Abstract
AbstractUrban water demand forecasting is key to municipal water supply management. Short-term urban water demands are influenced by weather conditions. Thus, short-term urban water demand forecasting could be improved by using accurate weather forecasting information. This study explores the potential of using an analog approach with a newly developed retrospective weather forecast (reforecast) of a numerical weather prediction (NWP) for improving short-term urban water demand forecasting. The analog method derives an analog ensemble forecast resampled from observed data (analogs) based on the reforecast of a NWP: the Global Ensemble Forecast System (GEFS). The probabilistic and ensemble mean forecasts generated from analogs of weekly total rainfall (WeekRain), number of rainy days in one week (RainDays), number of consecutive rainy days in one week (CosRainDays), number of hot days in one week (HotDays), and daily mean temperature of the first seven lead days (T) from the reforecast were evaluated using...
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