Simulation of snowmelt-runoff under climate change scenarios in a data-scarce mountain environment

Figures & data

Figure 1. Map of Pakistan including the UIB area, its sub-basins, Tarbela dam and study area.

Figure 2. GDEM of the Shyok River basin showing five altitudinal zones, glacier coverage across them, and overlaid by the hydro-climatic gauging stations.

Figure 3. Hypsometric curve and the distribution of area under 500-m elevation bands for the Shyok River basin (estimated from ASTER GDEM).

Table 1. Key features of the study area (Shyok River basin).

Catchment	Shyok
River flow gauging station	Yogo
Latitude	32° to 36°
Longitude	75° to 82°
Elevation of gauging station	∼2469 m ASL
Drainage area	∼ 68,290 km^2
Glacier-covered area	∼ 5982 km^2
Glacier cover percentage	∼8.46% (calculated from latest RGI V5)
Mean elevation (computed from hypsometric curve)	∼ 5150 m ASL
Area above 5000 m ASL	∼ 39,340 km^2
Name and elevation of meteorological stations	Skardu = 2317 m ASL	Hushey = 3075 m ASL

Table 2. Main features of the elevation zones extracted from the ASTER GDEM.

Zone	A	B	C	D	E
Elevation band (m ASL)	2387–3500	3501–4500	4501–5500	5501–6500	6501– 7724
Mean elevation (m ASL)	∼ 3150	∼ 4210	∼ 5040	∼ 5780	∼ 6450
Area (%)	2.28	14.35	58.86	24.28	0.23
Area (km^2)	1560	9798.4	40,194	16,578	159.5

Figure 4. Mean monthly SCA variations in the Shyok River basin as extracted from MODIS snow products.

Table 3. SRM parameters to be calibrated.

1. Runoff coefficient (snow), Cs	2. Runoff coefficient (rain), Cr
3. Critical temperature, Tcritical (°C)	4. DDF, a (cm °C^−1 d^−1)
5. Rainfall contributing area, RCA	6. Recession coefficient (Xc and Yc), k
7. Temperature lapse rate, γ (°C/100 m)	8. Time lag, L (hrs)

Figure 5. Snow cover distribution (basin-wide) in the Shyok River basin estimated from MODIS snow images over a period of 2000–2006.

Figure 6. Monthly temperature variations in different elevation zones of the study area. The data for all the elevation zones are estimated from the actual data of neighbouring Skardu climate station by using the temperature lapse rate of 0.65°C/100 m.

Figure 7. Snow cover distribution in five different altitudinal zones of the Shyok River basin estimated from the remotely sensed MODIS (MOD10A2) snow cover data.

Table 4. Efficiency of the basin-wide application of SRM over calibration and validation period (2000–2006) for the simulation of Shyok river discharge.

Year		Model efficiency
		Difference of volume (Dv%)	Nash–Sutcliffe coefficient (R^2)	Pearson correlation coefficient	Kendall rank correlation coefficient
Calibration	2000	14.44	0.74	0.90	0.77
	2001	−24.93	0.80	0.95	0.85
	2002	11.13	0.86	0.93	0.79
Validation	2003	8.70	0.90	0.95	0.77
	2004	−1.77	0.72	0.86	0.67
	2006	35.06	0.63	0.90	0.74

Figure 8. Evaluation of basin-wise (BW) SRM application (2000–2006) to the Shyok River basin during the snowmelt period (April–September).

Table 5. Basin-wide parametric values for the successful simulation of Shyok river discharge for years 2000−2006.

Parameter	Parameter values
Lapse rate (°C 100m^–1)	0.65–0.71
Tcritical (°C)	0
DDF (cm °C^–1 d^–1)	0.35
Lag time (h)	18
Cs	0.29
Cr	0.15
RCA	1
Xc	1.09
Yc	0.02–0.035

Table 6. Efficiency of the zone-wise application of SRM over calibration and validation period (2000–2006) for the simulation of Shyok river discharge.

Year		Model efficiency		Correlation coefficient
		Difference of volume (Dv%)	Nash–Sutcliffe coefficient (R^2)	Pearson correlation coefficient	Kendall rank correlation coefficient
Calibration	2000	−5.13	0.90	0.95	0.86
	2001	−19.88	0.75	0.89	0.78
	2002	−4.30	0.72	0.86	0.78
Validation	2003	1.29	0.93	0.96	0.84
	2004	1.94	0.74	0.89	0.78
	2006	11.06	0.82	0.94	0.81

Figure 9. Evaluation of zone-wise SRM application (2000–2006) to the Shyok River basin during the snowmelt period (April–September).

Table 7. Zone-wise parametric values for the successful simulation of Shyok river discharge for years 2000−2006.

Parameters	Zone A (2387–3500 m)	Zone B (3501–4500 m)	Zone C (4501–5500 m)	Zone D (5501–6500 m)	Zone E (6501–7724 m)
Lapse rate (°C 100 m^–1)	0.65	0.65	0.65	0.65	0.65
Tcritical (°C)	0	0	0	0	0
DDF (cm °C^–1 d^–1)	0.55	0.55	0.60	0.65	0.65
Lag time (h)	6	12	12	18	18
Cs	Jun–Aug 0.35 Sep–May 0.27	Jun–Aug 0.43 Sep–May 0.21	Jun–Aug 0.43 Sep–May 0.22	Jun–Aug 0.39 Sep–May 0.30	Jun–Aug 0.39 Sep–may 0.28
Cr	0.1	0.1	0.1	0.1	0.1
RCA	1	1	1	0	0
Xc	1.02	1.02	1.02	1.02	1.02
Yc	0.02	0.02	0.02	0.02	0.02

Note: June–August, Snow melt and monsoon period. September/October–May, Snow accumulation and dry period. Zone E, Zone with almost 100% glacierised area. C_s, Zone A has a small snowmelt runoff contribution. RCA, rainfall contributing area is small in Zone D and E because at this altitude the precipitation is in solid form.

Figure 10. Evaluation of basin-wide (BW) and zone-wise (ZW) SRM application over the hydrological year 2003 in the Shyok River basin. Upper panel shows the variation in mean monthly SCA for a hydrological year in the catchment.

Figure 11. Comparison of basin-wide (BW) and zone-wise (ZW) simulated runoff by applying the SRM over the years (2000–2006).

Figure 12. Mean monthly discharge simulations in the Shyok River under the SCA change scenarios. Discharge measured for year-2000 is used as current discharge.

Figure 13. Monthly discharge simulations in the Shyok River for different climate change (mean temperature) scenarios. Discharge simulated for 2000 with the SRM is used as current discharge.

Figure 14. Change in mean seasonal (summer) discharge (δQ) under future scenarios of change in mean temperature (δT_avg) and mean SCA (δSCA).

Table 8. Change in mean seasonal (summer) discharge under future scenarios of change in mean temperature (T_avg) and mean SCA.

Climate change scenarios		Change in mean discharge
Change in SCA	+10%	∼ +11% (∼74 m^3/s)
	+20%	∼ +20% (129 m^3/s)
	–10%	∼–8% (53 m^3/s)
Change in mean temperature (Tavg)	+1°C	∼ +26% (167 m^3/s)
	+2°C	∼ +54% (349 m^3/s)
	+3°C	∼ +81% (530 m^3/s)
	+4°C	∼ +114% (740 m^3/s)
	–2°C	∼ –36% (232 m^3/s)
Change in mean temperature (Tavg) and SCA	+3°C Tavg and +20% SCA	∼ +118% (768 m^3/s)