scholarly journals Temporal change of extreme precipitation intensity–duration–frequency relationships in Thailand

2021 ◽  
Author(s):  
N. Yamoat ◽  
R. Hanchoowong ◽  
S. Sriboonlue ◽  
A. Kangrang
Keyword(s):  
Time Series ◽  
Extreme Precipitation ◽  
Extreme Rainfall ◽  
Precipitation Intensity ◽  
Rainfall Time Series ◽  
The Past ◽  
The North ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract Due to climate change, many research studies have derived the updated extreme precipitation intensity–duration–frequency relationship (IDF curve) from forecasted sub-hourly rainfall intensity time series, which is one of the most important tools for the planning and designing of hydraulic infrastructures. In this study, the IDF curves (1990–2016) of the six regions and procedures are used in accordance with those of the Royal Irrigation Department (RID)’s study (1950–1988). Each set of IDF relationships consists of 81 intensity values which are the combination of nine durations and nine return periods. The intensity ratios of this study and RID are compared. A greater-than-1 ratio indicates extreme intensity increment from the past to the present. Considering 81 ratios for each region, the number of greater-than-1 ratios for the North, Northeast, Central, East, West, and South regions are 8, 2, 31, 34, 6, and 7, respectively. These ratio numbers are far below 81 which means that the majority of extreme rainfall intensities do not increase from the past to the present. The study found that using accurate historical sub-hourly rainfall time series to create a set of IDF curves would be more reliable than using forecasted rainfall modeling.

Simulating reference rainfall scenarios for hydrological applications using a multifractal approach

2021 ◽  
Author(s):  
Arun Ramanathan ◽  
Pierre-Antoine Versini ◽  
Daniel Schertzer ◽  
Ioulia Tchiguirinskaia ◽  
Remi Perrin ◽  
...  
Keyword(s):  
Time Series ◽  
Moment Analysis ◽  
Specific Reference ◽  
Rainfall Time Series ◽  
Time Series Dataset ◽  
Hourly Rainfall ◽  
Spatial Dimensions ◽  
Multifractal Theory ◽  
Intensity Duration Frequency ◽  
Hydrological Applications

<p><strong>Abstract</strong></p><p>Hydrological applications such as flood design usually deal with and are driven by region-specific reference rainfall regulations, generally expressed as Intensity-Duration-Frequency (IDF) values. The meteorological module of hydro-meteorological models used in such applications should therefore be capable of simulating these reference rainfall scenarios. The multifractal cascade framework, since it incorporates physically realistic properties of rainfall processes such as non-homogeneity (intermittency), scale invariance, and extremal statistics, seems to be an appropriate choice for this purpose. Here we suggest a rather simple discrete-in-scale multifractal cascade based approach. Hourly rainfall time-series datasets (with lengths ranging from around 28 to 35 years) over six cities (Paris, Marseille, Strasbourg, Nantes, Lyon, and Lille) in France that are characterized by different climates and a six-minute rainfall time series dataset (with a length of around 15  years) over Paris were analyzed via spectral analysis and Trace Moment analysis to understand the scaling range over which the universal multifractal theory can be considered valid. Then the Double Trace Moment analysis was performed to estimate the universal multifractal parameters α,C<sub>1</sub> that are required by the multifractal cascade model for simulating rainfall. A renormalization technique that estimates suitable renormalization constants based on the IDF values of reference rainfall is used to simulate the reference rainfall scenarios. Although only purely temporal simulations are considered here, this approach could possibly be generalized to higher spatial dimensions as well.</p><p><strong>Keywords</strong></p><p>Multifractals, Non-linear geophysical systems, Cascade dynamics, Scaling, Hydrology, Stochastic rainfall simulations.</p>

scholarly journals Machine Learning for Projecting Extreme Precipitation Intensity for Short Durations in a Changing Climate

Geosciences ◽  
2019 ◽  
Vol 9 (5) ◽  
pp. 209
Author(s):  
Huiling Hu ◽  
Bilal M. Ayyub
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Extreme Precipitation ◽  
Circulation Model ◽  
Machine Learning Algorithms ◽  
Precipitation Intensity ◽  
Potential Threat ◽  
Drainage Systems ◽  
Idf Curves ◽  
Intensity Duration Frequency

Climate change is one of the prominent factors that causes an increased severity of extreme precipitation which, in turn, has a huge impact on drainage systems by means of flooding. Intensity–duration–frequency (IDF) curves play an essential role in designing robust drainage systems against extreme precipitation. It is important to incorporate the potential threat from climate change into the computation of IDF curves. Most existing works that have achieved this goal were based on Generalized Extreme Value (GEV) analysis combined with various circulation model simulations. Inspired by recent works that used machine learning algorithms for spatial downscaling, this paper proposes an alternative method to perform projections of precipitation intensity over short durations using machine learning. The method is based on temporal downscaling, a downscaling procedure performed over the time scale instead of the spatial scale. The method is trained and validated using data from around two thousand stations in the US. Future projection of IDF curves is calculated and discussed.

scholarly journals Sub-daily extreme events distribution and changes in Northeastern Brazil in the 20th century

2015 ◽  
Vol 369 ◽  
pp. 135-140 ◽  
Author(s):  
R. Basso ◽  
D. Allasia ◽  
R. Tassi ◽  
D. M. Bayer
Keyword(s):  
20Th Century ◽  
Extreme Events ◽  
Regional Analysis ◽  
Extreme Rainfall ◽  
Northeastern Brazil ◽  
The North ◽  
Hourly Rainfall ◽  
Northern Portion ◽  
Intensity Duration Frequency ◽  
Engineering Projects

Abstract. The regional analysis of extreme hydrological events is connected with the availability of a dense network of rainfall data that is absent or inaccessible in Brazil, especially for sub-daily information. In engineering, extreme events rainfall information is represented by intensity–duration–frequency (IDF) relationships which are the most commonly used tools in water resources engineering for planning and design. Even if the sub-daily information that is included in the relationships is not available, the extreme rainfall information rest in the fundamentals of the IDF. This paper analyzes spatial distribution and track changes in sub-daily precipitation over Northeastern (NE) Brazil. Precipitation was estimated from IDF relationships information in Brazil based in rainfall measured from 1920's to 1950's (but still used in engineering projects) and information from the last half of the 20th century obtained from several IDFs gathered from municipalities' manuals, local symposia and books in many cases not easily obtainable. Results showed an intensification of extreme events in recent years, especially in shorter duration rainfall (less than 12 h). Hourly rainfall is bigger in almost all the Brazilian region, but especially in littoral and Northern portion, however, 12 and 24 h rainfall exhibit increases in the North, but, lower values in the Southern half of the region in concordance with flood changes reported by Milly et al. (2005). Analyzing the ratio between 1 and 24 h rainfall is possible to confirm its increase in all the region, with up to 35% in some areas. These results were able to show insight of sub-daily extreme events changes during 20th century in NE Brazil were previous reports were not found. The results also alerts for the necessity of engineering projects review, as outdated information is still being used for design purposes.

scholarly journals Trends in Extreme Precipitation Indices in Iran: 1951–2007

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Robert C. Balling ◽  
Mohammad Sadegh Keikhosravi Kiany ◽  
Shouraseni Sen Roy ◽  
Javad Khoshhal
Keyword(s):  
Time Series ◽  
Extreme Precipitation ◽  
Daily Rainfall ◽  
Extreme Rainfall ◽  
Rainfall Time Series ◽  
Upward Trend ◽  
Precipitation Total ◽  
Annual Precipitation Total ◽  
Extreme Precipitation Indices ◽  
Precipitation Indices

We investigate trends in extreme precipitation in Iran for 1951–2007 using the recently released APHRODITE daily rainfall time series. We find that seven different indices of extreme precipitation all show an upward trend through the study period. The seven different precipitation indices include annual precipitation total, number of days above a certain threshold, maximum precipitation received over a certain period of time, maximum one-day precipitation, and number of days with precipitation above the 90th percentile. A principal components analysis reveals one eigenvector explaining much of the variance in the seven indices and reveals that this component exhibits a strong upward trend for the whole of Iran. On a regional level, we find that the upward trend in extreme precipitation has a strong southwest-to-northeast gradient across the country for all the indices. We repeated all the analyses for 42 stations across the country to compare with the results from the gridded data; trends in extreme rainfall generated from the station data compare favorably with the results from the APHRODITE daily rainfall time series thereby reinforcing the robustness of our conclusions.

scholarly journals Cascade-based disaggregation of continuous rainfall time series: the influence of climate

2001 ◽  
Vol 5 (2) ◽  
pp. 145-164 ◽  
Author(s):  
A. Güntner ◽  
J. Olsson ◽  
A. Calver ◽  
B. Gannon
Keyword(s):  
Time Series ◽  
Extreme Rainfall ◽  
High Accuracy ◽  
Lower Percentage ◽  
Temperate Climate ◽  
Model Parameters ◽  
Hourly Rainfall ◽  
The Uk ◽  
Semi Arid ◽  
Hydrological Applications

Abstract. Rainfall data of high temporal resolution are required in a multitude of hydrological applications. In the present paper, a temporal rainfall disaggregation model is applied to convert daily time series into an hourly resolution. The model is based on the principles of random multiplicative cascade processes. Its parameters are dependent on (1) the volume and (2) the position in the rainfall sequence of the time interval with rainfall to be disaggregated. The aim is to compare parameters and performance of the model between two contrasting climates with different rainfall generating mechanisms, a semi-arid tropical (Brazil) and a temperate (United Kingdom) climate. In the range of time scales studied, the scale-invariant assumptions of the model are approximately equally well fulfilled for both climates. The model parameters differ distinctly between climates, reflecting the dominance of convective processes in the Brazilian rainfall and of advective processes associated with frontal passages in the British rainfall. In the British case, the parameters exhibit a slight seasonal variation consistent with the higher frequency of convection during summer. When applied for disaggregation, the model reproduces a range of hourly rainfall characteristics with a high accuracy in both climates. However, the overall model performance is somewhat better for the semi-arid tropical rainfall. In particular, extreme rainfall in the UK is overestimated whereas extreme rainfall in Brazil is well reproduced. Transferability of parameters in time is associated with larger uncertainty in the semi-arid climate due to its higher interannual variability and lower percentage of rainy intervals. For parameter transferability in space, no restrictions are found between the Brazilian stations whereas in the UK regional differences are more pronounced. The overall high accuracy of disaggregated data supports the potential usefulness of the model in hydrological applications. Keywords: Rainfall, temporal disaggregation, random cascade, scaling, semi-arid, temperate climate.

scholarly journals Deriving intensity–duration–frequency (IDF) curves using downscaled in situ rainfall assimilated with remote sensing data

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Yabin Sun ◽  
Dadiyorto Wendi ◽  
Dong Eon Kim ◽  
Shie-Yui Liong
Keyword(s):  
Remote Sensing ◽  
Daily Rainfall ◽  
Remote Sensing Data ◽  
Rainfall Events ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Improved Accuracy

AbstractThe rainfall intensity–duration–frequency (IDF) curves play an important role in water resources engineering and management. The applications of IDF curves range from assessing rainfall events, classifying climatic regimes, to deriving design storms and assisting in designing urban drainage systems, etc. The deriving procedure of IDF curves, however, requires long-term historical rainfall observations, whereas lack of fine-timescale rainfall records (e.g. sub-daily) often results in less reliable IDF curves. This paper presents the utilization of remote sensing sub-daily rainfall, i.e. Global Satellite Mapping of Precipitation (GSMaP), integrated with the Bartlett-Lewis rectangular pulses (BLRP) model, to disaggregate the daily in situ rainfall, which is then further used to derive more reliable IDF curves. Application of the proposed method in Singapore indicates that the disaggregated hourly rainfall, preserving both the hourly and daily statistic characteristics, produces IDF curves with significantly improved accuracy; on average over 70% of RMSE is reduced as compared to the IDF curves derived from daily rainfall observations.

scholarly journals Modelling and assessment of urban flood hazards based on rainfall intensity-duration-frequency curves reformation

2016 ◽  
Author(s):  
Reza Ghazavi ◽  
Ali Moafi Rabori ◽  
Mohsen Ahadnejad Reveshty
Keyword(s):  
Return Period ◽  
Urban Areas ◽  
Rainfall Intensity ◽  
Flood Hazards ◽  
Return Periods ◽  
Urban Flood ◽  
Design Storm ◽  
Hourly Rainfall ◽  
Idf Curves ◽  
Intensity Duration Frequency

Abstract. Estimate design storm based on rainfall intensity–duration–frequency (IDF) curves is an important parameter for hydrologic planning of urban areas. The main aim of this study was to estimate rainfall intensities of Zanjan city watershed based on overall relationship of rainfall IDF curves and appropriate model of hourly rainfall estimation (Sherman method, Ghahreman and Abkhezr method). Hydrologic and hydraulic impacts of rainfall IDF curves change in flood properties was evaluated via Stormwater Management Model (SWMM). The accuracy of model simulations was confirmed based on the results of calibration. Design hyetographs in different return periods show that estimated rainfall depth via Sherman method are greater than other method except for 2-year return period. According to Ghahreman and Abkhezr method, decrease of runoff peak was 30, 39, 41 and 42 percent for 5-10-20 and 50-year return periods respectively, while runoff peak for 2-year return period was increased by 20 percent.

Reversing hydrology: Estimation of sub-hourly rainfall time-series from streamflow

2014 ◽  
Vol 60 ◽  
pp. 290-301 ◽  
Author(s):  
Ann Kretzschmar ◽  
Wlodek Tych ◽  
Nick A. Chappell
Keyword(s):  
Time Series ◽  
Rainfall Time Series ◽  
Hourly Rainfall

scholarly journals Rainfall Intensity Analysis for Synoptic Stations in Northern Nigeria

2020 ◽  
Vol 17 (3) ◽  
pp. 223-228
Author(s):  
S.O. Oyegoke ◽  
A.S. Adebanjo ◽  
H.J. Ododo
Keyword(s):  
Rainfall Intensity ◽  
Linear Regression Analysis ◽  
Extreme Rainfall ◽  
Data Series ◽  
Northern Nigeria ◽  
Return Periods ◽  
Accurate Forecast ◽  
Idf Curves ◽  
Intensity Duration Frequency ◽  
Frequency Relationship

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

scholarly journals AUTOREGRESSIVE PROCESSES AND GRAIN YIELD FORECASTING IN THE NORTHERN KAZAKHSTAN

2018 ◽  
pp. 98-105
Author(s):  
T. A. Kussaiynov ◽  
A. A. Bulasheva ◽  
Zh. O. Zhakupova
Keyword(s):  
Time Series ◽  
Grain Yield ◽  
Crop Yields ◽  
Linear Trend ◽  
Statistical Properties ◽  
Time Series Models ◽  
Autoregressive Processes ◽  
Agricultural Economy ◽  
The Past ◽  
The North

Time series models are one of the most commonly used forecasting tools in the agricultural economy. In this case, the future values of the variable are function of the past values of the same variable. In other words, there are autoregressive processes. The dynamic of grain yields in the North-Kazakhstan and Kostanay regions of Kazakhstan demonstrate very similar statistical properties. In both cases, there is a positive linear trend, the cyclical development of the process is clearly discernible. Serious attention should also be given to the existence of a cycle in the dynamics of the dispersion level of crop yields. These stochastic features of the indicator should be taken into account in agricultural forecasting.

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