Hydrological modelling of the Lena River using SWIM

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1 Hydrological modelling of the Lena River using SWIM Michel Wortmann 1 1 Potsdam Institute for Climate Impact Research (PIK), Germany July 8, 214 Contents 1 The Lena catchment and data used Discharge data and catchment statistics Land cover and soil data Climate data preparation Precipitation correction Model setup 9 4 Calibration and validation of SWIM Krestovski station (headwaters) Stolb station (outlet) References 12 1 The Lena catchment and data used 1.1 Discharge data and catchment statistics Table 1: Station statistics and data ranges (Start/End). GRDC ID Name Lon Lat Area 1 3 km 2 Start End Mean Q m 3 s Zmeinovo Krestovski Solyanka Tabaga Kyusyur Stolb

2 Figure 1: The topography, rivers and stations (with available GRDC data) with their catchments in the Lena basin. 2

3 12 GRDC discharge data for the Lena catchment Mean discharge [1^3 m^3s^-1] Month Fraction of time equalled or exceeded Day of year 1 2 Zmeinovo (293426) Krestovski (293427) Solyanka (293428) Tabaga (293429) Stolb (29343) Kyusyur (kusur) (29342) Figure 2: Mean discharge at the 6 GRDC gauging stations in the Lena catchment. Monthly mean values only shown for , the period for which climate data is available 3

4 1.2 Land cover and soil data GLC Land cover 2 (in SWIM classes) 65 N 6 N 55 N km % cover dec forest 11 E 12 E 13 E tundra/heather everg forest bare soil mx forest wetland water grassland cropland Figure 3: Spatial and statistical distribution of the GLC 2 land cover (reclassed to the SWIM land cover classes) used in the SWIM model. Catchments (b/w lines) and stations (triangles) shown for reference. 4

5 HWSD soil map 65 N 6 N 55 N 11 E 12 E 13 E km 25 5 Figure 4: Soil units from the Harmonised World Soil Database aggregated to 78 SWIM soil units. 5

6 2 Climate data preparation met. station WATCH centroid gauge station Climate stations 65 N 6 N 55 N km 11 E 12 E E Figure 5: Meteorological stations and the WATCH grid used from which data was used as model input. 2.1 Precipitation correction Precipitation data was interpolated to the derived subbasins from meteorological stations (received from Gelfan) and the WATCH dataset, which includes two precipitation sources: CRU and GPCC. Total annual precipitation are plotted in Figure 2.1 including GPCC excluding snow and a precipitation using the Gelfan data. Berezovskaya et al. (25) provide a water balance analysis of the upper Lena catchment (until the Solyanka station) and values from two other papers; according to their study, annual precipitation is 5-6mm, approximately 1-15mm below the observed values and those from WATCH. They also mention that precipitation observation data has to be corrected for undercatch and other measurement underestimates. Berezovskaya et al. (25) also provide estimates of evapotranspiration for the upper Lena, which is 253mm per year. This finding also corresponds with Fukutomi et al. (23) and Ma et al. (2), who analyse the water balance of the entire Lena basin. Evapotranspiration (ETa) was derived from the precipitation (P) and discharge (Q) observation data by simple subtraction of the distributed annual discharge of the Krestovski catchment from the annual precipitation, the result of which is shown in Figure 2.1. Approximately 1mm are left for evapotranspiration. Considering the values given by the previous studies, this is 15-2mm per year lower. 6

7 Figure 6: Climate interpolation and correction chain. Main observations of temperature (T) and precipitation (P) were corrected and extended using the WATCH dataset. Considering both the cited precipitation and the too low derived evapotranspiration, the precipitation data needs to be corrected to an average of 5 55mm per year, i.e. a correction factor of (24 36%) needs to be applied. 7

8 Figure 7: Annual precipitation of the headwaters from WATCH and observation data. Figure 8: Climate interpolation and correction chain. Main observations of temperature (T) and precipitation (P) were corrected and extended using the WATCH dataset. 8

9 3 Model setup 2566 subbasins were delineated from the SRTM digital elevation model as shown in Figure 3. Mean subbasin sizes are varied between the mountainous headwater catchments (smaller) and the low relief middle and lower reaches (greater). By identifying the areas of unique combinations of subbasins, land cover, soil type and elevation band (interval of 2m), hydrotopes were delineated, SWIM s smallest disaggregation units. Figure 9: Subbasins derived from the SRTM DEM and the subbasin size distribution (inset). 9

10 4 Calibration and validation of SWIM Table 2: Model performance in the validation and calibration periods. Calibration Validation ID Name NSE %bias NSE %bias S8 Krestovski S11 Stolb SWIM was calibrated for to the observed discharge at the Krestovski and the Stolb station in the years Nash-Sutcliff Efficiencies (NSE) of.87 and a bias in water balance of less then -5.4% were achieved for the calibration period (see Table 4). The following 5 years were used as validation period; NSE values of.82 were achieved, while the bias at Krestovski is -1.5% and +1.8% at Stolb. 1

11 4.1 Krestovski station (headwaters) Calibration Discharge [m 3 s 1 ] Validation observed simulated Figure 1: Simulated (red) versus observed (black) discharge at Krestovski station for the calibration (top) and validation (bottom) period. 11

12 4.2 Stolb station (outlet) Calibration Discharge [m 3 s 1 ] Validation observed simulated Figure 11: Simulated (red) versus observed (black) discharge at the outlet station Stolb for the calibration (top) and validation (bottom) period. 5 References Berezovskaya, S., Yang, D., Hinzman, L., 25. Long-term annual water balance analysis of the Lena River. Global and Planetary Change 48, Fukutomi, Y., Igarashi, H., Masuda, K., Yasunari, T., 23. Interannual Variability of Summer Water Balance Components in Three Major River Basins of Northern Eurasia. Journal of Hydrometeorology 4, Ma, X., Fukushima, Y., Hiyama, T., Hashimoto, T., Ohata, T., 2. A macro-scale hydrological analysis of the Lena River basin. Hydrological Processes 14,

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