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Hydrological modelling of climate change impacts on river flows in Siberia’s Lena River Basin and implications for the Atlantic Meridional Overturning Circulation

A hydrological model of Siberia’s Lena River Basin is calibrated and validated against observed river discharge at five stations. Implications of the Representative Concentration Pathway 4.5 scenario for river discharge are assessed using projections from 41 Coupled Model Intercomparison Project Phase 5 General Circulation Models grouped into 12 genealogical-based groups as well as a group ensemble mean. Annual precipitation increases in all scenarios (1.7–47.4%). Increases in annual PET are of a similar range (6.0–45.5%). PET peaks in June compared to July for the baseline. All temperature changes exceed 1.5 C (range: 2.2 C–6.2 C). The largest absolute increases are in winter (maximum þ7 C). Changes inmean annual discharge range from 8.5 toþ69.9%. TenGCM groups and the group ensemble mean project increases. Earlier snowmelt is dominant so the annual flood peaks in May compared with June for the baseline. Increased discharge of the Lena and other Eurasian rivers to the Arctic Ocean has the potential to impact Atlantic Meridional Overturning Circulation (AMOC). Enhanced fluxes for four groups are capable of weakening the AMOC. Changes for other groups may contribute to weakening when combinedwith other sources of freshwater andwarmer temperatures. doi: 10.2166/nh.2019.151 ://iwa.silverchair.com/hr/article-pdf/50/6/1577/759033/nh0501577.pdf C. E. Hudson (corresponding author) J. R. Thompson UCL Department of Geography, University College London, Gower Street, London WC1E 6BT, UK E-mail: charlotte.hudson.15@ucl.ac.uk


INTRODUCTION
Climate change will intensify the global hydrological cycle.
Modified precipitation patterns coupled with changes in temperature and evapotranspiration will have important implications for river discharge (Vihma et al. ). The most severe hydrometeorological impacts of rising temperatures are being observed in, and are projected for, the Arctic, with mean annual air temperatures between 2001 and 2012 being 1.5 C warmer than during 1971-2000 (Overland et al. ). Precipitation is increasing and is projected to be >50% higher by 2100. Winter warming is projected to be four times greater than summer warming, modifying snowmelt, evapotranspiration and ultimately river discharge (Ye et al. ). of saltwater further reducing water density and, therefore, convection. However, studies using coupled general circulation models (GCMs) to assess AMOC alterations have not identified this instability, and the most recent consensus of the Intergovernmental Panel on Climate Change is that AMOC slowdown is more likely than complete collapse during the 21st century (Kirtman et al. ).

Reported increases in
The implications of a weakening or collapse of AMOC would be widespread due to global-scale teleconnections (Vellinga & Wood ). Climatic implications may include North Atlantic cooling, an equatorward shift of the Inter-Tropical Convergence Zone and weakened monsoons (Buckley & Marshall ). AMOC collapse may also increase water resources stress in Europe and southern Asia due to altered precipitation patterns (Gosling ). Additionally, reductions in the extent of boreal and temperate forests are projected, with implications for carbon storage in these latitudes (Köhler et al. ). Fisheries and crop yields could be negatively impacted due to changes in ocean circulation with the potential for major societal implications (Keller et al. ; Kuhlbrodt et al. ). Given the significance of changes in AMOC, this study investigates the potential impacts of climate change upon river flows within Siberia's Lena River Basin, a major contributor of freshwater to the Arctic. Results are scaled up to assess the potential implications for the AMOC of changes in Eurasian runoff to the Arctic Ocean.

STUDY AREA: THE LENA RIVER BASIN
The Lena River (Figure 1), which enters the Arctic Ocean via the Laptev Sea, is located in northern Asia and 1,640 m). It is the eleventh longest river in the world (4,400 km) with the ninth largest basin (32,000 km 2 ) (Gelfan et al. ). As the second largest Eurasian river in terms of discharge, following the Yenisei and preceding the Ob, the Lena provides around 15% of the total mean annual runoff to the Arctic Ocean (mean annual discharge: The lowest and highest river flows occur during winter and summer, respectively. Snowmelt during May causes rapid increases in discharge, which on average peaks in June (Gelfan et al. ). Permafrost underlays 93% of the basin and directs precipitation and snowmelt to rivers. It contributes to low sub-surface storage capacity, causing large differences between winter and summer flows (Ye et al. The reservoir on this tributary (completed in 1967) has a capacity equivalent to 7% of annual runoff. Whilst it increases winter flows above natural levels (Ye et al. ), these account for just 10% of annual discharge, and the higher summer flows are relatively unaffected (Holmes et al. ).
The basin is sparsely populated and vegetation is largely natural comprising forests (84%), shrublands (9%), grasslands (3%), croplands (2%) and wetlands (1%) (Liu & Yang ). Forests dominate the southwest and tundra dominates the north. Whilst the basin's water resources are utilised for domestic purposes, hydropower and irrigation, the total use comprises a very low percentage of the mean annual runoff (Berezovskaya et al. ). The impacts of climate change can, therefore, be more easily identified and are likely to dominate future changes as opposed to anthropogenic activities.
Temperature and precipitation have increased across the basin, especially during the cold season (November-April; Dzhamalov et al. ). Changes in river discharge include earlier seasonal peaks and larger flows in spring, summer and winter in contrast to autumn declines. A significant upward trend (up to 90%) at the basin outlet (Stolb) during low-flow periods has been recorded, whilst slight increases (5-10%) in high-flows have been observed (Ye et al. ). Recognition that climate change may have already impacted the discharge of the Lena River, combined with the important role these flows and those from the other Eurasian rivers play in the global climate system, provides the impetus for assessing potential future changes within the current study.

Model development, calibration and validation
This study employs a coupled hydrological/hydraulic model of the Lena River Basin developed using the MIKE SHE/ MIKE 11 modelling system. MIKE SHE is commonly described as a deterministic, fully distributed and physically based hydrological modelling system, although it includes a range of process descriptions, some of which are more conceptual and semi-distributed in nature (Refsgaard et al. ).
MIKE SHE is dynamically coupled to MIKE 11, a 1D hydraulic model that represents the channel flow (e.g. Thompson et al. ). Model development for the Lena Basin followed approaches used in other large river systems (e.g. Andersen et al. ; Thompson et al. ). Table 1 summarises the model set-up and the data it employs.

Sub-catchments
The USGS GTOPO-30 DEM, R-ArcticNET b gauging station locations and major tributaries.
Defined five main sub-catchments within MIKE SHE. Specified as a shapefile. Also defined the linear reservoir sub-catchments and baseflow sub-catchments. A grid file defined the locations of the smaller 19 meteorological sub-catchments, which allowed the spatial distribution of climatic variables. Within these areas, parameters were adjusted during model calibration.
Land use USGS 1 km Global Land Cover Characterisation data c Defined the spatial distribution of land use within the Lena River Basin. Twenty-nine original classes were reclassified into nine classes. Specified as a grid file.

Vegetation properties: RD and LAI
Values from the literature (Arnell ) Root depth was defined for each land-cover class. This value describes the depth of the zone from evapotranspiration can occur. These were constant for each land-cover classes. LAI describes the ratio of the leaf area to the ground area.

River network
Using the USGS GTOPO-30, the river network was identified using ArcMap Hydrology Tools.
A shapefile was specified in MIKE 11. It was then manually digitised to define the river network.
Cross-sections Identified and measured using Google Earth Pro. Elevations were extracted from the basin DEM.
Defined channel cross-sections within MIKE 11. Each channel width was assigned a stream order. Elevations were assigned to each cross-section.

Overland Flow: Manning Number
Values from the literature using the approach of Thompson et al. ().
This was spatially distributed throughout the catchment based on the overlying vegetation. Specified as a grid file. Defined the rate at which overland flow is routed to channels.

).
To account for variations in climate, the areas defining the extent of the five saturated zone linear reservoirs were further divided into a total of 19 smaller areas herein referred to as meteorological sub-catchments. The discretisation of these areas was based on their ranges in latitude, longitude and elevation, as well as the major tributaries within each saturated zone linear reservoir sub-catchment ( Figure 1). R-ArcticNET discharge data were separated into two periods, 1960-1979 and 1980-1999, for calibration and validation, respectively. In both cases, the previous year was used as a spin-up period. Calibration was undertaken from upstream to downstream by adjusting the parameters defined above (principally the saturated zone linear reservoir time constants and lapse rates). As previously indicated, simulated river discharges, which were stored at the maximum model time step of 24 hours, were aggregated to mean monthly discharge for comparison with the R-Arc-ticNET data. Model performance was assessed visually and statistically using the Nash-Sutcliffe efficiency coefficient (NSE), bias (Dv) and the Pearson correlation coefficient (r).
Performance based on the values of these three statistics was further classified into one of five classes (ranging between 'very poor' and 'excellent') using the scheme of Ho et al.    (Table 3). Dv is classified as 'excellent' at four stations and 'very good' at the remaining station. Figure   19.2%). All groups and the group ensemble mean project basin-wide peaks in June, 1 month earlier than for the baseline (although the largest absolute changes occur in May; Figure 3).

Projected river discharge
Changes in discharge are generally consistent with 10 of the 12 groups and the group ensemble mean projecting increases at all gauging stations. These increases are, however, of variable magnitude (Figure 4). Across the basin changes range between À8.5 and þ36.8%. Groups 1, 3 and 5 project the largest basin-wide increases. Declines are limited to groups 4 and 12, which project declines at four (À8.5 to À 1.0%) and five (À5.8 to À 1.7%) stations, respectively. These groups are associated with relatively large increases in respectively) that exceed increases in precipitation (1.7-17.2% and 9.6-19.5%, respectively). The group ensemble mean projects increases in the mean discharge of between 5.6 and 18.6% (mean: 10.1%) with the increase of 9.2% for Stolb, indicative of Arctic Ocean inflow, contrasting with the range for the 12 groups of À5.3 to 21.7%. All but two groups (again 4 and 12) are associated with increases in these flows.
High (Q5) and low (Q95) flows also increase for most groups. Changes in Q5 across all groups and gauging stations range between À2.8 and þ69.9%. Increases are, in percentage terms, larger than those for the mean annual discharge. Declines are again limited to groups 4 (three stations) and 12 (one station). However, they are small compared with most increases. The group ensemble mean projects increase in Q5 at all stations (range: 10.2-30.2%).
Q95 increases in most cases with relatively small ( 6.7%) declines limited to just two stations for Group 4 and one for groups 2 and 12. The small (2.8%) decline for Tabaga   Table 3 | Model performance statistics and classification for the calibration (Cal, 1960(Cal, -1979(Cal, ), baseline (1961(Cal, -1990 and validation (Val, 1980(Val, -1999    projected by Group 2 is the only reduction in any discharge measure beyond groups 4 and 12. These two groups project the smallest increases in Q95 (<8.2%), whilst groups 1, 3 and 5 project some of the largest (up to 41.7%, Group 3, Aldan). Increases in Q95 of between 15.7 and 28.0% are projected by the group ensemble mean.
Projected river regimes ( Figure 5) show that in many cases the seasonal peak advances to May compared with June under baseline conditions. This is most pronounced for groups 9 and 10, both of which project large basinwide increases in temperature, and Group 11 and the group ensemble mean at Vilui. Group 9 projects the most pronounced change at Stolb with the mean May discharge being 82% larger than the baseline. For many groups, the recession limb declines more rapidly so that discharges in September are lower than during baseline conditions. The largest reductions at Stolb (19.0%) are projected by Group 4.

Model performance
This study expands research into the impacts of climate change on river discharge within the Arctic (e.g. Peterson   for Yenisei and Ob, respectively; R-Arctic.Net). These estimates assume regionally homogeneous climatic changes, the same hydrological responses to these changes within the Yenisei and Ob basins, and exclude future anthropogenic impacts. Whilst it is recognised that this is a simplification, the approach does enable an initial assessment of climate change driven modifications to Eurasian runoff to the Arctic for each of the 12 GCM groups.