耦合分布式水文模拟及降雨集合预报的水库实时优化调度
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摘要
分布式水文模型所需的高精度驱动数据通常难以获得,预报信息不确定性阻碍了水库实时调度进程。针对以上问题,本文主要研究全球数据产品在流域尺度的可利用性,并采用集合预报描述预报误差,开发水库实时优化调度系统。主要研究成果与结论如下：
(1)以辉发河流域为研究区域,建立基于水和能量平衡的分布式水文模型WEB-DHM,模拟流域长系列(2000-2006年)水分(流量)和能量(陆面温度)循环过程。与地面实测日流量和遥感陆面温度对比表明,WEB-DHM模型能较好模拟流域水分和能量循环过程,这是本文的基础。
(2)针对分布式水文模型高精度驱动数据难以获得的问题,分析GLDAS产品在流域尺度的可利用性进行。结果表明,GLDAS的降雨,气温及长波辐射精度较高,但GLDAS高估了向下短波辐射Rsw,d'从而导致GLDAS模拟的净辐射,蒸散发,潜热及显热通量具有不确定性。将GLDAS的Rsw.d作简单的线性修正后,以GLDAS驱动WEB-DHM能较好再现流域水循环过程。
(3)开发了基于确定性数值天气预报的水库多目标(水库上下游防洪安全及兴利蓄水)实时优化系统。系统采用日本气象厅(JMA)实时预报作为驱动,使其实现真正的实时操作,并对原始WEB-DHM模型作了改进,使模型运行效率提高约63%。系统采用洗牌复形演化算法(SCE-UA)和动态惩罚函数法分别进行目标优化和解决多约束条件问题。在丰满水库对三场洪水进行检验(2001,2004和2005年)的结果表明,系统能较好预报汛期洪水及优化目标函数。
(4)针对数值天气预报普遍存在的不确定性问题,基于前人工作,改进降雨集合预报生成技术。第一,将降雨预报评价指标归一化,全面描述降雨强度误差；第二,考虑降雨强度和分布误差,并概括为数学公式以弱化人为因素对扰动结果的影响。统计2004和2005年汛期降水的连续概率排位分数(CRPS)和分布直方图(RH),结果表明,用本文方法生成的集合预报总体上优于JMA产品。
(5)耦合集合预报和分布式水文模型于水库实时优化模型,开发基于集合预报的水库实时调度系统(EPROS),在丰满流域对2004和2005年实测洪水检验。结果表明,EPROS通过产生一组场景(入库流量,水库泄流及水位),有效地描述了单值预报的不确定性。此外,EPROS系统对集合预报成员数并不敏感,在较大洪水下也能较好运行。系统易于操作,为水库实时调度提供了参考。
最后对全文做了总结,并对有待于进一步研究的问题进行了展望。
The accurate high-resolution forcing data are usually difficult to obtain. The uncertainty of forecast information hindered the process of real-time reservoir operation. The aim of this theis is:1) to assess the applicability of a global dataset in basin scale;2) to handle the forecast uncertainty by using ensemble approach;3) to develop an ensemble prediction-based reservoir optimization system. Main results and conclusions include:
(1) A hydrological model (The Water and Energy Budget-based Distributed Hydrological Model, WEB-DHM) was established in a semiarid river basin (Fengman basin). The water (discharge) and energy (Land Surface Temperature, LST) cycles is simulated from2000to2006. It was concluded that the WEB-DHM is able to predict water and energy fluxes accurately over the Fengman basin by comparing with measured streamflows and MODIS/Terra (Moderate Resolution Imaging Spectroradiometer/Terra) LSTs.
(2) Because accurate high resolution atmospheric forcing data is difficult to obtain for most cases, the applicability of GLDAS in basin scale water and energy budget study is evaluated. Main results include:1) the GLDAS is of high quality for daily and monthly precipitation, Tair, monthly Rlw.d, while it overestimates monthly Rsw.d,2) the GLDAS/Noah agrees well with the verified WEB-DHM and JRA-25in terms of LST, upward shortwave and longwave radiation. While the net radiation, evapotranspiration, latent and sensible heat fluxes modeled by GLDAS/Noah are larger than WEB-DHM and JRA-25simulations in wet seasons;3) the basin-integrated discharges and evapotranspiration can be reproduced reasonably well by WEB-DHM fed with GLDAS forcing except linear corrections ofRsw.d?
(3) A multi-objective (the upstream and downstream safety, and water use) real-time reservoir operation system is developed by using deterministic rainfall forecast obtained from Japan Meteorology Agency (JMA). The efficiency of the WEB-DHM model is improved by63%comparing with the original WEB-DHM model. The SCE-UA (Shuffled Complex Evolution developed at The University of Arizona) is applied to optimize the multi-objective. The dynamic penalty function is applied to solve the multi-constraint. The results show that the system is able to optimize the objectives by evaluating the system for the three flood events (2001,2004and2005).
(4) The ensemble precipitation generation method proposed by Saavedra et al,[2010] is improved in order to describe the uncertainties in NWPs. First, the precipitation forecast error is described by using the normalized evaluation index. Second, the definition of QPF perturbation weight is simplified by using mathematical functions instead of using proposed zones and a look up table. The ensemble QPFs generated by EPROS are comparable to that obtained from JMA by measuring their performances using CRPS (Continuous Ranked Probability Score) and RH (Rank Histogram) on2004and2005.
(5) An Ensemble Prediction based Reservoir Optimization System (EPROS) is presented in this study by coupling ensemble hydrological prediction with reservoir real-time optimization. The EPROS system has been evaluated on Fengman reservoir for the flood events in2004and2005. For both events, the ensemble based streamflow predictions described the uncertainties of single prediction effectively by generating multiple (e.g.,30-member) streamflow sceneries (water levels, reservoir inflows). The system's capability was evaluated under critical situations. The system is not sensitive to the ensemble sizes. The system is of high efficiency and easy to operate. It can provide reference for practical operation.
Finally, the summary and further directions are given.
(1)以辉发河流域为研究区域,建立基于水和能量平衡的分布式水文模型WEB-DHM,模拟流域长系列(2000-2006年)水分(流量)和能量(陆面温度)循环过程。与地面实测日流量和遥感陆面温度对比表明,WEB-DHM模型能较好模拟流域水分和能量循环过程,这是本文的基础。
(2)针对分布式水文模型高精度驱动数据难以获得的问题,分析GLDAS产品在流域尺度的可利用性进行。结果表明,GLDAS的降雨,气温及长波辐射精度较高,但GLDAS高估了向下短波辐射Rsw,d'从而导致GLDAS模拟的净辐射,蒸散发,潜热及显热通量具有不确定性。将GLDAS的Rsw.d作简单的线性修正后,以GLDAS驱动WEB-DHM能较好再现流域水循环过程。
(3)开发了基于确定性数值天气预报的水库多目标(水库上下游防洪安全及兴利蓄水)实时优化系统。系统采用日本气象厅(JMA)实时预报作为驱动,使其实现真正的实时操作,并对原始WEB-DHM模型作了改进,使模型运行效率提高约63%。系统采用洗牌复形演化算法(SCE-UA)和动态惩罚函数法分别进行目标优化和解决多约束条件问题。在丰满水库对三场洪水进行检验(2001,2004和2005年)的结果表明,系统能较好预报汛期洪水及优化目标函数。
(4)针对数值天气预报普遍存在的不确定性问题,基于前人工作,改进降雨集合预报生成技术。第一,将降雨预报评价指标归一化,全面描述降雨强度误差；第二,考虑降雨强度和分布误差,并概括为数学公式以弱化人为因素对扰动结果的影响。统计2004和2005年汛期降水的连续概率排位分数(CRPS)和分布直方图(RH),结果表明,用本文方法生成的集合预报总体上优于JMA产品。
(5)耦合集合预报和分布式水文模型于水库实时优化模型,开发基于集合预报的水库实时调度系统(EPROS),在丰满流域对2004和2005年实测洪水检验。结果表明,EPROS通过产生一组场景(入库流量,水库泄流及水位),有效地描述了单值预报的不确定性。此外,EPROS系统对集合预报成员数并不敏感,在较大洪水下也能较好运行。系统易于操作,为水库实时调度提供了参考。
最后对全文做了总结,并对有待于进一步研究的问题进行了展望。
The accurate high-resolution forcing data are usually difficult to obtain. The uncertainty of forecast information hindered the process of real-time reservoir operation. The aim of this theis is:1) to assess the applicability of a global dataset in basin scale;2) to handle the forecast uncertainty by using ensemble approach;3) to develop an ensemble prediction-based reservoir optimization system. Main results and conclusions include:
(1) A hydrological model (The Water and Energy Budget-based Distributed Hydrological Model, WEB-DHM) was established in a semiarid river basin (Fengman basin). The water (discharge) and energy (Land Surface Temperature, LST) cycles is simulated from2000to2006. It was concluded that the WEB-DHM is able to predict water and energy fluxes accurately over the Fengman basin by comparing with measured streamflows and MODIS/Terra (Moderate Resolution Imaging Spectroradiometer/Terra) LSTs.
(2) Because accurate high resolution atmospheric forcing data is difficult to obtain for most cases, the applicability of GLDAS in basin scale water and energy budget study is evaluated. Main results include:1) the GLDAS is of high quality for daily and monthly precipitation, Tair, monthly Rlw.d, while it overestimates monthly Rsw.d,2) the GLDAS/Noah agrees well with the verified WEB-DHM and JRA-25in terms of LST, upward shortwave and longwave radiation. While the net radiation, evapotranspiration, latent and sensible heat fluxes modeled by GLDAS/Noah are larger than WEB-DHM and JRA-25simulations in wet seasons;3) the basin-integrated discharges and evapotranspiration can be reproduced reasonably well by WEB-DHM fed with GLDAS forcing except linear corrections ofRsw.d?
(3) A multi-objective (the upstream and downstream safety, and water use) real-time reservoir operation system is developed by using deterministic rainfall forecast obtained from Japan Meteorology Agency (JMA). The efficiency of the WEB-DHM model is improved by63%comparing with the original WEB-DHM model. The SCE-UA (Shuffled Complex Evolution developed at The University of Arizona) is applied to optimize the multi-objective. The dynamic penalty function is applied to solve the multi-constraint. The results show that the system is able to optimize the objectives by evaluating the system for the three flood events (2001,2004and2005).
(4) The ensemble precipitation generation method proposed by Saavedra et al,[2010] is improved in order to describe the uncertainties in NWPs. First, the precipitation forecast error is described by using the normalized evaluation index. Second, the definition of QPF perturbation weight is simplified by using mathematical functions instead of using proposed zones and a look up table. The ensemble QPFs generated by EPROS are comparable to that obtained from JMA by measuring their performances using CRPS (Continuous Ranked Probability Score) and RH (Rank Histogram) on2004and2005.
(5) An Ensemble Prediction based Reservoir Optimization System (EPROS) is presented in this study by coupling ensemble hydrological prediction with reservoir real-time optimization. The EPROS system has been evaluated on Fengman reservoir for the flood events in2004and2005. For both events, the ensemble based streamflow predictions described the uncertainties of single prediction effectively by generating multiple (e.g.,30-member) streamflow sceneries (water levels, reservoir inflows). The system's capability was evaluated under critical situations. The system is not sensitive to the ensemble sizes. The system is of high efficiency and easy to operate. It can provide reference for practical operation.
Finally, the summary and further directions are given.
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