Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

Detecting Climate Change Trend, Size, and Change Point Date on Annual Maximum Time Series Rainfall Data for Warri, Nigeria

The study focused on the detection of indicators of climate change in 24-hourly annual maximum series (AMS) rainfall data collected for 36 years (1982-2017) for Warri Township, using different statistical methods yielded a statistically insignificant positive mild trend. The IMD and MCIMD downscaled model’s time series data respectively produced MK statistics varying from 1.403 to 1.4729, and 1.403 to 1.463 which were less than the critical Z-value of 1.96. Also, the slope magnitude obtained showed a mild increasing trend in variation from 0.0189 to 0.3713, and 0.0175 to 0.5426, with the rate of change in rainfall intensity at 24 hours duration as 0.4536 and 0.42 mm/hr.year (4.536 and 4.2 mm/decade) for the IMD and the MCIMD time series data, respectively. The trend change point date occurred in the year 2000 from the distribution-free CUSUM test with the trend maintaining a significant and steady increase from 2010 to 2015. Thus, this study established the existence of a trend, which is an indication of a changing climate, and satisfied the condition for rainfall Non-stationary intensity-duration-frequency (NS-IDF) modeling required for infrastructural design for combating flooding events.

Quantification of relationship between annual daily maximum temperature and annual daily maximum rainfall in South Australia

The empirical relationship between annual daily maximum temperature(ADMT)and annual daily maximum rainfall(ADMR)was investigated.The data were collected from four weather stations located in Adelaide,South Australia,from 1988 to 2017.Due to the influence of sea surface temperature on rainfall and temperature,the distance from the weather station to the sea was considered in the selection of weather stations.Two weather stations near the sea and two inland weather stations were selected.Three non-parametric statistical tests(Kruskal–Wallis,Mann–Whitney,and correlation)were applied to perform statistical analysis on the ADMT and ADMR data.It was revealed that the temperature and rainfall in South Australia varies according to weather station location.The distance from the sea to the weather station was found to have limited influence on temperature and rainfall.Meanwhile,with the 0.05 level of significance,the association between ADMT and ADMR near sea stations is not as significant as the association between the two inland weather stations.It is relatively unrealistic to use ADMR to predict ADMT,or vice versa,since their correlation is not statistically significant(Spearman’s rank correlation coefficient:−0.106).

Spatial Variability and Cartography of Maximum Annual Daily Rainfall under Different Return Periods in Northern Algeria

The estimation of precipitation quantiles has always been an area of great importance to meteorologists, hydrologists, planners and managers of hydrotechnical infrastructures. In many cases, it is necessary to estimate the values relating to extreme events for the sites where there is little or no measurement, as well as their return periods. A statistical approach is the most used in such cases. It aims to find the probability distribution that best fits the maximum daily rainfall values. In our study, 231 rainfall stations were used to regionalize and find the best distribution for modeling the maximum daily rainfall in Northern Algeria. The L-moments method was used to perform a regionalization based on discordance criteria and homogeneity test. It gave rise to twelve homogeneous regions in terms of LCoefficient of variation(L-CV), L-Skewness(L-CS) and L-Kurtosis(L-CK). This same technique allowed us to select the regional probability distribution for each group using the Z statistic. The generalized extreme values distribution(GEV) was selected to model the maximum daily rainfall of 10 groups located in the north of the steppe region and the generalized logistic distribution(GLO) for groups representing the steppes of Central and Western Algeria. The study of uncertainty by the bias and RMSE showed that the regional approach is acceptable. We have also developed maximum daily rainfall maps for 2, 5, 10, 20, 50 and 100 years return periods. We relied on a network of 255 rainfall stations. The spatial variability of quantiles was evaluated by semi-variograms. All rainfall frequency models have a spatial dependence with an exponential model adjusted to the experimental semi-variograms. The parameters of the fitted semi-variogram for different return periods are similar, throughout, while the nugget is more important for high return periods. Maximum daily rainfall increases from South to North and from West to East, and is more significant in the coastal areas of eastern Algeria where it exceeds 170 mm for a return period of 100 years. However, it does not exceed 50 mm in the highlands of the west.

Radiative Effects on Torrential Rainfall during the Landfall of Typhoon Fitow(2013)

Cloud microphysical and rainfall responses to radiative processes are examined through analysis of cloud-resolving model sensitivity experiments of Typhoon Fitow（2013） during landfall.The budget analysis shows that the increase in the mean rainfall caused by the exclusion of radiative effects of water clouds corresponds to the decrease in accretion of raindrops by cloud ice in the presence of radiative effects of ice clouds,but the rainfall is insensitive to radiative effects of water clouds in the absence of radiative effects of ice clouds.The increases in the mean rainfall resulting from the removal of radiative effects of ice clouds correspond to the enhanced net condensation.The increases（decreases） in maximum rainfall caused by the exclusion of radiative effects of water clouds in the presence（absence） of radiative effects of ice clouds,or the removal of radiative effects of ice clouds in the presence（absence） of radiative effects of water clouds,correspond mainly to the enhancements（reductions） in net condensation.The mean rain rate is a product of rain intensity and fractional rainfall coverage.The radiation-induced difference in the mean rain rate is related to the difference in rain intensity.The radiation-induced difference in the maximum rain rate is associated with the difference in the fractional coverage of maximum rainfall.

The Value of Using Unofficial Measurements of Rainfall: The Dublin Storm and Flood of June 1963

Rainfall measurements are vital for the design of hydraulic structures, climate change studies, irrigation and land drainage works. The most important source of design rainfall data comes from convective storms. Accurate assessment of the storm rainfall requires a fairly dense network of raingauges. In 1963, such a storm took place over Dublin in Ireland. However, the existing raingauge network was insufficient to identify both the depth and pattern of rainfall. An appeal was made by Met Eireann for additional unofficial rainfall data. The result was remarkable in that the estimated maximum rainfall depth was found to be more than double the official value and that the resulting depth area analysis suggested a rainfall volume over a large area much bigger than the original isohyet map indicated. This result has huge implications for the estimation of maximum rainfall and dam safety assessment, especially in countries where the raingauge network has a low density. This paper first provides a description of the synoptic conditions that led to the storm, second an analysis of the rainfall data and how the unofficial measurements produced a very different depth area relationship;third, the social consequences of the resulting flood are described. Fourth, the storm is then placed in the context of other storms in the British Isles Finally the implications for rainfall measurement, gauge density and an example of how revised estimates of probable maximum precipitation (PMP) have been used to improve the safety and design standard of a flood detention dam are discussed.

Analysis of Rainfall Intensity-Duration-Frequency Relationship for Rwanda

Global atmospheric and oceanic perturbations and local weather variability induced factors highly alter the rainfall pattern of a region. Such factors result in extreme events of devastating nature to mankind. Rainfall Intensity Duration Frequency (IDF) is one of the most commonly used tools in water resources engineering particularly to identify design storm event of various magnitude, duration and return period simultaneously. In light of this, the present study is aimed at developing rainfall IDF relationship for entire Rwanda based on selected twenty six (26) rainfall gauging stations. The gauging stations have been selected based on reliable rainfall records representing the different geographical locations varying from 14 to 83 years of record length. Daily annual maximum rainfall data has been disaggregated into sub-daily values such as 0.5 hr, 1 hr, 3 hr, 6 hr and 12 hr and fitted to the probability distributions. Quantile estimation has been made for different return periods and best fit distribution is identified based on least square standard error of estimate. At-site and regional IDF parameters were computed and subsequent curves were established for different return period. The moment ratio diagram (MRD) and L-moment ratio diagram (LMRD) methods have been used to fit frequency distributions and identify homogeneous regions for observed 24-hr maximum annual rainfall. The rainfall stations have been divided into five homogeneous rainfall regions for all 26 stations. The results of present analysis can be used as useful information for future water resources development planning purposes.

Rainfall Forecasting Using Fourier Series

The need for accurate rainfall prediction is readily apparent when considering many benefits in which such information would provide for river control, reservoir operation, forestry interests, flood mitigation, etc.. Due to importance of rainfall in many aspects, studies on rainfall forecast have been conducted since a few decades ago. Although many methods have been introduced, all the researches describe the study as complex because it involves numerous variables and still need to be improved. Nowadays, there are various traditional techniques and mathematical models available, yet, there are no result on which method provide the most reliable estimation. AR （auto-regressive）, ARMA （auto-regressive moving average）, ARIMA （auto-regressive integrated moving average） and ANNs （artificial neural networks） were introduced as a useful and efficient tool for modeling and forecasting. The conventional time series provide reasonable accuracy but suffer from the assumptions of stationary and linearity. The concept of neurons was introduced first which then developed to ANNs with back propagation training algorithm. Although certain ANNs） models are equivalent to time series model, but it is limited to short term forecasting. This Paper presents a mathematical approach for rainfall forecasting for Iran on monthly basic. The model is trained for monthly rainfall forecasting and tested to evaluate the performance of the model. The result Shows reasonably good accuracy for monthly rainfall forecasting.

Analysis of Rainfall Dynamics in Conakry,Republic of Guinea

Observed rainfall data of the National Meteorological Service of Guinea (NMS) exhibit that synoptic station usually records the largest rainfall amount in Guinea. Only few studies have been done on this rainfall peak observed in Conakry. This work better analyses the atmospheric dynamics leading to rainfall particularity. Using NMS data from 1981 to 2010, the monthly contribution and mean seasonal cycle of each station has been done. These findings of the study show that between July and August (rainfall season peak), the coastline particularly Conakry records the largest amount of rainfall. Using Era Interim data for the common period (1981-2010), we also investigate the rainfall dynamics in the lower level (1000 hPa - 850 hPa) from precipitable water, divergence, and moisture flow transport. There is a west and southwest moisture flow transport explained by a strong moisture convergence in the coastal region (Lower-Guinea). Furthermore, values of precipitable water in the same region are found, in agreement with the high moisture flow transport gradient. These incoming flow (west and south-west) undergo a return by blocking’s Kakoulima range (foehn effect) and Fouta Djallon massif to initiate convection clouds on the Guinean coast. These processes enhance a convergence of moisture associated with orographic origin convection. This has an important effect by increasing the rainfall amount in Conakry.

利用短序列高密度台站资料推算暴雨重现期方法研究及应用

暴雨重现期是城市排水防涝设计的重要基础,通常基于长年代观测数据进行推算。但在无降水观测或观测时间较短的情况下,如何进行重现期推算和暴雨强度评估是目前亟需解决的科学问题。基于重庆市近14年高密度台站降水观测资料,建立各站逐年日降水极值抽样数据集,以“空间换时间”的思想,对日降水极值样本进行空间抽样,通过与国家级气象站长序列观测数据(>60 a)进行交叉检验,构建试验区目标点最佳百分位合成序列,该方法简称为空间抽样合成法(SBS)。通过重庆地区34个测站长年代观测资料计算重现期降水量“真值”与SBS、邻近点替换、克雷斯曼(Cressman)空间插值、年多个样法等推算结果进行对比检验,就平均而言,SBS的相对误差最小,其中含目标点样本的SBS相对误差最小为7.2%,邻近点替代法相对误差最大(13.2%),表明SBS可以较好地用于中国复杂地形的重庆地区,利用短序列高密度台站降水资料构建无有效降水观测资料目标点处的长序列极值降水样本,从而开展概率拟合优选及暴雨重现期推算。在对上述方法验证基础上,实现重庆地区2062个高密度气象观测站多年(50 a)一遇重现期降水量推算,提高了日尺度极端降水的空间精细化水平,结果能更好反映山区地形对降水的影响。SBS可以充分利用短序列高密度台站降水观测资料,实现区域内任意目标点重现期降水量推算。

基于未来降雨的水库实时优化调度研究

为了充分利用未来降雨信息指导水库调度,构建了以最大削峰为目标的水库实时调度模型,提出了一种考虑未来降雨信息的水库优化调度方法,基于水箱模型利用24 h降雨量预报信息预测入库流量并建立每个时段的泄洪指标求解模型。以山美水库防洪调度为例进行研究,与降雨启发信息优化调度方法进行比较,结果表明,此优化调度方法在目标函数上表现更好,与利用洪水预报的优化调度方法效果相近,能较好地解决来水不确定性的问题。

基于最大熵Copula方法的古黄河宿迁段流域月降雨量模拟

为了解决Copula函数方法在拟合过程中要先选择函数类型和多变量水文模拟中保留相关性的问题,基于最大熵原理(POME),直接构建Copula函数,而无需进行Copula函数类型的优选,简化了联合概率分布函数的拟合过程。以古黄河宿迁段流域的皂河站、金锁站和泗阳站3个雨量站点39年(1980~2018年)的月降雨量实测资料为研究对象,进行实例分析。通过建立不同站点间的降雨量联合分布,检验最大熵Copula方法的有效性,并利用Gibbs采样法对月降雨量进行随机模拟。结果表明,基于最大熵Copula方法能保留各站点降雨序列的统计特性,以及不同站点间的降雨相关性,验证了该方法的有效性,可为流域多站点间的降雨量相关性分析和水资源规划与利用提供参考。

变化环境下可能最大洪水计算研究

气候变化与下垫面变化前提下,多因素共同影响明显增加了流域可能最大洪水(PMF)估算难度。为此,提出一种集气候模式结果后处理、气候变化情景下相应可能最大暴雨(PMP)估算及土地利用/覆被变化方案设定、基流/前期影响雨量影响分析、基于相似性的PMP时空展布于一体的PMF计算模式,将其应用于怒江上游。结果表明,基流/前期影响雨量及暴雨时空分布不确定性是影响流域PMF的重要因素,气候与下垫面变化双重驱动对于PMF影响较大,且变幅随着变化程度增强而增大。

港区含尘污水厂设计处理时间研究

煤炭和矿石码头的含尘污水处理厂设计中,对于设计径流雨水量的处理时间取值决定污水厂处理规模的大小,而现行规范对于此值的选取并未做出规定。通过统计15个典型港口地区降雨量数据,从降雨次数和降雨量两个方面进行分析和对比。结果表明,各地区连续2 d有2 mm以上降雨的平均发生比例较大,尤其南方地区基本在50%以上;连续2 d有2 mm以上降雨的日降雨量之和超过多年最大日降雨量的最小值的平均发生比例不超过20%,而超过2 a一遇日降雨量的平均发生比例不超过4%。为保证污水厂能及时处理含尘污水、不发生污水外溢情况,建议计算径流雨水量时多年最大日降雨量的最小值H取设计重现期对应的降雨量,且重现期不小于2 a;同时污水厂的设计处理时间不应大于48 h。

The Influence of Climate Variability on the Watermelon Production in Zanzibar

Climate change and variability, has embarked societies in Zanzibar to rely on horticulture (i.e. watermelon production) as an adaptive measure due to an unpromising situation of commonly used agricultural yields. Currently, there is either no or scant information that describes the influence of climate changes and variability to watermelon production in Zanzibar. Thus, this study aimed to determine the influence of climate variability on the quantity of watermelon production in Zanzibar. The study used both primary and secondary datasets, which include the anecdotal information collected from interviewers’ responses from four districts of Unguja and Pemba, and climate parameters (rainfall, maximum and minimum temperature (Tmax and Tmin) acquired from Tanzania Meteorological Authority (TMA) at Zanzibar offices. Pearson correlation was used for analyzing the association between watermelon production and climate parameters, while paired t-test was applied to show the significance of the mean differences of watermelon and climate parameters for two periods of 2014-2017 and 2018-2021, respectively. Percentage changes were used to feature the extent to which the two investigated parameters affect each other. The anecdotal responses were sorted, calculated in monthly and seasonal averages, plotted and then analyzed. Results have shown a strong correlation (r = 0.8 at p ≤ 0.02, and r = 0.7) between watermelon production, Tmax and rainfall during OND, especially in Unguja, as well as Tmin during JJA (i.e. r = - 0.8 at p ≤ 0.02) in Pemba. Besides, results have shown the existence of significant differences between the means of watermelon production and climate parameter for the two stated periods, indicating that the climate parameters highly affects the watermelon production by either enhancing or declining the yields by 69% - 162% and 17% - 77%, respectively. Moreover, results have shown that respondents were aware that excess temperature intensity during dry periods can lead to high production costs due number of soil and other environmental factors. Besides the results have shown that OND seasonal rainfall and MAM Tmax had good association with watermelon production in Unguja while JJA Tmin declined the production in Pemba. Thus, the study concludes that seasonal variability of climate parameter has a significant influence on the watermelon production. The study calls for more studies on factors affecting watermelon production (e.g. soil characteristics, pest sides and manure), and recommends for climate based decision making on rain fed agricultural yields and routine monitoring of weather information.

基于城市下垫面产汇流视角的盱眙县极值雨型和最大径流关系分析

选取江苏省淮安市盱眙县为研究区,通过文献研究法、芝加哥雨型法及统计分析方法,对盱眙县极值降雨雨型和最大径流关系进行研究.结果表明:1957-2020年,年均降水量为1 015 mm,且呈波动上升趋势,主要集中在7-8月,占比40%;年均蒸发量最大值在6月,占比12.7%;1957-2020年,最大日降水量均值为45 mm,其中64年中最大日降水量为1970年7月27日的233.2 mm;在120 min模式雨型中,雨峰系数确定为0.4,降雨强度呈单峰型分布;年径流总量控制率从60%提高到95%,对应的设计降水量从16.3 mm提高到71.5 mm,且设计降水量的增速越快.

齐大山铁矿西帮地下水涌水模拟预测

齐大山铁矿西帮的降水和河流入渗补给、地表水径流等,会造成地下水流动的复杂性和不确定性;因此采用Visual MODFLOW Flex数值模拟软件预测不同频预期的最大降雨量和河流入渗补给作用下的第四系边坡的渗水量值,并建立响应关系。结果表明:在丰水期河流补给呈现稳定补给状态,主要补给项为降雨直接汇入,而降雨入渗对地层的补给比重随着降雨量增大持续增长,两者的线性拟合程度较高,经过分析计算得出拟合优度R2的数值为0.998。

翻斗式雨量传感器现场校准相关问题探讨

为了使雨量传感器现场校准方法更好地应用于实际工作,根据翻斗式雨量传感器的特点、现场校准的工作经验及实验数据,发现并分析了《自动气象站现场校准方法》的不足,并在此基础上提出了最大允许误差的表述方法应为相对误差,以及在传感器分辨力不同时应增加重复性测量次数两点修订意见,从而进一步完善翻斗式雨量传感器现场校准指标和方法,为改进其现场校准方法提供了依据。

用小时降雨资料估算降雨侵蚀力的方法

降雨侵蚀力是进行土壤流失量预报的基本因子,EI30是迄今得到广泛应用的定量指标,但它的计算需要降雨过程资料,使其推广应用受到很大限制。用自动气象观测提供的高精度等间隔降雨资料,代替降雨过程资料,是估算降雨侵蚀力指标的首选。国际上对此已有研究,发现有很大的地区差异性。为此,本文在水蚀严重的中国东部季风区选择5个代表站点,共456次降雨过程资料,建立了用60 min等间隔雨量资料估算次降雨侵蚀力的计算方法。研究结果表明:直接用60 min等间隔资料计算的降雨侵蚀力指标值,与用降雨过程资料计算的结果相比,降雨动能E差异较小,主要差异体现在最大30 min雨强I30上,由此导致降雨侵蚀力指标EI30的差异也十分明显。利用自动气象观测小时雨量资料计算降雨侵蚀力指标值,通过公式(EI30)bp=1.730(EI30)60转换,可以较精确地估算全国降雨侵蚀力,与用日、月和年降雨量资料的估算值相比,能够提高土壤侵蚀预报精度。

灾难性地震和降雨滑坡的体积与运动距离研究

为预测和评价灾难性滑坡的致灾机制,基于国内近年来地震和降雨诱发的灾难性滑坡资料,对地震和降雨滑坡的等价摩擦系数H/L、最大水平运动距离L、最大垂直运动距离H与滑坡体积V的关系进行分析。研究灾难性地震和降雨滑坡的远程运动特征以及不同规模滑坡最大水平运动和垂直运动的优势距离。研究结果表明,滑坡的H/L、L、H与V具有幂律关系,其中H/L与V具有负幂律关系,L、H与V具有正幂律关系。同一规模等级的地震和降雨诱发灾难性滑坡的水平和垂直运动距离不同。以H/L=0.42作为滑坡远程运动的标准,地震诱发的灾难性滑坡与滑坡远程运动的关系较小,而降雨诱发灾难性滑坡与滑坡的远程运动的关系较大。根据滑坡运动距离的累积分布表,以80%滑坡的运动距离所分布的范围,建立了滑坡不同规模等级的优势运动距离区间,同规模等级的地震滑坡和降雨滑坡在水平和垂直运动的优势距离区间上存在差异。灾难性滑坡的运程不仅受滑坡体积的控制还与其诱发机制相关,其研究成果可为由地震和降雨诱发的灾难性滑坡的致灾区域和致灾强度的预测和评价提供参考依据。