Abstract
The symbolic concept of world water towers refers to the capacity of mountains and uplands to provide freshwater to lowland watersheds. Rivers, streams, or any other waterbody constitute the watershed. The most emblematic world water towers in Europe are the Alps. Due to the global rise in temperature, the precipitation patterns have changed, resulting in long dry periods and short and very-intense rain events, represented by drought and floods, respectively. In parallel, with the accelerated melting process of glaciers in the mountains and snow shortage periods, freshwater availability will considerably reduce during the following years. Monitoring hydrological parameters in mountain and remote areas mainly relies on measuring water runs off. This variable is insufficient to ingest real-time models for forecasting water supply for many ecosystems. There are many limitations to developing monitoring infrastructure that provides high-quality data, overcomes the terrain's difficulty, and reduces the spatial heterogeneity of precipitation and water storage. One solution is to deploy large soil moisture, snowpack, and weather sensor networks. However, it is costly and difficult to maintain. Another possibility is using remote sensing products to measure soil moisture and snow coverage. Unfortunately, the spatial resolution is too large for the variability of mountain conditions due to terrain changes. Between these two scales, a technique based on measuring the attenuation of cosmic rays. The retrieved signal is related to the interactions with hydrogen, directly proportional to snow water equivalent and soil water content. This technique offers an advantage because it is non-invasive and does not disrupt the environment. Additionally, its considerable horizontal range and ability to penetrate depths of several centimeters, sufficient to reach the typical rooting depth, make it superior to remote sensing estimates. In this work that has been running for three years, we present a hardware and software infrastructure that provides quasi-near-real-time information based on an online system. It consists of a Cosmic Ray Neutron Sensor (CRNS), a photogrammetry station, and additional sensors (soil moisture, snow depth). In addition, we fusion UAV-based orthomosaics and digital surface models produced every year, to understand the footprint of the CRNS that can act as a validation site for an up-scale remote sensing method.