World Environmental and Water Resources Congress 2017: Groundwater, Sustainability, and Hydro-Climate/Climate Change

During the cleanup of contaminated sites, it is often required that the health risk to construction/trench workers for exposure to impacted groundwater during intrusive work be evaluated. Regulatory agencies typically publish risk-based soil screening levels for direct contact to soil to facilitate risk evaluation, but rarely provide guidance or screening levels for exposure to groundwater during construction/trench work. While the risks from dermal contact with and incidental ingestion of groundwater can be readily evaluated using classic equations, the evaluation of risk from inhalation of vapor from groundwater is complicated by how airflow in the work zone affects the exposure concentration. Utilizing a groundwater volatilization factor that accounts for the airflow-induced dilution for a trench or excavation of certain geometry, the exposure concentration and then the risk can be easily calculated. This method of evaluation was demonstrated at a former bulk fuel terminal site in the San Francisco Bay region.

In the U.S., Federal guidelines and funding are provided to the states and tribes to monitor coastal recreational waters for pathogens or pathogen indicators to determine instances where pathogens may be present in amounts could be unhealthful for humans. The Florida Department of Health monitors beach waters, and for the period 2002–2011 collected weekly samples which were tested for two indicator species–enterococcus and fecal coliform–at all coastal counties. Beaches were posted with public health advisories when concentrations exceed 104 #CFU/100mL for enterococcus or 400#CFU/100mL for fecal coliform. The objective of this research was to determine whether presence of these two bacteria species in samples of near-shore marine waters is quantitatively associated. The research uses data from 16 Sarasota County beaches for the nine-year period August 2002–June 2011, the longest period for which weekly data are available for both enterococcus and fecal coliform. Results show poor correlation. Only 2 of the 16 beaches showed correlation coefficient R² of 0.70 or better when regressing one of these species against the other, with R² less than 0.35 for 4 of the 16. The 16 beaches showed variation in the number of occasions when the two different organisms were present in such high amounts as to trigger an advisory for bathers. Conclusions demonstrate that correlation of the two varies greatly among beaches, and that for many beaches the correlation between the two species is weak, with the implication that monitoring for either of the two may miss episodes when human-originating bacteria could be present in unhealthful amounts.

The City of Meriden has uncovered and daylighted portions of Harbor Brook, creating a blue-green corridor and park in its downtown area. For over 100 years, Harbor Brook flowed in a degraded open channel through an old industrial neighborhood. The river was dredged, straightened, and hardened; then portions of it were enclosed in a 30-foot-wide concrete conduit in the 1960s under a downtown retail shopping mall parking lot and urban renewal housing. However, the corridor remained subject to flooding, with major events in 1992 and 1996 causing $30 million in damages. In 1997, Meriden engaged Milone & MacBroom, Inc. to inventory and assess the channel, conduct a watershed-scale study, and create a flood management master plan. Extensive hydrologic and hydraulic studies were conducted leading to a comprehensive multifaceted master plan. The recommended strategy included renaturalization of 3 miles of the river and connection to its floodplain, simulating preurban conditions. Specific recommendations touched on 15 bridges, channel and floodplain restoration, daylighting of 1,700 linear feet of river, creation of upstream detention areas, and development of a downtown park with additional in-line water storage.

Groundwater management and withdrawal have gained prominence over recent years coincident with the shortage of surface water and drought occurrence in arid and semi-arid regions as those found in Iran. The Zayahndehroud Basin is located in Isfahan Province and is one of the water-crisis examples in Iran. It is necessary to monitor the spatial changes of groundwater resources as a prerequisite to manage them effectively. This study assesses the spatial and temporal distribution of the groundwater level in the Zayahndehroud employing inverse distance weighting (IDW) and ordinary, simple, and universal kriging over 11years (2002-2013). The accuracy of each interpolation method was compared with the mean absolute error, mean absolute percentage error, mean percent error, root mean squared error, and mean bias error. The spatial zoning maps were drawn by an interpolation method which had the least total error. The results indicate that ordinary kriging in the first and the middle periods, and universal kriging in the ending period were the best groundwater interpolation models. Comparisons of the maps also demonstrate that the level of groundwater has decreased by 10.9 meter over 11 years because of the Zayandehroud Basin drought since 2007 and over-pumping of groundwater.

Many regulatory agencies allow the use of a dilution and attenuation factor in calculating cleanup goals for groundwater discharging into surface water bodies. This is important for coastal aquifers where chemical-containing groundwater from upland areas undergoes dilution within the aquifer near the shore due to mixing with intruded seawater. The cleanup goals developed with or without this dilution factor can be significantly different. This paper provides a modeling method for estimating the dilution factor using the SEAWAT program to simulate the tidally influenced variable-density flow typical in a coastal aquifer. The SEAWAT modeling was conducted at an active marine fuel terminal site near the San Francisco Bay to estimate an effective dilution factor applicable to site monitoring wells. The groundwater cleanup goals were then calculated as the marine surface water cleanup goals multiplied by the effective dilution factor. This was approved by the regulatory agency and expedited site remediation and closure.

Thailand’s changing climate patterns has led to instability and challenges to the people and the nation’s economy. Drought caused by irregular rainfall has become a significant issue in Thailand in the most recent years as the central plain has no large water reservoirs of its own and is currently relying on dams in the lower Northern region for water. Long periods of droughts are impacting rice and other cash crops production. Water scarcity is a global threat that is estimated to hit Thailand hard and the country is in need to develop a long-term plan to deal with these challenges. Effective water management needs to be practiced and conjunctive use of surface water and groundwater is being implemented. This paper aims to use SWAT model for spatio-temporal surface water simulation and the estimation of groundwater recharge rates. Sensitivity analysis, calibration, validation, and uncertainty analysis were performed by SWAT-CUP software. Due to the semi-distributed features of SWAT and the difficulty of calculating groundwater distributed parameters, recharge values estimated by SWAT were used in a MODFLOW model for groundwater simulation at steady and unsteady states. Surface water and groundwater potentials in Sukhothai Province of Thailand were estimated based on aquifer hydrodynamic coefficients from calibrated and validated modeling results. SWAT and MODFLOW models were successfully tested and the results of the combination of the two models were found acceptable.

Coastal aquifers as vital fresh groundwater resources are subjected to coastal flooding due to storm surge and sea-level rise (SLR). Increasing the seawater intrusion volume (SWIV) from both seaward boundary and land-surface can be expected in coastal aquifers as a result of coastal flooding. In the present study, a numerical method using a saturated-unsaturated density-dependent flow and transport code, SUTRA, is employed to understand how such effects can change the groundwater quality of unconfined aquifers. Storm surge simulation shows that SWIV is increased during the coastal storm below the flooded land-surface. However, this increase is a short-term event. Also, existence of topographic depression negligibly enhances the SWIV in comparison with that of no topographic depression. Unconfined aquifers are significantly influenced from SLR as a long-term effect. Raising sea level and occurrence of a coastal storm causes that even an area much farther inland would be at risk of being flooded.

Climate signals recorded in groundwater are difficult to recognize in basins where there has been human impact to the resource. Signals are better recorded in undeveloped groundwater basins where long-term monitoring has occurred. In northeastern California there lies 22,000 km² Quaternary-aged volcanic aquifer system that is largely undeveloped. Based on isotope analyses, groundwater is recharged at volcanic centers of Mt. Shasta, Medicine Lake Volcano, and Lassen Peak, which act as focal points of high elevation snowmelt infiltration that flows 20-50 km in these aquifers before emerging as ~85 m³/s of spring discharge. Groundwater residence times were measure at <30 years. During extended droughts base flow shows 20-50% decrease in volumetric discharge. Furthermore, changes in aerial groundwater storage is captured by inter-annual differences in late summer base flow and records intra- and interdecadal climate cycling. No net long-term change in storage is observed over the past 100 years.

A recent hydrogeological study of the eastern portion of the Hueco Bolson identified three compartmentalized groundwater flow systems separated by major bounding faults and local groundwater divides. From west to east the compartmentalized flow systems include: (1) basin fill deposits near the main basin bounding fault, (2) Paleozoic and Mesozoic strata forming the transitional pediment/mountain province opposite the basin bounding fault, and (3) Permian carbonate rocks forming the western Diablo Plateau. Just west of the basin bounding fault, groundwater in basin fill is slightly saline, moderately evaporated, and ambient temperature. Groundwater in basin fill contains < 5 percent modern carbon and no detectable tritium. On the eastern side of the bounding fault, groundwater in the transitional region is fresh, not evaporated, and isotopically distinct from groundwater detected in basin-fill wells only 200 meters away. A few kilometers east of the main fault but still in the transitional region, groundwater contains bomb tritium and 30 to 50 percent modern carbon. The main basin bounding fault is interpreted to act as a flow barrier for a local groundwater flow cell developing in the middle transitional region. East of the transitional region a groundwater divide separates the Diablo Plateau “compartment” from the compartment identified in the transitional region. Groundwater in the Diablo Plateau has a unique character that is distinct from the other two compartments; it is marginally evaporated, slightly saline, non-thermal, and contains a mixture of modern and older groundwater. These types of complex geological conditions must be considered if models are to account for water budgets and simulate groundwater flow accurately.

Chaotic advection describes a flow field in which velocity variations produce radically different flow paths of fluid particles that are initially adjacent to each other, leading to spreading in laminar flows. This spreading can promote reaction by bringing together reactants that were initially separate. Chaotic advection can be generated in aquifers by employing time-varying injection and extraction of water through wells, which has been shown through numerical simulations to enhance degradation during in situ remediation of contaminated groundwater. Naturally-occurring time-varying flows are also present in aquifers. For example, coastal aquifer experience tidal fluctuations, and aquifers that are hydraulically connected to rivers may have fluctuations in flow due to seasonal variations in river stage. In this work, we use numerical simulations to investigate the presence of naturally-occurring chaotic advection in aquifers. We evaluate the chaotic behavior of time-varying velocity fields that are caused by periodic fluctuations in water levels in ocean or rivers that form the hydraulic boundaries of the aquifer. If chaotic advection exists naturally in these systems, it may create hot spots and hot moments of biogeochemical reactions in the aquifer caused by mixing the background groundwater with the groundwater derived from the influx of surface water.

During in situ remediation of contaminated groundwater, a treatment chemical is injected into the contaminated groundwater to react with and degrade the contaminant, with reactions occurring where the treatment chemical contacts the contaminant. Traditional in situ groundwater remediation relies on background groundwater flow for spreading of treatment chemicals into contaminant plumes. Engineered injection and extraction (EIE), in which time-varying induced flow fields are used to actively spread the treatment chemical into the contaminant plume, has been developed to increase contact between the contaminant and treatment chemical, thereby enhancing contaminant degradation. EIE has been investigated for contaminants that degrade through irreversible bimolecular reaction with a treatment chemical, but has not been investigated for a contaminant governed by reversible reactions. In this study, we investigate the effectiveness of EIE on remediation of uranium-contaminated groundwater. One technique for remediation of uranium-contaminated groundwater is in situ immobilization, which relies on geochemical processes, such as reduction of soluble U(VI) into insoluble U(IV) or sorption of soluble U(VI) to aquifer media. Reactions that govern uranium immobilization are favorable under certain pH values. In this study, we investigate the ability for EIE to facilitate and sustain favorable conditions to immobilize uranium during remediation, and to prevent re-mobilization of uranium into the aqueous phase after active remediation has ended. The simulations in this investigation are conducted using a semi-synthetic model based on physical and chemical conditions at the Naturita former uranium processing site in southwest Colorado. The EIE design is optimized for the Naturita site using the Borg multi-objective evolutionary algorithm.

Groundwater flows through voids and passages that are interconnected within porous media. Some of the pores are referred to as a dead-end pore space within the porous matrix. The presence of dead-end pores creates a “dead zone” where the advective and diffusive characteristics are affected. The exchange processes between the waters in the tortuous movement path of porous media and these dead zones become influenced as well. A method is developed and presented to solve for the influences of dead-end pores in the mass transport problem. The “dead zone” is treated as a finite volume or a zone between two or more obstructions where the constituent/contaminant is transported and/or removed from the dead-end pore.

The finite-difference model SEAWAT was used to model the flow of submarine groundwater discharge (SGD) into the Indian River Lagoon, an estuary in central Florida. The anisotropy ratio was spatially calibrated in the entire domain using four methods: (1) estimation of the root mean square error (RMSE), (2) estimation of the Nash-Sutcliffe efficiency (NSE) index, (3) two-sided t-test, and (4) visual comparisons of measured and model-predicted freshwater equipotential lines below the entire transect. The measured freshwater equipotential lines were obtained by the inverse distance weighted interpolation (IDW) of measured heads at 17 points. Calibration by the RMSE calculation was found to be meaningless since model predictions under or over predicted the annual SGD by 43 to 211% even when RMSE values were small (0.048 m to 0.085 m). The NSE statistic was not reliable when comparisons were made at the 17 measured points. However, adding 18 more points based on the IDW greatly improved the NSE calibration. The results provided by the two-sided t-test agreed well with the visual comparison. It is recommended that the IDW be conducted to obtain a complete distribution of the freshwater equipotential lines prior to conducting statistical analyses. The IDW not only improves the statistical analyses but also provides another calibration tool through visual comparison. Both the two-sided t-test and the visual comparison indicated that good statistical results were obtained when the predominant anisotropy ratio was 100 and values of 10,000 or higher were used close to the lagoon bed.

This study presents a comprehensive analysis of the groundwater recharge in the dams of the northern region of UAE. The study area included dams at Wadi Al Bih, Wadi Tawiyean, and Wadi Ham. A modular three-dimensional. MODFLOW was calibrated and validated to simulate the groundwater flow and recharge from rainfall events. Apart from the ponding area, the recharge coefficient is in the order of 0.2. The recharge efficiency of Wadi Ham Dam calculated as the ratio between the total recharge from the ponding area and the total storage during a specified period is around 47%. The remaining 53% of the water storage is mostly held in the unsaturated zone and some amounts are lost to the atmosphere through evaporation. The recharge efficiency of Al Bih Dam is around 31.4%. The major part of the infiltrated water is stored in the unsaturated zone causing a significant increase in the soil moisture content including the loss to the atmosphere through evaporation from the ponding area. The efficiency of Tawiyean Dam is around 22%.

Arsenic removal from drinking water by co-precipitation with naturally occurring iron is considered a low-cost water treatment option at the household level but its efficiency depends on the concentration of iron as well as other competing phosphate and silicate salts present in water. This study utilizes the available household-level potable water quality data to estimate upazilla-wise arsenic removal efficiency applying a previously developed competitive sorption model. Assuming a neutral pH and no competing anions, for varying arsenic and iron concentration combinations in potable water, a removal efficiency ranging from 6.34% to 100% is estimated. But considering the interference of phosphate and silicate salts the maximum removal efficiency can potentially be reduced to 71.38%. Consequently, the population exposure in Bangladesh to arsenic contamination above WHO guideline value of 10 ppb, which is currently 32.59%, can only be reduced to 27.77% if interference of phosphate and silicate salts are taken into consideration. These estimates show that treatment of arsenic-contaminated water by co-precipitation with naturally occurring iron will only be marginally efficient for Bangladesh given the prevailing groundwater composition.

Groundwater is a repository of various minerals that are essential micronutrients and can aid proper physiological functioning of human body if consumed as drinking water. This study assesses the quality of household potable water in Bangladesh in terms of selected nutrient minerals (Ca, Cu, Fe, Mg, Mn, Mo, P, Ni, K, Se, Na, and Zn) and estimates their contribution to the dietary reference intake (DRI) values for males and females established by the Institute of Medicine. It has been found that drinking water contributes largely to the intake of iron and manganese (median population fulfilling >25% of their DRI values) mainly because elevated concentration of these elements in groundwater in Bangladesh. The contributions of Ca and Mg, the two essential elements for good cardiovascular health, are moderate (>5% and >8% DRI fulfilled for the 50 percentile population in the case of Ca and Mg, respectively) and so are for Na, Se and Cu (each contributing >4% of DRI). The dietary contribution from the rest of the minerals (Mo, K, P, and Zn) is very much marginal.

Many of the existing river-aquifer interaction models available in the literature are very complex with limited applicability in semi-gauged and ungauged catchments. In this study, a simplified modeling approach is presented by coupling the hillslope-storage Boussinesq (hsB) model with the variable parameter McCarthy-Muskingum (VPMM) river flow transport model to estimate the influent and effluent fluxes. The hsB model has the capability to estimate the subsurface flow using the geologic and topographic features of a catchment under limited aquifer data. The VPMM-based rainfall-runoff modeling approach is used to model the spatio-temporal variation of flow depths in a river reach due to continuous rainfall forcing. The flux exchange process is modelled by Darcian approach with the variable hydraulic head between the river stage and groundwater table. This approach is field-tested in a typical reach of the Brahmani River Basin in eastern India.

Eleven wastewater samples from three water reclamation plants combined with nine groundwater samples were analyzed in this study. Three types of micropollutants, entailing organochlorine pesticides (OCPs), polychlorinated biphenyls (PCBs), and polyaromatic hydrocarbons (PAHs), were investigated. OCPs were below the minimum detection limit for most wastewater and groundwater samples, except four wastewater samples from 3AWRP. Chlordane-gamma, chlordane-alpha and trans-Nonachlor were measured in the range of 2.60-7.13, 2.79-8.69 and 1.11-4.95 ng/L, respectively. The PCB concentrations were the below minimum detection limit for all samples, while PAHs were detectable in all twenty wastewater and groundwater samples. Naphthalene, 2-methylnaphthalene, 1-methylnaphthalene, biphenyl, acenaphthene, fluorene, phenanthrene, anthracene, fluoranthene and pyrene, PAHs, were observed in both wastewater and groundwater. The PAH concentrations in groundwater samples were approximately one to one hundred folds lower than those concentrations in the raw sewage samples. Finally, these WRPs demonstrated the ability to remove all organochlorine pesticides and PAH compounds.

This project formulates criteria and methodology for developing salt balance analysis in groundwater basins. The project utilizes a basic approach to account for geological processes including water/rock and water/soil interactions and mineral dissolution as an in situ source of salt loading to groundwater basins. The study applies methodology to a pilot/case study basin in order to demonstrate the summary approach. The case study is performed for the San Fernando Valley Groundwater Basin, a large water supply basin in a heavily urbanized part of the Los Angeles region, where natural salinity contrasts are found across the basin.

In November 2014, the California governor signed the Sustainable Groundwater Management Act (or SGMA), 100 years after the passing of the Water Commission Act of 1914 which established California’s surface water rights system. Effective January 1, 2015, SGMA establishes a new structure for sustaining groundwater and, for the first time, attempts to manage groundwater use in the State outside of the legal courts. While the goal of SGMA is unmistakable, the Act itself provided a clear timetable for implementation along with a mixed bag of useful tools for sustainable groundwater management and conflicting directions which have the potential to stymie implementation. Now two years into the process and facing the first major regulatory deadline, State regulators are scrambling to develop and clarify guidelines and regulations while water agencies and public entities grapple with the implications of the Act, work to overcome differences to form the required governance structures for sustainable groundwater management, and initiate tentative steps towards meeting key sustainability deadlines. In general, SGMA compliance consists of 6 key steps: (1) prioritizing basins; (2) identifying basins in critical overdraft; (3) determining if basin or subbasin boundaries require modification; (4) developing Groundwater Sustainability Agencies; (5) preparing Groundwater Sustainability Plans; and ultimately (6) sustainably managing California’s groundwater basins. Presented herein are summaries of progress made to date relative to complying with SGMA, problems that have arose and solutions suggested, and an assessment of what SGMA implementation will really mean for California as it tries to achieve groundwater sustainability by the year 2040.

Bioretention systems have become common in stormwater management. Bioretention typically requires a large footprint to accommodate required water quality volumes, which may not be feasible in high traffic areas such as ferry terminals, bridges, and other urban areas. Shallow, portable planters with sandy loam and compost were evaluated for zinc and copper retention using synthetic stormwater. The addition of vermiculite, tree bark, and plants (tufted hairgrass) were evaluated. The mass of zinc retained was consistently greater than 90% for both the vermiculite and tree bark systems, and greater than 80% for all planters in every test. Copper and zinc retention varied with each simulated storm event in the control and tufted hairgrass systems. To better understand copper and zinc distribution within the bioretention systems, simulations were conducted in Hydrus 2D. Model simulations showed copper and zinc accumulating near the surface, indicating physical processes are likely the primary mechanism of metal retention in the planters. Our results indicate that shallow bioretention systems, which have a relatively small footprint, effectively retain copper and zinc.

This research presents how Brazilian Law is changing the traditional model of environmental management in public sector, considering sustainable public procurement and the introduction of news paradigms of environmental management. The focus is the exam of new regulation about the use of environmental criteria in public buildings, considering less impact on natural resources and the execution of public policies, notably the national housing policy. The aim is to demonstrate the potential that a different public procurement process has on fostering innovation, new technologies, sustainable practices and materials in public buildings and buildings financed with public funds. This is an exploratory research, which demonstrates that there is a lack of information by public managers about which are the best technologies to be adopted and a vast opportunity in changing the procurement process underpinning the national housing policy.

To better understand how coastline orientation, together with wind direction, plays a role in storm surge height and propagation, we investigated 58 wind-surge events that occurred between the years 1995-2015 near the mouth of Chesapeake Bay, Virginia. We defined and calculated wind angle, and found that the angle between coastline orientation and wind direction directly affects the magnitude of storm surge. Our results provide evidence that the maximum surge height in a wind-surge event is positively related to (1) the percentage of negative wind occurrence and, (2) the absolute value of average wind angle in the surge accumulation period. We recognize that coastline orientation matters to the magnitude of storm surge when storms land from open seas. These results suggest that it is both possible and important to consider coastline orientation when designing protective strategies to address storm surge and flooding damages.

From climate risk assessment to adaptation, model projections of future extreme climate variables are fundamental for planning and engineering at the local level. For coastal infrastructure in particular, climate change adaptation needs the data of site-specific accurate wind analysis to develop a sound design. In this case study, we examine the ways in which GCM projections can be used to develop the design basis for infrastructure under future climate changes. Employing statistical analysis, we verify GCM projections using site specific observations, and quantify how the design value of wind speed would change over time. Our results show that 1) individual GCM simulations underestimate the design values by up to 71.6%, but can be corrected through post-bias correction; 2) design values for low-probability wind events do not have significant temporal changes under future climates, and 3) there are spatial variations in design wind values among different tide gauge locations. These findings help in developing adaptation designs based on GCM outputs.

One of the pressing issues being faced by water industry today is incorporating sustainability considerations into design practices. Water treatment, an indispensable step for safeguarding public health, is an energy-intensive process. Changing climate, carbon emissions, and rising energy costs are some of the issues that warrant exploring alternate energy sources for achieving sustainability goals of water treatment systems. The goal of the current study was to determine the feasibility of using photovoltaics (PV) as a source of energy generation for an existing drinking water treatment plant (DWTP). The selected 10 MGD plant, located in the southwestern U.S., treated groundwater by primarily using filtration and chlorination processes. Based on the energy consumption, individually determined for each unit process of the DWTP, the DWTP was sized for distributed PV and the subsequent reduction in carbon emissions was computed. Results showed that the dependency on the traditional electric grid of a DWTP can be greatly reduced by the potential use of solar PV.

Unsafe drinking water is a major cause of disease in developing countries. Lack of adequate water treatment and delivery infrastructure, high operational costs and poor maintenance are some of the factors contributing to the problem. Many developing countries also have large population clusters in cities and inadequate sanitation services, which increase the risk of water-borne disease outbreak. Incorporating renewable energy sources for treatment and distribution of potable water may be the key to developing sustainable water supply systems to reduce water-borne diseases in developing countries. This study focused on evaluating the potential of using distributed solar for a 4.5 million gallons per day (MGD) existing drinking water treatment plant (DWTP), located in Sindh, Pakistan. The DWTP utilized a conventional treatment train, consisting of coagulation, flocculation, sedimentation, filtration and disinfection processes to treat water obtained from the Indus River. The DWTP was sized by designing the various unit processes involved and then the energy consumption associated with each unit process was determined. The results showed that the energy consumption was largest for the flash and rapid mixers. Existing land holdings were sufficient for the deployment of solar photovoltaics (PV) which was successfully incorporated into the design of the DWTP.

There is an increasing regulatory requirement in the Northwest United States to implement green stormwater infrastructure (GSI) as a means to manage rainfall, decrease long term maintenance costs and lower pollution in water bodies. The West Eugene EmX Extension (WEEE) project has embraced GSI principles and practice and enhanced stormwater quality by using green infrastructure along its 9 mile round trip bus rapid transit (BRT) system route. In this multi-agency jurisdiction and federally funded project, the design team incorporated comprehensive stormwater requirements of the Oregon Department of Transportation (ODOT), the City of Eugene and the U.S. Army Corps of Engineers (U.S. ACOE) while also implementing an infrastructure voluntary evaluation sustainability tool (INVEST) rating system to certify the sustainability of the project design. Nearly 1,500 linear feet of infiltration street-side planters and seven bioretention raingardens were designed to provide treatment for roadway runoff. A unique bioengineering approach was developed to provide bank protection and slope stabilization for the two pedestrian bridges in the project. Construction started in early 2015 and is scheduled to finish by Fall 2017. This paper discusses design approach, challenges and advantages of using green infrastructure in high density mass transit projects and how this can benefit the community and environment.

Regulated rivers worldwide are managed to meet human water demands, but resulting flows often fail to support hydrogeomorphic processes and other downstream ecosystem needs. This failure is highlighted in California’s Sacramento-San Joaquin River Watershed where complex and decentralized water management regimes confound efforts to balance co-equal management goals of supplying agricultural and urban water demands with maintaining ecosystem functioning. As California struggles to meet competing demands for scarce water, water managers are increasingly required to provide environmental flows in the right place, at the right time, and in the right amount. We present the framework for getting “more pop per drop” in environmental flow management by focusing on a ‘functional flows’ approach, which emphasizes process-based hydrograph components to guide management of regulated river systems. Key flow regime components like peak magnitude flows, dry-season low flows, wet-season initiation flows, recession flows, and interannual variability are indexed against key history strategies of focal species such as salmonids and other native fishes. These framework principles are a guide to selecting hydrograph components, acceptable ranges of variability, and meaningful flow portfolios to meet ecosystem needs. While the Sacramento-San Joaquin River offers an important use case, application of this framework, which connects natural flow regime components to specific biophysical riverine functions, can inform water resource management strategies and environmental flow requirements globally. This is important because hydropower dams are expected to more than double over the next 15 years globally, and thus water management strategies that balance ecosystem needs with human demands are urgently needed.

This paper evaluates the future sea level trend near Miami, Florida. A time span of 100 years is used as the basis for the assessment. The method for the 100-year forecast is based on linear and nonlinear extrapolations of historical sea level data from the national oceanic and atmospheric administration (NOAA) tides and currents database. The NOAA tide gage stations utilized are Miami Beach and Key West, in Florida. The expected rate of sea level rise near Miami, Florida for the next 100 years is postulated. In addition, the forecast sea level is compared against recent predictions by U.S. Army Corps of Engineers (USACE), National Research Council (NRC) and NOAA which account for different acceleration rates on the change of global mean sea level due to changes in the shape of ocean basins, total mass of water and water density.

The present study proposes a statistical downscaling (SD) approach to represent the linkages between global scale climate predictors and daily precipitation processes at many local sites concurrently. This SD method is based on a combination of two multiple regression models for describing precipitation occurrences and amounts and on the use of the Singular Value Decomposition technique for modelling the stochastic components of these two models. The feasibility of the proposed procedure was assessed using the NCEP/NCAR re-analysis data and the daily precipitation data from a network of 10 raingages located in the Quebec-Ontario region (Canada). Results of this application have indicated the ability of this SD approach to reproduce accurately the observed statistical properties of daily precipitations, and the temporal-spatial dependence and intermittency of the underlying precipitation processes. The proposed SD tool can be used for assessing the climate change impacts on daily precipitations at many different sites over an area of interest.

In 2016, the Federal Highway Administration (FHWA) completed an effort to provide new design guidance for engineers and designers of hydraulic structures, drainage facilities, and highway encroachments that incorporates the best actionable climate science and risk assessment approaches. The new guidance is known as Hydraulic Engineering Circular Number 17 (HEC-17) “Highways in the River Environment–Floodplains, Extreme Events, Risk, and Resilience.” This paper summarizes selected features of the guidance including the incorporation of the uncertainty associated with hydrologic data and models into hydrologic design. Specifically, the paper describes the use of confidence limits to build more resilient infrastructure and how to incorporate climate change into hydrologic design within a framework of different levels of effort that depend on the nature of the project. Example computations are provided to illustrate key concepts.

An estimate of the 72-hour basin-averaged maximum precipitation was calculated for five watersheds in the southern region of the Sierra Nevada in California using a physically based atmospheric model. First, the weather research and forecasting (WRF) model was calibrated and validated using the climate forecast system reanalysis (CFSR) dataset from October 1979 until September 2015 for the five watersheds. Then, using the reconstructed precipitation data, maximum 72 hour precipitation events were selected for each year and for each watershed. Given that all of the storm events selected were caused by a narrow high-moisture atmospheric belt coming from the Pacific Ocean, called atmospheric river (AR), the boundary conditions of the CFSR dataset were then shifted in order to maximize the contribution of the AR for each event over each watershed. For all cases, the shifting that caused the maximum precipitation was done in the negative meridional direction meaning that the center of the storm was shifted to the south from the original boundary conditions. The maximum value obtained after the boundary conditions shifting surpassed the original storm 72-hour precipitation, increasing its value between 102% and 227% for all five watersheds. The watersheds analyzed in this study correspond to the Stanislaus River, the Tuolumne River, the Merced River, the Upper San Joaquin River, and the Upper King River.

Estimating maximum precipitation (MP) over a watershed is a necessary process to estimate maximum flood which is used in the planning and design of dams. Major storms in Northern California are caused by so called atmospheric rivers (ARs), which are narrow, but rich moisture atmospheric flows from the tropics. To estimate the MP over the Shasta Dam Watershed (SDW), the atmospheric boundary condition shifting (ABCS) method was employed, which shifts atmospheric boundary conditions of a regional atmospheric model in space in order to optimize the path of an AR that historically hit Northern California to maximize precipitation by that AR over SDW. Before the applications of the ABCS method, the historical dataset over SDW was created by the weather research and forecasting model with the Twentieth Century reanalysis version 2C dataset for 159 years, and we identified the most severe event in each year with respect to 72-hour basin-average precipitation. This presentation shows the preliminary results obtained by shifting boundary conditions with respect to latitude only. Compared with the historical conditions of the selected severe storm events, the results showed an increase in the 72-hour basin-average precipitation by 31% on average for all years. With respect to the largest 72-hour basin average precipitation, the largest depth was obtained as 187 mm in 1888 after the shifting, while the largest historical precipitation depth was 172 mm in 1965. Since the proposed approach is promising for future applications, it can be used as a scientific baseline in implementing adaptations by local agencies.

Future climate conditions will likely not resemble historic conditions, creating long-term planning challenges for agencies responsible for water supply and flood control. To help facilitate long-term water resource planning, we compiled climate change projections for the Santa Clara Valley in California. By using an ensemble of 10 climate models, we capture some of the uncertainty in future projections and assess changes in precipitation, temperature, and surface runoff for the 2025-2054 period. We use the surface runoff estimates to calculate inflows to local reservoirs that serve as an important component of the regional water supply system. We find model consensus for wetter winter conditions, which drives increases in wet year reservoir inflows. Changes in dry year inflows show insignificant changes with the future projections, at least for the early-to-mid 21st century examined here.

Recently, the frequency of extreme rainfall event has increased due to the climate change and the impermeable area in an urban watershed has also increased due to the rapid urbanization. Therefore, the flood risk is increasing and we ought to prepare countermeasures for flood damage reduction. For the determination of appropriate measures or alternatives, firstly, this study estimated the frequency based rainfall considering the climate change according to the each target period (reference: 1971~2010, Target period I: 2011~2040, Target period II: 2041~2070, Target period III: 2071~2100). Then, estimation of expected flood damage in Seom River Basin using MD-FDA. As a result, Minimum and maximum of estimation flood damage are 0.11% and 1.19% when using RCP 4.5 scenario. Also minimum and maximum of estimation flood damage are 0.36% and 1.69% when using RCP 8.5 scenario. Therefore, we may need prepare structural and nonstructural measures for minimizing the future flood damage by predicting the flood damage caused by the climate change.

The physical upper bound of precipitation, referred to as the maximum precipitation (MP), was estimated over the American River Watershed in Northern California under future climate conditions by means of a physically-based regional atmospheric model. Severe storm events over ARW are mainly caused by an atmospheric river (AR) which is a high-moisture atmospheric flow coming from the Pacific Ocean. Thirteen future climate projections from two general circulation models (GCMs: ECHAM5 and CCSM3) based on four IPCC SRES future climate scenarios (A1B, A2, B1, A1FI) were utilized to obtain climate conditions for 90-year future period from 2010 to 2100. After dynamically downscaling the 13 future climate projections by means of the regional atmospheric model, first, the most severe storm was identified for each year for each projection. Then, the 1,170 (13 projections x 90 years) identified severe storm events were maximized with respect to 72-hour basin-average precipitation over the ARW by shifting atmospheric boundary conditions of the regional atmospheric model in space with respect to latitude and longitude. This maximized method is called the atmospheric boundary condition shifting (ABCS) method. This presentation provides some preliminary results of the MP estimation with the ABCS method over the ARW.

Precipitation over Northern California under future climate conditions was obtained by dynamically downscaling IPCC CMIP5 future climate projection realizations. Six different future climate projection realizations from three general circulation models (GCMs: CCSM4, HadGEM2ES and MIROC5) based on two CMIP5 future climate scenarios (RCP4.5 and RCP8.5) were dynamically downscaled at 9 km resolution grids over eight study watersheds in Northern California for a period of 90 water years (2011 through 2100) by means of a regional climate model, the weather research and forecasting (WRF) model. Before investigating future climate change impacts based on the projections, model biases were corrected by comparing the dynamically downscaled precipitation based on the historical runs of the GCMs with the corresponding observations. The bias-corrected results were used to calculate basin-average precipitation over the eight study watersheds. Here some results of basin-average precipitation over the eight stud watershed are presented.

Fitting probability distributions to data is important in hydrology, where one seeks to select a distribution that suits an observed data set well. Several distributions are available, some of which fit the data more closely than others. There is a need for comparing methods of discrimination between competing models, which differ in their ability to select the correct distribution from a group of alternatives. It is useful to compare the various methods, with a focus on discrimination between commonly used hydrological frequency models. We aim to address this practical problem. We will suggest some discrimination statistics (DS) and give recommendations concerning their ability for correct model selection. These DS include the ratio of maximized likelihood (RML) statistic, closely related to the akaike information criterion (AIC) and the bayesian information criterion (BIC). We will also include goodness-of-fit (GoF) statistics such as the Anderson-Darling DS, the “modified Shapiro-Wilk” DS, and the probability plot correlation coefficient DS. Despite the importance of 3-parameter distributions in hydrological practice, comparisons of discrimination tests between them have been limited. For this reason, our focus will be on 2-parameter models, to which many discrimination studies have been consecrated. Such models are frequently employed in the peaks-over-threshold (POT) approach to analyzing hydrological extremes.

We used the peaks over threshold (POT) approach to analyze the seasonal behavior of flood frequencies extracted from daily streamflow records of a group of hydrometric stations in Eastern Canada. For each record, we analyzed the distribution of the times of occurrence of flood flows above a threshold. The aim was to achieve a seasonal portioning of the year based on the time distribution of flood occurrences. It may be possible to assemble stations that are similar in their flood seasonality into geographical regions that exhibit some homogeneity. This broadly provides “homogeneous regions based on seasonality”. The number of significant “seasons” and the dates of beginning and end of each season jointly characterize the seasonal behavior of floods in a homogeneous region. We will provide examples of graphical analyses that help identify the seasons from a hydrometric record. The most important graph is based on plotting the mean number of exceedances in the time interval (zero, t] as a function of increasing t from zero to 365 days. One diagram may combine several plots for a number of threshold levels. Regional flood modeling based on grouping catchments with similar seasonal flood behavior should help reduce the uncertainty in flood forecasts at individual flood sites.

Dynamic interactions of atmospheric and hydrological processes result in large temporal and spatial changes of storm events in precipitation and wind speed in coastal regions of current and future climates. This can impact the design and sustainability of water infrastructure and other environmental assets. We have examined the nature of this challenge and explored the feasibilities of determining future design basis at the U.S. eastern coastal sites. Long-duration historical precipitation datasets, along with wind records, at 14 local USHCN stations are analyzed. Design storm values are determined using sliding time window of the 30-yr and 50-yr duration. The results are compared with the Atlas-14 precipitation design curves and with the design storms derived from the downscaled CMIP5 daily precipitation datasets (1950-2000). We show that Atlas-14 design charts, mostly based on pre-1990 data, describe well the design storms of the past, but not for recent years of high-intensity precipitation. The 132 CMIP5 climate models and their ensembles also under-estimate the design storms. Similar bias is found in design wind speeds from AOGCM outputs. Based on these results, a post-bias correction procedure is proposed for developing design storm values from CMIP5 and AOGCM projections.

The transportation engineering approaches to climate resiliency (TEACR) study is a federal highway administration initiative to broaden the understanding of climate change impacts on infrastructure design. One TEACR case study was an investigation into the impacts of wildfire and changing climate on the design of hydraulic infrastructure. Wildfire and the related hydrologic impacts represent an increasing risk to infrastructure due to land management practices and changing climate. Trends in wildfire have had a significant upward trend since the 1960s with increases in wildfire occurrence and fire severity. Post-fire monitoring studies have shown conditions where a 5-year precipitation event produces a 50-year flow event. Our study includes investigation of watershed post-wildfire hydrologic response and post-fire adaptation practices by the U.S. Forest Service. In the TEACR study, an 11-step decision-making framework for evaluating climate change uncertainty and risk in the engineering design process was developed. The process is demonstrated in the context of a sample wildfire analysis for a culvert in Big Thompson Creek Canyon, Colorado. Hydrologic modeling of the wildfire-impacted watershed was performed using theoretical watershed modeling with wildfire and watershed impact research data published by the USGS, the Colorado Wildfire Risk Assessment Program, and the NRCS. Climate change inputs were developed for the study from the Intergovernmental Panel on Climate Change’s CMIP5 dataset. The study concluded with a Monte-Carlo based benefit/cost analysis to determine the recommended approach for the project.

Along with socioeconomic developments, and population increase, natural disasters around the world have recently increased the awareness of harmful impacts they cause. Among natural disasters, drought is of great interest to scientists due to extraordinary diversity of their severity and duration. Motivated by developing a potential approach to investigate future possible droughts in a probabilistic manner based on climate change projections, a methodology to consider thirteen future climate projections based on four emission scenarios to characterize droughts is presented. The proposed approach uses a hydro-climate model (watershed environmental hydrology hydro-climate model; WEHY-HCM) to generate equally likely thirteen future water supply projections. The water supply projections were compared to current water demand for detection of drought events and estimation of drought properties. The procedure was applied to Shasta Dam Watershed to analyze drought conditions at the watershed outlet, Shasta Dam. The results suggest an increasing water scarcity at Shasta Dam with severer and longer future drought events. This study presents an advantage of the future probabilistic structure in drought analysis by providing drought properties of the 100-year and 200-year return periods without resorting to any extrapolation of the frequency curve.

California’s interconnected water system is one of the most advanced water management systems in the world, and understanding of long-term trends in atmospheric and hydrologic behavior has increasingly being seen as vital to its future well-being. Knowledge of such trends is hampered by the lack of long-period observation data and the uncertainty surrounding future projections of atmospheric models. This study examines historical precipitation trends over the Shasta Dam Watershed (SDW), which lies downstream of one of the most important aspects of California’s water system, Shasta Dam, using a dynamic downscaling methodology that can obtain reconstructed climate data at fine time-space scales. The methodology for reconstructing historical precipitation data over SDW started with the coarse-resolution historical 2.5 degrees Twentieth Century Reanalysis Version 2c (20CRv2c) dataset. The weather research and forecasting (WRF) model was then used to produce 159 years of long-term reconstructed hourly precipitation data at a 3 km spatial resolution over SDW. Trend analysis on this data indicated an increase in total precipitation over the study period as well as a growing intensity of extreme events such as 6, 12, 24, 48, and 72-hour storms. These results both inform long-term planning decisions regarding the future of Shasta Dam and California’s water system and validate a methodology that can be used in data-sparse basins around the world.

In arid and semi-arid regions of North West China, glacier-melt, seasonal snowmelt and rainfall are the primary sources of flow in the rivers that originate from alpine areas. Spring and summer peak flow resulting from snowmelt and rainfall, respectively, are the main characteristics of streamflow pattern. Because of the damages caused by the spring and summer peak flow, a better understanding of the streamflow pattern variation under future climate warming is crucial. To analyze the variation of streamflow pattern under climate warming, the Kaidu River and the Manasi River Watersheds in northern and southern slopes of Middle Tianshan Mountains, located in Xinjiang were selected as study areas. These watersheds receive water from water sources in different proportions. A modified hydrological model was forced with metrological data from CIMP5 data set and the streamflow in Kaidu and Manasi River Watersheds were simulated. The results indicate that one-peak-flow pattern is projected to turn to the two-peak-flow pattern in the Manasi River Watershed in the future. The two-peak flow pattern will continue in the Kaidu River Watershed, but the dominant peak flow will shift from summer to spring in future. This study provides useful information for water resources managers to take different actions to reduce damages caused by spring and summer peak flow under future climate warming.

This paper describes impact of flood depth on the transportation system in Houston, Texas. Generally, bad weather simultaneously impacts on derivers, by reducing visibility, and also the conditions of vehicles and roadways. These effects cause reduction speed and increasing density in roadways, so transportation agencies are seeking to integrate (or consider) flood, and whether in general, into traffic operation in order to improve system functionality. It should be mentioned the driver’s behavior is very sensitive to the environment they derive in; for instance in flood situation, some drivers cancel their trip, some other choose another pathway, that is usually longer than normal one and these new decisions will effect on the transportation system indirectly. In this study, the methods that have been used to relate precipitation intensity and flood depth to reduction in speed, are reviewed. Then, considering a case study of Houston, because of the commonness of flood events in that area, flood depth-velocity reduction analyses will be conducted for Highways. The developed curve will be used to link the flood model to a transportation model, which considers the effect of runoff/flood on the transportation parameters. The paper will also report existing curves and techniques to represent operational impact (e.g., possibility, traffic flow volumes) on transportation system.

In this study, the drought contingency plans of reservoir operation rules were developed to mitigate drought risks and satisfy the water demand. Drought contingency plans are the triggering criteria and guideline for initiation and termination of drought response stages and consist of two criteria (standard daily water levels (or volumes) and release rules by five levels of drought response stages; normal water supply, mild water shortage, moderate water shortage, severe water shortage, emergency and water shortage). Five sets of standard daily water volumes are constructed and satisfied the water supply reliability of 95% for water demand at each five level of drought response stages. As a result of application to five multi-purse dams in Nakdong River Basin, it is found that each dam could preserve the high water levels during historical periods and mitigate the past severe drought. However, the future water supply reliability ranges from 99% to 65% depending on AR5 RCP climate change scenarios. It means that the reservoir operation rules are not sufficient and need to modify for future inflow conditions based on the AR5 RCP climate change scenarios.

This study investigated the climate change assessment on water resources with respect to precipitation and flow discharge over five multi-purpose dam watersheds in Nakdong River Basin. From the results of this study, it is found that the inter-annual variability of precipitation and inflow values is quite different among 56 projection. The precipitation and inflow trends toward the end of 21st century are diverse at five target watersheds. In general, precipitation trends are generally increased toward the early (3~4%), mid (8~11%), and the end (11~17%) of 21^st century. The trends of inflow to dams are generally increased toward the early (4~5%), mid (8~11%), and the end (12~18%) of 21st century.

The climate change adaptation program (CCAP) at the Philadelphia Water Department (PWD) is responsible for identifying the most urgent climate-related risks that the utility will face and adaptation strategies to address these risks. Projections for Philadelphia indicate increasing precipitation, which may pose challenges to the operation and management of PWD systems. In order to understand the risks from increased rainfall, the CCAP is applying representative concentration pathway 8.5 (RCP8.5) global climate model (GCM) projections to local precipitation data for use in hydrologic and hydraulic (H&H) modeling applications. The process of applying GCM projections to system models presents multiple challenges. The spatial and temporal resolution of GCM output is often not high enough for direct use in local H&H models. Additionally, GCM output may not accurately reflect observed regional precipitation patterns, presenting further challenges to directly working with the output. This paper will present the approach that the CCAP took to understand the following: (1) the methods available to downscale GCM output for use in H&H models; (2) the accuracy of GCM simulations in representing local precipitation patterns; and, (3) projected increases in precipitation for Philadelphia considering RCP8.5 output from 9 GCMs and a GCM ensemble. Results indicate that projected increases in precipitation under RCP8.5 are significant. While the GCMs fairly accurately simulate average total precipitation values, the models do not accurately simulate local precipitation characteristics, including the intensity and duration of storm events. This inaccuracy, in combination with the finding that there is no one accepted method to downscale GCM output to resolutions appropriate for H&H modeling, implies that the CCAP would have to develop its own method for applying GCM projections to precipitation time series data.

Increasing water demand and the potential for increased occurrences and severity of drought add new challenges for reservoir operation. Drought contingency plans (DCP) aid drought mitigation by providing tools for timely identification of drought and for coordinating temporary operational deviations. However, policy deviations require full risk and uncertainty assessments for approval. This paper proposes a methodology to update the Pine Flat Reservoir DCP originally published in 1992 to include tools to expedite approval of operation deviations. The methodology includes a probabilistic hydrologic hazard approach to estimate current and future risks. The method combines a stochastic weather generator, outputs of global climate models, a hydrological model and a reservoir model in a Monte Carlo simulation framework to generate patterns of hydrologic loads. The method allows the development of unconditional (all possible hydrological events) and conditional (possible events conditioned to current conditions) hazard curves, taking into consideration possible climate change scenarios.

The trend and shift in the seasonal temperature, precipitation and streamflow time series across the Midwest have been analyzed, for the period 1960-2013, using the statistical analyses (Mann-Kendall test with and without considering short term persistence (MK2 and MK1, respectively) and Pettitt test). The paper also utilizes a relatively new approach, wavelet analysis, for testing the existence of trend and shift in the time series. The method has the ability to decompose a time series in to lower (trend) and higher frequency components (noise). Discrete wavelet transform (DWT) has been employed in the present study with an aim to find which periodicities are mainly responsible for trend in the original data. The combination of MK1, MK2, and DWT along with Pettitt test hasn’t been extensively used up to this time, especially in detecting trend and shift in the Midwest. The analysis of climate division temperature and precipitation data and USGS naturalized streamflow data revealed the presence of periodicity in the time series data. All the incorporated time series data were seasonal to analyze the trends and shifts for four seasons-winter, spring, summer and fall independently. D3 component of DWT were observed to be influential in detecting real trend in temperature, precipitation and streamflow data, however unlike temperature, precipitation and streamflow showed decreasing trend as well. Shift was relatively observed more than trend in the region with dominance of D3 component in the data. The result indicate the significant warming trend which agrees with the “increasing temperature” observations in the past two decades, however a clear explanation for precipitation and streamflow is not obvious.

The Colorado River is a critical water resource that has enabled the development of the southwestern U.S. About 85% of the river’s annual runoff volume of originates in the northern half of the watershed, the Upper Colorado River Basin (UCRB). Recently, basin-wide water demand has nearly eclipsed supplies, yet population and associated water demands are projected to significantly increase, with the majority of new demand coming from the municipal and industrial sectors. Simultaneously, climate change is expected to cause earlier snowmelt and peak runoff. With these compounding stressors, continued skillful forecasting of warm-season water resources will be critical to mitigate changing conditions. Snow water equivalent (SWE) at key dates during the late winter and spring (e.g., April 1) is widely used in such forecasting because it represents the major water storage term in a snowmelt-dominated system like the UCRB. Snowfall and seasonal snowpacks are likely to be significantly affected by warming temperatures, portending a future where snow may not be as robust an indicator of water supply and drought. Thus, this research addresses the question: How are the key indicators of drought in the UCRB likely to change under a future climate? We seek to assess changes in drought predictability under future climate using downscaled hydrologic simulations driven by CMIP5 ensemble mid-century (2045-2055) projections. We evaluate historical hydrologic simulations from the variable infiltration capacity (VIC) model against observations to understand model performance and then applied the hydrologic framework to explore changes in future skill. We find a strong predictive relationship between historical April 1 SWE and streamflow for the May-July period (R=0.82), with similar skill for the model (R=0.88). Despite a persistent negative bias between simulated and observed April SWE (31%), simulated SWE is strongly correlated with observed (R=0.93) indicating the utility of the model to characterize hydrologic behavior and a viable tool to assess future predictability. Mid-century projected streamflows are modestly reduced on average (6.9%), with key reductions occurring during the warm season (13.9% reduced) and peak flow occurring a full month earlier than historic, presenting important challenges for water managers. Finally, the strength of the predictive relationship between SWE and warm-season flow is notably diminished under future climate (R=0.77) and is consistently diminished during historical and future drought years relative to non-drought years. These results indicate an appreciable challenge for seasonal forecasting to mitigate projected drier conditions and prompting our recommendation for water managers to explore other non-snow-based sources of predictability.

The study evaluated the relationship between two climate variability indicators–sea-surface temperature (SST) and 500-mbar geopotential height (HGT/Z₅₀₀)–and the monsoonal precipitation pattern of Pakistan. Data from 30 precipitation gauges were obtained and were analyzed over a period of 35 years from 1980 to 2014. Singular-valued decomposition (SVD) technique was used to determine the association of previous year’s SST and HGT with the current year’s monsoonal precipitation. The results indicated that the association of SST and HGT with precipitation varied depending on the lead-times selected. Multiple regions of the North Indian Ocean were identified that showed significant association in affecting Pakistan’s precipitation. The long term trend and abrupt shift patterns of precipitation were also evaluated across the selected gauges to determine the generic change patterns. The findings of the study can be useful predictors of forecasting models for water management in Pakistan.

In water resources, understanding potential changes in rainfall patterns in the future is important for long-term planning as water availability for various purposes are often highly dependent on streamflow and reservoir storage driven by rainfall. The technologies for predicting future rainfall have advanced and data from future rainfall projections have been more readily available not only in continental scales but also in regional or even local scales. In this study, projected future rainfall from a regional climate models (RCM) were utilized to assess the impact of potential change in rainfall on streamflow over the 3S Sub-Basin that encompasses Sekong, Sesan, Srepok Joint River Basins (3S Sub-Basins), a 78,650 km² tributary of the Lower Mekong Basin. The RCM weather research and forecasting (WRF) has been utilized to dynamically downscale an ensemble of three Global Climate Models (CCSM3.0, ECHAM5 and MIROC medium resolution), under the Coupled Models Inter-comparison Project Phase 3 (CMIP3) over the historical baseline (1961-1990) and future (2011-2040) climates under two emission scenarios A2 and A1B. A hydrological model to estimate streamflow rate on a monthly basis was built and calibrated using various available rainfall and streamflow data within the watershed. The projected future rainfall was then applied to the calibrated hydrological model to determine potential changes in streamflow in the next 30 years, especially in critical low flow conditions. The projected rainfall indicates increases of up to 10%. The increases are likely to be more prominent in Srepok than Sekong and Sesan, and in Srepok the increase is likely to be more in the upstream than the downstream drainage area. The study also indicates an increase in average streamflow up to 10%, especially during wet periods. However, the dry flow in April was found to reduce for the future climate and the reduction might be greater in Sekong and downstream of Srepok. The results of this study would be useful to the policy makers and stake holders to devise their adaptive strategies in the context of changing climate.

Lima holds ~30% of Peru’s entire population. It is listed among the 30 most populated cities of the world, and since the past decade, it faces an increasing water stress. In this context, evaluating future precipitation patterns in the Rimac Basin, which runs along Lima and provides for 60% of the drinking water to its population, is crucial. In this paper, we use statistical downscaling (SD) to correct and evaluate 22 years (Set/1982–Ago/2004) of historical daily precipitation data from the HadGEM2 general circulation models (GCM) to assess a near future time frame (Dec/2015–Nov/2045) being centered in 2030. To perform SD, we apply quantile-mapping techniques that uses a non-parametric transformation function being represented by the Bernoulli-Gamma mixture probabilistic model from eight ground weather stations. HadGEM2 models were evaluated by considering two model efficiency metrics, namely: bias and relative root mean squared error (RRSME). Our results show that the bias and RRSME were reduced to the ranges 0.7–1.6 units and -2.3%–8.3%, respectively. Likewise, we determined that the HadHGEM2-ES and HadHGEM2-CC models performed markedly better during dry and wet seasons.

Mesoscale convective systems (MCSs) are known for their ability to generate localized extreme precipitation. Therefore, it is important to understand how such storm systems will evolve in the context of a changing climate. This goal can be achieved by using a numerical weather model such as the weather research and forecasting (WRF) model, forced by a climate projection from a global climate model. Recent studies have shown that the WRF model can reconstruct relatively well MCSs in the forecasting mode, where data assimilation techniques are used to improve the model’s performances. Nevertheless, no observation is available for the future. To this extent, it is important to evaluate the performances of numerical weather models in reproducing MCSs in the simulation mode, for which the model is only subject to the influence of the initial and boundary conditions. In this study, we used the WRF model to simulate at 5-km resolution a MCS which generated local extreme precipitation in the Northern United States on Aug 19th 2007. We tested two reanalysis datasets along with 150 combinations of the parameterization schemes. The model’s performances were evaluated by the use of two statistics: the relative error for the total inner-domain averaged precipitation, and the percentage of overlapping between the simulated and observed fields associated with several precipitation thresholds. We show that under an appropriate choice of the model’s options and boundary conditions, the WRF model provides satisfactory results in reproducing the location, intensity, and texture of the intense precipitation field in the MCS.

This study is designed to quantify the effects of climate change on hydrologic flow regimes in the Gediz Basin in Western Turkey during the 21^st century. As the regional atmospheric model, the weather research and forecasting (WRF) Model was employed to dynamically downscale the outputs of two global climate models, HadGEM2-ES and GFDL-ESM2M, to a 6-km grid resolution under two IPCC representative concentration pathway scenarios (RCP4.5 and RCP8.5). The downscaled atmospheric data were then used to drive the watershed environmental hydrology (WEHY) model, a fully physically-based hydrologic model, over the Gediz Basin in order to obtain the total amount of water inflows into the basin’s major reservoir. Historical period inflows (1985-2012) were compared to the future projections of reservoir inflows (2017-2100). Trends in annual inflow projections were also analyzed. The results suggest an increase in the amount of future projected inflows during the 21^st century.

Watershed Environmental Hydrology Hydro-Climate Model (WEHY-HCM) was used to simulate the surface flows of the Upper Middle Fork (UMF) Watershed under different climate conditions. Long-term historical atmospheric conditions over the Middle Fork Feather River Basin were reconstructed for the 63-year period between October 1950 and September 2013 by the dynamical downscaling of NCEP/NCAR Reanalysis Data. Future atmospheric conditions were also simulated by dynamically downscaling future climate projections during the 21^st century from two GCMs (CCSM3 and ECHAM5) based on four SRES future climate scenarios. The downscaled atmospheric data were used as the inputs into a physically-based hydrologic model of the WEHY-HCM, to simulate stream flows at the Upper Middle Fork Watershed. The data were also used with DWR’s physically based groundwater and root zone model, IWFM, to simulate groundwater stresses in the Sierra Valley Aquifer of Northern California.

The presence of uncertainties in flow parameters (e.g., roughness, lateral inflow, etc.) would make the Saint-Venant open-channel flow a stochastic process. While the Monte Carlo method can be used to obtain the ensemble behavior of such a process, its large number of simulations causes it to be computationally intensive. This study proposed a methodology for solving the stochastic Saint-Venant equations to obtain the expected system behavior and statistical properties of the flow variables in one shot, without the need for a large number of simulations. The uncertainty considered in this study came from the channel roughness coefficient. The proposed methodology involved developing the nonlocal Lagrangian-Eulerian Fokker-Planck Equation (LEFPE) of the characteristic form of the stochastic Saint-Venant equations for an open-channel flow problem, and then solving it to obtain the ensemble behavior and variability of the system. The new methodology results were validated against the statistical properties calculated by the Monte Carlo approach over the same open-channel flow problem. The validation demonstrated that the developed LEFPE can adequately express the ensemble behavior of the Saint-Venant open-channel flow process under uncertain channel properties.

This study performs dynamical downscaling simulations using a regional atmospheric model, WRF (the weather research and forecasting model), over the Gediz Basin at 6 km grid resolution in order to investigate changes in temperature and precipitation during the 21^st century under two IPCC representative concentration pathway scenarios (RCP4.5 and RCP8.5). The global climate models (GCMs) used in this study are HadGEM2-ES and GFDL-ESM2M. Bias correction was applied for precipitation on a monthly basis by comparing the dynamically-downscaled precipitation obtained from the historical simulations of each GCM to the corresponding observed data. Historical temperature and precipitation data (1985–2005) were then compared to the temperature and precipitation projections (2017–2099). In addition, trends in annual projected temperature and precipitation were also analyzed.

The Grizzly Valley Dam is an earth and rockfill dam located in the Lake Davis Basin of the Feather River Watershed, which is in California’s northern Sierra Nevada. The dam is situated just downstream of Lake Davis, with the purposes of water supply (to Portola), fish and wildlife enhancement, streamflow enhancement, as well as recreation. Historical data was reconstructed over the Lake Davis Basin by dynamically downscaling NCEP/NCAR reanalysis data. Using the same technique, the data of 13 projected future climate conditions obtained from two global climate models (CCSM3 and ECHAM5) were dynamically downscaled to obtain future climate conditions over the Lake Davis Basin. The physically-based watershed environmental hydrology (WEHY) model was implemented over the Lake Davis Basin, and it used the downscaled atmospheric data as inputs and provided simulated inflows into the dam as outputs. Accordingly, a historical analysis of the reservoir operation was done, with the main focus of determining the dam’s historical operation procedures. Using the derived dam operation procedures, the reservoir operation was studied under the future flow projections. Reservoir storage values, shortages, and spills were analyzed and compared between the different projections. Modifications to the historical dam operations were suggested, along with other possible approaches, in order to reduce the risk of extreme water depletion in the reservoir, as well as to control the amounts of shortages and spills from the dam during the 21^st century.

In this study, molecular dynamics (MD) simulation is done to predict the release of PAHs from the asphalt concrete (AC) pavements in the presence of moisture, tire pressure, and temperature. Naphthalene and fluoranthene PAHs are simulated with asphaltene phenol in this study. The bond stretching energy loss and the total energy loss comprehends the release of PAHs from the asphalt binder. At 5% moisture content and no tire pressure, the bond stretching energy loss is approximately 91% for both naphthalene and fluoranthene. At 5% moisture content and no tire pressure, naphthalene loses total energy of approximately 90%, while fluoranthene loses 88% of total energy. The total energy loss is approximately 85% and 88% for naphthalene and fluoranthene, respectively, at 0.68 MPa tire pressure. Results show that as the tire pressure increases the release of PAHs from asphaltene phenol decreases.

A statistical extremal analysis was performed to assess flooding elevations in Philadelphia along the tidal Delaware River, to inform a flood risk assessment for the Philadelphia Water Department. A peaks over threshold analysis identified flooding events in a 116-year continuous tidal record. An apparent natural break in the data informed a “split” in the extreme distribution curve fitting performed, though a General Pareto curve was used for both event groupings. The resulting GPD curves were used to estimate flood elevations at various return intervals, including the 100-year flood. With projected local sea level rise superimposed at various planning horizons, these flood elevations are being used to identify assets that may be exposed to future flood hazards, and prioritize adaptation measures to reduce flood risk.

Intensity-duration-frequency (IDF) relations of extreme rainfalls at a single location are usually required for planning and design of urban and highway drainage structures. Traditionally, these IDF relations were developed based on the frequency analysis of annual extreme rainfalls in which a common probability distribution such as the generalized extreme value (GEV) was fitted to the annual extreme rainfall data for different durations without considering the dependence between these extreme rainfalls. This traditional approach could lead to inaccurate estimation of extreme rainfalls for different return periods. In the present study, an improved procedure was proposed to describe the distribution of extreme rainfalls in consideration of the scale-invariance properties of extreme rainfall processes for different durations. More specifically, the proposed approach was based on the use of the GEV distribution and on the identification of the scaling behavior of the extreme rainfall processes for different time scales. The feasibility of this scaling GEV method was tested using annual extreme rainfall data from a network of nine raingage stations located in the north and northeast region of Thailand during 1950-2010. Results of this illustrative application have indicated the feasibility and accuracy of the proposed scale-invariance GEV model in the derivation of the IDF relations. In addition, the annual extreme rainfall data for this study region were found to display a simple scaling behavior over different time scales.

Infrastructure and buildings constructed today will experience significantly different weather patterns over the course of their lifetime due to the impacts of climate change. In order for utility agencies and property developers to plan for these changes, localized data on the projected changes in rainfall patterns is needed. For stormwater management, this data would include changes in rainfall intensity, duration, and frequency, along with correlating updates to existing hydrologic design standards. The WeatherShift flooding tool uses data from 21 global climate models to generate projected rainfall statistics for a range of emission scenarios and future time frames. This data is presented in the form of localized climate change-shifted rainfall Intensity-Duration-Frequency (IDF) curves for use in drainage infrastructure design, such as for sizing storm drain networks, pump stations, and treatment plants. In this paper we discuss how we use data from global climate models and an Argos Analytics-developed tool to construct distributions of future rainfall intensity as a function of rainfall duration and return time, which can then be applied in engineering practice for risk-based resiliency planning of drainage infrastructure. Optimizing infrastructure capacity design enables planning for risk-based adaptations while minimizing lifecycle costs. We also discuss a proposed tool for morphing daily rainfall time series to reflect future climate conditions, which can be used by the TopUp rainfall harvesting tool to predict future rainfall harvesting scenarios.

This study presents a top-down, bottom-up modeling framework to investigate the effects of future climate on crop production in the Mississippi River Basin, a world leading crop producer. Specifically, this study will examine how climate will alter erosion, soil organic carbon (SOC) loss, soil moisture, and hence crop yields. Representative hillslopes from the Obion River Watershed in west Tennessee/southwest Kentucky are identified using outputs from the variable infiltration capacity (VIC) regional hydrologic model. This identification criteria considers both soil properties and changing hydrology, through the runoff coefficient. In the representative areas a process-based, hillslope-scale, erosion model, namely the water erosion prediction project (WEPP), is used to examine the cause-effect relations between management and climate with soil erosion, SOC loss, and changes in soil moisture. The ultimate goal of this study is to forecast yield variations until 2050 under established climate scenarios to find sustainable solutions.