Effects of large-scale climate signals on snow cover in Khersan watershed, Iran
Book Chapter
Choubin, B, Roshan, H, Sajedi-Hosseini, F et al. (2019). Effects of large-scale climate signals on snow cover in Khersan watershed, Iran
. 1-10. 10.1016/B978-0-12-815998-9.00001-4
Choubin, B, Roshan, H, Sajedi-Hosseini, F et al. (2019). Effects of large-scale climate signals on snow cover in Khersan watershed, Iran
. 1-10. 10.1016/B978-0-12-815998-9.00001-4
Snowmelt is used for flow forecasting, agricultural productivity, soil moisture monitoring, and drought management. This is particularly in mountainous areas, such as Khersan watershed in Iran. In this chapter, the effects of large-scale climate signals on snow cover are discussed for up to 3-month lag time. For snow cover monitoring, the moderate resolution imaging spectroradiometer (MODIS) products were used during the period 2000-17. The most related signals were selected as predictors to model snow cover using multivariate adaptive regression splines (MARS) and M5Tree models. Results indicate that the correlation between snow cover and signals in the lag-time approach is higher than that in the simultaneous approach. Most important signals related with snow cover are geopotential height and Niño 1+2. Snow cover modeling results show that the M5Tree model can be useful for policy makers in mountainous basins where precipitation is falling mostly as snow.
