1956-2000年中国潜在蒸散量时空变化特征

1 Introduction Evaporation is one of the important components in the water and heat balances. The transpiration of vegetation and evaporation from soil are collectively called evapotranspiration. Potential evapotranspiration is not only the theoretical li…     

基于推理公式的山洪预警雨量计算方法研究

基于水科院推理公式,从山洪雨量预警需求出发,解除原公式在部分汇流中对流域面积分配曲线的矩形概化,经反演得出各典型时段临界雨量计算式;同时采用等流时方法,有效解决了计算式中最大部分汇流面积的定量问题。研究提出的预警雨量计算方法,物理概念清晰,易于理解和掌握,计算便捷,且无需水文资料,可作为现行山洪预警雨量分析计算的一种新方法。     

沉桩引起的三维超静孔隙水压力计算及其应用

引入时间、深度参数分析在饱和软粘土中沉桩时引起的超静孔隙水压力,给出了考虑固结效应的超静孔隙水压力的三维解析解;分析了超静孔隙水压力的消散过程中桩周土发生曼德尔效应的时间和区域,提出了在群桩施工过程中土体中的超静孔隙水压力是消散与累加的综合过程,施工完毕后则变为单一的消散的计算模型,并给出计算公式。通过算例,分析了桩群不同桩距、不同入桩顺序对超静孔隙水压力的影响。     

基于标准有效温度和不舒适指标研究南京热舒适状况

采用标准有效温度和不舒适指标,分析了南京市热舒适状况。以南京市2010年全年的逐时气温和相对湿度资料为基础,计算了2010年逐月每小时气温和相对湿度平均值。通过假定在均匀的环境条件下,遮阴的室内,伏案工作活动量为1.0 met,夏季服装热阻为0.6 clo,春、秋、冬季服装热阻为0.9 clo,室内风速约为0.125 m/s,计算出各月逐时标准有效温度和不舒适指标。结果表明,南京市的热舒适状况具有明显的季节变化和日变化特征。季节变化特征显示：夏冬两季热舒适度偏低,夏季平均标准有效温度和不舒适指标分别为27.6℃和0.7,人体感觉偏热;冬季平均标准有效温度和不舒适指标分别为9.4℃和-2.8,人体感觉偏冷;春秋两季热舒适度指数高,春季平均标准有效温度和不舒适指标分别为19.7℃和-0.8,秋季为17.2℃和-1.3,人体普遍感觉舒适,但舒适期持续时间短,全年约62天。就日变化特征而言,冬季白天人体热舒适度普遍高于夜间,夏季则相反。上述结果能够较好地反映南京市人体的普遍热舒适感,可为旅游、建筑、医疗、交通等相关行业和部门提供参考。     

热压薄壁金刚石钻头的设计制造与应用

对薄壁金刚石钻头的结构、钢体、加工工艺和规程进行了介绍与分析,并对薄壁金刚石钻头胎体作了不同配方的筛选,选出了ＧＷ１和ＧＷ２号配方,在室内和生产试验中取得了较好的效果。     

基于二元样条函数的DEM传递误差模型

根据两点数值微分公式建立了基于二元样条函数的规则格网数字高程模型(DEM)的表面表达模型,得出了基于二元样条函数的传递误差公式。公式表明,二元样条函数的DEM传递误差与双线性多项式的传递误差相同。但由于样条函数的DEM表面建模误差低于线性多项式的DEM表面建模误差,因此,基于样条函数的DEM表面模型具有更高的精度。     

PUBLICATIONS OF THE IAHS

Abstract

Gauging stations where the stage—discharge relationship is affected by hysteresis due to unsteady flow represent a challenge in hydrometry. In such situations, the standard hydrometric practice of fitting a single-valued rating curve to the available stage—discharge measurements is inappropriate. As a solution to this problem, this study provides a method based on the Jones formula and nonlinear regression, which requires no further data beyond the available stage—discharge measurements, given that either the stages before and after each measurement are known along with the duration of each measurement, or a stage hydrograph is available. The regression model based on the Jones formula rating curve is developed by applying the monoclinal rising wave approximation and the generalized friction law for uniform flow, along with simplifying assumptions about the hydraulic and geometric properties of the river channel in conjunction with the gauging station. Methods for obtaining the nonlinear least-squares rating-curve estimates, while factoring in approximated uncertainty, are discussed. The broad practical applicability and appropriateness of the method are demonstrated by applying the model to: (a) an accurate, comprehensive and detailed database from a hydropower-generated highly dynamic flow in the Chattahoochee River, Georgia, USA; and (b) data from gauging stations in two large rivers in the USA affected by hysteresis. It is also shown that the model is especially suitable for post-modelling hydraulic and statistical validation and assessment.     

Parameterization of the Ångström–Prescott formula based on machine learning benefit estimation of reference crop evapotranspiration with missing solar radiation data

Accurately estimated reference evapotranspiration (ET₀) is essential to regional water management. The FAO recommends coupling the Penman–Monteith (P-M) model with the Ångström–Prescott (A-P) formula as the standard method for ET₀ estimation with missing R_s measurements. However, its application is usually restricted by the two fundamental coefficients (a and b) of the A-P formula. This paper proposes a new method for estimating ET₀ with missing R_s by combining machine learning with physical-based P-M models (PM-ET₀). The benchmark values of the A-P coefficients were first determined at the daily, monthly, and yearly scales, and further evaluated in R_s and ET₀ estimates at 80 national R_s measuring stations. Then, three empirical models and four machine-learning methods were evaluated in estimating the A-P coefficients. Machine learning methods were also used to estimate ET₀ (ML-ET₀) to compare with the PM-ET₀. Finally, the optimal estimation method was used to estimate the A-P coefficients for the 839 regular weather stations for ET₀ estimation without R_s measurement for China. The results demonstrated a descending trend for coefficient a from northwest to southeast China, with larger values in cold seasons. However, coefficient b showed the opposite distribution as the coefficient a. The FAO has recommended a larger a but a smaller b for southeast China, which produced the region's largest R_s and ET₀ estimation errors. Additionally, the A-P coefficients calibrated at the daily scale obtained the best estimation accuracy for both R_s and ET₀, and slightly outperformed the monthly and yearly coefficients without significant difference in most cases. The machine learning methods outperformed the empirical methods for estimating the A-P coefficients, especially for the sites with extreme values. Further, ML-ET₀ outperformed the PM-ET₀ with yearly A-P coefficients but underperformed those with daily and monthly ones. This study indicates an exciting potential for combining machine learning with physical models for estimating ET₀. However, we found that using the A-P coefficients with finer time scales is unnecessary to deal with the missing R_s measurements.     

面平均雨量的积分计算

利用二重积分表示流域降雨总量。目前计算面平均雨量的三种方法,均可视为对区域进行某种划分及观测点做为特殊点时用二重积分定义进行的近似计算。对区域降雨量函数进行了探讨。     

雄安新区长历时暴雨强度公式及其设计雨型推求

设计暴雨研究是城市排水防涝工程建设的重要基础。基于1981—2020年雄安新区3个地面气象观测站的降雨资料,对其降雨量和暴雨日数的时间变化特征进行了分析;采用雄县分钟级降雨数据,通过年最大值法选样,为兼顾长、短历时降雨样本的拟合优度,选用P-III型曲线对降雨数据进行理论频率分析,通过MATLAB的高斯—牛顿法求解暴雨强度公式中的参数,最终得到长历时综合暴雨强度公式,根据同频率分析法对雄县1440 min的设计暴雨雨型进行推求。结果表明：雄安新区多年平均降雨量为490.4 mm,暴雨日数为4.4 d;2000—2020年暴雨日数呈增多趋势,尤以大暴雨增多明显,近10 a大暴雨发生日数占暴雨日数的比率最大,为20.8%,较21世纪初10 a大将近7倍。编制的长历时综合暴雨强度公式,可计算5—1440 min任意历时、2—100 a任意重现期的设计暴雨。雄县以5 min为步长的1440 min设计暴雨雨型为单峰型,雨峰系数为0.806,结合所编制的长历时综合暴雨强度公式,可推求任意指定重现期下1440 min的设计雨型。