Simulating Current and Future River-Flows in the Karakoram and Himalayan Regions of Pakistan Using Snowmelt-Runoff Model and RCP Scenarios

Abstract

Upper Indus Basin (UIB) supplies more than 70% flow to the downstream agricultural areas during summer due to the melting of snow and glacial ice. The estimation of the stream flow under future climatic projections is a pre-requisite to manage water resources properly. This study focused on the simulation of snowmelt-runoff using Snowmelt-Runoff Model (SRM) under the current and future Representative Concentration Pathways (RCP 2.6, 4.5 and 8.5) climate scenarios in the two main tributaries of the UIB namely the Astore and the Hunza River basins. Remote sensing data from Advanced Land Observation Satellite (ALOS) and Moderate Resolution Imaging Spectroradiometer (MODIS) along with in-situ hydro-climatic data was used as input to the SRM. Basin-wide and zone-wise approaches were used in the SRM. For the zone-wise approach, basin areas were sliced into five elevation zones and the mean temperature for the zones with no weather stations was estimated using a lapse rate value of −0.48 °C to −0.76 °C/100 m in both studied basins. Zonal snow cover was estimated for each zone by reclassifying the MODIS snow maps according to the zonal boundaries. SRM was calibrated over 2000–2001 and validated over the 2002–2004 data period. The results implied that the SRM simulated the river flow efficiently with Nash-Sutcliffe model efficiency coefficient of 0.90 (0.86) and 0.86 (0.86) for the basin-wide (zone-wise) approach in the Astore and Hunza River Basins, respectively, over the entire simulation period. Mean annual discharge was projected to increase by 11–58% and 14–90% in the Astore and Hunza River Basins, respectively, under all the RCP mid- and late-21st-century scenarios. Mean summer discharge was projected to increase between 10–60% under all the RCP scenarios of mid- and late-21st century in the Astore and Hunza basins. This study suggests that the water resources of Pakistan should be managed properly to lessen the damage to human lives, agriculture, and economy posed by expected future floods as indicated by the climatic projections.

Incorporating snow model and snowmelt runoff model for streamflow simulation in a snow-dominated mountainous basin in the western Hindukush-Himalaya region

“…The DDF values varied with elevation and the values for the low (1593-3000 m), middle (3001-3500 m) and high (3501-5694 m) elevation zones were 0.3, 0.6 and 0.9 (cm°C -1 d -1 ), respectively. This finding is in line with prior studies on Himalayan basins showing that the DDF increases with elevation (Tahir et al, 2011;Hayat et al, 2019). In addition, we found that the PG is positive at altitudes 1593-4000 m (+ 0.002 m -1 ) while becoming zero in high elevation zones above 4000 m. A previous study (Immerzeel et al, 2012) also found a strong positive vertical precipitation gradient value of 0.0021 m -1 in the upper Indus basin.…”

“…Further evaluation of the SRM was carried out with the Pearson correlation coefficient and the Root Mean Square Error (RMSE) to determine the correlation between the measured and simulated daily discharges (Table II). Landsat and MODIS satellite remote sensing products are widely used as input for snowmelt runoff modelling for current and future runoff simulations (Martinec and Rango, 1986;Dey et al, 1989;Tahir et al, 2011;Adnan et al, 2017;Azmat et al, 2017;Hayat et al, 2019), although these products have limitation in snow cover estimation due to their spatio-temporal resolution and cloud cover. There are also limitations with assuming the future SCA for runoff simulation.…”

“…The spatial distribution of snowfall and snowmelt, including their altitudinal characteristics, is essential for snowmelt runoff modelling in high mountain catchments. Previous studies (Tahir et al, 2011;Zhang et al, 2014;Hayat et al, 2019) have assumed parameter values from the literature or during model calibration for runoff simulations. But the topography, geography and geology of regions differ, which affects climatic conditions and runoff generation.…”

Hydrological/Hydraulic Modeling-Based Thresholding of Multi SAR Remote Sensing Data for Flood Monitoring in Regions of the Vietnamese Lower Mekong River Basin

“…Broadly, dams, sediment mining, and climate change effects led to significant changes in the hydrological regime, the environment, and various ecosystems [13,27], such as a decline in the flood season water discharge and annual sediment flux, water quality degradation, riverine aquatic biological communities, and fish assemblages [28]. The sediment discharge is −80 million ton/year and decreased over the last decades as a result of dam construction [29].…”

“…However, fewer studies have inverted this process and used the results of hydrological/hydraulic models to calibrate remote sensing-based flood extractions. Hydrological and hydraulic modeling commonly require extensive data inputs [12,13] based around four key groupings, namely, topographic, hydro-meteorological, soil, and land cover data.…”