TY - JOUR
T1 - A salinity projection model for determining impacts of climate change on river ecosystems in Taiwan
AU - Suen, Jian Ping
AU - Lai, Hung Nien
N1 - Funding Information:
The authors gratefully acknowledge the research support of the National Science Council, Taiwan under Grant Number 96-2221-E-006-264-MY3 . The authors also acknowledge the assistance of Dr. Wayland Eheart, Dr. Pao-Shan Yu, and Dr. Cathy Marcinkevage in various aspects of this work.
PY - 2013/6/7
Y1 - 2013/6/7
N2 - Climate change would impact ecosystems in many different ways, including alteration of hydrological conditions. The purpose of the research described in this paper is to determine the potential impacts of climate change on river ecosystems by mathematically simulating changes in salinity. Salinity, which is highly related to the relative abundance of particular organisms in the river and estuary wetland ecosystems, is a good indicator for impacts of climate change. The salinity projection model described in this research uses back-propagation neural networks, a robust method to simulate water quality conditions, to simulate salinity changes at several locations in a Taiwanese river. The results show the increase of salinity among all study sites under all climate change scenarios. We relate this to aquatic organism population effects by noting the threats of increased salinity on blockages or competition in some areas among species. Riparian mangroves and wetland plants near the river mouth may face increased stress due to the increased salinity concentrations. This tool allows a potential threat caused by salinity change to be analyzed as precautionary information for water resources and river ecosystem management.
AB - Climate change would impact ecosystems in many different ways, including alteration of hydrological conditions. The purpose of the research described in this paper is to determine the potential impacts of climate change on river ecosystems by mathematically simulating changes in salinity. Salinity, which is highly related to the relative abundance of particular organisms in the river and estuary wetland ecosystems, is a good indicator for impacts of climate change. The salinity projection model described in this research uses back-propagation neural networks, a robust method to simulate water quality conditions, to simulate salinity changes at several locations in a Taiwanese river. The results show the increase of salinity among all study sites under all climate change scenarios. We relate this to aquatic organism population effects by noting the threats of increased salinity on blockages or competition in some areas among species. Riparian mangroves and wetland plants near the river mouth may face increased stress due to the increased salinity concentrations. This tool allows a potential threat caused by salinity change to be analyzed as precautionary information for water resources and river ecosystem management.
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U2 - 10.1016/j.jhydrol.2013.04.020
DO - 10.1016/j.jhydrol.2013.04.020
M3 - Article
AN - SCOPUS:84877901951
SN - 0022-1694
VL - 493
SP - 124
EP - 131
JO - Journal of Hydrology
JF - Journal of Hydrology
ER -