USE OF A RAPID HYDROLOGIC ASSESSMENT METHODOLOGY FOR CLARIFYING FUTURE STREAMFLOW VULNERABILITIES IN THE CONTEXT OF RIVER DEVELOPMENT DECISIONS ON THE RIO MARANON, PERU

The water resource wealth of remote mountain regions is paradoxically coupled with limited scientific study due to access, climate and terrain challenges. Hydrologic processes change rapidly across mountain landscapes and researchers face continued pressure to clarify what processes govern water supply at lower elevations, hundreds of kilometers from cryospheric source waters, where people, agriculture and hydropower utilize water.

Clarifying the spatial variation of hydrologic processes is central to improving our ability to scale across large basins. Promising remote sensing and modeling approaches to better understand surface-groundwater interactions stand to gain accuracy and robustness with field data validation, but longitudinal field data is often not available in remote mountain regions. I utilize water sampling and hydrochemistry (isotopes and major ions) of surface and source waters to clarify elevational gradients of surface-groundwater interactions over large scales (200-1000km from glacier snout). I employ a “rapid hydrologic assessment” methodology that targets only the most essential sampling locations over regional basins using a combination of satellite image processing to map controlling landscape variables and anomalous feature mapping that may indicate hydrologic “hot spots” in the study domain. Sampling plan design responds to the prompt: “how can we explain the most hydrologic variability with the least amount of data?” Honing in on only the most critical hydrologic knick points yields the ability to acquire in situ data over large, water-management relevant basin scales at the expense of superfluous data.

Here I present results from a 620km alpine-to-jungle longitudinal hydrologic study in Peru on the Rio Maranon, a system subject to imminent, major hydropower development. Utilizing mixing model approaches, the hydrochemistry of surface waters can shed light on the variation in surface-groundwater interactions from headwaters to plains. In turn, this data provides a calibration/validation data set for hydrologic models relied on by water managers, and it gives perspective to future water vulnerability statements and flow sustainability concerns in snow and ice fed mountain basins.