1 Suspended sediments Table 3 presents a summary of remote sensing Suspended sediments can be estimated from reflected solar observations of surface water with the appropriate sensors. radiation measurements made between 0.6 and 0.8 )lm. In general, reflectance is a nonlinear function of concentra tion of suspended sediments with maximum reflectance TABLE 3 dependent on wavelength and suspended sediment Remote sensing observation of surface water concentration. At wavelengths from 0.6 to 0.8 )lm, reflectance is nearly linear with suspended sediment concentrations below 200 mg/1. Because turbidity and Observation Sensor Application suspended sediments are closely linked in most water bodies (but not all), estimates of turbidity can also be Area Images Quantity made. Both satellite and aircraft scanner data can be used Scanners (VIS & JR) Floods to estimate suspended sediments (Curran and Novo, 1988). Radar Productivity Scanner data could be used to develop a monitoring Stage Precision Radar Floods program to follow changes in suspended sediments. Alimi Altimeters, Lasers Power Generation tation on the use of this technique is the need to collect Runoff field data to calibrate the relationship between suspended sediments and reflectance. Current indications are that Depth Scanners (VIS NaVigation calibration curves are not time dependent and may be Lasers applicable to regional areas (Ritchie and Cooper, 1991). Scanner data can be used without calibration data to map Temperature Thermal IR Productivity relative suspended sediment concentrations in river Microwave Radiometers Evaporation plumes and draw conclusions about sediment deposition Water Quality patterns in lakes and estuaries. Some examples of Salinity Microwave Radiometers Water Quality suspended sediment measurements from airplanes up to 50 mgllare given by Gitelson et al. (1988) and Shutko (1990). Sediments Scanners (VIS & JR) Sediment Deposition Productivity 8.1.6.2 Chlorophyll Nutrient Loads Concentration of chlorophyll can also be estimated using Water Quality aircraft or satellite scanner data (Gitelson et aI., 1987; Shutko, 1990; Strumph and Taylor, 1988). Again, calibra Chlorophyll Scanners (VIS & IR) Productivity tion data are needed to quantify the relationship between Laser Water Quality chlorophyll and reflectance. Estimates of chlorophyll in Other Pollutants Scanners (VIS & IR) Water Quality oceans and estuaries have been made using data from the Lasers CZCS, AVHRR, and other satellite scanners. Current satel lite scanners proVide only broad wavelength data that may be useful to determine chlorophyll in surface waters with VIS = visible low (<25 mg/l) suspended sediments. At higher suspended IR :::: infrared sediment concentrations, the reflectance from suspended sediments will mask the chlorophyll reflectance in these broad wavelengths making estimates of chlorophyll very References difficult (Ritchie et aI., 1992). Future satellite scanners Acklesoll, S. G. and Klemas} V'I 1987. Remote sensing of with higher spectral resolution may make it possible to submerged aquatic vegetation in Lower Chesapeake determine chlorophyll in the presence of suspended sedi Bay: A comparison of Landsat MSS to TM imagery, ments. Using the same principles, macrophytes and other Remote Sensing of Environment, 22, pp. 235-248. aquatic vegetation in surface water can be mapped Barton, I.]. and Bathois, J. M., 1989. Monitoring floods with (Ackleson and Klemas, 1987). AVHRR, Remote Sensing of Environment, 30, pp. 89 94. 8.1.6.3 Other pollutants Blasco, F., Bellan, M. F. and Chaudhury, M. D., 1992. Oil spill detection and monitoring on surface waters using Estimating the extent of floods in Bangladesh using scanner, laser, or radar data are operational programmes SPOT data, Remote Sensing of Environment, 39, pp. (Cross, 1992). Remote sensing programmes using aircraft 167-178. scanners and cameras are used routinely to follow the fate Carder, K. L.} Hawes/ S, K.} Baker, K. A.} Smithl R. c.} Stewart, of oil spills in surface water. Changes in water colour due R. G., and Mitchell, B. G., 1991. Reflectance models to natural organic chemicals may change reflectance for quantifying chlorophyll a in the presence of (Carder et aI., 1991; Davies-Colley et aI., 1988). Remote productivity degradation products, Joumal of sensing of these colour changes requires high spectral reso Geophysical Research, 96, pp. 20599-20611. lution data. 22 CHAPTERS
Cross/ A. M" 1992. Monitoring marine oil pollution using Penny, M. F., Billard, B., and Abbot, R. H., 1989. LADS-the
AVHRR data: observations off the coast of Kuwait Australian Laser Airborne Depth SounderJ and Saudi Arabia during]anuary 1991, International International Journal o{Remote Sensing, 10, pp. 1463 Journal ofRemote Sensing, 13, pp. 781-788. 1479. Curran, P. ]. and Novo, E. M. M., 1988. The relationship Rango, A. and Anderson, A. T., 1974. Flood bazard studies between suspended sediment concentration and in the Mississippi River basin using remote remotely sensed spectral data: A review, Journal of sensing, Water Resources Bulletin, 10, pp. 1060 Coastal Research, 4, pp. 3S1-368. 1081. Davies-Colley, R.]., Vant, W. N., and Wilcock, R.]., 1988. Lake Ridley, J. K, 1989. The topography and surface characteristics water color: Comparison ofdirect observations with of the Larson Ice Shelf Antarctica, using satellite
underwater spectral irradiancel Water Resources altimetry, Journal ofGlaciology, 35, pp. 299-310. Bulletin, 24, pp. 11-18. Ritchie,]. C. and Cooper, C. M., 1991. An algorithm for using Gibbons, D. E., Wukelic, G, E., Leighton,]. P., and Doyle, M. Landsat MSS for estimating surface suspended sedi ]., 1989. Application of Landsat thematic mapper ments, Water Resources Bulletin, 27, pp. 373-379. data for coastal thermal plume analysis at Diablo Ritchie,]. c., Cooper, C. M. and Schiebe, E R., 1990. The reia Canyon, Photogrammetric Engineering and Remote tionship of MSS and TM digital data with suspended Sensing, 66, pp. 903-909. sediments} chlorophyll, and temperature in Moon
Gitelson, A. A" DubovitskYI G. A' I Keydant G. p'} and Lake} Mississippi, Remote Sensing of Environment, Lopatchenko, 1. 1., 1988. Evalualion of water ecosys 33, pp. 137-148. tem quality by its radiation in the visible spectrum Ritchie,]. C., Schiebe, E R., Cooper, C. M. and Harrington,]. (in Russian)/ in: Ecological standardization and A., ]r., 1992. Landsat MSS studies of chlorophyll in modelling of anthropogeneolls influence on water sediment dominated lakes, Proceedings of lGARRS ecosystems, Rastov-on-Don, Hydrochemical '92 Symposium, Vol. 11, Clear Lake City, TX, pp. Institute, Leningrad, pp. 101-135. 1514-1S17. Gross, M. F., Hardisky, M. A., Klemas, V., and Wolf, P. 1., 1987. Shutko, A. M., 1985. Radiometry for farmers, Science in the Quantification of biomass of marsh grass Sparlina USSR, No.6, pp. 97-113. alterniflora Loisel using Landsat thematic mapper Shutko, A. M., 1986. Microwave Radiometry of Water Surface imagery, PhotQgrammetric Engineering and Remote and Grounds, NaukaJScience Publishing House, Sensing, 53, pp. 1577-1583. Moscow, 190 pp. Hilton,]., 1984. Airborne remote sensing for freshwater and estu Shutko, A. M., 1987. Remote sensing of the waters and lands arine monitoring, Water Research, 18, pp. 1195-1223. via microwave radiometry (the principles ofmethod, Ibrahim, M. and Cracknell, A. P., 1990. Bathymetry using problems feasible for solving, economic use), in: Landsat MSS data of Penang Island in Malaysia, Remote Sensing and Its Impact on Developing International Journal of Remote Sensing, 11, pp. 557 Countries, Pontificia Academia Scientiaruffi/ Scripta 560. Varia-68, Vatican City, pp. 413-441. McKim, H. 1., Marlar, T. L.and Anderson, D. M., 1972. The Shutko, A. M., 1990. Offer on hardware, software and services use of ERTS-l imagery in the national program for on survey of soil, vegetation, and water areas from inspection of darns, CRREL Special Report 183, U.S. aircraft, Institute of Geoinformatics, Nongovern Army Cold Region Research and Engineering mental Center for Research and Institute of Laboratory, Hanover, New Hampshire. Radioengineering and Electronics, Academy of Minister,]. E, et aI., (20 other authors), 1991, Satellite altime Sciences, USSR, IGl, IRE, Moscow, 16 pp. try observations of ocean dynamic topography, Strumpf, R. P. and Tyler, M. A., 1988. Satellite detection of International JOllrnal ofRemote Sensing, 12, pp. 1619 bloom and pigment distribution in estuaries] 1930. Remote Sensing of Environment, 24, pp. 38S-404. CHAPTER 9
BASIN CHARACTERISTICS
9.1 Basin characteristics and inventory which they compared conventional methods with severai methods types of remotely sensed data on a number of watersheds The drainage basin is the basic areal unit in which various in the United States. They found that watershed area, physiographic features can be measured and studied. The shape, and channel sinuosity estimates from Landsat measurement of these watershed characteristics is impO[M images at a 1:100,000 scale were comparable to data tant because they are intimately related to basin water obtained from 1:62,500 scale topographic maps, partIcu yield and sediment load. Physiographic parameters larly In well-dissected terrain with moderate vegetation. In measurable from space platform include stream order, fiat terrain or heavily forested areas, results were compara stream length, basin area, basin shape, drainage density, ble to 1:250,000 scale maps (Salomonson, 1983). drainage pattern, and stream sinuosity or meander wave The drainage system is controlled by the slope of length. Additional drainage basin parameters such as the the surface and the type of underlyIng rock (Travaglia, percentage of the basin in forests, swamps, surface water, 1989). One of the easiest physiographic features to iden open area, and urban or impervious area can also be delin tify using satellite imagery is the drainage area of a eated from high resolution satellite imagery and are watershed. Divides between adjacent watersheds demar valuable in characterizing the hydrologiC response of a cate differences in drainage direction which can be readily basin. The physiographic and associated land use informa observed from most Earth resources-type satellites. tion thus extracted is suitable for use in mean annual Drainage density, which is the number of stream streamflow and/or mean annual flood regression models channels per unit area, -can be extracted adequately in and can also be u.sed to calculate basic information neces those areas where the landscape is sufficiently dissected to sary for the calibration of watershed models which permit detailed drainage mapping. Dissected areas provide simulate daily discharge (Rango et aI., 1975). belter contrast and thus belter detaIl than non-dissected Mapping of basin characteristics using satellite areas. For the most part these areas are characterized by data has been accomplished since the early 1970s. Using moderate or high relief, non-glaciated landscapes, and satellite based electro-optical systems, scales of up to resistant, impermeable lithologies. Local relief of approxi 1:50,000 may be obtained (Doyle, 1984). Due to the mately 90 m or more between basIn divide and valley stereoscopic capabilities of the SPOT satellite and the high boltom In watersheds less than 2600 kmz usually provides spatial resolution of its sensors (10 m), the smallest errors enough contrast to accurately map the drainage network achieveda-re now 5-20 -In in both the -vertical-and horizon from hIgh resolution satellite imagery. An exception to tal planes. For economic reasons, however, the most this was found in ridge and valley topography where suitable scales are those of 1:100,000 to 1:250,000. It adequate local relief existed, but where most stream devel should -be stressed that increasing spatial resolution means opment has occurred on the flat, wide valley floor. increased amounts of data and processing costs, and so for Drainage areas which were once covered by glacial ice each task the spatial resolution must be selected carefully. often exhibit a lack of structural and bedrock control as For watersheds larger than 10,000 km2, data from polar well as a lack of drainage patterns with a significant degree orbiting satellites having reduced resolution capabilities of integration or dissection. Streams which encounter are more practical (Tarpley, 1984). resistant rocks tend to form valleys with steep slopes Perhaps the most widely used type of remotely regardless of the climate, and landscapes of this type are sensed data for land cover in water-resources studies is that conducive to physiographic mapping from high resolution obtained within the visible and near infrared region of the space sensors (Rango et aI., 1975). spectrum. One reason for choosing this type of data is that The inspection of seasonal data over a given it is relatively easy to interpret since the energy that is watershed greatly increases the chances that detailed sensed is reflected energy (Salomonson, 1983). drainage network information can be extracted. For The spectral resolution attainable with scanners example, during times of minimum leaf coverage, snow make their data more suitable than cameras for various often enhances tributaries which may be difficult to mapping and inventory purposes. Scanning sensors with discern during the summer season. wavelengths ranging from shortwave visible data to long· Drainage patterns can provide useful information wave microwave data are either currently in orbit or concerning rock and soil relationships and landform asso planned for launch in the 1990s. The all-weather, day ciations. For instance, radial drainage patterns are usually night capability of mIcrowave data is especially indicative of resistant rocks and are associated with volca advantageous and results of experimental inventories using noes and other domelike structures (see Table 4). radar (active microwave) data are quite favorable (Brisco et Additionally, bifurcation ratios and drainage textures can aI., 1983; Foster and Hall, 1981). But a better understand be useful In assessing permeabIlity of the soli and bedrock. ing of how microwaves respond and react to different For example} coarse drainage textures suggest resistant, kinds of media is needed before these data can be utilized permeable bedrock materials. In coarse drainage systems in an operational way. the first-order streams are farther apart than they are for Drainage network information is generally medium and fine drainage textures (Travaglia, 1989). obtaIned from topographic maps, which are usually out-of Of the Earth resources satellites which are date. Remote sensing; due to its more current nature, can currently operating, the SPOT satellite system with its often provide better and more reliable information than stereoscopic viewing capabilities and superior resolution these maps. Rango et al. (1975) reported on a study in (10 m) provIdes excellent mapping detail of drainage area 24 CHAPTER 9
TABLE 4 Major drainage patterns and associated characteristics
Drainage Configuration Occurrence LotJd{oml pattem (rock and soil relationship) association
Dentritic Tree-like branching tributaries Homogeneous, uniform rock and soil Soft, sedimentary, volcanic join the mainstream at acute angles materials tuff, deposits of glacial till, and old dissected coastal plains
Trellis Modified dentrific with parallel Indicative of bedrock structure rather Tiltred interbedded tributaries converging at right angles than material of bedrock sedimentary rock; main parallel channels follow strike of beds
Parallel Major tributaries parallel major Homogeneous, gentle, uniformly sloping Young coastal plains and streams and join the mainstream surfaces whose main streams may large basalt flows at approximately the same angle indicate a fault or fracture zone the same angle
Radial Circular network of approximately Usually indicative of resistant materials Volcanoes, isolated hills and parallel channels floWing away from with regard to the local environmental domelike structure a central high point conditions
Annular Concentric network of channels Layered, jointed and fractured bedrock, Granitic and sedimentary domes floWing down and around a central control the pattern high point
(Source: Way, 1973) and density. The Landsat TM has greater spectral range 2. Impervious areas. Urban areas affect the hydrol" than the SPOT system which compensates for its coarser ogy at local scales by concentrating and resolution (30 m). enhancing runoff. Jackson (1975) developed a procedure for estimating the percentage of imper 9.2 Land use information vious area directly from Landsat data. Using data Basin land use inventories are needed to improve surface from a period when most pervious covers had a runoff and streamflow estimates. Some of the most impor high ratio of near infrared response to visible tant land use types are listed below. response, he formulated an· exponential equation 1. Floodplains and wetlands. Identification and using the ratio between Landsat bands 7 and 4.
mapping of flood-prone areas or floodplains are crit Basically, impervious coversl excluding bare soils, ical for emergency preparedness and for flood have low ratios and pervious covers have high insurance evaluation. Flood-inundation mapping ratios. Mixtures fall in between these low and using remotely sensed imagery has been successful high ratios. on many rivers and in different regions using visible 3. Vegetation cover. Vegetation which for the most data and, to a limited degree, thermal infrared and part absorbs visible light but reflects near-infrared radar data. Distinctive changes induced by addi light can be detected and classified on multispec tional water in an area facilitate the mapping of tral imagery. Coniferous forests can be floods. These include increased soil moisture, mois distinguished from deciduous forests during the ture-stressed vegetation, and standing water, all of winter season. Forested areas versus non-forested which result in reduced reflectivity in the visible areas can be most easily discriminated on snow wavelengths that lasts up to two weeks after an event covered scenes since the forest canopy conceals (Salomonson, 1983). the underlying snowpack. Grasses and crops typi Wetlands are an essential component of the hydro cally exhibit spectral signatures which facilitate logic system. Increased pUblic concern over the their identification. The density and height of a environment in recent years has led to the enaction forest stand have been estimated with an accu of national, state, and local legislation for the protec racy of between 60 and 70 per cent using SPOT tion of both inland and coastal wetlands. panchromatic data (DeWulf et aI., 1990). Most large-scale applications involve delineation of A global vegetation index has been prepared the wetlands in terms of the upland boundary and using the visible and near infrared bands on the NOAA mean high-water mark, as well as the major species of series of satellites which is especially useful in determining vegetation. Generally, the vegetation is used to iden vegetation type and vigor (Tarpley et aI., 1984). The spec tify the boundaries since the species of vegetation is tral reflectance of chlorophyll pigment in the visible and usually indicative of the depth and duration of inun near infrared part of the spectrum provides a means of dation (Carter and Schubert, 1974). Because of the monitoring density and rigor of green vegetation. importance of vegetation identification} most appli Chlorophyll in green leaves has a reflectance in the 0.58 cations require the use ofseasonal multispectral data 0.68 ].lm spectral interval (Channell) of less than 20 per that include visible and near infrared measurements cent but a reflectance of about 60 per cent in the 0.73-1.10 (Salomonson, 1983). ].lm spectral range (Channel 2). The differential reflectance BASIN CHARACTERISTICS 25 in these bands has been widely used to derive a simple when conditions were optimum. However, the SAR pene index of the form VI = Ch2 - Ch1 where Ch2 is the trates clouds and snow, and data can be acquired day or reflectance in Channel 2, ChI is the reflectance in Channel night. Drainage density detail is good on SAR imagery 1 and VI is the resulting vegetation index. The denser and because individual streams show up well due to riparian greener the plant canopy, the greater the vegetation index. vegetation causing higher radar reflections which results The resolution of the NOAA sateliites (1 km in Channell) from the IIrough" surface which vegetation creates (Foster probably limits the use of this vegetation index to basins and Hall, 1981). larger than about 1000 km2. Passive microwave systems such as the Scanning In addition to the above-mentioned basin charac Multi-spectral Microwave Radiometer (SMMR) on the Nimbus teristics, hydrologIcally important phenomena such as 7 spacecraft cannot currently achieve adequate resolution for desertification, erosion, sedimentation and forest fires can mapping watershed features. But, for basins larger than also be monitored by remote sensing methods. For hydro 10,000 km2, the snow cover areal extent and snow water logical modelling, information on basin characteristics is equivalent can be estimated using algorithms which account clearly needed and has been found to improve the results for the scattering of microwave radiation (at 37 and 18 GHz) when included (Rango et aI., 1983). by snow crystals (Rango et aI., 1989). This information is useful for forecasting streamflow in the spring for mountain 9.3 Other spectral applications ous watersheds where seasonal snowpacks form. 9.3.1 Thermal infrared data 9.4 Geographic information systems Although most physIographic mapping of drainage basins To derive the basin characteristics using remote sensing has been accomplished using visible datal thermal infrared techniques, data must be reduced, processed, and inter and microwave technologies have also been explored. preted. For optimal benefits and for future inventories of Digital infrared data have been analysed to corre basin characteristics, utilization of a geographic informa~ late sateliite-derlved temperatures with local topography. tion system (GIS) is recommended. The ultimate value of a The thermal infrared channel (10.S-12.5 I'm) on the GIS, in regard to the watershed, lies in its ability to orga NOAA-5 sateliite was employed to delineate topographical nize and input data for models that simulate hydrological features In North and South Dakota in October 1977 processes. Such systems or models can be used interac (Schneider et aI., 1979). tively for analysing trends or for predicting consequences Differences in temperature between wet and adja of planning decisions. GIS allow remotely sensed data to cent drier ground permits the delineation of terrain be geocoded for specific basins or sub-areas. A scheme for features such as hills, escarpments, glacial moraines, processing physiographic precipitation and evaporation drainage networks and north and south-facing river valley data for the purpose of hydrological forecasts is discussed slopes on nighttime thermal infrared imagery. by Fortinet ai. (1986). On an image taken on 19 October 1977 at 2106 Although in most GIS remote sensing inputs do (local time), radiative cooling of the ground allowed the not represent the primary source of data, they do represent surface moisture to stand out thermally. Bodies of water a potential source of new data elements for the GIS, or an appear warm due to their relatively high thermal inertia alternative form of data capture for one or more well (thermal inertia being defined as resistance to temperature defined data elements currently incorporated within the change). This inertia results in water retaining its daytime GIS. As such, the problems of integration of remote heat longer than the surrounding terrain, thus appearing sensing inputs are judged by GIS operators largely on the warmer at night. North-facing slopes of river valleys, being basis of the efficiency and ease of utilization of remote in shadow much of the day, receive less incoming solar sensing data as compared to more conventional data, such radiation than south-facing slopes and, therefore, retain as maps (Marble and Peuquet, 1983). However it appears moisture in the soil longer. The soil moisture disparity that any effort in modifying or designing models to be leads, in turn, to a difference in thermal inertia between compatible with remote sensing data is easily justified on north and south-facing slopes and gives rise to the shaded the basis of potential improved simulation accuracies and a relief effect. The utility of NOAA data for thermal physio better understanding of physical processes. graphic mapping is likely to vary depending on the time of the day and the season of the year. Cannon (1973) found References that nighttime thermal infrared imagery provided more Brisco, B., Ulaby, F. T. and Dobson, M. C., 1982. Spaceborne drainage "information than imagery taken at mid~morning SAR data for iand-cover classification and change or mid-afternoon. detection, Proceedings of the lGARSS '82 Symposium, San Francisco, CA, Digest Vol. I, PS-2, 9.3.2 ~icrolVavetiata pp. 1.1-1.8. Active microwave sensors such as SAR and radar altimeters, Cannon, P. L., 1973. The application of radar and infrared because of the high resolution these systems can achieve, imagery to quantitative geomorphic investigations, can also be used for detailed watershed mapping. Proceedings of the Second Annual Conference on In a study in 1981, SAR imagery of the Wind Remote Sensing of Earth Resources, Tullahoma, River Range area in Wyoming was compared to visible and Tennessee, pp. 503-S27. near-infrared imagery of the same area (Foster and Hall, Carter, V. and Schubert, ]., 1974. Coastal wetlands analysis 1981). Data from the Seasat L-Band SAR and aircraft X from ERTS MSS digital data and field spectral Band SAR were compared to Landsat Return Beam Vidicon measurements, Proceedings of the Ninth (RBV) visible data and near-infrared aerial photography International Symposium on Remote Sensing of and topographic maps of the same area. Visible and near EnVironment, Environmental Research Institute of infrared data proVided more information than the SAR data Michigan, Ann Arbor, Michigan, pp. 1241-1260. 26 CHAPTER 9
DeWulf, R. R.} Goossens, R. E., DeRoover, B. P' I and Borry, EC. I Rango} A" Martinec} J'/ Chang, A' I Foster, J. and van 1990. Extraction of forest stand parameters from Katwijkl V., 1989. Average areal water equivalent panchromatic and multispectral SPOT· 1 data, of snow on a mountainous basin using International Journal ofRemote Sensing, Vol. 11(9), pp. microwave and visible data, IEEE Transactions on 1571·1588. Geoscience and Remote Sensing, GE·27(6), pp. Doyle, F. J., 1984. Surveying and mapping with space data, 740·745. ITC Journal, 1984·1, pp. 314·321. Salomonson, V. V;J 1983. Water Resources Assessment, in Fortin, J. P., Villeneuve, J. P., Guilbot, A. and Seguin, B., 1986. Manual of Remote Sensing, (R. N. Colwell, Editor· Development of a modular hydrological forecasting in·Chief), American Society of Photogrammetry, model based on remote sensed data for interactive Sheridan Press, Falls Church, Virginia. Vol. Z, pp. utilization on a microcomputer, Hydrologic 1497·1570.
Applications of Space Technology, lAHS Publication Schneiderl S. R., McGinnis;. D. F., and Pritchardl J. A' I 1979. No. 160, pp. 307·319. Delineation of drainage and physiographic Foster, J. L. and Hall, D. K, 1981. Multisensor analysis of features in North and South Dakota using NOAA· hydrologic features with emphasis on the Seasat 5 infrared data, in Satellite Hydrology (Edited by SAR, Photogrammetric Engineering and Remote M. Deutsch, D. Wiesnet and A. Rango), American Sensing, Vol 47(5), pp. 655·664. Water Resources Association, Minneapolis, Jackson, T.J., 1975. Computeraided techniques for estimating the Minnesota, pp. 324·329. percent ofimperviolls area from Landsat data, Tarpley, J. D., 1984. Monitoring global vegetation from Proceedings of the Workshop on Environmental meteorological satellite data, Proceedings of the Applications of Multispectral Imagery, American Society 18th International 'Symposium on Remote of Photogrammetry, Ft. Belvoir, Virginia, pp. 140·155. Sensing of Environment, Environmental Research Marble, D. and Peuquet, D., 1983. Geographic Information Institute of Michigan, Paris, France, pp. 773·784. Systems and Remote Sensing} in Manual of.Remote Tarpley, J. D., Schneider, S. R., and Money, R. 1., 1984. Sensing, (R. N. Colwell, Editor·in·Chief). American' Global vegetation indices from the NOAA·7 mete· Society of Photogrammetry, Sheridan Press, Falls orological satellite, Journal ofClimate and Applied Church, Virginia, Vol. 1, pp. 923·958. Meteorology, 23, pp. 491·493.
Rango, A' I Foster! J. and Salomonsollj V. V., 1975. Extraction Travaglia, C., 1989. Drainage analysis, in Remote Sensing and utilization ofspace acqUired physiographic data Applications to Land Resources, Report of the for water resources development, Water Resources 14th UN/FAD International Training Course in Bulletin, 11(6), pp. 1245·1255. cooperation with the Government of ItalYI Rome, Rango, A., Feldman, A., George III, T. S. and Ragan, R. M., 1983. Italy, RSC Series 54, pp. 101·106. Effective use of Landsat data in hydrologic models. Way, D. S" 1973. Terrain Analysis, Dowden, Hutchinson, Water Resources Bulletin, 19(2), pp. 165·174. and Ross Oohn Wiley and Sons), Stroudsburg, PA. CHAPTER 10 REMOTE SENSING INPUTS FOR HYDROLOGICAL MODELS
Hydrological models, for the most part, have not taken regression model that is based on Barrett's (1970) indexing advantage of potentially valuable new data in the form of technique. The cloud area and temperature are the satel remote sensing products. The principal reason for this is lite variables used to develop a temperature weighted cloud that the models have been designed to use traditional cover index. This index is then transformed linearly to point data, or at best map data, and not the spatial data mean monthly runoff. Their results from the River Baise that remote sensing provides. Although some of the catchment are very promising. models were designed to have a distributed structure that could accept areal data, the variables defined by the model 10.2 Land cover generally are not the same as remote sensing provides. There have been a number of successful applications where Although there is currently a significant amount of Landsat MSS data have been used to determine both urban research directed to adapting current models and develop and general land covers for estimating runoff coefficients. ing new models to use these unique datal hydrologists, to Land use is an important characteristic of the date, have not made optimum use of remote sensing. runoff process that affects infiltration, erosion, and evapo Runoff cannot be directly measured by remote transpiration. Thus, almost any physically-based sensing techniques. The role of remote sensing in runoff hydrological model uses some form of land use data or calculations is generally to prOVide a source of input data parameters based on thIs data. Distributed models, in for variables or to aid in estimating equation coefficients particular, need specific data on land use and its location and model parameters. The general areas where remote within the basin. Most of the work on adapting remote sensing has been used as input data for computing runoff sensing to hydrological modelling has been with the Soil are discussed below. Conservation Service '(SCS) runoff curve number modei (US Department of Agriculture, 1972; Ragan and Jackson, 10.1 Basin characteristics 1980). The general approach is to use remote sensing data as a substitute for land cover maps obtained by conven 10.1.1 Watershed geometry tional surveys. Remote sensing data can be used to acquire almost any information that is typically obtained from maps and used 10.3 Rainfall to initialize hydrological models. In many regions of the Direct measurement of rain from satellites for operational world, remotely sensed data, and particularly Landsat TM purposes has not been generally feasible because the or SPOT data, may be the only source of good cartographic opacity of clouds prevents observation of the precipitation information. Drainage basin area and the drainage network directly with visible) near infrared) and thermal infrared a-reeasi-lyobtained from good imagerY1even in remote sensor-so Microwave techniques in which the rainfall -inter regions. There have also been a number of studies to acts through scattering or attenuation of the radiation extract quantitative geomorphic information from Landsat have not yet developed to the stage of practical applica imagery (Haralick et aI., 1985). See Chapter 9 for addi tion, especially over land. However) improved analysis of tional information. rainfall can be achieved using both satellite and conven tional ground-based data. Satellite data are most useful in 10.1.2 Empirical relationships proViding information on the spatial distribution of poten Empirical fiood formulae can be useful for making quick tial rain- producing clouds, and gauge data are most useful estimates of peak flow or for making peak fiow estimates for accurate point measurements. Ground-based radar has when there is very littie other information available. A proved to be the most useful remote sensing technique for user must be cautioned1however, to be fully aware of their estimating rainfall rates. limitations. Generally these equations are restricted to a However, because the satellites do provide range of basin areas and the climatic/hydrologic regions of frequent observations) even at night with the thermal the world in which they were developed. sensors) the characteristics of potentially precipitating Most of the empirical flood formulae are based clouds and the rates of changes in cloud area and shape on the drainage area of the basin. A list of empirical flood can be observed. From these observations) estimates of formulae from many regions of the world can be found in rainfall can be made which relate cloud characteristics to the United Nations Flood Control Series No.7 (United instantaneous rain rates and rain totals over time) as well Nations, 19S5). as areas of basin receiving rainfall. Landsat data can be used to improve empirical equations of various runoff characteristics. Regression lOA Snowmelt runoff equations relating runoff to basin characteristics have been Forecasting snowmelt runoff for either water supply or proposed by a number of hydrologists, including Thomas flood prediction is a major task for hydrologists in many and Benson (1970). Work by Allord and Scarpace (1979) parts of the world. In some areas, such as the western have shown how the addition of Landsat derived land United States) snowmelt provides nearly all the water for cover data can improve regression equations based solely industry, agriculturel and domestic use. Accurate and on topographic maps. timely prediction of snowmelt runoff is necessary for effi There are other applications of remote sensing to cient reservoir management and water distribution hydrological models that are not land use related. planning. Certain parts of the world are habitually Strubing and Schultz (1983) have developed a runoff plagued by flooding from rapidly melting snow. 28 CHAPTER 10
Snowmelt funoff procedures using remote sensing Martinec, J. and Rango, A., 1986. Parameter values for have followed two distinct paths; either empirical relation snowmelt runoff modelling, Journal of Hydrology, ships or numerical modelling. The choice of approach 84, pp. 197-219. depends somewhat on the available data and to a great Martinec} 1"1 Rango, A., and Major, E., 1983. The extent on the detail in output desired. Snowmelt-Runoff Model (5RM) User's Manual, The most direct approach is to relate the satellite NASA Reference Publication, 1100 Washington, snow cover area on a given date to the seasonal runoff. D.C., 118 pp. Using data from several snow seasons enables one to Martinec, J./ Rango, A. and Roberts, R., 1992. User's develop an empirical curve such as that developed by manual for the Snowmelt Runoff Model (SRM) Rango et al. (1975) from l.andsat data for some basins in (Updated edition 1992, version 3.2), Hydrology the Wind River Mountains in Wyoming (USA). Laboratory Technical Report HL-17, Agricultural Snow cover depletion curves are another empirical Research Service, Beltsville} MD, 70 pp. approach that use satellite-derived snow cover area. The 50 Ragan, R. M. and Jackson, T. J., 1980. Runoff synthesis called modified snowcover depletion curves show a melt using l.andsat and SCS model, Journal of the sequence that is repeatable from one year to the next (Hall and Hydraulics Division, ASCE 106(HY5), pp. 667-678. Martinec, 1985). The displacement of the curves from one year Rango, A., 1980. Operational applications of satellite snow to the next is related to the snowpack water equivalent. cover observations, Water Resources Bulletin, 16(6), Although these curves are developed for one basin, they may pp. 1066-1073. possibly be transposed to other nearby basins as an estimate of Rango, A., 1983. Application of a simple snowmelt-runoff the melt process in the nearby basin. modd to large river basins, Proceedings of the A number of models for forecasting and simulat 51st Western Snow Conference} Vancouver, WA, ing snowmelt runoff have been developed or have been pp.89-99. modified from existing models to incorporate satellite Rango, A. and Martinec, J., 1979. Application of a derived snow cover data. snowmelt-runoff model using Landsat data, The Snowmelt Runoff Model (SRM) (Martinec et Nordic Hydrology, 10, pp. 225-238. al., 1983; 1992)1 used for simulating snowmelt, is one of _Rango} A., Salomonson, V. V. and Foster} ]. L., 1975. the better known and most thoroughly tested models avail Employment of satellite snow cover observations able. SRM has been developed to simulate and forecast for improving seasonal runoff estimates, daily streamflow in mountain basins where snowmelt is a Proceedings of the Workshop on Operational major component of the annual water balance. SRM is a Applications of Satellite Snowcover Observations, degree-day model that uses the percentage of the basin or NASA SP-391, Washington, D.C., pp. 157-174. elevation zone covered by snow as the primary input. Strubing, G. and Schultz, G. A., 1985. Estimation of Using Landsat and NOAA-AVHRR data, SRM has been monthly river runoff data on the basis of satellite successfully run on various size basins in Europe and the imagery, Hydrologic Application of Remote United States (Rango and Martinec, 1979; Rango, 1980; Sensing and Remote Data Transmission Rango, 1983; Martinec and Rango, 1986). (Proceedings of the Hamburg Symposium), IAH5 Publication No. 145, pp. 491-498. References Thomas, D. M. and Benson, M. A., 1970. Generalized Allard, G. J. and Scarpace, F. L., 1979. Improving streamflow streamflow characteristics from drainage basin estimates through use of Landsat, in Satellite characteristics, USGS Water Supply Paper 1955, Hydrology} American Water Resources Association, Washington, DC. Minneapolis, MN, pp. 284-291. United Nations, 1955. Multi-purpose river basin develop Barrett, E. c., 1970. The estimation of monthly rainfall from ment, Part I, Manual of river basin planning satellite data, Monthly Weather Review, 98; pp. 322 flood control series No.7, Economic Commission 327. for Asia and the Far East, United Nations Hall, D. K. and Martinec, J., 1985. Remote sensing of ice and Publication ST/ECAFE/5ERF/7, New York. snow, Chapman and Hall, London, 189 pp. US Department of Agriculture, 1972. National Engineering Haralick, R. M., Wang, S., Shapir, L.G. and Campbell, J. B., Handbook, section 4, Soil Conservation Service, 1985. Extraction of drainage networks by using a U.S. Government Printing Office, Washington, consistent labelling technique, Remote Sensing of DC. Environment, 18, pp. 163-175. CHAPTER 11 OPERATIONAL APPLICATIONS
For remote sensing techniques to be termed operational, A somewhat related operational application takes several qualifications must be met. The application must place in the Himalayan region. Ramamoorthi (1983; 1987) produce an output on a regular basis or the remote sensing has developed a regression model relating April basin snow approach must be used regularly and on a continuing basis cover to the April-June seasonal runoff on the Sutlej River as part of a procedure to solve a problem. There are several basin (43,230 km2) of India. The snow cover data are good examples of operational remote sensing applications obtained from NOAA-AVHRR. Four years of forecasts for water resources. produced an average forecast error of 10 per cent on the A! the present time the only operational soil Sutlej basin with similar results also being found on other moisture techniques are the aircraft based gamma ray and major basins in India. These forecasts are being used oper passive microwave approaches. The gamma approach is ationally in India and being extended to additional basins. operational in both the USA and The russian federation. In Finland, Landsat TM data are used opera In the USA this method is used by the National Weather tionally to inventory basin characteristics, primarily land Service primarily to establish background conditions for cover, for input to hydrological and energy balance snow studies/ however; some River Forecast Centers of the models. The classification accuracies of 95-100 per cent for National Weather Service in the Upper Midwest relate the water and about 80 per cent for separating various forest gamma ray soil moisture to the Antecedent-Precipitation types have been termed acceptable for model inputs Index for the region (Carroll, 1987). (Sucksdorff et aI., 1991). An operational aircraft passive microwave There are many other applications that are nearly programme is used within The russian federation for soil operational but do not fully meet the regular and continu moisture mapping, controlling the application of irrigation ing criteria. water from sprinklers, and detecting the areas of seepage from canals. The Russian scientists have taken the References
advances in the passive microwave remote sensing of soil Carroll, T. R. I 1987. Operational airborne measurements of moisture and developed a system for irrigation scheduling. snow water equivalent and soil moisture using Three radiometers at wavelengths of 2.25, 18, and 30 em terrestrial gamma radiation in the United States, are mounted on a small biplane (Antonov-2 type) and Large Scale Effects of Seasonal Snow Cover flown over agriculturaHields (Shutko, 1986). The multi (Proceedings for the Vancouver Symposium), lAHS wavelength capability not only provides surface layer soil Publication No. 166, pp. 213-223, moisture measurements, but also allows some indications Carroll, T. R., 1990. Airborne and satellite data used to map of upper layer soil ,moisture profiles. The soil moisture snow cover operationally in the U.S. and Canada, data are supplied to thefarm operators 5-10 hours after the Proceedings of the International Symposium on flights (Shutko, 1986). On some of the agricultural areas, Remote Sensing and Water Resources, International similar radiometers mounted on tractors, provide supple Association of Hydrogeologists, Enschede, The mental data. The soil moisture data thus obtained is then Netherlands, pp. 147-155.
used as a direct input to irrigation scheduling decisions. Mkrtchjan, F. A' I Reutov, E. A' I Shutko, A. M' I Kostov, KG.I
Bulgarian speCialists have used this technique and method Michaievi M. A., Nedeltchev, N. M., Spasovi A. Y. I and for organizing operational aircraft services for land recla Vichev, B. 1., 1988. MIcrocomputer-based radiometer mation and ecological studies in a framework of. an data acquisition and processing system for large-area "Interwaterautomatics" program (Mkrtchjan et aI., 1988). mapping of soil moisture in the top one meter layer, In the field of snow hydrology, the United States Proceedings of the IGARSS '88 SympOSium, National Weather Service has set up a National Remote Edinburgh, Scotland, ESA SP-284, pp. 1563-1564. Sensing Hydrology Center in Minneapolis, Minnesota. Ramamoorthi, A. S., 1987. Snow cover area (SCA) is the main Two operational products are turned out by the centre. factor in forecasting snowmelt runoff from major Gamma radiation remote sensing from low altitude aircraft river basins, Large Scale Effects of Seasonal Snow is used to measure snow water equivalent over a network Cover (Proceedings of the Vancouver Symposium), of more than 1 500 flight lines covering portions of 25 lAHS Publication No. 166, pp. 187-198. USA states and 7seven Canadian provinces. NOAA-AVHRR Ramamoorthi, A. S., 1983. SnowMmelt run-off studies using satellite data are used to digitally map areal extent of remote sensing data, Proceedings of the Indian snow-covered regions covering two-thirds of the USA and Academy of Sciences, 6(3), pp. 279-286. southern Canada where snow cover is an important hydro· Shutko, A. M., 1986. Microwave Radiometry of Water Surface
logical variable. The snow cover was mapped for about and Grounds l Nauka/Science Publishing House, 2000 basins in 1990 and about 300 of these basins are Moscow, 190 pp.
mapped by elevation zone. The airborne and satellite Sucksdorff, Y., Michels, G., Tattaril S.I and Heikinheimo, M' I alphanumerical and digital image snow coverage date sets 1991. Operational satellite remote sensing for are available electronically to users in near real time for hydrological modelling, Proceedings of the IGARSS __hydrological forecastiIlg purposes (Carroll, 1990). '9!SYillIJPsi]lm,EAPQO, finland,pp. 67-70. CHAPT--n 12
GAPS IN KNOWLEDGE BASE
There are specific areas of research that are certainly ready with new high resolution data (Gardner et al., 1989). More for more of an operational application. As previously research with high resolution (e.g., SPOT and l.andsat TM) mentioned} remotely sensed land cover information has and digital topography data needs to be conducted to only been operational in a few situations (e.g., Sucksdorff determine the current capabilities regarding detectable et al., 1991), although there are many opportunities to use features and applicable map scales. it. Because of its accuracy and cost effectiveness, the Albedo investigations have been conducted, but remotely sensed land cover data should be promoted for as yet there is not an effective way to remotely measure use in hydrological modelling and other types of water albedo. Remote sensors collect only a small portion of resources studies. light refiected by the Earth's surface, I.e., light reflected Many good examples of how multispectral toward the sensor in the specific electromagnetic band of remote sensing data can be used to determine sediment the sensor. The albedo is made up of light reflected in all load in reservoirs and rivers also exist (Ritchie and Cooper, directions over all portions of the electromagnetic spec 1988; Ritchie et al., 1986; 1987; Verdin, 1985). Because of trum. Much research, like that of Dozier et al. (1988), relatively easy application, these multispectral techniques needs to be done on the bidirectional reflectance-distribu should be promoted for operational monitoring of sedi tion function so that one remote sensing reflectance ment loads in water bodies. measurement can be used to deduce the albedo. There are more remote sensing water resources Evapotranspiration is the most elusive of the areas that have shown significant promise but need addi hydrological cycle components to measure. Research is tional research before operational application can be progressing slowly on this topic, but various parts of the attempted. Passive microwave determination of snow problem are falling into place. Remote determinations of water equivalent in relatively flat areas has shown much surface temperature and upper layer soil moisture are promise (Rango et aI., 1979; Hall et aI., 1984; 1987; essential for estimation of evapotranspiration. Evaluations Goodison et al., 1986; Foster et aI., 1980; Chang et aI., of how remote sensing can be used in energy balance 1982). Products being turned out using SSM/! data in computations, e.g., the work by Kustas and Daughtry Canada (Goodison et aI., 1990) are nearly ready for opera (1989), are needed before evapotranspiration can be calcu tional distribution. Additional research is required to lated operationally. determine corrections needed for forest areas and to deter In addition to these areas, there are several aspects of mine how the techniques can be used in areas outside the water resources that have not been found to be amenable to current regions of application. remote sensing me-asurement. Some of these may never be There is also a need for additional research using measured using remote senSing. So far, it has been impossible passive microwave data in soil moisture applications. to measure streamflow occurring in river basins. No remote Work needs to be done to develop techniques similar to sensing method for measuring infiltration of precipitation into Shutko's (1987) for operational application in non-irrigated the soil has been found either. Snow grain size affects the regions. The study done by Jackson et al. (1987) on the microwave measurement of snow water equivalent, but only Texas High Plains is an example of the type of project that limited information on snow grain size on the surface of the could be turned into an operational application. A major snowpack has been available using visible and near infrared research emphasis is required to relate the upper layer soil data (Dozier, 1987; 1989). These visible and infrared measure moisture value obtained by remote sensing to the soil ments mayor may not be related to the grain size influencing moisture present in the deeper layers. microwave measurements. Microwave penetration into the Sporadic success has been obtained in using soil is limited to the surface layer. As yet, no truly operational remote sensing data to locate groundwater. Most methods for measuring deep soil moisture or groundwater are approaches use surficial indicators of the underlying available. Although remote sensing of sediment pollution in groundwater reservoir and require considerable skill and water bodies is possible1 no comprehensive ways have been knowledge on the part of the interpreter. More documenta found to measure the levels of chemical pollutants. tion of the techniques used is needed, perhaps in handbook form. One such area, among many that would References34 benefit by such specific gUidance, would be the use of frac Chang, A. T. C., Foster, J. 1.., Hall, D. K., Rango, A., and ture intersections to locate new groundwater wells. Hartline, B. K., 1982. Snow water equivalent estima Soil erosion is alarge problem in water resources and tion by microwave radiometry, Cold Regions agriculture. Recent work has shown that airborne lasers can be Research and Technology, 5, pp. 259-267. used to measure the occurrence and dimensions of ephemeral Dozier, J., 1989. Spectral signature of alpine snow cover frorh gullies (Ritchie and Jackson, 1989). Such work could be used the l.andsat Thematic Mapper, Remote Sensing of in estimations of soil loss; however, research is needed to Environment, 28, pp. 9-22. determine how such measurements can be used in a sampling Dozier! J., 1987. Recent research in snow hydrology, Reviews scheme to get estimates of soil loss over large areas. of Geophysics, 25(2), pp. 153-161. A number of early studies on the remote measure Dozier! J., Davis, R. E., Chang, A. T. c., and Brown, K., 1988. ment of physiographic and basin characteristics indicated The spectral bidirectional reflectance of snow, that adequate measurement could be made at certain map Spectral Signatures of Objects in Remote Sensing, scales (Rango et aI., 1975). At that time the need was for Fourth International ColloqUium, ESA SP-287, better resolution data. Only a few studies have been made European Space Agency, Paris, pp. 87-92. GAPS IN KNOWLEDGE BASE 31
Foster,]. 1., Rango, A., Hall, D. K. Chang, A. T. C., Allison, 1.]. Rango, A., Chang, A. T. C. and Foster,]. 1., 1979. The utiliza and Diesen, B. C., 1980. Snowpack monitoring in tion of spaceborne microwave radiometers for North America and Eurasia using passive microwave monitoring snowpack properties, Nordic Hydrology, satellite data, Remote Sensing of Environment, 10, 10, pp. 25-40.
pp. 285-298. Rango, A' I Foster} J. and Salomonsonj V. V., 1975. Extraction Gardner, T. W./ Connors, K. F. and Hu , H" 1989. and utilization of space acqUired physiographic data Extraction of fluvial networks from SPOT for water resources development} Water Resources panchromatic data in a low relief, arid basin, Bulletin, 11(6), pp. 1245-1255. International Journal of Remote Sensing, 10(11), Ritchie, ]. C. and Cooper, C. M., 1988. Comparison of pp. 1789-1801. measured suspended sediment concentrations with Goodison, B., Walker, A. E. and Thirkettle, F., 1990. suspended sediment concentrations estimated from Determination of snow water equivalent on the Landsat MSS data, International Journal ofRemote Canadian prairies using real-time passive microwave Sensing, 9(3), pp. 379-387. data, Proceedings of the Workshop on Application of Ritchie,]. C. and]ackson, T. ]., 1989. Airborne laser measure Remote Sensing in Hydrology, National Hydrology ments of the surface topography of simulated Research Institute, Saskatoon, Saskatchewan, pp. 297 concentrated flow gullies, Transactions of the ASAE, 316. 32(2), pp. 645-648. Goodison, B. E., Rubinstein, L, Thirkettle, F. W. and Langham, Ritchie,]. C., Schiebe, F. R. and Cooper, C. M., 1986. Surface E.]., 1986. Determination ofsnow water equivalent water quality measurements of Lake Chicot, Arkansas on the Canadian prairies using microwave radiome using data from Landsat satellites, Journal of try, Modelling Snowmelt-Induced Processes Freshwater Ecology, 3(3), pp. 391-397. (Proceedings of the Budapest Symposium), IAHS Ritchie,]. c., Cooper, C. M. and]iang, Y., 1987. Using Landsat Publication No. 155, pp. 163-173. multispectral scanner data to estimate suspended Hall, D. K., Chang, A. T. C. and Foster,). 1., 1987. Seasonal and sediments in Moon Lake, Mississippi, Remote interannual observations and modelling of the snow Sensing of Environment, 23, pp. 65-81. pack on the arctic coastal plain of Alaska using Shutko, A. M., 1987. Remote sensing of the waters and lands satellite data, Proceedings of the Cold Regions via microwave radiometry (the principles of method, Hydrology Symposium, American Water Resources problems feasible for solVing} economic use)} in: Association, Fairbanks, Alaska, pp. 521-529. Remote Sensing and its Impact on Developing Hall, D. K., Foster,]. L. and Chang, A. T. C., 1984. Nimbus-7 Countries} Pontificia Academia Scientiarum, Scripta SMMR polarization responses to snow depth in the Varia-68, Vatican City, pp. 413-441. mid-western U.S., Nordic Hydrology, 15, pp. 1-8. Sucksdorff, Y., Michels, G.} Tattari, S.} and Heikinheimo, M., Jackson, T. ]., Hawley, M. E. and O'Neill, P. E., 1987. 1991. Operational satellite remote sensmgfor hydrO Preplanting soil moisture using passive logical modelling, Proceedings of the IGARSS '91 microwave sensors, Water Resources Bulletin} 23(1), Symposium, Espoo, Finland, pp. 67-70. pp.11-19. Verdin}]. P., 1985. Monitoring water quality conditions in a Kustas, W. P. and Daughtry, C. S. T., 1989. Estimation of the soil large western reservoir with Landsat imagery, heat flux/net radiation ratio from spectral datal Photogrammetric Engineering and Remote Sensing, Agricultural and Forest Meteorology, 49, pp. 205-223. 51, pp. 343-353. CHAPTER 13
FUTURE TRENDS
13.1 Forthcoming sensors and systems ral soil moisture. Existing hydrological models and engi There are a number of new remote sensing and satellite neering techniques have been developed to solve specific systems that are being planned for the next few decades. water resources problems (Le. water supply, flood protec Many of these are designed for observing many of the tion, etc). As such, many of these are lumped models that physical and biological characteristics of the Earth. As have been developed from point measurements. Models hydrologists, we can anticipate new, as well as better} data with this structure are not capable of using the spatial for process and global hydrologIc studies. nature of remote sensing data. Before soil moisture data of Within the near future, there are two major this nature can be used in hydrology, there is a need to initiatives that will have significant hydrologic benefits: modify existing models or develop new models that reflect The Tropical Rainfall Measuring Mission (TRMM) and the soil moisture in a way that is more physically realistic and Mission to Planet Earth's Observing System (EOS). so that soil moisture data can be used as input or output verification. Also, there is need to develop procedures for 13.2 Planned Earth observing systems into the modelling or estimating profile soil moisture from time 21st centnry series near surface measurements or from using multifre The TropIcal Rainfall Measurement Mission (Simpson et aI., quency data. 1988), to be launched into an orbit inclined at about 30°, will have on board a rainfall radar that will be capable of 13.2.3 Model approaches to use real·time areal data estimating rainfall rates over land. The orbit is such that Several investigators have proposed the use of remotely sensed any point within the tropics will be sampled twice each rainfall as input to real-time hydrology and short-time forecast month at every hour. models. Roll (1986) has studied the potential for using EOS (NASA, 1988) and its counterpart European Meteosat data as an indication of rainfall input to a basin. A and Japanese platforms will lead to considerable advances runoff model that uses a cloud index developed from the ther in the understanding of earth sciences as a whole) includ mal data was applied to two large basins in Europe. The ing hydrology. The manifest of instruments planned is concept was demonstrated by predicting runoff for one to impressive, but the organization of the data and of other three days ahead, starting with the measured flow. earth science data in an information system where time Schultz (1986) has proposed using historical series of all the data will be easily available is of at least NOAA satellite data to generate a long-term runoff record equal importance. The data system will also allow many for data-sparse basins. A cloud cover index developed from types of data to be used simultaneously for calibration of cloud-top temperatures is transformed into runoff with a or for assimilation into numerical models. linear transformation function. For short-term flood fore cast problems, Schultz has also proposed developing 13.2.1 New sensors rainfall inputs from near real-time satellite data, and, if From a hydrological perspective, new sensors in the microwave available} combining them with ground;.based radar data. region are perhaps the most importantand offer the opportu The flood flows are then calculated with a runoff model nity to collect new data forms. Several satellites and capable of using this type of precipitation input. instruments are of interest to hydrologists, including the SARs There are several satellites, such as ERS-l recently mounted on the ERS-l, J-ERS-l, ALMAZ, and Radarsat space launched by the European Space Agency and JERS-1 craft. At this writing, SAR data are being acquired by ERS-l, launched by Japan, which have primarily oceanographic JERS-l, and ALMAZ with Radarsat to follow in 1995. applications but which will also be used for acquiring data Continuing high spatial resolution data from the Landsat and over land. Both carry single-polarization, single-wave SPOT satellites} passive microwave data from the special sensor length SARs, plus radiometers at various wavelengths microwave/imager (SSM/I) on the DMSP satellite series, and which may also give useful data over land. The duty cycles continuing meteorological satellite coverage from NOAA} and coverage of the SARs will be limited in both cases, but GOES, GMS and Meteosat series all mean that the remotely the use of SAR data for mapping, particularly in polar areas sensed techniques can continue to be employed and expanded where overlapping satellite ground tracks mean that the upon. In addition, very high resolution (5 m) photo images are repeat interval between data on different days is reduced} is now available from the Russian satellite Sojuzkarta. Specific clearly of interest to the hydrology community. small area applications may make effective use of the data. 13.3 Development of hydrological models 13.2.2 Employment ofnew remote sensing data lt is apparent that some improvement in forecasts and New remote sensing data} such as microwave data, will not simulations can be achieved by modifying existing models be able to be used in hydrological modelling without some to use remote sensing data. However} it follows that even major changes in the structure of the models. The follow greater gains can be achieved with models designed to use ing example illustrates the problem with reference to soil remote sensing as well as conventional data. Such models moisture, but it is pertinent for many other data forms as would resemble contemporary simulation models struc well} Le. surface temperature and snow water equivalent. turally but would be able to account for the spatial Because soil moisture has not been used as variability found in natural basins in a more realistic way. measured data in hydrological modelling, there are a Also, the subprocess algorithms (Le., infiltration, evapo number of issues that hydrologists must address and solve transpiration, etc.) would be written to use remote sensing in anticipation of actually working with spatial and tempo_ data as a primary input as well as the more typical inputs. FUTURE TRENDS 33
13.3.1 New model structure to use remote sensing One feature of the large-scale hydrological modeis data that is not well described anywhere is the spatial variability A pioneering attempt to develop a model designed to use of the land surface. Some advances are being made (e.g., remote sensing input data has been made by Groves and Entekhabi and Eagleson, 1989), but many models just Ragan (1983). This model is similar in structure to other average measured variables by taking the arithmetic mean models such as the Stanford model (Crawford and Linsley, for all quantities over large areas. Remote sensing can help 1966), but more of its parameters are physically based in in dealing with spatial variability of the land surface the sense that they can be determined directly by remote through observationsj however, experiments are needed to sensing. Another feature of this model is the use of a understand what these remotely sensed data are related to geographic information system (GIS) as a data manage and how they can be used. ment tool to handle the spatial nature of the various data. The GIS assimilates remote sensing data and the histori References cally more common point data and provides a spatially Crawford, N. H. and Linsley, R. K, 1966. Digital simulation in distributed framework for the model. hydrology: Stanford watershed model IV, Stanford A somewhat analogous effort has been proposed University, Technical Report 39. by Fortin et al. (1986) with a model that has nine modules. Dickinson, R. E., Henderson-Sellers, A., Kennedy, P. ]. and The framework of the model is built on a square grid infor Wilson, M. F., 1986. Biosphere-atmosphere transfer mation system with variable-sized pixels to incorporate scheme (BATS) for the NCAR community climate many types of remote sensing data. The hydrology module model, Tech. Note TN275 +STR, NCAR, Boulder, CO. is really two modules} a production function and a transfer Eagleson, P.S., 1991. Hydrologic science: a distinct geoscience, function. The production is based on a contributing area Reviews o{Geophysics, 29, pp. 121-278. concept that is} in turn, based on land use, soils} topogra Entekhabi, D. and Eagleson, P. S., 1989. Land surface hydrol phy, and drainage pattern. Water from the production is ogy parameterization for atmospheric general routed through a number of reaches in the drainage circulation models including subgrid scale spatial network by the transfer function. The transfer function is variability, Journal o{Climate, 2, pp. 816-831. based on a modified kinematic wave formulation, Fortin,]. P., Villeneuve,]. P., Guillot, A.} Sequin} B., 1986. Development of a modular hydrological forecastlog 13.4 Scientific development related to remote model based on remotely sensed data for interactive sensing and hydrology advances utilization on a microcomputer, Hydrologic The increased interest of the. scientific community in Applications of Space Technology, lAHS Publication global change and the Earth's system as a whole has No. 160, pp. 307-319. resulted in an increased awareness of hydrological sciences Groves,]. R. and Ragan, R. M., 1983. Development of a remote as oppos.ed to engine.ering hydrology.and water resources. sensing -based -continuous streamflow model, Proceedings ofthe 17th International Symposium on 13.4.1 Global atmospheric modelling Remote Sensing of Environment, Environmental Although standard hydrological models continue to Research Institute of -Michigan, Ann Arbor} MI, pp. improve and become more physically based, there is a 447-456. whole new class of models that is now receiving attention Manabe, S., 1969. Climate-and ocean circulation: 1. The atmo from hydrologists (Eagleson, 1991). These are global spheric circulation and the hydrology of the Earth's models that include the whole water budget. Early global surface, Monthiy Weather Review, 97, pp. 739-740. models were developments of atmospheric general circula NASA, 1988. From pattern to process: The strategy of the tion models for weather forecasting; and included only the Earth Observing System, National Aeronautics and simplest representations of atmospheric hydrologic Space Administration, EOS - Science Steering processes (e.g., condensation) and only minimal descrip Committee Report, Washington, D.C., 140 pp. tions of the land and ocean surfaces. However, as these Rott, H., 1986. Estimation of daily runoff based on meteosat models were refined for climatological studies, ocean circu data, Hydrologic Applications of Space Technology, lation and air-sea interaction had to be included. The land IAHS Publication No. 160, pp. 321-330. surface hydrology has also-begun to be represented in Schultz, G. A., 1986. Satellite data as input for long-term and global models, with models varying from the very simple short-term hydrological models, Hydrologic (Manabe, 1969) representation of the land surface as a -Applications of Space Technology, lAHS Publication /lbucket"1 to the very complicated (Dickinson et aI., 1986i No. 160, pp. 297-306. Sellers et aI., 1986). Sellers, P. ]., Mintz, Y., Sud, Y. C. and Dalcher, A., 1986. A The level of complexity that ought to be included simple biosphere model for use with general circula varies from representation to representation, though it is .tion models, JOl/mal o{ Atmospheric Science, 43, pp. cleariy difficult to validate a model with many parameters. 505-531. The level of complexity should match the level of physical Simpson, ]., Adler, R. F. and North, G. R., 1988. A proposed representation elsewhere in a global model: a global model Tropical Rainfall Measuring Mission (TRMM) satel is only as good as the least accurate physical representation lite, Bulletin o{the AmericalT Meteorological Society, 69, within it. pp. 278-295.