An innovative tailored seasonal rainfall forecasting production in Zimbabwe

Farmers?? adaptation to climate change over southern Africa may become an elusive concept if adequate attention is not rendered to the most important adaptive tool, the regional seasonal forecasting system. Uptake of the convectional seasonal rainfall forecasts issued through the southern African regional climate outlook forum process in Zimbabwe is very low, most probably due to an inherent poor forecast skill and inadequate lead time. Zimbabwe??s recurrent droughts are never in forecast, and the bias towards near normal conditions is almost perpetual. Consequently, the forecasts are poorly valued by the farmers as benefits accrued from these forecasts are minimal. The dissemination process is also very complicated, resulting in the late and distorted reception. The probabilistic nature of the forecast renders it difficult to interpret by the farmers, hence the need to review the whole system. An innovative approach to a regional seasonal forecasting system developed through a participatory process so as to offer a practically possible remedial option is described in this paper. The main added advantage over the convectional forecast is that the new forecast system carries with it, predominantly binary forecast information desperately needed by local farmers??whether a drought will occur in a given season. Hence, the tailored forecast is easier for farmers to understand and act on compared to the conventional method of using tercile probabilities. It does not only provide a better forecasting skill, but gives additional indications of the intra-seasonal distribution of the rainfall including onsets, cessations, wet spell and dry spell locations for specific terciles. The lead time is more than 3?months, which is adequate for the farmers to prepare their land well before the onset of the rains. Its simplicity renders it relatively easy to use, with model inputs only requiring the states of El Nino Southern Oscillation (ENSO) and Indian Ocean Dipole (IOD) climate modes. The developed forecast system could be one way to enhance management of risks and opportunities in rain-fed agriculture among small-holder farmers not only in Zimbabwe but also throughout the SADC region where the impact of ENSO and/or IOD on a desired station rainfall is significant.     

Univariate modelling of summer-monsoon rainfall time series: Comparison between ARIMA and ARNN

The present article reports studies to develop a univariate model to forecast the summer monsoon (June–August) rainfall over India. Based on the data pertaining to the period 1871–1999, the trend and stationarity within the time series have been investigated. After revealing the randomness and non-stationarity within the time series, the autoregressive integrated moving average (ARIMA) models have been attempted and the ARIMA(0,1,1) has been identified as a suitable representative model. Consequently, an autoregressive neural network (ARNN) model has been attempted and the neural network has been trained as a multilayer perceptron with the extensive variable selection procedure. Sigmoid non-linearity has been used while training the network. Finally, a three-three-one architecture of the ARNN model has been obtained and after thorough statistical analysis the supremacy of ARNN has been established over ARIMA(0,1,1). The usefulness of ARIMA(0,1,1) has also been described.     

Limitations of real-time models for forecasting river flooding from monsoon rainfall

Very intense rainfall during the southwest and northeast monsoons causes severe river flooding in India. Some traditional techniques used for real-time forecasting of flooding involve the relationship between effective rainfall and direct surface runoff, which simplifies the complex interactions between rainfall and runoff processes. There are, however, serious problems in deducing these variables in real time, so it is highly desirable to have a real-time flood forecasting model that would directly relate the observed discharge hydrograph to the observed rainfall. The storage routing model described by Baba and Hoshi (1997), Tanaka et al. (1997), and Baba et al. (2000), and a simplified version of this model, have been used to compute observed river discharge directly from observed hourly rainfall. This method has been used to study rainfall–runoff data of the Ajay River Basin in eastern India. Five intense rainfall events of this basin were studied. Our results showed that the Nash–Sutcliffe efficiency of discharge prediction for these five events was 98.6%, 94.3%, 86.9%, 85.6%, and 67%. The hindcast for the first two events is regarded as completely satisfactory whereas for the next two events it is deemed reasonable and for the fifth it is unsatisfactory. It seems the models will yield accurate hindcast if the rainfall is uniform over the drainage basin. When the rainfall is not uniform the performance of the model is unsatisfactory. In future this problem can, in principle, be corrected by using a weighted amount if rainfall is based upon multiple rain-gauge observations over the drainage basin. This would provide some measure of the dispersion in the rainfall. The model also seems unable to simulate flooding events with multiple peaks.     

Local rainfall thresholds for forecasting landslide occurrence: Taipingshan landslide triggered by Typhoon Saola

This paper presents a case study of the Taipingshan landslide, which was triggered by Typhoon Saola in 2012. Taipingshan villa is one of the most famous scenic locations within the Taipingshan National Forest Recreation Area in northern Taiwan. Since the early 1990s, evidence of recent landslide activity appeared throughout the Taipingshan villa and included features such as tension cracks, ground settlement, and cracking in manmade structures. In response, a series of geological investigations and in-site/laboratory tests were conducted in 2010 to estimate slope stability and predict critical rainfall thresholds (event accumulated rainfall) for landslide activity. Results revealed that the critical rainfall threshold for the Taipingshan National Forest Recreation Area is 1765 mm. In 2012, that threshold was tested when Typhoon Saola brought tremendous rainfall to northern and eastern Taiwan and triggered activity along the main scarp of sliding mass B located near the History Exhibition Hall. According to in situ extensometer readings and on-site precipitation data, the extensometer was severed at an accumulated rainfall 1694 mm. Field monitoring data during the typhoon event are in good agreement with the rainfall threshold. These preliminary results suggest that the threshold may be useful for assessing the rainfall threshold of other landslides and a good reference for establishing early warning systems for landslides.     

Coupling typhoon rainfall forecasting with overland-flow modeling for early warning of inundation

Taiwan suffers from an average of three or four typhoons annually, and the inundation caused by the heavy precipitation that is associated with typhoons frequently occurs in lowlands and floodplains. Potential inundation maps have been widely used as references to set up non-structural strategies for mitigating flood hazards. However, spatiotemporal rainfall distributions must be addressed to improve the accuracy of inundation forecasting for emergency response operations. This study presents a system for 24-h-ahead early warning of inundation, by coupling the forecasting of typhoon rainfall with the modeling of overland flow. A typhoon rainfall climatology model (TRCM) is introduced to forecast dynamically the spatiotemporal rainfall distribution based on typhoon tracks. The systematic scheme for early warning of inundation based on the spatiotemporal downscaling of rainfall and 2D overland-flow modeling yields not only the extent of inundation, but also the time to maximum inundation depth. The scheme is superior to traditional early warning method referring to the maximum extent and depth of inundation determined from conditional uniform rainfall. Analytical results show that coupling TRCM with an overland-flow model yields satisfactory inundation hydrographs for warning of the extent and peak time of inundation. This study also shows that the accuracy of forecasting spatiotemporal rainfall patterns determines the performance of inundation forecasting, which is critical to emergency response operations.     

降雨影响下滑坡变形预测的GA-NN模型研究

八尺门滑坡是福-宁高速公路施工现场的一个降雨型滑坡,近年来该滑坡由于人为及降雨的因素而频频发生滑动,对坡下的高速公路施工及滑坡区内的人民生命财产安全造成了严重威胁。为了准确掌握降雨量与滑坡位移之间的关系,在对八尺门滑坡现场降雨量及滑坡位移的长达一年的监测资料的基础上,利用GA-NN模型,对降雨条件下的滑坡位移演化发展做出了精确的预测。研究成果已作为重要的基础性数据被有关施工和研究部门采用,对于指导现场施工和保证滑坡影响区内人民生命财产的安全发挥了重要作用。     

Multivariate geostatistical methods of mean annual and seasonal rainfall in southwest Saudi Arabia

A multivariate geostatistics (cokriging) is used for regional analysis and prediction of rainfall throughout the southwest region of Saudi Arabia. Elevation is intruded as a covariant factor in order to bring topographic influences into the methodology. Sixty-three representative weather stations are selected for a 21-year period covering different microclimate conditions. Results show that on an annual basis, there is no significant change using elevation. On the seasonal basis, the cokriging method gave more information about rainfall occurrence values, its accuracy related to the degree of correlation between elevation and rainfall by season. The prediction of spring and winter rainfall was improved owing to the importance of orographic processes, while the summer season was not affected within its monsoon climatology. In addition, fall season shows inverse and weak correlation of elevation with rainfall. Cross-validation and cokriging variances are also used for more accuracy of rainfall regional estimation. Moreover, even though the correlation is not significant, the isohyet values of cokriged estimates provided more information on rainfall changes with elevation. Finally, adding more secondary variables in addition to elevation could improve the accuracy of cokriging estimates.     

Deformation responses of landslides to seasonal rainfall based on InSAR and wavelet analysis

Landslides - Rainfall-induced landslides are an important type of dangerous natural disaster worldwide and have always been the focus of research. Yet, the impact of seasonal rainfall on landslides...     

Trend analysis and ARIMA modelling of pre-monsoon rainfall data for western India

Spatial and temporal variability of rainfall over different seasons influence physical, social and economic parameters. Pre-monsoon (March, April and May – MAM) rainfall over the country is highly variable. Since heat lows and convective rainfall in MAM have an impact on the intensity of the ensuing monsoons, hence the pre-monsoon period was chosen for the study. The pre-whitened Mann Kendall test was used to explore presence of rainfall trend during MAM. The results indicate presence of significant (at 10% level) increasing trend in two stations (Ajmer, Bikaner). The practical significance of the change in rainfall was also explored as percentage changes over long term mean, using Theil and Sen's median slope estimator. Forecast using univariate ARIMA model for pre-monsoon months indicates that there is a significant rise in the pre-monsoon rainfall over the northwest part of the country.     

Analysis of seasonal and annual rainfall trends for Ranchi district,Jharkhand, India

The aim of this study was to investigate temporal variation in seasonal and annual rainfall trend over Ranchi district of Jharkhand, India for the period (1901–2014: 113 years). Mean monthly rainfall data series were used to determine the significance and magnitude of the trend using non-parametric Mann–Kendall and Sen’s slope estimator. The analysis showed a significant decreased in rainfall during annual, winter and southwest monsoon rainfall while increased in pre-monsoon and post-monsoon rainfall over the Ranchi district. A positive trend is detected in pre-monsoon and post-monsoon rainfall data series while annual, winter and southwest monsoon rainfall showed a negative trend. The maximum decrease in rainfall was found for monsoon (? 1.348 mm year^?1) and minimum (? 0.098 mm year^?1) during winter rainfall. The trend of post-monsoon rainfall was found upward (0.068 mm year^?1). The positive and negative trends of annual and seasonal rainfall were found statistically non-significant except monsoon rainfall at 5% level of significance. Rainfall variability pattern was calculated using coefficient of variation CV, %. Post-monsoon rainfall showed the maximum value of CV (70.80%), whereas annual rainfall exhibited the minimum value of CV (17.09%), respectively. In general, high variation of CV was found which showed that the entire region is very vulnerable to droughts and floods.     

离心模拟技术中运动学的物理意义

研究离心模拟中的运动学,有助于提高对离心模型试验结果的认识。笔者推导了描述离心模型中任一质点运动的整体速度和加速度的数学表达式。按照牛顿第二定律,在离心模拟中的加速度是连接运动学与动力学的重要因素。笔者描述了整体加速度表达式中各项的物理意义,指出了离心机稳定运转时的向心加速度、由角加速度效应引起的切向加速度、互补(复合向心)加速度分量、径向(原型的竖向)、环向和轴向(原型的两个水平方向)振动效应以及离心机臂伸长效应对整体加速度的贡献。分析结果表明,对于单向振动的动力离心模拟试验,选轴向(平行于转轴)为振动方向便于理解试验结果。另外,仔细检查了Schofield[1]对离心模拟中运动学的描述并发现其混淆之处。     

Indian summer monsoon rainfall (ISMR) forecasting using time series data: A fuzzy-entropy-neuro based expert system

This study presents a model to forecast the Indian summer monsoon rainfall(ISMR)(June-September)based on monthly and seasonal time scales. The ISMR time series data sets are classified into two parts for modeling purposes, viz.,(1) training data set(1871-1960), and(2) testing data set(1961-2014).Statistical analyzes reflect the dynamic nature of the ISMR, which couldn't be predicted efficiently by statistical and mathematical based models. Therefore, this study suggests the usage of three techniques,viz., fuzzy set, entropy and artificial neural network(ANN). Based on these techniques, a novel ISMR time series forecasting model is designed to deal with the dynamic nature of the ISMR. This model is verified and validated with training and testing data sets. Various statistical analyzes and comparison studies demonstrate the effectiveness of the proposed model.     

Effect of rainfall characteristics on removal efficiency evaluation in vegetative filter strips

The efficiency of a facility to remove non-point source pollution is likely to fluctuate according to conditions such as facility type and rainfall events; therefore, it is required to use a proper method to estimate removal efficiency. This study was conducted to estimate the efficiency of a facility with vegetative filter strips to remove pollutants by using methods previously used for the estimation of removal efficiency and compensate for weaknesses of the known methods. Other ways were presented to estimate an efficiency by which rainfall events were classified according to meteorological condition and amount of rainfall. Rainfall of frequency and summation of load as rainfall of frequency, where the frequencies per rainfall class were considered in efficiency ratio and summation of loads, respectively, seemed to have higher removal efficiencies than those estimated with the previous methods. Although it rained at the basin site, often in small quantity (below 10 mm), the rainfall events of below 10 mm were less frequent, during the monitored rainfall events, which accordingly resulted in low removal efficiencies. However, if the frequencies per rainfall class were considered, overall removal efficiencies of VFS might be increased because the removal efficiencies of the rainfall class under 10?mm was higher than other rainfall classes. Therefore, it is desirable to take into account such factors as effects of rainfall when it comes to measuring the removal efficiency of a non-point source pollutant of a factor, because those facilities are likely to be influenced by meteorological conditions including rainfall characteristics.     

降雨诱发直线型黄土填方边坡失稳模型试验

近年来,随着“治沟造地”和“固沟保塬”等工程在黄土高原的陆续开展,出现了许多直线型黄土填方边坡。降雨是诱发边坡失稳的重要因素,但对降雨诱发直线型黄土填方边坡变形演化特征和破坏模式的研究较少。以直线型黄土填方边坡为研究对象,通过传感器监测、三维激光扫描和人工降雨,开展室内降雨模型试验,记录了降雨入渗下边坡内部水文响应特征和边坡失稳破坏过程,并对湿润锋、土颗粒运移、坡体内部变形响应、裂缝演化特征及破坏模式进行了分析。试验结果表明：随着降雨入渗,湿润锋达到后,体积含水率增加,并在峰值后保持稳定,而基质吸力则减小,到达最低点后保持稳定。冲沟对填方边坡的影响较大,它的发育改变了坡体内含水率特征,同时也是控制边坡整体滑动的边界;边坡变形响应区域主要是以填方边坡前缘堆积区和后缘滑塌区为主;裂缝演化方向由边坡前缘向后缘发展,它的发育为雨水入渗提供优势通道,同时也加剧边坡的变形破坏;降雨形成的水动力驱使坡体中细颗粒从填方边坡后缘向前缘流失,减弱了土体颗粒之间的胶结能力,使其抗剪强度降低,进而使边坡失稳破坏。因此,在降雨入渗下,直线型黄土填方边坡的变形破坏模式为：坡顶冲沟破坏、坡脚软化→局部牵引坍塌、整体失稳→块体分割、流滑破坏。研究结果可为直线型黄土填方边坡的工程建设和滑坡灾害防治提供理论参考。     

Analysis of seasonal water pollution based on rainfall feature at Anyang river basin in Korea

To determine selected water pollution parameters of the Anyang River (one of the biggest contributory branches of the Han River in Korea) and its main tributaries, the geological and topographical and rainfall features in its basin were investigated, and the resulting data were tabulated. Samples were collected at the upper, mid and down parts of the Anyang River and its branches and were analyzed based on biochemical and chemical methods, Korean biotic index (KBI) and Saprobien systems. Selected parameters of concern include BOD, heavy metals, nonpoint pollution and sewage discharge. The Anyang River basin has a torrential heavy rainfall; however, the rate of rainfall significantly varies from season to season. Water pollution levels in the dry season increase dramatically. The mainstream of the Anyang River is classified as fifth grade polysaprobic water according to Saprobien system. In addition, the biotic index is over 2.5 in overall. General pollution at the junction of the Anyang River and each branch stream varies. Possible countermeasures to improve the water quality of the river include intercept the non-treated waste water and sewage at the Anyang River junction and each branch stream, enforcement of water management during the rainy season, and continuous investment on environmental restoration.     

Development of a technique for modelling clay liner desiccation

This paper presents a model for the analysis of clay liner desiccation in a landfill barrier system due to temperature effects. The model incorporates consideration of fully coupled heat‐moisture‐air flow, a non‐linear constitutive relationship, the dependence of void ratio and volumetric water content on stress, capillary pressure and temperature, and the effect of mechanical deformation on all governing equations. Mass conservative numerical schemes are proposed to improve the accuracy of the finite element solution to the governing equations. The application of the model is then demonstrated by examining three test problems, including isothermal infiltration, heat conduction and non‐isothermal water and heat transport. Comparisons are made with results from literature, and good agreement is observed. Copyright © 2003 John Wiley & Sons, Ltd.     

Validation and error analysis of a strata modelling technique

Summary Sources of error are investigated for a two-dimensional finite difference computer program designed to model strata deformation. The program calculates the displacements of a mesh of mass points, by the iterative solution of equations of equilibrium for the stresses acting on each mass point. The effect of errors on both displacement estimates and stress estimates is considered.Round-off errors are discussed analytically, while the effect of choosing too coarse a mesh density is demonstrated by comparison of two runs of the program with identical material properties, but different mesh densities. The influence of boundary conditions and the result of incomplete relaxation of the finite difference equations is estimated by comparison with Kirsch's analytical solution for a thin plate of finite width with a circular hole under unidimensional load.As a result of the analysis, estimators for stresses and displacements are derived, which make allowance for some of the sources of error; suitable boundary conditions for first and subsequent runs of the program are proposed; and a convergence criterion for the iterative process is suggested. These results are then applied to simulations of mining situations, together with various refinements of the basic model, such as separation and slip between adjacent strata, and an allowance for failure of material.