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Arctic lowlands are characterized by large numbers of small waterbodies, which are known to affect surface energy budgets and the global carbon cycle. Statistical analysis of their size distributions has been hindered by the shortage of observations at sufficiently high spatial resolutions. This situation has now changed with the high-resolution (<5 m) circum-Arctic Permafrost Region Pond and Lake (PeRL) database recently becoming available. We have used this database to make the first consistent, high-resolution estimation of Arctic waterbody size distributions, with surface areas ranging from 0.0001 km(2) (100 m(2)) to 1 km(2). We found that the size distributions varied greatly across the thirty study regions investigated and that there was no single universal size distribution function (including power-law distribution functions) appropriate across all of the study regions. We did, however, find close relationships between the statistical moments (mean, variance, and skewness) of the waterbody size distributions from different study regions. Specifically, we found that the spatial variance increased linearly with mean waterbody size (R-2 = 0.97, p < 2.2e-16) and that the skewness decreased approximately hyperbolically. We have demonstrated that these relationships (1) hold across the 30 Arctic study regions covering a variety of (bio)climatic and permafrost zones, (2) hold over time in two of these study regions for which multi-decadal satellite imagery is available, and (3) can be reproduced by simulating rising water levels in a high-resolution digital elevation model. The consistent spatial and temporal relationships between the statistical moments of the waterbody size distributions underscore the dominance of topographic controls in lowland permafrost areas. These results provide motivation for further analyses of the factors involved in waterbody development and spatial distribution and for investigations into the possibility of using statistical moments to predict future hydrologic dynamics in the Arctic.
Terrestrial gravimetry is increasingly used to monitor mass transport processes in geophysics boosted by the ongoing technological development of instruments. Resolving a particular phenomenon of interest, however, requires a set of gravity corrections of which the uncertainties have not been addressed up to now. In this study, we quantify the time domain uncertainty of tide, global atmospheric, large-scale hydrological, and nontidal ocean loading corrections. The uncertainty is assessed by comparing the majority of available global models for a suite of sites worldwide. The average uncertainty expressed as root-mean-square error equals 5.1nm/s(2), discounting local hydrology or air pressure. The correction-induced uncertainty of gravity changes over various time periods of interest ranges from 0.6nm/s(2) for hours up to a maximum of 6.7nm/s(2) for 6months. The corrections are shown to be significant and should be applied for most geophysical applications of terrestrial gravimetry. From a statistical point of view, however, resolving subtle gravity effects in the order of few nanometers per square second is challenged by the uncertainty of the corrections. Plain Language Summary Many scientists are exploring ways to benefit from gravity measurements in fields of high societal relevance such as monitoring of volcanoes or measuring the amount of water in underground. Any application of such new methods, however, requires careful preparation of the gravity measurements. The intention of the preparation process is to ensure that the measurements do not contain information about processes that are not of interest. For that reason, the influence of atmosphere, ocean, tides, and hydrology needs to be reduced from the gravity. In this study, we investigate how this reduction process influences the quality of the measurement. We found that the precision degrades especially owing to the hydrology. The ocean plays an important role at sites close to the coast and the atmosphere at sites located in mountains. The overall errors of the reductions may complicate a reliable use of gravity measurements in certain studies focusing on very small signals. Nevertheless, the precision of gravity reductions alone does not obstruct a meaningful use of gravity measurements in most research fields. Details specifying the reduction precision are provided in this study allowing scientist dealing with gravity measurements to decide if their signal of interest can be reliably resolved.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007–2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash–Sutcliffe efficiency of 0.72 and a Kling–Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
During the last few decades, the rapid separation of the Small Aral Sea from the isolated basin has changed its hydrological and ecological conditions tremendously. In the present study, we developed and validated the hybrid model for the Syr Darya River basin based on a combination of state-of-the-art hydrological and machine learning models. Climate change impact on freshwater inflow into the Small Aral Sea for the projection period 2007-2099 has been quantified based on the developed hybrid model and bias corrected and downscaled meteorological projections simulated by four General Circulation Models (GCM) for each of three Representative Concentration Pathway scenarios (RCP). The developed hybrid model reliably simulates freshwater inflow for the historical period with a Nash-Sutcliffe efficiency of 0.72 and a Kling-Gupta efficiency of 0.77. Results of the climate change impact assessment showed that the freshwater inflow projections produced by different GCMs are misleading by providing contradictory results for the projection period. However, we identified that the relative runoff changes are expected to be more pronounced in the case of more aggressive RCP scenarios. The simulated projections of freshwater inflow provide a basis for further assessment of climate change impacts on hydrological and ecological conditions of the Small Aral Sea in the 21st Century.
The Central Asian Pamir Mountains (Pamirs) are a high-altitude region sensitive to climatic change, with only few paleoclimatic records available. To examine the glacial-interglacial hydrological changes in the region, we analyzed the geochemical parameters of a 31-kyr record from Lake Karakul and performed a set of experiments with climate models to interpret the results. delta D values of terrestrial biomarkers showed insolation-driven trends reflecting major shifts of water vapor sources. For aquatic biomarkers, positive delta D shifts driven by changes in precipitation seasonality were observed at ca. 31-30, 28-26, and 17-14 kyr BP. Multiproxy paleoecological data and modelling results suggest that increased water availability, induced by decreased summer evaporation, triggered higher lake levels during those episodes, possibly synchronous to northern hemispheric rapid climate events. We conclude that seasonal changes in precipitation-evaporation balance significantly influenced the hydrological state of a large waterbody such as Lake Karakul, while annual precipitation amount and inflows remained fairly constant.