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尽管美国河流中的磷浓度普遍下降,但磷流失量仍在增加。

Increasing phosphorus loss despite widespread concentration decline in US rivers.

机构信息

The National Key Laboratory of Water Disaster Prevention, Yangtze Institute for Conservation and Development, Key Laboratory of Hydrologic-Cycle and Hydrodynamic-System of Ministry of Water Resources, College of Hydrology and Water Resources, Hohai University, Nanjing 210024, China.

Department of Civil and Environmental Engineering, The Pennsylvania State University, University Park, PA 16802.

出版信息

Proc Natl Acad Sci U S A. 2024 Nov 26;121(48):e2402028121. doi: 10.1073/pnas.2402028121. Epub 2024 Nov 18.

Abstract

The loss of phosphorous (P) from the land to aquatic systems has polluted waters and threatened food production worldwide. Systematic trend analysis of P, a nonrenewable resource, has been challenging, primarily due to sparse and inconsistent historical data. Here, we leveraged intensive hydrometeorological data and the recent renaissance of deep learning approaches to fill data gaps and reconstruct temporal trends. We trained a multitask long short-term memory model for total P (TP) using data from 430 rivers across the contiguous United States (CONUS). Trend analysis of reconstructed daily records (1980-2019) shows widespread decline in concentrations, with declining, increasing, and insignificantly changing trends in 60%, 28%, and 12% of the rivers, respectively. Concentrations in urban rivers have declined the most despite rising urban population in the past decades; concentrations in agricultural rivers however have mostly increased, suggesting not-as-effective controls of nonpoint sources in agriculture lands compared to point sources in cities. TP loss, calculated as fluxes by multiplying concentration and discharge, however exhibited an overall increasing rate of 6.5% per decade at the CONUS scale over the past 40 y, largely due to increasing river discharge. Results highlight the challenge of reducing TP loss that is complicated by changing river discharge in a warming climate.

摘要

磷(P)从陆地流失到水生系统,已经污染了世界各地的水域,并威胁到粮食生产。由于历史数据稀疏且不一致,对不可再生资源 P 的系统趋势分析一直具有挑战性。在这里,我们利用密集的水文气象数据和深度学习方法的最新复兴来填补数据空白并重建时间趋势。我们使用美国大陆(CONUS) 430 条河流的数据,通过多任务长短时记忆模型训练总磷(TP)。对重建的每日记录(1980-2019 年)的趋势分析表明,浓度普遍下降,分别有 60%、28%和 12%的河流呈现下降、上升和无显著变化的趋势。尽管过去几十年城市人口不断增加,但城市河流的浓度下降幅度最大;然而,农业河流的浓度大多上升,表明与城市的点源相比,对农业用地的非点源的控制效果不佳。然而,以浓度和流量相乘计算得出的 TP 流失量,在过去 40 年里,以每年 6.5%的速度在 CONUS 范围内总体呈上升趋势,这主要是由于河流流量增加所致。研究结果强调了在气候变暖的情况下,减少磷流失的挑战,这一挑战因河流流量的变化而变得复杂。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5ebb/11621846/02a57339e2a0/pnas.2402028121fig01.jpg

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