Civil Engineering Faculty Publications and Presentations

Explaining the Hydroclimatic Variability and Change in the Salmon River Basin

Venkataramana Sridhar et al. — Thu, 16 May 2013 13:10:42 PDT

Climate change in the Pacific Northwest and in particular, the Salmon River Basin (SRB), is expected to bring about 3–5 °C rise in temperatures and an 8 % increase in precipitation. In order to assess the impacts due to these changes at the basin scale, this study employed an improved version of Variable Infiltration Capacity (VIC) model, which includes a parallel version of VIC combined with a comprehensive parameter estimation technique, Shuffled Complex Evolution (SCE) to estimate the streamflow and other water balance components. Our calibration (1955–1975) and validation (1976–1999) of the model at the outlet of the basin, White Bird, resulted in an r² value of 0.94 which was considered satisfactory. Subsequent center of timing analysis showed that a gradual advancement of snowmelt induced-peak flow advancing by about 10 days in the future. Historically, the flows have shown a general decline in the basin, and in the future while the magnitudes might not be greatly affected, decreasing runoff of about 3 % over the next 90 years could be expected and timing of peak flow would shift by approximately 10 days. Also, a significant reduction of snow water equivalent up to 25 %, increased evapotranspiration up to 14 %, and decreased soil moisture storages of about 2 % is predicted by the model. A steady decline in SWE/P from the majority of climate model projections for the basin was also evident. Thus, the earlier snowmelt, decreasing soil moisture and increased evapotranspiration collectively implied the potential to trigger drought in the basin and could affect the quality of aquatic habitats and their spawning and a detailed investigation on these impacts is warranted.

Evaluation of the Complementary Relationship Using Noah Land Surface Model and North American Regional Reanalysis (NARR) Data to Estimate Evapotranspiration in Semiarid Ecosystems

W. Thilini Jaksa et al. — Wed, 27 Mar 2013 11:11:20 PDT

Estimating evapotranspiration using the complementary relationship can serve as a proxy to more sophisticated physically based approaches and can be used to better understand water and energy budget feedbacks. The authors investigated the existence of complementarity between actual evapotranspiration (ET) and potential ET (ET_p) over natural vegetation in semiarid desert ecosystems of southern Idaho using only the forcing data and simulated ﬂuxes obtained from Noah land surface model (LSM) and North American Regional Reanalysis (NARR) data. To mitigate the paucity of long-term meteorological data, the Noah LSM-simulated ﬂuxes and the NARR forcing data were used in the advection–aridity (AA) model to derive the complementary relationship (CR) for the sagebrush and cheatgrass ecosystems. When soil moisture was a limiting factor for ET, the CR was stable and asymmetric, with b values of 2.43 and 1.43 for sagebrush and cheatgrass, respectively. Higher b values contributed to decreased ET and increased ET_p, and as a result ET from the sagebrush community was less compared to that of cheatgrass. Validation of the derived CR showed that correlations between daily ET from the Noah LSM and CR-based ET were 0.76 and 0.80 for sagebrush and cheatgrass, respectively, while the root-mean-square errors were 0.53 and 0.61 mm day^--1 .

Groundwater Levels in Northern Texas High Plains: Baseline for Existing Agricultural Management Practices

Jairo E. Hernández et al. — Tue, 26 Mar 2013 13:57:30 PDT

New groundwater policies are being debated for the Northern Texas High Plains because of Ogallala Aquifer depletion. These policies should be evaluated using a calibrated groundwater model for assessing their impact on subsequent groundwater levels. The objective of this study was to calibrate and validate a regional groundwater model for predicting the impact of existing agricultural management practices on groundwater levels beneath 4 counties located in the Northern Texas High Plains. Results indicated that the MODFLOW-2000 groundwater model was calibrated and validated satisfactorily based on reproducing and comparing groundwater levels with coefficients of determination of 0.97 and 0.98, root mean square errors of 28.0 meters (91.9 feet) and 15.5 meters (50.9 feet). The model showed normalized root mean square errors of 6.9% and 4.3%, for calibration and validation, respectively. Analysis of prediction results indicated that 2 zones would become depleted if the current level of aquifer exploitation continues with no modification for the next 50 years. The calibrated model should assist water managers in evaluating alternative agricultural management policy scenarios.

How Rapidly Should Developing Countries Implement Intelligent Transportation Systems (ITS) to Solve the Growing Urban Traffic Congestion Problem?

Mandar Khanal — Mon, 25 Feb 2013 12:15:47 PST

Many newly developing countries are growing rapidly. One example is India, currently the second most populous country in the world. According to the Indian Ministry of Urban Development, from 1981 to 2001, the population in six major Indian cities increased twofold while motor vehicles increased eightfold. Such rapid growth in vehicles without a comparable growth in transportation infrastructure leads to increasing traffic congestion. Cities in India are already considered congested today, and are going to be even more congested in the coming years since the rate of urbanization in India in 2006 was only 29% and is expected to grow to 41% by 2030 [1]. The corresponding rates for the world and Asia as a whole are projected to be 61% and 55%, respectively.

Near Surface Hydrometeorology for Sustainable Water Management

V. Sridhar et al. — Thu, 25 Oct 2012 12:39:31 PDT

Due to strong interactions between the land and atmosphere and the resulting feedbacks as altered by the anthropogenic changes, it is critical to quantify the surface fluxes and boundary layer properties that has direct implications on the regional evolution of hydrometeorology. This study evaluates the impact of irrigation using the Weather Research and Forecasting (WRF) numerical weather prediction (NWP) model in the Snake River Basin in Idaho. Our simulation extends for the period in the growing season and compares the control and irrigation runs to assess the irrigation induced cooling on the surface energy balance. Understanding this near surface cooling is directly useful for sustainable water management under changing climate conditions in the future. We present simulated latent and sensible heat fluxes as well as air temperature, relative humidity and the depth of the planetary boundary layer (PBL) over the region.

Characterization of Groundwater Contaminant Source Using Bayesian Method

Hui Wang et al. — Tue, 18 Sep 2012 15:21:12 PDT

Contaminant source identification in groundwater system is critical for remediation strategy implementation, including gathering further samples and analysis, as well as implementing and evaluating different remediation plans. Such problem is usually solved with the aid of groundwater modeling with lots of uncertainty, e.g. existing uncertainty in hydraulic conductivity, measurement variance and the model structure error. Monte Carlo simulation of flow model allows the input uncertainty onto the model predictions of concentration measurements at monitoring sites. Bayesian approach provides the advantage to update estimation. This paper presents an application of a dynamic framework coupling with a three dimensional groundwater modeling scheme in contamination source identification of groundwater. Markov Chain Monte Carlo (MCMC) is being applied to infer the possible location and magnitude of contamination source. Uncertainty existing in heterogonous hydraulic conductivity field is explicitly considered in evaluating the likelihood function. Unlike other inverse-problem approaches to provide single but maybe untrue solution, the MCMC algorithm provides probability distributions over estimated parameters. Results from this algorithm offer a probabilistic inference of the location and concentration of released contamination. The convergence analysis of MCMC reveals the effectiveness of the proposed algorithm. Further investigation to extend this study is also discussed.

Interaction Between Electromagnetic Waves and Transport in Saturated Media

Mahsa Azad et al. — Fri, 01 Jun 2012 15:07:43 PDT

Air sparging is one of the most popular remediation technologies. However, it is limited to a small radius of influence (ROI) surrounding the air injection well. Hence, there have been several efforts to improve its effectiveness. To study the possibility of improving the effectivity of air sparging electromagnetic (EM) waves, an easily visible analogous problem (dye transport in water) is studied in this paper. In order to quantify the effects of EM stimulation on flow of an inert, nonreactive dye in water, EM-stimulated and unstipulated dye transport experiments tests were performed and compared. To quantify this interaction, both dye transport and EM wave propoagation (only the electric field component Z) are quantified experimentally in lab-scale. In addition to the experimental mapping of the electric field at limited location on depth (i.e., vertical) slices, the electric field is simulated in COMSOL Multiphysics 4.1 in three dimensions (3D) for accurate field analysis. Transport analysis of the dye was performed using digital imaging to determine temporal and spatial concentration variations. The results show a visible effect on the dye transport mechanisms (i.e., fingering and diffusion). However, further study is needed to validate the proposed correlation between the electric field and the transport mechanisms.

Assessing Canal Structure Automation Rules Using an Accuracy-Based Learning Classifier System, a Genetic Algorithm, and a Hydraulic Simulation Model in the Boise River

Jairo E. Hernández et al. — Tue, 29 May 2012 11:44:32 PDT

Using state-of-the-art computational techniques, a genetic algorithm (GA) and an accuracy-based learning classifier system (XCS) were shown to produce optimal operational solutions for gate structures operation in irrigation canals. An XCS has been successfully developed to generate a set of operational rules for canal gates through the exploration and exploitation of rules using a GA, with the support of an unsteady-state hydraulic simulation model. A computer program which implemented the XCS was used to develop operational rules to operate all canal gate structures simultaneously, while maintaining water depth near target values during variable-demand periods, and with a hydraulically stabilized system when demands were no longer changed. Data from two reaches of the Boise River Project were used for assessing performance of the model. In the tested cases, thousands XCS simulations involving thousands of hydraulic simulations, were required to produce satisfactory rules. However, the overall fitness of the set of rules was increased monotonically as XCS simulations progressed. Simulated water depths approached the respective target depths for variable water delivery demand through turnout structures in the simulated canal systems.

Modeling Groundwater Levels on the Calera Aquifer Region in Central Mexico Using ModFlow

Jairo E. Hernández et al. — Tue, 29 May 2012 11:24:06 PDT

A conceptual model for the Calera Aquifer has been created to represent the aquifer system beneath the Calera Aquifer Region (CAR) in the State of Zacatecas, Mexico. The CAR area was uniformly partitioned into a 500 X 500 m grid generating a high resolution model that represented the natural boundaries of the aquifer. A computer model was calibrated and validated to verify output from the model corresponding to situations that matched the historical aquifer performance. Predicted groundwater levels were compared with measured data collected from nine observation wells between 1954 and 2004 to evaluate model performance. The main objective of this study was to develop and evaluate a groundwater modeling system using ModFlow-2000 for the CAR. Performance statistics indicated that the model performed well in simulating historic groundwater levels in the central part of the CAR where irrigated agriculture was concentrated. Results evaluation yielded average coefficients of determination of 0.81 and 0.67 and root mean square error values lower than 25.1 m and 25.9 m for the calibration and validation processes, respectively. These results are indicative of a good agreement between predicted and observed groundwater levels. However, further improvements in the conceptual model may be needed to improve predictions in other parts of the CAR for evaluating alternative groundwater management strategies.

Pavement Thickness Evaluation by GPR Survey in Idaho

Joseph C. Sener et al. — Thu, 10 May 2012 15:25:31 PDT

In 1995 and 1996, the Idaho Transportation Department (lTD) conducted a series of ground-penetrating radar (GPR) surveys as a nondestructive testing (NDT) method to evaluate the thickness of asphalt and Portland cement concrete (AC/PCC) pavements in Idaho. GPR surveys employed both air-coupled and combination air and ground coupled systems with their associated equipment and software. A total of 30 miles of AC/PCC pavements were evaluated by GPR surveys. The results obtained were correlated with the site-specific ground-truth data from borings.

Knowledge of pavement layer thickness is needed to predict pavement performance, establish load carrying capacities and develop maintenance and rehabilitation priorities. In addition, for new construction, it is important to ensure that the thickness of materials being placed by the contractor is acceptably close to specification. Core sampling and test pits are destructive to the pavement system, expensive, time consuming and intrusive to traffic. The objective of the lTD study was to evaluate, compare and assess the ability of these two GPR systems to accurately measure the thickness of multiple pavement layers, and document the data nondestructively. This paper reviews the findings of these surveys and provides statistically based data for both AC and PCC pavements.

The overall study has shown that reasonably accurate, dependable determination of pavement thickness can be achieved by using GPR survey for conditions encountered in Idaho.

Experimental Validation of a Numerical Forward Model for Tunnel Detection Using Cross-Borehole Radar

Arvin Farid et al. — Fri, 16 Mar 2012 13:37:07 PDT

The goal of this research is to develop an experimentally validated twodimensional (2D) finite difference frequency domain (FDFD) numerical forward model to study the potential of radar-based tunnel detection. Tunnel detection has become a subject of interest to the nation due to the use of tunnels by illegal immigrants, smugglers, prisoners, assailants, and terrorists. These concerns call for research to nondestructively detect, localize, and monitor tunnels. Nondestructive detection requires robust image reconstruction and inverse models, which in turn need robust forward models. Cross-Well Radar (CWR) modality is used for experimentation to avoid soil-air interface roughness. CWR is not a versatile field technology for political boundaries but is still applicable to monitoring the perimeter of buildings or secure sites. Multiple-depth wideband frequency-response measurements are experimentally collected in fully water-saturated sand, across PVC-cased ferrite-bead-jacketed borehole monopole antennae at a pilot scale facility (referred to as SoilBED). The experimental results are then compared with the 2D-FDFD model. The agreement between the results of the numerical and experimental simulations is then evaluated. Results of this work provide key diagnostic tools that can help to develop the algorithms needed for the detection of underground tunnels using radar-based methods.

Impacts of Climate Change on Hydrology and Water Resources in the Boise and Spokane River Basins

Xin Jin et al. — Mon, 21 Nov 2011 16:35:21 PST

In the Pacific Northwest, warming climate has resulted in a lengthened growing season, declining snowpack, and earlier timing of spring runoff. This study characterizes the impact of climate change in two basins in Idaho, the Spokane River and the Boise River basins. We simulated the basin-scale hydrology by coupling the downscaled precipitation and temperature outputs from a suite of global climate models and the Soil and Water Assessment Tool (SWAT), between 2010 and 2060 and assess the impacts of climate change on water resources in the region. For the Boise River basin, changes in precipitation ranged from −3.8 to 36%. Changes in temperature were expected to be between 0.02 and 3.9°C. In the Spokane River region, changes in precipitation were expected to be between −6.7 and 17.9%. Changes in temperature appeared between 0.1 and 3.5°C over a period of the next five decades between 2010 and 2060. Without bias-correcting the simulated streamflow, in the Boise River basin, change in peak flows (March through June) was projected to range from −58 to +106 m³/s and, for the Spokane River basin, the range was expected to be from −198 to +88 m³/s. Both the basins exhibited substantial variability in precipitation, evapotranspiration, and recharge estimates, and this knowledge of possible hydrologic impacts at the watershed scale can help the stakeholders with possible options in their decision-making process

Near-Surface Soil-Water Monitoring for Water Resources Management on a Wide-Area Basis in the Great Plains

K. G. Hubbard et al. — Mon, 21 Nov 2011 15:19:30 PST

River salinization is a byproduct of water resource development that results from cumulative impacts of flow-regime modifications and crop irrigation. However, historical salinization in the Lower Pecos River is often attributed to natural, high-salinity groundwater. Here, evidence from literature and U.S. Geological Survey gaging stations is reviewed to summarize historical changes associated with water development that potentially contributed to Pecos River salinization. A suite of hydrological changes, initiated in the 1880s, likely contributed to streamflow salinization: (1) reduced flood frequency and magnitude, (2) diminished streamflow, (3) increased evapotranspiration, and (4) increased prevalence of natural, high-salinity groundwater. Salinization is presently highest where these cumulative impacts were greatest (Red Bluff Dam to Girvin, Texas). Prior to water-resource development, higher, fresher streamflows and periodic floods diluted natural, high-salinity groundwater inflows and continuously exported salts from the drainage. Predevelopment salinity was low enough to support at least 44 native fishes, 13 of which have disappeared from the region. Only seven euryhaline natives remain in the most salinized river reach. However, flow-regime restoration and improved irrigation practice could potentially reduce salinization and partially restore a freshwater fauna.

Climate Change and the Payette River Basin

David J. Hoekema et al. — Mon, 21 Nov 2011 15:10:34 PST

The Intergovernmental Panel on Climate Change’s Report on Climate Change and Water (Bates et al. 2008) identified the need to address the impacts of climate change at a scale applicable to the management of water resources. The Payette River basin, located in central Idaho, is a major tributary of the Snake River and contains three significant dams: the Black Canyon Dam (1924), Deadwood Dam (1931), and Cascade Dam (1948). The dams along the Payette River are operated by the Payette Division of the United States Bureau of Reclamation’s (USBR) Boise Project. Storage, which exceeds 800,000 acrefeet, provides irrigation for some of the most economically productive farmland in Idaho. This research seeks to answer the question of how robust the current water resource system is to handle future climate change and asks how climate changes compares with other factors influencing water resource planning. This research uses a local water resource management tool, the Snake River Planning Model (SRPM), to assess the impacts of climate change. We found that current water resource management practices in the Payette River basin are robust enough to handle the impacts of climate change at least through 2050. However, urbanization and increased flood risks with climate change will need to be addressed when considering the sustainable development of the basin.

The Adaptability and Sustainability of Surface Water Diversions Along the Main Stem of the Snake River in Southern Idaho

David J. Hoekema et al. — Tue, 20 Sep 2011 12:19:27 PDT

Agriculture in southern Idaho depends heavily on the conversion of snowpack into spring runoff. The Natural Resource Conservation Service (NRCS) has developed a Surface Water Supply Index (SWSI) as a tool to predict whether or not forecasted runoff and reservoir storage will be adequate to meet irrigator’s needs at a basin scale. This research by comparing SWSI to diversions for individual canals advances the use of SWSI to develop a Surface Water Supply Metric (SWSM) that can be used to estimate the reliability and sustainability of diversions under historic and projected time periods. An historic analysis of diversions during three time periods 1928-1957, 1960-1980, and 1980-2009 indicates how the construction of Palisades Reservoir in 1956 allowed some canals to increase diversions, while other canals where able to improve the reliability of diversions. The analysis also highlights how decreasing diversions by irrigators (10% and 13% in July and August, respectively) from the Twin Falls North Side Canal Compnay has increased diversion reliability in those months. The second section of the research uses the SWSM to assess the sustainably of diversions under three projected climate change scenarios. All projected flow scenarios were run using a system dynamics version of the Snake River Planning Model (SRPM) developed by the authors. SRPM is currently used by the Idaho Department of Water Resources (IDWR) to plan water resource management in the Snake River basin. The analysis indicates based on the projected climate scenarios analyzed that upstream irrigators may see a significant decline in reliability while downstream users may see improved irrigation reliability.

An Experimental Setup for Electromagnetic Stimulation of Air Sparging

Arvin Farid et al. — Fri, 09 Sep 2011 15:36:38 PDT

The task of cleaning leakage from aging underground tanks along with surface spills of gasoline and other hazardous chemicals is of utmost importance to federal and state agencies. Minimally disruptive remediation techniques, such as air sparging, have become more attractive in the past decade compared with more traditional ex-situ remediation technologies. However, formation of air channels and slow airflow between them can make air sparging and similar methods less effective. The existing methods to stimulate airflow, such as pulsating air sparging systems, are time-consuming and not as effective.

Using radio frequency (RF) stimulation can expedite the remediation by affecting the formation, shape and size of air channels, and increasing air diffusion between these channels. To study the diffusion and RF stimulation, different cases will be studied within a clear acrylic box with: (i) water as the medium and an inert dye as the diffusive matter, and (ii) a water-saturated glass bead medium with air as the diffusive matter. A high power (75W) electromagnetic (EM) field is radiated through the saturated medium using two parallel copper plates (antennae), one connected to the amplifier, and the other grounded. The alternating electric field oscillates the dipole water molecules, which in turn, enhances the airflow. The first case studies the effect of the stimulation on diffusion. In the second case, in addition to the effect of the electric field on air diffusion, its effect on air channel formation is studied.

An Experimental Setup for Electromagnetic Stimulation of Geoenvironmental Applications

Arvin Farid et al. — Fri, 09 Sep 2011 15:24:29 PDT

Cleaning contaminated soil/groundwater is important to federal and state agencies. Traditional contaminant removal methods are costly and impractical for large sites. Less disruptive remediation techniques (e.g., air sparging) are attractive but limited by the restriction of airflow in soil. The use of electromagnetic (EM) stimulation to expedite airflow, diffusion, and control air channel formation is investigated. The diffusion of an inert dye as the diffusive matter within water and the effect of EM waves on the diffusion are experimentally modeled. To study the effect on air sparging through saturated soil, a clear acrylic box filled with a water‐saturated glass bead medium and air as the diffusive matter is used. The effects of the electric field on air channel formation in the second case (i.e., glass‐bead medium) are studied. It is expected that the stimulation of the water increases the diffusion of air between air channels and expands the air channel volume. The EM field is made possible using a dipole antenna connected to an RF source. The alternating electric field emitted off the antenna into the medium, oscillates the dipole water molecules. The stimulation helps enhance diffusion and enlarge the formed air channels.

A New Coupled Optimization‐Hydraulic Routing Model for Real‐Time Operation of Regulated River Systems

Arturo S. Leon et al. — Wed, 10 Aug 2011 13:33:36 PDT

This paper presents the River Simulation and Optimization Coupled Model (RSOCM) for the optimal operation of regulated river systems in real-time conditions. This model couples a highly robust and numerically efficient hydraulic routing approach with the well-known multi-objective Non-dominated Sorting Genetic Algorithm II (NSGA-II). The proposed model overcomes the lack of robustness of current models for unsteady flow routing. The lack of robustness of current unsteady flow models (e.g., numerical instability) constitutes a strong limitation for the development and implementation of real-time strategies in complex hydraulic systems that are intended to fulfill multiple objectives (e.g., minimization of flooding, optimal water allocation at specified diversion points). The real-time control of such complex systems may require thousands of computations of hydraulic routing for each operation interval. The optimization objectives supported by the RSOCM model include the optimal water allocation at specified diversion points and minimization of flooding. To demonstrate the proof of concept of the RSOCM model, it was applied to a hypothetical river system. As frame of comparison for the RSOCM model, the MODSIM-DSS model (Colorado State University, 1995) was used in this paper. The results suggest that the RSOCM model is a robust tool that can be potentially used for the optimal operation of multi-objective regulated river systems in real-time conditions.

Flow Dynamics in Combined Storm‐Sewer Systems: Application of the Illinois Transient Model (ITM) to the Calumet TARP System in Chicago, Illinois

Arturo S. Leon et al. — Tue, 09 Aug 2011 13:03:29 PDT

The large variations in the inflows together with the complex operation of Combined Sewer Overflow (CSO) systems may result in flow conditions that vary from dry to free surface flow to partly free surface-partly pressurized flow (mixed flow), to fully pressurized flow. Transitions from one flow regime to another are governed by flow instabilities (Yen 1986). Some of these instabilities may produce undesirable events such as geysering phenomena, blow-off of manhole covers, manhole overtopping or structural damage of the system. In order to asses the impact of these undesirable events a transient analysis of these systems for various scenarios becomes important.

Bayesian Inference of Groundwater Contamination Source

Xin Jin et al. — Tue, 09 Aug 2011 12:08:56 PDT

Lots of uncertainty exists in the groundwater modeling, e.g. hydraulic conductivity, measurement variance and the model structure error. Monte Carlo simulation of flow model allows the input uncertainty onto the model predictions of concentration measurements at monitoring sites. Bayesian approach provides the advantage to update estimation. This work proposes a dynamic framework in contamination source identification of groundwater. Markov Chain Monte Carlo(MCMC) is being applied to infer the possible location and magnitude of contamination source. Unlike other inverse-problem approach to provide single but maybe untrue solution, the MCMC algorithm provides distribution over estimated parameters.