An Integrated Approach for Site Selection of Snow Measurement Stations

Abstract

Snowmelt provides a reliable water resource for meeting domestic, agricultural, industrial and hydropower demands. Consequently, estimating the available snow water equivalent is essential for water resource management of snowy regions. Due to the spatiotemporal variability of the snowfall pattern in mountainous areas and difficult access to high altitudes areas, snow measurement is one of the most challenging hydro-meteorological data collection efforts. Development of an optimum snow measurement network is a complex task that requires integration of meteorological, hydrological, physiographical and economic studies. In this study, site selection of snow measurement stations is carried out through an integrated process using observed snow course data and analysis of historical snow cover images from National Oceanic Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) at both regional and local scales. Several important meteorological and hydrological factors, such as monthly and annual rainfall distribution, spatial distribution of average frequency of snow observation (FSO) for two periods of snow falling and melting season, as well as priority contribution of sub-basins to annual snowmelt runoff are considered for selecting optimum station network. The FSO maps representing accumulation of snowfall during falling months and snowpack persistence during melting months are prepared in the GIS based on NOAA-AVHRR historical snow cover images. Basins are partitioned into 250 m elevation intervals such that within each interval, establishment of new stations or relocation/removing of the existing stations were proposed. The decision is made on the basis of the combination of meteorological, hydrological and satellite information. Economic aspects and road access constraints are also considered in determining the station type. Eventually, for the study area encompassing a number of large basins in southwest of Iran, several new stations and relocation of some existing stations are proposed.

Optimal design of snow stake networks to estimate snow depth in an alpine mountain range

“…On the other hand, in the scientific literature, we have not found any previous work that addresses the snow monitoring network optimization problem for a whole mountain range. The works related to the optimal design of snow monitoring networks are focused on catchment systems (Galeati et al, ; Oroza et al, ; Saghafian et al, ; Welch et al, ) and even at smaller scales (Butcher & McManamon, ; Kerkez et al, ; Molotch & Bales, ). The applicability of other techniques used in these works to large scale systems represents an interesting future research line.…”

“…They are summarized in Table . All of them aim to select an optimal network as a subset of the existing spatial observations, which sometimes comes from detailed field surveys or snow course data (Butcher & McManamon, ; Galeati et al, ; Molotch & Bales, ; Saghafian et al, ; Welch et al, ), or light detection and ranging images (Kerkez et al, ; Oroza et al, ). Decision makers need accurate historical snow information to quantify water resources and the potential impacts of climate change on it, which can be crucial for a rational definition of management decision.…”

GIS-AHP based site selection to identify the optimum number of meteorological stations: Karasu Watershed case study

“…Despite the good quality and well-functioning meteorological station instruments, the issue of station location and optimal number adds to the importance of the topic for reliable data collecting (Saghafian et al, 2016). However, climatic data can also be measured using satellite sensors and weather radars.…”

“…Pardo-Igúzquiza (1998) uses the simulated annealing as an algorithm of a random search for the optimal location of rainfall measurement gauges, where the double criterion of estimation accuracy and economic cost are taken into account. Also, a field observations method which is supported by satellite images is used by Saghafian et al (2016) to select a proper site for installing the meteorological stations. The composing method of kriging and entropy is used by Chen et al (2008); Xu et al (2018); Yeh et al (2011) for the determination of the location and number of raingauge stations in the optimal rainfall network.…”