The essential value of long-term experimental data for hydrology and water management

Doerthe Tetzlaff* (Corresponding Author), Sean K. Carey, James P. Mcnamara, Hjalmar Laudon, Chris Soulsby

*Corresponding author for this work

Research output: Contribution to journalArticle

34 Citations (Scopus)
5 Downloads (Pure)

Abstract

Observations and data from long-term experimental watersheds are the foundation of hydrology as a geoscience. They allow us to benchmark process understanding, observe trends and natural cycles, and are pre-requisites for testing predictive models. Long-term experimental watersheds also are places where new measurement technologies are developed. These studies offer a crucial evidence base for understanding and managing the provision of clean water supplies; predicting and mitigating the effects of floods, and protecting ecosystem services provided by rivers and wetlands. They also show how to manage land and water in an integrated, sustainable way that reduces environmental and economic costs.
Original languageEnglish
Pages (from-to)2598–2604
Number of pages7
JournalWater Resources Research
Volume53
Issue number4
Early online date20 Apr 2017
DOIs
Publication statusPublished - Apr 2017

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water management
hydrology
watershed
ecosystem service
water supply
wetland
economics
river
cost
water
trend
land
effect

Keywords

  • data
  • long-term monitoring
  • water management
  • hydrology
  • catchment studies

ASJC Scopus subject areas

  • Environmental Science(all)

Cite this

The essential value of long-term experimental data for hydrology and water management. / Tetzlaff, Doerthe (Corresponding Author); Carey, Sean K.; Mcnamara, James P.; Laudon, Hjalmar; Soulsby, Chris.

In: Water Resources Research, Vol. 53, No. 4, 04.2017, p. 2598–2604 .

Research output: Contribution to journalArticle

Tetzlaff, Doerthe ; Carey, Sean K. ; Mcnamara, James P. ; Laudon, Hjalmar ; Soulsby, Chris. / The essential value of long-term experimental data for hydrology and water management. In: Water Resources Research. 2017 ; Vol. 53, No. 4. pp. 2598–2604 .
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