Advancing ecohydrology in the 21st century: a convergence of opportunities

Research output: Contribution to journalReview articlepeer-review

Authors

  • Andrew J. Guswa
  • Doerthe Tetzlaff
  • John S. Selker
  • Darryl E. Carlyle-Moses
  • Elizabeth W. Boyer
  • Michael Bruen
  • Carles Cayuela
  • Irena F. Creed
  • Nick van de Giesen
  • Domenico Grasso
  • Janice E. Hudson
  • Sean A. Hudson
  • Shin'ichi Iida
  • Robert B. Jackson
  • Gabriel G. Katul
  • Tomo'omi Kumagai
  • Pilar Llorens
  • Flavio Lopes Ribeiro
  • Beate Michalzik
  • Kazuki Nanko
  • Christopher Oster
  • Diane E. Pataki
  • Catherine A. Peters
  • Andrea Rinaldo
  • Daniel Sanchez Carretero
  • Branimir Trifunovic
  • Maciej Zalewski
  • Marja Haagsma
  • Delphis F. Levia

Colleges, School and Institutes

Abstract

Nature-based solutions for water-resource challenges require advances in the science of ecohydrology. Current understanding is limited by a shortage of observations and theories that can further our capability to synthesize complex processes across scales ranging from submillimetres to tens of kilometres. Recent developments in environmental sensing, data, and modelling have the potential to drive rapid improvements in ecohydrological understanding. After briefly reviewing advances in sensor technologies, this paper highlights how improved measurements and modelling can be applied to enhance understanding of the following ecohydrological examples: interception and canopy processes, root uptake and critical zone processes, and up-scaled effects of land use on streamflow. Novel and improved sensors will enable new questions and experiments, while machine learning and empirical methods provide additional opportunities to advance science. The synergy resulting from the convergence of these parallel developments will provide new insight into ecohydrological processes and thereby help identify nature-based solutions to address water-resource challenges in the 21st century.

Details

Original languageEnglish
Article numbere2208
JournalEcohydrology
Volume13
Issue number4
Publication statusPublished - 8 Apr 2020

Keywords

  • critical zone processes, environmental sensing, interception, land use, machine learning, measurement, modelling, streamflow

Sustainable Development Goals