Estimating River Discharge Using Multiple-Tide Gauges Distributed Along a Channel

Reliable estimation of freshwater inflow to the ocean from large tidal rivers is vital for water resources management and climate analyses. Discharge gauging stations are typically located beyond the tidal intrusion reach, such that inputs and losses occurring closer to the ocean are not included. Here, we develop a method of estimating river discharge using multiple gauges and time-dependent tidal statistics determined via wavelet analysis. The Multiple-gauge Tidal Discharge Estimate (MTDE) method is developed using data from the Columbia River and Fraser River estuaries and calibrated against river discharge. Next, we evaluate the general applicability of MTDE by testing an idealized two-dimensional numerical model, with a convergent cross-sectional profile, for eighty-one cases in which nondimensional numbers for friction, river flow, and convergence length scale are varied. The simulations suggest that MTDE is applicable to a variety of tidal systems. Model results and data analyses together suggest that MTDE works best with at least three gauges: a reference station near the river mouth, and two upstream gauges that respond strongly to distinct portions of the observed range of flow. The balance between tidal damping and amplifying factors determines the favorable location of the gauges. Compared to previous studies, the MTDE method improves the time resolution of estimates (from 2.5 to \u3c 1 week) and is applicable to systems with mixed diurnal/semidiurnal tides. However, model results suggest that tide-induced residual flows such as the Stokes drift may still affect the accuracy of MTDE at seaward locations during periods of low river discharge

A Novel Approach to Flow Estimation in Tidal Rivers

Reliable estimation of river discharge to the ocean from large tidal rivers is vital for water resources management and climate analyses. Due to the difficulties inherent in measuring tidal-river discharge, flow records are often limited in length and/or quality and tidal records often predate discharge records. Tidal theory indicates that tides and river discharge interact through quadratic bed friction, which diminishes and distorts the tidal wave as discharge increases. We use this phenomenon to develop a method of estimating river discharge for time periods with tidal data but no flow record. Employing sequential 32 day harmonic analyses of tidal properties, we calibrate San Francisco (SF), CA tide data to the Sacramento River delta outflow index from 1930 to 1990, and use the resulting relationship to hindcast river flow from 1858 to 1929. The M2 admittance (a ratio of the observed M2 tidal constituent to its astronomical forcing) best reproduces high flows, while low-flow periods are better represented by amplitude ratios based on higher harmonics (e.g.). Results show that the annual inflow to SF Bay is now 30% less than before 1900 and confirm that the flood of January 1862 was the largest since 1858

The evolving landscape of sea-level rise science from 1990 to 2021

As sea-level rise (SLR) accelerates due to climate change, its multidisciplinary field of science has similarly expanded, from 41 articles published in 1990 to 1475 articles published in 2021, and nearly 15,000 articles published in the Web of Science over this 32-year period. Here, big-data bibliometric techniques are adopted to systematically analyse this large literature set. Four main research clusters (themes) emerge: (I) geological dimensions and sea-level indicators, (II) impacts, risks, and adaptation, (III) physical components of sea-level change, and (IV) coastal ecosystems and habitats, with 16 associated sub-themes. This analysis provides insights into the evolution of research agendas, the challenges and opportunities for future assessments (e.g. next IPCC reports), and growing focus on adaptation. For example, the relative importance of sub-themes evolves consistently with a relative decline in pure science analysis towards solution-focused topics associated with SLR risks such as high-end rises, declining ecosystem services, flood hazards, and coastal erosion/squeeze

Climate-informed environmental inflows to revive a drying lake facing meteorological and anthropogenic droughts

The rapid shrinkage of Lake Urmia, one of the world\u27s largest saline lakes located in northwestern Iran, is a tragic wake-up call to revisit the principles of water resources management based on the socio-economic and environmental dimensions of sustainable development. The overarching goal of this paper is to set a framework for deriving dynamic, climate-informed environmental inflows for drying lakes considering both meteorological/climatic and anthropogenic conditions. We report on the compounding effects of meteorological drought and unsustainable water resource management that contributed to Lake Urmia\u27s contemporary environmental catastrophe. Using rich datasets of hydrologic attributes, water demands and withdrawals, as well as water management infrastructure (i.e. reservoir capacity and operating policies), we provide a quantitative assessment of the basin\u27s water resources, demonstrating that Lake Urmia reached a tipping point in the early 2000s. The lake level failed to rebound to its designated ecological threshold (1274 m above sea level) during a relatively normal hydro-period immediately after the drought of record (1998–2002). The collapse was caused by a marked overshoot of the basin\u27s hydrologic capacity due to growing anthropogenic drought in the face of extreme climatological stressors. We offer a dynamic environmental inflow plan for different climate conditions (dry, wet and near normal), combined with three representative water withdrawal scenarios. Assuming effective implementation of the proposed 40% reduction in the current water withdrawals, the required environmental inflows range from 2900 million cubic meters per year (mcm yr−1) during dry conditions to 5400 mcm yr−1 during wet periods with the average being 4100 mcm yr−1. Finally, for different environmental inflow scenarios, we estimate the expected recovery time for re-establishing the ecological level of Lake Urmia

A Novel Approach to Flow and Sediment Transport Estimation in Estuaries and Bays

Reliable estimates of river discharge and sediment transport to the ocean from large tidal rivers are vital for water resources management, efficient river and harbor management, navigational purposes, and climate analyses. Due to the difficulties inherent in measuring tidal-river discharge, hydrological and sedimentological records are typically too short to adequately characterize long-term (decadal) trends. Also, uncertainties associated with observation and calibration of hydrological models suggest a need for more accurate methods based on longer records of hydrodynamic parameters (e.g. tides). Tidal theory indicates that tides and river discharge interact through quadratic bed friction, which diminishes and distorts the tidal wave as discharge increases. In this study, using tidal constituents, astronomical forcing and a model of the frictional interaction of flow and tides, I propose a novel Tidal Discharge Estimate (TDE) to predict freshwater discharge with an approximate averaging interval of 18 days for time periods with tidal data but no river flow records. Next, using continuous wavelet analysis of tidal properties, I develop a method of estimating river discharge using tides measured on multiple gages along tidal rivers to improve the time-resolution and accuracy of TDE. The applicability of the Multiple-gauge Discharge Estimate (MTDE) is first demonstrated in the two largest tidal-fluvial systems of the Pacific Northwest, the Columbia River Estuary (CRE) and Fraser River Estuary (FRE). A numerical model of an idealized estuary with similar forcing as the FRE and CRE is next run under different hydrologic and morphologic scenarios to evaluate the effect of convergence, friction, and river flow variations on the applicability of MTDE. The TDE method was applied to the San Francisco Bay, using the continuous hourly tide record available since 1858. Results show that TDE reproduces known San Francisco (SF) Bay delta inflows from 1930-present with a Nash-Sutcliffe coefficient of 0.81 and is a useful method for hindcasting historical flows from 1858 - 1929, a period that predates direct measurement of delta discharge. I also recover and digitize ~80 years of Sacramento River daily water level data between 1849 and 1946, from which river discharge to SF Bay is estimated on a daily basis, after adjusting for changes to the river channel. This discharge combined with Net Delta Outflow Index estimates (1930 - 2011) and flow estimates from tidal data (1858 - 2011) provides a more accurate version of SF Bay historic daily inflows from 1849 - 2011. Next, the history of sediment transport and discharge into SF Bay from 1849-present is reevaluated using the daily discharge estimates. A non-stationary rating curve between river flow and sediment transport is developed, with net sedimentation observed during five bathymetric surveys that were used to constrain the total integrated sediment discharge. Results show that ~1600±320 million-tons of sediment have been delivered to SF Bay between 1850 and 2011. There has been an approximately 25 - 30% reduction of annual flow since the 19th century, along with decreased sediment supply. This has resulted in a ~60% reduction in annual sediment delivery to SF Bay. The annual hydrograph of inflow to SF Bay and the seasonality of sediment flux have changed considerably over time, due to both human alteration and climate change. Significant historic spring-melt peak floods have disappeared in the modern system and now peak flows mostly occur in winter. My flow estimation methods also confirm that the flood of January 1862 had the largest daily sediment load and the second largest daily discharge since 1849

Increasing exposure of energy infrastructure to compound hazards: cascading wildfires and extreme rainfall

Floods and debris flows pose a significant threat, especially when extreme rain falls over burned areas. This is an example of a compound event in which two concurrent or consecutive events lead to extreme societal impacts. Compound and cascading hazards are becoming increasingly important and have notable impacts on threatened communities across the world. Wildfire followed by an intense precipitation event can result in a large flood under which the combined impacts of hazard drivers are much more intense than those from individual drivers. Here, we first quantify the change in exposure of natural gas infrastructure to individual hazards, wildfire and floods in the future relative to past. We, then quantify the compound hazards as coincidence likelihood of intense rain over burned areas and analyze the spatial patterns across the State of California, USA. Our results show that not only the exposure of natural gas infrastructure to individual hazards would be higher, the likelihood of compound hazards is expected to increase substantially in a warming climate

Stochastic Simulation of Storm Surge Extremes Along the Contiguous United States Coastlines Using the Max-Stable Proces

Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction

Estimating river discharge using multiple‐tide gauges distributed along a channel

Reliable estimation of freshwater inflow to the ocean from large tidal rivers is vital for water resources management and climate analyses. Discharge gauging stations are typically located beyond the tidal intrusion reach, such that inputs and losses occurring closer to the ocean are not included. Here, we develop a method of estimating river discharge using multiple gauges and time-dependent tidal statistics determined via wavelet analysis. The Multiple-gauge Tidal Discharge Estimate (MTDE) method is developed using data from the Columbia River and Fraser River estuaries and calibrated against river discharge. Next, we evaluate the general applicability of MTDE by testing an idealized two-dimensional numerical model, with a convergent cross-sectional profile, for eighty-one cases in which nondimensional numbers for friction, river flow, and convergence length scale are varied. The simulations suggest that MTDE is applicable to a variety of tidal systems. Model results and data analyses together suggest that MTDE works best with at least three gauges: a reference station near the river mouth, and two upstream gauges that respond strongly to distinct portions of the observed range of flow. The balance between tidal damping and amplifying factors determines the favorable location of the gauges. Compared to previous studies, the MTDE method improves the time resolution of estimates (from 2.5 to \u3c 1 week) and is applicable to systems with mixed diurnal/semidiurnal tides. However, model results suggest that tide-induced residual flows such as the Stokes drift may still affect the accuracy of MTDE at seaward locations during periods of low river discharge