Rain Series Research Articles

Comparing the hydrological performance of blue green infrastructure design strategies in urban/semi-urban catchments for stormwater management

ABSTRACT Blue green infrastructure (BGI), in recent decades, have been increasingly recognized as robust stormwater control measures to reduce urban flooding, promote infiltration, and restore a catchment's flow to its pre-development stage. However, studies comparing the hydrological benefits of BGI alternatives at catchment scale are often limited to single catchment or single/few BGI options scaled over a catchment. This study designed a set of BGI alternatives as a combination of different BGI facilities in terms of the following: (a) spatial distribution scale (end-of-pipe vs. decentralized) and (b) naturalness scale (less engineered vs. more engineered), in three different urban catchments representing an inner city, a residential suburb, and a new urban housing. In addition, their hydrological performances were compared. A 10-year return period design rain and a continuous rain series of 11 years were modelled for each BGI alternative using the computer model (stormwater management model). It was observed that in most catchments, decentralized alternatives (both engineered and natural) showed better potential to reduce the magnitude and frequency of flooding than centralized measures. Similarly, the tested decentralized natural, less engineered alternatives showed higher potential to increase infiltration than the decentralized engineered alternatives in all three catchments. Meanwhile, infiltration-based BGI alternatives showed similar potential to mimic pre-development flow as other decentralized BGI alternatives.

Compilation method of a catalogue of reasonable worst-case rainfall series for flash flood simulations of short, convective rainstorms

In this study, a categorisation method was developed and applied to identify, select and rank reasonable worst-case rainfall storm events with time-series resolution of one minute and duration of up to one hour. The method yields a catalogue of 24 reasonable worst-case rainfall series, i.e. potentially catastrophic events that could be used for safe-to-fail flash flood model scenarios, thus encouraging the testing of critical infrastructure and pedestrian safety for people trapped in floods. The identified 24 events were shown to be considerably more extreme than corresponding design storms, with a return interval of 100 years. In the selection of the extremes, special care was taken to consider different hazard attributes, which are associated with intrinsically different observed hyetograph shapes, including rectangular, short and long triangle, and double peak shape categories. Hydrodynamic simulations were carried out using the 2D robust shallow water model hms++ to quantify the flooding impact of the 24 rainfall scenarios in a small urbanised catchment, which enabled the ranking of the scenarios based on different hazard attributes. Overall, the rectangular and long-triangle events showed the highest total discharge, and the rectangular events comprise both the longest duration for hazard velocity and deep flooding. The long-triangle events presented the highest peak discharge and peak water depths. The short-triangle ones showed the highest flashiness (shortest time to peak), whereas the double peak events yielded the longest time to peak. The ranking emphasised the importance of the hyetograph shape characteristics of extreme storms and which needs to be taken into account in flash flood management. The novel categorisation method is easily transferable to other regions, if high-resolution rain series are available.

Comparative Study of Worst Month Rain Rate and Attenuation Statistics for Satellite Links in Nigeria

AbstractThis study aims to characterize the dynamic trend of the worst case scenario of rain rate and attenuation for satellite links applications in Nigeria. Rain rate data for four locations (Akure, Jos, Ikeja, and Port Harcourt) were obtained from the Tropospheric Data Acquisition Network at the Centre for Atmospheric Research, NASRDA at an integration time of 5 min from January 2013 to December 2014. The statistics of time series of worst month rain induced attenuation were computed using the method of Synthetic Storm Technique. The International Telecommunication Union model was found to overestimate the Q‐factor in Akure, Port Harcourt, and Ikeja by 34%, 115%, and 50%, respectively while a 25% underestimation was observed in Jos. The results obtained in this study will be useful for location based link design in tropical Nigeria to reduce the uncertainty of specification of design for communication links.

Efficient job list creation for long-term statistical modelling of combined sewer overflows.

The modelling of urban drainage systems is an important aspect of their design process and long-term statistical modelling using historical rain series is commonly used. The objective of this study is to determine whether logistic regression models that use rainfall event statistics can be a viable alternative to create job lists with fewer extraneous events. Two methods are used to develop a regression model; both use iterative stepwise algorithms to select the rain variables to include and both perform similarly. The resulting model is able to capture ∼90% of the relevant events with ∼50% fewer jobs compared to the reference job list. The results suggest that there is no right threshold to use, but instead this methodology facilitates balancing the number of jobs with the desired level of precision of the results. In all cases, it is possible to greatly decrease the number of jobs that need to be run. The methodology works relatively well on different nodes in the system, though node characteristics appear to impact the amount of CSOs captured.

An extreme rainfall event in summer 2018 of Hami city in eastern Xinjiang, China

Extreme rainfall events are rare in inland arid regions, but have exhibited an increasing trend in recent years, causing many casualties and substantial socioeconomic losses. A series of heavy rains that began on July 31st, 2018, battered the Hami prefecture of eastern Xinjiang, China for four days. These rains sparked devastating floods, caused 20 deaths, eight missing, and the evacuation of about 5500 people. This study examines the extreme rainfall event in a historical context and explores the anthropogenic causes based on analysis of multiple datasets (i.e., the observed daily data, the global climate models (GCMs) from the Coupled Model Intercomparison Project Phase 5 (CMIP5), the NCEP/NCAR Reanalysis 1, and the satellite cloud data) and several statistical techniques. Results show that this extraordinarily heavy rainfall was due mainly to the abnormal weather system (e.g., the abnormal subtropical high) that transported abundant water vapor from the Indian Ocean and the East China Sea crossed the high mountains and formed extreme rainfall in Hami prefecture, causing the reservoir to break and form a flood event with treat loss, which is a typical example of a comprehensive analysis of the extreme rainfall event in summer in Northwest China. Also, the fraction of attributable risk (FAR) value was 1.00 when the 2018 July–August RX1day (11.52 mm) was marked as the threshold, supporting the claim of a significant anthropogenic influence on the risk of this extreme rainfall. The results offer insights into the variability of precipitation extremes in arid areas contributing to better manage water-related disasters.

Testing the Homogeneity of Rainfall and Temperature Data in the Kurdistan Region- Iraq

In this study, the homogeneity test of the rain series and the observed monthly and annual temperatures was carried out using the following test methods: Pettitt test, Buishand test (BRT), Standard Normal Homogeneity test (SNHT) and Van Neumann test (VNT) at a confidence level of 5% for 9 stations registered in Various regions of Iraqi Kurdistan for the period from 1981-2020. The missing values ​​for the rain time series were compensated using the simple arithmetic method and the normal ratio method. The missing temperature values ​​were compensated using the simple arithmetic rate method and via the NASA Teree satellite. The results of the homogeneity tests of the monthly rain records data showed that most of the stations were homogeneous for the winter, spring and autumn months and were not homogeneous in the summer months. As for the data of the monthly temperature records, most of the stations had inconsistent data, except for the stations of Salah al-Din and Shaqlawa. The character of homogeneity prevailed over most of the months of the year. As for the annual data of rain and temperatures, the data of all stations became homogeneous after processing the monthly data.

CLIMACS: A method for stochastic generation of continuous climate projected point rainfall for urban drainage design

Climate projected continuous rain series are required for urban drainage design and analysis. Outputs from regional climate models are yet insufficient in quality and resolution for this purpose. Here, we introduce a novel method, CLIMACS (CLImate projection of MeAsured preCipitation Series) for stochastic climate projection of point rain series for urban drainage design. It is developed and evaluated to represent current climate conditions as well as projections for the period 2071–2100 with RCP scenarios 4.5 and 8.5. CLIMACS includes seasonal stochastic resampling of individual rain events and rainfall intermittency as well as climate scaling. Fifteen climate variables representing multiple changes in the future rainfall are selected and projected to target future conditions. Realizations of the resampled and stochastically generated rain series are ranked and selected according to the minimum relative error between realization and target. To give an insight into the uncertainty of the climate projection as well as year-to-year variability of precipitation climate variables, an ensemble of the top 100 realizations for each climate scenario is selected for further analysis. It is concluded that the ensembles represent the future conditions well, however, with a large variability due to the uncertainties in climate projection. With the aim of showing the impact in urban drainage system design, a stormwater detention pond design with multiple design parameters and climate scenarios is demonstrated. The pond design results show a significant difference in required pond volume depending on the design parameters and the choice of climate scenario, which emphasizes the need for climate projected continuous rain series for urban design purposes as an alternative to design storms.

Drought Monitoring Based on Remote Sensing in a Grain-Producing Region in the Cerrado–Amazon Transition, Brazil

Drought is a natural disaster that affects a country’s economy and food security. The monitoring of droughts assists in planning assertive actions to mitigate the resulting environmental and economic impacts. This work aimed to evaluate the performance of the standardized precipitation index (SPI) using rainfall data estimated by orbital remote sensing in the monitoring of meteorological drought in the Cerrado–Amazon transition region, Brazil. Historical series from 34 rain gauge stations, in addition to indirect measurements of monthly precipitation obtained by remote sensing using the products CHIRPS-2.0, PERSIANN-CDR, PERSIANN-CCS, PERSIANN, GPM-3IMERGMv6, and GPM-3IMERGDLv6, were used in this study. Drought events detected by SPI were related to a reduction in soybean production. The SPI calculated from the historical rain series estimated by remote sensing allowed monitoring droughts, enabling a high detailing of the spatial variability of droughts in the region, mainly during the soybean development cycle. Indirect precipitation measures associated with SPI that have adequate performance for detecting droughts in the study region were PERSIANN-CCS (January), CHIRPS-2.0 (February and November), and GPM-3IMERGMv6 (March, September, and December). The SPI and the use of precipitation data estimated by remote sensing are effective for characterizing and monitoring meteorological drought in the study region.

Adolescent Killer and Politician

Adolescent killer and politician : age-related ideologies in the dystopian future Sweden of Mats Wahl’s Blood Rain series

Impact of urbanisation (trends) on runoff behaviour of Pampulha watersheds (Brazil).

The paper presents an analysis of runoff behaviour of four urban catchments between the municipalities of Belo Horizonte and Contagem in Brazil, linked to their land use. Two years of online measurement of flow data, combined with spatial analysis, was linked through runoff modelisation with EPA SWMM. The coefficients of Nash obtained varying between 0.75 and 0.87 demonstrated an adequate modelling approach. A 1-year rain series was applied to evaluate the runoff behaviour of actual land cover and that of 2002. The peak flows normalised to watershed surfaces revealed asthe most urbanised (85%) watershed Ressaca with 178 L/ha/s, three times morerunoff intensive than the least urbanised (41%) Mergulhão with 67 L/ha/s. Statistical analysis of land cover data and modelling results on watershed and sub-watershed level showed main correlations between hydrological parameters such as peak flow, average event flow and restitution time, but also between land cover and runoff coefficient. This approach gave a linear relation between runoff and green surface, with a runoff coefficient of 0.86 for fully urbanised zone and 0.43 for full "green" cover. Prospective simulation with actual urbanisation rates varying from 4 to 34 ha/year suggested an increase between 6 and 18% of the flows and a possibleend of urbanisation within the next two to three decades. These findings should contribute to a better understanding of hydrological impact of Belo Horizonte urbanisation and to the restauration of its Lake Pampulha.

Erosion, Suspended Sediment Transport and Sedimentation on the Wadi Mina at the Sidi M’Hamed Ben Aouda Dam, Algeria

The objective of this study was to follow-up on the evolution of the hydro-pluviometric schemes and particular elements of Wadi Mina (6048 km2) to the Sidi M’Hamed Ben Aouda Dam to evaluate the silting origin and status of this dam situated in the northwest of Algeria. The pluviometric study targeted a series of rains during 77 years (1930–2007), the liquid discharge data cover a period of 41 years (1969–2010) and the solids and suspended sediment concentrations data cover very variable periods, starting from 22 to 40 years for the entire catchment area. The statistical tests for ruptures detection on the chronological series of rains and discharges indicate a net reduction of rains of more than 20% on the entire basin since 1970. The evolution of solids inputs was quantified: the maximum values are registered on autumn start and at the end of spring. The Wadi Mina basin brings annually 38 × 106 m3 of water with a specific degradation of 860 t·km−2·year−1. By comparing the results found, we thus observe that the basin upstream of SMBA (1B) Dam is the greatest sediment producer towards the dam because it shows a specific degradation equal to 13.36 t·ha−1·year−1.

Multiple long-term trends and trend reversals dominate environmental conditions in a man-made freshwater reservoir

Man-made reservoirs are common across the world and provide a wide range of ecological services. Environmental conditions in riverine reservoirs are affected by the changing climate, catchment-wide processes and manipulations with the water level, and water abstraction from the reservoir. Long-term trends of environmental conditions in reservoirs thus reflect a wider range of drivers in comparison to lakes, which makes the understanding of reservoir dynamics more challenging. We analysed a 32-year time series of 36 environmental variables characterising weather, land use in the catchment, reservoir hydrochemistry, hydrology and light availability in the small, canyon-shaped Římov Reservoir in the Czech Republic to detect underlying trends, trend reversals and regime shifts. To do so, we fitted linear and piecewise linear regression and a regime shift model to the time series of mean annual values of each variable and to principal components produced by Principal Component Analysis. Models were weighted and ranked using Akaike information criterion and the model selection approach. Most environmental variables exhibited temporal changes that included time-varying trends and trend reversals. For instance, dissolved organic carbon showed a linear increasing trend while nitrate concentration or conductivity exemplified trend reversal. All trend reversals and cessations of temporal trends in reservoir hydrochemistry (except total phosphorus concentrations) occurred in the late 1980s and during 1990s as a consequence of dramatic socioeconomic changes. After a series of heavy rains in the late 1990s, an administrative decision to increase the flood-retention volume of the reservoir resulted in a significant regime shift in reservoir hydraulic conditions in 1999. Our analyses also highlight the utility of the model selection framework, based on relatively simple extensions of linear regression, to describe temporal trends in reservoir characteristics. This approach can provide a solid basis for a better understanding of processes in freshwater reservoirs.

Short time step continuous rainfall modeling and simulation of extreme events

The design, planning, operation and overall assessment of urban drainage systems require long and continuous rain series in a high temporal resolution. Unfortunately, the availability of this data is usually short. Nevertheless a precipitation model could be used to tackle this shortcoming; therefore it is in the aim of this study to present a stochastic point precipitation model to reproduce average rainfall event properties along with extreme values. For this purpose a model is proposed to generate long synthetic series of rainfall for a temporal resolution of 5min. It is based on an alternating renewal framework and events are characterized by variables describing durations, amounts and peaks.A group of 24 stations located in the north of Germany is used to set up and test the model. The adequate modeling of joint behaviour of rainfall amount and duration is found to be essential for reproducing the observed properties, especially for the extreme events. Copulas are advantageous tools for modeling these variables jointly; however caution must be taken in the selection of the proper copula. The inclusion of seasonality and small events is as well tested and found to be useful. The model is directly validated by generating long synthetic time series and comparing them with observed ones. An indirect validation is as well performed based on a fictional urban hydrological system. The proposed model is capable of reproducing seasonal behaviour and main characteristics of the rainfall events including extremes along with urban flooding and overflow behaviour. Overall the performance of the model is acceptable compared to the design practice. The proposed model is simple to interpret, fast to implement and to transfer to other regions, whilst showing acceptable results.

Role of climate in the spread of shiga toxin-producing Escherichia coli infection among children

Haemolytic-uraemic syndrome (HUS) is a rare disease mainly affecting children that develops as a complication of shiga toxin-producing Escherichia coli (STEC) infection. It is characterised by acute kidney injury, platelet consumption and mechanical destruction of red blood cells (haemolysis). In order to test the working hypothesis that the spread of the infection is influenced by specific climatic conditions, we analysed all of the identified cases of infection occurring between June 2010 and December 2013 in four provinces of Lombardy, Italy (Milano, Monza Brianza, Varese and Brescia), in which a STEC surveillance system has been developed as part of a preventive programme. In the selected provinces, we recorded in few days a great number of cases and clusters which are unrelated for spatially distant or for the disease are caused by different STEC serotypes. In order to investigate a common factor that favoured the onset of infection, we have analysed in detail the weather conditions of the areas. The daily series of temperature, rain and relative humidity were studied to show the common climate peculiarities whilst the correlation coefficient and the principal component analysis (PCA) were used to point out the meteorological variable, maximum temperature, as the principal climate element in the onset of the infection. The use of distributed lag non-linear models (DLNM) and the climate indices characterising heat waves (HWs) has allowed to identify the weather conditions associated with STEC infection. The study highlighted a close temporal correlation between STEC infection in children and the number, duration and frequency of heat waves. In particular, if the maximum temperature is greater than 90th percentile, days classified as very hot, for 3 or more consecutive days, the risk of infection is increasing.

CoRain: A free and open source software for rain series comparison

A good climatic analysis requires accurate and homogeneous daily precipitation series; unluckily, inhomogeneity is frequently found and have to be considered, especially when it is due to non-climatic parameters. CoRain is a free and open source software written in R language that could greatly help analyzing inhomogeneity caused by rainfall measuring instruments. CoRain compares two parallel rain series (with an overlapping period) and tries to highlight overestimations and underestimations due to rain gauges in a specific condition, so that the user can consider it for future analysis. CoRain offers many information on the two analyzed series, starting with cleaning input data, comparing them and classifying rainy days by severity. CoRain is a cross-platform software, easily adaptable to different needs, that takes in input a single text file with daily information of the two rain series and outputs tables (in CSV format) and plots (as PNG images) that help in the interpretation of the data. Use of the program is very simple: the execution can be either interactive or non-interactive. CoRain code has been tested on different rain series in the Piedmont region (northwestern Italy), showing its importance in identifying climate variations and instrumentation errors.

Rivers of Risk and Redemption in Gregory of Tours’ Writings

Rivers of Risk and Redemption in Gregory of Tours’ Writings

Impact Du Changement Climatique Sur L’évolution De L'érosivité Des Pluies Dans Le Rif Occidental (Nord Du Maroc)

The rainfall erosivity factor (R factor in Universal Soil Loss Equation), denoting rain energy, is a key factor for soil loss modeling. Its present and future estimation is thus significant for any action related to soil and water conservation and planning. The extended series of precipitations at high temporal resolution, essential to its evaluation, are not readily available in Morocco. The objective of this study is to predict the evolution of rainfall erosivity by 2080 in the Western Rif, based on predictions of daily rain provided by the General Climatic Models (GCMs). To reflect the seasonal variability of rainfall, and thus of R factor, a series of instantaneous rain measured over 35 consecutive years was used to monthly calibrate a model to calculate erosivity based of daily rainfall. The application of this model to the predictions of different GCMs and for various scenarios of climate evolution in Western Rif shows a weak evolution of erosivity on an annual timescale but a very strong evolution of the latter according to seasons with a reduction in R factor during winter and spring, and a pronounced increase during summer and autumn. This discernable change of the seasonality of rainfall erosivity is very useful for adjusting the evolution of agricultural practices and for selecting appropriate soil protection measures.

Multivariate analysis of digital images of a paper sensor by partial least squares for determination of nitrite

Here, a disposable ultra-low cost and simple paper-based sensor (PBS) for on-site quantification of nitrite in environmental matrices is introduced. The PBS consists of a filter paper disc with 1.2cm in diameter that is impregnated with the Griess reagents including 3-nitroaniline, 1-naphthylamine and hydrochloric acid with the optimal concentrations obtained by response surface methodology. After introducing 20.0µL of a sample/standard solution to the sensor, nitrite reacts with the Griess reagents on the sensor and produces the red-pink colored azo dye after 30min. By use of a digital camera, the image of the PBS is captured and then analyzed by partial least squares for nitrite determination. The use of a blank and sample image reduces bias from variations in ambient light and makes it possible to acquire and process images on-site. In order to demonstrate the potential impact of this technology in the environment monitoring, the device was successfully applied to the analysis of a series of water samples, including tap, rain and wastewater. The results of the method were validated by standard method.

The Effects of Rainfall on the Population Dynamics of an Endangered Aquatic Plant, Schoenoplectus gemmifer (Cyperaceae).

The conservation of aquatic plants in river ecosystems should consider the wash-out (away) problem resulting from severe rainfall. The aquatic plant Schoenoplectus gemmifer is an endangered species endemic to Japan. Our previous study reported that the population size of S. gemmifer in Hamamatsu city, Japan, had decreased by one-tenth because many individuals had been washed out by a series of heavy rains in 2004. However, there is insufficient information on the ecological nature of this endangered aquatic plant for adequate conservation. In this paper, we report the population dynamics of one population in Hamamatsu city from 2004 to 2012 in relation to rainfall. We surveyed the number and growing location of all living individuals in the population 300 times during the study period. To examine the temporal changes of individual plants, we also counted the number of culms for 38 individuals in four observations among 300 records. Decreases and increases in the population size of this plant were associated with washing out and the settlement of gemmae (vegetative propagation), respectively. The major cause of the reduction in the population size was an increase in the number of washed-out individuals and not the decreased settlement of gemmae. The wash-out rates for small and large individuals were not significantly different. Small individuals having a stream form with linear leaves resisted flooding, and large individuals were often partially torn off by flooding events. Modification of river basins to reduce the flow velocity may be effective for the conservation of S. gemmifer.

<sup>GA</sup><i>SAKe</i>: forecasting landslide activations by a genetic-algorithms-based hydrological model

Abstract. GASAKe is a new hydrological model aimed at forecasting the triggering of landslides. The model is based on genetic algorithms and allows one to obtain thresholds for the prediction of slope failures using dates of landslide activations and rainfall series. It can be applied to either single landslides or a set of similar slope movements in a homogeneous environment. Calibration of the model provides families of optimal, discretized solutions (kernels) that maximize the fitness function. Starting from the kernels, the corresponding mobility functions (i.e., the predictive tools) can be obtained through convolution with the rain series. The base time of the kernel is related to the magnitude of the considered slope movement, as well as to the hydro-geological complexity of the site. Generally, shorter base times are expected for shallow slope instabilities compared to larger-scale phenomena. Once validated, the model can be applied to estimate the timing of future landslide activations in the same study area, by employing measured or forecasted rainfall series. Examples of application of GASAKe to a medium-size slope movement (the Uncino landslide at San Fili, in Calabria, southern Italy) and to a set of shallow landslides (in the Sorrento Peninsula, Campania, southern Italy) are discussed. In both cases, a successful calibration of the model has been achieved, despite unavoidable uncertainties concerning the dates of occurrence of the slope movements. In particular, for the Sorrento Peninsula case, a fitness of 0.81 has been obtained by calibrating the model against 10 dates of landslide activation; in the Uncino case, a fitness of 1 (i.e., neither missing nor false alarms) has been achieved using five activations. As for temporal validation, the experiments performed by considering further dates of activation have also proved satisfactory. In view of early-warning applications for civil protection, the capability of the model to simulate the occurrences of the Uncino landslide has been tested by means of a progressive, self-adaptive procedure. Finally, a sensitivity analysis has been performed by taking into account the main parameters of the model. The obtained results are quite promising, given the high performance of the model against different types of slope instabilities characterized by several historical activations. Nevertheless, further refinements are still needed for application to landslide risk mitigation within early-warning and decision-support systems.