基于因子分析的广东省短时强降水预报模型及其业务试验

利用每天4次0.125°×0.125°的ECMWF-Interim再分析资料和广东省2009—2018年地面气象站逐时雨量观测的短时强降水数据集,针对广东不同季节、不同地域的短时强降水,以提高命中率同时控制虚警率为目的,提出基于显著性和敏感性评价的物理量优选和因子分析法,用于构建分期、分区的广东短时强降水概率预报模型。以参数显著性和预测敏感性为标准,在49个待选物理量中挑选18个既与多年平均态存在明显差异,又具有较低虚警率的物理量,应用方差最大正交旋转因子分析法将遴选物理量组合成表征大气不同环境条件的6个因子;为使组合因子更具适应性,基于因子偏离度特征对广东前、后汛期不同区域独立建模,构建分期、分区短时强降水逐6 h格点概率预报模型。汛期业务试验表明,模型对短时强降水发生概率预报效果较好。对2019年汛期模型每天两次起报的12 h预报时效内概率产品进行格点检验,以训练期最优TS评分对应的固定概率作为预测概率阈值,广东省大部分区域TS评分超过0.25,最高超过0.42,平均较ECMWF-Fine业务模式在前、后汛期分别提升0.23与0.21,南部沿海TS评分提升幅度最大,并且模型在提升命中率与降低虚警率之间取得较好的平衡。个例分析表明,对于ECMWF模式常漏报的广东暖区短时强降水,概率预报模型具有明显优势,尤其能为天气尺度弱动力强迫的强降水早期预警提供更多有效信息。      

TOPMODEL模型在重庆市开县温泉小流域径流模拟中的应用研究

以重庆市开县温泉流域(984km2)为研究区域,利用自动雨量站资料作为TOPMODEL(TOPography based hydrological MODEL)降水一径流模型的输入,以08:00 BST观测的流域出口流量作为模型率定的依据,探讨了用小时面雨量和08:00流量资料和TOPMODEL水文模型进行小流域流量模拟的可行性.结果表明,以08:00流量为依据对TOPMODEL水文模型进行率定后,模型效率系数达到0.872.结果表明,TOPMODEL在所研究的流域基本上是适用的.此工作是自动雨量站资料、天气雷达定量测量降水产品等用于小流域山洪预报的基础工作之一.     

气象水文模型耦合研究及在西苕溪流域的模拟试验

为了提高洪水预报的精度,延长洪水预见期,利用WRF模式和HEC-HMS水文模型对太湖西苕溪流域2009年8月的一次典型暴雨洪水过程进行了降雨模拟和流量耦合预报,并与实测降雨和径流过程进行了对比分析。(1) WRF模式能够较好模拟出位于天目山的强降水中心,位置较实况略偏北;预报子流域面雨量时空分布与实况较一致,定量检验合格率达50%左右。(2) HEC-HMS模型对西苕溪流域日径流过程和场降雨洪水过程均有较好的模拟效果,模型参数验证和率定期间,确定性系数、洪峰流量相对误差和峰现时差等指标均小于业务预报许可误差。(3) 采用单向耦合法,将WRF模式(5 km网格)48 h预见期的滚动预报降雨场输入HEC-HMS水文模型进行流量滚动预报,耦合预报结果明显优于不考虑预见期内降雨的传统预报方法,在保证精度的前提下,有效延长了洪水预见期。      

基于HBV模型的淮河流域洪水致灾临界雨量研究

根据流域暴雨洪水致灾机制,文章提出了考虑前期基础水位的动态致灾临界雨量指标,并以淮河上游地区为例,基于HBV水文模型建立了降水-流量-水位关系,并根据这种关系确立了临界雨量确定的方法流程.首先基于历史水文数据率定和验证模型,得到适用于研究区的最优化模型参数,然后构建洪水上涨期水位流量关系,最后以是否达到致灾水位为标准,通过模型试算并结合水位流量关系曲线反推出致灾临界雨量值.在淮河上游地区的研究中,利用2002-2009年逐日气象水文数据对HBV模型进行了参数率定和检验,并针对洪水过程进行了参数优化,经过率定后HBV模型对王家坝以上流域具备较好的适用性,对典型洪水过程模拟的确定性系数和NASH效率系数均在0.8以上;根据王家坝站实测流量水位数据,构建了概化的单一关系曲线;结合HBV模型和水位流量关系得到了王家坝以上流域的动态致灾临界雨量指标,临界雨量值随前期基础水位升高而减小,并且随着前期水位的变化,临界雨量值呈现了明显的非线性响应特征.     

HLAFS业务预报系统改进对比试验

该文以国家气象中心的有限区域业务预报模式为基础，在模式中引入了简化的混合相云方案，其中包括云水雨水的冻结、冰雪的融化等冰相过程；并把模式的水平分辨率由0.5°×0.5°提高到0.25°×0.25°经纬度网格。在此基础上建立了较高分辨率的同化预报系统，并使用实时资料进行预报对比试验。试验结果表明，改进后的降水落区预报有了明显进步，强降水中心的降雨量预报也有所增强，与原方案相比更接近于降水实况。     

基于HBV模型的太子河流域致洪临界雨量的确定

以太子河流域为研究区域,基于流域内的气象水文数据、数字高程模型及土地利用等资料,采用HBV水文模型对流域的水文过程进行模拟,通过对模型参数的率定与验证,评估了HBV模型在该流域径流模拟的适用性,确定了适合太子河流域的最优化参数,结合水位-流量关系曲线,推算太子河流域不同等级洪水致洪临界雨量。结果表明: HBV模型对太子河流域的径流模拟效果较好,率定期与验证期Nash效率系数与确定性系数均超过0.60,模型中积雪和融雪模块(CFR)、土壤含水量计算模块(BETA)与响应模块(KUZ2、UZ1、PERC)中的这些参数最为敏感,模型基本模拟出了洪水对降水的响应过程。通过建立的HBV水文模型,结合小林子水文站的水位-流量关系曲线,以警戒水位、保证水位作为不同等级洪水的判别条件,推算得到了不同起始水位下太子河流域动态临界雨量指标,临界雨量随起始水位的升高而有所减小。     

一个载水预报模式的业务预报应用试验

该文在国家气象中心现行有限区域业务预报模式（LAM）的基础上,把模式的水平分辨率由1°×1°提高到0.5°×0.5°经纬度网格,垂直层次由15层变为20层。在原有物理过程中引入显式降水方案,并使用HLAFS业务系统的实时资料对1997年8月的一次登陆台风造成的强降水过程进行了个例预报试验,取得了较为合理的预报效果。     

浙江中西部大雾天气的气候特征及潜势预报方法

利用2010—2017年逐日雾观测数据、地面常规气象资料、NCEP/NCAR 1°×1°再分析资料和ECMWF细网格模式预报资料,采用统计法分析了浙江省中西部地区(27°N—30.0°N,118°E—121°E)雾日的时空分布特征,再通过相关性检验精选出物理因子,用逐步回归法建立雾的潜势预报模型。结果表明:(1)雾出现频率最高的区域是山区,时段是11月至次年4月、夜间至次日10:00;(2)通过精选的预报因子和提取的消空指标,确定的浙江省中西部地区冬半年雾日预报的多元回归方程,与实况拟合率为80.8%,回报检验的正确率、空报率、漏报率和TS评分分别为86.4%、39.0%、32.0%和0.47;(3)基于ECMWF细网格模式预报产品,每天可自动生成逐3 h雾预报产品并投入业务应用。     

我国面雨量研究及业务应用进展

面雨量是防汛部门在洪水预报与水库调度中一个非常重要的参数,是洪水预报中最重要的预报对象。介绍了国内外水文气象学者在面雨量的插值与估算方法和面雨量预报方法方面的研究及业务实践进展,为各地结合自身流域特点,开展面雨量预报业务及研究提供参考。     

15~30d延伸期逐日预报在线显示平台的设计与实现

延伸期逐日预报是近年来涌现出的新兴气象业务。详细介绍了浙江省气候中心研发的15~30 d延伸期逐日预报在线显示平台。该平台以CFSv2和DERF2.0两个气候模式的预报产品为依托,基于5日集合平均方案,运用双线性插值技术形成0.25°×0.25°格点预报产品和省、市、县(市、区)三级行政区域站点预报产品,通过绝对误差和空间相关系数两种方法开展预报检验。针对县级气象部门的精细化服务需求,设计了15~30 d预报时间序列显示界面,并通过"包络线法"和"误差线法"分别给出平均气温和降水预报的上下限。业务平台测试版试运行以来表现出较好的预报性能,以2016年4月两次持续性强降水过程为例分析了平台的预报表现,结果表明平台分别提前20 d和16 d预报出这两次过程。针对存在的问题和不足进行了探讨,指出大力发展数值模式解释应用技术和概率预报是业务平台不断走向深入的技术基石。     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.     

基于QPE和QPF的遗传神经网络洪水预报试验

以湖北省清江上游水布垭控制流域为例,利用分组Z-I关系并结合地面雨量站资料对雷达估算降水进行校准,计算出流域实况平均面雨量;再利用遗传算法和神经网络相结合的方法建立订正AREM预报降水的模型;最后,将订正前后的AREM预报降水输入新安江水文模型进行洪水预报试验。结果表明：订正后AREM预报降水能明显提高过程的累计降水量预报精度,平均相对误差减小幅度在60%以上,对逐小时过程降水预报精度也有一定提高,但与实况相比仍有一定差距;订正前后AREM预报降水的洪水预报试验的确定性系数的场次平均从-32.6%提高到64.38%,洪峰相对误差从39%减小到25.04%,确定性系数的提高效果优于洪峰相对误差,整体上洪水预报精度有所提高。     

Implications of 21st century climate change for the hydrology of Washington State

Pacific Northwest (PNW) hydrology is particularly sensitive to changes in climate because snowmelt dominates seasonal runoff, and temperature changes impact the rain/snow balance. Based on results from the Fourth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR4), we updated previous studies of implications of climate change on PNW hydrology. PNW 21st century hydrology was simulated using 20 Global Climate Models (GCMs) and 2 greenhouse gas emissions scenarios over Washington and the greater Columbia River watershed, with additional focus on the Yakima River watershed and the Puget Sound which are particularly sensitive to climate change. We evaluated projected changes in snow water equivalent (SWE), soil moisture, runoff, and streamflow for A1B and B1 emissions scenarios for the 2020s, 2040s, and 2080s. April 1 SWE is projected to decrease by approximately 38–46% by the 2040s (compared with the mean over water years 1917–2006), based on composite scenarios of B1 and A1B, respectively, which represent average effects of all climate models. In three relatively warm transient watersheds west of the Cascade crest, April 1 SWE is projected to almost completely disappear by the 2080s. By the 2080s, seasonal streamflow timing will shift significantly in both snowmelt dominant and rain–snow mixed watersheds. Annual runoff across the State is projected to increase by 2–3% by the 2040s; these changes are mainly driven by projected increases in winter precipitation.     

三峡库区降水—径流关系及径流量预报模型研究

利用2000—2007年长江上游各分流域面雨量实测资料、雷达遥测面雨量资料以及各水文站的历史资料,对流域降水量、洪水传播时间、径流数据以及基流值进行了针对性处理;通过单日产流Pa+P—R(降水量加前期影响雨量—径流)分析和场次洪水总量Crr—P(a径流系数—前期影响雨量)分析,结合各分流域拟合效果及检验,研究了三峡库区降水—径流关系,证明采用雷达遥测的降水数据作为降水量输入来预报各分流域未来时段内产流量是最佳选择,由此建立了三峡库区径流量的预报模型。     

Simulating the hydrological response to predicted climate change on a watershed in southern Alberta, Canada

The current body of research in western North America indicates that water resources in southern Alberta are vulnerable to climate change impacts. The objective of this research was to parameterize and verify the ACRU agro-hydrological modeling system for a small watershed in southern Alberta and subsequently simulate the change in future hydrological responses over 30-year simulation periods. The ACRU model successfully simulated monthly streamflow volumes (r ²?=?0.78), based on daily simulations over 27 years. The delta downscaling technique was used to perturb the 1961?C1990 baseline climate record from a range of global climate model (GCM) projections to provide the input for future hydrological simulations. Five future hydrological regimes were compared to the 1961?C1990 baseline conditions to determine the average net effect of change scenarios on the hydrological regime of the Beaver Creek watershed over three 30-year time periods (starting in 2010, 2040 and 2070). The annual projections of a warmer and mostly wetter climate in this region resulted in a shift of the seasonal streamflow distribution with an increase in winter and spring streamflow volumes and a reduction of summer and fall streamflow volumes over all time periods, relative to the baseline conditions (1961?C1990), for four of the five scenarios. Simulations of actual evapotranspiration and mean annual runoff showed a slight increase, which was attributed to warmer winters, resulting in more winter runoff and snowmelt events.     

Deep groundwater mediates streamflow response to climate warming in the Oregon Cascades

Recent studies predict that projected climate change will lead to significant reductions in summer streamflow in the mountainous regions of the Western US. Hydrologic modeling directed at quantifying these potential changes has focused on the magnitude and timing of spring snowmelt as the key control on the spatial–temporal pattern of summer streamflow. We illustrate how spatial differences in groundwater dynamics can also play a significant role in determining streamflow responses to warming. We examine two contrasting watersheds, one located in the Western Cascades and the other in the High Cascades mountains of Oregon. We use both empirical analysis of streamflow data and physically based, spatially distributed modeling to disentangle the relative importance of multiple and interacting controls. In particular, we explore the extent to which differences in snow accumulation and melt and drainage characteristics (deep ground water vs. shallow subsurface) mediate the effect of climate change. Results show that within the Cascade Range, local variations in bedrock geology and concomitant differences in volume and seasonal fluxes of subsurface water will likely result in significant spatial variability in responses to climate forcing. Specifically, watersheds dominated by High Cascade geology will show greater absolute reductions in summer streamflow with predicted temperature increases.     

Long-term modeling of soil C erosion and sequestration at the small watershed scale

The soil C balance is determined by the difference between inputs (e.g., plant litter, organic amendments, depositional C) and outputs (e.g., soil respiration, dissolved organic C leaching, and eroded C). There is a need to improve our understanding of whether soil erosion is a sink or a source of atmospheric CO₂. The objective of this paper is to discover the long-term influence of soil erosion on the C cycle of managed watersheds near Coshocton, OH. We hypothesize that the amount of eroded C that is deposited in or out of a watershed compares in magnitude to the soil C changes induced via microbial respiration. We applied the erosion productivity impact calculator (EPIC) model to evaluate the role of erosion–deposition processes on the C balance of three small watersheds (∼1 ha). Experimental records from the USDA North Appalachian Experimental Watershed facility north of Coshocton, OH were used in the study. Soils are predominantly silt loam and have developed from loess-like deposits over residual bedrock. Management practices in the three watersheds have changed over time. Currently, watershed 118 (W118) is under a corn (Zea mays L.)–soybean (Glycine max [L.] Merr.) no till rotation, W128 is under conventional till continuous corn, and W188 is under no till continuous corn. Simulations of a comprehensive set of ecosystem processes including plant growth, runoff, and water erosion were used to quantify sediment C yields. A simulated sediment C yield of 43 ± 22 kg C ha⁻¹ year⁻¹ compared favorably against the observed 31 ± 12 kg C ha⁻¹ year⁻¹ in W118. EPIC overestimated the soil C stock in the top 30-cm soil depth in W118 by 21% of the measured value (36.8 Mg C ha⁻¹). Simulations of soil C stocks in the other two watersheds (42.3 Mg C ha⁻¹ in W128 and 50.4 Mg C ha⁻¹ in W188) were off by <1 Mg C ha⁻¹. Simulated eroded C re-deposited inside (30–212 kg C ha⁻¹ year⁻¹) or outside (73–179 kg C ha⁻¹ year⁻¹) watershed boundaries compared in magnitude to a simulated soil C sequestration rate of 225 kg C ha⁻¹ year⁻¹ and to literature values. An analysis of net ecosystem carbon balance revealed that the watershed currently under a plow till system (W128) was a source of C to the atmosphere while the watersheds currently under a no till system (W118 and W188) behaved as C sinks of atmospheric CO₂. Our results demonstrate a clear need for documenting and modeling the proportion of eroded soil C that is transported outside watershed boundaries and the proportion that evolves as CO₂ to the atmosphere.     

Applying a coupled hydrometeorological simulation system to flash flood forecasting over the Korean Peninsula

In flash flood forecasting, it is necessary to consider not only traditional meteorological variables such as precipitation, evapotranspiration, and soil moisture, but also hydrological components such as streamflow. To address this challenge, the application of high resolution coupled atmospheric-hydrological models is emerging as a promising alternative. This study demonstrates the feasibility of linking a coupled atmospheric-hydrological model (WRF/WRFHydro) with 150-m horizontal grid spacing for flash flood forecasting in Korea. The study area is the Namgang Dam basin in Southern Korea, a mountainous area located downstream of Jiri Mountain (1915 m in height). Under flash flood conditions, the simulated precipitation over the entire basin is comparable to the domain-averaged precipitation, but discharge data from WRF-Hydro shows some differences in the total available water and the temporal distribution of streamflow (given by the timing of the streamflow peak following precipitation), compared to observations. On the basis of sensitivity tests, the parameters controlling the infiltration of excess precipitation and channel roughness depending on stream order are refined and their influence on temporal distribution of streamflow is addressed with intent to apply WRF-Hydro to flash flood forecasting in the Namgang Dam basin. The simulation results from the WRF-Hydro model with optimized parameters demonstrate the potential utility of a coupled atmospheric-hydrological model for forecasting heavy rain-induced flash flooding over the Korean Peninsula.     

Reconstructing snowmelt in Idaho’s watershed using historic streamflow records

In recent decades, a warming climate likely has accelerated the timing of spring snowmelt in the western United States; however, records of the timing of snowmelt typically only extend to the 1980s. Stream gage data can lengthen records of the timing of snowmelt back to the early 1900s, enhancing understanding of past, current, and future climate change on snowmelt-dominated watersheds and associated ecosystems. We used snowpack telemetry data and historic streamflow records to test reconstructions of final snowmelt dates using Short Time Fourier Transform (STFT) wavelet analysis of hydrographs. STFT reconstructions tested against known final snowmelt dates over the last ~25 years indicate final snowmelt can be determined within ±4 days ~95% of the time and within ±7 days 100% of the time. Comparison of the STFT method with the center of timing method indicates that in addition to reconstructing actual snowmelt dates (as opposed to dates associated with the center of timing of streamflow), the STFT method may limit interpretation errors associated with changes in discharge not related to snowmelt. Reconstructions of final snowmelt dates in the Idaho, U.S. study area show intervals of early snowmelt (1920s–1930s), later and less variable snowmelt (1940s–1970s), and both variable and early snowmelt (~1985–2007). Early and variable snowmelt during the last ~20 years is associated with large wildfires.     

Retrieving air humidity,global solar radiation,and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h(q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h(q). However, the relationship between the width of the singularity spectrum (Δα) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.