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1.
Abhiram S. P. Pamula Hamed Gholizadeh Mark J. Krzmarzick William E. Mausbach David J. Lampert 《Journal of the American Water Resources Association》2023,59(5):929-949
Harmful algal blooms (HABs) diminish the utility of reservoirs for drinking water supply, irrigation, recreation, and ecosystem service provision. HABs decrease water quality and are a significant health concern in surface water bodies. Near real-time monitoring of HABs in reservoirs and small water bodies is essential to understand the dynamics of turbidity and HAB formation. This study uses satellite imagery to remotely sense chlorophyll-a concentrations (chl-a), phycocyanin concentrations, and turbidity in two reservoirs, the Grand Lake O′ the Cherokees and Hudson Reservoir, OK, USA, to develop a tool for near real-time monitoring of HABs. Landsat-8 and Sentinel-2 imagery from 2013 to 2017 and from 2015 to 2020 were used to train and test three different models that include multiple regression, support vector regression (SVR), and random forest regression (RFR). Performance was assessed by comparing the three models to estimate chl-a, phycocyanin, and turbidity. The results showed that RFR achieved the best performance, with R2 values of 0.75, 0.82, and 0.79 for chl-a, turbidity, and phycocyanin, while multiple regression had R2 values of 0.29, 0.51, and 0.46 and SVR had R2 values of 0.58, 0.62, and 0.61 on the testing datasets, respectively. This paper examines the potential of the developed open-source satellite remote sensing tool for monitoring reservoirs in Oklahoma to assess spatial and temporal variations in surface water quality. 相似文献
2.
Jacob A. Zwart Samantha K. Oliver William David Watkins Jeffrey M. Sadler Alison P. Appling Hayley R. Corson-Dosch Xiaowei Jia Vipin Kumar Jordan S. Read 《Journal of the American Water Resources Association》2023,59(2):317-337
Deep learning (DL) models are increasingly used to make accurate hindcasts of management-relevant variables, but they are less commonly used in forecasting applications. Data assimilation (DA) can be used for forecasts to leverage real-time observations, where the difference between model predictions and observations today is used to adjust the model to make better predictions tomorrow. In this use case, we developed a process-guided DL and DA approach to make 7-day probabilistic forecasts of daily maximum water temperature in the Delaware River Basin in support of water management decisions. Our modeling system produced forecasts of daily maximum water temperature with an average root mean squared error (RMSE) from 1.1 to 1.4°C for 1-day-ahead and 1.4 to 1.9°C for 7-day-ahead forecasts across all sites. The DA algorithm marginally improved forecast performance when compared with forecasts produced using the process-guided DL model alone (0%–14% lower RMSE with the DA algorithm). Across all sites and lead times, 65%–82% of observations were within 90% forecast confidence intervals, which allowed managers to anticipate probability of exceedances of ecologically relevant thresholds and aid in decisions about releasing reservoir water downstream. The flexibility of DL models shows promise for forecasting other important environmental variables and aid in decision-making. 相似文献
3.
Conservation decisions are invariably made with incomplete data on species’ distributions, habitats, and threats, but frameworks for allocating conservation investments rarely account for missing data. We examined how explicit consideration of missing data can boost return on investment in ecosystem restoration, focusing on the challenge of restoring aquatic ecosystem connectivity by removing dams and road crossings from rivers. A novel way of integrating the presence of unmapped barriers into a barrier optimization model was developed and applied to the U.S. state of Maine to maximize expected habitat gain for migratory fish. Failing to account for unmapped barriers during prioritization led to nearly 50% lower habitat gain than was anticipated using a conventional barrier optimization approach. Explicitly acknowledging that data are incomplete during project selection, however, boosted expected habitat gains by 20–273% on average, depending on the true number of unmapped barriers. Importantly, these gains occurred without additional data. Simply acknowledging that some barriers were unmapped, regardless of their precise number and location, improved conservation outcomes. Given incomplete data on ecosystems worldwide, our results demonstrate the value of accounting for data shortcomings during project selection. 相似文献
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突发性环境污染事故会对环境造成较大的伤害,如果不能及时采取措施,就会使污染进一步扩大,不仅带来经济的损失,而且会破坏到生态的平衡。因此,要建立起突发环境污染事故的应急监测,这样才能尽可能的减少突发性环境污染事件的影响。基于此,本文从突发性环境污染事故的特征入手,首先分析其应急监测的意义,然后探究具体的措施,希望可以借此给突发性环境污染应急监测的相关研究提供一定的参考意见。 相似文献
6.
在我国社会经济快速发展的过程中,人们对自然资源需求无度,造成生态环境破坏问题非常严重。通过环境监测可以及时分析空气中有毒有害的物质成分,并且对环境污染问题进行及时有效的解决。但是在监测的过程中所采用大量的空气试剂很容易造成环境二次污染等问题,为此必须要积极加强对环境监测中重金属污染的合理控制,对空气试剂产生的大量废弃物进行及时的回收处理,从而有效避免出现二次污染的情况,充分发挥环境监测的作用。 相似文献
7.
质量保证与质量控制措施是土壤监测工作在具体开展过程中确保其监测结果准确性、代表性、全面性的重要措施,同时也是土壤监测工作在具体开展过程中的核心工作内容。在环境保护与可持续发展战略情况下,采取全面有效的质量保证与质量控制措施可以确保并优化土壤监测结果的真实性、准确性和全面性,对促进土壤监测工作的优化发展具有非常重要的意义。基于此,本文针对土壤监测工作开展过程中应当实施的各项质量保证与质量控制措施进行了分析总结。 相似文献
8.
本文主要是围绕地表水环境遥感检测展开讨论,全面介绍了水环境检测的关键技术和系统,建立改进双峰法的水体分布遥感提取方法,并以具体地区为例进行分析,采用不同方法建立解析方法,从根本上提升反演方法的区域和积极适用性,希望能够对相关人员起到参考性价值。 相似文献
9.
环境监测在环境保护中起着重要的作用,伴随着环境保护法的进一步落实,使我国的环保措施及标准有了越来越规范的准则。可从实际工作情况看,监测机构监测水平较低、设备滞后、监督不严格等问题依然存在因此,要全面提高环境监测水平,加大对环境监测工作的重视程度。本文主要以环境监测在生态环境保护中产生的作用入手,提出了一些完善措施。 相似文献
10.
《环境监测 分析方法标准制修订技术导则》(HJ 168—2010)对土壤环境监测标准制修订适用性探讨 总被引:1,自引:0,他引:1
针对土壤环境监测的复杂性和特殊性,从空白试验、检出限、方法验证、质量控制和标准文本等方面,指出了《环境监测分析方法标准制修订技术导则》《HJ 168—2010》对土壤环境监测标准制修订工作的适用性和执行中存在的问题。提出,为保证土壤标准制修订质量和标准执行质量,应研究适宜土壤监测方法标准的质量控制指标体系和评价体系,及时修订《HJ 168—2010》或发布补充要求;对现有土壤监测方法标准进行技术评估,加强对于土壤标准制修订工作的指导和监管。 相似文献