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At least 145 records · Page 8

Stochastic relativistic viscous hydrodynamics from the Metropolis algorithm

We propose an algorithm for simulating stochastic relativistic fluid dynamics based on Metropolis updates. Each step of the algorithm begins with an update based on ideal hydrodynamics. This is followed by proposing random (spatial) momentum transfers between fluid cells, keeping the total energy fixed. These proposals are then accepted or rejected using the change in entropy as a statistical weight. The algorithm reproduces relativistic viscous hydrodynamics in the “density frame,” which is a formulation of viscous hydrodynamics we review and clarify here. This formulation is first order in time and requires no auxiliary dynamical fields such as Π 𝜇⁢𝜈 . The only parameters are the shear and bulk viscosities and the equation of state. Here, by adopting the 3+1 split of general relativity, we extend the Metropolis algorithm to general space-time coordinates, such as Bjorken coordinates, which are commonly used to simulate heavy-ion collisions.

Hydrodynamic noise↗

Alpha Decay Chains as Thermal Power Sources: Analysis and Applications for RTGs

Radioactive sources can provide power in remote and environmentally harsh locations such as the arctic or space. The generators powered by such sources are rugged and can withstand extreme temperatures, lack of sunlight, and require no human intervention for multiple years. Radioisotopes are used in thermoelectric generators to provide power at remote sites and deep in space. Isotopes like Pu-238, Cm-244, and Am-241 are used in these generators by NASA for power in space probes and spacecrafts. These power sources deliver a steady supply of energy over extended periods of time. Alpha particles created during decay do not travel far in a material. Their kinetic energy is transferred to heat that we can then convert into energy. Unlike beta and gamma decay, the slower-moving alpha particles stop in the material, making their energy available for use. Energy from these natural decay processes provides a reliable source of power. Spontaneous fission is rare and unreliable, and unlike induced fission processes, alpha decay occurs naturally and does not require external management or ignition. The ideal properties of an isotope for use as a power source depend upon the intended use. For use in an Arctic research base over a period of several years, but less than a decade, an isotope that provides high power output over a shorter lifespan may be the most suitable option. Whereas, for deep space missions where a consistent power source for decades or perhaps more than 100 years is needed that would require a very different isotope. One with a much longer half-life that would provide consistent power throughout that time and survive in that state in for these extended periods of time. These examples represent two extreme sides in terms of time frames. By analyzing the power produced by different radioactive decay processes over time, we can evaluate the suitability of various isotope decay chains for specific uses. Some unstable isotopes undergo a series of radioactive decays, transforming into different isotopes at each step and resulting in a stable isotope. The lists of isotopes in these decay processes are known as decay chains. Some of these chains, illustrated in the figures below, are currently being investigated for use in radioisotope thermoelectric generators (RTGs) designed for a range of operational durations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Influence of weather on gobbling activity of male wild turkeys

Gobbling activity of Eastern wild turkeys (Meleagris gallopavo silvestris; hereafter, turkeys) has been widely studied, focusing on drivers of daily variation. Weather variables are widely believed to influence gobbling activity, but results across studies are contradictory and often equivocal, leading to uncertainty in the relative contribution of weather variables to daily fluctuations in gobbling activity. Previous works relied on road-based auditory surveys to collect gobbling data, which limits data consistency, duration, and quantity due to logistical difficulties associated with human observers and restricted sampling frames. Development of new methods using autonomous recording units (ARUs) allows researchers to collect continuous data in more locations for longer periods of time, providing the opportunity to delve into factors influencing daily gobbling activity. We used ARUs from 1 March to 31 May to detail gobbling activity across multiple study sites in the southeastern United States during 2014–2018. We used state-space modeling to investigate the effects of weather variables on daily gobbling activity. Our findings suggest rainfall, greater wind speeds, and greater temperatures negatively affected gobbling activity, whereas increasing barometric pressure positively affected gobbling activity. Therefore, when using daily gobbling activity to make inferences relative to gobbling chronology, reproductive phenology, and hunting season frameworks, stakeholders should recognize and consider the potential influences of extended periods of inclement weather.

60 APPLIED LIFE SCIENCES↗

Study of SXR/EUV radiation of exploded foils and wires with spectral, spatial and temporal resolution simultaneously on KING electric discharge facility.

The results of studies of the soft X-ray and extreme ultraviolet (SXR/EUV) radiation of thin flat aluminum foils and wires under the explosion in an electric discharge on the compact high-current KING generator are presented. These studies were based on the SXR/EUV spectroscopy with a spectral resolution of 6 Å, a temporal resolution of 5 ns and a spatial resolution of 200 μm. To study the plasma radiation of exploded foils and wires in the SXR/EUV range, we used a transmission diffraction grating spectrograph which in combination with two additional slits provided spectral and spatial resolution. The spectrograph was coupled with a 4-frame recorder based on a microchannel plate for providing temporal resolution. The analysis and comparison of the spectral, spatial, temporal, and energy characteristics of the SXR/EUV radiation of plasma formed under the explosion of foils and wires of a similar mass made of aluminum was carried out. Here, the spectra were calculated as well and the plasma parameters and their changes in time and space were estimated on the basis of these calculations and comparison with relevant experimental results. Experiments have shown that when foils explode, a single intense source of SXR/EUV radiation is formed with radiated energy in the range of 10-20 J and a power of up to 100 MW in the quantum energy range from 30 to 250 eV. At the same time, the radiation power under the explosion of foils turned out to be about twice above the power under the explosion of wires of comparable mass.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Hierarchical Fractional Advection-Dispersion Equation (FADE) to Quantify Anomalous Transport in River Corridor over a Broad Spectrum of Scales: Theory and Applications

Fractional calculus-based differential equations were found by previous studies to be promising tools in simulating local-scale anomalous diffusion for pollutants transport in natural geological media (geomedia), but efficient models are still needed for simulating anomalous transport over a broad spectrum of scales. This study proposed a hierarchical framework of fractional advection-dispersion equations (FADEs) for modeling pollutants moving in the river corridor at a full spectrum of scales. Applications showed that the fixed-index FADE could model bed sediment and manganese transport in streams at the geomorphologic unit scale, whereas the variable-index FADE well fitted bedload snapshots at the reach scale with spatially varying indices. Further analyses revealed that the selection of the FADEs depended on the scale, type of the geomedium (i.e., riverbed, aquifer, or soil), and the type of available observation dataset (i.e., the tracer snapshot or breakthrough curve (BTC)). When the pollutant BTC was used, a single-index FADE with scale-dependent parameters could fit the data by upscaling anomalous transport without mapping the sub-grid, intermediate multi-index anomalous diffusion. Pollutant transport in geomedia, therefore, may exhibit complex anomalous scaling in space (and/or time), and the identification of the FADE’s index for the reach-scale anomalous transport, which links the geomorphologic unit and watershed scales, is the core for reliable applications of fractional calculus in hydrology.

97 MATHEMATICS AND COMPUTING↗

The Optical Two- and Three-dimensional Fundamental Plane Correlations for Nearly 180 Gamma-Ray Burst Afterglows with Swift/UVOT, RATIR, and the Subaru Telescope

Gamma-ray bursts (GRBs) are fascinating events due to their panchromatic nature. We study optical plateaus in GRB afterglows via an extended search into archival data. We comprehensively analyze all published GRBs with known redshifts and optical plateaus observed by many ground-based telescopes (e.g., Subaru Telescope, RATIR) around the world and several space-based observatories such as the Neil Gehrels Swift Observatory. We fit 500 optical light curves, showing the existence of the plateau in 179 cases. This sample is 75% larger than the previous one, and it is the largest compilation so far of optical plateaus. We discover the 3D fundamental plane relation at optical wavelengths using this sample. This correlation is between the rest-frame time at the end of the plateau emission, ${T}_{\mathrm{opt}}^{* }$, its optical luminosity, L opt , and the peak in the optical prompt emission, L peak,opt , thus resembling the three-dimensional (3D) X-ray fundamental plane (the so-called 3D Dainotti relation). We correct our sample for redshift evolution and selection effects, discovering that this correlation is indeed intrinsic to GRB physics. We investigate the rest-frame end-time distributions in X-rays and optical (${T}_{\mathrm{opt}}^{* }$, ${T}_{{\rm{X}}}^{* }$), and conclude that the plateau is achromatic only when selection biases are not considered. We also investigate if the 3D optical correlation may be a new discriminant between optical GRB classes and find that there is no significant separation between the classes compared to the Gold sample plane after correcting for evolution.

79 ASTRONOMY AND ASTROPHYSICS↗

A Lagrangian perturbation theory in the presence of massive neutrinos

We develop a Lagrangian Perturbation Theory (LPT) framework to study the clustering of cold dark matter (CDM) in cosmologies with massive neutrinos. We follow the trajectories of CDM particles with Lagrangian displacements fields up to third order in perturbation theory. Once the neutrinos become non-relativistic, their density fluctuations are modeled as being proportional to the CDM density fluctuations, with a scale-dependent proportionality factor. This yields a gravitational back-reaction that introduces additional scales to the linear growth function, which is accounted for in the higher order LPT kernels. Through non-linear mappings from Eulerian to Lagrangian frames, we ensure that our theory has a well behaved large scale behavior free of unwanted UV divergences, which are common when neutrino and CDM densities are not treated on an equal footing, and in resummation schemes that manifestly break Galilean invariance. We use our theory to construct correlation functions for both the underlying matter field, as well as for biased tracers using ConvolutionLPT. Redshift-space distortions effects are modeled using the Gaussian Streaming Model. When comparing our analytical results to simulated data from the Quijote 1 simulation suite, we find good accuracy down to r = 20 Mpc h -1 at redshift z = 0.5, for the real space and redshift space monopole particle correlation functions with no free parameters. The same accuracy is reached for the redshift space quadrupole if we additionally consider an effective field theory parameter that shifts the pairwise velocity dispersion. For modeling the correlation functions of tracers we adopt a simple Lagrangian biasing scheme with only density and curvature operators, which we find sufficient to reach down to r = 20 Mpc h -1 when comparing to simulated halos.

79 ASTRONOMY AND ASTROPHYSICS↗

GaAsP/Si Tandem Solar Cells: Pathway to Low-Cost, High-Efficiency Photovoltaics

Si is the dominant PV technology, now and for the foreseeable future, due to its extensive manufacturing infrastructure, supply chain, feedstock availability, and highly optimized degree of fabrication processes, which altogether has produced an economic scenario where PV electricity generation is often cheaper than conventional fossil based generation. In many places, the overarching goal of grid parity has been achieved, but further improvement in performance-cost metrics are still needed to sustain the continued LCOE reductions needed to not only compete with conventional generation, but displace it on a global scale; a matter of critical importance if we stand any hope of slowing climate change. Nevertheless, single-junction Si PV is already nearing its physical limit, both in performance and cost, and is thus cannot meet these long-term goals alone. To this end, we are working on the development of monolithic III-V/Si tandem solar cells, which improve upon the performance of pure Si by providing enhanced utilization (reduced thermalization) of high-energy photons. This architecture nominally combines the substantial existing knowledge base, manufacturing infrastructure, and low cost of Si PV with the high efficiencies afforded by the well-established multijunction approach — the only proven way to break the single-junction limit. Although the metal-halide perovskite/Si tandem architecture has garnered substantial attention in recent years, serious questions regarding reliability and service lifetime remain, whereas III-V PV has a proven track record, including in the harsh concentrator and space environments. Additionally, there are multiple fabrication approaches to producing III-V/Si tandem cells, but we are focused on monolithic epitaxial integration as it is the most likely to yield the lowest ultimate LCOE in a fully mature, scaled technology. In this work we have produced multiple generations of GaAsP/Si tandem solar cells, demonstrating a more than 10% absolute AM1.5G efficiency improvement within the time frame of the project, including two verified world records. We have done this using industry-standard fabrication methods, showing that this platform can ultimately be manufactured at scale using existing or only slightly upgraded Si and III-V tooling. Our scientific and engineering advances across a range of fundamental and applied areas – III-V/Si heteroepitaxial integration, defect control in metamorphic III-V epitaxy, fundamental materials-oriented solar cell design and modeling methodology, and more – have created clear pathways for continued advances toward the goal of >30% AM1.5G cell efficiency (and >25% module) and will serve to inform the broader research community for well beyond this immediate application. Techno-economic modeling indicates that our approach can indeed meet SunShot/SETO LCOE targets, but as with any “post-Si” technology there are difficult, but not insurmountable barriers, requiring continued focused research and development efforts.

14 SOLAR ENERGY↗

Separability of the Dirac equation in the STU black hole spacetime: Pairwise-equal charge case study

We study the separability of the Dirac equation in the background of four dimensional charged rotating asymptotically flat black hole solution of supergravity and the low energy string theory known as STU black hole. In particular, we analyze in detail the separability conditions in the pairwise equal charge STU black hole space-time. While in the latter case the minimally coupled Dirac equation is not separable, the introduction of a specific torsion term ensures the separability. The source of the torsion is the Kalb-Ramond field, which is an integral part of string theory, but further aspects of its properties and coupling to fermionic fields remain to be studied. To derive the torsion, two different approaches are used in conformally related frames, showing that the torsion is not unique. The correspondingly modified Dirac equations in the Einstein and string frames are shown to be separable. Furthermore, the massless radial and angular wave equations are examined; they show close similarity with corresponding equations for the standard Kerr background. A generalization of the Teukolsky equation for the pairwise equal case is conjectured. We also briefly analyze a technically sophisticated radial equation in the massive case.

Dirac equation↗

Geometric Interpretation of the Cluster Location Problem Part I: Theory

We present a new framing of the seismic location problem using principles drawn from differential geometry. Our interpretation relies upon the common assumption that travel times observed across a network are continuous, differentiable functions of source location. In consequence, travel‐time functions constitute a differentiable map between the source region and a Riemannian manifold. The manifold is said to be the image of the source region embedded in a generally high‐dimension travel‐time vector space. A cluster of events in the source region has an image of discrete points on the manifold, that, except in the simplest cases, cannot be viewed directly. However, it is possible to project the image of a cluster into a tangent space of the manifold for direct visualization. The projection operator can be computed directly from the data without a velocity model, but produces a distorted rendering of the cluster geometry. With a model we can predict the distortions and correct them to estimate cluster geometry. We develop these points with the simplest possible example, one for which direct visualization of the manifold is possible, using the example as an introduction to the relevant concepts from differential geometry in a familiar setting. The tangent space, a local linearization of the manifold, plays a key role. We develop a metric to estimate the limits of linearization, that is, to determine when the curvature of the manifold invalidates the linear assumption. We also examine the interplay of model error, inadequate network geometry, and pick error. We then generalize our results from the simple case to the general case of 3D source regions observed by general networks. Although we do suggest a new “project and correct” method for location, we do not develop it into a practical algorithm. In conclusion, our intention rather is to highlight new analytical methods grounded in differential geometry.

East Pacific Ocean Islands↗

An editorial to the Special Issue on “Severe climate Risks”

The history of this Special Issue (https://www.sciencedirect.com/special-issue/10JD7LNJNQ0) indirectly dates back to the early 1990s, when the signature of the United Nations Framework Convention on Climate Change kicked-off an international political process based on one overarching and foundational principle: to avoid “dangerous anthropogenic interference with the climate system” at the global level. More than three decades later, such a principle remains central, though complementary aims made their way through the climate negotiation process, such as the importance of ensuring equity and justice, to give just one example here. Scientific knowledge also considerably progressed and we know more about the range of risks that climate change imposes and will continue to impose to the biosphere and humankind, worldwide and at all territorial levels. It is also clear that societal responses to these risks —“climate adaptation” as we know it— are increasingly happening, but definitely not at the pace of climate risk trends (Berrang-Ford et al., 2021, Erisken et al., 2021, Olazabal and Ruiz De Gopegui, 2021, Magnan et al., 2023a, Reckien et al., 2023, UNEP, 2023). As a result, concerns have emerged over the recent years in both the scientific and policy arenas around the idea that societies may not be able to address all climate risks, and that limits to adaptation and induced residual risks need to be considered more seriously. Such concerns further highlight the continuing importance of the imperative to minimise dangerous anthropogenic interference with the climate system, at any scale. But what does “dangerous interference” mean? How can we decide that we are entering the “dangerous” space, compared to a broader range of climate risks that would qualify as problematic but not necessarily “dangerous”? Who should make such a decision? Which conditions drive risk severity over time, including in the future? And what would be the environmental, economic, social and cultural implications of prioritising some climate risks over others? The Intergovernmental Panel on Climate Change (IPCC) was a pioneer in addressing such questions through the development of the “Key Risks” framing that describes those climate risks having the potential to become dangerous or “severe” over the course of this century (Schellnhuber et al., 2006, Schneider et al., 2007, Oppenheimer et al., 2014, O’Neill et al., 2022). The Fifth and Sixth assessment cycles (AR5 and AR6) went a step further by identifying about 120 Key Risks across regions and sectors, and clustering them into 8 “Representative Key Risks” covering a range of geographical systems (low-lying coasts, and to terrestrial and ocean ecosystems), sectors (critical infrastructure, living standards, human health, food security, and water security) and human dimensions (peace and mobility) (Oppenheimer et al., 2014, O’Neill et al., 2022). This Special Issue was born of the efforts of a range of authors, during the development of the IPCC AR6 main Assessment Report between 2019 and 2022, to characterise Key Risks and Representative Key Risks, and advance knowledge on what shapes “severe climate risks” conceptually as well as in the real-world. The series of papers forming this Special Issue is not intended to cover the topic exhaustively, but rather to give readers an overview through the following narrative: defining “severe climate risks” is highly challenging (Magnan et al., 2023b), but knowledge is expanding on the driving climate hazards (Tebaldi et al., 2023) and their implications on geographical systems, sectors and human dimensions, using here food security (Mirzabaev et al., 2023), human mobility (Gilmore et al., 2024) and peace (Buhaug et al., 2023) as illustrative examples. The overall intention is to support especially decision-makers, whatever the scale or sector considered, in asking severity-driven questions to identify sector- and context-specific “priority” risks from climate change.

54 ENVIRONMENTAL SCIENCES↗

JWST Noise Floor. I. Random Error Sources in JWST NIRCam Time Series

James Webb Space Telescope (JWST) transmission and emission spectra will provide invaluable glimpses of transiting exoplanet atmospheres, including possible biosignatures. This promising science from JWST, however, will require exquisite precision and understanding of systematic errors that can impact the time series of planets crossing in front of and behind their host stars. Here, we provide estimates of the random noise sources affecting JWST Near-Infrared Camera (NIRCam) time-series data on the integration-to-integration level. We find that 1/f noise can limit the precision of grism time series for two groups (230–1000 ppm depending on the extraction method and extraction parameters), but will average down like the square root of N frames/reads. The current NIRCam grism time-series mode is especially affected by 1/f noise because its GRISMR dispersion direction is parallel to the detector fast-read direction, but could be alleviated in the GRISMC direction. Care should be taken to include as many frames as possible per visit to reduce this 1/f noise source: thus, we recommend the smallest detector subarray sizes one can tolerate, four output channels, and readout modes that minimize the number of skipped frames (RAPID or BRIGHT2). We also describe a covariance-weighting scheme that can significantly lower the contributions from 1/f noise as compared to sum extraction. We evaluate the noise introduced by pre-amplifier offsets, random telegraph noise, and high dark current resistor capacitor (RC) pixels and find that these are correctable below 10 ppm once background subtraction and pixel masking are performed. We explore systematic error sources in a companion paper.

79 ASTRONOMY AND ASTROPHYSICS↗

A Novel Approach for Computing Rigid Body Motion Using Linear Accelerations

Here, a novel approach is presented for computing general rigid body motion based on a few known linear accelerations. This method utilizes linear acceleration data obtained from three distinct points on the body, all within a body-fixed reference frame. The only requirement is that the three chosen points must not be collinear. A system of differential-algebraic equations is derived, combining principles of rigid body kinematics with theory of the rotation group SO(3). These equations provide a framework for numerically computing various motion parameters, including angular velocity, angular acceleration, body orientation, velocity field, acceleration field, and displacement field. By numerically solving this system of equations, we can fully characterize rigid body motion in three-dimensional space. A numerical example is provided to demonstrate the practical implementation and efficacy of the proposed technique, illustrating its potential for accurate motion computation in various applications.

42 ENGINEERING↗

Extraction of Drell-Yan Angular Parameters in $pp$ Collisions with a 120 GeV Beam Energy Using a Deep-Learning Unfolding Algorithm

Dilepton production in pp collisions through the Drell-Yan process provides a crucial tool for studying the internal quark-gluon structure of the nucleon. By precisely measuring the $\cos2\phi$ asymmetry, where $\phi$ represents the azimuthal angle of the $l^{+}l^{-}$ pair in the Collins-Soper frame, we can gain valuable insights into the proton’s structure and the transverse momentum ($q_{T}$) dependence of the $\cos2\phi$ asymmetry. SeaQuest, a fixed-target Drell-Yan experiment at Fermilab, involved an unpolarized proton beam colliding with unpolarized LH$_{2}$ and LD$_{2}$ targets. Measurements obtained from experiments typically require corrections for detector inefficiencies, smearing, and acceptance. Traditionally, these corrections involve “unfolding” the detector-level measurements through matrix operations. However, in higher-dimensional phase space, these conventional methods fail to scale effectively. To overcome these limitations, we employ an unbinned unfolding method that utilizes deep neural networks for unfolding higher-dimensional phase space. In this presentation, we will explain the design of the neural network architecture, our training strategies, and outline our plans to achieve conclusive results.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Graph network heterogeneity predicts interplant wake losses

Wind plants generate large-scale wakes, which can affect the performance of neighboring installations. Such wakes are challenging to estimate due to the inherent complexity in modeling wake interactions between large quantities of turbines at various distances. Weighted directed graph networks can inform complex models by linking turbine pairs into chains of upstream and downstream neighbors for a given wind direction. A novel interpretation of the graph network adjacency matrix is proposed where each element of the matrix represents the cumulative impact of upstream turbines on an individual. In this study, wake losses were estimated with an engineering wake model across a range of inflow conditions for nine parametric variations of a system containing two neighboring wind plants. The parametric nature of the study isolates turbine spacing within the plant, separation distance between plants, and wind direction as the main drivers of wake losses. Spatial heterogeneity is computed from the weighted average adjacency matrix of each plant arrangement. The proposed method is orders of magnitude faster than wake modeling and does not require detailed turbine information or atmospheric conditions. Furthermore, the weighted average adjacency matrix provides insight on the spatial organization of wake losses at various scales. Plant heterogeneity is correlated with wake losses within and among plants. Framing wind plant wake interaction in terms of graph network spatial heterogeneity provides an efficient approach for predicting wake losses within and among neighboring wind plants with applications to other complex systems where wake interactions are key factor.

17 WIND ENERGY↗

Real World Use Case Evaluation of Radar Retro-reflectors for Autonomous Vehicle Lane Detection Applications

Lane detection plays a critical role in autonomous vehicles for safe and reliable navigation. Lane detection is traditionally accomplished using a camera sensor and computer vision processing. The downside of this traditional technique is that it can be computationally intensive when high quality images at a fast frame rate are used and has reliability issues from occlusion such as, glare, shadows, active road construction, and more. This study addresses these issues by exploring alternative methods for lane detection in specific scenarios caused from road construction-induced lane shift and sun glare. Specifically, a U-Net, a convolutional network used for image segmentation, camera-based lane detection method is compared with a radar-based approach using a new type of sensor previously unused in the autonomous vehicle space: radar retro-reflectors. This evaluation is performed using ground truth data, obtained by measuring the lane positions and transforming them into pixel coordinates. The performance of each method is assessed using the statistical R2 score, indicating the correlation between the detected lane lines and the ground truth. The results show that the U-Net camera-based method exhibits limitations in accurately detecting and aligning the lane lines, particularly in challenging scenarios. However, the radar-based lane detection method demonstrates a strong correlation with the ground truth which implies that the use of this sensor may improve current reliability issues from conventional camera lane detection approach. Furthermore, the study highlights the limitations of the U-Net model for camera lane detection, especially in scenarios with sun glare. This study shows that infrastructure-based radar retro-reflectors can improve autonomous vehicle lane detection reliability. The integration of different sensor modalities and the development of advanced computer vision algorithms are crucial for improving the accuracy, reliability, and energy efficiency of lane detection systems. Addressing these challenges contributes to the advancement of autonomous vehicles and the realization of safer and more efficient transportation systems.

Brown, Nicolas E.↗

HarDWR - Harmonized Water Rights Records

For a detailed description of the database of which this record is only one part, please see the HarDWR meta-record. Here we present a new dataset of western U.S. water rights records. This dataset provides consistent unique identifiers for each spatial unit of water management across the domain, unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of 7 broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of intersectoral water allocation changes through water markets (Grogan et al., in review). Specifically, the data were formatted for use as input to a process-based hydrologic model, WBM, with a water rights module (Grogan et al., in review). While this specific study motivated the development of the database presented here, U.S. west water management is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al, 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. west. The raw downloaded data for each state is described in Lisk et al. (in review), as well as here. The dataset is a collection of objects stored within an RDate file, stateWaterRightsHarmonized.RData. Each object either describes how one should interact with the other objects, or contains the harmonized water rights data. Here is each object described in detail: states: A character vector containing the state names for those states in which data was collected for. More importantly, the index of the state name is also the index in which that state's data can be found in the various following list objects. For example, if California is the third index in this object, the data for California will also be in the third index for each accompanying list. rightsByState_ground: A list of data frames with the cleaned ground water rights collected from each state. The column headers for each data frame are: waterRightID - The unique identifying ID of the water right, the same identifier as its state uses. basinNum - The alpha-numeric identifier of the WMA the record belongs to. priorityDate - The priority date associated with the right. allocatedFlow - The maximum flow of the allocation in cubic feet per second (ft3s-1). source - Whether the right is for surface water or groundwater. origWaterUse - The original stated water use from the state. waterUse - The water use category under the unified use categories established here. rightsByState_surface: A list of the cleaned surface water rights collected from each state. See rightsByState_ground for more details on how the data is formatted. fullRightsRecs: A list of the combined groundwater and surface water records for each state. Essentially, these lists are the merging of rightsByState_ground and rightsByState_surface by state. See rightsByState_ground for more details on how the data is formatted. projProj: The spatial projection used for map creation in the beginning of the project. Specifically, the World Geodetic System (WGS84) as a coordinate reference system (CRS) string in PROJ.4 format. wmaStateLabel: The name and/or abbreviation for what each state legally calls their WMAs. h2oUseByState: A list of spatial polygon data frames which contain the area(s) in which each water right is claimed to be used. It should be noted that not all water right records have a listed area(s) of use in this object. Currently, only Idaho and Washington provided valid data to be included in this object. h2oDivByState: A list of spatial points data frames which identifies the location of the Point of Diversion for the state's water rights. It should be noted that not all water right records have a listed Point of Diversion in this object. spatialWMAByState: A list of spatial polygon data frames which contain the spatial WMA boundaries for each state. The only data contained within the table are identifiers for each polygon. It is worth reiterating that Arizona is the only state in which the surface and groundwater WMA boundaries are not the same. wmaIDByState: A list which contains the unique ID values of the WMAs for each state. plottingDim: A character vector used to inform mapping functions for internal map making. Each state is classified as either "tall" or "wide", to maximize space on a typical 8x11 page.

Economics↗