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Rooftop Rainwater Harvesting for Mombasa: Scenario Development with Image Classification and Water Resources Simulation

机译:蒙巴萨的屋顶雨水收集:基于图像分类和水资源模拟的情景开发

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Mombasa faces severe water scarcity problems. The existing supply is unable to satisfy the demand. This article demonstrates the combination of satellite image analysis and modelling as tools for the development of an urban rainwater harvesting policy. For developing a sustainable remedy policy, rooftop rainwater harvesting (RRWH) strategies were implemented into the water supply and demand model WEAP (Water Evaluation and Planning System). Roof areas were detected using supervised image classification. Future population growth, improved living standards, and climate change predictions until 2035 were combined with four management strategies. Image classification techniques were able to detect roof areas with acceptable accuracy. The simulated annual yield of RRWH ranged from 2.3 to 23 million cubic meters (MCM) depending on the extent of the roof area. Apart from potential RRWH, additional sources of water are required for full demand coverage.
机译:蒙巴萨面临严重的水资源短缺问题。现有的供应无法满足需求。本文演示了将卫星图像分析和建模相结合作为开发城市雨水收集政策的工具。为了制定可持续的补救政策,已将屋顶雨水收集(RRWH)策略应用于供水和需求模型WEAP(水评估与计划系统)中。使用监督图像分类检测屋顶区域。未来的人口增长,生活水平的提高以及到2035年的气候变化预测都与四种管理策略结合在一起。图像分类技术能够以可接受的精度检测屋顶区域。根据屋顶面积的大小,RRWH的模拟年产量在2.3到2300万立方米(MCM)之间。除了潜在的RRWH,还需要其他水源才能完全满足需求。

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