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Identifying Climate and Human Impact Trends in Streamflow: A Case Study in Uruguay

1
National Research Program on Production and Environmental Sustainability, National Institute of Agricultural Research of Uruguay, 90200 Rincón del Colorado, Departamento de Canelones, Uruguay
2
Institute of Fluid Mechanics and Environmental Engineering, School of Engineering, Universidad de la República, 11200 Montevideo, Departamento de Montevideo, Uruguay
3
School of Life and Environmental Sciences, The University of Sydney, Sydney, NSW 2006, Australia
*
Author to whom correspondence should be addressed.
Water 2019, 11(7), 1433; https://doi.org/10.3390/w11071433
Received: 17 June 2019 / Revised: 6 July 2019 / Accepted: 9 July 2019 / Published: 12 July 2019
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Abstract

Land use change is an important driver of trends in streamflow. However, the effects are often difficult to disentangle from climate effects. The aim of this paper is to demonstrate that trends in streamflow can be identified by analysing residuals of rainfall-runoff simulations using a Generalized Additive Mixed Model. This assumes that the rainfall-runoff model removes the average climate forcing from streamflow. The case study involves the Santa Lucía river (Uruguay), the GR4J rainfall-runoff model, three nested catchments ranging from 690 to 4900 km 2 and 35 years of observations (1981–2016). Two exogenous variables were considered to influence the streamflow. Using satellite data, growth in forest cover was identified, while the growth in water licenses was obtained from the water authority. Depending on the catchment, effects of land use change differ, with the largest catchment most impacted by afforestation, while the middle size catchment was more influenced by the growth in water licenses. View Full-Text
Keywords: statistical hydrology; trend identification; land use change; GR4J statistical hydrology; trend identification; land use change; GR4J
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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MDPI and ACS Style

Navas, R.; Alonso, J.; Gorgoglione, A.; Vervoort, R.W. Identifying Climate and Human Impact Trends in Streamflow: A Case Study in Uruguay. Water 2019, 11, 1433.

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