Supplementary Information Files for The utility of Google Trends as a tool for evaluating flooding in data‐scarce places

Supplementary Information Files for The utility of Google Trends as a tool for evaluating flooding in data‐scarce placesGoogle Trends (GT) offers an historical database of global internet searches with the potential to compliment conventional records of environmental hazards, especially in regions where formal hydrometeorological data are scarce. We evaluate the extent to which GT can discern heavy rainfall and floods in Kenya and Uganda during the period 2014 to 2018. We triangulate counts of flood searches from GT with available rainfall records and media reports to build an inventory of extreme events. The Spearman rank correlation (rho) between monthly mean search interest for flooding and monthly Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) rainfall totals was rho = +0.38 (p < 0.005) for Kenya and rho = +0.64 (p < 0.001) for Uganda. Media reports of flooding were used to specify a threshold of detectability to give the same overall frequency of floods based on GT search interest. When the GT search index threshold was set at ≥15 and ≥29 the correct detection rate was 75% and 64% within a five‐day window of known flood events in Kenya and Uganda, respectively. From these preliminary explorations we conclude that GT has potential as a proxy data source, but greater skill may emerge in places with larger search volumes and by linking to historical information about environmental hazards at sub‐national scales. Wider applicability of the GT platform might be possible if there is greater transparency about how Google algorithms determine topics.

《Google Trends 在数据匮乏地区评估洪水效用之辅助信息文件》Google Trends (GT) 提供了一个全球互联网搜索的历史数据库，该数据库有望补充传统环境灾害记录，尤其是在正式水文气象数据稀缺的地区。本研究评估了 GT 在2014年至2018年期间对肯尼亚和乌干达的降雨和洪水事件的识别程度。通过将来自 GT 的洪水搜索次数与可用的降雨记录和媒体报道进行三角测量，构建极端事件清单。肯尼亚每月平均洪水搜索兴趣与每月气候灾害小组红外降水与站点（CHIRPS）降雨总量之间的斯皮尔曼秩相关系数（rho）为 +0.38（p < 0.005），乌干达为 rho = +0.64（p < 0.001）。利用媒体报道的洪水事件来指定可检测性阈值，以基于 GT 搜索兴趣给出相同的洪水总体频率。当 GT 搜索指数阈值设定为 ≥15 和 ≥29 时，肯尼亚和乌干达在已知洪水事件五日窗口内的正确检测率分别为 75% 和 64%。从这些初步探索中，我们得出结论，GT 作为替代数据源具有潜力，但在搜索量较大的地区以及与次国家尺度上的环境灾害历史信息相结合时，可能展现出更高的技能。如果关于 Google 算法如何确定主题的透明度更高，GT 平台的更广泛应用可能成为可能。