Water Resources Research, volume 61, issue 1

Temporal Variability in Reservoir Surface Area Is an Important Source of Uncertainty in GHG Emission Estimates

Carly Hyatt Hansen 1
Bilal Iftikhar 2
Rachel M. Pilla 1
Natalie A Griffiths 1
Paul G. Matson 1
Henriette I Jager 1
Publication typeJournal Article
Publication date2025-01-04
scimago Q1
wos Q1
SJR1.574
CiteScore8.8
Impact factor4.6
ISSN00431397, 19447973
Abstract

Ebullitive methane (CH4) emissions in lentic ecosystems tend to concentrate at river‐lake interfaces and within shallow littoral zones. However, inconsistent definitions of the littoral zone and static representations of the lake or reservoir surface area contribute to major uncertainties in greenhouse gas (GHG) emissions estimates, particularly in reservoirs with large water‐level fluctuations. This study examines temporal variation in littoral and total surface areas of US reservoirs and demonstrates how different methods and data sources lead to discrepencies in reservoir GHG emissions at large scales and over time. We also explore variability in remotely sensed water occurrence according to maximum surface area, reservoir purposes, and hydrologic regions. Notably, the largest relative variability in surface area is exhibited by small reservoirs with a maximum surface area <1 km2 and non‐hydroelectric reservoirs. Additionally, we use a case study of measured CH4 emissions from the southeastern United States (Douglas Reservoir) to illustrate the effects of varying surface area on reservoir‐wide GHG estimates. Upscaled CH4 emissions in Douglas Reservoir differed by nearly two‐fold depending on the source of total surface area data and whether estimates accounted for seasonal fluctuations in surface area. During seasonal drawdown in Douglas Reservoir, relative littoral area varies non‐linearly; periods of lower pool elevation (and thus larger relative littoral area) likely contribute disproportionately high CH4 emission rates compared to the commonly sampled summer season when water levels are at full‐pool elevation. Improved GHG monitoring and upscaling techniques require accounting for temporal variability in reservoir surface extent and littoral area.

Jager H.I., Pilla R.M., Hansen C.H., Matson P.G., Iftikhar B., Griffiths N.A.
Water (Switzerland) scimago Q1 wos Q2 Open Access
2023-11-27 citations by CoLab: 3 PDF Abstract  
Because methane is a potent greenhouse gas (GHG), understanding controls on methane emissions from reservoirs is an important goal. Yet, reservoirs are complex ecosystems, and mechanisms by which reservoir operations influence methane emissions are poorly understood. In part, this is because emissions occur in ‘hot spots’ and ‘hot moments’. In this study, we address three research questions, ‘What are the causal pathways through which reservoir operations and resulting water level fluctuations (WLF) influence methane emissions?’; ‘How do influences from WLF differ for seasonal drawdown and diurnal hydropeaking operations?’; and ‘How does understanding causal pathways inform practical options for mitigation?’. A graphical conceptual model is presented that links WLF in reservoirs to methane emissions via four causal pathways: (1) water-column mixing (2) drying–rewetting cycles, (3) sediment delivery and redistribution, and (4) littoral vegetation. We review what is known about linkages for WLF at seasonal and diurnal resolution, generate research questions, and hypothesize strategies for moderating methane emissions by interrupting each causal pathway. Those related to flow management involve basin-scale management of tributary flows, seasonal timing of hydropeaking (pathway #1), timing and the rate of drawdown (pathway #2). In addition, we describe how sediment (pathway #3) and vegetation management (pathway #4) could interrupt linkages between WLF and emissions. We demonstrate the strength of conceptual modeling as a tool for generating plausible hypotheses and suggesting mitigation strategies. Future research is needed to develop simpler models at appropriate timescales that can be validated and used to manage flow releases from reservoirs.
Hansen C.H., Matson P.G., Griffiths N.A.
2023-10-01 citations by CoLab: 3 Abstract  
Greenhouse gas (GHG) emissions from reservoirs are influenced by many factors, including the reservoir's morphology, watershed, and local climate. Failure to account for diversity in waterbody characteristics contributes to uncertainties in estimates of total waterbody GHG emissions and limits the ability to extrapolate patterns from one set of reservoirs to another. Hydropower reservoirs are of particular interest given recent studies that show variable - and sometimes very high - measurements and estimates of emissions. This study uses characteristics describing reservoir surface morphology and location within the watershed to identify US hydropower reservoir archetypes that represent the diversity of reservoir features relevant to GHG emissions. The majority of reservoirs are characterized by smaller watersheds, smaller surface areas, and lower elevations. Downscaled climate projections of temperature and precipitation mapped onto the archetypes show large variability in hydroclimate stresses (i.e., changes in precipitation and air temperature) within and across different reservoir types. Average air temperatures are projected to increase for all reservoirs by the end of the century, relative to historical conditions, while projected precipitation is much more variable across all archetypes. Variability in projected climate suggests that despite similar morphology-related traits, reservoirs may experience different shifts in climate, potentially resulting in a divergence in carbon processing and GHG emissions from historical conditions. Low representation in published GHG emission measurements among several reservoir archetypes (roughly 14 % of the population of hydropower reservoirs), highlights a potential limit to the generalization of current measurements and models. This multi-dimensional analysis of waterbodies and their local hydroclimate provides valuable context for the growing body of GHG accounting literature and ongoing empirical and modeling studies.
Kumar A., Kumar A., Chaturvedi A.K., Joshi N., Mondal R., Malyan S.K.
2023-04-03 citations by CoLab: 7 Abstract  
Rising need for various renewable and non-renewable energy resources became vital for developing countries to meet their rapid economic growth under an exponentially growing population scenario. The primary goal of COP-26 for climate change mitigation is to reduce greenhouse gas (GHG) emissions from different sectors. Because of their significant contribution to global warming, GHG emissions from hydroelectric reservoirs have been a contentious topic of discussion since the pre-industrial age. However, the exact methodology for quantification of GHG and important parameters affecting emission rate is difficult due to limited equipment facilities, techniques for GHG measurement, uncertainties in GHG emissions rate, insufficient GHG database, and significant spatio-temporal variability of emission in the global reservoirs. This paper discusses the current scenario of GHG emissions from renewable energy, with a focus on hydroelectric reservoirs, methodological know-how, the interrelationship between parameters impacting GHG emissions, and mitigation techniques. Aside from that, significant methods and approaches for predicting GHG emissions from hydroelectric reservoirs, accounting for GHG emissions, life cycle assessment, uncertainty sources, and knowledge gaps, have been thoroughly discussed.
Bonnema M., David C.H., Frasson R.P., Oaida C., Yun S.
Geophysical Research Letters scimago Q1 wos Q1 Open Access
2022-07-19 citations by CoLab: 16 Abstract  
Natural lakes and artificial reservoirs are important components of the Earth system and essential for freshwater, food, and energy. Relatively little is known about the variations of lake and reservoir surface area globally. For the first time, this study presents the global variation of lake and reservoir surface areas for all water bodies larger than 1 km2. Using radar remote sensing, we found that global aggregate area variations were only 2% of total surface area over a 3 year period. When considering the total surface area of shoreline regions that transition between land and water, these variations equaled 20% of total lake and reservoir surface area, largely driven by variations of smaller water bodies. Additionally, surface areas of reservoirs tends to be more variable than the surface area of lakes of similar size. The large surface area variations evidenced here, could have a previously underappreciated impact on the Earth System.
Jager H.I., Griffiths N.A., Hansen C.H., King A.W., Matson P.G., Singh D., Pilla R.M.
2022-07-01 citations by CoLab: 15 Abstract  
In the transition to low-carbon electricity, well-quantified estimates of carbon dynamics are needed to ensure that emissions reduction targets are achieved. We review the state of the science on carbon accounting for hydropower reservoirs and identify limitations and future solutions. Nearly all research on reservoir greenhouse-gas (GHG) emissions has focused on individual reservoirs in isolation without considering their position in a freshwater network draining organic matter from upstream watersheds or the coordinated operation of reservoir cascades. Second, carbon inventories have extrapolated from a small, non-probabilistic sample of highly variable measurements of GHG emissions to unsampled reservoirs. A stronger statistical foundation is needed to estimate a global inventory and its uncertainty. Third, attribution to hydropower is based on ranks assigned to reservoir purpose. Instead, the physical influence of hydropower on carbon dynamics could be directly measured. Fourth, current carbon-accounting practices neglect time. A time-varying approach would quantify variation in emissions for electricity portfolios from changes in the fuel mix at different times and account for ancillary services, i.e., the ability to support the grid when variable renewables are not available without using natural gas. Reservoirs also sequester a significant portion of inflowing carbon in sediments and slow the carbon cycle by delaying the return of carbon to the atmosphere for decades to centuries. Together, these refinements would help to illuminate pathways toward meeting energy demand with the longest-possible delay in returning carbon to the atmosphere and without adding ancient sources to the pool of carbon cycling through aquatic ecosystems. • Our review of reservoir carbon accounting suggested the following improvements: • Use carbon influxes as an upper limit on each reservoir's carbon footprint. • Quantify counterfactuals to facilitate attribution to reservoirs. • Assign credit for delaying the return of ecosystem carbon to the atmosphere. • Assign credit for hydropower effects on the electricity portfolio's footprint.
Kyzivat E.D., Smith L.C., Garcia‐Tigreros F., Huang C., Wang C., Langhorst T., Fayne J.V., Harlan M.E., Ishitsuka Y., Feng D., Dolan W., Pitcher L.H., Wickland K.P., Dornblaser M.M., Striegl R.G., et. al.
2022-06-06 citations by CoLab: 15 Abstract  
Areas of lakes that support emergent aquatic vegetation emit disproportionately more methane than open water but are under-represented in upscaled estimates of lake greenhouse gas emissions. These shallow areas are typically less than ∼1.5 m deep and can be detected with synthetic aperture radar (SAR). To assess the importance of lake emergent vegetation (LEV) zones to landscape-scale methane emissions, we combine airborne SAR mapping with field measurements of vegetated and open-water methane flux. First, we use Uninhabited Aerial Vehicle SAR data from the NASA Arctic-Boreal Vulnerability Experiment to map LEV in 4,572 lakes across four Arctic-boreal study areas and find it comprises ∼16% of lake area, exceeding previous estimates, and exhibiting strong regional differences (averaging 59 [50–68]%, 22 [20–25]%, 1.0 [0.8–1.2]%, and 7.0 [5.0–12]% of lake areas in the Peace-Athabasca Delta, Yukon Flats, and northern and southern Canadian Shield, respectively). Next, we account for these vegetated areas through a simple upscaling exercise using paired methane fluxes from regions of open water and LEV. After excluding vegetated areas that could be accounted for as wetlands, we find that inclusion of LEV increases overall lake emissions by 21 [18–25]% relative to estimates that do not differentiate lake zones. While LEV zones are proportionately greater in small lakes, this relationship is weak and varies regionally, underscoring the need for methane-relevant remote sensing measurements of lake zones and a consistent criterion for distinguishing wetlands. Finally, Arctic-boreal lake methane upscaling estimates can be improved with more measurements from all lake zones.
Khazaei B., Read L.K., Casali M., Sampson K.M., Yates D.N.
Scientific data scimago Q1 wos Q1 Open Access
2022-02-03 citations by CoLab: 55 PDF Abstract  
Waterbodies (natural lakes and reservoirs) are a critical part of a watershed’s ecological and hydrological balance, and in many cases dictate the downstream river flows either through natural attenuation or through managed controls. Investigating waterbody dynamics relies primarily on understanding their morphology and geophysical characteristics that are primarily defined by bathymetry. Bathymetric conditions define stage-storage relationships and circulation/transport processes in waterbodies. Yet many studies oversimplify these mechanisms due to unavailability of the bathymetric data. We developed a novel GLObal Bathymetric (GLOBathy) dataset of 1.4+ million waterbodies to align with the well-established global dataset, HydroLAKES. GLOBathy uses a GIS-based framework to generate bathymetric maps based on the waterbody maximum depth estimates and HydroLAKES geometric/geophysical attributes of the waterbodies. The maximum depth estimates are validated at 1,503 waterbodies, making use of several observed data sources. We also provide estimations for head-Area-Volume (h-A-V) relationships of the HydroLAKES waterbodies, driven from the bathymetric maps of the GLOBathy dataset. The h-A-V relationships provide essential information for water balance and hydrological studies of global waterbody systems. Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.16695070
Steyaert J.C., Condon L.E., W.D. Turner S., Voisin N.
Scientific data scimago Q1 wos Q1 Open Access
2022-02-03 citations by CoLab: 33 PDF Abstract  
There are over 52,000 dams in the contiguous US ranging from 0.5 to 243 meters high that collectively hold 600,000 million cubic meters of water. These structures have dramatically affected the river dynamics of every major watershed in the country. While there are national datasets that document dam attributes, there is no national dataset of reservoir operations. Here we present a dataset of historical reservoir inflows, outflows and changes in storage for 679 major reservoirs across the US, called ResOpsUS. All of the data are provided at a daily temporal resolution. Temporal coverage varies by reservoir depending on construction date and digital data availability. Overall, the data spans from 1930 to 2020, although the best coverage is for the most recent years, particularly 1980 to 2020. The reservoirs included in our dataset cover more than half of the total storage of large reservoirs in the US (defined as reservoirs with storage greater 0.1 km3). We document the assembly process of this dataset as well as its contents. Historical operations are also compared to static reservoir attribute datasets for validation. Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.17161415
Seekell D., Cael B., Norman S., Byström P.
Geophysical Research Letters scimago Q1 wos Q1 Open Access
2021-09-30 citations by CoLab: 18 Abstract  
The littoral zone varies in size among lakes from ∼3% to 100% of lake surface area. In this paper, we derive a simple theoretical scaling relationship that explains this variation, and test this theory using bathymetric data across the size spectra of freshwater lakes (surface area = 0.01–82,103 km2, maximum depth = 2–1,741 m). Littoral area primarily reflects the ratio of the maximum depth of photosynthesis to maximum lake depth. However, lakes that are similar in these characteristics can have different relative littoral areas because of variation in basin shape. Hypsometric (area-elevation) models that describe these patterns for individual lakes can be generalized among lakes to accurately predict the relative size of littoral habitat when there is incomplete bathymetric information. Collectively, our results provide simple rules for understanding patterns of littoral habitat size at the regional and global scales.
Calamita E., Siviglia A., Gettel G.M., Franca M.J., Winton R.S., Teodoru C.R., Schmid M., Wehrli B.
2021-06-14 citations by CoLab: 33 Abstract  
Significance Hydroelectric reservoirs emit substantial amounts of CO 2 , especially in the tropics. Since many such systems exist and many more will be built within decades, it is important to assess their role in the carbon cycle. A major source of emission that is rarely monitored and never at different timescales is the carbon released downstream of dams. We measured the seasonal and subdaily variability of CO 2 emission downstream of one of the world’s largest artificial reservoirs and find that its contribution is relevant for unbiased quantification of reservoir carbon budgets. These findings highlight the importance of subdaily variability in hydropower operation for downstream emission rates and call for appropriate analysis schemes to reassess the greenhouse gas footprint of this energy source.
Harrison J.A., Prairie Y.T., Mercier‐Blais S., Soued C.
Global Biogeochemical Cycles scimago Q1 wos Q1
2021-05-26 citations by CoLab: 60 Abstract  
Collectively, reservoirs constitute a significant global source of C-based greenhouse gases (GHGs). Yet, global estimates of reservoir carbon dioxide (CO2) and methane (CH4) emissions remain uncertain, varying more than four-fold in recent analyses. Here we present results from a global application of the Greenhouse Gas from Reservoirs (G-res) model wherein we estimate per-area and per-reservoir CO2 and CH4 fluxes, by specific flux pathway and in a spatially and temporally explicit manner, as a function of reservoir characteristics. We show: (a) CH4 fluxes via degassing and ebullition are much larger than previously recognized and diffusive CH4 fluxes are lower than previously estimated, while CO2 emissions are similar to those reported in past work; (b) per-area reservoir GHG fluxes are >29% higher than suggested by previous studies, due in large part to our novel inclusion of the degassing flux in our global estimate; (c) CO2 flux is the dominant emissions pathway in boreal regions and CH4 degassing and ebullition are dominant in tropical and subtropical regions, with the highest overall reservoir GHG fluxes in the tropics and subtropics; and (d) reservoir GHG fluxes are quite sensitive to input parameters that are both poorly constrained and likely to be strongly influenced by climate change in coming decades (parameters such as temperature and littoral area, where the latter may be expanded by deepening thermoclines expected to accompany warming surface waters). Together these results highlight a critical need to both better understand climate-related drivers of GHG emission and to better quantify GHG emissions via CH4 ebullition and degassing.
Keller P.S., Marcé R., Obrador B., Koschorreck M.
Nature Geoscience scimago Q1 wos Q1
2021-05-13 citations by CoLab: 102 Abstract  
Reservoir drawdown areas—where sediment is exposed to the atmosphere due to water-level fluctuations—are hotspots for carbon dioxide (CO2) emissions. However, the global extent of drawdown areas is unknown, precluding an accurate assessment of the carbon budget of reservoirs. Here we show, on the basis of satellite observations of 6,794 reservoirs between 1985 and 2015, that 15% of the global reservoir area was dry. Exposure of drawdown areas was most pronounced in reservoirs close to the tropics and shows a complex dependence on climatic (precipitation, temperature) and anthropogenic (water use) drivers. We re-assessed the global carbon emissions from reservoirs by apportioning CO2 and methane emissions to water surfaces and drawdown areas using published areal emission rates. The new estimate assigns 26.2 (15–40) (95% confidence interval) TgCO2-C yr−1 to drawdown areas, and increases current global CO2 emissions from reservoirs by 53% (60.3 (43.2–79.5) TgCO2-C yr−1). Taking into account drawdown areas, the ratio between carbon emissions and carbon burial in sediments is 2.02 (1.04–4.26). This suggests that reservoirs emit more carbon than they bury, challenging the current understanding that reservoirs are net carbon sinks. Thus, consideration of drawdown areas overturns our conception of the role of reservoirs in the carbon cycle. Globally, reservoirs are net emitters of carbon when drawdown areas are taken into account, according to an analysis of satellite observations of reservoir surface area.
Rosentreter J.A., Borges A.V., Deemer B.R., Holgerson M.A., Liu S., Song C., Melack J., Raymond P.A., Duarte C.M., Allen G.H., Olefeldt D., Poulter B., Battin T.I., Eyre B.D.
Nature Geoscience scimago Q1 wos Q1
2021-04-05 citations by CoLab: 567 Abstract  
Atmospheric methane is a potent greenhouse gas that plays a major role in controlling the Earth’s climate. The causes of the renewed increase of methane concentration since 2007 are uncertain given the multiple sources and complex biogeochemistry. Here, we present a metadata analysis of methane fluxes from all major natural, impacted and human-made aquatic ecosystems. Our revised bottom-up global aquatic methane emissions combine diffusive, ebullitive and/or plant-mediated fluxes from 15 aquatic ecosystems. We emphasize the high variability of methane fluxes within and between aquatic ecosystems and a positively skewed distribution of empirical data, making global estimates sensitive to statistical assumptions and sampling design. We find aquatic ecosystems contribute (median) 41% or (mean) 53% of total global methane emissions from anthropogenic and natural sources. We show that methane emissions increase from natural to impacted aquatic ecosystems and from coastal to freshwater ecosystems. We argue that aquatic emissions will probably increase due to urbanization, eutrophication and positive climate feedbacks and suggest changes in land-use management as potential mitigation strategies to reduce aquatic methane emissions. Methane emissions from aquatic systems contribute approximately half of global methane emissions, according to meta-analysis of natural, impacted and human-made aquatic ecosystems and indicating potential mitigation strategies to reduce emissions.
Shi W., Chen Q., Zhang J., Lu J., Chen Y., Pang B., Yu J., Van Dam B.R.
2021-03-10 citations by CoLab: 4
Pebesma E.
R Journal scimago Q2 wos Q1
2019-02-12 citations by CoLab: 2489 Abstract  
Simple features are a standardized way of encoding spatial vector data (points, lines, polygons) in computers. The sf package implements simple features in R, and has roughly the same capacity for spatial vector data as packages sp, rgeos and rgdal. We describe the need for this package, its place in the R package ecosystem, and its potential to connect R to other computer systems. We illustrate this with examples of its use. What are simple features? Features can be thought of as “things” or objects that have a spatial location or extent; they may be physical objects like a building, or social conventions like a political state. Feature geometry refers to the spatial properties (location or extent) of a feature, and can be described by a point, a point set, a linestring, a set of linestrings, a polygon, a set of polygons, or a combination of these. The simple adjective of simple features refers to the property that linestrings and polygons are built from points connected by straight line segments. Features typically also have other properties (temporal properties, color, name, measured quantity), which are called feature attributes. Not all spatial phenomena are easy to represent by “things or objects”: continuous phenoma such as water temperature or elevation are better represented as functions mapping from continuous or sampled space (and time) to values (Scheider et al., 2016), and are often represented by raster data rather than vector (points, lines, polygons) data. Simple feature access (Herring, 2011) is an international standard for representing and encoding spatial data, dominantly represented by point, line and polygon geometries (ISO, 2004). It is widely used e.g. by spatial databases (Herring, 2010), GeoJSON (Butler et al., 2016), GeoSPARQL (Perry and Herring, 2012), and open source libraries that empower the open source geospatial software landscape including GDAL (Warmerdam, 2008), GEOS (GEOS Development Team, 2017) and liblwgeom (a PostGIS component, Obe and Hsu (2015)). The need for a new package Package sf (Pebesma, 2017) is an R package for reading, writing, handling and manipulating simple features in R, reimplementing the vector (points, lines, polygons) data handling functionality of packages sp (Pebesma and Bivand, 2005; Bivand et al., 2013), rgdal (Bivand et al., 2017) and rgeos (Bivand and Rundel, 2017). However, sp has some 400 direct reverse dependencies, and a few thousand indirect ones. Why was there a need to write a package with the potential to replace it? First of all, at the time of writing sp (2003) there was no standard for simple features, and the ESRI shapefile was by far the dominant file format for exchanging vector data. The lack of a clear (open) standard for shapefiles, the omnipresence of “bad” or malformed shapefiles, and the many limitations of the ways it can represent spatial data adversely affected sp, for instance in the way it represents holes in polygons, and a lack of discipline to register holes with their enclosing outer ring. Such ambiguities could influence plotting of data, or communication with other systems or libraries. The simple feature access standard is now widely adopted, but the sp package family has to make assumptions and do conversions to load them into R. This means that you cannot round-trip data, as of: loading data in R, manipulating them, exporting them and getting the same geometries back. With sf, this is no longer a problem. A second reason was that external libraries heavily used by R packages for reading and writing spatial data (GDAL) and for geometrical operations (GEOS) have developed stronger support for the simple feature standard. A third reason was that the package cluster now known as the tidyverse (Wickham, 2017, 2014), which includes popular packages such as dplyr (Wickham et al., 2017) and ggplot2 (Wickham, 2016), does not work well with the spatial classes of sp: • tidyverse packages assume objects not only behave like data.frames (which sp objects do by providing methods), but are data.frames in the sense of being a list with equally sized column vectors, which sp does not do. The R Journal Vol. XX/YY, AAAA 20ZZ ISSN 2073-4859 CONTRIBUTED RESEARCH ARTICLE 2 • attempts to “tidy” polygon objects for plotting with ggplot2 (“fortify”) by creating data.frame objects with records for each polygon node (vertex) were neither robust nor efficient. A simple (S3) way to store geometries in data.frame or similar objects is to put them in a geometry list-column, where each list element contains the geometry object of the corresponding record, or data.frame “row”; this works well with the tidyverse package family.

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