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首页> 外文期刊>Physics and chemistry of the earth >Assessing the feasibility of integrating remote sensing and in-situ measurements in monitoring water quality status of Lake Chivero, Zimbabwe
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Assessing the feasibility of integrating remote sensing and in-situ measurements in monitoring water quality status of Lake Chivero, Zimbabwe

机译：评估将遥感和现场测量相结合以监测津巴布韦奇韦罗湖水质状况的可行性

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This work investigates the likelihood of integrating the cheap and readily-available broadband multi-spectral MODIS data and in-situ measurements in quantifying and monitoring water quality status of an inland lake within Upper Manyame Catchment in Zimbabwe. Specifically we used MODIS images to quantify inland lake chlorophyll_a concentrations, as a proxy for predicting lake pollution levels. The findings of this study show a high chlorophyll_a concentration of 0.101 +/- 0.128 mu g/L within the Lake. The results further demonstrated that the chlorophyll_a concentration levels did not significantly vary (p = 0.788) between sites, except among depths (p = 0.05). Further, prediction results based on the relationship between observed and predicted chlorophyll_a produced a high R-2 value of 0.89 and a root mean square error (RMSE) value of 0.003 mu g/L. Moreover, the derived landuse maps of Upper Manyame Catchment indicated a significant variation in the percentage settlement in 1985, 1994 and 2010 change from 1985 to 2010. For instance, 8% increase in settlement in the period between 1994 and 2010 and over 12% increase from 1985 to 2010 and a decline in percent forest coverage (i.e. 9.8% in 1985 to 2.0% in the year 2010) in the catchment was observed. Overall, the findings of this study highlights the importance of free and readily-available satellite datasets (such as the multispectral MODIS and Landsat) in quantifying and monitoring water quality across inland lakes especially in data-scarce areas like Sub-Saharan Africa. (C) 2016 Elsevier Ltd. All rights reserved.
机译：这项工作研究了将廉价且易于获得的宽带多光谱MODIS数据与原位测量相集成的可能性，以量化和监测津巴布韦的上曼雅梅集水区内陆湖泊的水质状况。具体来说，我们使用MODIS图像来量化内陆湖泊的叶绿素a浓度，作为预测湖泊污染水平的代理。这项研究的结果表明，湖中的叶绿素浓度很高，为0.101 +/- 0.128μg / L。结果进一步表明，除深度之间（p = 0.05）外，各部位之间的叶绿素a浓度水平没有显着变化（p = 0.788）。此外，基于观察到的叶绿素a与预测叶绿素a之间的关系的预测结果产生高的R-2值0.89和均方根误差（RMSE）值0.003μg / L。此外，上曼雅曼克集水区的土地利用分布图表明，1985年，1994年和1985年至2010年的定居百分比变化显着，例如，1994年至2010年期间的定居增加了8％，而超过12％的增加从1985年到2010年，该流域的森林覆盖率下降了（即1985年为9.8％，到2010年为2.0％）。总的来说，这项研究的结果突出了免费和易于获得的卫星数据集（例如多光谱MODIS和Landsat）在定量和监测内陆湖泊尤其是在撒哈拉以南非洲等数据稀缺地区的水质方面的重要性。 （C）2016 Elsevier Ltd.保留所有权利。

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