Predicting glacio‐hydrologic change in the headwaters of the Zongo River, Cordillera Real, Bolivia

Abstract

In many partially glacierized watersheds glacier recession driven by a warming climate could lead to complex patterns of streamflow response over time, often marked with rapid increases followed by sharp declines, depending on initial glacier ice cover and rate of climate change. Capturing such “phases” of hydrologic response is critical in regions where communities rely on glacier meltwater, particularly during low flows. In this paper, we investigate glacio‐hydrologic response in the headwaters of the Zongo River, Bolivia, under climate change using a distributed glacio‐hydrological model over the period of 1987–2100. Model predictions are evaluated through comparisons with satellite‐derived glacier extent estimates, glacier surface velocity, in situ glacier mass balance, surface energy flux, and stream discharge measurements. Historically (1987–2010) modeled glacier melt accounts for 27% of annual runoff, and 61% of dry season (JJA) runoff on average. During this period the relative glacier cover was observed to decline from 35 to 21% of the watershed. In the future, annual and dry season discharge is projected to decrease by 4% and 27% by midcentury and 25% and 57% by the end of the century, respectively, following the loss of 81% of the ice in the watershed. Modeled runoff patterns evolve through the interplay of positive and negative trends in glacier melt and increased evapotranspiration as the climate warms. Sensitivity analyses demonstrate that the selection of model surface energy balance parameters greatly influences the trajectory of hydrological change projected during the first half of the 21st century. These model results underscore the importance of coupled glacio‐hydrology modeling.

Rapid decline of snow and ice in the tropical Andes – Impacts, uncertainties and challenges ahead

“…Wagnon et al (1999) Characterizing evapotranspiration from non-glacierized surfaces has equally been a challenge and studies are limited due to lack of meteorological data. Buytaert et al (2007) and Córdova et al (2015), suggested values between 1.8 and 2.0 mm d A reduction of glacier cover will therefore reduce streamflow, because of increased evapotranspiration from newly ice-free areas (Frans et al, 2015). However, this effect tends to reduce quickly with catchment size and distance from the glacier terminus.…”

“…Frans et al, 2015). Ideally this requires a realistic simulation of dynamic glacier flow, which is still a challenge in hydro-glaciologic modeling.…”

“…In another study on Zongo glacier, Frans et al (2015) applied a distributed glacio-hydrologic model to study the response of river discharge to future glacier retreat, with a simplified dynamic model using the shallow ice approximation approach. Their climate forcing data were obtained by downscaling reanalysis and CMIP5 model data using a stochastic weather generator.…”

“…As discussed in Sections 3.2 and 3.3, the only future glacier change projections including ice dynamics performed in the tropical Andes were done on the highly monitored Zongo glacier, Bolivia (Réveillet et al, 2015;Frans et al, 2015) where ice thickness was measured in-situ. However, even though more in-situ measurements on individual glaciers are needed, it is impossible to directly measure ice thickness on all the individual glaciers, given the cost, logistics, accessibility, etc.…”

Quantification of different flow components in a high-altitude glacierized catchment (Dudh Koshi, Nepalese Himalaya)

“…The resulting DHSVM-GDM simulates the spatial distribution and the temporal evolution of the principal water balance terms (soil moisture, evapotranspiration, sublimation, glacier mass balance, snow cover, and runoff) at hourly to daily time scales. It uses a two-layer energy and mass balance module for simulating snow cover evolution and a single layer energy and mass balance module for glaciers (Andreadis et al, 2009;Naz et al, 2014) and has been applied in a number of studies 5 for snow and cold regions hydrology (e.g., Leung et al, 1996;Leung and Wigmosta, 1999;Westrick et al, 2002;Whitaker et al, 2003;Zhao et al, 2009;Bewley et al, 2010;Cristea et al, 2014;Frans et al, 2015). Distributed meteorological data (air temperature, precipitation, relative humidity, wind speed, and shortwave and longwave incoming radiation) are requested as input, as well as distributed geographical information (elevation, soil type, landcover, soil depth, and ice thickness).…”