Abstract We present a general Bayesian hierarchical framework for conducting nonstationary frequency analysis of multiple hydrologic variables. In this, annual maxima from each variable are assumed to follow generalized extreme value (GEV) distribution in which the location parameter is allowed vary time. A Gaussian elliptical copula used model joint all demonstrate utility this with peak snow water equivalent (SWE), flow, and reservoir elevation at Taylor Park dam Colorado, USA. Indices...

Abstract Hydroclimate time series often exhibit very low year‐to‐year autocorrelation while showing prolonged wet and dry epochs reminiscent of regime‐shifting behavior. Traditional stochastic models cannot capture the features thereby misrepresenting risk periods, consequently impacting management planning efforts. Upper Colorado River Basin (UCRB) annual flow highlights this clearly. To address this, a simulation framework is developed using hidden Markov (HM) model in combination with...

Abstract We examine the characteristics of 3 day total extreme precipitation in western United States. Coherent seasonal spatial patterns timing and magnitude are evident data, motivating a seasonally based analysis. Using clustering method that is consistent with value theory, we identify coherent regions for extremes vary seasonally. Based on storm back trajectory analysis, demonstrate unique moisture sources dominant pathways each region. In winter Pacific Ocean source across west, but...

As we move towards a decarbonized grid, reliance on weather-dependent energy increases as does exposure to prolonged natural resource shortages known droughts. Compound droughts occur when two or more predominant renewable sources simultaneously are in drought conditions. In this study present methodology and dataset for examining compound wind solar well the first standardized benchmark of across Continental United States (CONUS) 2020 infrastructure. Using recently developed simulated...

Variable renewable energy (VRE) droughts are periods of low electricity production due to natural variability in the weather and climate. These compound occur when two or more (typically wind solar) generation sources availability conditions at same time. Compound solar most commonly studied hourly daily timescale short-term nature markets battery storage capacity. However seasonal time scale allows for examination broader climate hydrologic patterns that influence a portfolio inform needs...

Hydropower is a critical electricity resource in the United States which, addition to renewable and carbon-free generation, provides valuable ancillary grid services, supports integration of wind solar resources. Despite its value an increasingly decarbonized grid, there are very few comprehensive datasets available from which study both historical future impacts climate change, variable energy droughts, integration. In this paper, we present hydropower generation dataset covering over 1,400...

As variable renewable energy resources become a larger part of the generation mix in United States (U.S.), so does potential impact prolonged periods low wind and solar generation, known as (VRE) droughts. In future decarbonized or low-carbon grid, naturally occurring VRE droughts need to be evaluated for their on grid reliability. This study is first its kind examine impacts compound Western U.S. across range climate change infrastructure scenarios. We find that drought severity will...

Abstract Variable renewable energy (VRE) droughts are periods of low electricity production due to natural variability in the weather and climate. These compound occur when two or more (typically wind solar) generation sources availability conditions at same time. Compound solar most commonly studied hourly daily timescale short-term nature markets battery storage capacity. However seasonal time scale allows for examination broader climate hydrologic patterns that influence a portfolio...

In this paper we present a comprehensive framework developed by the Northwest River Forecast Center (NWRFC) for calibration of arbitrary hydrologic basins. The includes hydrology, snow, routing, channel loss, and consumptive use models. Data inputs include wide range open access datasets land use, cover, meteorology. can handle basins with diverse conditions, including permanently glaciated regions. We also develop flexible automatic system which numerous unobservable model parameters in...

This Perspective article provides a brief overview of the topic wind and solar energy droughts (henceforth WSDs). It does not attempt to provide complete literature review subject but rather highlights some main concepts associated with WSDs. These include drought definitions metrics; meteorological conditions producing WSDs; comparison their characteristics hydrologic hydropower droughts; model-based observational datasets useful for WSD analyses; linkage WSDs transmission, storage, demand...

We present a technique for providing seasonal ensemble streamflow forecasts at several locations simultaneously on river network. The framework is an integration of two recent approaches: the nonparametric multimodel forecast and space‐time disaggregation technique. four main components proposed are as follows: (1) index gauge constructed sum flows all desired spatial locations; (2) potential predictors spring season (April–July) this identified from large‐scale ocean‐atmosphere‐land system,...

In many complex water supply systems, the next generation of resources planning models will require simultaneous probabilistic streamflow inputs at multiple locations on an interconnected network. To make use valuable multicentury records provided by tree-ring data, reconstruction must be able to produce appropriate multisite inputs. Existing typically focus one site a time, not addressing intersite dependencies and potentially misrepresenting uncertainty. this end, we develop model for with...

Abstract We propose a Bayesian hierarchical model for spatial extremes on large domain. In the data layer Gaussian elliptical copula having generalized extreme value (GEV) marginals is applied. Spatial dependence in GEV parameters captured with latent regression spatially varying coefficients. Using composite likelihood approach, we are able to efficiently incorporate precipitation set, which includes stations missing data. The demonstrated by application fall at approximately 2600 covering...

As renewable energy continues its rapid expansion in the Unites States, multi-decadal hourly datasets of electricity production are needed to asses reliability and resource adequacy power grids. Recent years have seen release grid-cell-level simulated meteorological variables, however these not extended domain, developed from a dynamically consistent numerical weather model, only cover historical baseline less than decade. To fill this gap, work provides dataset 43 coincident plant-level...

Abstract Effective conservation requires monitoring and pro‐active risk assessments. We studied the effects of at‐sea mortality events (ASMEs) in marine mammals over two decades (1990–2012) built a risk‐based indicator for European Union's Marine Strategy Framework Directive. Strandings harbor porpoises ( Phocoena phocoena ), short‐beaked common dolphins Delphinus delphis striped Stenella coeruleoalba ) along French coastlines were analyzed using Extreme Value Theory (EVT). EVT...