Abstract

AbstractCosmic‐ray neutron sensing (CRNS) is a promising non‐invasive technique to estimate snow water equivalent (SWE) over large areas. In contrast to preliminary studies focusing on shallow snow conditions (SWE 130 mm), more recently the method was shown experimentally to be sensitive also to deeper snowpacks providing the basis for its use at mountain experimental sites. However, hysteretic neutron response has been observed for complex snow cover including patchy snow‐free areas. In the present study we aimed to understand and support the experimental findings using a comprehensive neutron modeling approach. Several simulations have been set up in order to disentangle the effect on the signal of different land surface characteristics and to reproduce multiple observations during periods of snow melt and accumulation. To represent the actual land surface heterogeneity and the complex snow cover, the model used data from terrestrial laser scanning. The results show that the model was able to accurately reproduce the CRNS signal and particularly the hysteresis effect during accumulation and melting periods. Moreover, the sensor footprint was found to be anisotropic and affected by the spatial distribution of liquid water and snow as well as by the topography of the nearby mountains. Under fully snow‐covered conditions the CRNS is able to accurately estimate SWE without prior knowledge about snow density profiles or other spatial anomalies. These results provide new insights into the characteristics of the detected neutron signal in complex terrain and support the use of CRNS for long‐term snow monitoring in high elevated mountain environments.

Highlights

  • In regions relying on snow-fed mountain rivers, snow water equivalent (SWE) is a fundamental environmental variable for the management of water resources (Clark et al, 2011; Sturm et al, 2017; Viviroli et al, 2007)

  • The 3 (2D) and 4 (3D) scenario shows lower total neutron counts being caused by topographic shielding (Dunne et al, 1999) of parts of the neutron flux

  • Focusing on Cosmic-ray neutron sensing (CRNS) with a footprint of several hectares, only the large-scale effects caused by elevation changes were considered

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Summary

Introduction

In regions relying on snow-fed mountain rivers, snow water equivalent (SWE) is a fundamental environmental variable for the management of water resources (Clark et al, 2011; Sturm et al, 2017; Viviroli et al, 2007). In contrast to single SWE measurements that are affected by small-scale variability, data aggregated over distances of up to 400 m have been found to correlate well with terrain parameters (Grünewald et al, 2013; Helfricht et al, 2014; Jost et al, 2007). This is of high relevance for the calibration and validation of snow-hydrological models, as most modeling approaches dealing with snow redistribution are designed to capture processes at an intermediate scale of hundreds of meters, neglecting the sub-grid variability (Freudiger et al, 2017). Differences between single point measurements and modeled SWE values can be substantial, even when the mean value of a grid cell is captured accurately by the model

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