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Quantifying microclimatic conditions: an attempt to more accurately estimate urban landscape water requirements
Urban Forestry & Urban Greening ( IF 6.4 ) Pub Date : 2020-10-01 , DOI: 10.1016/j.ufug.2020.126767
Paria Shojaei , Mahdi Gheysari , Baden Myers , Hadi Esmaeili

Abstract The competing demands of landscape irrigation and other urban water requirements are motivating improvements in water efficiency in arid urban areas. Complex urban environments create unique microclimates that can result in different irrigation requirements across the landscape. The microclimate coefficient ( K m c ) is applied to adjust evapotranspiration from reference surfaces to local microclimatic conditions. The objectives of this study were to quantify and model urban microclimate conditions across the landscape. Air temperature and relative humidity were recorded at five landscapes with different surrounding land cover/use in the city of Isfahan, Iran, over a period of three years. The results showed that the K m c values varied both locally and over time. The monthly K m c at the five sites varied from 0.87 to 1.34. Results indicated that assuming a constant K m c throughout the year may lead to errors in estimating the water requirement of a landscape. The best regression models developed for predicting the K m c as a linear function of surface cover types explained 83 % of the variance in the K m c .

中文翻译:

量化小气候条件:尝试更准确地估计城市景观用水需求

摘要 景观灌溉和其他城市用水需求的竞争需求正在推动干旱城市地区用水效率的提高。复杂的城市环境创造了独特的小气候,可能导致整个景观的灌溉需求不同。小气候系数 (K mc ) 用于将参考表面的蒸散量调整为当地的小气候条件。本研究的目标是量化和模拟整个景观中的城市小气候条件。在三年的时间里,在伊朗伊斯法罕市的五个具有不同周围土地覆盖/用途的景观中记录了空气温度和相对湿度。结果表明,K mc 值在局部和随时间变化。五个站点的月 K mc 从 0.87 到 1.34 不等。结果表明,假设全年恒定 K mc 可能会导致估计景观需水量时出现错误。为预测 K mc 作为表面覆盖类型的线性函数而开发的最佳回归模型解释了 K mc 中 83% 的方差。
更新日期:2020-10-01
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