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DisciplineGraduate College (195)

Hydrology and Water Resources (195)

AuthorsNeuman, Shlomo P. (28)Ince, Simon (26)Evans, Daniel D. (25)Sorooshian, Soroosh (25)Simpson, Eugene S. (23)Davis, Donald R. (20)Harshbarger, John W. (19)Warrick, Arthur W. (17)Davis, Stanley N. (14)Maddock, Thomas (14)View MoreTypes
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Rainfall estimation from satellite infrared imagery using artificial neural networks

Hsu, Kuo-lin,1961- (The University of Arizona., 1996)

Infrared (IR) imagery collected by geostationary satellites provides useful information about the dirunal evolution of cloud systems. These JR images can be analyzed to indicate the location of clouds as well as the pattern of cloud top temperatures (Tbs). During the past several decades, a number of different approaches for estimation of rainfall rate (RR) from Tb have been explored and concluded that the Tb-RR relationship is (1) highly nonlinear, and (2) seasonally and regionally dependent. Therefore, to properly model the relationship, the model must be able to: (1) detect and identify a non-linear mapping of the Tb-RR relationship; (2) Incorporate information about various cloud properties extracted from IR image; (3) Use feedback obtained from RR observations to adaptively adjust to seasonal and regional variations; and (4) Effectively and efficiently process large amounts of satellite image data in real-time. In this study, a kind of artificial neural network (ANN), called Modified Counter Propagation Network (MCPN), that incorporates these features, has been developed. The model was calibrated using the data around the Japanese Islands provided by the Global Precipitation Climatology Project (GPCP) First Algorithm Intercompari son Project (AIP-I). Validation results over the Japanese Islands and Florida peninsula show that by providing limited ground-truth observation, the MCPN model is effective in monthly and hourly rainfall estimation. Comparison of results from MCPN model and GOES Precipitation Index (GPI) approach is also provided in the study.

The microenvironment of a desert hackberry plant (Celtis pallida).

Sammis, Theodore W. (The University of Arizona., 1974)

Evapotranspiration rates of plots with vegetative cover and evaporation rates from bare soil differed during the active growing season of desert hackberry (Celtis pallida) plants but total water losses from both plots for the year were the same. Thermally induced vapor flux appeared to contribute insignificantly to moisture movement under the desert hackberry plant. The difference in measured available soil moisture was independent of location from the plant center during the growing season. During the winter months, when the plants were semidormant, soil moisture measurements had more variability and measurement locations appeared to be important due to differential rainfall input. The determined soil moisture release curve and soil water conductivity values (using an in situ technique) appeared to be representative of the conditions at the study site. A model using soil and plant parameters predicted evapotranspiration rates during the active growing season of the plants when water was not a limiting factor. Calculated results using the model were unreliable when plants were under stress -- very low soil water content. Monitoring of climatic parameters delineated only major differences in surface albedo and net radiation between plant cover and bare ground. Potential evapotranspiration estimations were high but within acceptable bounds for desert conditions. Plant diffusion resistance for the desert hackberry plant, determined from a climatological model and measured soil moisture changes, appeared to increase linearly with decreasing soil moisture until it reached a critical value, below which it rose sharply.

Analysis of factors affecting water level recovery data

Hargis, David Robert. (The University of Arizona., 1979)

Water level recovery data collected in wells following controlled pumping tests are affected by both borehole and formation factors. The borehole factors comprise those effects attributed to the presence of the wellbore, such as step-increases in pumping rate, wellbore storage, well efficiency, and skin effects. The formation factors comprise those effects associated with the geologic environment in which an aquifer system occurs, such as variation of the coefficient of storage, and aquifer barrier boundaries. The recovery data should plot as a straight line on a semilogarithmic plot. Step-increases in the discharge rate during the pumping period cause the water level recovery plot to be concave downward. The curvature of the recovery data plot can be eliminated by applying a correction proposed by Harrill in 1970. However, the effect of step-increases in pumping rate on the recovery data is minimal so long as the duration of the pumping steps is less than about one-third of the total duration of pumping. The well efficiency and skin effects cause an additional component of drawdown in a pumped well, which is manifested as an initially rapid recovery rate after pumping stops. The effects of skin and well efficiency are usually dissipated within a few minutes after pumping stops. Wellbore storage effects can be critical in large diameter wells (wellbore radius greater than 0.5 feet) that penetrate aquifers with transmissivities less than about 2,700 feet squared per day. The time required to dissipate wellbore storage effects in the water level recovery data is inversely proportional to the aquifer transmissivity, and directly proportional to the borehole size. Variation of the coefficient of storage during the recovery period results in a semi-logarithmic recovery plot that is concave downward. The curvature of the recovery plot increases as the variation of the coefficient of storage increases. Variation in the coefficient of storage of one order of magnitude during the recovery period introduces an error of more than fifty percent in the transmissivity calculation at late recovery times. The recovery plot of data collected in a well influenced by a barrier boundary defines two straight line segments. The early-time straight line segment has a slope one-half that of the late-time straight line segment. Analysis of the early-time straight line yields the true aquifer transmissivity. Analysis and interpretation of water level recovery data collected in 59 wells following controlled pumping tests in aquifers of various rock types indicate that, in general, the shape of the recovery plot can be used to diagnose the presence of skin effects, low well efficiency, wellbore storage, and variation of the coefficient of storage. Analysis of data from seventeen wells in alluvial aquifers and thirteen wells in sandstone aquifers indicates that the concave downward recovery plot is the most common type of response curve. This shape of recovery curve indicates that the coefficient of storage is commonly smaller during the recovery period than during the drawdown period. Recovery data collected in twenty wells in fractured hard-rock aquifers indicate that the characteristic shape of the recovery plot predicted by Warren and Root in 1963 is generally diagnostic of flow in non-homogeneous, anisotropic, fractured aquifers. When the fracturing approaches being homogeneous and isotropic, the recovery plot can resemble data collected in non-fractured rocks. Recovery data from nine wells in composite limestone-sandstone aquifers indicate that the recovery plot is sometimes similar to the concave downward shape exhibited in sandstone and alluvial aquifers, and sometimes is similar to the shape predicted by Warren and Root for fractured rocks.

Innovative tracers for subsurface characterization

Nelson, Nicole Terese (The University of Arizona., 1999)

Proper site characterization is a critical component in making risk-based decisions and in selecting an appropriate action for a site, whether it is active remediation, containment or natural attenuation. The overall purpose of this work is to investigate innovative techniques for characterizing the factors controlling the transport and fate of organic chemicals at contaminated sites. It is expected that results from this work will lead to improved and more cost-effective methods for characterizing contamination at hazardous waste sites. The information gained from using these methods may lead to a better understanding of factors controlling contaminant transport at sites and therefore more informed risk-based decision making and selection of remediation strategies. The results indicate that (1) the presence of porous media heterogeneity and distinct zones of dense nonaqueous liquid (DNAPL) saturation lead to reduced performance (reduced accuracy) of the partitioning tracer test for measuring DNAPL saturation in saturated subsurface systems, (2) gas-phase tracer tests have the potential to accurately measure water contents for a system with uniform water content and homogeneous porous media, (3) the diffusivity-tracer test method can be used to determine whether diffusion-mediated processes are significant at a particular site, and (4) for a 2-dimensional flow cell flushing experiment the magnitude of trichloroethene concentration and the shape of the trichloroethene elution curves varied as a function of location and sampling type and that the less than solubility concentrations observed at almost all ports were caused by the nonuniform NAPL distribution and porous media heterogeneity, rather than by rate-limited interphase mass transfer at the pore-scale.

Artificial neural networks and conditional stochastic simulations for characterization of aquifer heterogeneity

Balkhair, Khaled Saeed (The University of Arizona., 1999)

Although it is one of the most difficult tasks in hydrology, delineation of aquifer heterogeneity is essential for accurate simulation of groundwater flow and transport. There are various approaches used to delineate aquifer heterogeneity from a limited data set, and each has its own difficulties and drawbacks. The inverse problem is usually used for estimating different hydraulic properties (e.g. transmissivity) from scattered measurements of these properties, as well as hydraulic head. Difficulties associated with this approach are issues of indentifiability, uniqueness, and stability. The Iterative Conditional Simulation (ICS) approach uses kriging (or cokriging), to provide estimates of the property at unsampled locations while retaining the measured values at the sampled locations. Although the relation between transmissivity (T) and head (h) in the governing flow equation is nonlinear, the cross covariance function and the covariance of h are derived from a first-order-linearized version of the equation. Even if the log transformation of T is adopted, the nonlinear nature between f (mean removed Ln[T]) and h still remains. The linearized relations then, based on small perturbation theory, are valid only if the unconditional variance of f is less than 1.0. Inconsistent transmissivity and head fields may occur as a result of using a linear relation between T and h. In this dissertation, Artificial Neural Networks (ANN) is investigated as a means for delineating aquifer heterogeneity. Unlike ICS, this new computational tool does not rely on a prescribed relation, but seeks its own. Neural Networks are able to learn arbitrary non-linear input-output mapping directly from training data and have the very advantageous property of generalization. For this study, a random field generator was used to generate transmissivity fields from known geostatistical parameters. The corresponding head fields were obtained using the governing flow equation. Both T and h at sampled locations were used as input vectors for two different back-propagation neural networks designed for this research. The corresponding values of transmissivities at unsampled location (unknown), constituting the output vector, were estimated by the neural networks. Results from the ANN were compared to those obtained from the (ICS) approach for different degrees of heterogeneity. The degree of heterogeneity was quantified using the variance of the transmissivity field, where values of 1.0, 2.0, and 5.0 were used. It was found that ANN overcomes the limitations of ICS at high variances. Thus, ANN was better able to accurately map the highly heterogeneous fields using limited sample points.

Integrated hydrogeochemical modeling of an alpine watershed: Sierra Nevada, California.

Wolford, Ross Alan. (The University of Arizona., 1992)

Seasonally snow covered alpine areas play a larger role in the hydrologic cycle than their area would indicate. Their ecosystems may be sensitive indicators of climatic and atmospheric change. Assessing the hydrologic and bio-geochemical responses of these areas to changes in inputs of water, chemicals and energy should be based on a detailed understanding of watershed processes. This dissertation discusses the development and testing of a model capable of predicting watershed hydrologic and hydrochemical responses to these changes. The model computes integrated water and chemical balances for watersheds with unlimited numbers of terrestrial, stream, and lake subunits, each of which may have a unique, variable snow-covered area. Model capabilities include (1) tracking of chemical inputs from precipitation, dry deposition, snowmelt, mineral weathering, baseflow or flows from areas external to the modeled watershed, and user-defined sources and sinks, (2) tracking water and chemical movements in the canopy, snowpack, soil litter, multiple soil layers, streamflow, between terrestrial subunits (surface and subsurface movement), and within lakes (2 layers), (3) chemical speciation, including free and total soluble species, precipitates, exchange complexes, and acid-neutralizing capacity, (4) nitrogen reactions, (5) a snowmelt optimization procedure capable of exactly matching observed watershed outflows, and (6) modeling riparian areas. Two years of data were available for fitting and comparing observed and modeled output. To the extent possible, model parameters are set based on physical or chemical measurements, leaving only a few fitted parameters. Thc effects of snowmelt rate, rate of chemical elution from the snowpack, nitrogen reactions, mineral weathering, and flow routing on modeled outputs are examined.

Geometric simplification of a distributed rainfall-runoff model over a range of basin scales.

Goodrich, David Charles. (The University of Arizona., 1990)

Distributed rainfall-runoff models are gaining widespread acceptance; yet, a fundamental issue that must be addressed by all users of these models is definition of an acceptable level of watershed discretization (geometric model complexity). The level of geometric model complexity is a function of basin and climatic scales as well as the availability of input and verification data. Equilibrium discharge storage is employed to develop a quantitative methodology to define a level of geometric model complexity commensurate with a specified level of model performance. Equilibrium storage ratios are used to define the transition from overland to channel-dominated flow response. The methodology is tested on four subcatchments in the USDA-ARS Walnut Gulch Experimental Watershed in southeastern Arizona. The catchments cover a range of basins scales of over three orders of magnitude. This enabled a unique assessment of watershed response behavior as a function of basin scale. High quality, distributed, rainfall-runoff data were used to verify the model (KINEROSR). Excellent calibration and verification results provided confidence in subsequent model interpretations regarding watershed response behavior. An average elementary channel support area of roughly 15% of the total basin area is shown to provide a watershed discretization level that maintains model performance for basins ranging in size from 1.5 to 631 hectares. Detailed examination of infiltration, including the role and impacts of incorporating small-scale infiltration variability in a distribution sense, into KINEROSR, over a range of soils and climatic scales was also addressed. The impacts of infiltration and channel losses on runoff response increase with increasing watershed scale as the relative influence of storms is diminished in a semi-arid environment such as Walnut Gulch. In this semi-arid environment, characterized by ephemeral streams, watershed runoff response does not become more linear with increasing watershed scale but appears to become more nonlinear.

Contaminant transport coupled with nonlinear biodegradation and nonlinear sorption

Xie, (Lily) Hong, 1965- (The University of Arizona., 1996)

A coupled process one-dimensional model with two-region transport, two-domain nonlinear sorption, and nonlinear biodegradation is formulated in this research. A numerical code is developed for this complex system with two sets of initial/boundary conditions. The second order upwind method is used to solve PDEs of the system, and the Adam-Bashforth three step method is used to solve ODEs of the system. By nondimensionalizing the governing equations for transport and nonlinear biodegradation, we show that biodegradation is controlled by three characteristic combined factors: the effective maximum specific growth rate, the relative half-saturation constant, and the relative substrate-utilization coefficient. A diagram with type curves was constructed based on the three characteristic factors to show the conditions under which complete and incomplete biodegradation is observed, and the conditions for which the linear, first-order approximation is valid for representing biodegradation. Analytical and numerical approaches were used to study the effect of substrate boundary concentration on biodegradation in a coupled-process system. For a system with fixed biotic and abiotic properties, substrate input concentration could be positively or negatively correlated to the magnitude of substrate degradation, depending on the time scale of the process. The relative scale of substrate concentration and its half-saturation constant is very important for the success and efficiency of bioremediation. It is found that bioremediation can be more efficient for higher concentration contaminant under certain conditions. The impact of biodegradation on solute transport with linear or nonlinear, equilibrium sorption was studied by using moments analysis. Computation results show that linear biodegradation has no impact on spatial moments of transport with linear instantaneous sorption. Conversely, it has an impact when sorption is nonlinear, since nonlinear sorption is enhanced by biodegradation. Nonlinear biodegradation causes preferential non-uniform substrate degradation and, therefore, affects spatial moments of transport with linear or nonlinear sorption. The oxygen constraint decreases the degree of nonlinear biodegradation and increases the degree of preferential degradation, thus it also impacts spatial moments of transport with linear or nonlinear sorption.

New taxonomy of clastic sedimentary structures and a procedure for its use in the simulation of groundwater flow

Mock, Peter Allen. (The University of Arizona., 1997)

This work describes a new taxonomy for elastic, sedimentary porous media. The taxonomy is synthesized for the investigation and characterization of ground-water flow from accumulating developments in the genetic analysis of elastic, sedimentary depositional structures. Genetic analysis recognizes spatial associations of elastic, sedimentary structures imposed during genesis. The taxonomy is a nested hierarchy of discrete elastic, sedimentary structures distinguished by the bounding surfaces created during their emplacement and rearrangement. The investigation and characterization of a specific ground-water flow system in elastic, sedimentary porous media can be improved by imposing a structural context on lithologie observations, geophysical measurements, head measurements, and hydraulic conductivity estimates. Globally-valid and transferable descriptions of structures in the taxonomy from modern exposures, outcrops, and densely sampled subsurface systems are modified to fit site-specific geologic observations and measurements. A specific procedure is developed for applying the taxonomy in the investigation and analysis of ground-water flow. The procedure quantitatively measures the hydraulic validity of alternative geologic interpretations of site-specific data under the taxonomy. The application of the taxonomy and procedure to a typical set of data types, densities, and quality is illustrated with data from a site of ground-water contamination investigation.

On the theory and modeling of dynamic programming with applications in reservoir operation

Sniedovich, Moshe (The University of Arizona., 1976)

This dissertation contains a discussion concerning the validity of the principle of optimality and the dynamic programming algorithm in the context of discrete time and state multistage decision processes. The multistage decision model developed for the purpose of the investigation is of a general structure, especially as far as the reward function is concerned. The validity of the dynamic programming algorithm as a solution method is investigated and results are obtained for a rather wide class of decision processes. The intimate relationship between the principle and the algorithm is investigated and certain important conclusions are derived. In addition to the theoretical considerations involved in the implementation of the dynamic programming algorithm, some modeling and computational aspects are also investigated. It is demonstrated that the multistage decision model and the dynamic programming algorithm as defined in this study provide a solid framework for handling a wide class of multistage decision processes. The flexibility of the dynamic programming algorithm as a solution procedure for nonroutine reservoir control problems is demonstrated by two examples, one of which is a reliability problem. To the best of the author's knowledge, many of the theoretical derivations presented in this study, especially those concerning the relation between the principle of optimality and the dynamic programming algorithm, are novel.

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