HYDROLOGIC UNCERTAINTY MEASURE AND NETWORK DESIGN1

ABSTRACT: This paper presents a simple methodology, using the entropy concept, to estimate regional hydro logic uncertainty and information at both gaged and ungaged grids in a basin. The methodology described in this paper is applicable for (a) the selection of the optimum station from a dense network, using maximization of information transmission criteria, and (b) expansion of a network using data from an existing sparse network by means of the information interpolation concept and identification of the zones from minimum hydrologic information. The computation of single and joint entropy terms used in the above two cases depends upon single and multivariable probability density functions. In this paper, these terms are derived for the gamma distribution. The derived formulation for optimum hydrologic network design was tested using the data from a network of 29 rain gages on Sleeper River Experimental Watershed. For the purpose of network reduction, the watershed was divided into three subregions, and the optimum stations and their locations in each subregion were identified. To apply the network expansion methodology, only the network consisting of 13 stations was used, and feasible triangular elements were formed by joining the stations. Hydrologic information was calculated at various points on the line segments, and critical information zones were identified by plotting information contours. The entropy concept used in this paper, although derived for single and bivaviate gamma distribution, is general in type and can easily be modified for other distributions by a simple variable transformation criterion.     

HYDROLOGIC IMPACT OF WEATHER MODIFICATION1

ABSTRACT: Weather modification is being proposed as a routine method of augmenting agricultural water supplies in the Southern Great Plains. This paper discusses some of the potential hydrologic impacts of weather modification. Previous work in assessing hydrologic impact is covered; the conclusion is drawn that the work is insufficient. An approach based on hydrologic models is suggested that can consider uncertainties about the effect of weather modification on rainfall and some uncertainties about the effect of model error on impact conclusions.     

HYDROLOGIC RESPONSE OF MASSACHUSETTS WATERSHEDS1

Hydrologic response, defined as the annual direct runoff divided by the annual precipitation, was computed for twenty-one watersheds in or near western Massachusetts, using a total of 232 years of hydrologic records. Variability of the results over the period of analysis was greater than is desirable to inspire confidence in the usefulness of the hydrologic response function; however, the results do suggest that the hydrologic response concept, with appropriate refinements, could be applied successfully to the problem of delineating hydrologic provinces and determination of drainage and storage in unregulated watersheds.     

SPACE-TIME MODELING OF VECTOR HYDROLOGIC SEQUENCES1

Stochastic modeling of vector hydrologic sequences is examined with a general class of space-time autoregressive integrated moving average (STARIMA) models. The models describe spatial and temporal autocorrelatjon, through dependent variables lagged both in space and time. The model structures incorporate a hierarchical ordering scheme to map the vector of observations into a network configuration. The neighboring structure used introduces a physical/geographical hierarchy to enable the model identification procedures to assist in determining appropriate correlative relationships. The three-stage iterative space-time model building procedure is illustrated using average monthly streamfiow data for a four-station network of the Southeastern Hydropower System.     

DEVELOPMENT OF EARTH SATELLITE TECHNOLOGY FOR THE TELEMETRY OF HYDROLOGIC DATA1

ABSTRACT The use of satellite telemetry is playing a major role in the collection of hydrologic data. Advancing technology and availability of government satellites have permitted many agencies to take advantage of new procedures for acquiring data from automated remote data collection stations. Experiments with Earth satellite technology started in the 1960's and 1970's, with the polar-orbiting National Aeronautics and Space Administration Nimbus and Landsat satellites. Subsequent advancements took place through the development phase to operational systems using the Geostationary Operational Environmental Satellite (GOES) of the National Oceanic and Atmospheric Administration. This satellite system supports more than 2,500 active telemetry sites, of which approximately 1,200 are Geological Survey stream-gaging stations for the collection of hydrologic data. A satellite data collection system is made up of three primary components; a small battery-operated radio, and Earth-orbiting satellite, and an Earth receive and data processing station. The data relay satellites' vast aerial view of the Earth's surface gives satellite telemetry a large advantage over ground-based systems for the collection of real-time hydrologic data for flood warning, reservoir management, irrigation water control, hydropower generation, and the operation of hydrologic stations.     

MODEL PREDICTIONS OF WATERSHED HYDROLOGIC COMPONENTS: COMPARISON AND VERIFICATIION1

ABSTRACT: Model predictions of the relatively simple soil compartment model SESOIL are compared with those of the more data-intensive terrestrial ecosystem hydrology model AGTEHM. Comparisons were performed using data from a deciduous forest stand watershed, a grassland watershed, and two agricultural field plots. Good agreement was obtained between model predictions for annual values of infiltration, evapotranspiration, surface runoff, and groundwater runoff. SESOIL model predictions also compare well with empirical measurements at the forest stand and the grassland watersheds.     

REASONABLY FULL HYDROLOGIC DEVELOPMENT OF RESERVOIR SITES1

The size of multipurpose reservoir development is usually determined by an economic analysis of reservoir capabilities and the present and projected water resources needs which can be satisfied. This analysis is referred to as project formulation, wherein optimum conditions are sought. In responding to multiple objectives, i.e., national economic development, regional development and environmental quality, which are being considered in river basin planning in recent years, reservoirs should provide for reasonably full hydrologic development. Additional storage will be needed to provide opportunities for economic development, as well as meet unexpected development. Also, it provides more flow regulation capability for quality of environment considerations. An analysis has been made on twelve reservoir sites in the New York State portion of the Susquehanna River Basin to determine the so-called “reasonably full hydrologic development of reservoir sites.” Hydrologic, economic, environmental and physical characteristics of the sites are taken into consideration. For normal conditions, it can be concluded that a yield equivalent to about 80 percent of the average discharge (runoff) can be considered as reasonably full hydrologic development for reservoir sites in the Susquehanna River Basin in New York. The same technique can be applied elsewhere to determine reasonably full hydrologic development of reservoir sites.     

COMPARING SOME METHODS OF ESTIMATING MEAN AREAL RAINFALL1

ABSTRACT: A comparison of 13 different methods of estimating mean areal rainfall was made on two areas in New Mexico, U.S.A., and one area in Great Britain. Daily, monthly and yearly rainfall data were utilized. All methods, in general, yielded comparable estimates, especially for yearly values. This suggested that a simpler method would be preferable for estimating mean areal rainfall in these areas.     

CORRELATION OF SELECTED WELL WATER QUALITY PARAMETERS WITH SOIL AND AQUIFER HYDROLOGIC PROPERTIES1

ABSTRACT: The geographical distribution of well water specific electrical conductivity and nitrate levels in a 932 km² ground water quality study area in the Fresno-Clovis, California, indicated that frequently areas of lower ground water salinity were also areas of relatively greater soil and aquifer permeability. From these observations and certain assumptions we hypothesized that the quality of the well water should be better in areas with permeable soils and geological formations. Correlation and multiple linear regression analysis supported this hypothesis for well water salinity. However, well water nitrate levels were significantly negatively correlated with only the estimated equivalent specific yield of the aquifer system. The multiple R² values of the most significant multiple linear regression models showed that only a fourth to a third of the variability in well water specific electric conductivity and nitrate levels could be ascribed to the effects of the hydrogeological parameters considered with more than 90 percent confidence. This indicates that three-fourths to two-thirds of the variability in ground water salinity and nitrate levels may be related to land use. Thus, there is considerable room for land use management techniques to improve ground water quality and reduce its variability.     

NONPARAMETRIC STATISTICAL METHODS IN URBAN HYDROLOGIC RESEARCH1

ABSTRACT. In urban hydrologic studies, it is often necessary to determine the effect of changes in urban land use patterns on such runoff characteristics as flood peaks and flow volumes. Nonparametric statistical methods have certain properties that make them a valuable tool for detecting hydrologic change caused by a treatment, such as urbanization, that changes watershed over a period of time. As many hydrologists do not have a working familiarity with nonparametric methods, a number of them are used for illustrative purposes to analyze the effect of urbanization on 24 years of annual flood peaks for a Louisville, Kentucky, watershed. In the example, urbanization was found to increase the central tendency, but not the dispersion of the peaks. Peak flows modeled by holding watershed parameters constant were also found to be increasing because of an upward trend in precipitation. By following the numerical examples in the paper and looking up test statistics in referenced sources, the reader can easily apply these methods to other situations.     

DETERMINISTIC HYDROLOGIC MODELING OF GRAZING SYSTEM IMPACTS ON INFILTRATION RATES1

ABSTRACT: Techniques for predicting the hydrologic effects of grazing schemes have heretofore been unavailable. The available literature on grazing intensity influences on infiltration rates is used as a basis for a model of infiltration behavior in response to grazing systems. Background, development, cautions, and an example are given.     

REGIONAL FREQUENCY ANALYSIS OF HYDROLOGIC MULTIYEAR DROUGHTS1

This paper is concerned with regional frequency analysis of hydrologic multiyear droughts. A drought event is defined by three parameters: severity, duration, and magnitude. A method is proposed here to standardize drought severities with a duration adjustment to enable comparison among drought events. For purposes of a regional study, the index drought method is selected and applied to standardized droughts to give a regional frequency curve. However, the recurrence intervals of the drought events obtained from index drought method are limited to the historic period of record. Therefore, by taking advantage of random variations of droughts in both time and space, a multivariate simulation model is used to estimate exceedence probabilities associated with regional drought maxima. This method, named the regional extreme drought method, is capable of generating a series of drought events which, although they have not occurred historically, are more severe than historic events. By combining the results of the index drought method and regional extreme drought analysis, a regional drought probability graph is constructed which ranges from severe droughts to more frequent droughts. This procedure is applied to the mean annual flow records of streams located in the San Joaquin Valley of California, and drought-severity-frequency plots are prepared for 1-year, 2-year, and 3-year durations.     

THE PALMER DROUGHT SEVERITY INDEX AS A MEASURE OF HYDROLOGIC DROUGHT1

ABSTRACT: The Palmer Drought Severity Index (PDSI) is perhaps the most widely used regional drought index. However, there is considerable ambiguity about its value as a measure of hydrologic drought. In this paper the PDSI for climatic divisions in New Jersey is compared to the occurrence within each climatic division of streamflows in their lower quartile for the month (streamflow index), and ground-water levels in their lower quartile for the month (ground-water index). These indices are found to have distinct properties. It is not uncommon for PDSI values to indicate “severe” or “extreme” drought at times when the streamflow or groundwater index is above its lower quartile at many stations within the climatic division. The PDSI values and groundwater index indicate more persistent subnormal conditions than the streamflow index for truncation levels yielding the same total duration of drought over a period. The ground-water index tends to indicate a later beginning to droughts and of the three indices is the most conservative indicator of a drought's end. Drought timing and duration properties for the ground-water index are found to be highly influenced by the average depth to water in the well. Overall, the three indices of drought can provide three very different characterizations of drought. In particular, the results indicate that considerable caution should be exercised in drawing conclusions about hydrologic drought from the PDSI.     

EFFECTIVE USE OF LANDSAT DATA IN HYDROLOGIC MODELS1

ABSTRACT: In a cooperative demonstration project, NASA and the U.S. Army Corps of Engineers (Corps) compared conventional and Landsat-derived land-use data for use in hydrologic models, and the resulting discharge frequency curves were analyzed. When a grid-based data-management system was used on a cell-by-cell basis (size about 1.1 acres or 0.45 hectare), Landsat classification accuracy was only 64 percent, but, when the grid cells were aggregated into watersheds, the classification accuracy increased to about 95 percent. When both conventional and Landsat land-use data were input to the HEC-1 model for generating discharge frequency curves, the differences in calculated discharge were judged insignificant for subbasins as small as 1.0mi² (2.59 km²). For basins larger than 10mi² (25.9km²), use of the Landsat approach is more cost-effective than use of conventional methods. Digital Landsat data can also be used effectively by local and regional agencies for hydrologic analysis by incorporating the data into grid-based data-management systems. The transfer of this new technology is well under way through inclusion in some Corps training courses and through use by both county government personnel and private consultants.     

HYDROLOGIC EFFECTS OF TWO METHODS OF HARVESTING MATURE SOUTHERN PINE1

ABSTRACT: Hydrologic responses to logging with skidders and responses to logging with a cable yarder are compared. After a 23-year calibration with an undisturbed control catchment, mixed stands of shortleaf pine (Pinus echinata Mill.) and hardwoods were clearfelled on two small catchments in the hilly Coastal Plain of north Mississippi and observed for five years. Runoff increased 370 mm (skidded) and 116 mm (yarded) during the first year with 1876 mm of rainfall, and 234 mm (skidded) and 228 mm (yarded) during the second year when 1388 mm of precipitation equaled the calibration mean. Sediment concentrations for the yarded catchment during the first two years averaged 641 and 1,629 mg L^?1, respectively, and yields were 6,502 and 12,086 kg ha^?1. Compared to calibration means of 74 mg L^?1 and 142 kg ha^?1, these extreme values can be attributed largely to transport of sediment stored in the channel and to erosion of subsurface flow paths, which was exacerbated by high flow volumes. During the first year, the concentration (231 mg L^?1) and yield (2,827 kg ha^?1) for the control catchment also exceeded the calibration means. However, concentrations (134 mg L^?1) and yields (1,806 kg ha^?1) for the skidded catchment were about 40 percent lower than for the control catchment during the first year, and were higher than those for the control only during the second year. Because deep percolation was limited and because rainfall was unusually high, increases in flows and sediment concentrations and yields probably approximate maximum responses to clearcut harvesting in the uplands of the southern Coastal Plain.     

THE APPLICATION OF RIDGE REGRESSION ANALYSIS TO A HYDROLOGIC TARGET-CONTROL MODEL1

ABSTRACT: Ridge regression analysis is used to investigate the stability of regression estimates over twenty-three years of data in a target-control model. Two target stations in the Wind River Range in Wyoming are studied using two sets of control variables. The predictive ability of ridge regression analysis is compared to that of ordinary regression analysis. The results of this study indicate improved stability of the estimates of ridge regression over ordinary regression. The predictive ability of the ridge regression estimates is as good or better than regression estimates.     

SIMULATION OF SPATIAL AND TEMPORAL CHANGES IN WATER QUALITY WITHIN A HYDROLOGIC UNIT1

Water quality must be considered in the development and planning aspects of water resource management. To accomplish this, the decision-maker needs to have at his disposal a systematized procedure for simulating water quality changes in both time and space. The simulation model should be capable of representing changes in several parameters of water quality as they are influenced by natural and human factors impinging on the hydrologic system. The objective of this work is two-fold. The first goal is to demonstrate the feasibility of developing and utilizing a water quality simulation model in conjunction with a hydrologic simulation model. The model represents water quality changes in both time and space in response to changing atmospheric and hydrologic conditions and time-varying waste discharges at various points in the system. This model has been developed from and verified with actual field data from a prototype system selected for this purpose. The second aim is to set forth procedural guidelines to assist in the development of water quality simulation models as tools for use in the quality-quantity management of a hydrologic unit.     

INDEXED SEQUENTIAL HYDROLOGIC MODELING FOR HYDROPOWER CAPACITY ESTIMATION1

ABSTRACT: The indexed sequential hydrologic modeling (ISM) methodology is utilized by the Western Area Power Administration as the basis for risk-based estimation of project-dependable hydropower capacity for several federally owned/operated projects. ISM is a technique based on synthetic generation of a series of overlapping short-term inflow sequences obtained directly from the historical record. The validity of ISM is assessed through application to the complex multireservoir hydropower system of the Colorado River basin for providing risk estimates associated with determination of reliable hydrogeneration capacity. Performance of ISM is compared with results from stochastically generated streamflow input data to the Colorado River Simulation System (CRSS). Statistical analysis and comparison of results are based on monthly power capacity, energy generation, and downstream water deliveries. Results indicate that outputs generated from ISM synthetically generated sequences display an acceptable correspondence with those obtained from stochastically generated hydrologic data for the Colorado River Basin.     

REGIONALIZATION OF LOW-FLOW FREQUENCY ESTIMATES: AN ALABAMA CASE STUI)Y1

ABSTRACT: Low-flow estimates, as determined by probabilistic modeling of observed data sequences, are commonly used to describe certain streamflow characteristics. Unfortunately, however, reliable low-flow estimates can be difficult to come by, particularly for gaging sites with short record lengths. The shortness of records leads to uncertainties not only in the selection of a distribution for modeling purposes but also in the estimates of the parameters of a chosen model. In flood frequency analysis, the common approach to mitigation of some of these problems is through the regionalization of frequency behavior. The same general approach is applied here to the case of low-flow estimation, with the general intent of not only improving low-flow estimates but also illustrating the gains that might be attained in so doing. Data used for this study is that which has been systematically observed at 128 streamflow gaging sites across the State of Alabama. Our conclusions are that the log Pearson Type 3 distribution is a suitable candidate for modeling of Alabama low-flows, and that the shape parameter of that distribution can be estimated on a regional basis. Low-flow estimates based on the regional estimator are compared with estimates based on the use of only at-site estimation techniques.     

ON THE MISMATCH BETWEEN DATA AND MODELS OF HYDROLOGIC AND WATER RESOURCE SYSTEMS1

ABSTRACT: Many difficulties exist in the matching of models with data. This paper identifies elements of this problem and discusses considerations involved in model evaluation. The well known multivariate linear regression model is used to illustrate the distinctions between accuracy and precision and between estimation and prediction (because the model is commonly misused.) No amount of additional data will improve the accuracy of a poor model. A high R², while indicative of a good matching between the observed data and model estimates, is a poor criterion for judging adequacy of the model to make good predictions of future events. Model evaluation also includes the problem of introducing secondary data and proxy variables into a model. Secondary data frequently enter, for example, the mass, energy and water budget equations because of difficulties in measuring the primary variables. Proxy variables arise because of a desire to collapse a vector of incomparable values, say, of water quality into a single number. Review of the above issues indicates that model evaluation is a multi-criterion problem, often imbedded in a larger framework where models are intended to meet multiple objectives. The mismatch of models and data has increasing legal and social consequences.