Search

After the reported discovery of room-temperature superconductivity at only 1GPa in nitrogendoped lutetium trihydride [1] and the resulting heated discussions, there is an urgent need to reproduce the results and synthesis of this compound. Here, we report the synthesis of stable trigonal LuH3 by hydrogenating pure lutetium which was subsequently pressurised to 2GPa in a dilute-N2/He-rich pressure medium. Raman spectroscopy and X-ray diffraction were used to characterise the structures throughout. After depressurising, energy-dispersive and wavelength-dispersive X-ray spectroscopies were used to characterise the final compound. Though our compound exhibits similar structural behaviour to the Dasenbrock-Gammon et al. sample [1], we do not observe any nitrogen within the structure of the recovered sample at ambient pressure. We observe two cubic structures under pressure that may simultaneously explain the X-ray diffraction and Raman spectra observed: the first corresponds well to Fm-3m LuH2+x, whilst the latter is a novel Ia-3 - type structure., Comment: 8 pages, 3 figures

La(Fe,Si)$_{13}$-based compounds are considered to be very promising magnetocaloric materials for magnetic refrigeration applications. Many studies have focused on this material family but only in bulk form. In this paper, we report the fabrication of thick films of La(Fe,Si)$_{13}$, both with and without post-hydriding. These films exhibit magnetic and structural properties comparable to those of bulk materials. We also observe that the ferromagnetic phase transition has a negative thermal hysteresis, a phenomenon not previously found in this material but which may have its origins in the availability of a strain energy reservoir, as in the cases of other materials in which negative thermal hysteresis has been found. Here, it appears that the substrate acts to store strain energy. Our exploratory study demonstrates the viability of thick films of the La(Fe,Si)$_{13}$ phase and motivates further work in the area, while showing that additional perspectives can be gained from reducing the dimensionality of magnetocaloric materials in which the magneto-volume effect is large., Comment: 16 pages, 3 figures

In this paper, we mainly focus on the magnetic and magnetocaloric features of La2-xDyxNiMnO6 double perovskites. Their magnetocaloric properties are investigated in terms of both entropy and adiabatic temperature changes. In contrast to early works, it was found that the Dy2NiMnO6 compound unveils dominant antiferromagnetic interactions under very low magnetic fields. The ordering of its Dy3+ magnetic moments is associated with a giant magnetocaloric effect at very low temperatures, while the established ferromagnetic Ni-O-Mn super-exchange interactions close to 100 K give rise to a moderate magnetocaloric level, only. On the other hand, the doping of Dy2NiMnO6 with high amounts of large-size rare earth elements such as La would enable us to cover an unusually wide magnetocaloric temperature range going from the liquid helium temperature up to room-temperature. More interestingly, the presence of both ordered and disordered ferromagnetic phases in La1.5Dy0.5NiMnO6 maintains constant the isothermal entropy changes over a temperature span of about 200 K, being a favorable situation from a practical point of view., Comment: Accepted for publication in Journal of Physics: D, 2019

This work addresses the coordination problem of multiple robots with the goal of finding specific hazardous targets in an unknown area and dealing with them cooperatively. The desired behaviour for the robotic system entails multiple requirements, which may also be conflicting. The paper presents the problem as a constrained bi-objective optimization problem in which mobile robots must perform two specific tasks of exploration and at same time cooperation and coordination for disarming the hazardous targets. These objectives are opposed goals, in which one may be favored, but only at the expense of the other. Therefore, a good trade-off must be found. For this purpose, a nature-inspired approach and an analytical mathematical model to solve this problem considering a single equivalent weighted objective function are presented. The results of proposed coordination model, simulated in a two dimensional terrain, are showed in order to assess the behaviour of the proposed solution to tackle this problem. We have analyzed the performance of the approach and the influence of the weights of the objective function under different conditions: static and dynamic. In this latter situation, the robots may fail under the stringent limited budget of energy or for hazardous events. The paper concludes with a critical discussion of the experimental results., Comment: 40 pages

The mine detection in an unexplored area is an optimization problem where multiple mines, randomly distributed throughout an area, need to be discovered and disarmed in a minimum amount of time. We propose a strategy to explore an unknown area, using a stigmergy approach based on ants behavior, and a novel swarm based protocol to recruit and coordinate robots for disarming the mines cooperatively. Simulation tests are presented to show the effectiveness of our proposed Ant-based Task Robot Coordination (ATRC) with only the exploration task and with both exploration and recruiting strategies. Multiple minimization objectives have been considered: the robots' recruiting time and the overall area exploration time. We discuss, through simulation, different cases under different network and field conditions, performed by the robots. The results have shown that the proposed decentralized approaches enable the swarm of robots to perform cooperative tasks intelligently without any central control., Comment: Soft Computing, 2017

The radiometric calibration of SeaWiFS data includes a correction for the temperature dependence of the individual detector sensitivities. The detector temperature are measured by temperature sensors mounted on instrument focal planes. Processing of the temperature sensor output by an onboard instrument computer introduces a nonlinear response into the temperature data. This paper describes the calibration of the temperature sensor output and the computation of the temperature corrections for the radiometric calibration of the instrument.

Satellite microwave data have been used to derive areal snow water equivalent in flat homogeneous areas. Over heterogeneous mountainous areas different algorithms are needed to retrieve the water equivalent of the snow cover. A mixed pixel model based on the percentage of vegetation cover within a pixel has been developed to simulate the microwave brightness temperatures for the Rio Grande basin in southwestern Colorado. A relationship between the difference in microwave-brightness temperature at two different frequencies (37- and 18-GHz horizontal polarization), and the basin-wide average snow water equivalent was obtained. The areal snow-water equivalent values derived from the model were consistent with values generated by a reliable snowmelt run-off model using snow-cover extent data.

Satellite microwave data were used to evaluate the average areal water equivalent of snow cover in the mountainous Rio Grande basin of Colorado. Areal water equivalent data for the basin were obtained from contoured values of point measurements and from zonal water volume values generated by a snowmelt runoff model. Comparison of these snow water equivalent values shows the model values to consistently exceed the contoured values, probably because of the narrow elevation range in the lower part of the basin where the point measurements are concentrated. A significant relationship between the difference in microwave brightness temperatures at two different wavelengths and a basin-wide average snow water equivalent value is obtained. The average water equivalent of the snow cover in the basin was derived from differences of the microwave brightness temperatures.

Satellite microwave data were used to evaluate the average areal water equivalent of snow cover in the mountainous Rio Grande basin of Colorado. Areal water equivalent data for the basin were obtained from contoured values of point measurements and from zonal water volume values generated by a snowmelt runoff model. Comparison of these snow water equivalent values shows the model values to consistently exceed the contoured values, probably because of the narrow elevation range in the lower part of the basin where the point measurements are concentrated. A significant relationship between the difference in microwave brightness temperatures at two different wavelengths and a basin-wide average snow water equivalent value is obtained. The average water equivalent of the snow cover in the basin was derived from differences of the microwave brightness temperatures.

Remotely sensed snow cover information is the critical data input for the Snowmelt-Runoff Model (SRM), which was developed to simulatke discharge from mountain basins where snowmelt is an important component of runoff. Of simple structure, the model requires only input of temperature, precipitation, and snow covered area. SRM was run successfully on two widely separated basins. The simulations on the Kings River basin are significant because of the large basin area (4000 sq km) and the adequate performance in the most extreme drought year of record (1976). The performance of SRM on the Okutadami River basin was important because it was accomplished with minimum snow cover data available. Tables show: optimum and minimum conditions for model application; basin sizes and elevations where SRM was applied; and SRM strengths and weaknesses. Graphs show results of discharge simulation.

One of the major scientific questions in hydrology is: Can remote sensing data be used effectively with models to improve our understanding of hydrologic processes? Virtually all hydrologic models, with only a few exceptions, were designed to interface with conventional point data. These models must be modified or new ones developed to be compatible with remote sensing capabilities (areal coverage, high spatial resolution, repetitiveness, etc.). A comprehensive program of development and testing of these models at various application scales ranging from flash flood modeling and small tributary streams to continental size general circulation models must be carried out.

A manual to provide a means by which a user may apply the snowmelt runoff model (SRM) unaided is presented. Model structure, conditions of application, and data requirements, including remote sensing, are described. Guidance is given for determining various model variables and parameters. Possible sources of error are discussed and conversion of snowmelt runoff model (SRM) from the simulation mode to the operational forecasting mode is explained. A computer program is presented for running SRM is easily adaptable to most systems used by water resources agencies.

In this study the snow cover extent during the autumn months in both North America and Eurasia has been related to the ensuing winter temperature as measured at several locations near the center of each continent. The relationship between autumn snow cover and the ensuing winter temperatures was found to be much better for Eurasia than for North America. For Eurasia the average snow cover extent during the autumn explained as much as 52 percent of the variance in the winter (December-February) temperatures compared to only 12 percent for North America. However, when the average winter snow cover was correlated with the average winter temperature it was found that the relationship was better for North America than for Eurasia. As much as 46 percent of the variance in the winter temperature was explained by the winter snow cover in North America compared to only 12 percent in Eurasia.

Both LANDSAT and NOAA satellite data were used in improving snowmelt runoff forecasts. When the satellite snow cover data were tested in both empirical seasonal runoff estimation and short term modeling approaches, a definite potential for reducing forecast error was evident. A cost benefit analysis run in conjunction with the snow mapping indicated a $36.5 million annual benefit accruing from a one percent improvement in forecast accuracy using the snow cover data for the western United States. The annual cost of employing the system would be $505,000. The snow mapping has proven that satellite snow cover data can be used to reduce snowmelt runoff forecast error in a cost effective manner once all operational satellite data are available within 72 hours after acquisition. Executive summaries of the individual snow mapping projects are presented.

The purpose of the handbook is to update the various snowcover interpretation techniques, document the snow mapping techniques used in the various ASVT study areas, and describe the ways snowcover data have been applied to runoff prediction. Through documentation in handbook form, the methodology developed in the Snow Mapping ASVT can be applied to other areas.

Walden Reservoir, a freshwater lake in north-central Colorado, was overflown six times by a NASA C-130 aircraft between January 1977 and April 1980. The aircraft was equipped with four microwave radiometers operating between 0.81 and 6.0 cm in wavelength (37.0 to 5.0 GHz). The 6.0-cm radiometer data showed a good relationship with ice thickness based on a sample of four ice thickness values. The 1.67- and 1.35-cm radiometer data showed weaker relationships with ice thickness. The 0.81-cm sensor data showed no positive relationship with ice thickness. None of the relationships was statistically significant because of the small sample size. The 6.0-cm sensor data in the nadir-viewing mode was found to have the most potential of all the wavelengths studied, for use in remotely determining ice thickness. The 6.0-cm radiometer probably sensed the entire thickness of the ice on the reservoir (ranging from 25.4 to 67.3 cm in thickness) and was apparently not significantly affected by the snow overlying the ice. The shorter wavelengths are scattered by the snow overlying the ice and are more suitable for snow studies than for ice thickness studies.

Philosophical and technical backgrounds for the application of remote sensing by earth scientists are presented. Interests and activities of participating agencies of the United States and Canadian governments, universities, and the private sector in implementing satellite technology in a diverse array of water-related programs are described. Consideration is then given to applications of satellite data to the various aspects of the hydrologic cycle and man's impact on it: meteorology, snow and ice, surface water, soil moisture, ground water, wetlands, coastal zone, water quality and environment, and water use and management.

Truck-mounted, airborne, and spaceborne systems with various radiometers ranging in wavelength from 0.8 to 21 cm were used to measure the brightness temperatures of snow-covered areas at test sites near Steamboat Springs and Walden, Colorado. The brightness temperature at a short wavelength (0.8 cm) was found to decrease more rapidly with increasing snow depth than the brightness temperature at a longer wavelength (6 cm). More scattering of the shorter-wavelength radiation by the snow crystals results in a lower brightness temperature. The longer-wavelength (6 cm) radiation penetrates through meters of dry snowpack and is useful for the assessment of the underlying ground conditions.

One of the most important parameters for accurate snowmelt runoff prediction is snow water equivalent (SWE) which is contentionally monitored using observations made at widely scattered points in or around specific watersheds. Remote sensors which provide data with better spatial and temporal coverage can be used to improve the SWE estimates. Microwave radiation, which can penetrate through a snowpack, may be used to infer the SWE. Calculations made from a microscopic scattering model were used to simulate the effect of varying SWE on the microwave brightness temperature. Data obtained from truck mounted, airborne and spaceborne systems from various test sites were studied. The simulated SWE compares favorable with the measured SWE. In addition, whether the underlying soil is frozen or thawed can be discriminated successfully on the basis of the polarization of the microwave radiation.

Areas of the Canadian high plains, the Montana and North Dakota high plains, and the steppes of central Russia have been studied in an effort to determine the utility of spaceborne microwave radiometers for monitoring snow depths in different geographic areas. Significant regression relationships between snow depth and microwave brightness temperatures were developed for each of these homogeneous areas. In each of the study areas investigated in this paper, Nimbus-6 (0.81 cm) ESMR data produced higher correlations than Nimbus-5 (1.55 cm) ESMR data in relating microwave brightness temperature to snow depth. It is difficult to extrapolate relationships between microwave brightness temperature and snow depth from one area to another because different geographic areas are likely to have different snowpack conditions.

The electrically scanning microwave radiometer (ESMR) on the Nimbus 5 satellite was used to observe microwave emissions from vegetated and soil surfaces over an Illinois-Indiana study area, the Mississippi Valley, and the Great Salt Lake Desert in Utah. Analysis of microwave brightness temperatures (T sub B) and antecedent rainfall over these areas provided a way to monitor variations of near-surface soil moisture. Because vegetation absorbs microwave emission from the soil at the 1.55 cm wavelength of ESMR, relative soil moisture measurements can only be obtained over bare or sparsely vegetated soil. In general T sub B increased during rainfree periods as evaporation of water and drying of the surface soil occurs, and drops in T sub B are experienced after significant rainfall events wet the soil. Microwave observations from space are limited to coarse resolutions (10-25 km), but it may be possible in regions with sparse vegetation cover to estimate soil moisture conditions on a watershed or agricultural district basis, particularly since daily observations can be obtained.

The Patuxent River Watershed is located in central Maryland between Baltimore and Washington, D.C. and is approximately 2330 sq km in area and 175 km long. This region is now at a critical point because of major concerns such as water management and quality, flooding and land use within the watershed. Data from the NASA-directed LANDSAT and Earth Resources Aircraft Programs were used to provide a new dimension in information collection and processing for the management of watersheds. Digital data from LANDSAT-1 were analyzed along with selected IR photography from U-2 flight number 74-060B taken 28 April 1974, which was digitized in three channels. Processing of the data was accomplished using a multispectral analysis system. Land use themes consisting of surface water, wetlands, forest, residential, cropland/pasture, urban, and extractive were developed and delineated through the watershed. Area measurements of watershed themes were obtained and will serve as a calibration input to a deterministic hydrologic model on a sub-watershed. Using the derived residential and urban theme areas from LANDSAT an estimated basin imperviousness was also calculated. Thematic maps were produced at 1:62,500 scale. Floodprone areas were also classified and delineated at a scale of 1:24,000. Comparison with standard floodprone area maps at the same scale have indicated a few areas of discrepancy. Such information can be used for updating or checking floodprone area boundaries as well as monitoring changes in floodplain areas.

An effort was made to evaluate the utility of satellite snowcover observations for seasonal streamflow prediction. On a representative, large watershed(10 to the 5th power to 10 to the sixth power sq km) it was found, based on six years of data, that meteorological satellite observations of snow cover early in the snowmelt season exhibit a relationship to seasonal runoff having a statistically significant coefficient of determination of 0.92. Analyses of LANDSAT-1 snow-cover observations over the Wind River Mountains of Wyoming reveals that for areas with infrequent cloud cover the extent of snowcover and its change with time can be monitored on watersheds as small as 10 sq km in areal extent. The change in the snow cover with time as observed from LANDSAT-1 is found to reflect major differences in seasonal runoff from high altitude (mean altitude 3 km) and low altitude ( 3 km) watersheds. There are quantitative indications that LANDSAT observations over small watersheds could be used in a manner similar to that employed for meteorological satellite observations to relate the percent of a basin snowcovered on a given data to seasonal runoff.

Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.

The environmental satellites NOAA-2 and ERTS-1 observed flooding in United States' rivers such as the Mississippi during 1973. Combination of NOAA-2 observation frequency and the ERTS-1 resolution provides an adequate satellite system for monitoring floods. Several polar-orbiting satellites of the ERTS type could view flooded areas at a reasonably high resolution every three to five days. A high-resolution earth-synchronous satellite would further enhance flood mapping by providing observations whenever clouds are absent.

Low resolution meteorological satellite and high resolution earth resources satellite data have been used to map snow covered area over the upper Indus River and the Wind River Mountains of Wyoming, respectively. For the Indus River early spring snow covered area was extracted and related to April through June stream flow from 1967-1971 using a regression equation. Prediction of the April-June 1972 stream flow from the satellite data was within three percent of the actual total. Composited results from two years of data over seven Wind River Mountain watersheds indicated that LANDSAT-1 snow cover observations, separated on the basis of watershed elevation, could also be related to runoff in significant regression equations.

The ongoing Operational Applications of Satellite Snowcover Observations (OASSO) Project of NASA's Applications Systems Verification Test (ASVT) Program is discussed. The general objectives, organization, and study-area activities of the OASSO program are outlined. It is noted that this part of the ASVT Program is designed to evaluate under operational conditions the overall utility of satellite snowcover observations for stream flow forecasts and will be carried out in four regions centered in Arizona, California, Colorado, and Oregon.

Various techniques for reducing the satellite data to a form usable by the operational agencies were covered in mini-presentations by the operational satellite snow interpretive personnel. Similar discussions were made by operational agency stream flow forecasters on how satellite-derived snow data could be incorporated into runoff forecasting methods.

LANDSAT and NOAA satellites data were used to study snow depth. These snow measurements were used to help forecast runoff and flooding. Many areas of California, Arizona, Colorado, and Wyoming were emphasized.

The capability of the LANDSAT and NOAA satellites to accurately measure snowcovered area on various size watersheds was demonstrated. Recent research has shown a highly significant statistical relationship between satellite-derived snowcovered area at the beginning of the snowmelt period and seasonal runoff. The decision was made to test the results of several satellite snowcovered area studies in an Applications Systems Verification Test (ASVT) Program where quasi-operational evaluations of total technical capability are performed. The objective of these ASVT's is to provide all the information necessary for a potential user to make effective decisions concerning the implementation of the new remote sensing technology in an operational applications system.

A continuous simulation watershed model has been used to perform sensitivity analyses that provide guidance in defining remote sensing requirements for the monitoring of watershed features and processes. The results show that out of 26 input parameters having meaningful effects on simulated runoff, 6 appear to be obtainable with existing remote sensing techniques. Of these six parameters, 3 require the measurement of the areal extent of surface features (impervious areas, water bodies, and the extent of forested area), two require the descrimination of land use that can be related to overland flow roughness coefficient or the density of vegetation so as to estimate the magnitude of precipitation interception, and one parameter requires the measurement of distance to get the length over which overland flow typically occurs. Observational goals are also suggested for monitoring such fundamental watershed processes as precipitation, soil moisture, and evapotranspiration. A case study on the Patuxent River in Maryland shows that runoff simulation is improved if recent satellite land use observations are used as model inputs as opposed to less timely topographic map information.

ERTS-1 satellite imagery was evaluated as a means of providing useful watershed physiography information. From these data physiographic parameters such as drainage basin area and shape, drainage density, stream length and sinuosity, and the percentage of a watershed occupied by major land use types were obtained in three study areas. The study areas were: (1) Southwestern Wisconsin; (2) Eastern Colorado, and (3) portions of the Middle Atlantic States. Using ERTS-1 imagery at 1:250,000 and 1:100,000 scales it was found that drainage basin area and shape and stream sinuosity were comparable (within 10%) in all study areas to physiographic measurements derived from conventional topographic maps at the same scales.

Low resolution meteorological satellite and high resolution earth resources satellite data were used to map snowcovered area over the upper Indus River and the Wind River Mountains of Wyoming, respectively. For the Indus River, early Spring snowcovered area was extracted and related to April through June streamflow from 1967-1971 using a regression equation. Composited results from two years of data over seven Wind River Mountain watersheds indicated that LANDSAT-1 snowcover observations, separated on the basis of watershed elevation, could also be related to runoff in significant regression equations. It appears that earth resources satellite data will be useful in assisting in the prediction of seasonal streamflow for various water resources applications, nonhazardous collection of snow data from restricted-access areas, and in hydrologic modeling of snowmelt runoff.

Consideration of the use of remote sensing technology applied from satellites to obtain information for the rapid and continuing assessment of the hydrologic cycle. A detailed account is given of the hydrological information made available through the activities of the ERTS-1 satellite, an experimental satellite entirely devoted to earth resources observations, and the NOAA-2 satellite, a high-resolution operational environmental satellite. Following a description of the satellites and their payloads, it is shown how with their aid information can be obtained regarding atmospheric moisture, surface water and snow cover, glaciers, potential flood situations, and subsurface water fluctuations. In addition, the use of the ERTS-1 and NOAA-2 satellites in watershed characterization and modeling and in monitoring water quality is discussed.

The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicated that ERTS-1 is extremely useful as a regional tool for flood mamagement. Quantitative estimates of area flooded were made in St. Charles County, Missouri and Arkansas. Flood hazard mapping was conducted in three study areas along the Mississippi River using pre-flood ERTS-1 imagery enlarged to 1:250,000 and 1:100,000 scale. Initial results indicate that ERTS-1 digital mapping of flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.

A region of low brightness temperature lying along the Mississippi River from Cairo, Illinois, to Morganza, Louisiana was observed in early Nimbus 5 Electrically Scanning Microwave Radiometer images. This region, which generally corresponds to an outwash aquifer in the Mississippi Valley, had brightness temperatures, at times as much as 40 K below the surrounding (drier) older uplands. Fluctuations of as much as 30 K were observed during the time interval 15 December 1972 to 28 February 1973. Comparison images taken from the Earth Resources Technology Satellite indicate that the study area is aligned with the Mississippi River floodplain, a region of potentially high soil moisture content. The brightness temperature fluctuations were compared with variations in precipitation and other hydrologic parameters in order to delineate the causative factors.

Some ERTS-1 observations of snowcover, turbidity variations in the major lakes, surface water area changes, land use features, and phenomena associated with industrial emissions are described. Turbidity patterns in the major water bodies can be observed that appear to be related to the general wind flow, or to lake circulation patterns, and the chemical or biological constituents in the water. Monthly, seasonal, and annual changes in surface water extent can be monitored and serve as indicators of water availability. Time and space variations in snowcover that are a function of exposure or time of year were observed in some regions. Specific measurements of snowline altitude during the major snowmelt period of 1973 were obtained. The existence and effect of industrial emission on vegetation were found to be detectable.

The delineation of flood-prone areas is an important activity in several parts of the world. Conventional methods map the topography surrounding the river via ground surveys and supplementary aerophotography. The conventional method costs approximately $2,000 per river-kilometer, is laborious and time-consuming. ERTS information can supplement this method by two complementary techniques: (1) the dynamic method images the floods as they occur, exploiting the fact that visible evidence of inundation remains for a substantial period after the high waters have receded; (2) the static method utilizes the fact that several flood plains have been found recognizable on ERTS imagery from distinctive, permanent indicators left by previous floods. For areas whose full development is still in the future, the dynamic method allows the gradual buildup with time of a flood plain map, by simply correlating existing ERTS imagery. The static method allows in several areas, a first-cut indication, of proneness to floods.

The Spring 1973 Mississippi River flood was investigated using remotely sensed data from ERTS-1. Both manual and automatic analyses of the data indicate that ERTS-1 is extremely useful as a regional tool for flood and floodplain management. The maximum error of such flood area measurements is conservatively estimated to be less than five percent. Change detection analysis indicates that the flood had major impacts on soil moisture, land pattern stability, and vegetation stress. Flood hazard identification was conducted using photointerpretation techniques in three study areas along the Mississippi River using pre-flood ERTS-1 imagery down to 1:100,000 scale. Flood prone area boundaries obtained from ERTS-1 were generally in agreement with flood hazard maps produced by the U.S. Army Corps of Engineers and the U.S. Geological Survey although the latter are somewhat more detailed because of their larger scale. Initial results indicate that ERTS-1 digital mapping of the flood-prone areas can be performed at least 1:62,500 which is comparable to conventional flood hazard map scales.

The history of remote sensing of snow cover is reviewed and the following topics are covered: various techniques for interpreting LANDSAT and NOAA satellite data; the status of future systems for continuing snow hydrology applications; the use of snow cover observations in streamflow forecasts by Applications Systems Verification and Transfer participants and selected foreign investigators; and the benefits of using satellite snow cover data in runoff prediction.

Areas of the steppes of central Russia, the high plains of Montana and North Dakota, and the high plains of Canada were studied in an effort to determine the relationship between passive microwave satellite brightness temperature, surface air temperature, and snow depth. Significant regression relationships were developed in each of these homogeneous areas. Results show that sq R values obtained for air temperature versus snow depth and the ratio of microwave brightness temperature and air temperature versus snow depth were not as the sq R values obtained by simply plotting microwave brightness temperature versus snow depth. Multiple regression analysis provided only marginal improvement over the results obtained by using simple linear regression.

The author has identified the following significant results. A snow runoff model developed for European mountain basins was used with LANDSAT imagery and air temperature data to simulate runoff in the Rocky Mountains under conditions of large elevation range and moderate cloud cover (cloud cover of 40% or less during LANDSAT passes 70% of the time during a snowmelt season). Favorable results were obtained for basins with area not exceeding serval hundred square kilometers and with a significant component of subsurface runoff.

Snow accumulation and depletion at specific locations can be monitored from space by observing related variations in microwave brightness temperatures. Using vertically and horizontally polarized brightness temperatures from the Nimbus 6 electrically scanning microwave radiometer, a discriminant function can be used to separate snow from no snow areas and map snowcovered area on a continental basis. For dry snow conditions on the Canadian high plains, significant relationships between snow depth or water equivalent and microwave brightness temperature were developed which could permit remote determination of these snow properties after acquisition of a wider range of data. The presence of melt water in the snowpack causes a marked increase in brightness temperature which can be used to predict snowpack priming and timing of runoff. As the resolutions of satellite microwave sensors improve the application of these results to snow hydrology problems should increase.

Monitoring of precipitation using remote sensing has been carried out successfully over oceans with passive microwave data and over land with visible and infrared data. Further research is necessary to improve accuracy and timeliness of estimations in a variety of rainfall situations. Snowmelt runoff prediction has been demonstrated using satellite snowcover data. Snow depth and wetness measurements are feasible using microwave techniques. The monitoring of ice cover, type, and thickness has been carried out successfully using remote methods. Results from remote sensing evapotranspiration studies have been inconclusive. The remote measurement of evapotranspiration seems to be the most challenging of all applications of remote sensing to hydrometeorology.