Improved short-term operational streamflow forecasting for snow-melt dominated basins
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Snowmelt
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The spatial variability of snow water equivalent (SWE) can exert a strong influence on the timing and magnitude of snowmelt delivery to a watershed. Therefore, the representation of sub-grid or sub-watershed snow variability in hydrologic models is important for accurately simulating snowmelt dynamics and runoff response. The U.S. Geological Survey National Hydrologic Model infrastructure with the precipitation-runoff modelling system (NHM-PRMS) represents the sub-grid variability of SWE with snow depletion curves (SDCs), which relate snow-covered area to watershed-mean SWE during the snowmelt period. The main objective of this research was to evaluate the sensitivity of simulated runoff to SDC representation within the NHM-PRMS across the continental United States (CONUS). SDCs for the model experiment were derived assuming a range of SWE coefficient of variation values and a lognormal probability distribution function. The NHM-PRMS was simulated at a daily time step for each SDC over a 14-year period. Results highlight that increasing the sub-grid snow variability (by changing the SDC) resulted in a consistently slower snowmelt rate and longer snowmelt duration when averaged across the hydrologic response unit scale. Simulated runoff was also found to be sensitive to SDC representation, as decreases in simulated snowmelt rate by 1 mm day−1 resulted in decreases in runoff ratio by 1.8% on average in snow-dominated regions of the CONUS. Simulated decreases in runoff associated with slower snowmelt rates were approximately inversely proportional to increases in simulated evapotranspiration. High snow persistence and peak SWE:annual precipitation combined with a water-limited dryness index was associated with the greatest runoff sensitivity to changing snowmelt. Results from this study highlight the importance of carefully parameterizing SDCs for hydrologic modelling. Furthermore, improving model representation of snowmelt input variability and its relation to runoff generation processes is shown to be an important consideration for future modelling applications.
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Meltwater
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Stream flow
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Streamflow can be only measured as a spatially integrated value among the basin-wide water balance components. As the measurement of high-water flow is important for the river planning and the flood control measures in large rivers in Japan, new studies are proceeding with the improving the accuracy of streamflow measurement such as ADCP and PIV techniques. Meanwhile, during the low-flow period or in the small river, conventional gauging methods are used, including the current meter method and the weir. Dilution gauging method is effective particularly in the mountainous gravel-bed streams. However, reported examples are not so much. Understanding to the role of snow within the snowmelt runoff process is essential in the snowy cold region. Snow lysimeter and snow pillow are useful in these studies. Preferential flow through the snowpack and the dependence of percolation speed on the snow properties are studied using those equipments. Most difficult problem is how to estimate the basin averaged snowmelt amount. Additional researches are needed which combines conventional snow melting factor method and satellite imagery data.
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Meltwater
Flood forecasting
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Hydrological modelling
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While mountain runoff provides great potential for the development and life quality of downstream populations, it also frequently causes seasonal disasters. The accurate modeling of hydrological processes in mountainous areas, as well as the amount of meltwater from ice and snow, is of great significance for the local sustainable development, hydropower regulations, and disaster prevention. In this study, an improved model, the Soil Water Assessment Tool with added ice-melt module (SWATAI) was developed based on the Soil Water Assessment Tool (SWAT), a semi-distributed hydrological model, to simulate ice and snow runoff. A temperature condition used to determine precipitation types has been added in the SWATAI model, along with an elevation threshold and an accumulative daily temperature threshold for ice melt, making it more consistent with the runoff process of ice and snow. As a supplementary reference, the comparison between the normalized difference vegetation index (NDVI) and the quantity of meltwater were conducted to verify the simulation results and assess the impact of meltwater on the ecology. Through these modifications, the accuracy of the daily flow simulation results has been considerably improved, and the contribution rate of ice and snow melt to the river discharge calculated by the model increased by 18.73%. The simulation comparison of the flooding process revealed that the accuracy of the simulated peak flood value by the SWATAI was 77.65% higher than that of the SWAT, and the temporal accuracy was 82.93% higher. The correlation between the meltwater calculated by the SWATAI and the NDVI has also improved significantly. This improved model could simulate the flooding processes with high temporal resolution in alpine regions. The simulation results could provide technical support for economic benefits and reasonable reference for flood prevention.
Meltwater
SWAT model
Snowmelt
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Remote sensing is changing the approach in snowmelt runoff modelling. Instead of a simulated snow cover, the areal extent of the real snow cover can be periodically evaluated. Adaptation of depletion curves of the snow coverage for real time forecasts is outlined.
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Hydrological modelling
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Snowpack
Hydrological modelling
Elevation (ballistics)
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Meltwater
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