A Preliminary Assessment of the “Undercatching” and the Precipitation Pattern in an Alpine Basin

Patricia Jimeno-Sáez,Leticia Baena-Ruiz,Javier Senent-Aparicio,Eulogio Pardo-Igúzquiza,David Pulido-Velazquez,Antonio-Juan Collados-Lara

doi:10.3390/w12041061

Patricia Jimeno-Sáez, Leticia Baena-Ruiz + Show 4 more

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https://doi.org/10.3390/w12041061

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Abstract

Gauges modify wind fields, producing important systematic errors (undercatching) in the measurement of solid precipitation (Ps), especially under windy conditions. A methodology that combines geostatistical techniques and hydrological models to perform a preliminary assessment of global undercatch and precipitation patterns in alpine regions is proposed. An assessment of temperature and precipitation fields is performed by applying geostatistical approaches assuming different hypothesis about the relationship between climatic fields and altitude. Several experiments using different approximations of climatic fields in different approaches to a hydrological model are evaluated. A new hydrological model, the Snow-Témez Model (STM), is developed including two parameters to correct the solid (Cs) and liquid precipitation (Cr). The procedure allows identifying the best combination of geostatistical approach and hydrological model for estimating streamflow in the Canales Basin, an alpine catchment of the Sierra Nevada (Spain). The sensitivity of the results to the correction of the precipitation fields is analyzed, revealing that the results of the streamflow simulation are improved when the precipitation is corrected considerably. High values of solid Cs are obtained, while Cr values, although smaller than the solid one, are also significant.

Highlights

Solid precipitation measurement shows significant bias with respect to real values due to the phenomenon of undercatch
KED and RK): (1) calibrated Snow-Témez Model (STM) for which we included the correction coefficients (Cs and Cr) of the estimated precipitation and calibration parameters in the parameters to be optimized; (2) an approach obtained from the calibrated model (1) by removing the correction of the estimated precipitation (Cs = 1 and Cr = 1, instead of the optimal values obtained in the first approach); (3) a new STM model obtained by a new calibration in which the precipitation fields are not corrected
In this study a methodology to optimally combine different geostatistical approaches and a conceptual hydrological model was proposed in order to minimize differences between estimated and observed streamflow

Summary

Introduction

Solid precipitation measurement shows significant bias with respect to real values due to the phenomenon of undercatch This phenomenon, which is especially significant under windy conditions, depends on a number of relevant physical processes that affect the systematic errors involved in using gauges to measure precipitation [1,2,3,4,5]. These errors are long recognized as affecting all types of precipitation gauges [6] and are mainly associated with the deformation of the wind field above the gauge orifice, the wetting and evaporation losses on the internal walls of the gauge, and the splashing of raindrops or blowing of snow into or out of the gauge [3,7]; their aggregation usually yields underestimates of precipitation [2,7,8]. Sevruk (1982) [7], who considered wetting and evaporative losses, as well as wind-induced loss, estimated that wind effects decrease snowfall measurements by 50% or even more and published his work on methods for correcting systematic

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