FLOW DURATION CURVES II: A REVIEW OF APPLICATIONS IN WATER RESOURCES PLANNING1

ABSTRACT: A streamflow duration curve illustrates the relationship between the frequency and magnitude of streamflow. Flow duration curves have a long history in the field of water-resource engineering and have been used to solve problems in water-quality management, hydropower, instream flow methodologies, water-use planning, flood control, and river and reservoir sedimentation, and for scientific comparisons of streamflow characteristics across watersheds. This paper reviews traditional applications and provides extensions to some new applications, including water allocation, wasteload allocation, river and wetland inundation mapping, and the economic selection of a water-resource project.     

ESTIMATING ANNUAL FLOOD PROBABILITIES USING FOURIER SERIES METHOD1

ABSTRACT: The Fourier series method is proposed as a feasible non-parametric approach for the estimation of the density and distribution functions of annual floods. Clearly, the goodness of fit to empirical data improves as higher Fourier terms are incorporated, and the choice of a higher term depends on whether the inclusion of this term will reduce the fitting error to within a specified tolerance level. This method was applied to the flood data from eight rivers, and to data simulated from known distributions. The results are clearly better than other parametric methods, just like other non-parametric techniques currently used to estimate annual flood probabilities.     

ESTIMATING MEAN AND VARIANCE FOR ENVIRONMENTAL SAMPLES WITH BELOW DETECTION LIMIT OBSERVATIONS1

ABSTRACT: Left-censoring of data sets complicates subsequent statistical analyses. Generally, substitution or deletion methods provide poor estimates of the mean and variance of censored samples. These substitution and deletion methods include the use of values above the detection limit (DL) only, or substitution of 0, DL/2 or the DL for the below DL values during the calculation of mean and variance. A variety of statistical methods provides better estimators for different types of distributions and censoring. Maximum likelihood and order statistics methods compare favorably to the substitution or deletion methods. Selected statistical methods applicable to left-censoring of environmental data sets are reviewed with the purpose of demonstrating the use of these statistical methods for coping with Type I (and Type II) left-censoring of normally and log-normally distributed environmental data sets. A PC program (UNCENSOR) is presented that implements these statistical methods. Problems associated with data sets with multiple DLs are discussed relative to censoring methods for life and fatigue tests as recently applied to water quality data sets.     

COMPARING SOME METHODS OF ESTIMATING MEAN AREAL RAINFALL1

ABSTRACT: A comparison of 13 different methods of estimating mean areal rainfall was made on two areas in New Mexico, U.S.A., and one area in Great Britain. Daily, monthly and yearly rainfall data were utilized. All methods, in general, yielded comparable estimates, especially for yearly values. This suggested that a simpler method would be preferable for estimating mean areal rainfall in these areas.     

PARAMETRIC/NONPARAMETRIC MIXTURE DENSITY ESTIMATION WITH APPLICATION TO FLOOD-FREQUENCY ANALYSIS1

Much attention has been invested in the model choice problem for peak annual flows, in the context of flood frequency analysis. The authors would sidestep this dilemma through non-parametric density estimation methodology, but recognize that the standard nonparametric estimators preclude the use of prior information and related data, and furthermore have virtually no tail at all. Here we offer a remedy for these inadequacies by introducing an estimator which mixes parametric and nonparametric density estimates. We prove that our mixture rule is consistent. By this procedure, we do allow incorporation of prior information, experience, and regional data information, but nevertheless provide a safeguard against incorrect model choice.     

Air Pollution Effects on Annual Ring Widths of Forest Trees in Mountainous Land of Izmir (Turkey)

Annual ring widths of forest trees are affected from different ecologicalfactors (e.g. climate, soil, etc.) and also from air pollution. In the areas with intensive air pollution annual ring width reductions are observed. For this reason, some methods which detect the annual ring widths, in other words, the increase or decrease in diameter increments, are used to examine air pollution. Industrial establishments found in the northern part of Izmir city (Aliaga region) affect air quality of this area negatively. In this investigation, annual ring widths of 13 Pinus brutia Ten. (Calabrian pine) and 20 Pinus nigra Arnold. (Austrian pine) from 4 mountains (Karabelen, Manisa, Kemalpasa, and Yamanlar) with different altitudes and exposures around Izmir city were detected and the effects of air pollution on these trees were determined. Intensive effects of air pollution have started in 1985, for that reason, annual ring widths were examined through a reference period before this year and a study period (1985–1998) after this year and results are statistically evaluated. Annual ring widths of tree samples in the northern exposure were affected from air pollution, and some reductions were observed. These reductions increased when there is a long drought period.     

Spatial and temporal relationships between precipitation and ANPP of four types of grasslands in northern China

Precipitation is considered to be the primary resource limiting terrestrial biological activity in water-limited regions. Its overriding effect on the production of grassland is complex. In this paper, field data of 48 sites （including temperate meadow steppe, temperate steppe, temperate desert steppe and alpine meadow） were gathered from 31 published papers and monographs to analyze the relationship between above-ground net primary productivity （ANPP） and precipitation by the method of regression analysis. The results indicated that there was a great difference between spatial pattern and temporal pattern by which precipitation influenced grassland ANPP. Mean annual precipitation （MAP） was the main factor determining spatial distribution of grassland ANPP （r^2 = 0.61, P 〈 0.01）; while temporally, no significant relationship was found between the variance of AN PP and inter-annual precipitation for the four types of grassland. However, after dividing annual preeipitation into monthly value and taking time lag effect into account, the study found significant relationships between ANPP and precipitation. For the temperate meadow steppe, the key variable determining inter-annual change of ANPP was last August-May precipitation （r^2 = 0.47, P = 0.01）; for the temperate steppe, the key variable was July precipitation （r^2 = 0.36, P = 0.02）; for the temperate desert steppe, the key variable was April-June precipitation （r^2 = 0.51, P 〈 0.01）; for the alpine meadow, the key variable was last September-May precipitation （r^2 = 0.29, P 〈 0.05）. In comparison with analogous research, the study demonstrated that the key factor determining inter-annual changes of grassland ANPP was the cumulative precipitation in certain periods of that year or the previous year.     

加速度均方根地震动统计研究

根据美国加州等地的强震记录,采用回归分析方法研究了加速度记录水平、竖向分量的峰值加速度(PGA)和一定时间窗内加速度均方根(SRSTM S)的衰减规律。所采用的加速度记录共795组(两水平向与一竖向)2 385条。对作为地震危险性分析的主要参数PGA的衰减规律与SRSTM S的衰减规律作了详细的研究,结果表明,SRSTM S的离散性明显的小于PGA,因此建议将SRSTM S的衰减关系应用于地震动强度的危险性分析。     

Drivers of future streamflow changes in watersheds across the Northeastern United States

Accurate projections of streamflow, which have implications for flooding, water resources, hydropower, and ecosystems, are critical to climate change adaptation and require an understanding of streamflow sensitivity to climate drivers. The northeastern United States has experienced a dramatic increase in extreme precipitation over the past 25 years; however, the effects of these changes, as well as changes in other drivers of streamflow, remain unclear. Here, we use a random forest model forced with a regional climate model to examine historical and future streamflow dynamics of four watersheds across the Northeast. We find that streamflow in the cold season (November–May) is primarily driven by 3-day rainfall and antecedent wetness (Antecedent Precipitation Index) in three rainfall-dominant watersheds, and 30-day rainfall, antecedent wetness, and 30-day snowmelt in the fourth, more snowmelt-dominated watershed. In the warm season (June–October), streamflow is driven by antecedent wetness and rainfall in all watersheds. By the end of the century (2070–2099), cold season streamflow depends on the importance placed on snow in the machine learning model, with changes ranging from −7% (with snow) to +40% (without snow) in a single watershed. Simulated future warm season streamflow increases in two watersheds (56% and 193%) due to increased precipitation and antecedent soil wetness, but decreases in the other two watersheds (−6% and −27%) due to reduced precipitation.     

中等变质程度软硬煤瓦斯放散规律研究

自主设计了煤粒瓦斯吸附-放散试验系统,以郑煤集团告成煤矿普遍存在的中等变质程度贫瘦软硬煤为研究对象,对比分析了贫瘦煤软硬煤前120 min瓦斯解吸规律,试验结果表明,瓦斯解吸初期软煤的解吸速度都大于硬煤的解吸速度,软煤在前30 min解吸量占总解吸累积量的84.07%以上,而硬煤仅为67.76%;对比了多种描述瓦斯解吸-扩散过程的经验公式,发现孙重旭式和文特式拟合效果最好,且相关指数的变化范围较小。