Recording Rain Gauges Research Articles

Isopluvial Analysis and Intensity Duration Frequency (IDF) Curves for different cities in India

Globally water resource management is becoming a priority for every Government. This is due to tremendous increase in population growth,urbanization, modern life style, increase in agricultural activities, industrialization etc. which is increasing the water demand day by day. This paper focuses on design storms studiesusing return period analysis technique (Isopluvial analysis) based on 129 well distributedSelf Recording Raingauge (SRRG) stations in the various climatic zones of India. The extreme rainfall values are taken for preparation of Isopluvial maps for return period of 2-year, 5- year, 10-year, 25-year, 50-year and 100-year at1-hour, 3-hour, 6-hour, 12-hour and 24-hour duration. Further, station wise Intensity Duration Frequency (IDF) curves are also prepared for 27 stations of the country. The Gumble distribution technique for extreme rainfall series is used for this study. Isopluvial maps & IDF curves are found very useful for Design engineers, hydrologists and hydraulic-consultants for the purpose of planning & designing of water resources related projects in the country forthe construction of any drainage network system, metro, road ways etc.and also, to some extend for the estimation of availability of water.
 

Cloudburst events observed over Uttarakhand during monsoon season 2017 and their analysis

Cloudburst is an extreme weather event characterised by the occurrence of a large amount of rainfall over a small area within a short span of time with a rainfall of 100 mm or more in one hour. It is responsible for flash flood, inundation of low lying areas and landslides in hills causing extensive damages to life and property. During monsoon season 2017 five number of cloudburst events are observed over Uttarakhand and analysed. Self Recording Rain Gauge (SRRG) and 15 minutes interval data from the newly installed General Packet Radio Service (GPRS) based Automatic Weather Station (AWS) are able to capture the cloudburst events over some areas in Uttarakhand. In this paper, an attempt has been made to find out the significant synoptic and thermodynamic conditions associated with the occurrence of the cloudburst events in Uttarakhand. These 5 cases of cloudburst events that are captured during the month of June, July and August 2017 in Uttarakhand are studied in detail. Synoptically, it is observed that the existence of trough at mean sea level from Punjab to head Bay of Bengal running close to Uttarakhand, the movement of Western Disturbance over north Pakistan and adjoining Jammu & Kashmir and existence of cyclonic circulation over north Rajasthan and neighbourhood are favourable conditions. Also, the presence of strong south-westerly wind flow from the Arabian Sea across West Rajasthan and Haryana on upper air charts are found during these events. Thermodynamically, the Convective Available Potential Energy (CAPE) is found to be high (more than 1100 J/Kg) during most of the cases and vertically integrated precipitable water content (PWC) is more than 55mm. The GPRS based AWS system can help in prediction of the cloud burst event over the specified location with a lead time upto half to one hour in association with radar products.

Rainfall Intensity Analysis for Synoptic Stations in Northern Nigeria

With the large inter-annual variability of rainfall in Northern Nigeria, a zone subject to frequent dry spells which often result in severe and widespread droughts, the need for intense study of rainfall and accurate forecast of rainfall intensity duration frequency (IDF) curves cannot be over emphasized. The Intensity Duration Frequency relationship is a mathematical relationship between the rainfall intensity and rainfall duration for given return periods. Using a subset of the network of fifteen continuous auto recording rain gauges available in Northern Nigeria, a total of seven different time durations ranging from 12 minutes to 24 hours were developed for return periods of 2, 5, 10, 25, 50 and 100 years. The maximum data series so obtained was fitted to Gumbel’s Extreme Value Type 1 distribution. Linear Regression Analysis was then used to obtain the intensity-duration relationships for the various locations from which Intensity-Duration Frequency (IDF) curves were generated using Microsoft Excel for various return periods.
 Keywords: Extreme rainfall, intensity, duration, frequency, Northern Nigeria

Intensity-duration-frequency curve derivation from different rain gauge records

Development of Intensity-Duration-Frequency (IDF) Curves is important for the design of various hydraulic structures such as culverts, dams, and stormwater drainage systems. In this paper, rainfall analyses are conducted to evaluate the effect of using rainfall records from different rain gauge types on IDF Curves construction. Rainfall data are collected from two recording rain gauges at Namman catchment in western Saudi Arabia. Using the available 13 years rainfall data of the two gauges, annual maxima rainfall series values are extracted and used for IDF curves computations. The rainfall gauge which is equipped with a siphon produced IDF curves with higher precipitation intensities in comparison with the other gauge. This indicates that the siphon mechanism plays an important role in decreasing the under-catchment amount of the tipping bucket gauges during heavy rainfall storms. The current study shows that the under-catchment amount of tipping-bucket rain gauges can have a significant impact on the IDF curves and the characteristics of the design storm. A correction relationship to adjust rain intensity data sets of recording rain gauges that are not furnished with siphons is proposed in this paper. The adjusted rainfall intensity values are utilized to construct reliable IDF curves.

Improved input to distributed hydrologic model in areas with sparse subdaily rainfall data using multivariate daily rainfall disaggregation

Abstract Flood forecasting relies on good quality of observed and forecasted rainfall. In Serbia, the recording rain gauge network is sparse and rainfall data mainly come from dense non-recording rain gauges. This is not beneficial for flood forecasting in smaller catchments and short-duration events, when hydrologic models operating on subdaily scale are applied. Moreover, differences in rainfall amounts from two types of gauges can be considerable, which is common in operational hydrological practice. This paper examines the possibility of including daily rainfall data from dense observation networks in flood forecasting based on subdaily data, using the extreme flood event in the Kolubara catchment in May 2014 as a case study. Daily rainfall from a dense observation network is disaggregated to hourly scale using the MuDRain multivariate disaggregation software. The disaggregation procedure results in well-reproduced rainfall dynamics and adjusts rainfall volume to the values from the non-recording gauges. The fully distributed wflow_hbv model, which is under development as a forecasting tool for the Kolubara catchment, is used for flood simulations with two alternative hourly rainfall data. The results show an improvement when the disaggregated rainfall from denser network is used, thus indicating the significance of better representation of rainfall temporal and spatial variability for flood forecasting.

Comprehensive evaluation of 3-hourly TRMM and half-hourly GPM-IMERG satellite precipitation products

ABSTRACTAccurate estimation of precipitation is crucial for crop yield assessment, flood and drought monitoring, and water structures management. Precipitation is subject to both temporal and spatial variability. While recording rain gauges support temporal resolution, they measure point rainfall and require dense network and application of interpolation techniques to provide spatial dimension. On the other hand, remote-sensing products cover regional and global spatial scales. Building upon the Tropical Rainfall Measuring Mission (TRMM) heritage, the Global Precipitation Measurement (GPM) mission is an international net of satellites that present the next-generation global observations of rain and snow at a spatial resolution of 0.1° × 0.1° with a half-hour temporal resolution. In this study, March–December 2014 3-hourly TRMM data (3B42V7) and half-hourly Integrated Multi-satellite Retrievals for GPM (IMERG) data are compared with the 3-hourly rain gauges data in Khorasan Razavi province, located in northwest of Iran. Coefficient of determination (R2), Bias, MBias, RBias, mean absolute error (MAE), root mean square error (RMSE) as well as probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) metrics were measured for validation purposes. The result showed that correlation between IMERG data and rain gauge rainfall data is higher than those of 3B42V7 data. In addition, the values of MBias, Bias, and RBias confirmed that both of 3B42V7 and IMERG underestimated rainfall over the study area, whereas MBias of IMERG was higher than 3B42V7. Furthermore, MAE and RMSE values of 3B42V7 and IMERG were similar while IMERG evaluation turned out a better correlation coefficient (r) and POD than 3B42V7. This study showed that IMERG generally had reasonable agreement with the gauge data.

Estimate of the (R)USLE rainfall erosivity factor from monthly precipitation data in mainland Spain

The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (R-factor) of the (R)USLE model in areas without good temporal data coverage. In mainland Spain, the Nature Conservation Institute (ICONA) determined the R-factor at few selected pluviographs, so simple estimates of the R-factor are definitely of great interest. The objectives of this study were: (1) to identify a readily available estimate of the R-factor for mainland Spain; (2) to discuss the applicability of a single (global) estimate based on analysis of regional results; (3) to evaluate the effect of record length on estimate precision and accuracy; and (4) to validate an available regression model developed by ICONA. Four estimators based on monthly precipitation were computed at 74 rainfall stations throughout mainland Spain. The regression analysis conducted at a global level clearly showed that modified Fournier index (MFI) ranked first among all assessed indexes. Applicability of this preliminary global model across mainland Spain was evaluated by analyzing regression results obtained at a regional level. It was found that three contiguous regions of eastern Spain (Catalonia, Valencian Community and Murcia) could have a different rainfall erosivity pattern, so a new regression analysis was conducted by dividing mainland Spain into two areas: Eastern Spain and plateau-lowland area. A comparative analysis concluded that the bi-areal regression model based on MFI for a 10-year record length provided a simple, precise and accurate estimate of the R-factor in mainland Spain. Finally, validation of the regression model proposed by ICONA showed that R-ICONA index overpredicted the R-factor by approximately 19%.

Diurnal Variations in Rainfall over Indian Region Using Self Recording Raingauge Data

Diurnal Variations in Rainfall over Indian Region Using Self Recording Raingauge Data

Frequency distributions of areal rainfall intensity and duration in western Saudi Arabia

In this study, rainfall analysis is carried out to investigate the areal rainfall characteristics of three major basins in western Saudi Arabia. The drainage area of study basins ranges from 395 to 3500 km2. Records of rainfall intensity and durations were collected from nine recording rain gauge located in these basins. The mean areal rainfall depth is determined and used to compute the mean areal rainfall intensity for all the recoded rainfall events. The data were also utilized to compute frequency distributions of areal rainfall intensity and duration. Exponential distributions are fitted for the areal rainfall intensity and durations. The fitted distributions are found in a good agreement with the observed frequencies.

Estimating the rainfall erosivity factor from monthly precipitation data in the Madrid Region (Spain)

Abstract The need for continuous recording rain gauges makes it difficult to determine the rainfall erosivity factor (Rfactor) of the Universal Soil Loss Equation in regions without good spatial and temporal data coverage. In particular, the R-factor is only known at 16 rain gauge stations in the Madrid Region (Spain). The objectives of this study were to identify a readily available estimate of the R-factor for the Madrid Region and to evaluate the effect of rainfall record length on estimate precision and accuracy. Five estimators based on monthly precipitation were considered: total annual rainfall (P), Fournier index (F), modified Fournier index (MFI), precipitation concentration index (PCI) and a regression equation provided by the Spanish Nature Conservation Institute (RICONA). Regression results from 8 calibration stations showed that MFI was the best estimator in terms of coefficient of determination and root mean squared error, closely followed by P. Analysis of the effect of record length indicated that little improvement was obtained for MFI and P over 5- year intervals. Finally, validation in 8 additional stations supported that the equation R = 1.05·MFI computed for a record length of 5 years provided a simple, precise and accurate estimate of the R-factor in the Madrid Region.

Characterising the space–time structure of rainfall in the Sahel with a view to estimating IDAF curves

Abstract. Intensity–duration–area–frequency (IDAF) curves are increasingly demanded for characterising the severity of storms and for designing hydraulic structures. Their computation requires inferring areal rainfall distributions over the range of space scales and timescales that are the most relevant for hydrological studies at catchment scale. In this study, IDAF curves are computed for the first time in West Africa, based on the data provided by the AMMA-CATCH Niger network, composed of 30 recording rain gauges having operated since 1990 over a 16 000 km2 area in south-western Niger. The IDAF curves are obtained by separately considering the time (intensity–duration–frequency, IDF) and space (areal reduction factor, ARF) components of the extreme rainfall distribution. Annual maximum intensities are extracted for resolutions between 1 and 24 h in time and from point (rain gauge) to 2500 km2 in space. The IDF model used is based on the concept of scale invariance (simple scaling) which allows the normalisation of the different temporal resolutions of maxima series to which a global generalised extreme value (GEV) is fitted. This parsimonious framework allows one to use the concept of dynamic scaling to describe the ARF. The results show that coupling a simple scaling in space and time with a dynamical scaling that relates to space and time allows one to satisfactorily model the effect of space–time aggregation on the distribution of extreme rainfall.

Large scale evaluation of single storm and short/long term erosivity index models

Rainfall erosivity of the Revised Universal Soil Loss Equation (RUSLE) is influenced by the type, amount, and intensity of storm. In this research, rainfall data from 18 recording rain gauge stations were collected and analyzed. Further, their single storm, daily, monthly, and annual erosion indices were calculated and estimated by different models. Duration of each rainfall was divided into 15 min intervals. Intensity and energy of each interval, maximum rainfall intensity of 30 min, total energy of each rainfall, and erosivity index of every single storm were calculated. Furthermore, Cooley's model for single storm was evaluated and its coefficients were estimated. For daily rainfall erosion index prediction, Richardson's model was assessed and its coefficients were also estimated. A new power model based on monthly rainfall was proposed in order to predict monthly rainfall erosion index. For the estimation of the annual rainfall erosion index, the Arnoldus model was evaluated and its coefficients were estimated. The coefficients for all equations were also determined using multiple regression. According to the calibrated Arnoldus model, an iso-rainfall erosion index map was drawn for the studied area consisting of 150 rain gauge information. The results indicated that models of Cooley, Richardson, Arnoldus, and the newly proposed model for monthly rainfall erosion index provide a reasonable agreement with the rainfall characteristics of the studied area.

Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada

Southern Ontario, Canada, has been impacted in recent years by many heavy rainfall and flooding events that have exceeded existing historical estimates of infrastructure design rainfall intensity–duration–frequency (IDF) values. These recent events and the limited number of short-duration recording raingauges have prompted the need to research the climatology of heavy rainfall events within the study area, review the existing design IDF methodologies, and evaluate alternative approaches to traditional point-based heavy rainfall IDF curves, such as regional IDF design values. The use of additional data and the regional frequency analysis methodology were explored for the study area, with the objective of validating identified clusters or homogeneous regions of extreme rainfall amounts through Ward's method. As the results illustrate, nine homogeneous regions were identified in Southern Ontario using the annual maximum series (AMS) for daily and 24-h rainfall data from climate and rate-of-rainfall or tipping bucket raingauge (TBRG) stations, respectively. In most cases, the generalized extreme value and logistic distributions were identified as the statistical distributions that provide the best fit for the 24-h and sub-daily rainfall data in the study area. A connection was observed between extreme rainfall variability, temporal scale of heavy rainfall events and location of each homogeneous region. Moreover, the analysis indicated that scaling factors cannot be used reliably to estimate sub-daily and sub-hourly values from 24- and 1-h data in Southern Ontario. Citation Paixao, E., Auld, H., Mirza, M.M.Q., Klaassen, J. & Shephard, M.W. (2011) Regionalization of heavy rainfall to improve climatic design values for infrastructure: case study in Southern Ontario, Canada. Hydrol. Sci. J. 56(7), 1067–1089.

Modeling precipitation of short duration by means of the modified Bartlett-Lewis rectangular pulse model

The objective of this work was to evaluate the mathematical modeling of rainfall of duration less than one hour using the modified Bartlett-Lewis model with six parameters. The data used were for the period October 1980 to December 2007, from recording rain gauges (pluviographs) at the meteorological station of Epagri, Urussanga, south of Santa Catarina (latitude 28.31° S, longitude 48.19 ° W). Based on simulations of series with 100 years of data it can be concluded that: the adjustment of the parameters of the modified Bartlett-Lewis model enables the simulation of rain at intervals as small as 5 minutes of duration, preserving the statistical properties of precipitation over various intervals of aggregation in time. In general there was a tendency toward overestimation of the probability of dry periods and underestimation of the covariance for intervals of 24 hours, especially in summer. The total annual rainfall simulated for all time intervals examined remains within the confidence interval of 95%.

Flood Inundation Modeling Using Nakagami-m Distribution Based GIUH for a Partially Gauged Catchment

Flood inundation extent is highly dependent on intensive rainfall and topography of floodplain. This paper presents a study to develop a flood inundation model for partially gauged upper Ganga catchment. For design flood computations, 100-year return period of 1 h duration rainfall is adopted. This is obtained by intensity duration frequency (IDF) relationship based on Self Recording Rain Gauge (SRRG) data of the study area. The SCS-CN method is used for rainfall excess computations. The Nakagami-m distribution has been used to compute Geomorphological Instantaneous Unit Hydrograph (GIUH) of different sub-catchments of upper Ganga river system because of non-availability of observed hydrograph. Routing of the hydrograph has been done by the Kinematic Wave (KW) approach. KW equations have been solved through Preissmann implicit method. The most sensitive KW parameters (i.e. overland roughness and channel roughness) have been estimated for a stretch on river Bhagirathi, a tributary of river Ganga. Nakagami-m distribution based GIUHs have been fed at the upper (i.e. input to the proposed model) as well as at downstream point (i.e. output to the proposed model) of that river stretch. Consequently, KW parameters have been calibrated by comparing the computed hydrograph with output hydrograph. Validation of estimated KW parameters has been carried out in the catchment of river Alaknanda which is another significant tributary of river Ganga. Thereafter, adopted KW parameters have been applied to calculate the design flood peak at the outlet of study area i.e. downstream of Haridwar city. Computations of overtopping water above the natural levees downstream of Haridwar city have been carried out considering the levee as broad crested weir. Topographic features of the floodplain have been obtained from freely available Shuttle Radar Topography Mission (SRTM) data. Finally, extents of submerged areas in different flood hours corresponding to design rainfall have been developed by ArcGIS 9.2 software.

Characteristic features of hourly rainfall in India

AbstractHourly rainfall data recorded at 72 Self Recording Raingauge Stations (SRRG) for the period 1969–2006 are utilized to study the characteristic features of hourly rainfall and diurnal variations of rainfall in India. Temporal changes in the short duration (less than 12 h) rainfall extremes are examined. Time distribution of a heavy rain spell of 24 h duration, which is an important component in water resources management and flood control studies, is analysed. Different aspects of hourly rainfall such as, average number of rain hours in a year, empirical probability distribution functions have also been examined. Analysis indicates, many stations in India have recorded more than 10 cm of rainfall in an hour's duration. Such stations are located along the west coast, foothills of Himalayas and along the tracks of monsoon disturbances. Extreme rainfall events of various duration (3–12 h) show increasing trends, significant at 5% level, at many stations located in central India and peninsular India except for southern part of west coast. Time distribution of hourly rainfall shows that, on average, 25% of the daily rainfall can be received in just 3 h, while 80% can occur in 12 h during the heavy rain spells of 24‐h duration. Copyright © 2011 Royal Meteorological Society

Sediment Export from a Highway Construction Site in Central North Carolina

Sediment export and turbid runoff from active construction sites continue to be a source of impairment to surface water resources. Few studies have been published that include monitoring data from construction sites, particularly highway construction sites. In this study, water quality monitoring of runoff originating from three sections of a highway construction corridor was conducted during a 4.5-year period. Two unnamed tributaries, referred to as Tilly and Ellery for this study, were monitored at two locations downstream of the highway corridor, and one tributary, referred to as King's Mill, was monitored upstream and downstream of the highway corridor. At each station, discharge was continuously monitored and flow-proportional samples were collected. Samples were analyzed for total suspended solids, total solids, and turbidity. A recording raingauge was also maintained at one of the highway monitoring stations. Monitoring data at all stations documented increased sediment export and turbidity levels during the construction period as compared to the pre- and post-construction periods. During construction, sediment export rates ranged from 2.7 to 17.7 Mg ha-1 year-1, while mean turbidity levels ranged from 466 to 1,607 NTU for the five stations downstream of the highway corridor. For the station with the greatest sediment export, about 32% of the export occurred during two back-to-back tropical storms. At this time, one section of the highway was particularly susceptible to erosion because more than 6 m of fill material had recently been added to bring the road surface to near grade and vegetation had not yet been established. Increases in sediment export and turbidity at the other four downstream stations during highway construction were less pronounced. Mean turbidity levels during construction at all downstream stations were greater than 50 NTU. Post-construction mean turbidity levels were much less than during construction but were still greater than pre-construction at four of the five stations. Post-construction turbidity levels on the King's Mill tributary downstream of the highway were not significantly different from upstream.

Scale Interactions in Radar Rainfall Estimation Uncertainty

This study formulates an experimental strategy that couples rainfall observations from a locally deployed mobile X-band dual polarization radar with recording rain gauge measurements to create an error assessment of the spatio-temporal variability of high-resolution gridded rainfall fields. We discuss the trade-offs and values in the radar-rainfall uncertainty associated with different measurement resolutions. Overall, we found that radar measurement errors naturally decrease with averaging in space and time, but there is a generally negative value associated with the increase in spatial scale from 300 m to 5 km. Spatial averaging of radar rainfall increased the probability of detection slightly by 4%. However the decrease in relative root-mean-squared error (R-RMSE) was negligible as the false alarm rate increased by 10% and the Heidke skill score reduced by 16%. In terms of reducing measurement uncertainty, there was greater overall value by averaging temporally up to 60 min than averaging spatially to ...

Development of isopluvial map using L-moment approach for Tehri-Garhwal Himalaya

Estimation of design rainfall intensity is crucial for design and planning of water resources engineering projects. The intent of the present study is to develop regional IDF curves for Tehri-Garhwal Himalayan region in India, wherein numbers of hydropower projects are in planning and execution stage. Self Recording Rain Gauge (SRRG) stations are generally not so frequent in the project locations. Under this situation, the engineers are forced to use regional intensity duration frequency (IDF) curves. Under this study, four stations viz. Tehri M.T.Lab, Mukhim, Pilkhi and Dhuttu were available with SRRG data. These data are used to develop the regional IDF curve for entire Tehri-Garwal region. After selection of the most intensive storms, return periods has been determined using regionalized L-moment method. After developing IDF curves for above four raingauge stations, Thiessen Ploygon method is applied to find out average IDF curve. To show the spatial variability, Isopluvial maps have been generated using ArcGIS and a relation equation has been developed.

Recent trends in the Central and Western Sahel rainfall regime (1990–2007)

One motivation for setting up the CATCH ( Couplage de l’Atmosphère Tropicale et du Cycle Hydrologique ) project at the end of the 1990s, was to contribute to documenting the Sahelian rainfall variability at the interannual scale and to provide a fine monitoring of possible long-term trends of the rainfall regime. This paper is a first attempt at characterising the Sahelian rainfall regime of the two last decades (1990–2007) by comparison to the rainfall regime of the previous decades, namely the 20-year wet period 1950–1969 and the 20-year dry period 1970–1989. While the rainfall deficit remained unabated in the Western Sahel (1990–2007 mean equal to the 1970–1989 mean, both being lower than the 1950–1969 mean), the Central Sahel progressively recorded wetter years from the end of the 1990s, but this recovery is limited (1990–2007 average larger by 10% than the 1970–1989 average, but still lower than the 1950–1989 average). There are also significant differences between the Western Sahel and the Central Sahel when looking at the interannual variability pattern and at the seasonal cycle. The low-frequency rainfall patterns are similar between the Western Sahel and the Central Sahel, but the interannual year-to-year variability is weakly related to each other. In the Central Sahel, the major modification of the seasonal cycle in the most recent decades was the disappearance of the well marked August peak observed during the wet period. In the Western Sahel the rainfall deficit is more or less evenly distributed all along the rainy season. The second part of the paper makes use of the CATCH-Niger recording rain gauge network in order to compare several ways of defining rainy events. The statistical properties of these various populations of rainy events are compared. It is shown that a simple CPP model allows for retrieving the statistical characteristics of point rainy events from daily rainfall series. It is also confirmed that in this area, the interannual rainfall variability is primarily linked to the year-to-year fluctuation of the number of large mesoscale rainfall events.