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通过高分辨率空间统计网络模型指导跨界流域的河岸管理。

Guiding riparian management in a transboundary watershed through high resolution spatial statistical network models.

机构信息

ORISE participant at U.S. Environmental Protection Agency, Atlantic Coastal Environmental Sciences Division, 27 Tarzwell Drive, Narragansett, RI, 02882, USA.

U.S. Environmental Protection Agency, Atlantic Coastal Environmental Sciences Division, 27 Tarzwell Drive, Narragansett, RI, 02882, USA.

出版信息

J Environ Manage. 2021 Jan 15;278(Pt 2):111585. doi: 10.1016/j.jenvman.2020.111585. Epub 2020 Nov 13.

Abstract

The United States Environmental Protection Agency and the Houlton Band of Maliseet Indians (HBMI) built a stream temperature spatial statistical network (SSN) model for the Meduxnekeag Watershed. The headwaters of the Meduxnekeag Watershed are in Maine, United States of America and the outlet is in New Brunswick, Canada, creating an additional challenge because many datasets are constrained to political boundaries. The release of the High-Resolution National Hydrology Dataset Plus included transboundary watersheds and enabled creation of fine resolution (1:24,000) SSN temperature models consistent with management scales for riparian buffers. SSN models were developed for July, August, and September median stream temperatures and the growing season maximum (GSM). Fitted SSN models had relatively high R values (0.88-0.96) and all final models included significant parameters for shade-attenuated solar radiation, reference flow, air temperature, and bankfull depth or width. Fitted models predicted stream temperatures during a dry (2010) and wet (2011) year. Monthly models predicted the fewest cold water (<19.0 °C) reaches in July with 28% in the dry and 68% in the wet year. September had >99% cold water reaches, and August results were intermediate between July and September. GSM predictions found 81% of stream reaches could not support salmonid survival (>27.0 °C) in the dry year and 59% of the reaches were warmwater (22.5-27.0 °C) in the wet year. The model was used to predict stream temperatures following restoration scenarios of a forested 30-m or 90-m buffer of stream segments bordered by agricultural or developed land. The restoration scenarios expanded cold water habitat based on monthly median temperatures and decreased the habitat area with GSM above survival thresholds, with little difference in effectiveness of the two buffer widths. These results will guide riparian restoration projects by the HBMI to expand habitat for cold water fishes.

摘要

美国环境保护署和豪顿马利塞特印第安人部落(HBMI)为梅杜斯内克格流域建立了一个溪流温度空间统计网络(SSN)模型。梅杜斯内克格流域的源头位于美国缅因州,出口位于加拿大新不伦瑞克省,这给模型的建立带来了额外的挑战,因为许多数据集都受到政治边界的限制。高分辨率国家水文数据集 Plus 的发布包括了跨境流域,并能够创建与河岸缓冲区管理规模一致的精细分辨率(1:24,000)SSN 温度模型。SSN 模型是为 7 月、8 月和 9 月的中值溪流温度以及生长季节最大值(GSM)而开发的。拟合的 SSN 模型具有较高的 R 值(0.88-0.96),所有最终模型都包括了阴影衰减太阳辐射、参考流量、空气温度和满流深度或宽度等显著参数。拟合模型预测了干旱(2010 年)和湿润(2011 年)年份的溪流温度。月度模型预测 7 月冷水(<19.0°C)的到达次数最少,干旱年份为 28%,湿润年份为 68%。9 月有超过 99%的冷水到达,8 月的结果介于 7 月和 9 月之间。GSM 预测发现,在干旱年份,81%的溪流流域无法支持鲑鱼的生存(>27.0°C),而在湿润年份,59%的流域为温水(22.5-27.0°C)。该模型用于预测森林覆盖的 30 米或 90 米溪流缓冲区的恢复情景下的溪流温度,这些缓冲区的边界为农业或开发用地。恢复情景基于每月的中值温度扩大了冷水栖息地,并减少了超过生存阈值的 GSM 栖息地面积,两种缓冲区宽度的效果差异不大。这些结果将指导 HBMI 进行河岸恢复项目,以扩大冷水鱼类的栖息地。

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