山东水资源分析及趋势预测

通过分析近３９年山东省水资源的历史倾向性、阶段性、周期性,研究了水资源总量及径流量和地下水位的变化特征。结果表明,山东水资源量的年际变化大且呈快速下降态势,其中,地表径流量的下降尤为明显;水资源的变化存在一定的阶段性和周期性。通过分析降水与水资源的关系,发现两者的变化规律一致,但降水对水资源,特别是对地下水分量的影响有一定的持续性。建立均生函数预测模型,对未来水资源总量进行预测显示,１９９８￣２０     

北京暴雨与旱涝关系的分析

根据北京近百年的逐日降水资料,分析了汛期暴雨与汛期旱涝的关系。指出:汛期暴雨多少和强度对汛期降水丰歉具有决定性作用;在给出的3种暴雨指数中,相当暴雨日数与旱涝级别的相关性最好。文中还讨论了旱涝短期气候预测与暴雨过程的短期气候预测相结合的必要性。     

“地气图”方法用于省级旱涝预测的实践

简要介绍用“地气图”方法进行降水预测的基本思路,总结此方法的预报实践,指出省级尺度旱涝预测需要解决的几个关键问题,强调除加密观测外,上游地热涡增强的能量频散作用是下游地热涡发展的重要原因     

中国地区大气气溶胶辐射强迫及区域气候效应的数值模拟

利用太阳直接辐射日总量和日照时数等多年观测资料,反演了中国地区大气气溶胶0.75 μm光学厚度的年、月平均值,分析了我国大气气溶胶状况的时空分布特征。据此,在中国区域气候模式中考虑气溶胶的辐射影响,模拟中国地区气溶胶直接辐射强迫的大小及气候响应的季节变化特征。计算结果表明: 我国大气气溶胶光学厚度多年平均分布状况是以四川盆地为大值中心向四周减少;长江中下游武汉附近和南疆盆地为另两个大值中心;青藏高原为气溶胶低值区;我国绝大部分地区春季气溶胶光学厚度值最大,各地气溶胶光学厚度最小值出现的季节则有所不同。气溶胶辐射强迫介于-5.3～-13 W/m2之间;辐射强迫具有春、夏季大,秋、冬季小,冬季南方偏大,夏季北方偏大的特征。气溶胶辐射强迫的分布与其光学厚度的分布基本一致。由于气溶胶的影响,中国大陆地区地面气温均有所下降,四川盆地到长江中下游地区以及青藏高原北侧到河套地区降温最为明显,分别可达-0.4℃和-0.5℃。气候响应具有明显的季节特征。地面气温的变化除与辐射强迫的大小有关外,还受大气环流的影响。     

Numerical weather prediction relevant to the monsoon problem

In this short paper we have identified some of the modelling groups that have the capability of simulating or carrying out short range numerical weather prediction over the monsoon belt. We have next outlined some of the important and desirable ingredients for a multilevel primitive equation model over the tropics, with most of the emphasis on the present version of Florida State University's Tropical Prediction Model. Finally, we present briefly some important results based on the present version of our prediction models that relate to the NWP efforts over the monsoon belt. Here we have identified the importance of mountains, convection, the radiative heating balance of the earth's surface, and the planetary boundary layer over the Arabian Sea.     

A comparative study of extensive machine learning models for predicting long-term monthly rainfall with an ensemble of climatic and meteorological predictors

Rainfall prediction is of vital importance in water resources management. Accurate long-term rainfall prediction remains an open and challenging problem. Machine learning techniques, as an increasingly popular approach, provide an attractive alternative to traditional methods. The main objective of this study was to improve the prediction accuracy of machine learning-based methods for monthly rainfall, and to improve the understanding of the role of large-scale climatic variables and local meteorological variables in rainfall prediction. One regression model autoregressive integrated moving average model (ARIMA) and five state-of-the-art machine learning algorithms, including artificial neural networks, support vector machine, random forest (RF), gradient boosting regression, and dual-stage attention-based recurrent neural network, were implemented for monthly rainfall prediction over 25 stations in the East China region. The results showed that the ML models outperformed ARIMA model, and RF relatively outperformed other models. Local meteorological variables, humidity, and sunshine duration, were the most important predictors in improving prediction accuracy. 4-month lagged Western North Pacific Monsoon had higher importance than other large-scale climatic variables. The overall output of rainfall prediction was scalable and could be readily generalized to other regions.     

Response of saturated and nearly saturated porous media: Different formulations and their applicability

The response of saturated porous medium is of significant interest in many fields ranging from geomechanics to biomechanics. Biot was the first to formulate the basic equations governing the process of coupled flow and deformation in porous media. Depending on the nature of loading vis‐à‐vis the characteristics of the media, different formulations (fully dynamic, partly dynamic, quasi‐static) are possible. In this study, analytical solutions are developed for the response of saturated and nearly saturated porous media under plane strain condition. The solutions for different formulations are developed in terms of non‐dimensional parameters. The response is studied for various conditions and the regions of validity for various formulations are identified in a parametric space. An assessment of the needed formulation for few important problems is also presented. Copyright © 2008 John Wiley & Sons, Ltd.     

Effects of land‐use changes on hydrological processes in the middle basin of the Heihe River,northwest China

The effects of land‐use changes on the runoff process in the midstream plain of this arid inland river basin are a key factor in the rational allocation of water resources to the middle and lower reaches. The question is whether and by how much increasingly heavy land use impacts the hydrological processes in such an arid inland river basin. The catchment of the Heihe River, one of the largest inland rivers in the arid region of northwest China, was chosen to investigate the hydrological responses to land‐use change. Flow duration curves were used to detect trends and variations in runoff between the upper and lower reaches. Relationships among precipitation, upstream runoff, and hydrological variables were identified to distinguish the effects of climatic changes and upstream runoff changes on middle and downstream runoff processes. The quantitative relation between midstream cultivated land use and various parameters of downstream runoff processes were analysed using the four periods of land‐use data since 1956. The Volterra numerical function relation of the hydrological non‐linear system response was utilized to develop a multifactor hydrological response simulation model based on the three factors of precipitation, upstream runoff, and cultivated land area. The results showed that, since 1967, the medium‐ and high‐coverage natural grassland area in the midstream region has decreased by 80·1%, and the downstream runoff has declined by 27·32% due to the continuous expansion of the cultivated land area. The contribution of cultivated land expansion to the impact on the annual total runoff is 14–31%, on the annual, spring and winter base flow it is 44–75%, and on spring and winter discharge it is 23–64%. Once the water conservation plan dominated by land‐use structural adjustments is implemented over the next 5 years, the mean annual discharge in the lower reach could increase by 8·98% and the spring discharge by 26·28%. This will significantly alleviate the imbalance between water supply and demand in both its quantity and temporal distribution in the middle and lower reaches. Copyright © 2006 John Wiley & Sons, Ltd.     

Modelling observed and future runoff from a glacierized tropical catchment (Cordillera Blanca, Perú)

Monthly runoff from the 34.3% glacierized tropical catchment of Llanganuco in the tropical Cordillera Blanca, Perú, is successfully simulated and compared with a measured 44 year time series. In the investigation area, the climate is characterized by all-year round homogenous temperature conditions and a strong variability in air humidity and moisture content of the atmosphere. Thus, contrary to the mid latitudes, the seasonal variation in glacier melt strongly depends on moisture-related variables, rather than on air temperature. The here presented ITGG-2.0-R model aims for these requirements. The lack of moisture-related input data other than precipitation demands for an intermediate calibration step. Net shortwave radiation, the emissivity of the atmosphere and a sublimation/melt ratio are related to precipitation amounts. Runoff is well simulated and correlates with the measured record with r² = 0.76. Seasonally obtained r² are only slightly smaller. On a long-term, the cumulative deviation is minor, and the mean annual cycle of runoff is reproduced rather well (r² = 0.99). Based on four different IPCC climate change scenarios, future runoff is simulated. All runoff scenarios are modelled for the respective steady-state glacier extent. This leads to a reduction in the glacier size and a decreased amount of glacier melt. On the other hand, direct runoff increases due to larger glacier free areas. Consequently, mean annual runoff remains almost unchanged, but the seasonality intensifies considerably with more runoff during the wet and less runoff during the dry season.     

Vertical dynamic response of a rigid foundation embedded in a poroelastic soil layer

A simplified analytical method is presented for the vertical dynamic analysis of a rigid, massive, cylindrical foundation embedded in a poroelastic soil layer. The foundation is subjected to a time‐harmonic vertical loading and is perfectly bonded to the surrounding soil in the vertical direction. The soil underlying the foundation base is represented by a single‐layered poroelastic soil based on rigid bedrock while the soil at the side of the foundation is modeled as an independent poroelastic layer composed of a series of infinitesimally thin layers. The behavior of the soil is governed by Biot's poroelastodynamic theory and its governing equations are solved by the use of Hankel integral transform. The contact surface between the foundation base and the soil is smooth and fully permeable. The dynamic interaction problem is solved following standard numerical procedures. The accuracy of the present solution is verified by comparisons with the well‐known solutions obtained from other approaches for both the elastodynamic interaction problem and poroelastodynamic interaction problem. Numerical results for the vertical dynamic impedance and response factor of the foundation are presented to demonstrate the influence of nondimensional frequency of excitation, soil layer thickness, poroelastic material parameters, depth ratio and mass ratio on the dynamic response of a rigid foundation embedded in a poroelastic soil layer. Copyright © 2008 John Wiley & Sons, Ltd.