SATELLITE MICROWAVE OBSERVATIONS OF SOIL MOISTURE VARIATIONS1

ABSTRACT: Results from studies in the Illinois-Indiana and Texas-Oklahoma areas indicate that satellite microwave observations at the 1.55 cm wavelength are responsive to relative moisture variations in the near surface layer of the soil. Because significant vegetation cover absorbs the 1.55 cm microwave emission from the soil, the target area must be predominately bare soil or low density vegetation cover for meaningful measurements to result. The 25 km resolution of the satellite sensor limits application of the microwave techniques to large areas such as watersheds or agricultural districts rather than individual fields. In general, at 1.55 cm. there is an inverse relationship between microwave brightness temperature and changes in soil moisture levels (as indicated by antecedent rainfall) in agricultural regions before the planting of crops or during the early growing season when vegetation cover is sparse. Even early season observations should be of great value in deciding on the time and type of crop planting and for initial irrigation scheduling when the root zone is still in close proximity to the surface.     

FLOOD HAZARD STUDIES IN THE MISSISSIPPI RIVER BASIN USING REMOTE SENSING1

ABSTRACT. 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-I is extremely useful as a regional tool for flood management. 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. The flood prone areas delineated on these maps correspond to areas that would be inundated by significant flooding (approximately the 100 year flood). The flood prone area boundaries were generally in agreement with flood hazard maps produced by the U. S. Army Corps of Engineers and 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 flood prone areas can be performed at 1:62,500 which is comparable to some conventional flood hazard map scales.     

LAKE EVAPORATION STUDIES USING SATELLITE THERMAL INFRARED DATA1

Thermal infrared radiation data were acquired by the Heat Capacity Mapping Mission (HCMM) satellite over the surface area (385 km²) of Utah Lake during periodic overpasses in 1978 and 1979. The thermal infrared data were converted to lake surface temperatures which were subsequently used in correlations with lake evaporation. Correlations between HCMM surface temperature and pan-derived evaporation exceeded r = 0.90 when HCMM night and day/night average temperatures and two-day average evaporation values were tested. Similar regression studies were done using monthly data from a conceptual evaporation model and the evaporation pan versus monthly HCMM temperature data. In this test both the HCMM day and night monthly temperature versus the monthly model or pan evaporation had correlations exceeding r = 0.95. Empirical estimates of both short and long term lake evaporation using satellite thermal infrared data seem feasible. Attempts to use the HCMM thermal information as direct input to a theoretical approach to calculating evaporation were inconclusive; however, a definite potential seems to exist.     

DEVELOPMENT AND TESTING OF A SNOWMELT-RUNOFF FORECASTING TECHNIQUE1

ABSTRACT: The snowmelt-runoff model (SRM) was used to produce accurate simulations of streamfiow during the snowmelt period (April-September) for ten years on the Rio Grande Basin (3419 km²) near Del Norte, Colorado, U.S.A. In order to use SRM in the forecast situation, it was necessary to develop a family of snow cover depletion curves for each elevation zone based on accumulated snow water equivalent on April 1. Selection of an appropriate curve for a particular year from snow course measurements allows input of the daily snow cover extent to SRM for forecast purposes. Data from three years (1980, 1981, and 1985) were used as a quasi-forecast test of the procedure. In these years forecasted snow cover extent data were input to SRM, but observed temperature and precipitation data were used. The resulting six-month hydrographs were very similar to the hydrographs in the ten simulation years previously tested based on comparisons of performance evaluation criteria. Based on this result, the Soil Conservation Service (SCS) requested SRM forecasts for 1987 on the Rio Grande. Using the same procedure but with SCS estimated temperature and precipi-tation data, SRM produced a forecast hydrograph that had a r²= 0.82 and difference in seasonal volume of 4.4 percent. To approximate actual operational conditions, SRM computed daily flows were updated every seven days with measured flows. The resulting forecast hydrograph had a R²= 0.90 and a difference in volume of 3.5 percent. The method developed needs to be refined and tested on additional years and basins, but the approach appears to be applicable to operational runoff forecasting using remote sensing data.     

EFFECT OF SIMULATED CLIMATE CHANGE ON SNOWMELT RUNOFF MODELING IN SELECTED BASINS1

ABSTRACT: The projected increase in the concentration of CO₂ and other greenhouse gases in the atmosphere is likely to result in a global temperature increase. This paper reports on the probable effects of a temperature increase and changes in transpiration on basin discharge in two different mountain snowmelt regions of the western United States. The hydrological effects of the climate changes are modeled with a relatively simple conceptual, semi-distributed snowmelt runoff model. Based on the model results, it may be concluded that increased air temperatures will result in a shift of snowmelt runoff to earlier in the snowmelt season. Furthermore, it is shown that it is very important to include the expected change in climate-related basin conditions resulting from the modeled temperature increase in the runoff simulation. The effect of adapting the model parameters to reflect the changed basin conditions resulted in a further shift of streamflow to April and an even more significant decrease of snowmelt runoff in June and July. If the air temperatures increase by approximately 5°C and precipitation and accumulated snow amounts remain about the same, runoff in April and May, averaged for the two basins, is expected to increase by 185 percent and 26 percent, respectively. The runoff in June and July will decrease by about 60 percent each month. Overall, the total seasonal runoff decreases by about 6 percent. If increased CO₂ concentrations further change basin conditions by reducing transpiration by the maximum amounts reported in the literature, then, combined with the 5°C temperature increase, the April, May, June, and July changes would average +230 percent, +40 percent, ?55 percent, and ?45 percent, respectively. The total seasonal runoff change would be +11 percent.     

EXTRACTION AND UTILIZATION OF SPACE ACQUIRED PHYSIOGRAPHIC DATA FOR WATER RESOURCES DEVELOPMENT1

ABSTRACT: ERTS-1 satellite imagery has been 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 Land use information can be usefully extracted for watersheds as small as 30 mi²(78 km²) in area. Improved drainage network and density information is obtained from ERTS-1 imagery in dissected areas such as Southwestern Wisconsin, but in heavily vegetated areas (Middle Atlantic States) or areas with little physical relief (Eastern Colorado) low order streams are difficult to detect and the derived drainage densities are significantly smaller than those obtained from standard maps. It is concluded that ERTS-1 imagery can be employed to advantage in mean annual runoff prediction techniques and in providing or maintaining land use information used in the calibration and operation of watershed models.     

WATER RESOURCES APPLICATIONS OF STREAM CHANNEL CHARACTERISTICS ON SMALL FORESTED BASINS1

ABSTRACT. Stream channel characteristics were found to be useful indices to the hydrology of 27 small forested basins in the Northeast United States. Channel width alone explained 37 percent of the variation in mean annual runoff, whereas channel width combined with basin area explained 78 percent of the variation in mean annual runoff. This approached the percentage of variation in mean annual runoff explained by mean annual precipitation (83 percent). A simulated 15% increase in precipitation, such as might occur in a weather modification project, produced increases in channel width, depth, and channel area of 3, 4, and 8 percent, respectively.     

MODEL ACCURACY IN SNOWMELT-RUNOFF FORECASTS EXTENDING FROM 1 TO 20 DAYS1

ABSTRACT: This paper examines the performance of snowmelt-runoff models in conditions approximating real-time forecast situations. These tests are one part of an intercomparison of models recently conducted by the World Meteorological Organization (WMO). Daily runoff from the Canadian snowmelt basin Illecille. waet (1155 km², 509–3150 m a.s.l.) was forecast for 1 to 20 days ahead. The performance of models was better than in a previous WMO project, which dealt with runoff simulations from historical data, for the following reasons: (1) conditions for models were more favorable than a real-time forecast situation because measured input data and not meteorological forecast inputs were distributed to the modelers; (2) the selected test basin was relatively easy to handle and familiar from the previous WMO project; and (3) all kinds of updating were allowed so that some models even improved their accuracy towards longer forecast times. Based on this experience, a more realistic follow-up project can be imagined which would include temperature forecasts and quantitative precipitation forecasts instead of measured data.     

ASSESSMENT OF REMOTE SENSING INPUT TO HYDROLOGIC MODELS1

Remotely sensed variables such as land cover type and snow-cover extent can currently be used directly and effectively in a few specific hydrologic models. Regression models can also be developed using physiographic and snow-cover data to permit estimation of discharge characteristics over extended periods such as a season or year. Most models, however, are not of an appropriate design to readily accept as input the various types of remote sensing parameters that can be obtained now or in the future. Because this new technology has the potential for producing hydrologic data that has significant information content on an areal basis, both inexpensively and repetitively, effort should be devoted now to either modifying existing models or developing new models that can use these data. Minor modifications would at least allow the remote sensing data to be used in an ancillary way to update the model state variables, whereas major structural modifications or new models would permit direct input of the data through remote sensing compatible algorithms. Although current remote sensing inputs to hydrologic models employ only visible and near infrared data, model modification or development should accommodate microwave and thermal infrared data that will be more widely available in the future.