Water (Jun 2024)

Reflection of Daily, Seasonal and Interannual Variations in Run-Off of a Small River in the Water Isotopic Composition (δ<sup>2</sup>H, δ<sup>18</sup>O): A Case of the Ala-Archa Mountain River Basin with Glaciation (Kyrgyzstan, Central Asia)

  • Igor Tokarev,
  • Evgeny Yakovlev,
  • Sergey Erokhin,
  • Tamara Tuzova,
  • Sergey Druzhinin,
  • Andrey Puchkov

DOI
https://doi.org/10.3390/w16111632
Journal volume & issue
Vol. 16, no. 11
p. 1632

Abstract

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Small intermountain river basins are most suitable for developing new methods to estimate water balance due to their well-defined catchment boundaries, relatively rapid runoff processes, and accessible landscapes for study. In general terms, dissecting the hydrograph of a small mountain river requires calibration of the flow model against multi-year data sets, including (a) glacier mass balance and snow water content, (b) radiation balance calculation, (c) estimation of the groundwater contribution, and (d) water discharge measurements. The minimum primary data set is limited to the precipitation and temperature distributions at the catchment. This approach postulates that the conditions for the formation of all components of river flow are known in advance. It is reduced to calculating the dynamic balance between precipitation (input part) and runoff, ablation, and evaporation (output part). In practice, accurately accounting for the inflow and outflow components of the balance, as well as the impact of regulating reservoirs, can be a challenging task that requires significant effort and expense, even for the extensively researched catchments. Our studies indicate the potential benefits of an approach based on one-time, but detailed, observations of stable isotope composition, temperature, and water chemistry, in addition to standard datasets. This paper presents the results of the 2022–2023 work conducted in the basin of the small mountain river Ala-Archa, located on the northern slope of the Kyrgyz Range in Tien-Shan, which was chosen as an example due to its well-studied nature. Our approach could identify previously unknown factors of flow formation and assess the time and effectiveness of work in similar conditions.

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