hydrograph separation in the headwaters of the shule river basin: combining water chemistry and stable isotopes

hydrograph separation in the headwaters of the shule river basin: combining water chemistry and stable isotopes

;Jiaxin Zhou;Jinkui Wu;Shiwei Liu;Guoxiong Zeng;Jia Qin;Xiuna Wang;Qiudong Zhao
The Journal of biological chemistry 2015 Vol. 2015 pp. -
246
zhou2015advanceshydrograph

Abstract

The runoff components were identified in the headwater area of Shule River Basin, using isotopic and chemical tracing with particular focus on the temporal variations of catchment sources. A total of 95 samples, including precipitation, groundwater, and glacial meltwater, were collected and analyzed for stable water isotopes (18O and 2H) and major chemical ion parameters (potassium, sodium, calcium, magnesium, sulfate, chloride, and bicarbonate). Based on the isotope and water chemistry data, we applied end member mixing analysis (EMMA) to identify and quantify the major runoff generating sources and their contributions. The contributions of groundwater, precipitation, and glacial meltwater were 66.7%, 19.9%, and 13.4%, respectively. The study indicated that groundwater dominated runoff in the headwater area of Shule River Basin. The roles of glacier meltwater should be remarkable in water resource management in this basin. The uncertainties of the EMMA method were summarized and estimated via a classical Gaussian error propagation technique. Analyses suggested that the uncertainty in the measurement method was less important than that in the temporal and spatial variations of tracer concentrations. The uncertainty was sensitive when the difference between mixing components was small. Therefore, the variation of tracers and the difference of mixing components should be considered when hydrograph separation was applied in the basin.

Citation

ID: 137366
Ref Key: zhou2015advanceshydrograph
Use this key to autocite in SciMatic or Thesis Manager

References

Blockchain Verification

Account:
NFT Contract Address:
0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
137366
Unique Identifier:
10.1155/2015/830306
Network:
Scimatic Chain (ID: 481)
Loading...
Blockchain Readiness Checklist
Authors
Abstract
Journal Name
Year
Title
5/5
Creates 1,000,000 NFT tokens for this article
Token Features:
  • ERC-1155 Standard NFT
  • 1 Million Supply per Article
  • Transferable via MetaMask
  • Permanent Blockchain Record
Blockchain QR Code
Scan with Saymatik Web3.0 Wallet

Saymatik Web3.0 Wallet