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At least 235 records · Page 13

FTICR-MS, Sensor, and Environmental Data from 5 Streams Impacted by the 2020 Holiday Farm Fire Associated with: "Spatiotemporal controls on the delivery of dissolved organic matter to streams following a wildfire"

This data package is associated with the publication "Spatiotemporal Controls on the Delivery of Dissolved Organic Matter to Streams Following a Wildfire" submitted to Geophysical Research Letters (Roebuck et al., 2022). The study aims to understand storm induced transport of pyrogenic materials to streams impacted by varying degrees of burn severity. Time series samples (24 samples in 1-hour intervals) were collected at 5 sites within the McKenzie River Watershed (Oregon, USA) whose catchment were each completely engulfed by the 2020 Holiday Farm Fire. The samples were collected in November 2020 during the first major storm pulse following the conclusion of the wildfire. Samples were characterized for dissolved organic carbon, total dissolved nitrogen, and by ultra-high resolution mass spectrometry. In situ turbidity data also collected.This data package contains 4 primary folders that include the following: 1) Metadata, 2) EnvData (Environmental Data), 3) SensorData, and 4) FTICR_SupportingData. The package contains a single file-level metadata (flmd) file. Each primary folder also contains individual data dictionaries (dd) to define and provide descriptors of column/row headers and data flags. The FTICR_SupportingData, folder 4, contains raw, unprocessed FTICR-MS Data files in addition to a csv containing processed FTICR-MS data. This package contains the following file types: csv, xml, pdf.

54 ENVIRONMENTAL SCIENCES↗

Spatial Study 2022: Surface Water Samples, Cotton Strip Degradation, and Hydrologic Sensor Data across the Yakima River Basin, Washington, USA (v3)

This dataset supports a broader study examining the drivers of spatial variability in sediment respiration rates in the Yakima River Basin. The dataset provides data and photos generated from sample collection during the same one-week period at 48 sites within multiple rivers throughout the Yakima River Basin in Washington, USA. The contents include surface water geochemistry data; river substrate grain size photos; stream depth data; manual chamber open channel respiration data; and field metadata (including qualitative information on instream and river corridor characteristics). Grain size photos can be used to improve estimates of channel substrate D50 data. The dataset also includes tensile strength and photos from cotton strip field degradation experiments; five-week sensor time series temperature, dissolved oxygen, pressure, pH, specific conductance, chlorophyll A, and turbidity data; plots of the sensor data; and R scripts used to generate the plots. Samples collected during this study were labeled as “Second Spatial Study” or “SSS.” A subset of data from the SSS samples were published in the contiguous United States (CONUS)-Scale Model-Sample (CM) study data package available at https://data.ess-dive.lbl.gov/view/doi:10.15485/1923689 that presents data from across the CONUS. SSS data published in the CM data package were not included in this data package. They include dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC), total nitrogen (TN), grain size, aerobic sediment respiration, dissolved oxygen (DO), and temperature. Parent IDs and Site IDs are consistent between the SSS and CM data packages, and they can be mapped directly so data across packages can be used together. Additionally, sensor data from a similar 2021 spatial study can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052 and 2021 sample data can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1898914. The 2021 spatial study had some sites in common with this 2022 spatial study. This dataset is comprised of three photo folders and one main data folder with six subfolders. The photo folders contain photographs and videos of cotton strip retrieval and sediment quadrats. The main data folder consists of (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) total suspended solids (TSS) data and cotton strip tensile strength data and averages; (5) field protocol; (6) readme; (7) methods codes; (8) international generic sample number (IGSN) mapping file; (9) sensor installation methods summary; (10) stream depth and averages; and (11) Ultrameter data and averages. The Sonar subfolder consists of Sonar time-series depth data and a processing script. The BarotrollAtm, DepthHOBO, MantaRiver, miniDOT, and miniDOTManualChamber subfolders contain time-series data, plots, and summary files. All files are .csv, .pdf, .txt, .R, .Rmd, .jpg, .jpeg, .AVI, .mp4, or .mov. The data package was originally published in April 2023. It was updated in August 2023 (v2; modified files) and September 2024 (v3; modified files). See the change history section in the readme for details. We acknowledge the Yakama Nation as owners and caretakers of the lands where we collected these data. We thank the Confederated Tribes and Bands of the Yakama Nation Tribal Council and Yakama Nation Fisheries for working with us to facilitate sample collection and optimization of data usage according to their values and worldview.

54 ENVIRONMENTAL SCIENCES↗

Yakima River Basin Temporal Study: Sensor and Sample Data from Wenas Creek following the Evans Canyon Fire in Washington, USA

The Evans Canyon Fire occurred in Washington in August 2020 and burned 76,000 acres of the semi-arid shrub-steppe landscape at low to moderate severities. This fire burned across the Wenas Creek watershed, allowing for a sampling design that included a portion of the stream within the burned area and a reference site upstream of the burn. Monthly data was collected at an unburned (W10) and burned (W20) site from November 2020 to August 2022 for in situ hydrological and water chemistry sensor data, handheld sensor water chemistry data, general environmental context photos, and field metadata. This dataset is comprised of one folder with field photos and one main data folder containing (1) sensor and sample field protocols; (2) file-level metadata (flmd); (3) data dictionary (dd); (4) international geo-sample number (IGSN) mapping file; (5) field metadata; (6) readme; (7) methods codes; (8) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (9) total nitrogen (TN); (10) total suspended solids (TSS); (11) sensor data (specific conductance, pH, total dissolved solids, temperature, pressure, dissolved oxygen, and turbidity) averages; and (12) sensor installation methods. All files are .csv, .jpg, .jpeg, or .pdf.

54 ENVIRONMENTAL SCIENCES↗

Water quality data collected from the Muskegon River (MI, USA) using AquaBOT June-July 2024.

This dataset contains processed output from AquaBOT, which combines 30-second interval measurements of GPS location and YSI water quality parameters (temperature (degrees Celsius), dissolved oxygen (mg/l), specific conductance(microSiemens/cm at 25 degrees Celsius), and turbidity (NTU)), for 3 sections of the Muskegon River in Michigan, USA. The file aquabot2024_MuskegonRiver.csv has information on locations, dates and times, and observations. The data were processed by removing observations recorded before and after AquaBOT was in the water and observations where no data values were recorded. No other QA/QC was done. This research was performed as part of the DOE Research Development and Partnership Pilot award “Expanding Collaborative Capacity to Address Climate Resiliency in the Great Lakes Region”, which aims to expand collaborations between researchers at Central Michigan University and U.S. Department of Energy labs and projects focused on enhancing climate resilience in Great Lakes communities and ecosystems.

54 ENVIRONMENTAL SCIENCES↗

Subsurface Spectroscopy in Heterogeneous Materials Using Self-Healing Laser Beams

Self-healing optical beams are a class of propagation modes that can recover their beam shapes after distortion or partial blockage. This self-healing property makes them attractive for use in applications involving turbid media as they can—in theory—penetrate further into these materials than standard Gaussian beams. In this paper, we characterize the propagation of two different self-healing beams (Bessel and Airy) through a solid scattering material with different scatterer concentrations and find that both beams do recover after scattering for samples below a threshold scatterer concentration. Additionally, we test the applicability of both beam shapes for improved sub-surface spectroscopy in heterogeneous materials using fluorescent particles and find that there is an average fluorescence intensity enhancement of 1.3× using self-healing beams versus a standard Gaussian beam.

47 OTHER INSTRUMENTATION↗

Hardware Selection and Performance of Low-Cost Fluorometers

Access to and extensive use of fluorometric analyses is limited, despite its extensive utility in environmental transport and fate. Wide-spread application of fluorescent tracers has been limited by the prohibitive costs of research-grade equipment and logistical constraints of sampling, due to the need for high spatial resolutions and access to remote locations over long timescales. Recently, low-cost alternatives to research-grade equipment have been found to produce comparable data at a small fraction of the price for commercial equipment. Here, we prototyped and benchmarked performance of a variety of fluorometer components against commercial units, including performance as a function of tracer concentration, turbidity, and temperature, all of which are known to impact fluorometer performance. While component performance was found to be comparable to the commercial units tested, the best configuration tested obtained a functional resolution of 0.1 ppb, a working concentration range of 0.1 to >300 ppb, and a cost of USD 59.13.

42 ENGINEERING↗

Multi-Band Atmospheric Correction Algorithm for Ocean Color Retrievals

NASA's current Atmospheric Correction (AC) algorithm for ocean color utilizes two bands and their ratio in the Near Infrared (NIR) to estimate aerosol reflectance and aerosol type. The algorithm then extrapolates the spectral dependence of aerosol reflectance to the visible wavelengths based on modeled spectral dependence of the identified aerosol type. Future advanced ocean color sensors, such as the Ocean Color Instrument (OCI) that will be carried on the Plankton, Aerosol, Cloud, and ocean Ecosystem (PACE) satellite, will be capable of measuring the hyperspectral radiance from 340 to 890 nm at 5-nm spectral resolution and at 7 discrete Short-wave Infrared (SWIR) channels: 940, 1038,1250, 1378, 1615, 2130, and 2260 nm. To optimally employ this unprecedented instrument capability, we propose an improved AC algorithm that utilizes all atmospheric-window channels in the NIR to SWIR spectral range to reduce the uncertainty in the AC process. A theoretical uncertainty analysis of this, namely Multi-Band AC (MBAC), indicates that the algorithm can reduce the uncertainty in remote sensing reflectance (Rrs) retrievals of the ocean caused by sensor random noise. Furthermore, in optically complex waters, where the NIR signal is affected by contributions from highly-reflective turbid waters, the MBAC algorithm can be adaptively weighted to the strongly-absorbing SWIR channels to enable improved ocean color retrievals in coastal waters. We provide here a description of the algorithm and demonstrate the improved performance in ocean color retrievals, relative to the current NASA standard AC algorithm, through comparison with field measurements and assessment of propagated uncertainties in applying the MBAC algorithm to MODIS and simulated PACE OCI data.

PACE↗

Stream discharge and water quality data for East Fork Poplar Creek beginning 2012

This data note describes 15-min discharge and in situ water quality data at two locations along East Fork Poplar Creek in east Tennessee, USA. Data records include temperature, gauge height, water surface elevation above mean sea level, and volumetric discharge. Water quality measurements include temperature, specific conductance, pH, dissolved oxygen (percent saturation and concentration), turbidity, and less extensive fDOM data at one site. The data records begin in 2012 at one site and 2015 at the second site; monitoring at both sites is ongoing (as of 2021). The goal of this data collection is to improve understanding of watershed functions, hydrologic dynamics, and material flux. The data will contribute to site conceptual and numerical models, exposure and risk evaluation, remediation selection and design, and performance monitoring. The data are publicly available and can be accessed via unique url or DOI.

54 ENVIRONMENTAL SCIENCES↗

A Review of Factors Affecting the Susceptibility of Juvenile Salmonids to Avian Predation

Abstract We reviewed studies of piscivorous colonial waterbird predation on juvenile salmonids to synthesize current knowledge of factors affecting fish susceptibility to avian predators. Specifically, we examined peer-reviewed publications and reports from academic, governmental, and nongovernmental agencies to identify commonalities and differences in susceptibility of salmonids to avian predation, with a focus on mark–recovery studies in the Columbia River basin. Factors hypothesized to influence salmonid susceptibility to avian predation were grouped into four general categories: (1) salmonid species and populations, (2) environmental factors, (3) prey density, predator density, and migration timing, and (4) prey characteristics. Our review focused on predation by Caspian terns Hydroprogne caspia, double-crested cormorants Nannopterum auritum, and gull species Larus spp. as these are the most well-studied avian predators of salmonids. Results indicated that predator–prey interactions varied across salmonid species and populations and species of avian predator. Inferences across studies supported multiple hypotheses regarding predator–prey dynamics, including environmental factors that influence prey exposure to predators (e.g., river flows, turbidity, alternative prey), variation in predator and prey abundances, predator characteristics (e.g., foraging behavior, colony location), and prey characteristics (e.g., fish length, condition). Mark–recovery studies of avian predation on fish populations have greatly improved our understanding of the factors affecting fish susceptibility to avian predation, the relative contributions of abiotic and biotic factors to predation susceptibility, and the extent to which avian predation affects fish survival and the viability of prey populations. Future studies that jointly model predation and survival and the factors affecting those processes will further broaden our understanding of predator–prey dynamics and directly evaluate the effects of predation on prey population dynamics.

Hostetter, Nathan J. (ORCID:0000000160752157)↗

Effects of Livestock Exclusion on Stream Habitat and Aquatic Biota: A Review and Recommendations for Implementation and Monitoring

Abstract To inform riparian restoration, research, and monitoring and to provide management recommendations, we reviewed published studies evaluating the physical and biological effectiveness of livestock exclusion and grazing reduction on various metrics in riparian and aquatic areas. We identified 95 North American studies that reported the effects of livestock grazing reduction on physical habitat (channel morphology, mesohabitats, substrate, and bank stability), biological assemblages (riparian vegetation, macroinvertebrates, fish, and birds), and water quality metrics (temperature, nitrates, phosphorus, and turbidity). Most studies reported that methods to reduce or exclude livestock decreased channel width, width-to-depth ratio, bank erosion, soil bulk density, bare ground, water temperature, nitrogen, and phosphorus and increased riparian vegetation (cover, height, productivity, biomass, and abundance), riparian bird abundance, and young-of-the-year fishes. Results for channel depth, instream substrate, mesohabitats, water depth, juvenile and adult fishes, and macroinvertebrates showed no consistent response to exclusion. Project success was influenced by the time since exclusion; whether there was complete exclusion or continued grazing; and local climate, geology, and soils. Apart from bank erosion and stability, most of the physical and biological metrics took more than a decade to respond to livestock exclusion. However, coupling exclusion with planting and other restoration measures decreased the recovery time. Complete exclusion of livestock produced more consistent improvements in riparian condition and other metrics than rest–rotation or other grazing management strategies. Understanding how physical and biological metrics respond to livestock exclusion will require (1) focused, long-term studies using before–after or before–after, control–impact designs; and (2) monitoring of metrics that most consistently respond to exclusion. Ultimately, the design of exclusions should be driven by local climate, geology, biophysical conditions, and management history. Our results highlight the need for watershed-scale approaches to excluding livestock from broad areas and the need for implementation monitoring to ensure that fencing and other exclusion measures continue to exclude livestock and produce the desired responses.

Krall, Michelle↗

Monitoring water quality in the lower Kansas River using remote sensing

Abstract We demonstrate how to combine remote sensing data from satellite imagery (Sentinel‐2) with in situ water quality gauging (USGS Super Gages and the Gybe hyperspectral radiometer) to create spatially dense maps of water quality parameters (chlorophyll‐a concentration, turbidity, and nitrate plus nitrite concentration) along the lower Kansas River. The water quality maps are created using locally tuned models of the target water quality parameters, and this study describes the steps used to design, calibrate, and validate the empirical correlations. Water quality parameters such as chlorophyll‐a concentration are correlated with well‐studied absorption and scattering features in the visible spectrum (roughly 400–700 nm). Nutrients (such as nitrate plus nitrite concentration) lack strong absorption features in the visible spectrum, and in those cases we describe a novel surrogate data modeling approach that identifies overlapping water parcels between the in situ gauging and the remote sensing imagery. Measurements from the overlapping water parcels yield excellent correlations () for the target water quality parameters for limited windows of time (or limited sections of river reaches). Examples are provided illustrating how the water quality maps can be used to track river inputs from ungauged sources (such as creeks), or reveal the mixing patterns at the confluences.

Tufillaro, Nicholas↗

Electrocoagulation of high-salinity produced water: lessons learned from its early applications in unconventional reservoir plays

Ample research has demonstrated that electrocoagulation is a versatile technology capable of facilitating the removal of a wide range of physical, biological, organic, and inorganic constituents such as suspended solids, turbidity, bacteria, viruses, oil and grease, organic carbon (including chemical and biological oxygen demand), silica, fluoride, and so on. Despite its purported advantages and extensive lab-scale evaluations, it has not yet been widely adopted for water and wastewater treatment and reuse at commercial scale. This is symptomatic of a chasm between its technological capabilities on one hand and field performance and reputation on the other. Herein, we opine as to why this might be the case using our collective experiences with the oil and gas industry as an exemplar. In this study, we highlight scientific, technological, engineering, and business issues that need to be addressed to realize the full potential of this promising technology.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Earthquake-triggered submarine canyon flushing transfers young terrestrial and marine organic carbon into the deep sea

Submarine canyons transfer substantial amounts of sediment and organic carbon (OC) into the deep ocean, nourishing deep-sea ecosystems and contributing to the global carbon cycle through OC burial and sequestration. Tracking lateral OC transport through submarine canyon systems is challenged by the deep-ocean setting, difficulties with constraining episodic depositional events, and the need to assess the composition and age of marine and terrestrial organic matter. We apply innovative parallel ramped pyrolysis oxidation accelerator mass spectrometry and pyrolysis-gas chromatography-mass spectrometry with isotope analyses to track OC age and sources in the 2016 Kaikoura earthquake-triggered, canyon-flushing event that deposited along >1300 km of a submarine canyon-channel system, offshore Aotearoa New Zealand. Specifically, these techniques allow us to determine the ages, sources, and partitioning of OC within the Kaikoura turbidite deposit and test hypotheses of how submarine canyon systems contribute to lateral OC flux and burial. Our results show that, despite considerable canyon floor erosion, substantial amounts of young OC were flushed into the deep sea, with relatively little (~2%) pre-Holocene OC contributions. Even without a direct connection between rivers and submarine canyons, most (~55%) of the OC in the Kaikoura event bed is from terrestrial sources. However, the deposit also contains substantial amounts (~22%) of marine-derived OC and ~23% of the material is of unassignable origin. Particle sorting imparts variability on the age and composition of OC within turbidite deposits and along the turbidity current flow path. Terrestrial-derived OC is preferentially older than marine-derived OC and concentrated in coarser particle sizes found more commonly at the deposit base and in proximal settings. Young, marine-derived OC is concentrated at the surface of the deposits and tends to be enriched in finer particle sizes. Such OC partitioning in turbidites supports the relevance of depositional models for predicting and quantifying distribution of OC in deep-sea deposits. Earthquake-triggered, canyon flushing events and resulting turbidites enhance OC burial efficiency and can sequester OC effectively, contributing an important carbon sink to the sedimentary carbon cycle.

54 ENVIRONMENTAL SCIENCES↗

The influence of submarine canyons-related processes on recent benthic foraminiferal distribution, Espírito Santo Basin, Southeastern Brazil

The complex topography of submarine canyons may result in different composition of benthic foraminifera assemblages. To understand how trophic, hydrological and sedimentological conditions in submarine canyons can influence the distribution of benthic foraminifera, and to use this information to corroborate paleoenvironmental interpretations for the Holocene, we investigated recent benthic foraminiferal assemblages (total fauna >63 μm) and sedimentological data in two canyons (CANWN and CAND) in the Espírito Santo Basin (ESB) between 18°20' and 21°20' S. Surface sediment samples (0–2 cm) were collected inside the canyons (150 to 1300 m water depth) and in shelf-slope adjacent transects (50 to 1300 m water depth). The density, taxonomic diversity, and assemblage composition of benthic foraminifera change with depth and location. The distinct ecological preferences of the most abundant taxa allowed us to recognize five benthic foraminiferal groups. Three groups (V, III, and I) are present in different bathymetric sectors; Group V: outer shelf (50 m), Group III: upper, and middle – lower slope (150 to 400 m), and Group I: middle – lower slope (1000 to 1300 m). Groups II and IV show no characteristic bathymetric distribution and are present only in CAND and in CANWN, respectively. Group V consists of Hanzawaia boueana, Peneroplis planatus, and Quinqueloculina lamarckiana; Group III is dominated by Globocassidulina rossensis and Trifarina spp.; Group I consists of Globocassidulina crassa, Bolivina lowmani, Gavelinopsis versiformis, Alabaminella weddellensis, and Epistominella exigua. The main species in Group II (CAND, 150, 1000 to 1300 m) are Trifarina angulosa, Globocassidulina subglobosa, and Discorbis vilardeboanus. Group IV (middle – lower CANWN, 1000 to 1300 m), consists mainly of agglutinated species Glomospira charoides, Rhabdammina abyssorum, and Psammosphaera fusca. Further, our data suggest that the quantity (and quality) of food supply, hydrodynamic conditions and sediment properties are the main drivers controlling the bathymetric distribution of benthic foraminiferal assemblages in both canyons. The middle – lower CANNW revealed unstable trophic conditions, related to terrigenous sediment input due to turbidity currents. In CAND, the foraminiferal assemblages ecology indicated sufficient organic matter supply that favors species establishment and diversity, indicating a more productive and less unstable environment than in CANWN.

58 GEOSCIENCES↗

Hydrate-bearing sands in the Terrebonne Basin record the transition from ponded deposition to bypass in the deep-water Gulf of Mexico

Here, we integrated well and seismic data to interpret the stratigraphic architecture and the paleogeographic evolution of two hydrate-bearing sand reservoirs in the Terrebonne Basin in the deep-water Gulf of Mexico. These sands were deposited during the final stage of ponded fill within the Terrebonne Basin. The Green sand filled the final accommodation in the basin as a perched apron; it was formed coincidentally with downstream erosion and sediment bypass which cut through a canyon formed on the southeastern edge of the basin. Subsequently, a low energy turbidite channel continued to bypass sediment through the basin and aggrade. The Orange sand was then deposited as a second perched apron and it was once again incised by the low energy turbidite channel. The Green and Orange sands are regional sheet sands that extend and thicken deep into the Terrebonne Basin. They provide a connected regional aquifer that captured and focused gas migration to the crest of the structure where hydrate was formed. These sands were formed by large, unconfined, turbidity flows. We envision that they will be composed of coarser grained deposits relative to previously explored hydrate reservoirs within levee deposits. As such, they have the potential to be relatively coarse grained and hence have higher permeability: a condition favorable to production of hydrate deposits.

3D seismic interpretation↗

Real-time monitoring and prediction of water quality parameters and algae concentrations using microbial potentiometric sensor signals and machine learning tools

We report the overarching hypothesis of this study was that temporal microbial potentiometric sensor (MPS) signal patterns could be used to predict changes in commonly monitored water quality parameters by using artificial intelligence/machine learning tools. To test this hypothesis, the study first examines a proof of concept by correlating between MPS's signals and high algae concentrations in an algal cultivation pond. Then, the study expanded upon these findings and examined if multiple water quality parameters could be predicted in real surface waters, like irrigation canals. Signals generated between the MPS sensors and other water quality sensors maintained by an Arizona utility company, including algae and chlorophyll, were collected in real time at time intervals of 30 min over a period of 9 months. Data from the MPS system and data collected by the utility company were used to train the ML/AI algorithms and compare the predicted with actual water quality parameters and algae concentrations. Based on the composite signal obtained from the MPS, the ML/AI was used to predict the canal surface water's turbidity, conductivity, chlorophyll, and blue-green algae (BGA), dissolved oxygen (DO), and pH, and predicted values were compared to the measured values. Initial testing in the algal cultivation pond revealed a strong linear correlation (R 2 = 0.87) between mixed liquor suspended solids (MLSS) and the MPSs' composite signals. The Normalized Root Mean Square Error (NRMSE) between the predicted values and measured values were <6.5%, except for the DO, which was 10.45%. The results demonstrate the usefulness of MPSs to predict key surface water quality parameters through a single composite signal, when the ML/AI tools are used conjunctively to disaggregate these signal components. The maintenance-free MPS offers a novel and cost-effective approach to monitor numerous water quality parameters at once with relatively high accuracy.

54 ENVIRONMENTAL SCIENCES↗

Evaluation of clear-sky and satellite-derived irradiance data for determining the degradation of photovoltaic system performance

Knowing the degradation in performance of a photovoltaic (PV) system over time is important for estimating the lifetime energy produced and the financial return. A key parameter for normalizing performance and determining degradation is the plane-of-array (POA) irradiance. Because accurate long-term POA measurements are not always readily available, three methods of providing irradiance data for determining the degradation rate of PV systems were evaluated—a method using irradiance data modeled with the Ineichen clear-sky model and monthly Linke turbidity coefficients, a method using the supplemental clear-sky irradiance data from the National Solar Radiation Data Base (NSRDB), and a method using the NSRDB solar irradiance data for both cloudy and clear-sky conditions (all-sky). The irradiance data from the three methods were evaluated using measured irradiance data from 1998 through 2018 for the seven-station SURFRAD network and for 3-, 5-, and 10-year periods that might be used for evaluating PV system performance. Only the two clear-sky methods for the 10-year periods had less uncertainty with respect to determining PV system degradation than the expected median degradation rate for PV systems of -0.5%/year to -0.6%/year. Shorter periods and the all-sky method had larger uncertainties, making their use questionable for determining the degradation rates of PV systems.

14 SOLAR ENERGY↗