Greening vs browning? Surface water cover mediates how tundra and boreal ecosystems respond to climate warming

Abstract. The world's largest continental shelf, the East Siberian Shelf Sea, receives substantial input of terrestrial organic carbon (terr-OC) from both large rivers and erosion of its coastline. Degradation of organic matter from thawing permafrost in the Arctic is likely to increase, potentially creating a positive feedback mechanism to climate warming. This study focuses on the Buor-Khaya Bay (SE Laptev Sea), an area with strong terr-OC input from both coastal erosion and the Lena river. To better understand the fate of this terr-OC, molecular (acyl lipid biomarkers) and isotopic tools (stable carbon and radiocarbon isotopes) have been applied to both particulate organic carbon (POC) in surface water and sedimentary organic carbon (SOC) collected from the underlying surface sediments. Clear gradients in both extent of degradation and differences in source contributions were observed both between surface water POC and surface sediment SOC as well as over the 100 s km investigation scale (about 20 stations). Depleted δ13C-OC and high HMW/LMW n-alkane ratios signaled that terr-OC was dominating over marine/planktonic sources. Despite a shallow water column (10–40 m), the isotopic shift between SOC and POC varied systematically from +2 to +5 per mil for δ13C and from +300 to +450 for Δ14C from the Lena prodelta to the Buor-Khaya Cape. At the same time, the ratio of HMW n-alkanoic acids to HMW n-alkanes as well as HMW n-alkane CPI, both indicative of degradation, were 5–6 times greater in SOC than in POC. This suggests that terr-OC was substantially older yet less degraded in the surface sediment than in the surface waters. This unusual vertical degradation trend was only recently found also for the central East Siberian Sea. Numerical modeling (Monte Carlo simulations) with δ13C and Δ14C in both POC and SOC was applied to deduce the relative contribution of – plankton OC, surface soil layer OC and yedoma/mineral soil OC. This three end-member dual-carbon-isotopic mixing model suggests quite different scenarios for the POC vs SOC. Surface soil is dominating (63 ± 10 %) the suspended organic matter in the surface water of SE Laptev Sea. In contrast, the yedoma/mineral soil OC is accounting for 60 ± 9 % of the SOC. We hypothesize that yedoma-OC, associated with mineral-rich matter from coastal erosion is ballasted and thus quickly settles to the bottom. The mineral association may also explain the greater resistance to degradation of this terr-OC component. In contrast, more amorphous humic-like and low-density terr-OC from surface soil and recent vegetation represents a younger but more bioavailable and thus degraded terr-OC component held buoyant in surface water. Hence, these two terr-OC components may represent different propensities to contribute to a positive feedback to climate warming by converting OC from coastal and inland permafrost into CO2.

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Clustering analysis for the hydro-geomorphometric characterization of the George River watershed (Nunavik, Canada)

10.5194/egusphere-egu21-206 ◽

2021 ◽

Author(s):

Eliot Sicaud ◽

Jan Franssen ◽

Jean-Pierre Dedieu ◽

Daniel Fortier

Keyword(s):

Surface Water ◽

Land Cover ◽

Vegetation Cover ◽

Landsat 8 ◽

Number Of Clusters ◽

River Watershed ◽

Fcm Algorithm ◽

Water Cover ◽

George River ◽

The Impact

For remote and vast northern watersheds, hydrological data are often sparse and incomplete. Fortunately, remote sensing approaches can provide considerable information about the structural properties of watersheds, which is useful for the indirect assessment of their hydrological characteristics and behavior. Our main objective is to produce a high-resolution territorial clustering based on key hydrologic landscape metrics for the entire 42 000 km2 George River watershed (GRW), located in Nunavik, northern Qu&#233;bec (Canada). This project is being conducted in partnership with the local Inuit communities of the GRW for the purpose of generating and sharing knowledge to anticipate the impact of climate and socio-environmental change in the GRW.Our clustering approach employs Unsupervised Geographic Object-Based Image Analysis (GeOBIA) applied to the entire GRW with the subwatersheds as our objects of analysis. The landscape metric datasets used to generate the input variables of our GeOBIA classification are raster layers with a 30m x 30m pixel resolution. Topographic metrics are derived from a Digital Elevation Model (DEM) and include elevation, slopes, aspect, drainage density and watershed elongation. Land cover spectral metrics comprised in our analysis are the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Moisture Index (NDMI) (Gao, 1996) and the Normalized Difference Water Index (NDWI) (McFeeters, 1996), which are all computed from a Landsat-8 cloud-free surface reflectance mosaic dating from 2015. Rasterized maps of surface deposit distribution and permafrost distribution, both produced by the Minist&#232;re des For&#234;ts, de la Faune et des Parcs of Qu&#233;bec (MFFP), respectively constitute the surface and subsurface metrics of our GeOBIA.The clustering algorithm used in this Unsupervised GeOBIA is the Fuzzy C-Means (FCM) algorithm. The FCM algorithm provides the objects a set of membership coefficients corresponding to each cluster. The greatest membership coefficient is then used to attribute the distinct subwatersheds to a cluster of watersheds with similar hydro-geomorphometric characteristics. The classification returns a Fuzzy Partition Coefficient (FPC), which describes how well-partitioned our dataset is. The FPC can vary greatly depending on the number of clusters we want to produce. Thus, we find the optimal number of clusters by maximizing the FPC.Preliminary clustering results, computed only with topographic and land cover metrics, have identified two distinct watershed classes/clusters. In general, &#8220;Type 1&#8221; subwatersheds are clustered over the southern and northwestern portion of the GRW and are characterized by low to moderate elevation, high vegetation cover, high moisture and high surface water cover. Whereas &#8220;Type 2&#8221; subwatersheds located over the northeastern portion of the GRW are characterized by high elevation, low vegetation cover, low moisture and low surface water cover. These results will be refined with the use of additional metrics and will provide the detailed understanding necessary to assess how the hydrological regime of the river and its tributaries will respond to climate change, and how landscape change and human activities (e.g., planned mining development) may impact the water quality of the George River and its tributaries.

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Hydrogeochemical characteristics at Cape Lamb, Vega Island, Antarctic Peninsula

Antarctic Science ◽

10.1017/s0954102012000478 ◽

2012 ◽

Vol 24 (6) ◽

pp. 591-607 ◽

Cited By ~ 14

Author(s):

L. Moreno ◽

A. Silva-Busso ◽

J. López-Martínez ◽

J.J. Durán-Valsero ◽

C. Martínez-Navarrete ◽

...

Keyword(s):

Surface Water ◽

Antarctic Peninsula ◽

Climate Warming ◽

Significant Influence ◽

Water Samples ◽

Environmental Changes ◽

Hydrological Cycle ◽

Surface Water Chemistry ◽

Ocean Spray ◽

Hydrological Cycles

AbstractEnvironmental changes in the northern Antarctic Peninsula provide a sensitive local indicator of climate warming. A consequence of these changes is the activation of surface and subsurface hydrological cycles in areas where water, in colder conditions, would remain frozen. This paper analyses the effects of hydrological cycle activation at Cape Lamb, Vega Island. The conclusions are based on hydrochemistry and isotope interpretation of 51 representative water samples from precipitation, streams, lakes, ice, snow and groundwater. Based on these results relationships between the different components of the hydrological cycle are proposed. This paper highlights the important contribution of groundwater to surface water chemistry, the disconnection of the lakes from the overall flow, the lack of an ocean spray signature in surface water and groundwater and the significant influence of windblown dust in the composition of the analysed waters.

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Mediating the Effects of Climate on the Temperature and Thermal Structure of a Monomictic Reservoir through Use of Hydraulic Facilities

Water ◽

10.3390/w13081128 ◽

2021 ◽

Vol 13 (8) ◽

pp. 1128

Author(s):

Maurice Alfonso Duka ◽

Tetsuya Shintani ◽

Katsuhide Yokoyama

Keyword(s):

Climate Change ◽

Surface Water ◽

Climate Warming ◽

Thermal Structure ◽

Heat Content ◽

Thermal Conditions ◽

Long Term Effects ◽

Air Temperatures ◽

Lower Heat

Climate warming can alter the thermal conditions of reservoirs. However, some hydraulic interventions can be explored to mitigate this impact. This study investigates the long-term effects of climate on the temperature and thermal structure of a monomictic reservoir that has had varying operations from 1959 to 2016. Reservoir progressively operated through three distinct periods, namely, (A) deep penstock withdrawal (DPW; 1959–1991), (B) purely selective withdrawal (SW; 1992–2001), and (C) combination of SW and vertical curtain (VC; 2002–2016). Although annual air temperatures are increasing (+0.15 °C decade−1) in the long term, the reservoir’s surface water temperatures have been found to be decreasing (−0.06 °C decade−1). Periods B and C produced colder profiles and exhibited lower heat content and higher potential energy anomaly than Period A. Furthermore, stronger thermoclines, as indicated by Brunt–Vaisala frequency, were observed in the two latter periods. The results of this study show that varying operations bear a stronger influence on the reservoir’s temperature and thermal structure than climate change itself. Mitigating the thermal impacts of climate warming in reservoirs appears promising with the use of SW and VC.

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Carbon isotopes and lipid biomarker investigation of sources, transport and degradation of terrestrial organic matter in the Buor-Khaya Bay, SE Laptev Sea

Biogeosciences Discussions ◽

10.5194/bgd-8-3463-2011 ◽

2011 ◽

Vol 8 (2) ◽

pp. 3463-3496 ◽

Cited By ~ 3

Author(s):

E. S. Karlsson ◽

A. Charkin ◽

O. Dudarev ◽

I. Semiletov ◽

J. E. Vonk ◽

...

Keyword(s):

Organic Matter ◽

Surface Water ◽

Organic Carbon ◽

Climate Warming ◽

Surface Sediment ◽

Positive Feedback ◽

Coastal Erosion ◽

Surface Soil ◽

Mineral Soil ◽

Laptev Sea

Abstract. The world's largest continental shelf, the East Siberian Shelf Sea, receives substantial input of terrestrial organic carbon (terr-OC) from both large rivers and erosion of its coastline. Degradation of organic matter from thawing permafrost in the Arctic is likely to increase, potentially creating a positive feedback mechanism to climate warming. This study focuses on the Buor-Khaya Bay (SE Laptev Sea), an area with strong terr-OC input from both coastal erosion and the Lena river. To better understand the fate of this terr-OC, molecular (acyl lipid biomarkers) and isotopic tools (stable carbon and radiocarbon isotopes) have been applied to both particulate organic carbon (POC) in surface water and sedimentary organic carbon (SOC) collected from the underlying surface sediments. Clear gradients in both extent of degradation and differences in source contributions were observed both between surface water POC and surface sediment SOC as well as over the 100 s km investigation scale (about 20 stations). Depleted δ13C-OC and high HMW/LMW n-alkane ratios signaled that terr-OC was dominating over marine/planktonic sources. Despite a shallow water column (10–40 m), the isotopic shift between SOC and POC varied systematically from +2 to +5 per mil for δ13C and from +300 to +450 for Δ14C from the Lena prodelta to the Buor-Khaya Cape. At the same time, the ratio of HMW n-alkanoic acids to HMW n-alkanes as well as HMW n-alkane CPI, both indicative of degradation, were 5–6 times greater in SOC than in POC. This suggests that terr-OC was substantially older yet less degraded in the surface sediment than in the surface waters. This unusual vertical degradation trend was only recently found also for the central East Siberian Sea. Numerical modeling (Monte Carlo simulations) with δ13C and Δ14C in both POC and SOC was applied to deduce the relative contribution of plankton OC, surface soil layer OC and yedoma/mineral soil OC. This three end-member dual-carbon-isotopic mixing model suggests quite different scenarios for the POC vs SOC. Surface soil is dominating (63 ± 10%) the suspended organic matter in the surface water of SE Laptev Sea. In contrast, the yedoma/mineral soil OC is accounting for 60 ± 9% of the SOC. We hypothesize that yedoma-OC, associated with mineral-rich matter from coastal erosion is ballasted and thus quickly settles to the bottom. The mineral association may also explain the greater resistance to degradation of this terr-OC component. In contrast, more amorphous humic-like and low-density terr-OC from surface soil and recent vegetation represents a younger but more bioavailable and thus degraded terr-OC component held buoyant in surface water. Hence,these two terr-OC components may represent different propensities to contribute to a positive feedback to climate warming by converting OC from coastal and inland permafrost into CO2.

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Modeling streamflow sensitivity to climate warming and surface water inputs in a montane catchment

Journal of Hydrology Regional Studies ◽

10.1016/j.ejrh.2021.100976 ◽

2022 ◽

Vol 39 ◽

pp. 100976

Author(s):

K.E. Hale ◽

A.N. Wlostowski ◽

A.M. Badger ◽

K.N. Musselman ◽

B. Livneh ◽

...

Keyword(s):

Surface Water ◽

Climate Warming

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Spatiotemporal Variations in Dianchi Lake’s Surface Water Temperature From 2001 to 2017 Under the Influence of Climate Warming

IEEE Access ◽

10.1109/access.2019.2935767 ◽

2019 ◽

Vol 7 ◽

pp. 115378-115387 ◽

Cited By ~ 4

Author(s):

Yi Luo ◽

Yueyue Zhang ◽

Kun Yang ◽

Zhenyu Yu ◽

Yu Zhu

Keyword(s):

Surface Water ◽

Water Temperature ◽

Climate Warming ◽

Surface Water Temperature ◽

Spatiotemporal Variations

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Use of satellite images to determine surface-water cover during the flood event of September 13, 2013, in Lyons and western Longmont, Colorado

Open-File Report ◽

10.3133/ofr20151042 ◽

2015 ◽

Author(s):

Christopher J. Cole ◽

Beverly A. Friesen ◽

Earl M. Wilson ◽

Stanley R. Wilds ◽

Suzanne M. Noble

Keyword(s):

Surface Water ◽

Satellite Images ◽

Flood Event ◽

Water Cover

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Landsat-Based Estimation of Seasonal Water Cover and Change in Arid and Semi-Arid Central Asia (2000–2015)

Remote Sensing ◽

10.3390/rs11111323 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1323 ◽

Cited By ~ 6

Author(s):

Xianghong Che ◽

Min Feng ◽

Joe Sexton ◽

Saurabh Channan ◽

Qing Sun ◽

...

Keyword(s):

Surface Water ◽

Central Asia ◽

Learning Algorithm ◽

Water Area ◽

Water Bodies ◽

Ecological Zones ◽

Hydrological Variability ◽

Global Mapping ◽

Water Cover ◽

Semi Arid

Surface water is of great importance to ecosystems and economies. Crucial to understanding hydrological variability and its relationships to human activities at large scales, open-access satellite datasets and big-data computational methods are now enabling the global mapping of the distribution and changes of inland water over time. A machine-learning algorithm, previously used only to map water at single points in time, was applied over 16 years of the USGS Landsat archive to detect and map surface water over central Asia from 2000 to 2015 at a 30-m, monthly resolution. The resulting dataset had an overall classification accuracy of 99.59% (±0.32% standard error), 98.24% (±1.02%) user’s accuracy, and 87.12% (±3.21%) producer’s accuracy for water class. This study describes the temporal extension of the algorithm and the application of the dataset to present patterns of regional surface water cover and change. The findings indicate that smaller water bodies are dramatically changing in two specific ecological zones: the Kazakh Steppe and the Tian Shan Montane Steppe and Meadows. Both the maximum and minimum extent of water bodies have decreased over the 16-year period, but the rate of decrease of the maxima was double that of the minima. Coverage decreased in each month from April to October, and a significant decrease in water area was found in April and May. These results indicate that the dataset can provide insights into the behavior of surface water across central Asia through time, and that the method can be further developed for regional and global applications.

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