{"title":"Pitman-WR2012模式在季节性水文预报中的实施框架:以南非克拉伊河为例","authors":"Sesethu Fikileni, Piotr Wolski","doi":"10.17159/wsa/2022.v48.i1.3891","DOIUrl":null,"url":null,"abstract":"Hydrological forecasting becomes an important tool in water resources management in forecasting the future state of the water resources in a catchment. The need for a reliable seasonal hydrologic forecast is significant and is becoming even more urgent under future climate conditions, as the assimilation of seasonal forecast information in decision making becomes part of the short and long-term climate change adaptation strategies in a range of contexts, such as energy supply, water supply and management, rural-urban, agriculture, infrastructure and disaster preparedness and relief. This work deals with the framework for implementation of the Pitman-WR2012 model in a hydrological forecasting mode. The Pitman-WR2012 model was forced with 10-member ensemble seasonal climate forecast from Climate Forecast Systems v.2 (CFSv2), which is downscaled using the principal components regression (PCR) approach. The generated seasonal hydrological forecast focused on the summer season, in particular on the Dec–Jan–Feb (DJF) period, which is the rainy season in the studied catchment (Kraai River catchment in the Eastern Cape Province of South Africa). The hydrological forecast issued at the end of November showed skill in December and February (assessed through Receiver Operating Characteristic (ROC) and Ranked Probability Skill Score (RPSS)), with poorer skill in January. Importantly, the skill of streamflow forecast was better than that of rainfall forecast, which likely results from the influence of the initial conditions of the hydrological model. In conclusion Pitman-WR2012 model performed realistically when implemented in seasonal hydrological forecasts mode, and it is important that in that mode the model is run with near-real-time rainfall data in order to maximize forecast skill arising from initial conditions.","PeriodicalId":23623,"journal":{"name":"Water SA","volume":"13 1","pages":""},"PeriodicalIF":1.0000,"publicationDate":"2022-01-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Framework for implementation of the Pitman-WR2012 model in seasonal hydrological forecasting: a case study of Kraai River, South Africa\",\"authors\":\"Sesethu Fikileni, Piotr Wolski\",\"doi\":\"10.17159/wsa/2022.v48.i1.3891\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Hydrological forecasting becomes an important tool in water resources management in forecasting the future state of the water resources in a catchment. The need for a reliable seasonal hydrologic forecast is significant and is becoming even more urgent under future climate conditions, as the assimilation of seasonal forecast information in decision making becomes part of the short and long-term climate change adaptation strategies in a range of contexts, such as energy supply, water supply and management, rural-urban, agriculture, infrastructure and disaster preparedness and relief. This work deals with the framework for implementation of the Pitman-WR2012 model in a hydrological forecasting mode. The Pitman-WR2012 model was forced with 10-member ensemble seasonal climate forecast from Climate Forecast Systems v.2 (CFSv2), which is downscaled using the principal components regression (PCR) approach. The generated seasonal hydrological forecast focused on the summer season, in particular on the Dec–Jan–Feb (DJF) period, which is the rainy season in the studied catchment (Kraai River catchment in the Eastern Cape Province of South Africa). The hydrological forecast issued at the end of November showed skill in December and February (assessed through Receiver Operating Characteristic (ROC) and Ranked Probability Skill Score (RPSS)), with poorer skill in January. Importantly, the skill of streamflow forecast was better than that of rainfall forecast, which likely results from the influence of the initial conditions of the hydrological model. 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引用次数: 1
摘要
水文预报是水资源管理中预测流域未来水资源状况的重要工具。对可靠的季节性水文预报的需求是巨大的,而且在未来气候条件下变得更加迫切,因为在决策过程中吸收季节性预报信息已成为能源供应、供水和管理、城乡、农业、基础设施以及备灾和救灾等一系列情况下的短期和长期气候变化适应战略的一部分。这项工作涉及在水文预报模式中实施Pitman-WR2012模型的框架。Pitman-WR2012模式是用来自气候预报系统v.2的10元集合季节气候预报进行强迫的(CFSv2),使用主成分回归(PCR)方法进行了缩减。生成的季节性水文预报侧重于夏季,特别是12月至1月至2月(DJF)期间,这是所研究的集水区(南非东开普省的Kraai河集水区)的雨季。11月底发布的水文预报在12月和2月(通过Receiver Operating Characteristic (ROC)和rank Probability skill Score (RPSS)评估)表现出较好的技能,1月的技能较差。重要的是,流量预报的技巧要优于降雨预报,这可能是由于水文模型初始条件的影响。总之,Pitman-WR2012模型在季节性水文预报模式下的表现是真实的,在该模式下,为了最大限度地提高初始条件引起的预报技能,重要的是使用近实时降雨数据运行模型。
Framework for implementation of the Pitman-WR2012 model in seasonal hydrological forecasting: a case study of Kraai River, South Africa
Hydrological forecasting becomes an important tool in water resources management in forecasting the future state of the water resources in a catchment. The need for a reliable seasonal hydrologic forecast is significant and is becoming even more urgent under future climate conditions, as the assimilation of seasonal forecast information in decision making becomes part of the short and long-term climate change adaptation strategies in a range of contexts, such as energy supply, water supply and management, rural-urban, agriculture, infrastructure and disaster preparedness and relief. This work deals with the framework for implementation of the Pitman-WR2012 model in a hydrological forecasting mode. The Pitman-WR2012 model was forced with 10-member ensemble seasonal climate forecast from Climate Forecast Systems v.2 (CFSv2), which is downscaled using the principal components regression (PCR) approach. The generated seasonal hydrological forecast focused on the summer season, in particular on the Dec–Jan–Feb (DJF) period, which is the rainy season in the studied catchment (Kraai River catchment in the Eastern Cape Province of South Africa). The hydrological forecast issued at the end of November showed skill in December and February (assessed through Receiver Operating Characteristic (ROC) and Ranked Probability Skill Score (RPSS)), with poorer skill in January. Importantly, the skill of streamflow forecast was better than that of rainfall forecast, which likely results from the influence of the initial conditions of the hydrological model. In conclusion Pitman-WR2012 model performed realistically when implemented in seasonal hydrological forecasts mode, and it is important that in that mode the model is run with near-real-time rainfall data in order to maximize forecast skill arising from initial conditions.
期刊介绍:
WaterSA publishes refereed, original work in all branches of water science, technology and engineering. This includes water resources development; the hydrological cycle; surface hydrology; geohydrology and hydrometeorology; limnology; salinisation; treatment and management of municipal and industrial water and wastewater; treatment and disposal of sewage sludge; environmental pollution control; water quality and treatment; aquaculture in terms of its impact on the water resource; agricultural water science; etc.
Water SA is the WRC’s accredited scientific journal which contains original research articles and review articles on all aspects of water science, technology, engineering and policy. Water SA has been in publication since 1975 and includes articles from both local and international authors. The journal is issued quarterly (4 editions per year).