Application of SWAT model to assess snowpack development and streamflow in the Cannonsville watershed, New York, USA

Abstract

Abstract:Snow is an important component of the water resources of New York State and the watersheds and reservoirs of New York City (NYC) water supply. In many of the NYC water supply watersheds the hydrologic regimes of high-elevation headwaters are linked to streamflow and channel processes in low-elevation stream reaches that serve as inputs to water supply reservoirs. To better simulate this linkage there is a need to understand spatial variations in snowpack and snowmelt. Snowmelt hydrology is an important component of the Soil and Water Assessment Tool (SWAT) model in watersheds where spring runoff is strongly affected by melting snow. This study compares model simulated snowpack and snowmelt at different elevation bands with snow survey data available for the Cannonsville reservoir watershed. Simulations examine the effects of parameterising the SWAT snowmelt sub-model using 1, 3, and 5 elevation bands by comparison with measured snow and streamflow. Comparison between measured and simulated snowpack produced correlation coefficients ranging from 0Ð35 to 0Ð85. Simulations of both daily and seasonal streamflow, improved when using 3 elevation bands with r 2 of 0Ð73 and E NS of 0Ð72. Streamflow simulations showed slightly lower model performance when basin elevation was assumed to be equal to snow survey site elevation, due to the snow survey sites being somewhat biased toward lower elevations. The effect of climate change was also evaluated and showed that under higher air temperatures in future climate change scenarios, SWAT indicated more precipitation falling as rain, increased and earlier snowmelt, and a reduced snowpack leading to a change in the pattern of streamflow, particularly during winter and early spring.

Hydrological Modeling of the Upper Indus Basin: A Case Study from a High-Altitude Glacierized Catchment Hunza

“…However, the SCS-CN approach defines a rainfall event as the sum of all rainfall that occurs during one day, and this might lead to underestimation of peak runoff [42]. Similarly, other factors (topographic properties, aspects, slope, soil, and different land use/cover) also have an effect on the peak flow, snow accumulation and melt processes [12]. The p-factor and r-factor values were 0.45 and 0.25 during the calibration period (1998)(1999)(2000)(2001)(2002)(2003)(2004)) and these were 0.79 (p-factor) and 0.85 (r-factor) for the validation period (2008-2010), respectively (Table 4).…”

“…Many different parameters affect snow extent and melting processes, including altitude, topography and terrain, aspect, slope and land-cover/use. However, such parameters are not well represented in the temperature index with elevation bands method [12]. This could possibly be a reason for not showing the insignificant impact of the catastrophic incidence of Attaabad Lake (initially, 24 km long and 130.032 m deep with surface area of 10,414 km 2 ) was formed on Hunza River due a massive landslide that occurred on 4 January 2010, took 20 precious human lives and rendered another 392 families homeless, and blocked Hunza River for about five months (4 January-27 May 2010) [45] formation on downstream flow in Hunza.…”

“…The model calibration was performed on daily, monthly, and yearly time steps. In this study, 21 parameters of the SWAT that affected snow, glacier-melt runoff, groundwater recharge, and evapotranspiration were calibrated (modified) to obtain simulated results that were close to the observed results by using a sensitivity analysis, in addition to relevant literature on the snow and glaciated mountainous regions [12,23,36,37]. Various parameters used for calibration and their ranges, with their source, are shown in Table 3.…”

“…The snow parameters SMFMN and SMFMX represent the minimum and maximum snow melting in winter and summer, respectively; if any changes occur in these values, the resultant melting is increasing [12]. The SNOCOVMX parameter represents the minimum water content of snow that agrees with a full cover of the snowy watershed [39].…”

“…Many studies have been conducted to calculate the snow and glacier melt and their hydrological processes on watershed or river basin scales in the Upper Indus Basin (UIB). Tahir et al [2], Akhtar et al [11], and others [12][13][14] have overlooked discussing glacier behavior on river basin scale [2,6], except [15]. Some studies have been carried out for the long-term prediction of streamflow based on future climate scenarios by adding the future monthly precipitation and temperature changes simulated by General Circulation Models (GCMs) to the baseline precipitation and temperature data [2] but none have adopted multi-objective or multi-variable calibration approaches, with the exception of [16], who used different parameters to analyze internal consistency simulation of glacier mass.…”