Comparison of Snow Indices in Assessing Snow Cover Depth in Northern Kazakhstan

2022

Full text Open access: Gold Metadata (CSL-JSON)
DOI 10.3390/su14159643
Data confidence 70 medium
How this score is calculated

It is built from checkable properties of the record itself: whether the article has a DOI, how many independent sources confirmed its data, whether the required fields are filled in, and how recent the latest confirmation is. Disagreement between sources and a missing identifier lower it. A value of 80 or above means the record was published without further checking; 60 to 79 means it is published at reduced confidence, with a manual check advisable. A record verified by an editor by hand is never pushed below 90 by a recalculation. This scores our data about the article, not the article itself.

Abstract

This study compares the performances of four existing snow indices (Normalized-Difference Snow Index, Normalized-Difference Snow and Ice Index, Difference Snow Index, and Ratio Snow Index) in estimating snow cover depth at three agricultural enterprises in different soil zones, namely, the “North Kazakhstan Agricultural Experimental Station”, A.I. Barayev “Research and Production Center for Grain Farming”, and “Naidorovskoe”. From 30 January to 9 February 2022, the snow cover thickness and density were measured at 410 and 285 points, respectively, throughout the agricultural enterprise territories. It was found that: (1) snow-covered territories were effectively classified using all spectral indices except both combinations of RSI; (2) the snow cover fraction maps generated from DSI most accurately classified the non-snow areas as forest plantations, settlements, and strongly blown uplands; (3) the maps generated from DSI-2 presented a clear pattern of objects in all three study areas; (4) the liquid water in snowpacks is available in excess for possible reservation and rational use in agriculture during the dry season. At the “North Kazakhstan AES”, A.I. Barayev “Research and Production Center for Grain Farming”, and “Naidorovskoe”, the RMSE varied from 5.62 (DSI-2) to 6.85 (NDSII-2), from 3.46 (DSI-2) to 4.86 (RSI-1), and from 2.86 (DSI-2) to 3.53 (NDSII-1), respectively. The DSI-2-based snow depths best matched the ground truth, with correlations of 0.78, 0.69, and 0.80, respectively.