Legacies in Flux: How Nutrient Histories, Land Use, and Climate Change Reshape Riverine N:P Ratios

Long-term dynamics of riverine nitrogen-to-phosphorus (N:P) ratios remain inadequately understood due to interactions among climate, land use, and legacy nutrients. Based on a 40-year (1980–2020) data set from the Yongan Watershed in eastern China, this study quantified watershed N and P inputs and riverine N/P ratio dynamics, disentangled the effects of legacy nutrients, land use, and climate variability on river N/P ratios, and projected their future trends under alternative scenarios of land use and climate change. Our results revealed nonlinear and asynchronous relationships between watershed inputs and riverine exports, driven by differential legacy responses of N and P. A 14-year lag provided the best fit between watershed input ratios and riverine export ratios (R2 = 0.93). Riverine N/P ratios were positively correlated with agricultural land and grassland cover but negatively correlated with urban land and temperature. Our scenario-based projections indicate that future climate warming, urban expansion, and grassland loss will further decrease riverine N/P ratios and heighten the risk of eutrophication. Therefore, river management in the Yongan Watershed should consider both N and P together in a coordinated manner with particular attention to legacy nutrient pools and urban P runoff.

Authors

Institutions

Publication Details

Journal
ACS ES&T Water
Published
2026-01-27
DOI
https://doi.org/10.1021/acsestwater.5c01112
Primary Topic
Soil and Water Nutrient Dynamics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Legacies in Flux: How Nutrient Histories, Land Use, and Climate Change Reshape Riverine N:P Ratios

Jia Zhou, Zheqi Pan, Zhihan Cheng, Minpeng Hu et al.
ACS ES&T Water
Soil and Water Nutrient Dynamics
article

Legacies in Flux: How Nutrient Histories, Land Use, and Climate Change Reshape Riverine N:P Ratios

Jia Zhou, Zheqi Pan, Zhihan Cheng, Minpeng Hu, Yucang Wang, Longdan Ma, Yi Pan, Jianguo Wu, Dingjiang Chen
article en

Abstract

Long-term dynamics of riverine nitrogen-to-phosphorus (N:P) ratios remain inadequately understood due to interactions among climate, land use, and legacy nutrients. Based on a 40-year (1980–2020) data set from the Yongan Watershed in eastern China, this study quantified watershed N and P inputs and riverine N/P ratio dynamics, disentangled the effects of legacy nutrients, land use, and climate variability on river N/P ratios, and projected their future trends under alternative scenarios of land use and climate change. Our results revealed nonlinear and asynchronous relationships between watershed inputs and riverine exports, driven by differential legacy responses of N and P. A 14-year lag provided the best fit between watershed input ratios and riverine export ratios (R2 = 0.93). Riverine N/P ratios were positively correlated with agricultural land and grassland cover but negatively correlated with urban land and temperature. Our scenario-based projections indicate that future climate warming, urban expansion, and grassland loss will further decrease riverine N/P ratios and heighten the risk of eutrophication. Therefore, river management in the Yongan Watershed should consider both N and P together in a coordinated manner with particular attention to legacy nutrient pools and urban P runoff.

ACS ES&T WaterVol. 6(2)
ZheJiang Academy of Agricultural Sciences (CN), Arizona State University (US), Zhejiang University (CN)
Climate action
Openalex Percentile: Top 78%
Soil and Water Nutrient Dynamics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.