https://doi.org/10.5194/hess-29-983-2025

Uncertainty in estimating precipitation in mountain headwaters can be transmitted to estimates of river discharge far downstream. Quantifying and reducing this uncertainty is needed to better constrain the uncertainty of hydrological predictions in rivers with mountain headwaters. Spatial estimation of precipitation fields can be accomplished through interpolation of snowfall and rainfall observations. These are often sparse in mountains, and so gauge density greatly affects precipitation uncertainty. Elevational lapse rates also influence uncertainty as they can vary widely between events, and observations are rarely made at multiple proximal elevations. Therefore, the spatial, temporal, and elevational domains need to be considered to quantify precipitation gauge network uncertainty. This study aims to quantify the spatiotemporal and elevational uncertainty of the spatial precipitation interpolated from gauged networks in the snowfall-dominated, triple continental divide Canadian Rockies headwaters of the Mackenzie, Nelson, Columbia, Fraser, and Mississippi rivers of British Columbia and Alberta in Canada and Montana in the USA. A 30-year (1991–2020) daily precipitation database was created in the region and utilized to generate spatial precipitation and uncertainty fields with kriging interpolation and lapse rates. The results indicate that gauge network coverage improved after the drought of 2001–2002, but it was still insufficient to decrease the domain-scale uncertainty, because most gauges were deployed in valley bottoms. Deploying gauges above 2000 m was identified as having the greatest cost benefits for decreasing uncertainty in the region. High-elevation gauge deployments associated with university research and other programs after 2005 had a widespread impact on the reduction of uncertainty. The greatest uncertainty in the recent period remains in the Nelson headwaters, whilst the lowest uncertainty is in the Mississippi headwaters. These findings show that both spatiotemporal and elevational components of precipitation uncertainty need to be quantified in order to estimate uncertainty for use in precipitation network design in mountain headwaters. Understanding and then reducing these uncertainties through additional precipitation gauges is crucial for more reliable prediction of river discharge.

https://doi.org/10.5194/hess-29-983-2025