SDSM‐MTI (SemiDistributed Snowmelt Model - Modified Temperature Index)

A modified temperature index model (SDSM‐MTI) that uses both near surface soil temperature (Tg) and air temperature (Ta).

temperature indexnear surfacesoil temperatureair temperature



Initial contribute: 2020-01-09


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Application-focused categoriesNatural-perspectiveLand regions
Application-focused categoriesNatural-perspectiveFrozen regions

Detailed Description

English {{currentDetailLanguage}} English

Quoted from: Singh, Purushottam Raj, Thian Yew Gan, and Adam Kenea Gobena. "Evaluating a hierarchy of snowmelt models at a watershed in the Canadian Prairies." Journal of Geophysical Research: Atmospheres 114, no. D4 (2009). 

A modified TI model (SDSM‐MTI) that includes the near‐surface soil temperature (Tg) as an additional predictor is proposed,
equation image
where Mrf is an adjustment factor for Mf so as to better capture the onset of initial snowmelt and is estimated from
equation image
where β1, β2, β3, and ψ are model parameters derived through calibration [see Singh et al., 2005]. As a tangent function, Mrf is relatively small when Tg < 0°C, and reaches an upper limit of one when Tg ≥ 0°C. The effect of Mrf is “felt” mostly during the onset of snowmelt because its value approaches 1.0 when Tg approaches 0°C. The desired rate of change of Mrf can be achieved by adjusting the parameter ψ. Tr is a reference temperature computed as a weighted average of Tg and Ta,
equation image
where χ is also a model parameter.

[10] The rationale for this model comes from past studies that pointed out the importance of Tg as an indicator of spring snowmelt [Woo and Valverde, 1982], as well as our own empirical analysis of data observed at the Paddle River Basin (PRB) in central Alberta. Analysis of hourly data observed for 6 years during the spring season (1 March to 30 April) at PRB shows that there is a significant correlation between net radiation (Rn) and Tg at daily time step [Singh et al., 2005]. Moreover, the data revealed that the correlation coefficient (ρ) between Tg and Rn (ranging from 0.62 to 0.89) was mostly higher than ρ between Ta and Rn (ranging from 0.47 to 0.87). Since Rn generally dominates the energy balance during spring snowmelt in the Canadian Prairies [Shook, 1995], adding Tg as another predictor should improve the performance of the TI method.



SDSM‐MTI team (2020). SDSM‐MTI (SemiDistributed Snowmelt Model - Modified Temperature Index), Model Item, OpenGMS,


Initial contribute : 2020-01-09



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