H33D-0489 1340h
Better Insight Into Water Resources Management With Integrated Hydrodynamic And Water Quality Models
Models have long been used in water resources management to guide decision making and improve understanding of the system. Numerous models of different scales -spatial and temporal - are available. Yet, very few models manage to bridge simulations of hydrological and water quality parameters from both upland watershed and riverine system. Most water quality models, such as QUAL2E and EPD-RIV1 concentrate on the riverine system while CE-QUAL-W2 and WASP models focus on larger waterbodies, such as lakes and reservoirs. On the other hand, the original SWAT model, HSPF and other upland watershed hydrological models simulate agricultural (diffuse) pollution sources with limited number of processes incorporated to handle point source pollutions that emanate from industrial sectors. Such limitations, which are common in most hydrodynamic and water quality models undermine better understanding that otherwise could be uncovered by employing integrated hydrological and water quality models for both upland watershed and riverine system. The SWAT model is a well documented and verified hydrological and water quality model that has been developed to simulate the effects of various management scenarios on the health of the environment in terms of water quantity and quality. Recently, the SWAT model has been extended to include the simulation of hydrodynamic and water quality parameters in the river system. The extended SWAT model (ESWAT) has been further extended to run using diurnally varying (hourly) weather data and produce outputs at hourly timescales. This and other improvements in the ESWAT model have been documented in the current work. Besides, the results from two case studies in Texas will be reported.
H33D-0490 1340h
Using a Watershed-Based Effluent Trading Approach to Manage Coalbed Methane Produced Water in a Cost-Effective and Environmentally Sound Manner
Coalbed methane (CBM) is expected to supply much of the incremental U.S. natural gas demand in the coming decades. Extraction of methane from coal seams necessitates reduction of the hydrostatic pressure in the coalbed by removal of water, called produced water. The large volume of produced water not only raises concerns about its impact on surface water quality but also negatively affects producers' profitability because of costs associated with handling the water in a manner consistent with environmental regulatory requirements imposed by the Clean Water Act. Alternatively, watershed-based effluent trading could provide a market mechanism for managing CBM produced water and more quickly improving the overall water quality in a watershed at a lower cost. However, the complexity of appraising the potential trading options in accordance with the prerequisites of implementation feasibility and the effects on environment, economy, and equity dictates an easy-to-be-implemented tool. This paper presents a decision support tool that can be used by both water resources managers and other stakeholders to evaluate various trading options. The tool consists of a database on water quality and discharge baseline determined in terms of the U.S. Environmental Protection Agency's Total Maximum Daily Loads, algorithms to define trading types and trading and transferability rules, a SPARROW (SPAtially Referenced Regression On Watershed attributes) watershed model, a two-dimensional hydrodynamic water quality model, and a simplified economic model. These components are seamlessly integrated with ArcView GIS to facilitate use of this tool. In addition to the prototype developed for the Powder River Basin in Wyoming and Montana, this study formulates a general framework upon which similar tools can be created for other watersheds.
H33D-0491 1340h
Sensitivity of Alpine and Subalpine Lakes to Atmospheric Deposition in Grand Teton National Park and Yellowstone National Park, Wyoming
Acidification of high-elevation lakes in the Western United States is of concern because of the storage and release of pollutants in snowmelt runoff combined with steep topography, granitic bedrock, and limited soils and biota. Land use managers have limited resources for sampling and thus need direction on how best to design monitoring programs. We evaluated the sensitivity of 400 lakes in Grand Teton (GRTE) and Yellowstone (YELL) National Parks to acidification from atmospheric deposition of nitrogen and sulfur based on statistical relations between acid-neutralizing capacity (ANC) concentrations and basin characteristics to aid in the design of a long-term monitoring plan for Outstanding Natural Resource Waters. ANC concentrations that were measured at 52 lakes in GRTE and 23 lakes in YELL during synoptic surveys were used to calibrate the statistical models. Basin-characteristic information was derived from Geographic Information System data sets. The explanatory variables that were considered included bedrock type, basin slope, basin aspect, basin elevation, lake area, basin area, inorganic nitrogen (N) deposition, sulfate deposition, hydrogen ion deposition, basin precipitation, soil type, and vegetation type. A logistic regression model was developed and applied to lake basins greater than 1 hectare (ha) in GRTE (n=106) and YELL (n=294). For GRTE, 36 percent of lakes had a greater than 60-percent probability of having ANC concentrations less than 100 microequivalents per liter, and 14 percent of lakes had a greater than 80-percent probability of having ANC concentrations less than 100 microequivalents per liter. The elevation of the lake outlet and the area of the basin with northeast aspects were determined to be statistically significant and were used as the explanatory variables in the multivariate logistic regression model. For YELL, results indicated that 13 percent of lakes had a greater than 60-percent probability of having ANC concentrations less than 100 microequivalents per liter, and 9 percent of lakes had a greater than 80-percent probability of having ANC concentrations less than 100 microequivalents per liter. Only the elevation of the lake outlet was determined to be statistically significant and was used as the explanatory variable in the multivariate logistic regression model. The lakes that exceeded 80-percent probability of having an ANC concentration less than 100 microequivalents per liter, and therefore had the greatest sensitivity to acidification from atmospheric deposition, are located at elevations greater than 2,810 meters (m) in GRTE, and greater than 2,655 m in YELL.
H33D-0492 1340h
Implications of Metal Load Randomness for Mine Water Pollution Abatement
Spatial and temporal variability of pollution transport from point and diffuse mine water sources (e.g. mine wastes, abandoned mine voids, contaminated groundwater) in catchments imply uncertainty in mine water pollution loads at important compliance boundaries (CB) and in cost-efficient abatement solutions for handling these loads. We use a stochastic description of total pollution loading from different possible mine water sources and quantify the effect of random load variance on minimum abatement costs for various targeted zinc load reductions to the Dal River, Sweden. Consideration of randomness in mine water pollution loads implies that, under certain conditions, compliance costs may be lower for higher than for lower load reduction targets, for the same load coefficient of variation and required probability to reach targeted load reductions. In addition, we illustrate that total costs in the cost-efficient abatement solutions converge with increasing zinc load reduction targets. Cost-efficient abatement solutions and costs are therefore more sensitive to uncertainty in pollution loading at lower than at higher compliance targets. For the example case of the Dal River Basin, we also show that the generally increasing abatement costs with increasing load variance and desired probability to reach targeted load reductions is only step-wise continuous, because cost-efficient abatement requires both continuous (e.g. constructed wetlands) and discrete (e.g. soil covers) abatement measures.
H33D-0493 1340h
An Example Uncertainty and Sensitivity Analysis at the Horonobe Site for Performance Assessment Calculations
Given pre-existing Groundwater Modeling System (GMS) models of the Horonobe Underground Research Laboratory (URL) at both the regional and site scales, this work performs an example uncertainty analysis for performance assessment (PA) applications. After a general overview of uncertainty and sensitivity analysis techniques, the existing GMS site-scale model is converted to a PA model of the steady-state conditions expected after URL closure. This is done to examine the impact of uncertainty in site-specific data in conjunction with conceptual model uncertainty regarding the location of the Oomagari Fault. In addition, a quantitative analysis of the ratio of dispersive to advective forces, the F-ratio, is performed for stochastic realizations of each conceptual model. All analyses indicate that accurate characterization of the Oomagari Fault with respect to both location and hydraulic conductivity is critical to PA calculations. This work defines and outlines typical uncertainty and sensitivity analysis procedures and demonstrates them with example PA calculations relevant to the Horonobe URL. {\st Sandia is a multiprogram laboratory operated by Sandia Corporation, a Lockheed Martin Company, for the United States Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.}
H33D-0494 1340h
Simulation of Conjunctive Agricultural Water Use with the new FARM package for MODFLOW-2000
A new Farm Package (FMP) was developed for the U.S. Geological Survey's groundwater modeling program, MODFLOW-2000 (MF2K), to estimate irrigation water allocations from conjunctively used surface and ground water. The FMP package dynamically integrates irrigation water demand, surface and ground-water supply, and return flow from excess irrigation. Routed surface-water delivery is optional, but can be simulated by coupling the FMP package with the Streamflow Routing Package (SFR1). Applying MF2K with the FMP and SFR1 packages facilitates estimating the allocation of surface and ground-water to farms for simulations of historical calibration or future projections directly within MF2K. These simulations also can be useful for assessing water rights issues and operational decisions as well as for non-drought versus drought supply and demand strategies. Estimates of historic pumpage may be particularly useful where well pumpage has not been recorded, such as agivulture in the southwestern United States. Estimates of future pumpage may be facilitated through the use of climate-model predictions to generate forecasts of potential water supply and demand for irrigation. Legal questions such as adjudications and appropriative water rights also could be assessed with simulations that use the FMP package in areas where there is a history of land use but no direct or complete record of water use. Operational decision in irrigation management depends on the ability to estimate conjunctively used surface-water and groundwater allocations just prior to or during the growing season. Conjunctive management of surface and ground-water is especially needed for periods when the proposed water supply is thought to be insufficient to meet the water demand. Simulations with the FMP package offer several choices of drought policy scenarios, such as acreage optimization that facilitates assessing an economically optimal conjunctive management. The FMP package maintains a dual mass balance of a farm budget and a groundwater budget. Flows between these two budgets are accommodated by head-dependent inflows and outflows, such as the actual evapotranspiration or transpiration from groundwater. All flows of interest, such as irrigation demand, surface-water and groundwater supply, and excess irrigation return flow may depend on these head-dependent inflows and outflows. Consumption of water by individual crops from each farm is simulated with steady-state transpiration, varying with changing water level that is approximated in FMP by an analytical solution. These solutions were validated by soil column simulations with the variably saturated flow model HYDRUS2D. When irrigation demand in the farm budget cannot be sufficiently supplied by surface or ground water, a distortion of mass balance occurs. The FMP package provides the user with several drought policy response options including deficit irrigation, water stacking, and acreage optimization. A hypothetical example with 55 scenarios that represent 5 drought policy scenarios each with 11 parameter-group scenarios demonstrates the consistency and utility of the FMP package under different irrigation conditions. The first real-world application of `MF2K with FMP and SFR1 packages' was a model for the southern Rincon Valley, along the Lower Rio Grande of New Mexico, within the Elephant Butte Irrigation District. Another larger scale application of MF2K with FMP is being implemented by updating the USGS model of the Central-Valley Regional Aquifer System Analysis in California.
H33D-0495 1340h
A Modelling Framework to Simulate the Dynamics of the Groundwater, Hydrologic, and Ecologic System in an Alpine floodplain
Most surface flows to the 20-km-long Maggia Valley in Southern Switzerland are impounded and the valley is being investigated to determine environmental flow requirements (EFRs). The long-term aim of the investigation is the development of a modelling framework that simulates the joint dynamics of the groundwater, hydrologic, and ecologic systems. A nested modelling framework is selected for the purpose. Large scale models are first developed to provide the boundary conditions for more detailed models of ecologically interesting reaches. The initial (large-scale) groundwater (GW) model is constructed using MODFLOW-2000 and its surface water package. The aquifer is modelled with two confined aquifers and the water table is considered iteratively. Parameters are defined to represent the areal recharge, the hydraulic conductivity of the aquifer (up to 5 classes), and the streambed hydraulic conductivity. Several conceptual models are evaluated by changing the number of hydraulic conductivity classes, and one most likely model is identified, which best fits observations with realistic parameter estimates. The model robustness is tested using sensitivity analysis and a cross-validation method, whereas its predictive capability is discussed with a completely independent set of data. The GW model is further evaluated by accounting for the boundary conditions as predicted by a raster-based, physically oriented and continuous in time rainfall-runoff (R-R) model. This model has proven to perform very well in the investigated area and computes among others the sub-surface flow over the entire flooplain boundary domain. It provides thus an observation-like input to the GW model, which can be thus investigated with respect to the changes in the performance when substituting such input for the homogeneous lateral flow obtained through calibration. The subsurface flows simulated for selected periods or events are used to assess the importance of realistic input to the groundwater model in terms of both initial and boundary conditions. Finally, the coupling of the R-R/GW model system with a 2D hydrodynamic model to complete the nested modelling framework required for detailed simulations of the floodplain dynamics is discussed.
H33D-0496 1340h
Fine-Resolution Hydrologic Modeling of Semiarid River Basins: Preliminary Results from the Upper Rio Grande
Water resources management and decision making in arid and semiarid regions require scientific knowledge and predictive capability of the physical processes occurring within hydrologic systems at scales sufficient to capture the variability inherent in the resource and its utilization. Our understanding of the interaction between water supply and demand is aided through numerical models that best represent our current knowledge of the hydrologic, ecological and meteorological processes in river basins. To this end, advances in distributed hydrologic modeling over large regional watersheds can aid in providing estimates of water availability and its susceptibility to climate variations, land-cover change and population growth. In this study, we utilize the TIN-based Real-time Integrated Basin Simulator (tRIBS) model to simulate continuous hydrological processes within subbasins of the Upper Rio Grande in north-central New Mexico. First, we introduce the distributed model by highlighting the following salient features: (1) coupled unsaturated and saturated zones through a dynamic water table, (2) coupled energy and hydrologic balance at the land surface and (3) topographically-driven soil moisture redistribution, radiation and evapotranspiration. Accurate terrain representation at fine-resolution is achieved through the use of a triangulated irregular network (TIN) terrain model. Second, we present semiarid case studies in model setup, parameterization and continuous operation for the Upper Rio Puerco and Jemez River. These river basins provide test cases for the calibration and validation of the tRIBS model through the use of in-situ measurement networks and long-term rainfall and stream gauging records. We will present the catchment hydrological response and its spatial organization by integrating geospatial data on topography, land-surface properties and precipitation obtained from geographic information systems, gauging networks and remote sensing. Although preliminary, our results indicate the potential for using fine-resolution hydrologic models over large semiarid regional watersheds such as the Upper Rio Grande.
H33D-0497 1340h
Hydrologic and Ecologic Responses to Diminished Spring Discharge; Surface-Water/Groundwater and Vegetation Modeling, Grand Canyon, Arizona
Numerous springs discharge from the regional Redwall-Muav aquifer of the Coconino Plateau along the South Rim of the Grand Canyon, AZ. Many of these springs provide base flow to Colorado River tributaries, and support stands of native riparian vegetation. Development of the Redwall-Muav aquifer as a water supply began in 1989, with potential abstraction rates up to ~1.1 x 106 m3/yr. Regional groundwater flow models predict that groundwater pumping has the potential to result in diminished discharges at the South Rim Springs, which may result in negative impacts to the associated riparian ecosystems. Management of this regional spring-aquifer system requires an interdisciplinary understanding of the dynamics between the operating hydrologic, ecologic and cultural processes. To aid in this effort, we calibrated a coupled numerical surface-water and groundwater flow model for the riparian aquifer associated with one of the smaller of the South Rim springs, Cottonwood Springs. The model simulated the seasonal variability of surface-water and groundwater flow in the aquifer as observed between March 2003 and January 2004 at a 1-m grid spacing. Surface-water flux and groundwater flux data were extracted from the model at various transects through the riparian area to highlight temporal and spatial variations in water availability to the associated riparian communities. During the winter, the total flux of water was relatively constant throughout the model area and was ~60 m3/d. During the peak of the growing season, the total flux of water in the upstream portion of the model area was ~60 m3/d and decreased progressively down to ~35 m3/d in the downstream portion of the model. The downstream decrease in water availability is manifested in downstream changes in woody riparian vegetation structure and composition. Changes in cottonwood stand and individual tree metrics were examined quantitatively in relation to this moisture availability gradient. An analysis of stream gauging data (1994-2003) from two South Rim springs showed statistically significant decreasing discharge trends over the period of record. These trends, coupled with ongoing groundwater pumping, climatic predictions of continuing drought, and the observed sensitivity of the riparian vegetation to variations in water availability suggests there is a potential for alteration to the riparian ecosystem over relatively short timescales.
H33D-0498 1340h
Restoring Consistency In Subjective Information For Groundwater Driven Health Risk Assessment
In an earlier work (Ozbek and Pinder, 2003), we constructed a fuzzy rule-based knowledge base that uses subjective expert opinion to calculate risk-based design constraints (i.e., dose and pattern of exposure) to sustain the groundwater-driven individual health risk at a desired level. Ideally, our system must be capable to produce for any individual a meaningful risk result or for any given risk a meaningful design constraint, in the sense that the result is neither the empty set nor the whole domain of the variable of interest. Otherwise we consider our system as inconsistent. We present a method based on fuzzy similarity relations to restore consistency in our implicative fuzzy rule based system used for the risk-based groundwater remediation design problem. Both a global and a local approach are considered. Even though straightforward and computationally less demanding, the global approach can affect pieces of knowledge negatively by inducing unwarranted imprecision into the knowledge base. On the other hand, the local approach, given a family of parameterized similarity relations, determines a parameter for each inference such that consistent results are computed which may not be feasible in real time applications of our knowledge base. Several scenarios are considered for comparing the two approaches that suggest that for specific applications one or several approaches ranging from a completely global to a completely local one will be more suitable than others while calculating the design constraints.
H33D-0499 1340h
Snow pack and stream flow simulation of an eastern slopes watershed using WATFLOOD, MTCLIM, and GLUE
The set up and parameterization of a hydrological model is described for a watershed extending from the continental divide along the Rocky Mountains into the grasslands of southern Alberta, Canada. The hydrological model WATFLOOD (a flood forecast model), based on the group response unit (GRU), was used for a 13-month stream flow simulation. Required monthly surfaces of snow water equivalent were derived by integrating spatial precipitation patterns, orographic effects and topography-induced microclimate. Spatial and temporal changes in radiation and temperature were modeled at a 100 m resolution to simulate the snowmelt and accumulation processes using MTCLIM (a mountain microclimate simulation model). The simulated surfaces of snow water equivalent enabled the optimization of WATFLOOD parameters using GLUE, a Monte Carlo simulation tool for estimating the predictive uncertainty of models. This was important, because the majority of stream flow in this region originates as snowmelt. The verification of the stream flow simulations indicates that WATFLOOD is applicable in mountainous watersheds.
H33D-0500 1340h
KNOWLEDGE DISCOVERY IN HYDROLOGIC DATA: A FRAMEWORK FOR SIMULATION AND PREDICTION
Uncertainty, non-stationarity, noise, and paucity of data all limit the prediction capabilities of hydrologic models. In this paper, we adopt a Bayesian predictive approach for forecasting that combines the features of excellent generalization properties and sparse representation. There are three novelties in the resulting framework: first, the uncertainty in model parameters is incorporated in the prediction; second, a multi-objective optimization algorithm is employed to account for the uncertainty in model structure (i.e., optimal model selection); and third, this framework allows detection of shifts in the sense that, as we observe the behavior of a process through time, our framework detects drift (e.g., changes in the hydrologic processes caused by climatic changes) and thence initiates adaptations in model structure in response to a recognized shift in the underlying processes. Finally, given knowledge of some state and exogenous conditions, the framework is applied in an on-line fashion to provide probabilistic forecasts of future system states. For many hydrologic systems of practical interest, these forecasts can be accomplished in real-time and can provide valuable management information.
H33D-0501 1340h
Taking the Next Step: Using Water Quality Data in a Decision Support System for County, State, and Federal Land Managers
Each passing year amplifies the demands placed on communities across the US in terms of population growth, increased tourism, and stresses resulting from escalated use. The conflicting concerns of recreational users, local citizens, environmentalists, and traditional economic interests cause land managers to contend with controversial decisions regarding development and protection of watersheds. Local history and culture, politics, economic goals, and science are all influential factors in land use decision making. Here we report on a scientific study to determine the sensitivity of alpine areas, and the adaptation of this study into a decision support framework. We use water quality data as an indicator of ecosystem health across a variety of alpine and subalpine landscapes, and input this information into a spatially-based decision support tool that planners can use to make informed land use decisions. We develop this tool in a case study in San Juan County, Colorado, a site chosen because its largest town, Silverton, is a small mountain community experiencing a recent surge in tourism and development, and its fragile high elevation locale makes it more sensitive to environmental changes. Extensive field surveys were conducted in priority drainages throughout the county to map the spatial distribution and aerial extent of landscape types during the summers of 2003 and 2004. Surface water samples were collected and analyzed for inorganic and organic solutes, and water quality values were associated with different land covers to enable sensitivity analysis at the landscape scale. Water quality results for each watershed were entered into a module linked to a geographic information system (GIS), which displays maps of sensitive areas based on criteria selected by the user. The decision support system initially incorporates two major water quality parameters: acid neutralizing capacity (ANC) and nitrate (NO3-) concentration, and several categories of sensitivity were created based on ANC and NO3- levels (e.g., pristine, slightly sensitive, moderately sensitive, highly sensitive, sensitive but unimpacted, disturbance impacted). We based threshold concentrations for these water quality parameters on first principles developed at the Niwot Ridge LTER site. Additional parameters such as specific conductance, base cation concentration, sulfate concentration, and dissolved organic carbon concentration may be added for a particular landscape type. Superimposed on this categorization, federal, state, and county planners are able to make decisions about the degree of potential impairment or enhancement produced by a particular project, or the maximum level of acceptable impairment to a particular area. Because water quality parameters are correlated with landscape types, the model returns a map of the watershed, partitioned by landscape type, presenting the sensitivity level of each area. This format provides land use managers with spatial criteria for project implementation.
H33D-0502 1340h
The Watershed and River Systems Management Program: Decision Support for Water- and Environmental-Resource Management
Increasing demands for limited fresh-water supplies, and increasing complexity of water-management issues, present the water-resource manager with the difficult task of achieving an equitable balance of water allocation among a diverse group of water users. The Watershed and River System Management Program (WARSMP) is a cooperative effort between the U.S. Geological Survey (USGS) and the Bureau of Reclamation (BOR) to develop and deploy a database-centered, decision-support system (DSS) to address these multi-objective, resource-management problems. The decision-support system couples the USGS Modular Modeling System (MMS) with the BOR RiverWare tools using a shared relational database. MMS is an integrated system of computer software that provides a research and operational framework to support the development and integration of a wide variety of hydrologic and ecosystem models, and their application to water- and ecosystem-resource management. RiverWare is an object-oriented reservoir and river-system modeling framework developed to provide tools for evaluating and applying water-allocation and management strategies. The modeling capabilities of MMS and Riverware include simulating watershed runoff, reservoir inflows, and the impacts of resource-management decisions on municipal, agricultural, and industrial water users, environmental concerns, power generation, and recreational interests. Forecasts of future climatic conditions are a key component in the application of MMS models to resource-management decisions. Forecast methods applied in MMS include a modified version of the National Weather Service's Extended Streamflow Prediction Program (ESP) and statistical downscaling from atmospheric models. The WARSMP DSS is currently operational in the Gunnison River Basin, Colorado; Yakima River Basin, Washington; Rio Grande Basin in Colorado and New Mexico; and Truckee River Basin in California and Nevada.
http://www.usbr.gov/pmts/rivers/warsmp/
H33D-0503 1340h
Evaluating the hydrologic and economic impacts of incresed groundwater use in the Yaqui Valley Irrigation District, Mexico
An integrated hydrological-economic-agronomic modeling framework is developed to address water policy in the Yaqui Valley, a semi-arid agricultural region in northwest Mexico. The modeling framework includes physically-based hydrological and agronomic processes and hierarchical decision-making by water managers and farmers. The hydrologic component consists of (a) a physically-based canal routing model, and (b) a complete, stand-alone three-layer groundwater flow model. The agronomic component represents the yield response of major Yaqui Valley crops to total seasonal irrigation depth and salinity. The economic component is a set of mathematical formulations representing the decision-making processes of (a) groups of farmers (modules), and (b) water managers in the Yaqui Valley. Each Module-Level Decision Model determines crop, irrigation, and pumping levels to maximize single-year profits, subject to land, water, and scheduling constraints. The set of module-level decision models successfully reproduced 1996-2002 Valley-wide crop production, in part due to the underlying spatial variability in yield potential and irrigation efficiency.
H33D-0504 1340h
Airborne Laser Altimetry (LIDAR) Support of Floodplain Inundation Modeling of Arid Southwest Stream Systems to Predict WoUS Boundaries
The U.S. Army Corps of Engineers (COE) is actively involved in floodplain management and regulation of dry wash floodplains in the western United States. The COE also regulates "Waters of the United States" (WoUS) under Sec. 404 of the Clean Water Act by determining the extent of surface indicators related to "ordinary" flood discharges known as Ordinary High Water Marks (OHWM). Currently, the return interval for inundation to the WoUS boundary is not well understood. Large flood inundation models (50, 100 yr flood events) currently available do not reflect features found in the field useful for placement of OHWM. At the present time, COE hydrologic models such as HEC-1 and HEC-RAS require detailed site information for rainfall and stream flow characteristics as well as on-site surveys to determine channel morphology, width, fluvial patterns, slope and other physical attributes. Typically, the fine-scale resolution necessary for 1-D hydrologic models is obtained from a limited number of channel cross sections obtained with survey equipment. The focus of this research is to develop a quantitative method to accurately reproduce determined flood return inundation levels in support of identifying the events that best represent the extent of the "ordinary" high water using high-resolution topography acquired through Light Infrared Detection and Ranging (LIDAR). Using NASA's Airborne Topographic Mapper (ATM) as a source of high-resolution topographic data we were able to acquire highly precise horizontal (~10cm) and vertical height locations (~5-10 cm) at several arid stream test reaches throughout the Mojave Desert, California. By incorporating LIDAR data into HEC-RAS models at a non-interpolated 2m cross section spacing our results have shown that 1-D flood inundation models that are typically used for high-flow events is capable of determining the geomorphic signature, extent and inundation frequency of "ordinary" flood events.
H33D-0505 1340h
Economic Valuation of Aquifer Storage Projects
There are economic benefits and costs associated with using aquifers as storage reservoirs for water-supply systems. Direct benefits include utilization of the conveyance and treatment capabilities of groundwater systems, reduction of pumping lifts, and control of subsidence and seawater intrusion. Indirect benefits include the buffer and existence values of storing water within aquifers. These benefits may include the avoided costs of obtaining water from other sources during water-short periods (when aquifer-stored water is available for use instead), or the avoided economic and social impacts of a water shortfall during such periods. Costs include the direct capital and operating costs of aquifer storage projects, as well as indirect costs such as water-quality degradation. To quantify these costs and benefits, it is necessary to correlate economic measures with the relevant hydrologic variables. Case studies of projects in California illustrate some specific economic aspects of aquifer storage programs. Objectives for these projects range from maximizing water stored in the ground to minimizing the marginal costs of operations. Economic valuation of aquifer storage projects also can be conducted within the larger context of conjunctive groundwater/surface-water management. For example, simulation-optimization modeling is being used to identify economically efficient strategies for operating spreading and injection facilities under alternative scenarios regarding availability and costs of different water sources, regulatory requirements, and groundwater demand.
H33D-0506 1340h
Evaluating the Management Implications of Scientific Research
When doing scientific research, we collect some data, apply statistical analysis, and then discuss its management implications. These management implications generally consist of interpretations and/or calculations to make the inferred statistical statements meaningful to decision makers. As with any other simplification, a management implication is an imperfect representation, which can recommend management actions quite unlike those that would have been recommended by the data or statistical results. There is no rigorous framework however for evaluating management implications that is comparable to the use of experimental design in the collection of data or statistical inference in the evaluation of hypotheses. A framework for evaluating management implications can be constructed by noting that the goal of management implications is to guide management decisions. A good management implication can be defined as one that recommends management actions similar to those that would have been recommended by the data or statistical results. The true unsimplified management implication of the data can in turn be defined as, "the probability of alternate outcomes of a proposed action given the observed outcomes of past actions." This is know in statistics as the posterior predictive distribution and can be directly calculated. Applying the posterior predictive distribution to alternate management actions identifies the actions that are recommended by the data. These recommendations in turn can be compared to the recommendations of alternate simplified management implications to identify the best simplified management implication. A less rigorous framework can be created by simply trying to use the results of classical statistics to predict the consequences of proposed actions. The potential consequences of the non-rigorous approach (and the utility of this proposed framework) can be seen by revisiting the previous analyses of the impacts of timber harvest on peak streamflow in the H.J. Andrews experimental forest. Applying this framework to the same data and models shows that contrary to the previous management implications, there actually is strong evidence that timber harvest has large impact on peak streamflows and that this impact increases with larger floods. Similar results could also have been produced if the previous results had been used to predict the consequences of alternate actions.
H33D-0507 1340h
Forest Road Decommissioning Policies Determined using Deterministic and Stochastic Dynamic Programming
Extensive timber harvesting and the accompanying road construction in the Pacific Northwest region have decreased the quality of fish-bearing streams. The decommissioning of abandoned forest roads increases stream quality by decreasing erosion and downstream sedimentation. Road removal treatments have been performed in many locations. However, the management of these treatments has been generally site-specific, with little investigation of how the treatments will affect the entire watershed. Land managers have a need to design a watershed wide management policy to reduce sedimentation, while maintaining overall costs within a reasonable limit. Identifying the trade-offs of the costs of different treatment policies associated with net reduction of sediment can be quantified. This work further develops optimization approaches to manage road decommissioning projects. Previous work in deterministic dynamic programming and genetic algorithmes did not incorporate the uncertainty of the effectiveness of the road treatments. Stochastic dynamic programming is used to determine the road treatment policy that maximizes the expected sediment saved. This approach is used to determine a policy for the Lost Man Creek Watershed in Northern California containing 691 road segments and road crossings. The model determines the optimal treatment level for each road segment and road crossing while considering a budgetary constraint.