Estimating the volume and age of water stored in global lakes using a geo-statistical approach

A novel approach for accurate quantification of lake residence time — Lake Kinneret as a case study

Ecosystem carbon (C) storage strongly regulates climate-C cycle feedback and is largely determined by both C residence time and C input from net primary productivity (NPP). However, spatial patterns of ecosystem C storage and its variation have not been well quantified in earth system models (ESMs), which is essential to predict future climate change and guide model development. We intended to evaluate spatial patterns of ecosystem C storage capacity simulated by ESMs as part of the 5th Climate Model Intercomparison Project (CMIP5) and explore the sources of multi-model variation from mean residence time (MRT) and/or C inputs. Five ESMs were evaluated, including C inputs (NPP and [gross primary productivity] GPP), outputs (autotrophic/heterotrophic respiration) and pools (vegetation, litter and soil C). ESMs reasonably simulated the NPP and NPP/GPP ratio compared with Moderate Resolution Imaging Spectroradiometer (MODIS) estimates except NorESM. However, all of the models significantly underestimated ecosystem MRT, resulting in underestimation of ecosystem C storage capacity. CCSM predicted the lowest ecosystem C storage capacity (~10 kg C m−2) with the lowest MRT values (14 yr), while MIROC-ESM estimated the highest ecosystem C storage capacity (~36 kg C m−2) with the longest MRT (44 yr). Ecosystem C storage capacity varied considerably among models, with larger variation at high latitudes and in Australia, mainly resulting from the differences in the MRTs across models. Our results indicate that additional research is needed to improve post-photosynthesis C-cycle modelling, especially at high latitudes, so that ecosystem C residence time and storage capacity can be appropriately simulated.

Residence times provide vital information on hydrological, geochemical, and ecological processes in watersheds. The common perception is that mean residence times in watersheds are very short, on the order of days to years. However, there is growing concern that longer residence times of centuries to millennia are not being captured by traditional surface water age‐dating methods. We hypothesize that if mean residence times are biased short, then weathering rates calculated from mean residence times will be forced unrealistically high to match observed solute concentrations. We test this hypothesis by calculating weathering rates from springs based upon residence times estimated using three different age‐dating methods. Observed solute concentrations require unrealistically large weathering rates if typical short residence times are employed as compared to rates derived from longer residence times. Residence time distributions in watersheds have substantially longer tails than previously thought, with implications for age‐dating methods and their interpretation to infer process behavior.

Information on the mean residence time and the residence time distribution is of importance when optimizing a continuous dryer. In this study, an industrial method for determining the mean residence time is developed. The produced method is benchmarked on a laboratory scale against the stop-and-empty method. The method, which uses LiCl as the tracer does not cause any disturbances in the biofuel drying or pelleting processe.

Staying afloat in the sensor data deluge

BackgroundDiversity patterns result from ecological to evolutionary processes operating at different spatial and temporal scales. Species trait variation determine the spatial scales at which organisms perceive the environment. Despite this knowledge, the coupling of all these factors to understand how diversity is structured is still deficient. Here, we review the role of ecological and evolutionary processes operating across different hierarchically spatial scales to shape diversity patterns of bats—the second largest mammal order and the only mammals with real flight capability.Main bodyWe observed that flight development and its provision of increased dispersal ability influenced the diversification, life history, geographic distribution, and local interspecific interactions of bats, differently across multiple spatial scales. Niche packing combined with different flight, foraging and echolocation strategies and differential use of air space allowed the coexistence among bats as well as for an increased diversity supported by the environment. Considering distinct bat species distributions across space due to their functional characteristics, we assert that understanding such characteristics in Chiroptera improves the knowledge on ecological processes at different scales. We also point two main knowledge gaps that limit progress on the knowledge on scale-dependence of ecological and evolutionary processes in bats: a geographical bias, showing that research on bats is mainly done in the New World; and the lack of studies addressing the mesoscale (i.e. landscape and metacommunity scales).ConclusionsWe propose that it is essential to couple spatial scales and different zoogeographical regions along with their functional traits, to address bat diversity patterns and understand how they are distributed across the environment. Understanding how bats perceive space is a complex task: all bats can fly, but their perception of space varies with their biological traits.

Model intercomparisons and evaluations against observations are essential for better understanding of models’ performance and for identifying the sources of uncertainty in their output. The terrestrial vegetation carbon simulated by 11 Earth system models (ESMs) involved in phase 5 of the Coupled Model Intercomparison Project (CMIP5) was evaluated in this study. The simulated vegetation carbon was compared at three distinct spatial scales (grid, biome, and global) among models and against the observations (an updated database from Olson et al.’s “Major World Ecosystem Complexes Ranked by Carbon in Live Vegetation: A Database”). Moreover, the underlying causes of the differences in the models’ predictions were explored. Model–data fit at the grid scale was poor but greatly improved at the biome scale. Large intermodel variability was pronounced in the tropical and boreal regions, where total vegetation carbon stocks were high. While 8 out of 11 ESMs reproduced the global vegetation carbon to within 20% uncertainty of the observational estimate (560 ± 112 Pg C), the simulated global totals varied nearly threefold between the models. The goodness of fit of ESMs in simulating vegetation carbon depended strongly on the spatial scales. Sixty-three percent of the variability in contemporary global vegetation carbon stocks across ESMs could be explained by differences in vegetation carbon residence time across ESMs (P < 0.01). The analysis indicated that ESMs’ performance of vegetation carbon predictions can be substantially improved through better representation of plant longevity (i.e., carbon residence time) and its respective spatial distributions.

Lakes have been highlighted as one of the largest natural sources of the greenhouse gas methane (CH4) to the atmosphere. However, global estimates of lake CH4 fluxes over the last 20 years exhibit widely different results ranging from 6 to 185 Tg CH4 yr−1, which is to a large extent driven by differences in lake areas and thaw season lengths used. This has generated uncertainty regarding both lake fluxes and the global CH4 budget. This study constrains global lake water CH4 emissions by using new information on lake area and distribution and CH4 fluxes distinguished by major emission pathways; ecoclimatic lake type; satellite‐derived ice‐free emission period length; and diel‐ and temperature‐related seasonal flux corrections. We produced gridded data sets at 0.25° latitude × 0.25° longitude spatial resolution, representing daily emission estimates over a full annual climatological cycle, appropriate for use in global CH4 budget estimates, climate and Earth System Models, bottom‐up biogeochemical models, and top‐down inverse model simulations. Global lake CH4 fluxes are 41.6 ± 18.3 Tg CH4 yr−1 with approximately 50% of the flux contributed by tropical/subtropical lakes. Strong temperature‐dependent flux seasonality and satellite‐derived freeze/thaw dynamics limit emissions at high latitudes. The primary emission pathway for global annual lake fluxes is ebullition (23.4 Tg) followed by diffusion (14.1 Tg), ice‐out and spring water‐column turnover (3.1 Tg), and fall water‐column turnover (1.0 Tg). These results represent a major contribution to reconciling differences between bottom‐up and top‐town estimates of inland aquatic system emissions in the global CH4 budget.

Abstract. Lakes and reservoirs are crucial elements of the hydrological and biochemical cycle and are a valuable resource for hydropower, domestic and industrial water use, and irrigation. Although their monitoring is crucial in times of increased pressure on water resources by both climate change and human interventions, publically available datasets of lake and reservoir levels and volumes are scarce. Within this study, a time series of variation in lake and reservoir volume between 1984 and 2015 were analysed for 137 lakes over all continents by combining the JRC Global Surface Water (GSW) dataset and the satellite altimetry database DAHITI. The GSW dataset is a highly accurate surface water dataset at 30 m resolution compromising the whole L1T Landsat 5, 7 and 8 archive, which allowed for detailed lake area calculations globally over a very long time period using Google Earth Engine. Therefore, the estimates in water volume fluctuations using the GSW dataset are expected to improve compared to current techniques as they are not constrained by complex and computationally intensive classification procedures. Lake areas and water levels were combined in a regression to derive the hypsometry relationship (dh ∕ dA) for all lakes. Nearly all lakes showed a linear regression, and 42 % of the lakes showed a strong linear relationship with a R2 > 0.8, an average R2 of 0.91 and a standard deviation of 0.05. For these lakes and for lakes with a nearly constant lake area (coefficient of variation < 0.008), volume variations were calculated. Lakes with a poor linear relationship were not considered. Reasons for low R2 values were found to be (1) a nearly constant lake area, (2) winter ice coverage and (3) a predominant lack of data within the GSW dataset for those lakes. Lake volume estimates were validated for 18 lakes in the US, Spain, Australia and Africa using in situ volume time series, and gave an excellent Pearson correlation coefficient of on average 0.97 with a standard deviation of 0.041, and a normalized RMSE of 7.42 %. These results show a high potential for measuring lake volume dynamics using a pre-classified GSW dataset, which easily allows the method to be scaled up to an extensive global volumetric dataset. This dataset will not only provide a historical lake and reservoir volume variation record, but will also help to improve our understanding of the behaviour of lakes and reservoirs and their representation in (large-scale) hydrological models.

Global lake volume estimates are scarce, highly variable, and poorly documented. We developed a rigorous method for estimating global lake depth and volume based on the Hurst coefficient of Earth's surface, which provides a mechanistic connection between lake area and volume. Volume‐area scaling based on the Hurst coefficient is accurate and consistent when applied to lake data sets spanning diverse regions. We applied these relationships to a global lake area census to estimate global lake volume and depth. The volume of Earth's lakes is 199,000 km3 (95% confidence interval 196,000–202,000 km3). This volume is in the range of historical estimates (166,000–280,000 km3), but the overall mean depth of 41.8 m (95% CI 41.2–42.4 m) is significantly lower than previous estimates (62–151 m). These results highlight and constrain the relative scarcity of lake waters in the hydrosphere and have implications for the role of lakes in global biogeochemical cycles.

The residence time measures the rate at which a pollutant escapes from a region of interest. Previous studies of urban ventilation have estimated the mean residence time from Eulerian data by assuming a spatially homogeneous pollutant field. Using a large-eddy simulation and a Lagrangian particle model, the residence and exposure times are calculated for an idealized street canyon in the skimming-flow region and a deep street canyon within a realistic urban area. For both domains, the mean residence time is on the order of a canyon circulation time scale, while the mean exposure time, which includes re-entrainment and characterizes the total time spent by a pollutant in a region of interest, is about 20% longer. Intensive quantities such as the Lagrangian visitation factor and return coefficient indicate that re-entrainment is modest. Probability distribution functions of the exposure and residence times are nearly exponential for both domains, in accord with pure diffusion and single-time-scale, vertical-exchange parameterizations. It is argued that, by analogy with Brownian motion, the mean residence and exposure times are set primarily by the mean circulation rather than the turbulence when the flow approximates that within a two-dimensional street canyon.

Estimating seasonal water budgets in global lakes by using multi-source remote sensing measurements

Welcome to this Special Issue of the Journal of Geoscience Education, dedicated to discussing Earth system science education: its present state and future directions. Due to the diversity and complexity of Earth system processes, scientists and educators commonly are required to comprehend and apply knowledge of the atmosphere, biosphere, geosphere, hydrosphere, and anthroposphere in their research and in the classroom. The exciting and integrative aspects of Earth system science enter with the recognition that none of these spheres occurs in isolation; instead, they interact to produce the Earth system, in a grand of the spheres. The symphony metaphor can be used to describe the concordant physical, biological, chemical and social processes that define conditions on our planet. Just as each instrument in a symphony works in concert with the others to make polyphonic music, so to do elements of air, water, land and fife act and interact to create the Earth system that operates in harmony on a planetary scale. Whether symphony or planet Earth, the ensemble of interrelated states ana processes produces a complexly woven music that collectively makes the group far more interesting and dynamic than any of the parts. Of course the metaphor has limitations, and there are important differences between a symphony and the Earth system, including issues of direction (e.g., lack of a score in the Earth system), scale and complexity. A student of the symphony has a fundamentally finite task when listening and examining the musical score to extract a theme, a melody or a variation. A student of music can even experiment with the score to examine the effect of individual instruments or sections on the final symphonic performance. The student of the Earth system, however, has a much more daunting task. The nearly infinite combined effects of a myriad of complex processes defy simple analysis, and direct, controlled experiments upon the system as a whole are impossible. Yet, careful observation of the Earth system coupled with an understanding of physical, chemical and biological principles has given rise to complex models of air, water, land and life processes that can be used to predict the state, process and evolution of the system overall. Indeed, the study of Earth system science can be considered exploration in itself as deeper or more subtle relationships and dependencies within and among the spheres emerge. Developing student understanding of these spheres and their linkages is a central focus of Earth system science. Hence, at its finest, Earth system science education engages scientists and educators in the collaborative interdisciplinary development and offering of courses and learning resources focused on understanding and application of Earth system and global change science in the classroom and laboratory. This special issue focuses on exploring exemplary courses, curricula, degree programs, learning resources and programs centered on Earth system science education. Papers include demonstration of effective technological tools, techniques facilitating systems thinking, and pedagogical approaches. Authors address diverse topics and questions including: How is Earth system science defined and what are appropriate strategies for conveying this concept to students? What are the most productive instructional technologies, and how and when are they best applied? What are effective means to teach students of the connectivity among spatial and temporal scales and on linkages among the spheres? Our solicitation expressed special interest in papers describing lessons learned in: developing and sharing content; utilizing Earth system science topics to engage students in science, technology, engineering and mathematics (STEM) learning; and in building working interdisciplinary partnerships, as well as papers that pursued formal evaluation of Earth system science learning materials and programs overall. …

Dynamic earth system and ecological controls of rainfall-initiated landslides

Lake water storage changes are important factors that influence the climate, hydrological cycle, and environments. However, long‐term estimation of global lake storage changes is challenging because historical in‐situ hydrological observations worldwide are rarely available. Benefiting from the laser altimeter ICESat and ICESat‐2, we comprehensively assessed water level and volume changes in global natural lakes larger than 10 km2 during 2003–2020. The 6,567 lakes observable by ICESat/ICESat‐2, which account for ∼94% of the total global lake volume, showed a total water storage increase of 10.88 ± 16.45 Gt/yr during 2003–2020, and the estimate reaches 16.12 ± 20.41 Gt/yr when also taking account of the remaining unobserved lakes. Despite water gains in most natural lakes, large lakes under dry and high water‐stress conditions experienced dramatic water loss in general. Presumably, these drying lakes may continue to shrink with a warming climate and continuously increasing water demands in the future without further action.