Importance and vulnerability of the world's water towers.

Mountains are the water towers of the world, supplying a substantial part of both natural and anthropogenic water demands1,2. They are highly sensitive and prone to climate change3,4, yet their importance and vulnerability have not been quantified at the global scale. Here we present a global water tower index (WTI), which ranks all water towers in terms of their water-supplying role and the downstream dependence of ecosystems and society. For each water tower, we assess its vulnerability related to water stress, governance, hydropolitical tension and future climatic and socio-economic changes. We conclude that the most important (highest WTI) water towers are also among the most vulnerable, and that climatic and socio-economic changes will affect them profoundly. This could negatively impact 1.9 billion people living in (0.3 billion) or directly downstream of (1.6 billion) mountainous areas. Immediate action is required to safeguard the future of the world's most important and vulnerable water towers.

Geomorphic and geologic controls of geohazards induced by Nepal's 2015 Gorkha earthquake.

The Gorkha earthquake (magnitude 7.8) on 25 April 2015 and later aftershocks struck South Asia, killing ~9000 people and damaging a large region. Supported by a large campaign of responsive satellite data acquisitions over the earthquake disaster zone, our team undertook a satellite image survey of the earthquakes' induced geohazards in Nepal and China and an assessment of the geomorphic, tectonic, and lithologic controls on quake-induced landslides. Timely analysis and communication aided response and recovery and informed decision-makers. We mapped 4312 coseismic and postseismic landslides. We also surveyed 491 glacier lakes for earthquake damage but found only nine landslide-impacted lakes and no visible satellite evidence of outbursts. Landslide densities correlate with slope, peak ground acceleration, surface downdrop, and specific metamorphic lithologies and large plutonic intrusions.

Detection and quantification of snow algae with an airborne imaging spectrometer.

We describe spectral reflectance measurements of snow containing the snow alga Chlamydomonas nivalis and a model to retrieve snow algal concentrations from airborne imaging spectrometer data. Because cells of C. nivalis absorb at specific wavelengths in regions indicative of carotenoids (astaxanthin esters, lutein, beta-carotene) and chlorophylls a and b, the spectral signature of snow containing C. nivalis is distinct from that of snow without algae. The spectral reflectance of snow containing C. nivalis is separable from that of snow without algae due to carotenoid absorption in the wavelength range from 0.4 to 0.58 microm and chlorophyll a and b absorption in the wavelength range from 0.6 to 0.7 microm. The integral of the scaled chlorophyll a and b absorption feature (I(0.68)) varies with algal concentration (C(a)). Using the relationship C(a) = 81019.2 I(0.68) + 845.2, we inverted Airborne Visible Infrared Imaging Spectrometer reflectance data collected in the Tioga Pass region of the Sierra Nevada in California to determine algal concentration. For the 5.5-km(2) region imaged, the mean algal concentration was 1,306 cells ml(-1), the standard deviation was 1,740 cells ml(-1), and the coefficient of variation was 1.33. The retrieved spatial distribution was consistent with observations made in the field. From the spatial estimates of algal concentration, we calculated a total imaged algal biomass of 16.55 kg for the 0.495-km(2) snow-covered area, which gave an areal biomass concentration of 0.033 g/m(2).