Sediment deposit ages inferred from radiocarbon dating of stream bank material were used to estimate residence times of valley-floor deposits in headwater valleys of the Oregon Coast Range, USA. Inherited ages of radiocarbon-dated material, i.e., time between carbon fixation in wood and its incorporation in a sediment deposit, can result in over-estimation of the ages of those deposits and, hence, the residence times of sediment within those units. Calibrated radiocarbon dates of 126 charcoal pieces sampled from Knowles Creek were used to estimate the distribution of inherited ages in fourteen depositional units representing three deposit types: fluvial fines, fluvial gravels, and debris flows. Within a depositional unit, the inherited age distribution of a piece of charcoal was estimated by convolving its calibrated age distribution with that of the piece of charcoal with the smallest weighted-mean calibrated age (i.e., an approximation of a unit's date of deposition) within that unit. All inherited age distributions for a particular deposit type were then added and normalized to provide a probability distribution of inherited ages for that deposit type. Probability distributions of inherited ages average 688, 1506, and 666 yr for fluvial fines, fluvial gravels, and debris flow units, respectively. Curves were fit to inherited age distributions for each deposit type. These curve fits were then convolved with deposit age distributions (i.e., equal to calibrated age distributions of woody material sampled from stream banks) of samples from Bear Creek (Lancaster and Casebeer, 2007) to correct these deposit ages for inherited age. This convolution gives a corrected deposit age. In cases in which means of corrected deposit age distributions for an upper unit were older than those of a lower unit within a stratigraphic column, the upper sample’s corrected deposit age distribution was set to that of the youngest lower in the stratigraphic section. Convolution shifted individual deposit age distributions towards zero and increased their standard deviation by an average of 365%. However, convolution decreased the standard deviations of normalized probability distribution functions of deposit ages inferred from many samples from 1340 to 1197 yr, and from 471 to 416 yr for lower and upper reaches, respectively, of the Bear Creek valley in the Oregon Coast Range. Convolution decreased estimates of mean deposit ages from 1296 to 1051 yr, and from 308 to 245 yr for lower and upper reaches, respectively, of the Bear Creek. Estimates of percentages of basin denudation passing through each reach's deposit ("trapping efficiency") increased from 11.6% to 14.4%, and from 25.4% to 31.9% for lower and upper Bear Creek, respectively. However, basic shapes of residence time distributions and, thus, inferences regarding removal of sediment from the reaches did not change after deposit dates were corrected. Sediment residence times in the lower Bear Creek valley are exponentially distributed, which implies that all sediment has a uniform probability of evacuation from deposits, whereas the power-law-distributed residence times in upper Bear imply preferential evacuation of younger deposits and preservation of older deposits. Much of the sediment transported onto valley floors via debris flows is deposited, and then is evacuated over longer times. Volumes and residence times of stored sediment in these deposits at the transition from debris flow to fluvial evacuation, and their associated width of valley floors, vary throughout a network. Export volumes and frequencies from tributaries are controls on deposit volumes and may control valley widening of mainstem valley floors. In addition, closely spaced tributaries may exert composite effects on valley floor landforms. It is hypothesized that the volumes of sediment stored at confluences increases with contributing watershed area of tributaries to the point where tributary slopes are low enough to cause most debris flows to be deposited within tributary valleys instead of in the mainstem valley. In four ~1 km reaches with contributing watershed areas of 0.3 to 5.0 km², field surveys provided measures of width of valley floors and volume of deposits, and radiocarbon dating of charcoal provided residence times of sediment in these deposits. Mean residence times of reaches vary between 1.1 and 2.5 kyr. Exponential distributions fit to residence times within two of the reaches imply evacuation of sediment independent of deposit ages. Power-law fits to residence times of the other two reaches imply age-dependent evacuation of deposits. Distribution shapes of residence times, and their means, do not vary systematically with contributing watershed area of mainstems. Mean width of mainstem valley floors increases with contributing watershed areas of both mainstems and their respective tributaries. Volumes of sediment stored on the valley floor increase with contributing areas of mainstems, and these volumes at tributary junctions peaked at tributary contributing areas of ~0.1 km². Percentage of basin denudation entering storage decreases with contributing area of mainstem. This decrease may be due to increasing percentages of sediment supply via fluvial transport for larger watersheds, and much, if not most, of this supply routes through the system quickly. / Graduation date: 2012

Topographic depressions are naturally occurring low land areas surrounded by areas of high elevations, also known as “pits” or “sinks”, on terrain surfaces. Traditional watershed modeling often neglects the potential effects of depressions by implementing removal (mostly filling) procedures on the digital elevation model (DEM) prior to the simulation of physical processes. The assumption is that all the depressions are either spurious in the DEM or of negligible importance for modeling results. However, studies suggested that naturally occurring depressions can change runoff response and connectivity in a watershed based on storage conditions and their spatial arrangement, e.g., shift active contributing areas and soil moisture distributions, and timing and magnitude of flow discharge at the watershed outlet. In addition, recent advances in remote sensing techniques, such as LiDAR, allow us to examine this modeling assumption because naturally occurring depressions can be represented using high-resolution DEM. This dissertation provides insights on the effects of depressions on overland flow processes at multiple spatial scales, from internal depression areas to the watershed scale, based on hydrologic connectivity metrics. Connectivity describes flow pathway connectedness and is assessed using geostatistical measures of heterogeneity in overland flow patterns, i.e., connectivity function and integral connectivity scale lengths. A new algorithm is introduced here to upscale connectivity metrics to large gridded patterns (i.e., with > 1,000,000 cells) using GPU-accelerated computing. This new algorithm is sensitive to changes of connectivity directions and magnitudes in spatial patterns and is robust for large DEM grids with depressions. Implementation of the connectivity metrics to overland flow patterns generated from original and depression filled DEMs for a study watershed indicates that depressions typically decrease overland flow connectivity. A series of macro connectivity stages based on spatial distances are identified, which represent changes in the interaction mechanisms between overland flow and depressions, i.e., the relative dominance of fill and spill, and the relative speed of fill and formation of connected pathways. In addition, to study the role of spatial resolutions on such interaction mechanisms at watershed scale, two revised functional connectivity metrics are also introduced, based on depressions that are hydraulically connected to the watershed outlet and runoff response to rainfall. These two functional connectivity metrics are sensitive to connectivity changes in overland flow patterns because of depression removal (filling) for DEMs at different grid resolutions. Results show that these two metrics indicate the spatial and statistical characteristics of depressions and their implications on overland flow connectivity, and may also relate to storage and infiltration conditions. In addition, grid resolutions have a more significant impact on overland flow connectivity than depression removal (filling).

Declines in glacier area and volume are widespread. These changes will have important hydrologic consequences since glaciers store tremendous amounts of fresh water and buffer seasonally low flows in many densely populated regions. In this thesis I focus on a region that is hydrologically vulnerable to glacier change, namely the Cordillera Blanca, Peru. I present three manuscripts that focus on measuring glacier area change, modeling the effect of this area change on the hydrology of one watershed, and isotopic sampling to elucidate hydrologic processes in this watershed and the entire Cordillera Blanca. In the first manuscript, I describe a methodology for mapping glaciers using satellite imagery. Satellite data, in conjunction with automated glacier mapping methods, are being used more frequently to map changes in glacier size. In contrast to the majority of studies using automated methods, I correct satellite images for atmospheric effects. Mapping glaciers with atmospherically-corrected satellite images resulted in an approximately 5% increase in glacier area, relative to glaciers mapped with non-atmospherically-corrected images. I also applied a consistent threshold that was validated using high-resolution satellite imagery. This helps to reduce error associated with change analysis. For the entire Cordillera Blanca, I calculated a 25% decrease in glacier area from 1987 to 2010. The rate of glacier area loss has increased significantly based on the most recent estimates. In the second manuscript, I use a physically-based, hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM) with a newly-coupled dynamic glacier model to simulate stream discharge and glacier change in the Llanganuco watershed of the Cordillera Blanca. I also examined statistical trends associated with historical records of temperature, precipitation, and discharge. I observed significant positive trends in annual temperature, but no trends in precipitation or discharge despite a 25% reduction in glacier area in this watershed over the same time. The model setup process and the results of sensitivity analyses are described. Of the input parameters I examined, I found that the model was particularly sensitive to changes in albedo and precipitation. Based on established efficiency criteria, the newly-coupled model did a decent job of simulating historical stream discharge and glacier area during 10 year calibration and validation periods. However, due to the lack of additional validation data and an inability to quantify uncertainty associated with model output, the model is not yet ready to be used for predicting future discharge based on different climate projections. In the third manuscript I describe the knowledge gained about hydrologic processes from isotopic sampling in the Llanganuco watershed, as well as other watersheds of the Cordillera Blanca. Thirty water samples from Llanganuco were collected in July 2011 and measured for stable isotopes of water, δ¹⁸O and δ²H. I first calculated the isotopic lapse rate, or the relationship between isotopic values and elevation. Lapse rates from this watershed are slightly more positive than global averages. This observation is best explained by the influence of glaciers. I also calculated the strength of the relationship between isotopic values and percent glacier cover. For Llanganuco, glacier cover is a better predictor of isotopic value than elevation. Based on examination of the same relationships at larger scales in the Cordillera Blanca, this relationship appears to be persistent at a regional scale. Finally, I used a simple two-component mixing model to estimate the relative contributions of glacier meltwater and groundwater in the Llanganuco watershed. Glacier meltwater made up approximately three-fourths of surface water that exited the watershed during this two week period in July, 2011. The importance of glacier meltwater is clearly demonstrated using stable isotopes, but further, more detailed monthly sampling is necessary to accurately determine annual and dry season streamflow contributions from glacier meltwater and groundwater. / Graduation date: 2013

The plantation forestry is economically a very important industry in South Africa because it promotes the upliftment of many rural South African communities. However, afforestation has significant impacts on water use and biodiversity in a catchment. Thus, understanding the effects of afforestation on water resources at the catchment level is fundamental for optimal water resource allocation, long-term sustainable use, development and conservation. Much of the Limpopo Province is climatically and physiographically suitable for plantation forestry but it only contains approximately 4.7 % of the total existing plantation area in South Africa. For example, the size of the Letaba Catchment of the Limpopo Province is 13 669 km² but only approximately 484 km² of it is currently afforested. This study aims to identify potential areas for further afforestation in the Letaba Catchment using the Water Resources Modelling Platform (WReMP) model to determine if afforestation can be expanded here to promote development in South Africa‟s poorest Province. / Geography / M. Sc. (Geography)

This study investigates the hydrologic effects of urbanization in two Portland, Oregon streams through a comparison of three hydrologic metrics. Hydrologic metrics used in this study are the mean annual runoff ratio (Qa), mean seasonal runoff ratio (Qw and Qd), and the fraction of time that streamflow exceeds the mean streamflow during the year (TQmean). Additionally, the relative change in streamflow in response to storm events was examined for two watersheds. For this investigation urban development is represented by two urbanization metrics: percent impervious and road density. Descriptive and inferential statistics were used to evaluate the relationship between the hydrologic metrics and the amount of urban development in each watershed. The effect of watershed size was also investigated using nested watersheds, with watershed size ranging from 6 km2 to 138km 2. The results indicate that annual and seasonal runoff ratios have difficulty capturing the dynamic hydrologic behavior in urban watersheds. TQmean was useful at capturing the flashy behavior of the Upper Fanno watershed, however it did not perform as well in Kelley watershed possibly due to the influence of impermeable soils and steep slopes. Unexpected values for hydrologic metrics in Lower Johnson, Sycamore and Kelley watersheds could be the result water collection systems that appear to route surface water outside of their watersheds as well as permeable soils. Storm event analysis was effective at characterizing the behavior for the selected watersheds, indicating that shorter time scales may best capture the dynamic behavior of urban watersheds.

This dissertation integrates a process-based hydrological investigation with an ongoing paired-catchment study to better understand how forest harvest impacts catchment function at multiple scales. We do this by addressing fundamental questions related to the stocks, flows and transit times of water. Isotope tracers are used within a top-down catchment intercomparison framework to investigate the role of geology in controlling streamwater mean transit time and their scaling relationships with the surrounding landscape. We found that streams draining catchments with permeable bedrock geology at the Drift Creek watershed in the Oregon Coast Range had longer mean transit times than catchments with poorly permeable bedrock at the HJ Andrews Experimental Forest in the Oregon Cascades. We also found that differences in permeability contrasts within the subsurface controlled whether mean transit time scaled with indices of catchment topography (for the poorly permeable bedrock) or with catchment area (for the permeable bedrock). We then investigated the process-reasons for the observed differences in mean transit time ranges and scaling behavior using a detailed, bottom-up approach to characterize subsurface water stores and fluxes. We found that the mean transit times in catchments underlain by permeable bedrock were influenced by multiple subsurface storage pools with different groundwater ages, whereas storage in the poorly permeable catchments was limited to the soil profile and that resulted in quick routing of excess water to the stream at the soil bedrock interface, leading to mean transit times that were closely related to flowpath lengths and gradients. Finally, we examined how and where forest trees interacted with subsurface storage during the growing season using a forest manipulation experiment, where we tested the null hypothesis that near-stream trees alone influenced daily fluctuations in streamflow. We felled trees within this zone for two 2.5 ha basins and combined this with isotopic tracing of tree xylem water to test if water sources utilized by trees actively contributed to summer streamflow. We rejected our null hypotheses and found that diel fluctuations in streamflow were not generated exclusively in the near-stream zone. We were unable to link, isotopically, the water sources trees were utilizing to water that was contributing to streamflow. Our results provide new process-insights to how water is stored, extracted, and discharged from our forested catchments in Western Oregon that will help better explain how forest removal influences streamflow across multiple scales and geological conditions. / Graduation date: 2012

The Walla Walla basin lies in an arid region of Eastern Washington and Oregon. A large portion of the area is devoted to agricultural production, relying on irrigation water diverted from the Walla Walla River and underlying aquifers occurring within Quaternary and Mio-pliocene era gravel deposits, as well as a supplemental source from the Columbia River Basalt formation. Heavy water demand over summer months has resulted in a fully allocated surface water supply and significant drawdown in groundwater levels. The Walla Walla River also hosts two salmonid species listed as threatened under the endangered species act and entitled to federal protection. Specific questions have emerged regarding regional water supply as stakeholders work towards management strategies that meet water user demands, well also addressing concerns such as groundwater depletion and fish habitat. Currently, there are proposals aimed at increasing water use efficiency such as the lining of permeable canal beds and the expansion of a shallow aquifer recharge program. Effective implementation of such strategies, in part, relies on understanding the interactions between surface water and groundwater within this region. This project used the distributed hydrologic model, Integrated Water Flow Model (IWFM), for simulating surface and subsurface flows over a portion of the Walla Walla River basin spanning from Milton Freewater, Oregon to west of Touchet, Washington. This application of IWFM uses a grid with an average spacing of 100 x 100 meters over the 230 square kilometer model area. The model was developed and calibrated using data from 2007 through 2009, with 2010 data to be used as a data set for validation. Data collection has been a collaborative effort between a research team from Oregon State University and the Walla Walla Basin Watershed Council (WWBWC). This thesis provides explanation and documentation of model development. This includes details of data collection and processing for groundwater and surface water conditions, estimation of initial and boundary conditions, parameter calibration, model validation, and error analysis. Data sources include federal and state agencies, a gauge network managed by the WWBWC, and geologic research primarily performed by Kevin Lindsey of GSI Water Solutions with support of the WWBWC. Parameters have been independently determined from field measurements whenever possible. Otherwise they were estimated using established methods of hydrologic analysis, values drawn from previous regional studies, or the process of model calibration. Outputs include detailed hydrological budgets and hydrographs for groundwater and surface water gauges. The calibrated model has an overall correlation coefficient of 0.59 for groundwater and 0.63 for surface water. The standard deviation for groundwater is 3.2 meters at 62 well locations and surface water has a mean relative error of 22.3 percent at 34 gauges. This model intended as a tool for formulating water budgets for the basin under present conditions and making predictions of systemic responses to hypothetical water management scenarios. Scenarios of increased inputs into the Locher Road aquifer recharge site and conversion of irrigation district canals into pipelines are presented. / Graduation date: 2012

This research project focuses on the Walla Walla River Basin located on the east side of the states of Oregon and Washington, USA. With the support and collaboration of the Walla Walla Basin Watershed Council, this work embraces four research topics. The first topic includes the feasibility study of artificial aquifer recharge in the Walla Walla Basin. Through development and application of a regional hydrological model, a methodology for evaluating locations of artificial aquifer recharge is presented with a test case. The second research topic evaluates the recharge rates observed from pilot test studies of artificial aquifer recharge. Scale dependence of recharge rates should be considered when excessive induced groundwater mounding forms beneath the infiltrating basins. The third topic utilizes groundwater tracers and simulation models to evaluate the hydraulic connection of springs to infiltrating basins of artificial aquifer recharge. Finally, the fourth topic as a proof of a technique, utilizes distributed temperature sensing technology with a pair of black and white coated fiber optic cables to estimate the effective exposure to solar radiation over the Walla Walla River. / Graduation date: 2013

No description available.

Indiana University-Purdue University Indianapolis (IUPUI) / Environmental planning is very cumbersome work for environmentalists, government agencies like USDA and NRCS, and farmers. There are a number of conflicts and issues involved in such a decision making process. This research is based on the work to provide a common platform for environmental planning called WRESTORE (Watershed Restoration using Spatio-Temporal Optimization of Resources). We have designed a system that can be used to provide the best management practices for environmental planning. A distributed system was designed to combine high performance computing power of clusters/supercomputers in running various environmental model simulations. The system is designed to be a multi-user system just like a multi-user operating system. A number of stakeholders can log-on and run environmental model simulations simultaneously, seamlessly collaborate, and make collective judgments by visualizing their landscapes. In the research, we identified challenges in running such a system and proposed various solutions. One challenge was the lack of fast optimization algorithm. In our research, several algorithms are utilized such as Genetic Algorithm (GA) and Learning Automaton (LA). However, the criticism is that LA has a slow rate of convergence and that both LA and GA have the problem of getting stuck in local optima. We tried to solve the multi-objective problems using LA in batch mode to make the learning faster and accurate. The problems where the evaluation of the fitness functions for optimization is a bottleneck, like running environmental model simulation, evaluation of a number of such models in parallel can give considerable speed-up. In the multi-objective LA, different weight pair solutions were evaluated independently. We created their parallel versions to make them practically faster in computation. Additionally, we extended the parallelism concept with the batch mode learning. Another challenge we faced was in User Modeling. There are a number of User Modeling techniques available. Selection of the best user modeling technique is a hard problem. In this research, we modeled user's preferences and search criteria using an ANN (Artificial Neural Network). Training an ANN with limited data is not always feasible. There are many situations where a simple modeling technique works better if the learning data set is small. We formulated ways to fine tune the ANN in case of limited data and also introduced the concept of Deep Learning in User Modeling for environmental planning system.