Evaluation of rain gauge network in arid regions using geostatistical approach: case study in northern Oman

A geostatistical approach based on ordinary kriging is presented for the evaluation and the augmentation of an existing rain gauge network. The evaluation is based on estimating the percentage of the area that achieves a targeted level of acceptable accuracy. The variances of kriging estimation erros at un-gauged locations were assumed to be normally distributed. Kriging estimation erros with a probability that equals to or exceeds a given threshold value of acceptance probability were assumed to have satisfactory accuracies. The percentage of the area that achieved the targeted probability of acceptance is delineated and used to judge the overall performance of the existing rain gauge network. A study area in northern Oman located in Sohar governorate is selected as the pilot case. The area has 34 rain gauges and it is characterized by a terrain surface that varies from coastal plain to mountains. For a threshold value of 0.85, and 0.90 of acceptance probability, the existing network achieved area of acceptable probability of 88.71 and 77.72 %, respectively. For a success criterion of 80 %, the existing rain gauge network indicated acceptable performance for acceptance probability threshold of 0.85 and inadequate performance is noticed in the case of probability threshold of 0.90, which necessitated further network augmentation. A sequential algorithm for ranking and prioritization of the existing rain gauges is used to classify the existing rain gauges into base and non-base rain gauges. The base rain gauge network for mean annual rainfall comprised about 29 of the existing rain gauges. The identified non-base rain gauges were sequentially relocated to achieve higher levels of percentage of area with acceptable accuracy. The percentage of area with acceptable accuracy increased from 88.71 % for the original rain gauge network to about 94.51 % for the augmented network by adding four rain gages at probability acceptance threshold of 0.85. It also increased from 77.72 % for the existing network to 90.50 % for the augmented rain gauge network at acceptance threshold of 0.9.     

Analysis of the 1 November 2015 heavy rainfall episode in Algarve by using weather radar and rain gauge data

The trigger for the study presented in this paper was the extreme rain event of 1 November 2015 in Algarve region. The main objective was the analysis and improvement of the precipitation field using a radar–rain gauge merging method. Ordinary kriging with radar-based error correction has been applied to hourly values of precipitation from both sensors. The merging technique allowed keeping the better radar spatial pattern, being the respective estimates corrected by the rain gauges observations. The procedure led to a reduction in the errors of the precipitation estimates, evaluated by cross-validation, when compared to univariate interpolation of rain gauge observation or radar rain product. Finally, some discussion is also added on the problematic of flooding in urban areas, especially those with absent or deficient urban planning.     

Bias adjustment of satellite-based precipitation estimation using artificial neural networks-cloud classification system over Saudi Arabia

Precipitation is a key input variable for hydrological and climate studies. Rain gauges can provide reliable precipitation measurements at a point of observations. However, the uncertainty of rain measurements increases when a rain gauge network is sparse. Satellite-based precipitation estimations SPEs appear to be an alternative source of measurements for regions with limited rain gauges. However, the systematic bias from satellite precipitation estimation should be estimated and adjusted. In this study, a method of removing the bias from the precipitation estimation from remotely sensed information using artificial neural networks-cloud classification system (PERSIANN-CCS) over a region where the rain gauge is sparse is investigated. The method consists of monthly empirical quantile mapping of gauge and satellite measurements over several climate zones as well as inverse-weighted distance for the interpolation of gauge measurements. Seven years (2010–2016) of daily precipitation estimation from PERSIANN-CCS was used to test and adjust the bias of estimation over Saudi Arabia. The first 6 years (2010–2015) are used for calibration, while 1 year (2016) is used for validation. The results show that the mean yearly bias is reduced by 90%, and the yearly root mean square error is reduced by 68% during the validation year. The experimental results confirm that the proposed method can effectively adjust the bias of satellite-based precipitation estimations.     

Analysis of the 1 November 2015 heavy rainfall episode in Algarve by using weather radar and rain gauge data

The trigger for the study presented in this paper was the extreme rain event of 1 November 2015 in Algarve region. The main objective was the analysis and improvement of the precipitation field using a radar–rain gauge merging method. Ordinary kriging with radar-based error correction has been applied to hourly values of precipitation from both sensors. The merging technique allowed keeping the better radar spatial pattern, being the respective estimates corrected by the rain gauges observations. The procedure led to a reduction in the errors of the precipitation estimates, evaluated by cross-validation, when compared to univariate interpolation of rain gauge observation or radar rain product. Finally, some discussion is also added on the problematic of flooding in urban areas, especially those with absent or deficient urban planning.

     

中国大陆流域分区TRMM降水质量评价

根据中国境内2 257个气象站点1998-2013年逐日降水资料,结合流域分区,采用探测准确性、相关系数以及相对误差等指标,对热带降水测量（TRMM）降水精度和一致性进行系统评价。结果表明:① TRMM日降水准确性从东南沿海向西北内陆递减;② 气象站点年均降水日数显著大于TRMM年均降水日数;③ 西北片区以外气象站点降水量和TRMM降水量在月尺度和年尺度上均具有较好的相关关系;④ 各流域年均TRMM面降水量均高于气象站点面降水量,且TRMM面降水量相对误差雨季较小,枯季较大;⑤ 各流域TRMM面降水量与气象站点面降水量演变趋势基本一致,南方各流域年降水量均呈减少趋势,北方各流域年降水量均呈增加趋势,全国尺度上年降水量呈微弱的减少趋势。     

Inconsistency in rainfall characteristics estimated from records of different rain gauges

The goal of this work is to assess the effect of utilizing different types of tipping bucket rain gauges in investigating rainfall characteristics. A dual tipping bucket (TB) rain gauge station is installed in the upper catchment of Numan basin in Saudi Arabia. The main difference between the two gauges is that the Hydrological Services (HS) gauge is equipped with a siphon tube which reduces undercatchment particularly during heavy rainfall. Records of both gauges for the period 2006 to 2013 are collected, analyzed, and compared, focusing on the characteristics of rainfall events as well as rainfall temporal variability. The HS gauge recorded higher values of total rainfall depth compared to the Texas Electronics (TEMM) gauge. For the individual storms as well as the 5-min rainfall, HS gauge also reported higher mean rainfall depths. Regarding temporal characteristics of reported rainfall, no significant variations are observed between the values of storm duration of the two gauges. The TEMM gauge has the advantage of recoding more storms with depth less than 1 mm. The current study suggests the use of a corrective factor for rainfall record of the TEMM gauge.     

基于GNSS技术的高速公路边坡自动化监测系统

为探究基于GNSS监测站的高速公路边坡自动化监测系统的实际作用,本文以重庆巴南至綦江高速公路YQTJ5标青年互通K69+080段为依托进行研究。首先,基于LZMR02-GNSS接收机和FS-YL雨量计自主开发北斗+安全监测云平台,能够实时管理和分析现场布置的GNSS地表位移监测站和深层位移监测孔,监测结果表明该坡体已出现局部垮塌及开裂等不稳定现象并且迅速发出预警到相关部门单位;随后,基于传递系数法计算该边坡的剩余下滑力并且采用Geo5有限元软件进行数值模拟,其结果均验证了该监测系统的准确性。因此,建立高速公路边坡自动化监测系统不仅能解决常规人工监测边坡的不足,也能保证监测数据的时效性,为未来智能化监测边坡提供了一定的参考价值。     

Examining the rainfall–topography relationship using non-stationary modelling technique in semi-arid Aseer region,Saudi Arabia

The mountainous region of Aseer, corresponding to the Afromontane phytogeographic region, is an eco-sensitive zone and has complex relationship between topography and rainfall. The region is located inland of the red sea escarpment edge in the west. Therefore, rainfall can occur during any month of the year in the mountain of the high Aseer region when moist air forces up the escarpment from the red sea. Monitoring the rainfall data and its topographical elevation variable in Aseer region is an essential requirement for feasible and accurate rainfall-based data for different applications, such as hydrological and ecological resource management in rugged terrain and remote areas. The relationship of elevation and rainfall are spatially non-stationary, non-linear, scale dependent, and often modelled by conventional regression models. Therefore, a local modelling technique, geographically weighted regression (GWR), was applied to deal with non-stationary, non-linear, scale-dependent problems. The GWR using topoclimatic data (elevation and rainfall) to analyse the cumulative rainfall data for rainy months (March to June) of the 4 years estimated from CHIRPS (Climate Hazards Group InfraRed Precipitation with Stations) product for Aseer region. The bandwidth (scale-size) of the Aseer region rainfall–elevation relationship has stabilised at round off 12 km. By selecting the suitable bandwidth, the spatial pattern of the rainfall–elevation relationship was significantly enhanced by using the GWR than the traditional ordinary least squares (OLS) regression model. GWR local modelling techniques estimated well in terms of accuracy, predictive power and decreased residual autocorrelation. Additionally, GWR assesses the significance of local statistic at each location and identified the location of spatial clusters with local regression coefficients significantly improved as compared with global OLS model, thereby highlighting local variations. Therefore, the GWR, local modelling approach managed to produce more accurate estimates by taking into account local characteristics.     

在役输油气管道沿线滑坡灾害监测预警技术及应用

滑坡灾害是浅埋输油气管道的主要风险源之一,监测预警是管道滑坡风险控制的重要手段。管道滑坡灾害的监测预警需要滑坡体和管道的联合监测,注重管体轴向应变监测。为获得管道轴向应变的准确值,每截面至少需要布置3个应变计。推导了已知截面上3点、9点、12点钟位置应力时,管体监测截面上任意点应力的计算方法;探讨了基于材料强度破坏的管道预警阈值的确定方法。汶川地震期间,在兰成渝成品油管道羊木山滑坡获得了成功应用,为管道滑坡灾害监测预警的推广提供了借鉴。     

Satellite-based rainfall estimation and discharge measurement of Middle Indus River,Pakistan

The impacts of floods and droughts are intensified by climate change, lack of preparedness, and coordination. The average rainfall in study area is ranging from 200 to 400 mm per year. Rain gauge generally provides very accurate measurement of point rain rates and the amounts of rainfall but due to scarcity of the gauge locations provides very general information of the area on regional scale. Recognizing these practical limitations, it is essential to use remote sensing techniques for measuring the quantity of rainfall in the Middle Indus. In this research, Tropical Rainfall Measuring Mission (TRMM) estimation can be used as a proxy for the magnitude of rainfall estimates from classical methods (rain gauge), quantity, and its spatial distribution for Middle Indus river basin. In order to use TRMM satellite data for discharge measurement, its accuracy is determined by statistically comparing it with in situ gauged data on daily and monthly bases. The daily R ² value (0.42) is significantly lower than monthly R ² value (0.82), probably due to the time of summation of TRMM 3-hourly precipitation data into daily estimates. Daily TRMM data from 2003 to 2012 was used as input forcing in Soil and Water Assessment Tool (SWAT) hydrological model along with other input parameters. The calibration and validation results of SWAT model give R ² = 0.72 and 0.73 and Nash-Sutcliffe coefficient of efficiency = 0.69 and 0.65, respectively. Daily and monthly comparison graphs are generated on the basis of model discharge output and observed data.     

多源降雨信息质量评估技术

多源降雨信息质量评估遇到的基本问题是各类降雨信息的空间特征不同,信息采集传输的时间频次不同和降雨真值不明。本文在地面站雨量为点降雨真值、经地面雨量站校正后的雷达观测产品反映了降雨真值的空间分布等假定基础上,提出了单点雨量、区域点雨量、面雨量、降雨空间分布和洪水预报系统产品等5个层次的多源降雨信息质量评估体系和技术。     

Use of artificial neural network for spatial rainfall analysis

In the present study, the precipitation data measured at 23 rain gauge stations over the Achaia County, Greece, were used to estimate the spatial distribution of the mean annual precipitation values over a specific catchment area. The objective of this work was achieved by programming an Artificial Neural Network (ANN) that uses the feed-forward back-propagation algorithm as an alternative interpolating technique. A Geographic Information System (GIS) was utilized to process the data derived by the ANN and to create a continuous surface that represented the spatial mean annual precipitation distribution. The ANN introduced an optimization procedure that was implemented during training, adjusting the hidden number of neurons and the convergence of the ANN in order to select the best network architecture. The performance of the ANN was evaluated using three standard statistical evaluation criteria applied to the study area and showed good performance. The outcomes were also compared with the results obtained from a previous study in the area of research which used a linear regression analysis for the estimation of the mean annual precipitation values giving more accurate results. The information and knowledge gained from the present study could improve the accuracy of analysis concerning hydrology and hydrogeological models, ground water studies, flood related applications and climate analysis studies.     

考虑有雨无雨辨识的多源降水融合方法

多源降水融合是精准估计降水时空分布的重要途径,多聚焦降水量或降水强度的误差订正,对短历时降水雨区辨识的重视不足。提出考虑有雨无雨辨识的多源降水融合框架,耦合地理加权逻辑回归与地理加权回归模型,构建兼顾雨区辨识及雨量估计的降水融合方法,并应用于汉江流域MSWEP V2.1与地面站网观测日降水融合。结果表明：所提方法成功再现有雨无雨空间格局并刻画了降水中心,整体强化了MSWEP V2.1对地面降水的表征能力,降低误报率和误报降水量的幅度超过了60%,提高临界成功指数和Kling-Gupta效率系数达40%以上;较降水空间插值数据,削减误报降水量并提升Kling-Gupta效率系数高于10%;另外,较参考数据,降水融合改善强降水事件(雨强≥50 mm/d)分辨精度的增益不低于60%。所提方法有效改善了降水估计效果,为多源降水融合提供了新思路。     

Spatially distributed rainfall information and its potential for regional landslide early warning systems

Crucial to most landslide early warning system (EWS) is the precise prediction of rainfall in space and time. Researchers are aware of the importance of the spatial variability of rainfall in landslide studies. Commonly, however, it is neglected by implementing simplified approaches (e.g. representative rain gauges for an entire area). With spatially differentiated rainfall information, real-time comparison with rainfall thresholds or the implementation in process-based approaches might form the basis for improved landslide warnings. This study suggests an automated workflow from the hourly, web-based collection of rain gauge data to the generation of spatially differentiated rainfall predictions based on deterministic and geostatistical methods. With kriging usually being a labour-intensive, manual task, a simplified variogram modelling routine was applied for the automated processing of up-to-date point information data. Validation showed quite satisfactory results, yet it also revealed the drawbacks that are associated with univariate geostatistical interpolation techniques which solely rely on rain gauges (e.g. smoothing of data, difficulties in resolving small-scale, highly intermittent rainfall). In the perspective, the potential use of citizen scientific data is highlighted for the improvement of studies on landslide EWS.     

三种JDZ型翻斗式雨量计性能比对实验研究

在我国,JDZ系列翻斗式雨量计已广泛用于降雨量的观测。为了掌握JDZ系列雨量计测量降雨的精度和可靠性,以三种JDZ型翻斗式雨量计(JDZ02、JDZ05和JDZ10)为研究对象,基于一套智能化的雨量计率定系统开展室内性能比对实验。结果表明:(1)以小雨强0.4mm·min^-1作为零误差参考雨强,JDZ02在小于2mm·min^-1时的误差在-4%以内,JDZ05在小于4mm·min^-1时的误差在-4%以内,JDZ10在小于6mm·min^-1时的误差在-4%以内。(2)在雨强-总误差的拟合关系中,二次多项式拟合的效果最好,线性拟合的效果次之,幂函数拟合的效果最差,故建议采用雨强-误差的二次多项式关系订正JDZ系列雨量计监测的降雨数据。(3)左右翻斗水量过程线可以精细刻画翻斗内水量动态变化,判断出翻斗式雨量计的翻斗左右平衡性能,并可计算出翻斗式雨量计动态率定过程中的误差变化。     

宁德市降水量异常点剔除的影响分析

发现异常点是对逐时降水资料质量控制的有效方法,但简单的剔除未修正的异常点必然会影响其周围一定范围内降水量的空间变化。本文提出综合评分法定量的分析不同时段不同异常监测点被剔除后对降水量变化幅度的影响,探讨剔除区域异常点后降水量的时空变化分布特征。对宁德市降水资料进行实例验证,分析结果表明:在相邻站点数大于12个、相邻站点最近距离小于3km、相邻站点平均监测值大于6mm时,其降水量变化幅度相对较小,可剔除异常点。综合考虑三个相邻站点指标的综合分析可以显著表现不同时段不同监测站点降水量空间变化的地带性分布,在宁德市西北和东南区域出现高变化幅度站点的概率最高,呈现出高变化幅度站点多、分布范围广特点;在其东北区域监测站点分布不均匀,降水高变化幅度站点易受逐时降水量大小影响,呈现出小雨大范围、大雨小范围分布;在其西南和中部区域监测站点分布密集,出现高变化幅度站点的可能性最小。因此,综合分析可剔除区域异常点对降水量空间变化的影响特征,确定对降水量变化幅度影响最小的监测站点,有效提高了降水资料的质量控制水平。     

What has geography got to do with it? Using GWR to explore place-specific associations with prenatal care utilization

We use a geographically weighted regression (GWR) approach to examine how the relationships between a set of predictors and prenatal care vary across the continental US. At its most fundamental, GWR is an exploratory technique that can facilitate the identification of areas with low prenatal care utilization and help better understand which predictors are associated with prenatal care at specific locations. Our work complements existing prenatal care research in providing an ecological, place-sensitive analysis. We found that the percent of the population who was uninsured was positively associated with the percent of women receiving late or no prenatal care in the global model. The GWR map not only confirmed, but also demonstrated the spatial varying association. Additionally, we found that the number of Ob-Gyn doctors per 100,000 females of childbearing age in a county was associated with the percentage of women receiving late or no prenatal care, and that a higher value of female disadvantage is associated with higher percentages of late or no prenatal care. GWR offers a more nuanced examination of prenatal care and provides empirical evidence in support of locally tailored health policy formation and program implementation, which may improve program effectiveness.     

黄土地区小流域降雨空间变化特征分析

利用黄土地区雨量站网较密,控制条件较好的小流域资料,统计分析了5min、15min、30min、60min时段降雨及次降雨空间变化的点面关系、频率特征及结构特征,研究了时段降雨分布同次降雨分布的内在联系,为进一步在产流模拟计算中的应用提供了基础。     

The reliability of rainfall data from a volunteer observer network in the Central United States

Summer weekly rainfall data collected by approximately 120 untrained volunteers (mainly farmers) using unofficial gauges in McLean County, Illinois, reveal unambiguous mesoscale patterns. The volunteers collected rainfall data for the County Extension Service as part of an ongoing project spanning many years. All volunteers used the same clear plastic, funnel shaped gauge that could measure up to 140 mm of rain. We found few problems of rainfall distribution, and correlation decay with distance was compatible with decay rates reported elsewhere. Yet local variations in rain day frequencies suggest variable thresholds in the reporting of light rainfalls, and recurrent seasonal patterns of rain day frequency and total rainfall possibly imply data problems or local control. But the large number of sites precludes random observer bias as a factor. Our analysis illustrates that climatologists can safely utilize volunteer observers for research.     

雨量站网布设对水文模型不确定性影响的比较

雨量站网布设会影响径流模拟精度,研究不同雨量站密度和空间分布的径流响应规律对提高径流模拟精度和减小不确定性具有重要意义。应用新安江模型和HBV（Hydrologiska Fyrans Vattenbalans）模型,以湘江流域为研究对象,采用贝叶斯方法比较分析在不同雨量站密度及空间分布下径流模拟的不确定性。结果表明:增加雨量站密度可以降低面雨量的估计误差,使模型在不同的雨量站空间分布下具有较高的模拟精度;通过优化雨量站空间分布,可以减小雨量站网布设导致的模型不确定性,从而提高径流模拟精度;在相同的降雨输入和参数采样方法下,新安江模型和HBV模型对降雨输入导致的不确定性响应规律具有相似性,但是本研究结果显示在湘江流域新安江模型的模拟精度更高,而HBV模型的不确定性更大。