Department of Civil, Surveying and Environmental Engineering. Includes bibliographical references (leaves R-1--R-9)

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A simple model of surface and sub -surface soil temperature was developed at the watershed scale ( -100 km2) in a semi -arid rangeland environment. The model consisted of a linear combination of air temperature and net radiation and assumed: 1) topography controls the spatial distribution of net radiation, 2) near- surface air temperature and incoming solar radiation are relatively homogeneous at the watershed scale and are available from ground stations and 3) soil moisture dominates transient soil thermal property variability. Multiplicative constants were defined to account for clear sky diffuse radiation, soil thermal inertia, an initially fixed ratio between soil heat flux and net radiation and exponential attenuation of solar radiation through a partial canopy. The surface temperature can optionally be adjusted for temperature and emissivity differences between mixed hare soil and vegetation canopies. Model development stressed physical simplicity and commonly available spatial and temporal data sets. Slowly varying surface characteristics, such as albedo, vegetation density and topography were derived from a series of Landsat TM images and a 7.5" USGS digital elevation model at a spatial resolution of 30 m. Diurnally variable atmospheric parameters were derived from a pair of ground meteorological stations using 30 -60 min averages. One site was used to drive the model, the other served as a control to estimate model error. Data collected as part of the Monsoon '90 and WG '92 field experiments over the ARS Walnut Gulch Experimental. Watershed in SE Arizona were used to validate and test the model. Point, transect and spatially distributed values of modeled surface temperature were compared with synchronous ground, aircraft and satellite thermal measurements. There was little difference between ground and aircraft measurements of surface reflectance and temperature which makes aircraft transects the preferred method to "ground truth" satellite observations. Mid- morning modeled surface temperatures were within 2° C of observed values at all but satellite scales, where atmospheric water vapor corrections complicate the determination of accurate temperatures. The utility of satellite thermal measurements and models to study various ground phenomena (eg. soil thermal inertia and surface energy balance) were investigated. Soil moisture anomalies were detectable, but were more likely associated with average near -surface soil moisture levels than individual storm footprints.

A simple model of surface and sub-surface soil temperature was developed at the watershed scale (-100 km²) in a semi-arid rangeland environment. The model consisted of a linear combination of air temperature and net radiation and assumed: (1) topography controls the spatial distribution of net radiation, (2) near-surface air temperature and incoming solar radiation are relatively homogeneous at the watershed scale and are available from ground stations and (3) soil moisture dominates transient soil thermal property variability. Multiplicative constants were defined to account for clear sky diffuse radiation, soil thermal inertia, an initially fixed ratio between soil heat flux and net radiation and exponential attenuation of solar radiation through a partial canopy. The surface temperature can optionally be adjusted for temperature and emissivity differences between mixed bare soil and vegetation canopies. Model development stressed physical simplicity and commonly available spatial and temporal data sets. Slowly varying surface characteristics, such as albedo, vegetation density and topography were derived from a series of Landsat TM images and a 7.5" USGS digital elevation model at a spatial resolution of 30 m. Diurnally variable atmospheric parameters were derived from a pair of ground meteorological stations using 30-60 min averages. One site was used to drive the model, the other served as a control to estimate model error. Data collected as part of the Monsoon '90 and WG '92 field experiments over the ARS Walnut Gulch Experimental Watershed in SE Arizona were used to validate and test the model. Point, transect and spatially distributed values of modeled surface temperature were compared with synchronous ground, aircraft and satellite thermal measurements. There was little difference between ground and aircraft measurements of surface reflectance and temperature which makes aircraft transects the preferred method to "ground truth" satellite observations. Mid-morning modeled surface temperatures were within 2° C of observed values at all but satellite scales, where atmospheric water vapor corrections complicate the determination of accurate temperatures. The utility of satellite thermal measurements and models to study various ground phenomena (e.g. soil thermal inertia and surface energy balance) were investigated. Soil moisture anomalies were detectable, but were more likely associated with average near-surface soil moisture levels than individual storm footprints.

Natural factors limit the extent to which land disturbed by man's activities such as the strip mining of coal may be returned to productivity. In the western United States, the availability of water is frequently the most important of these factors. To assist decision makers in land restoration efforts, a procedure is developed by which precipitation and the distribution of precipitation water on reclaimed areas may be forecast. With this information, reclamation decisions can be made with increased confidence. The initial phase of the procedure is the development of a sequence-based stochastic precipitation model which provides as output simulated sequences of annual precipitation events. Probability distributions for storm parameters such as precipitation per event, event duration, distribution of events in time, etc. are obtained from analysis of historic climatological data for the study area. From these distributions simulated series of annual events possessing statistical characteristics of the actual event sequences are generated. Statistical analysis shows no significant differences between parameters of the actual events and those generated by the model. The stochastic precipitation model is used to drive a deterministic model simulating other hydrologic processes. In the second model, a finite difference solution records changes in water content within the soil profile. Root extraction, evaporation, infiltration and percolation are also simulated based upon changing hydraulic head at selected depth intervals. The kinematic wave approximation and the continuity of mass equation are used to route overland flow from the watershed. The model accurately predicts the distribution of water resulting from annual series of precipitation and potential evapotranspiration event sequences.

The basic concepts of hydrologic forecasting using the Streamflow Synthesis And Reservoir Regulation Model of the U.S. Army Corps of Engineers, auto-regressive-moving-average time series models (including Greens' functions, inverse functions, auto covariance Functions, and model estimation algorithm), and the Kalman filter (including state space modeling, system uncertainty, and filter algorithm), were explored. A computational experiment was conducted in which the Kalman filter was applied to update Mehama local basin model (Mehama is a 227 sq. miles watershed located on the North Santiam River near Salem, Oregon.), a typical SSARR basin model, to streamflow measurements as they became available in simulated real time. Among the candidate AR and ARMA models, an ARMA(l,l) time series model was selected as the best-fit model to represent the residual of the basin model. It was used to augment the streamflow forecasts created by the local basin model in simulated real time. Despite the limitations imposed by the quality of the moisture input forecast and the design and calibration of the basin model, the experiment shows that the new stochastic methods are effective in significantly improving the flood forecast accuracy of the SSARR model.

Understanding the processes involved in the transport of dissolved gas plumes in groundwater aquifers is essential for comprehending the effect that these transport processes can have on site characterization and remedial design applications. Previous laboratory and field studies have indicated that dissolved gas transport in groundwater can be greatly affected by the presence of even small amounts of trapped gas in the pore space of an aquifer. Recently, Fry et al. (1995) reported an increase in retardation factors R (where R=pore water velocity/dissolved gas velocity) for dissolved oxygen with increasing amounts of trapped gas. Fry showed that the retardation factor for a dissolved gas can be predicted using a relationship between the dimensionless Henry's Law constant for the dissolved gas, the volumetric gas content (i.e., the fraction of the total volume occupied by trapped gas), and the volumetric water content (i.e., the fraction of total volume occupied by water). In their experiments, Fry et al. (1995) found this relationship in an equilibrium model accurately predicted observed retardation factors for dissolved oxygen when the volumetric gas content was small, but underpredicted retardation factors for larger volumetric gas contents. Also, predicted breakthrough curves for dissolved oxygen obtained by incorporating this relationship into the advection-dispersion equation did not match the shape of experimentally observed breakthrough curves. The experimental curves were asymmetrical with long tails indicating that the local equilibrium assumption is inaccurate and suggesting that mass transfer of oxygen between the aqueous and trapped gas phases is diffusion limited. In an effort to gain further understanding of this process, a kinetic model was developed for dissolved gas transport that includes a diffusion type expression for the rate of gas transfer between the mobile aqueous and trapped gas phases. The model was tested in a series of transport experiments conducted in sand packed columns with varying amounts and composition of trapped gas. The kinetic model was found to better fit the shape of dissolved oxygen breakthrough and elution curves than the equilibrium model of Fry et al. (1995). This model was then extended to the case of two-dimensions to simulate dissolved gas transport in the presence of trapped gas under conditions that approximate injection and extraction wells used to distribute dissolved gases in an aquifer (e.g. to promote in situ bioremediation processes or to perform a dissolved gas tracer test). We then compared these predicted concentrations with measured concentrations obtained in a series of dissolved gas transport experiments in a large-scale physical aquifer model using two dissolved gases (oxygen and hydrogen) with very different physical properties. The model could accurately fit the development and movement of these plumes providing that key parameters, the amount of trapped gas and the effective mass transfer coefficient, were adjusted between the injection and drift stages. / Graduation date: 1997

No description available.

Abstract not available

Design of engineering projects involve a certain amount of uncertainty. How should design decisions be taken in face of the uncertainty? What is the most efficient way of handling the data? Decision theory can provide useful answers to these questions. The literature review shows that decision theory is a fairly well developed decision method, with almost no application in hydrology. The steps of decision theoretic analysis are given. They are augmented by the concept of expected expected opportunity loss, which is developed as a means of measuring the expected value of additional data before they are received. The method is applied to the design of bridge piers and flood levees for Rillito Creek, Pima County, Arizona. Uncertainty in both the mean and the variance of the logarithms of the peak flows of Rillito Creek is taken into account. Also shown are decision theoretic methods for: 1) handling secondary data, such as obtained from a regression relation, 2) evaluating the effect of the use of non - sufficient statistics, 3) considering alternate models and 4) regionalizing data.It is concluded that decision theory provides a rational structure for making design decisions and for the associated data collection and handling problems.