Description: The Lena River Delta in Northern Yakutia forms one of the largest deltas in the Arctic and its catchment area (2 430 000 km2) is one of the largest in the whole of Eurasia. The Lena River distributes water and sediment in four main channels before discharging in total about 30 km3 of water through the delta into the Arctic Ocean every year and its discharge has been observed to be increasing. The goal of this presentation is to characterize the hydrologic processes that are strongly affected by a transient climate component- the permafrost. Permafrost plays a major role for storage and release of water to rivers and surface and subsurface water bodies. Conversely, the coupled water and heat fluxes in the atmosphere and below ground have a marked influence on the permafrost’s thermal regime. Our study site, the Lena River Delta, is also one of the coldest and driest places on Earth, with mean annual air temperatures of about -13 °C, a large annual air temperature range of about 44 °C and summer precipitation usually less than 150 mm. Very cold continuous permafrost of about −8.6 °C (11 m depth) underlays the area between about 400 and 600 m below surface and since 2006 the permafrost has warmed than 1 °C at 10.7 m. Roughly half of the land surface is dominated by wet surfaces, such as polygons, ponds and thermokarst lakes. This contribution summarizes past and ongoing research on hydrologic processes across spatial scales, from microtopographic processes of polygonal tundra to regional scale deltaic processes to assess short and long term changes in water fluxes. We quantify unfrozen water in soils, streams and river discharges and water bodies’ storage at larger scales. Water bodies were mapped using optical and radar satellite data with resolutions of 4 m or better, Landsat-5 TM at 30 m and the MODIS water mask at 250 m resolution. Ponds, i. e. water bodies with surface are smaller than 104 m, make over 95 % of the total number of water bodies and are not resolved in Landsat-scale land cover classifications. Ponds are generally well mixed and experience high water temperatures up to 23 °C during the summer and are, therefore, hotspots for biological activity and CO2 emission. The ponds in the study area freeze completely in winter, whereas the deeper thermokarst lakes do not freeze to the bottom, with implications for coupling of the permafrost to the atmosphere. These deep thermokarst lakes are thermally stratified during winter and reach maximum water temperatures of up to 19 °C during summer. The summer water balance at the catchment scale was found to be mainly controlled by vertical fluxes (precipitation and evapotranspiration). On the other hand, redistribution of storage water due to lateral fluxes takes place within the microtopography of polygonal tundra. The long-term summer storage (precipitation minus evapotranspiration) from 1958-2011 indicates a reasonably balance on the polygonal tundra with an average surplus of 5 mm, but it is also characterized by high interannual variability due to precipitation input. During negative water balance years where evapotranspiration exceeds precipitation, shallower water bodies dry out. The extent of wetlands and water bodies will shift with changes in vertical water fluxes as well as permafrost warming and thaw. Thus, water bodies can serve as sentinels of environmental change and we present applicable remote-sensing observations and upscaling methods

Description: A challenging problem in climate modeling is how to deal with interactions and feedbacks across a multiplicity of spatial scales, and how to improve our understanding of the role played by local soil heterogeneities in the climate system. This is of particular interest in northern peatlands, because of the large amount of carbon stored in the soil. Greenhouse gas (GHG) fluxes, such as methane, carbon dioxide and water vapor, vary largely within the environment, as an effect of the small scale processes that characterize the landscape. It is then essential to consider the local heterogeneous behavior of the system components in order to properly estimate water and carbon balances. We propose a novel method to fill the scaling gap from local mechanistic models to large scale mean field approximations. We developed a surface model for peatlands working at the landscape scale, which is able to show the impact of surface microtopography in modeling greenhouse gas fluxes. We tuned our landscape-scale model with data from a peatland site in the Komi Republic of Russia. We simulate surface microtopography and hydrology, and we couple it to a process-based model for methane emissions from the soil (Walter and Heiman, 1996). By partitioning the space in smaller subunits and then analyzing the statistical properties of the tiling, we are able to resolve the small scale processes and investigate their effects at larger scales. We not only investigate the influence of the hummocky surface on GHG emissions, but we are also able to simulate how complex hydrological interactions happening within the system at a subgrid scale affect the landscape-scale land-atmosphere GHG fluxes. We force our model climatology with data from the CMIP5 experiments. Future projections use forcing from the RCP 8.5 scenario, in order to investigate the impact of microrelieves on the future carbon cycle. We also explore potential dynamical feedbacks with the atmospheric water cycle and energy balance by coupling the surface model with an idealized box model of the atmosphere.

Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Geoscientific Model Development 11 (2018): 497-519, doi:10.5194/gmd-11-497-2018.

Description: Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peatland map and identified with peat-specific soil hydraulic properties. Runoff from non-peat vegetation within a grid cell containing a fraction of peat is routed to this peat soil tile, which maintains shallow water tables. The water table position separates oxic from anoxic decomposition. The model was evaluated against eddy-covariance (EC) observations from 30 northern peatland sites, with the maximum rate of carboxylation (Vcmax) being optimized at each site. Regarding short-term day-to-day variations, the model performance was good for gross primary production (GPP) (r2 =  0.76; Nash–Sutcliffe modeling efficiency, MEF  =  0.76) and ecosystem respiration (ER, r2 =  0.78, MEF  =  0.75), with lesser accuracy for latent heat fluxes (LE, r2 =  0.42, MEF  =  0.14) and and net ecosystem CO2 exchange (NEE, r2 =  0.38, MEF  =  0.26). Seasonal variations in GPP, ER, NEE, and energy fluxes on monthly scales showed moderate to high r2 values (0.57–0.86). For spatial across-site gradients of annual mean GPP, ER, NEE, and LE, r2 values of 0.93, 0.89, 0.27, and 0.71 were achieved, respectively. Water table (WT) variation was not well predicted (r2 〈 0.1), likely due to the uncertain water input to the peat from surrounding areas. However, the poor performance of WT simulation did not greatly affect predictions of ER and NEE. We found a significant relationship between optimized Vcmax and latitude (temperature), which better reflects the spatial gradients of annual NEE than using an average Vcmax value.

Description: This study was supported by the European Research Council Synergy grant ERC-2013-SyG- 610028 IMBALANCE-P.