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Hydraulic jacking is a serious threat to concrete spillway chutes, demonstrated by the catastrophic spillway chute failure at California's Oroville Dam in 2017. To improve the understanding of uplift pressure and joint flow developed at open, offset joints and enable design and evaluation of anchors, drain systems, and joint remediations that could help prevent such failures, laboratory tests were performed in a supercritical flume furnished with a model joint where the gap width to offset height ratio was varied over a 725∶1 range. The tests included measurement of boundary layer velocity profiles approaching the joint. Uplift pressures were normalized to the velocity head near the boundary, which is related to the depth-wise velocity profile exponents determined in the experiments and can be estimated for field applications from the chute friction factor. The normalized uplift varies with the joint aspect ratio and the flow depth to offset height ratio. The new relations reduce the uncertainty of modeled uplift pressures by a factor of 2.87 over previous methods. Example applications demonstrate practical upper limits for potential uplift pressure. Subsequent articles will address discharge into offset joints, the dissipation of uplift via drainage, and the effect of different methods for remediating existing offsets to reduce uplift. Practical Applications: Concrete spillway chutes develop cracks and must necessarily be constructed with joints, both of which are prone to displacement over time that may create offsets into the flow. Flow striking such offsets is brought suddenly to rest, similar to a pedestrian tripping on a sidewalk crack. The local stoppage of flow at the offset creates dangerously high pressures that can be injected into the foundation, leading to erosion beneath the slab and potential uplift failure, often called 'hydraulic jacking'. This mechanism has caused several notable failures including the Oroville Dam spillway in 2017. Protection against such failures is usually provided by a combination of the weight (thickness) of the slab itself, anchors that hold the slab down, and subsurface drains that reduce the buildup of pressure. This paper provides experimentally based equations for predicting uplift pressure to enable effective design of new spillways and evaluation of existing spillways. The new equations are significantly more accurate than previous methods because they account for the roughness of the chute surface and the reduced flow velocity near the boundary. Subsequent papers will address flow rate through joints, pressure dissipation by drainage, and methods for treating existing offsets to reduce potential uplift. [ABSTRACT FROM AUTHOR]

For evaluating the resistance performance of cement-stabilized soils in cold regions, the variation of the strength of the cemented sand–gravel (CSG) mixture concerning the hydration process should be explored. This paper aims to study the effect of freeze–thaw (F–T) cycles on the strength and microstructure of a CSG mixture with 10% cement that is subjected to 12 cycles of freezing at a temperature of −23°C for 24 h and then melted at room temperature of 24°C for the next 24 h. The uniaxial compressive strength (UCS), California bearing ratio (CBR), and weight volume loss of the samples were measured after individual F–T cycles. Furthermore, the change in the microstructure of the CSG mixture in various F–T cycles was explored. The results showed a considerable reduction in the UCS up to Cycle 3, then a slight increase for Cycles 3–6, and finally a gradual decrease for further cycles. However, the CBR and weight loss slightly fluctuated up to Cycle 6, and then gradually decreased for subsequent cycles. The majority of compounds of hydrated cement were damaged in the first three cycles. In the following cycles, between Cycles 3 and 6, the portlandite compound was dissolved and recrystallized within the microvoids. Depending on the environmental conditions, carbonation may be generated from the hydrated cement fraction, which fills the microvoids and improves the strength and structure of the mixture. During further cycles after the sixth cycle, the mechanical action of the ice lenses coupled with the disintegration of the hydrate compounds imposed many new microvoids and cracks with considerable length and width, which intensified the strength reduction of the moisture and weakened the adhesion between grains. Since cement is widely used in pavement and dam engineering for stabilizing soils, the durability of cemented soils is of prime concern. This study may help improve the durability and resistance of cemented soils in cold climates. The F–T action not only influences the macrostructure of cement-stabilized soils by imposing a wide crack and ice lens but also induces a considerable change in the complexes existing in the hydrated cement paste of the mixture. Three patterns govern the change of the mixture microstructure in various F–T cycles that correspond to the observed trend in strength. The mentioned trend for the microstructure change and, consequently, the strength variation of the CSG mixture are associated with many factors such as pH, cement content, CO2 content, moisture content within the mixture, and relative humidity within the environment. Accordingly, the pattern of microstructural changes in the CSG mixture after the middle F–T cycles may vary depending on environmental conditions. [ABSTRACT FROM AUTHOR]

Some areas of the California coast have physical conditions—such as local bathymetry, topography, shoreline orientation, and other factors—that increase the risk for damage from tsunami inundation compared with other regions. Technical tsunami hazard analyses can inform decision-makers on regional planning and policy decisions. In this paper, we focus on recent efforts in California to delineate various tsunami hazard zones along the coastline under the Seismic Hazard Mapping Act, wherein structural mitigation measures will be recommended. To define the zone wherein structural mitigation measures are recommended, we present a state-wide tsunami reliability analysis that combines existing probabilistic hazard information and structure fragility curves derived from recent events. We examine design-life chances of significant structural damage for various structure types along all developed coastlines throughout California and use this analysis to show how hazard and risk have different correlations throughout the State. Finally, we outline an approach for creating mitigation zones, which provides state-wide tsunami risk consistency for all structures in the tsunami inundation zone. [ABSTRACT FROM AUTHOR]

This paper describes a public domain semiautomated data screening and quality assurance processing tool useful for both discrete and continuous data. This application serves both a field research project assessing salinity and methylmercury drainage load control options and the requirements of a public domain watershed-based water quality forecasting model used to provide decision support for short-term salinity management in the San Joaquin River Basin of California. The US Army Corps of Engineers HEC-DSSVue data management and visualization platform was enhanced in the former application with Python scripts that performed the basic data quality assurance functions. Analogous tools were developed for use on the HOSTGATOR cloud server using the same Python scripts and algorithms to migrate quality-controlled data directly to a server for use by the Watershed Analysis Risk Management Framework (WARMF) water quality forecasting model. The Python scripts for both applications are easily adaptable by other potential users who do not currently have the resources to implement an enterprise-level hydrological data management and real-time quality assurance software system. [ABSTRACT FROM AUTHOR]

This paper presents the analytical formulation and computational implementation of a conceptual probabilistic performance-based seismic design (PBSD) framework for ordinary standard bridge (OSB) structures. An updated probabilistic performance-based earthquake engineering (PBEE) assessment methodology is used for the parametric performance assessment of four distinct OSBs in California to investigate the effects of varying key structural design parameters over a primary design parameter space on risk-based structural performance measures. The dire need for a systematic PBSD framework for OSBs is illustrated given the significant variability in risk-based performance levels exhibited by these traditionally designed testbed OSBs. A PBSD methodology involving the design of the bridge piers is proposed wherein a risk-based feasible design domain in the primary design parameter space is identified which facilitates the risk-informed design/decision making process in the face of uncertainty. Sensitivities of risk-based feasible design domains compared with other (secondary) design variables and with the method employed for damage hazard assessment are investigated. [ABSTRACT FROM AUTHOR]

In California, after three decades of water market development, volume of water traded in the market remains lower than desired. Total volume of water traded annually accounts for just around 2%–5% of total water used. Vast difference in the marginal values of water in agriculture and urban or environmental uses suggest that significant economic gains can be achieved by easing the barriers to trading water across sectors. This paper draws attention to the role of state and local policies in restricting water transfers. Using novel, purpose-built, satellite-mapped data of a sample of water-trading irrigation districts in California, this paper shows how districts' water transfer decisions are made in response to conflicting pressures of drought-induced high-water demand against the need to support the agricultural economy and the environment in water-exporting areas. The time period under study is 1991–2019, which spans the entire history of water market activity in California from inception to maturity, and helps illustrate the role of changing local and state policies on irrigation districts' water market participation. Despite policy-induced restrictions, this paper shows that sample irrigation districts are highly responsive to demand in water-buying areas, have increased the volume and frequency of water transfers, particularly in the last decade. This paper highlights important research and policy questions about the distribution of economic and environmental effects of water transfers in source area communities that could affect the future potential of water markets in easing structural and drought-induced water scarcity in California. [ABSTRACT FROM AUTHOR]

Red beds (RBs) are widely distributed in all continents of the world. With the rapid development of road and railway construction, the construction of roads and railways in RB areas is increasing. However, when RB is the filler, it will expose three aspects of serious deficiencies in compaction, mechanical bearing capacity, and water stability, which will cause fatal harm to the subgrade. Therefore, RB has to be abandoned and cannot be used as a subgrade filler. In this paper, different microwave irradiation temperatures (DMITs) from room temperature of 25°C to 700°C were used to reveal the enhancing mechanism of RB in three aspects based on the analysis results of microscopic composition and structure. The microscopic composition and structure show that RB can be divided into a low-temperature section (25°C–400°C) and a high-temperature section (500°C–700°C) under the microwave condition. The low-temperature section has some improvement in the engineering performance of RB, but the influence is limited. The engineering performance of RB is improved completely in the high-temperature section. Specifically, the coarse size of RB increases with the rise in microwave temperature, which is beneficial for improving fine size. The compaction property of RB is not largely affected by the water content and can still meet the most stringent subgrade filler requirements, even under saturated conditions or 0. The California bearing ratio (CBR) value can maintain more than 20% under the ultimate working condition, far higher than the code requirements. The increase of internal friction angle and cohesion can enhance the stability of the cut slope, which is conducive to construction in remote mountainous areas. The water resistance of RB is positively correlated with the microwave irradiation temperature, especially at 700°C; RB experiences secondary hardening after encountering water, the mechanical strength increases, and the softening coefficient reaches 107.44%. The research shows that after microwave high-temperature stabilization, the engineering characteristics of the RB are thoroughly strengthened, and it becomes a high-quality subgrade filler to eliminate the three diseases of RB subgrade completely. Compared with the traditional method of adding stabilizers, microwave in situ RB stabilization reduces the site construction's complexity, saves a lot of stabilizer use and transportation costs, and can effectively reduce carbon emissions. This study provides a positive perspective on the in situ application of the RB soft rock subgrade. It could be a starting point for understanding the microwave-based stabilization of soft rock soils subgrade filler in situ. [ABSTRACT FROM AUTHOR]

The existing machine learning (ML) models for vibration-based damage assessments often use highly compressed features or are restricted to preprocessed signals with fixed durations and sampling rates. Additionally, the learning capacities of ML models and computational resources are limited, which restricts using raw signals as direct input. This paper studied Mel filter banks (MFBs) for seismic signal processing, inspired by speech recognition technology. It is argued that the same filter designs in audio engineering may not be appropriate for seismic records, and therefore, a customized filter bank formulation was developed. Hybrid deep learning models for rapid assessments (HyDRA) were introduced as multibranch neural network architectures that enable end-to-end training for different types of processed vibration data structures. Moreover, the performance-based earthquake engineering (PBEE) equation was adjusted to integrate ML model uncertainties for probabilistic assessments. The proposed concepts were validated in a case study based on a data set of 32,400 nonlinear time-history analyses of a highway bridge in California. Insights and guidelines are provided for optimum filter design based on 5,184 experiments. Several HyDRA architectures were compared with benchmark models. The optimized MFB feature type outperformed features obtained from continuous wavelet transform and a stacked vector of conventional earthquake engineering indexes. A Bayesian variant of HyDRA was investigated to showcase its integration in the modified PBEE equation. Adopting custom filter banks with the HyDRA architecture enables effective feature extraction from raw vibration records by diversifying feature space and preserving information in the time and frequency domains. [ABSTRACT FROM AUTHOR]

Roads constructed over poor ground conditions that carry high traffic volumes and axle loads may, over time, experience persisting occurrences of pavement distress. Road construction, be it a new or a rehabilitation project, is both costly and time-consuming. An appealing option that improves pavement durability, reduces construction cost and time, accelerates strength development over a short curing period, and decreases pavement thickness is to chemically stabilize local road materials. In contrast to other aggregate materials, there has been a gap in evaluating and quantifying the feasibility of chemical stabilization of sandstone aggregate that possesses marginal quality as a road construction material. Therefore, the aim of this paper is to provide an experimental investigation of relative strength development of sandstone aggregate subbase of marginal quality stabilized with combinations of Portland composite cement (PCC), ordinary Portland cement (OPC), and styrene–butadiene latex copolymer (or polymer). The samples were prepared with different gravel-to-sand (G:S) ratios of 2.1, 1.2, and 0.4 and subsequently stabilized with a polymer-cement (P/C) blend. Samples were compacted and cured under dry and wet conditions before measuring their unconfined compressive strength (UCS), indirect tensile strength (ITS), and California bearing ratio (CBR). At the same curing condition and P/C contents, it was found that the UCS and CBR of P/C-stabilized samples increased with increasing G:S ratios. At the same polymer and cement contents, the P/C-stabilized samples with the highest G:S ratio of 2.1 also demonstrated a significantly higher rate of UCS strength development compared with the samples with lower G:S ratio and unstabilized samples. Soil stabilization with a combination of 0.75% polymer and 5% cement contents yielded the highest UCS that was approximately seven times the UCS of unstabilized samples and an ITS of 0.73 MPa. Stabilization with a combination of 0.75% polymer and 3% cement contents yielded the highest CBR value that significantly exceeded 30% after only 4 days of soaking and was seven times that of unstabilized samples. This paper has thus demonstrated the potential improvement to the strength development of sandstone aggregate subbase stabilized with P/C blend under the optimal curing condition and the importance of identifying and using the optimal proportion of polymer and cement to achieve the target strength development and improvement. [ABSTRACT FROM AUTHOR]

This paper presents the formulation of a comprehensive risk-targeted performance-based seismic design (PBSD) framework involving the seismic design of bridge piers for California Ordinary Standard Bridges (OSBs), facilitating risk-informed design and decision making in the face of uncertainty. A full-fledged implementation of this all-inclusive design method formulated by retaining the inherent rigor of the underlying seismic performance assessment methodology might impose a seemingly prohibitive computational cost for the available resources in the current scenario of seismic bridge design practice. For reasons of practicability, the findings of the full-fledged design framework are inventively utilized to distill out a simplified and computationally more economical PBSD procedure. Its efficacy is validated using four already-built California testbed OSBs as cases in point. The proposed simplified design methodology is able to (1) find a design point in the primary design parameter space of a bridge to be designed for multiple risk-targeted performance objectives; and (2) delineate an approximate, yet sufficiently accurate, feasible design domain and identify the limit states controlling its boundary in the primary design parameter space of the bridge, at a computational cost significantly lower than that of the original method. [ABSTRACT FROM AUTHOR]

This paper presents full-scale experiments and computational analyses on exposed column–base plate connections with ductile anchors. The aim is to examine the seismic performance of these connections for their prospective use as weak bases, wherein steel moment frames are designed to concentrate inelastic rotations in the base connections rather than in the connected columns. The connections feature upset thread anchor rods in which the threads are milled to a smooth shank, providing a designated stretch length over which inelastic deformations may be concentrated. The shank is frictionally isolated from the footing using polyethylene tape. The four full-scale experiments investigate the effects of axial force, rod diameter, and rod material grade. The test specimens withstand (without anchor rod failure) the application of two Applied Technology Council–the Joint Venture partners of the Structural Engineers Association of California, the Applied Technology Council, and the Consortium of Universities for Research in Earthquake Engineering (ATC-SAC) protocols applied consecutively (each to drift amplitudes of 5%), followed by additional cycles to 6.5% drift amplitude. Complementary line element–based and continuum finite-element simulations are conducted to examine to what extent the experimentally observed response may be generalized to untested configurations. Implications for design are summarized, along with the limitations of the study. [ABSTRACT FROM AUTHOR]

The intensity of an atmospheric river (AR) is only one of the factors influencing the damage it will cause. We use random forest models fit to hazard, exposure, and vulnerability data at different spatial and temporal scales in California to predict the probability that a given AR event will cause flood damage, as measured by National Flood Insurance Program (NFIP) claims. We first demonstrate the usefulness of data-driven models and interpretable machine learning to identify and describe drivers of AR flood damage. Hazard features, particularly measures of AR intensity such as total precipitation, increase the probability of damage with increasing values up to a threshold point, after which the probability of damage saturates. Although hazard is generally the most important risk dimension across all models, exposure and vulnerability contribute up to a third of the explanatory power. Exposure and variability features generally increase the probability of damage with increasing values, apart from a few instances which can be explained by physical intuition, but tend to affect the probability of damage less for the largest AR events. Comparisons between random forest models at different spatial and temporal scales showed general agreement. We then examine limitations inherent in publicly available exposure, vulnerability, and loss data, focusing on the difference in temporal resolution between variables from different risk dimensions and discrepancies between NFIP claims and total flood losses, and describe how those limitations may affect the model results. Overall, the application of interpretable machine learning to understand the contributions of exposure and vulnerability to AR-driven flood risk has identified potential community risk drivers and strategies for resilience, but the results must be considered in the context of the data that produced them. [ABSTRACT FROM AUTHOR]

Changes in demand, various hydrological inputs, and environmental stressors are among the issues that reservoir managers and policymakers face on a regular basis. These concerns have sparked interest in applying different techniques to determine reservoir operation policy decisions. As the resolution of the analysis increases, it becomes more difficult to effectively represent a real-world system using traditional methods such as dynamic programming and stochastic dynamic programming for determining the best reservoir operation policy. One of the challenges is the "curse of dimensionality," which means the number of samples needed to estimate an arbitrary function with a given level of accuracy grows exponentially with respect to the number of input variables (i.e., dimensionality) of the function. Deep reinforcement learning (DRL) is an intelligent approach to overcome the curses of stochastic optimization problems for reservoir operation policy decisions. To our knowledge, this study is the first attempt that examines various novel DRL continuous-action policy gradient methods, including deep deterministic policy gradients, twin delayed DDPG (TD3), and two different versions of Soft Actor-Critic (SAC18 and SAC19) for optimizing reservoir operation policy. In this study, multiple DRL techniques were implemented to find an optimal operation policy for Folsom Reservoir in California. The reservoir system supplies agricultural, municipal, hydropower, and environmental flow demands and flood control operations to the City of Sacramento. Analysis suggests that the TD3 and SAC are robust to meet the Folsom Reservoir's demands and optimize reservoir operation policies. Experiments on continuous-action spaces of reservoir policy decisions demonstrated that the DRL techniques can efficiently learn strategic policies in spaces and can overcome the curse of dimensionality and modeling. [ABSTRACT FROM AUTHOR]

In recent years, the construction industry has shifted toward sustainability, replacing traditional binders with eco-friendly alternatives. One such alternative is vinyl acetate-ethylene (VAE) polymer, known for its hydrophobic properties and used in various construction materials. This study explores the potential of VAE polymer to stabilize expansive clay as road subgrade material. VAE polymer was introduced into low-plasticity clay in varying percentages (1%, 1.5%, and 2% by dry weight of clay), and the mixtures underwent a series of geotechnical tests (compaction, unconfined compressive strength (UCS), California bearing ratio (CBR), resilient modulus, shrinkage-swelling, and soil-water retention curve) and microstructural and chemical analyses [x-ray diffraction (XRD), x-ray fluorescence (XRF), microcomputed tomography (MicroCT), and thermogravimetric analysis (TGA)]. The results show that 1 adding 1% polymer resulted in the highest increase in mechanical strength (UCS, CBR, resilient modulus) by 34%, 40%, and 51%, respectively. Moreover, the incorporation of 2% polymer reduced the swelling-shrinkage potential by 67%. Microstructural analyses support these findings. [ABSTRACT FROM AUTHOR]

Stiffness quantification of unbound granular materials (UGMs) is essential for designing pavement structures. This stiffness can be determined directly through the resilient modulus test, or indirectly, by correlation, with the California bearing ratio (CBR) test. Alternatively, the dynamic CBR test (dCBR) has been proposed as a simple and low-cost method for this assessment. This study investigated a new dCBR test protocol based on a novel strain-stage approach, applying 20 load cycles/stage. This testing protocol is expected to facilitate characterization and on-site control of stiffness for UGMs, including marginal granular materials (MGMs). The study characterized four MGMs using the new dCBR test protocol and the resilient modulus test; four replicate specimens manufactured by gyratory compaction were assessed per material and test. The protocol was implemented successfully for the MGMs studied to compute an equivalent resilient modulus. A methodology is proposed for calculating an adjusted equivalent resilient modulus with values similar to those of the resilient modulus. Further research is suggested to explore the relationship between the dCBR and CBR tests to advance the characterization of granular materials for pavement structures and expand the experimental data using a broader set of soils to validate the protocol. [ABSTRACT FROM AUTHOR]

Phosphogypsum, which contains toxic components (e.g., heavy metal elements and fluoride), is one of the byproducts of phosphoric acid production, and filling subgrade is one of the recycling methods for it. In this study, phosphogypsum was stabilized by lime to improve the mechanical properties [California bearing ratio (CBR), resilience modulus, unconfined compressive strength, and shear strength], water stability, and harmful substances dissolubility. Combined with scanning electron microscopy, the strength formation and water stability enhancement mechanism of lime-stabilized phosphogypsum (LSP) were explored. The results demonstrated that the mechanical properties of LSP were better with the lime content of 6%–10%. The CBR, resilience modulus, unconfined compressive strength, and shear strength were 3.35 times, 2.46 times, 8.61 times, and 1.39 times that of plain phosphogypsum, respectively. An intensity prediction model with a correlation of 97% was constructed. The CBR and resilience modulus softening coefficient of LSP reached best values when lime content was 6%–8%. The leaching concentration of arsenic, chromium, and lead of LSP with 2% lime met the quality standards of groundwater levels I, II, and IV, respectively. Fluoride and phosphate were not detected in LSP when lime content was greater than 6.0%. The results show that LSP is feasible as subgrade filler. Considering the mechanical properties, water stability, and dissolution of hazardous substances of LSP, it is recommended to add 6%–8% lime content to LSP as highway subgrade filler. [ABSTRACT FROM AUTHOR]

Natural geotextiles both woven and nonwoven have proved to be beneficial in stabilizing the weak subgrade by extending the service life of pavement and reducing the cost of construction. Nonwoven geotextiles can be used as separator in pavements as they allow in-plane permeability, but their tensile strength is low. In this study, an attempt is made to develop eco-friendly needle-punched coir latex composite sheets as an alternative to nonwoven coir geotextiles. Three types of products were developed by the impregnation of nonwoven needle-punched fabric with prevulcanized latex having densities 400, 600, and 800 grams per square meter (GSM). An experimental investigation on the effect of latex content on the mechanical properties of coir composites revealed that latex impregnation improves the mechanical properties of all coir composites and composites with 50% latex content exhibited maximum performance. Strength and drainage characteristics of reinforced soil-aggregate system were studied to evaluate the potential of coir composites as a separator in low volume roads by conducting the California bearing ratio (CBR) test, permeability, and transmissivity tests. The performance of the developed coir composites was compared with nonwoven coir felt and woven coir geotextile. It was found that 800 GSM coir composite showed 47% improvement in performance when compared to 400 GSM woven coir geotextile which showed only 40% performance improvement. [ABSTRACT FROM AUTHOR]

Coordinated ramp metering (CRM) systems are implemented on freeways primarily to improve operational conditions. However, smoother traffic flow resulting from CRM may also have significant safety benefits. The main objective of this research is to evaluate the safety performance of CRM systems on the Interstate 80 (I-80) corridor in California by using an empirical Bayes before–after approach. We collected geometric features, traffic volume, and historical crash data from I-80 in the San Francisco Bay area (Caltrans District 4). Then, the freeway safety prediction methodology implemented using the Enhanced Interchange Safety Analysis Tool (ISATe, developed as part of a National Cooperative Highway Research Program Project 17-45) was utilized to estimate the counterfactual, i.e., the number of crashes if no CRM system was implemented on the corridor. Based on a comparison of this counterfactual with the actual crash counts in the post-CRM period, CRM implementation led to a decrease in the number of fatal and injury crashes on I-80 but an increase in minor property damage only crashes. Disaggregate analysis of the results was used to gain further understanding of the CRM safety performance. The differences in the resulting safety performances were contextualized based on the different settings where the systems were implemented. As expected, CRM systems were more effective for segments in the vicinity of ramps. Safety performance functions for shorter durations (e.g., for peak hours), the subject of the ongoing National Cooperative Highway Research Program Project 22-48, will help more precisely estimate the safety impact of CRMs. [ABSTRACT FROM AUTHOR]

Conservation in working landscapes is an important aspect of stream restoration. Landowners with agricultural water rights are increasingly adding instream flow as a beneficial use of their allocated water. However, stream restoration projects commonly focus on the quantity of water dedicated to the environment and overlook water quality. For cold-water ecosystems, the preservation of natural thermal regimes is a key to conservation efforts in the face of a changing climate. This study explored the effects of increasing stream flow using alternative water sources (e.g., instream runoff versus offchannel springs) to enhance cold-water stream habitat on a working cattle ranch. Using empirical data to create a steady-state stream flow and water temperature model, we evaluated temperature benefits and management trade-offs for ecological and agricultural water use. The modeled results showed that the source of water and the method used to deliver water to the channel affected the quality and extent of cold-water habitat. Offchannel spring water cooled 7-day average maximum temperatures and 7-day average mean temperatures by as much as 3.7°C and 2.9°C, respectively, but only when potential offchannel aquatic habitat was sacrificed for mainstem habitat. When offchannel, spring-fed habitat was provided, the value of spring water to the main channel decreased. Our findings suggest that source water thermal quality is of paramount importance for enhancing ecosystem function and improving cold-water habitat in working landscapes. In addition, the restoration of a historic spring channel may provide added ecosystem benefits by enhancing aquatic habitat for cold-water species. In the western United States, understanding the best possible uses for high-quality cold-water sources may provide the greatest benefits to the environment and adjacent working landscapes. Whereas water purchases and leases tend to focus on water quantity, this study could direct such investments toward higher value sources for the environment. In places like California, where drought has resulted in water right curtailments for agricultural diverters, understanding the best uses for high quality cold water compared with other sources can provide the greatest benefits to both agriculture and the environment. [ABSTRACT FROM AUTHOR]

In this study, the usability of recycled concrete aggregates (RCAs) together with crushed aggregate (CA) in granular road base (GRB) and granular road subbase (GRSB) layers was investigated. Three different RCAs as RCA1, RCA2, and RCA3 were used according to their parent concrete compressive strength. The performance of the designs created by mixing three different RCAs with CA at 25%–50%–75% by mass was examined by laboratory tests [modified Proctor, California bearing ratio (CBR), permeability, resilient modulus, and plastic deformation]. CBR values for pure RCAs were higher than 100% and the CBR values were decreased for the mixture designs. Permeability coefficient (k) values of the CA and RCAs were close to each other. Resilient modulus (Mr) values were evaluated for three different models. In general, the lowest Mr values were obtained for pure RCAs, while the highest Mr value was obtained for pure CA. There was no statistically significant correlation between Mr values and CBR values. The plastic deformation (εp) value of the pure CA was significantly smaller than the εp values obtained for the pure RCAs and mixture designs. The RCAs generally increased the εp values. Flexible pavement thickness and cost analyses were performed for the 50CA 50RCA2 design, which was determined to be the most suitable for GRB material, 100RCA2, and 100CA designs for comparison. The 50CA 50RCA2 design reduced the GRB cost by 13% compared to using pure CA. As a result, it was determined that 50% RCA in GRB reduced the cost and had no adverse effect considering the material properties. Recycling of concrete wastes in this way can make significant contributions to reducing environmental pollution and prevent the depletion of natural resources. [ABSTRACT FROM AUTHOR]

Promoting the utilization of solid wastes such as mineral waste residue in highway engineering is a meaningful way to accelerate the development of green highway construction and to reduce environmental pollution caused by waste residue stacking. To comprehensively evaluate the engineering properties of waste argillaceous gangue–filled subgrade and recommend reasonable construction parameters, the effects of parameters such as moisture content, compaction work, and coarse grain content (CGC) on the engineering properties of waste argillaceous gangue were compared in this study. A multiobjective comprehensive evaluation model based on grey relational degree (GRD) and principal component analysis (PCA) was constructed, and the reliability of the model was verified. The results showed that the mechanical properties of argillaceous gangue are sensitive to various influencing factors. With increased coarse particle content, unconfined compressive strength (UCS) first increased and then decreased, while resilient modulus and California bearing ratio (CBR) gradually increased. The impact of compaction work on different mechanical properties was noticeable. When calculating the comprehensive GRD, the weights of UCS, CBR of unsoaked samples, CBR of soaked samples, and resilient modulus were 0.203, 0.318, 0.278, and 0.201, respectively. The comprehensive performance prediction model can be effectively applied to evaluate the correlation between technical parameters and engineering properties of argillaceous gangue, and the fitting degree reached 98.21%. The model provides a scientific basis for engineering design and construction parameter optimization of subgrade filled with waste argillaceous gangue. [ABSTRACT FROM AUTHOR]

This study investigated the different geotechnical characteristics of soil stabilization with the addition of lime and rice husk ash (RHA) in varying amounts (3%, 5%, 7%, and 9% lime, and 4%, 8%, 12%, and 16% RHA). A series of compaction, unconfined compressive strength (UCS), California bearing ratio (CBR), pH, and X-ray diffraction (XRD) tests were performed in the laboratory to assess the impact of the considered admixtures on the stabilized soil parameters. This study also proposes the successful integration of an artificial neural network (ANN) and a Gaussian process regression (GPR) with the experimental UCS observations. The lime concentration, RHA concentration, and curing period were considered as the input parameters, and UCS was considered as the response. The proposed framework was extended to analyze the compressive behavior of treated soil on the minuscule level. Such coupled machine learning-based experimental investigation can provide deep insight into the soil behavior which otherwise would have remained unexplored due to the prohibitive nature of performing laboratory experiments on a large scale. The findings demonstrated the effectiveness of RHA in addition to lime in stabilizing the considered expansive soil. With the addition of lime and RHA mix, the UCS and CBR values of the treated soil increased significantly. [ABSTRACT FROM AUTHOR]

This manuscript aims to utilize industrial wastes, i.e., ferrochrome slag (FS), ground granulated blast furnace slag, and fly ash to prepare alkali activated cementless controlled low strength material (CLSM). The physical properties, i.e., flowability, bleeding, unit weight, and mechanical properties such as strength, durability, and settlement were assessed for different CLSM mix designs and compared with cement-based FS-CLSM. The alkali activated FS-based CLSM achieved adequate flowability and unit weight with a strength value of 1.72 to 10.44 MPa for different CLSM mix propotions, with a California bearing ratio (CBR) value of 328% to make the CLSM mix a feasible pavement material. The study concludes that a high molar ratio of potassium hydroxide (KOH) accelerates the alkali activation process which helps in the formation of alkaline alumino/calcium silicate hydrates to bind the FS and produce CLSM with adequate strength. The high durability and low levels of toxic metals in the leachate cause the FS-based CLSM environment to be acceptable. Furthermore, life cycle analysis was carried out to investigate the effects of the FS-based CLSM on the ecosystem and human health. The present study aims to utilize a less explored industrial waste from the ferroalloys industry, ferrochrome slag (FS), in preparing controlled low strength material (CLSM) without the addition of cement. The CLSM is prepared by mixing FS with other industrial waste to achieve adequate properties and can be utilized as an unpaved road material or in structural filling. The study concludes that production of CLSM by using FS is economical and safe relative to the environment and human health. Since the developed construction material is prepared by using industrial wastes and without cement, it is an alternative solution to reutilize the industrial waste more efficiently particularly inside and in the vicinity of the industry. Based on the above results, a pilot study is in process to develop and repair the construction works of roads and trench filling in the plant premises and outside in the vicinity of the plant. [ABSTRACT FROM AUTHOR]

When critical infrastructure system services are disrupted, households typically respond by reducing, delaying, or relocating their demand (e.g., delaying laundry), or augmenting supply (e.g., using a generator). While this phenomenon is well known, there has been little systematic empirical investigation of it. Focusing on electric power and water service interruptions and using revealed and stated preference survey data from Los Angeles County, California, we develop 24 mixed logit models, one each to predict the probability an individual undertakes a specified adaptation as a function of outage duration and characteristics of the individual. The analysis aims to determine: (1) how common different household adaptations are; (2) how adaptation implementation varies with infrastructure type, outage duration, and uses of the service; (3) what household characteristics are associated with implementation of different adaptations; and (4) how adaptations tend to occur together. The percentage of individuals who report doing an adaptation varies greatly across adaptations and outage durations, from 2% to 88%. In general, adaptations that require moving out of the home are the least common of those investigated. For electric power outages, adaptations that could be done at home are less likely as the outage duration increases, while those that require going somewhere are more likely as the duration increases. For water outages, all adaptations (except delaying consumption) are more likely as an outage lasts longer. Using electric power or water for medical devices and/or work and business has a large effect on the likelihood of implementing many adaptations. Preevent conservation habits are also associated with an increased likelihood of implementing adaptations. The influence of household characteristics varies greatly across adaptations. There is evidence that some adaptations tend to occur together (e.g., using water from lakes and the government) and others tend not to (e.g., delaying electricity use and going to a hotel). Knowing what kinds of adaptations are found among different segments of the population, how common they are, and when they are likely to be implemented can help policymakers know what sorts of crisis-coping behaviors to expect in their locality, and can help them to know the timeframe in which those adaptations would be implemented. This in turn can provide needed knowledge for how to support those adaptations. Such support could take the form of enhanced contacts and outreach in specific populations (e.g., medically fragile), advance planning (having materials on hand, or including adaptations in drills or exercises), or timely improvising as an event unfolds. [ABSTRACT FROM AUTHOR]

Public institutions are facing natural and manmade hazards of increasing frequency and severity. While the costs of disasters can be greatly reduced when individuals prepare, successfully encouraging preparation is difficult for governments, given the low salience of such risks. We examine whether the increased salience of other types of risks can influence individual willingness to prepare for natural and manmade hazards, and whether message impact varies with recipients' levels of trust in their source. We capitalize upon a rare policy experiment—the staged rollout of COVID-19 lockdowns in California—to assess if increases in the salience of the pandemic were associated with greater willingness to store water for earthquake-induced system outages. We find that experiences of a disaster in a different domain (public health) and higher levels of trust in message source both increase willingness to store water. This suggests that public agencies should encourage preparedness during actual emergencies, or "not let a crisis go to waste." [ABSTRACT FROM AUTHOR]

Past research has shown that households living in manufactured housing have outsized exposure and vulnerability to multiple climate-related hazards, including floods, tornadoes, and hurricanes. Yet, few studies have specifically analyzed the risk of hot and dry climate change-induced hazards, such as extreme heat and wildfires, on households living in manufactured housing. In this study, we first use national American Housing Survey data to provide background context on the adaptive capacity to these hazards among manufactured home occupants nationally. We then focus our primary analysis on California, where the prevalence of such hazards is growing substantially due to climate change. We compile a unique, census tract-level data set of occupied housing unit characteristics by tenure status, along with extreme heat and wildfire hazard measures. We also incorporate address-level locations of mobile home parks in the state. We use descriptive statistics, t-tests, and bivariate correlations to compare the exposure for households in manufactured housing with renter and owner households residing in other housing structure types. We find that households in manufactured housing face consistently higher exposure to heat and fire hazards across all exposure measures. Census tracts with higher proportions of households in manufactured housing are much more likely to be located in areas with greater historical and projected extreme heat hazards than households living in other lower-cost housing types or households in general. Households in manufactured housing are also the most likely of all housing types to be located in tracts affected by past wildfires and in tracts with high future wildfire risk. We conclude by providing recommendations for future research and policy consideration. [ABSTRACT FROM AUTHOR]

This study examines how prior relationships between construction industry project teams influence work outcomes. Drawing on social network literature, we theorize that factors like the frequency of partner interactions, resource requirements, and level of competition impact performance. Using a dataset of public infrastructure projects in the State of California, we test how network structures (structural holes and Simmelian ties) affect project performance. Longitudinal network analyses reveal a strong positive effect of cliques on project performance in the construction industry. Even when tested under varying conditions of stress—competition and access to valuable resources—the positive effect of cliques remained intact. This study links the social networking theory to construction cost overruns and shows that cliques between contractors and subcontractors affect project performance. [ABSTRACT FROM AUTHOR]

The evaluation of water systems based on historical statistics is problematic when shifts in the hydrologic system occur due to a changing climate. An explicit link to thermodynamic and dynamic pathways in the climate system that may control water system performance is missing from current operational policies prescribed by regulation manuals within the US. In response, this study contributes an extended version of an existing weather regime (WR)–based stochastic weather generator (SWG) that allows (1) hourly simulation, (2) over the entire year, and (3) with a corrected representation of extremes. A range of climate scenarios is developed to demonstrate the insights that can be gained from linking the impacts of climate change to their thermodynamic and dynamic causal mechanisms, in this case for inflows to the Don Pedro Reservoir within the Tuolumne River Watershed of California. Application of the WR-SWG and water system modeling chain shows that the magnitude of flood events can be heavily influenced by antecedent hydrologic factors such as snow water equivalent (SWE) and soil moisture. Our results suggest that, under all climate change scenarios, SWE decreases as temperature increases and contributes more (sometimes up to 2.5 times more than the baseline) inflow as part of rain-on-snow events. The monthly reservoir inflows show the potential to cause extreme floods as the average rate of inflow increases by up to 80% with temperature increases, whereas SWE tends to increase by 50%, adding water to the stream during the high flow season. In addition to the temperature increase, if the water-holding capacity of the atmosphere increases with Clausius-Clapeyron scaling, reservoir inflows are projected to increase. This provides insight for risk-hedging policies: winter storm and spring snowmelt release and storage decisions that drive flood and drought risk, respectively. [ABSTRACT FROM AUTHOR]

Automated vehicle (AV) technology is expected to make roads safer. However, until recently only a handful of studies could test such hypotheses due to limited access to testing data. This study contributes to the literature by jointly analyzing the associated factors of three interrelated outcome variables--vehicle at fault, collision type, and injury outcome in AV-involved crashes. We use Bayesian networks to analyze the manually extracted data from reports of 333 AV-involved crashes that occurred in California between January 2017 and October 2021. The summary statistics indicate that rear-end collisions are the dominant (63.5%), while AVs are at fault for a small proportion of crashes (14.4%), and a majority of crashes (84.4%) are noninjury. The joint inferences of the Bayesian networks show that irrespective of the collision type, when the AV is at fault, the chance of the physical injury in a crash increases significantly. Further, the chance of an AV being at fault seems higher in parking locations, and during driving at wet pavements in unclear weather. The chances of AV rear-end collisions are lower in the parking lot, and when nonvehicular participants are involved but increase in high traffic flow roadways. We also find that the likelihood of physical injury is higher at high-speed locations, intersections, and wet pavements. These insights suggest specific areas (unsignalized intersections, less structured right-of-way rules, and wet pavements) where technological improvements could enhance the safety performance of AVs. [ABSTRACT FROM AUTHOR]

Bridges in earthquake-prone states like California have been studied for near-field and far-field loadings. However, there is a research gap in terms of how an earthquake of a certain strike, dip, and rake is going to influence the bridge response. Here, we focus on multispan continuous concrete single-frame box girder bridges. In this study, we simulate earthquakes of varying focal mechanisms and perform nonlinear dynamic analysis of bridges with the synthesized ground motion. Furthermore, the influence of azimuth orientation with respect to the source is studied by placing the bridge model a few kilometers from the source at certain azimuths motivated by the radiation pattern of seismic waves. Fixing a magnitude, depth, and reference focal mechanism angles determining a focal mechanism is varied to study the effect of strike, dip, and rake on the bridges. In each of these cases, the potential risk is identified, and the study underscores the need to include these focal mechanism parameters into bridge fragility computations in risk assessment platforms such as HAZUS. [ABSTRACT FROM AUTHOR]

Compared to linear analysis approaches, nonlinear analysis of bridge models under large seismic demands has enabled more realistic prediction of global and local responses. However, the sensitivity to modeling assumptions, element and material formulations, software-dependent implementations, and parameter selection may lead to variable results between nonlinear analysis software packages. While previous work has led to a better understanding of how to model nonlinear static response of bridge components and systems, seismic loads and the corresponding material hysteresis introduce additional sources of variability in the nonlinear response. Two ordinary standard bridges in California were analyzed using simplified steel and concrete constitutive models in concentrated plasticity elements for the columns and nonlinear gap-link springs for the abutments. The models were implemented in SAP2000 and OpenSees and calibrated to achieve common material, section, and element-level nonlinear static responses. Subsequently, the models were extended to seismic excitation with common unloading-reloading rules for the material models as well as common definitions for damping and mass. Analysis results showed consistent drift, base shear, and moment-curvature response histories between the software packages. However, the nonlinear seismic response sensitivity for alternative column hinge formulations and abutment models should be investigated in future studies. [ABSTRACT FROM AUTHOR]

Base isolators and fluid viscous dampers are viable protective devices that have been commonly considered in the seismic protection of civil engineering structures. However, the optimal design of these devices remains a tedious and iterative undertaking due to the uncertainty of ground motions, the nonlinear behavior of the structure, and its change of dynamic characteristics (i.e., effective stiffness and damping ratio) under each new design. The optimal design problem becomes more challenging concerning a multiresponse bridge system where conflicting damage potential is often expected among multiple bridge components (e.g., column, bearing, shear key, deck unseating, foundation). In this respect, this study develops a risk-based optimization strategy that directly links the expected annual repair cost ratio (ARCR) of the bridge to the design parameters of base isolators and fluid dampers. This strategy is achieved by devising a multistep workflow that integrates a seismic hazard model, a design of experiment for bearings and dampers, a logistic regression towards parameterized component-level fragility models, and a bridge system-level seismic loss assessment. The developed ARCR is parameterized as a convex function of the influential parameters of seismic protective devices. As such, optimal bearing and damper designs can be pinpointed by directly visualizing the global minimum of the parameterized ARCR surface. The optimal design is carried out against a typical reinforced concrete highway bridge in California that is installed with the fluid dampers and three types of widely-used isolation bearings—the elastomeric bearing, lead-rubber bearing, and friction pendulum system. It is shown that optimal design parameters can be obtained to significantly reduce the expected ARCR of the bridge, whereas combining optimally designed bearings and dampers can provide the minimum seismic risk. [ABSTRACT FROM AUTHOR]

Soils in the San Joaquin Valley of California have been a source of selenium (Se) release through dissolution into agricultural drainage, requiring treatment before discharge to the environment. A full-scale primarily anaerobic, granular activated-carbon (GAC) bioreactor with an empty bed contact time ranging from 3.4 to 5.0 h was fed 757 L/min of second-pass agricultural drainage water (ADW) at the San Luis Demonstration Treatment Plant (SLDTP) in Firebaugh, California, for 1,062 days. This study summarized startup of an actual water treatment plant with a process scheme that had never been designed or operated at this scale. ADW nitrate (NO3−) and dissolved oxygen (O2(aq)) concentrations largely dictated the externally dosed carbon (EDC), or glycerin dose, which served as the electron donor to achieve selenate (SeO42−) reduction to elemental Se (Se0). Total Se (SeT) influent concentrations between 111 and 332 μg/L were treated to average effluent SeT concentrations of 7.4 μg/L across the bioreactor. Bioreactor effluent SeT concentrations were further reduced across a downstream ultrafiltration membrane system (UFMS) to an average permeate SeT concentration of 2.9 μg/L. It was determined that most of the SeT removed from the ADW was retained on the bioreactor GAC and was not amenable to removal through backwashing, rendering it hazardous waste by both California and federal standards. Removal of other trace metals such as chromium and uranium were investigated. [ABSTRACT FROM AUTHOR]

Efficient utilization of problematic soils such as soft clay by imparting additional strength using various stabilization techniques is done to improve soil properties. The application of nanomaterials in the area of soil stabilization has great potential to create a stiff skeleton, especially when blended with cementitious materials. Using the response surface method, this study focused on studying the effects of single and blended cementitious systems, comprising cement (0% to 20%), slag (0% to 20%), and nanosilica (0% to 2.4%), on the properties of soft clay in wet conditions [water-to-soil ratio (w/s) of 53% to 87%]. The mechanical [California bearing ratio (CBR), unconfined compressive strength up to 91 days] and durability (freezing-thawing durability factor) properties of stabilized clay were investigated, and the bulk trends were corroborated by thermogravimetry and microscopy analyses. Based on statistical analysis, incremental addition of cement, slag, and nanosilica led to the systematic increase in the properties of soft clay, albeit to different extents and with different mechanisms. At the low w/s (53%), superior mechanical and durability properties were obtained for soft clay stabilized with the ternary binder comprising cement, slag, and nanosilica. Numerical optimization showed that stabilizing this weak type of soft/expansive clay is possible, but the results (proportions, performance, cost) varied based on the target design criteria and application. [ABSTRACT FROM AUTHOR]

Water-resources planners use regional water management models (WMMs) to identify vulnerabilities to climate change. Frequently, dynamically downscaled climate inputs are used in conjunction with land-surface models (LSMs) to provide hydrologic streamflow projections, which serve as critical inputs for WMMs. Here, we show how even modest projection errors can strongly affect assessments of water availability and financial stability for irrigation districts in California. Specifically, our results highlight that LSM errors in projections of flood and drought extremes are highly interactive across timescales, path-dependent, and can be amplified when modeling infrastructure systems (e.g., misrepresenting banked groundwater). Common strategies for reducing errors in deterministic LSM hydrologic projections (e.g., bias correction) can themselves strongly distort projected climate vulnerabilities and misrepresent their inferred financial consequences. Overall, our results indicate a need to move beyond standard deterministic climate projection and error management frameworks that are dependent on single simulated climate change scenario outcomes. [ABSTRACT FROM AUTHOR]

In California, daily crop evapotranspiration (ETc) is commonly estimated using near-real-time, standardized reference evapotranspiration (ETo) calculated from ground-based meteorological data and crop coefficient (Kc) values that adjust for the difference between ETo and ETc. However, using ETo calculated from forecast rather than near-real-time meteorological data provides more timely information to growers, farm managers, urban water users, irrigation practitioners, and water purveyors to anticipate water demand for the upcoming days. This is particularly important for water allocation and delivery planning and for irrigation scheduling decisions. Forecast ETo is also relevant for scientific research for developing methods and tools enabling more resource-efficient water use for agricultural production and urban landscapes. Verifying the reliability of ETo forecast models for various climatic conditions is crucial for promoting the broad adoption and use of ETo predictions for weather-based adaptive water management and prospective irrigation scheduling. The US National Weather Service (NWS) has released a product called forecast reference evapotranspiration (FRET) that provides ETo forecasts at a 2.5-km grid resolution for the entire continental US. In this study, comparisons were made between ETo forecasts from FRET and observed ETo values from the California Irrigation Management Information System (CIMIS) for a total of 78 days during the peak irrigation water demand period of 2019, which corresponded to the midseason period for major crops. FRET ETo forecasts and CIMIS ETo observations (calculated from measured weather parameters) were compared for 15 CIMIS station locations to represent a variety of weather conditions of some major agricultural production and urban areas in California. Air temperature, dew point temperature, wind speed, and solar radiation data were collected from NWS and CIMIS and analyzed to assess the accuracy of predicted weather variables and FRET ETo forecasts. The FRET data consisted of 1, 3, 5, and 7-day forecasts of weather parameters and calculated ETo values; these were compared with the corresponding observed daily weather and ETo data from CIMIS in order to statistically evaluate FRET performance. The comparison among forecast and measured weather variables revealed a good match for maximum air temperature (R2 between 0.98 and 1.00), minimum air temperature (R2>0.91), dew point temperature (R2 between 0.7 and 1.00), and wind speed (R2 between 0.66 and 0.99); less accurate results were obtained for solar radiation (R2 between 0.21 and 0.87). The analysis also showed a good correlation between FRET ETo forecast data and observed CIMIS ETo data (R2 between 0.93 and 1.00 and root mean square error (RMSE) was less than 1 mm·day−1) for the majority of the selected stations, with some differences that were likely due to the climatic conditions of specific locations. This suggests that FRET ETo forecasts provide reliable information for predicting near-future water demand and improving irrigation water management in California. The comparisons showed a good match for most of the 15 CIMIS stations, and the FRET model may potentially provide accurate ETo forecasts in similar semiarid and subhumid areas elsewhere. Weekly irrigation schedule examples are provided in the Appendix to illustrate the use of FRET ETo forecasts in combination with site-specific information on soil hydraulic properties and irrigation system performance for prospective irrigation scheduling of some specialty crops and urban landscapes. The information provided in this article can help improve the water management efficiency of high-frequency agricultural irrigation systems and urban sprinkler systems in California and other locations with similar climates. It also offers a less expensive method to obtain ETo data in countries that do not have ETo station networks, because it offers an alternative to installing and maintaining ETo stations in agricultural and urban areas where it is difficult to find acceptable surfaces for developing reliable ETo information. [ABSTRACT FROM AUTHOR]

A climatically driven, water system modeling framework that captures a full range of interacting components at necessary spatiotemporal scales was developed for the Southwestern United States, including a detailed representation of California's water supply and demand network, within the Water Evaluation and Planning (WEAP) system. Credibility of the model as a tool for water-energy analysis was garnered through evaluation of the historic regional water balances, including metrics of water supply, water use, groundwater storage, environmental requirements, and the energy use associated with water. The ability of the model to address policy-relevant questions was demonstrated by evaluating the impacts of a future 30-year drought scenario that included a realistic 2°C warming trend through 2050. With drought, the total energy used to supply water decreases by about 3% compared to the historic use, and warming alone reduces overall energy use by a modest 1% due to overall reductions in water delivery. The strongest signal of persistent warming expresses itself in groundwater storage, which decreases by an additional 9% beyond the impact of drought alone. A water conservation scenario was used to demonstrate the response of the water sector to the types of conservation strategies being pursued at local and state levels, with conservation reducing water use by about 10% and energy use by 3% relative to historic levels. Such measures overcome the warming trend, but it is demonstrated that persistent drought challenges groundwater conservation strategies and reductions in energy use by the water sector, leading to further overdraft of aquifers and increased energy use. [ABSTRACT FROM AUTHOR]

Geogrid reinforcement effectively controls the rutting of pavements under traffic loads, especially when constructed over soft subgrades. In this study, extensive large-scale model pavement experiments (LSMPEs) were performed to quantify the rut depths of flexible pavements. In all, 20 LSMPEs were performed on pavement sections overlying subgrades of different strengths with California bearing ratio (CBR) values varying from 1% to 5%. Three geogrid types were considered to study the effects of material type [polypropylene (PP) and polyester (PET)] and tensile strengths (30–60 kN/m) on the rutting behavior of flexible pavements. LSMPEs were first performed under monotonic loading to obtain the optimum depth of reinforcement within the base layer of flexible pavement. Thereafter, a series of repetitive load (haversine loading) was applied on paved sections of reinforced flexible pavements using a high-end, linear, double-acting actuator system. Rut deformations were measured at both the surface and the subgrade levels of the model pavements. The rut deformations were found to distinctly vary in accordance with the condition of the subgrade, the thickness of the pavement layers, and the type of geogrid used. The rut depth reduction (RDR) at the pavement surface was found to range from 22% to 69% for PP- and PET-geogrid reinforced base layers. Geogrid reinforcement significantly reduced the rut depths at the subgrade level (as high as 90%) compared to unreinforced sections. In addition, the model pavements were instrumented with the earth pressure cells to measure the vertical pressures transferred to the subgrade due to surface loading. The ability of geogrid reinforcement to distribute loads to wider areas was quantified in terms of the vertical stress distribution angle, αmax , at the end of the load cycles (N=100,000 cycles). The αmax maximum values for geogrid (GG1/GG2/GG3)-reinforced pavements built over weak subgrade (CBR=1%) varied from 28.4° to 32.2°, while it was 25.7° for unreinforced pavements. Likewise, αmax values for geogrid-reinforced pavements overlying a relatively fair subgrade (CBR=5%) varied from 34.5° to 43.6° against 30.4° for an unreinforced case. [ABSTRACT FROM AUTHOR]

Domain-specific architectures of artificial neural networks (ANNs) have been developed to estimate salinity levels for planning at key monitoring stations in the Sacramento-San Joaquin Delta, California. In this work, we propose three major enhancements to existing ANN architectures for purposes of training time reduction, estimation error reduction, and better feature extraction. Specifically, we design a novel multitask ANN architecture with shared hidden layers for joint salinity estimation at multiple stations, achieving a reduction of 90% training and inference time. As another major structural redesign, we replace predetermined preprocessing on input data by a trainable convolution layer. We further enhance the multitask ANN design and training for salinity forecasting. Test results indicate that these enhancements substantially improve the efficiency and expand the capacity of the current salinity modeling ANNs in the Delta. Our enhanced ANN design methodologies have the potential for incorporation into the current modeling practice and provide more robust and timely information to guide water resource planning and management in the Delta. [ABSTRACT FROM AUTHOR]

Expansive soils are susceptible to ground movements and are problematic to overlying geotechnical structures. There is a growing shift to use nontraditional sustainable and economical alternatives. To date, limited research is available on investigating the reaction mechanism of nontraditional soil stabilization; thus, this research aims to fill this gap in the knowledge. A series of experiments was conducted to assess the mechanical and hydraulic behavior of field expansive soil with the enzyme-based soil stabilizer. Moreover, the reaction mechanism of enzyme soil stabilization was studied using microstructural-driven analytical techniques. The results indicate substantial increase in California bearing ratio, unconfined compressive strength, and resilient modulus with a considerable reduction in permeability with the addition of enzymes into the expansive soil. The enzyme additive is adsorbed by the clay particles, which reflects a reduced affinity for water, an improved density, and a reduced ingress of water within the soil. Adding enzymes causes the expansive clay mineral lattices to relax, as the enzyme stabilizers penetrate the inner layers leading to expansion and subsequent moisture entrapment of the inner layers, emphasizing densification and a reduced affinity for water. The outcomes from the study are beneficial for the understanding of enzyme-based ground improvement to inhibit the expansive nature of reactive soils. [ABSTRACT FROM AUTHOR]

Managing risk in construction projects has proven to be a challenge for many project managers and stakeholders involved in projects. The lack of a systematic approach and standardized processes are key factors influencing improper risk management techniques. This research introduces a new model to evaluate and assess risk in terms of cost impact, utilizing a fuzzy Monte Carlo simulation approach for the first time. The method consists of ranking the top risks using a fuzzy logic system utilized in an objective manner by setting criteria for experts to rank the risk based on cost impact and probability to reduce human biases, then evaluating their cost impact through a Monte Carlo simulation both pre- and postmitigation. This work proposes a new strategy to elicit risk for construction projects based on risk cost impact, project type, project location, project contract type, and project delivery method. Based on the findings, implementation of a risk mitigation response plan can decrease the project cost remarkably. This model proved to be beneficial in forecasting risk impact when executed on a commercial construction project in California. This model can be applied as a general tool for risk mitigation processes for the construction industry. [ABSTRACT FROM AUTHOR]

Vegetation can have an appreciable impact on the hydrodynamics and scour potential in natural rivers, but this effect is generally unaccounted for in high-fidelity computational fluid dynamic models. In this study, we have incorporated trees into the flow domain using two different approaches to study the hydrodynamics of the American River in Northern California under flood conditions. In the first approach, we resolved numerous trees as discrete objects. The second method incorporated a vegetation model into our in-house numerical model to treat the vegetation as a momentum sink along the banks. The flood flow of both cases was modeled using the large-eddy simulation. The computed hydrodynamics results of the cases were compared with a baseline case, which did not include any trees. Although both the tree-resolving and vegetation model approaches compared well with one another with respect to the flow field, they significantly altered the computed river flow dynamics and bed shear stress near the banks and the midwidth of the river compared with that of the no-tree case. Both methods that accounted for the resistance of the trees obtained lower and higher bed shear stresses and velocities along the banks and the midwidth of the river, respectively, than that of the baseline case. This research identified the important role that vegetation plays in natural rivers and provided researchers and engineers with the conceptual tools needed to incorporate vegetation into numerical models to improve the accuracy of the model results. [ABSTRACT FROM AUTHOR]

This study develops the probabilistic seismic response and capacity models for the broad collection of standard pile designs that are routinely incorporated into bridges in California. A review of the state bridge inventory indicates considerable variations in design details for different standard pile types used across multiple eras. For each pile type, fiber-section-based pile models attached with p-y soil springs are built to incorporate nonlinear behaviors of soil materials, a wide array of heterogeneous soil profiles, full-range damage states of piles, and realistic connection details between piles and footings (i.e., pile caps). Moreover, force-displacement responses of pile-soil systems under a large number of pushover analyses are regressed as response models consisting of five parameters [termed as response five parameter (R5P) models], which can capture all essential behaviors of laterally-loaded piles. Capacity damage states and limit state models are defined for different pile types by linking pile global responses to fiber-scale material behaviors at plastic hinge locations. Procedures are further provided to expand R5P models to pile foundation models at the regional scale, taking into account the pile group effect and capacities of pile cap backfills. R5P models for all distinct pile types are further summarized in an Excel workbook to facilitate their practical implementations. In general, this study provides a comprehensive and consistent set of response and capacity models to quantify the seismic damage potential of regional pile foundations, as well as to capture their dynamic interplays with other crucial bridge components, such as columns and abutment components. The proposed pile models are expected to significantly enhance the existing modeling capability toward improved seismic risk assessment of California's bridge infrastructure. [ABSTRACT FROM AUTHOR]

For California water resource planning in the face of climate change, hydrological and water distribution models require inputs of high spatial– and temporal–resolution temperature and precipitation projections. We used a quantile delta mapping (QDM) procedure along with bias correction and localized constructed analogs (LOCA) downscaling to produce 6-km temperature and precipitation fields that preserve the relative changes in these quantities from climate model projections. We developed a wetter moderate warming (WMW) case from the Representative Concentration Pathway (RCP) 4.5 emissions scenario and a dry extreme warming (DEW) case from the RCP8.5 scenario to establish a range of projected hydroclimatological conditions. In both cases, we found that extreme precipitation becomes more extreme, but the sign of changes in moderate precipitation events differs between the two cases. The precipitation estimate range is most broad in southern California, where it varies by a factor of 2 and is 50% across the Sierra Nevada. This approach, adopted by the California Department of Water Resources, balances a host of practical water resource planning considerations with the evolving state of the science for future hydroclimatological projections. [ABSTRACT FROM AUTHOR]

High-fidelity models can simulate many detailed hydrodynamic features of flow in natural rivers. However, it is challenging to explicitly capture the effects of highly complex bathymetry and bank line vegetation on the simulation results of models. Often detailed hydrographic data representing the channel bed is unavailable, requiring the use of more simplified representations of the channel bathymetry. Furthermore, explicit modeling of vegetation is generally not accounted for in most three-dimensional (3D) numerical models, which could lead to significant error in obtaining accurate results. In this study, we have investigated these issues by comparing the effect of (1) different sonar survey resolutions of the channel bed, and (2) trees on the large-eddy simulation (LES) results of a test case in a reach of the American River, California. This comparison has shown that the higher resolution survey reduced the near bed velocities and bed shear stresses and increased the number of vortical structures in areas with highly detailed surface structures. The hydrodynamic results from the tree-resolving LES were compared against a baseline LES case that excluded trees. The results indicate that the inclusion of trees in the simulations can significantly alter the flow dynamics of the river by decreasing the flow momentum and bed shear stress along the banks, while increasing the momentum and stresses in the middle of the river. While trees appear to increase turbulent fluctuations near the bank, these fluctuations probably do not contribute to erosion processes. These findings have the potential to improve the accuracy of high-fidelity modeling of natural streams and rivers and add to the general understanding of the flow dynamics in natural waterways. [ABSTRACT FROM AUTHOR]