Return Period Analysis Research Articles

Assessing the Impacts of Extreme Precipitation Change on Vegetation Activity

Extreme climate events frequently have more severe effects on terrestrial vegetation activity than long-term changes in climate averages. However, changes in extreme climate events as well as their potential risk on vegetation activity are still poorly understood. By using the Middle and Lower Reaches of the Yangtze River (MLR-YR) in China as an example, this paper aims to understand the vegetation response to changes in extreme precipitation events from 1982 to 2012 using the maximum normalized difference vegetation index (NDVI) as an indicator. By applying extreme value theory (EVT), the potential risks of extreme precipitation events on vegetation activity were analyzed by conducting return period analysis. Results indicated that vegetation activity could be affected by extreme precipitation events, especially the combined effects of the frequency and intensity of precipitation extremes. For instance, vegetation activity could be enhanced in the regions with weakened intensity but increased occurrence of extreme precipitation events. In addition, we found potential risk of extreme precipitation events on vegetation activity from the results of precipitation extreme trend and return period analysis. These phenomena can be associated with the local occurrence of extreme precipitation events, different land cover types, and soil moisture cumulative effect on vegetation growth. This study stresses the importance of considering both current changes in and the potential risk of extreme precipitation events to understand their effects on vegetation activity.

Drought Analysis in East Nusa Tenggara (Indonesia) Using Regional Frequency Analysis.

Drought is a condition of a shortage of water that has an impact on economic activity. This research studies the severe drought area in Indonesia using Regional Frequency Analysis (RFA), based on daily precipitation data recorded at nine stations. The analysis reveals five homogeneous regions, based on discordancy and heterogeneity tests. Furthermore, the L-moment approach is applied to investigate the regional distribution and suggests that the Pearson type III distribution is the distribution that best fits the five regions. This distribution is also used to calculate the regional growth curve that is employed in the drought analysis. The drought return period analysis, for conditions of 40% of normal rainfall, concludes that the region containing the Fransiskus Xaverius, Gewayantana, and Mali stations has the highest drought risk, indicated by the fastest return period estimate of 2 years and 4 months. Moreover, the extreme drought analysis shows that two of the regions have the potential to experience the return of extreme drought, with less than 20% of normal rainfall, in less than four years.

Swell wave progression in the English Channel: implications for coastal monitoring

Energetic swell waves, particularly when they coincide with high water levels, can present significant coastal hazards. To better understand and predict these risks, analysis of the sea levels and waves that generate these events and the resulting coastal impacts is essential. Two energetic swell events, neither of which were predicted by modelled flood forecasts, occurred in quick succession in the English Channel. The first event, on 30 January 2021, produced moderate significant wave heights at or just below the 0.25 year return period along the southwest English coast, but combined with significant swell caused overtopping at East Beach in West Bay and at Chesil Beach. The second event, on 1 February 2021, generated the highest wave energy periods measured at many locations along the southern English coastline and, at high water, caused waves to run up over the promenades at Poole Bay and Christchurch Bay and caused overtopping at Hayling Island. Both events are described in detail, and their spatial footprints are mapped through a joint return period analysis using a copula function. It is found that typical joint return period analysis of water level and significant wave height underestimates potential impacts, while a joint consideration of water level and wave power (P) describes the 31 January event better and a joint consideration of water level and energy period (Te) best describes the 1 February event. Therefore, it is recommended that Te and P are adopted for coastal monitoring purposes, and that future studies further explore the use of both parameters for swell monitoring.

A Copula-Based Multivariate Probability Analysis for Flash Flood Risk under the Compound Effect of Soil Moisture and Rainfall

Flash floods can be characterized by several variables. Of these, soil moisture (SM) is an important environmental factor that plays a key role in hydrological and ecological processes and affects the mechanisms that cause flash floods. To more accurately determine the occurrence probability of flash floods, the combined effects of soil moisture and rainfall indexes were considered in this paper, and the copula function approach was explored for use in joint probability analyses of flash flood risks. The results showed that (1) the Clayton copula function offered the best fit for the bivariate joint distribution and captured the occurrence probability of the combination of both peak flow (PF) and SM, while the t-copula function achieved the best fit for the multivariate joint distribution, which presented different combinations of characteristic flash flood parameters. (2) The joint distribution probability of flash floods increased with increasing risk parameter thresholds. Return period analysis indicated that the return periods of the bivariate joint distribution were smaller than those of the multivariate joint distribution. (3) If PF and SM are fixed, the occurrence probability of flash floods is higher in regions where the maximum 1-h rainfall is higher. This study provides an effective and quantitative approach to improving flash flood prediction and advances the application of this approach for the management of future flash flood risks.

Joint values determination of wind and temperature actions on long-span bridges: Copula-based analysis using long-term meteorological data

The design of long-span bridges envisages simultaneous actions of wind and temperature factors. However, incorporation of their extreme values into the design specifications results in excessive safety margins, since they rarely occur simultaneously. In this paper, a copula-based technique is proposed to assess joint values of wind and temperature actions on long-span bridges using long-term meteorological data. This technique was applied to a currently constructed cable-stayed bridge with the longest main span in the world, namely the Changtai Yangtze River Bridge in China. The Archimedean copulas were adopted to establish the joint distributions of wind speed and air temperature by coupling their marginal distributions. The bivariate return period analysis was employed to assess the occurrence probabilities of different combinations of wind and temperature actions. Based on the proposed principle, which implies that the bivariate design return period is equal to the univariate one, several types of the joint values of wind and temperature actions were recommended for the bridge design. The comparative analysis revealed that when one of the two coupled actions (wind or temperature) is specified by a univariate characteristic value, the other one does not exceed 60% of the univariate characteristic value in most cases.

Climate change impact assessment on mild and extreme drought events using copulas over Ankara, Turkey

Climate change, one of the major environmental challenges facing mankind, has caused intermittent droughts in many regions resulting in reduced water resources. This study investigated the impact of climate change on the characteristics (occurrence, duration, and severity) of meteorological drought across Ankara, Turkey. To this end, the observed monthly rainfall series from five meteorology stations scattered across Ankara Province as well as dynamically downscaled outputs of three global climate models that run under RCP 4.5 and RCP 8.5 scenarios was used to attain the well-known SPI series during the reference period of 1986–2018 and the future period of 2018–2050, respectively. Analyzing drought features in two time periods generally indicated the higher probability of occurrence of drought in the future period. The results showed that the duration of mild droughts may increase, and extreme droughts will occur with longer durations and larger severities. Moreover, joint return period analysis through different copula functions revealed that the return period of mild droughts will remain the same in the near future, while it declines by 12% over extreme droughts in the near future.

Spatio-temporal analysis of drought and return periods over the East African region using Standardized Precipitation Index from 1920 to 2016

East African region is susceptible to drought due to high variation in monthly precipitation. Studying drought at regional scale is vital since droughts are considered a ‘creeping’ disaster by nature with devasting and extended impact often requiring long periods to reverse the recorded damages. This study assessed drought exceedance and return years over East Africa from 1920 to 2016 using Climate Research Unit (CRU) precipitation data records. Meteorological drought, where precipitation is the central quantity of interest, was adopted in the work. Standardize Precipitation Index (SPI) was used to study long term meteorological droughts and also to assess drought magnitude, frequency, exceedance probability and return years using Joint Probability Density Function (JPDF). Also, Mann-Kendall trend analysis was applied to precipitation and SPI to investigate the trend changes. Results showed that years with high drought magnitude ranged from 1920−22, 1926−29, 1942−46 and 1947−51 with values corresponding to 2.2, 3.2, 3.4 and 2.6, respectively while years with low drought magnitude ranged from 1930−31, 1988−89 and 2001−02 with values as 0.2, 0.12 and 0.15, respectively. The longest droughts occurred from 1926−29, 1937−41, 1942−46, 1947−51, 1952−56, and 1958−61 with values in years as 3, 4, 4, 4, 4, and 3 years, respectively, while the shortest droughts occurred in time period of 1 year and ranged from 1930−31, 1964−65, 1979−80, 1981−82, 1983−84, 1988−89, 1991−92, 1993−94, 1996−97 and 2001−02. Also, it was demonstrated that probability of drought occurrence is high when severity is low and such droughts occur at short time intervals and not all severest drought took longer periods. The SPI trends indicate high positive (negative) pixels above (below) the zero-trend mark, indicating that drought prevails in both low and high elevation areas up to 2000 m. There was no direct link between ENSO and drought but arguably the association of drought in most El Niño and La Niña years suggests that the impact of ENSO cannot be ruled out since peak ENSO events occur during October to March periods which coincides with the short (SON) and long (MAM) rainy seasons of East Africa. The study is particularly relevant in being able to depict continuous and synoptic drought condition all over East Africa, providing vital information to farmers and policy makers, using very cost-effective method.

Change Characteristics of Extreme Precipitations and Estimation of Precipitation in Different Return Periods in the Qingjiang Basin of the Yangtse River

Peng, T.; Wang, J., and Shen, T., 2019. Change characteristics of extreme precipitations and estimation of precipitation in different return periods in the Qingjiang Basin of the Yangtse River. In: Guido-Aldana, P.A. and Mulahasan, S. (eds.), Advances in Water Resources and Exploration. Journal of Coastal Research, Special Issue No. 93, pp. 200–208. Coconut Creek (Florida), ISSN 0749-0208.Based on the observations from 10 rain gauges from 1960 to 2016 in the Qingjiang Basin, this study aimed to discuss the spatial and temporal distributions of extreme precipitations in the Qingjiang Basin area using extreme daily precipitation, extreme precipitation, and extreme precipitation duration as extreme parameters, and provide the extreme precipitation spatial distribution and variation analysis of different time scale return periods based on the generalized extremum theory. The findings revealed that the maximum daily precipitation in the Qingjiang Basin was low in the upstream, downstream, and north, and high in the south. The upstream had always been a small area with extreme daily precipitation. The maximum value was located in the south of the basin, and the position alternated with the change in the age. The maximum extreme process precipitation exhibited a decreasing distribution from west to east. The rainfall in the upstream precipitation process was significantly greater than that in the downstream, and the spatial distribution of the corresponding precipitation days showed larger values in the south and the upstream, and smaller values in the north and the middle and lower reaches. The average precipitation was greater in the 1980s than in the 1960s and 1970s. In the 21st century, the maximum extreme continuous precipitation intensity was significantly reduced. The extreme longest process precedence presented two distinct extreme centers, and the corresponding precipitation days were high in the upstream and low in the middle and lower reaches. The return period of the Qingjiang Basin extreme precipitation was significantly different. The spatial distribution of the extreme daily precipitation at different return period levels was larger in the north than in the south, and smaller in the upper and lower reaches than in the midstream.

Assessment and Analysis of Temperature and Precipitation Return Periods Using Spectral Analysis and its Effect on Land Management (A Case Study: Khodaafarin Area, East Azerbaijan)

Assessment and Analysis of Temperature and Precipitation Return Periods Using Spectral Analysis and its Effect on Land Management (A Case Study: Khodaafarin Area, East Azerbaijan)

Bivariate Risk Analysis of Droughts Using a Nonparametric Multivariate Standardized Drought Index and Copulas

The Nonparametric Multivariate Standardized Drought Index (NMSDI) based on precipitation and soil moisture data in conjunction with copula functions is of primary concern in this study. We are the first to investigate bivariate return periods of the NMSDI using the two typical drought characteristics (duration and severity) at 10 stations in Konya Closed Basin (KCB) in Turkey. As a result, lognormal and log-logistic distributions were identified as the most suitable distributions for drought duration and severity series according to five commonly used goodness of fit tests. Various types of copulas were considered in modeling the joint dependence between duration and severity series at each station. Our results from the five goodness of fit tests and tail dependence assessments showed that BB6, BB7, and BB8 copulas outperformed the joint modeling of duration and severity series in the KCB. The bivariate return period analysis revealed a high risk for southeastern and southwestern regions in the KCB for the 3-month NMSDI series while north to northwestern regions could be exposed to high risk for the 6-month series.

Analysis of return periods and return levels of Yearly July–September extreme droughts in the West African Sahel

This paper aims to model the occurrence of Yearly July–September (YJAS) extreme droughts in the West African Sahel (WAS) and to estimate return periods and return levels of these events through stationary peaks-over-threshold model. For this purpose, the historical gridded monthly rainfall data from Climatic Research Unit for the period 1901–2009 were used. The results show that return levels of YJAS dry extremes have increased since 1970, implying that YJAS extreme droughts are consistently more severe after 1970 than they were before. Approximately $$62\%$$ of the WAS area in the postchange period of 1971–2009 was dominated by dry spells not longer than 1 year. The dynamics of the YJAS extremes drying trend indicate that the changes at the tails of YJAS dry extreme distribution have contributed to the dry trend in mean YJAS rainfall in the WAS. The estimated 40-year return level of these events based on 1971–2009 period was less than the average of dry extremes of the same period, suggesting that droughts could intensify in the future even though with some amelioration. Such a finding could prove helpful in anticipation of climate risks in this region where adaptive capacities are very low.

Regional rainfall thresholds for landslide occurrence using a centenary database

Abstract. This work proposes a comprehensive method to assess rainfall thresholds for landslide initiation using a centenary landslide database associated with a single centenary daily rainfall data set. The method is applied to the Lisbon region and includes the rainfall return period analysis that was used to identify the critical rainfall combination (cumulated rainfall duration) related to each landslide event. The spatial representativeness of the reference rain gauge is evaluated and the rainfall thresholds are assessed and calibrated using the receiver operating characteristic (ROC) metrics. Results show that landslide events located up to 10 km from the rain gauge can be used to calculate the rainfall thresholds in the study area; however, these thresholds may be used with acceptable confidence up to 50 km from the rain gauge. The rainfall thresholds obtained using linear and potential regression perform well in ROC metrics. However, the intermediate thresholds based on the probability of landslide events established in the zone between the lower-limit threshold and the upper-limit threshold are much more informative as they indicate the probability of landslide event occurrence given rainfall exceeding the threshold. This information can be easily included in landslide early warning systems, especially when combined with the probability of rainfall above each threshold.

Understanding land use and cover change impacts on run‐off and sediment load at flood events on the Loess Plateau, China

AbstractThe Loess Plateau has been experiencing large‐scale land use and cover changes (LUCCs) over the past 50 years. It is well known about the significant decreasing trend of annual streamflow and sediment load in the catchments in this area. However, how surface run‐off and sediment load behaved in response to LUCC at flood events remained a research question. We investigated 371 flood events from 1963 to 2011 in a typical medium‐sized catchment within the Plateau in order to understand how LUCC affected the surface run‐off generation and sediment load and their behaviours based on the analysis of return periods. The results showed that the mean annual surface run‐off and sediment load from flood events accounted for 49.6% and 91.8% of their mean annual totals. The reduction of surface run‐off and associated sediment yield in floods explained about 85.0% and 89.2% of declines in the total annual streamflow and sediment load, respectively. The occurrences of flood events and peak sediment concentrations greater than 500 kg/m3showed a significantly downward trend, yet the counterclockwise loop events still dominated the flood event processes in the catchment. The results suggest that LUCC over the past 50 years resulted in significant changes in the water balance components and associated soil erosion and sediment transportation in the catchment. This was achieved mainly by reducing surface run‐off and sediment yield during floods with return period of less than 5 years. Run‐off–sediment load behaviour during the extreme events with greater than 10‐year return periods has not changed. Outcomes from this study are useful in understanding the eco‐hydrological processes and assisting the sustainable catchment management and land use planning on the Loess Plateau, and the methodologies are general and applicable to similar areas worldwide.

Assessing typhoon damages to Taiwan in the recent decade: return period analysis and loss prediction

Devastating typhoons that induce enormous losses to various sectors of the economy underline the importance of an improved understanding of the regional hazard-to-loss relationship. This study utilizes the up-to-date loss data of typhoons in Taiwan from 2006 to 2015 to analyze the interannual variations in the annual aggregate losses (AALs) and develop a loss prediction model for the major administrative divisions. Return period analysis applied to the AALs identifies western-to-southwestern Taiwan as the high-risk region, among which Chiayi and Pingtung exhibit the highest 10-year AALs over 100 million. The gamma hurdle model (GHM) is adopted for loss prediction for its ability to stepwise model the loss occurrence and amount, leading to straightforward discussion regarding the explanatory power and statistical significance of meteorological predictors in their marginal and joint space. In the first part of the GHM, maximum daily rainfall and maximum gust wind are selected as the two most significant meteorological predictors for the logistic regression model of the loss occurrence, showing a remarkable model accuracy of $${\sim 0.9}$$ . In the second part of the GHM, maximum sustained wind is added to the gamma generalized linear model of the loss amount, generating the cross-validated Nash–Sutcliffe efficiency (mean absolute error) values higher (lower) than 0.6 (3 million) for several southwestern cities. Event assessment for Typhoons Soudelor (2015) and Morakot (2009) further demonstrates the utility of the GHM and illustrates the essential for accounting for the combination effect of rainfall and wind on loss estimation.

Bivariate Return Period for Design Hyetograph and Relationship with T-Year Design Flood Peak

This study focuses on the return period evaluation for design hyetographs, which is usually estimated by adopting a univariate statistical approach. Joint Return Period (JRP) and copula-based multivariate analysis are used in this work to better define T-year synthetic rainfall patterns which can be used as input for design flood peak estimation by means of hydrological simulation involving rainfall-runoff (RR) models. Specifically, a T-year Design Hyetograph (DH) is assumed to be characterized by its peak H, at the chosen time resolution Δt, and by the total rainfall height W, cumulated on its critical duration dCri, which has been a priori fixed. As stated in technical literature, the choice of the expression for JRP depends on which event is deemed as critical for the investigated system; the most important cases are: (i) all the variables must exceed a certain magnitude to achieve critical conditions; or (ii) at least one variable must be greater than a threshold; or (iii) critical conditions are induced by all the events with a joint Cumulative Density Function (CDF) overcoming an assigned probability threshold. Once the expression for JRP was chosen, the relationship among multivariate T-year design hyetographs and T-year design flood peak was investigated for a basin located in Calabria region (southern Italy). Specifically, for the selected case study, a summary diagram was obtained as final result, which allows the main characteristics of T-year DHs to be estimated, considering both the univariate and the copula based multivariate analysis, and the associated T-year design flood peaks obtained through the simulation with a RR model.

Influence of the runout potential on landslide-susceptible areas along the flysch–karst contact in Istria, Croatia

The constant threat from landslides in the northeastern part of Istria, Croatia, calls for the need to apply accurate and reliable methods in landslide hazard assessment in order to prevent landslide damage and to set an early warning system if necessary. Furthermore, landslide susceptibility and hazard assessment enable optimal area management and regional urban planning. The study area is in the northeastern and central part of the Istrian Peninsula, well known as an area of frequent, small and shallow slope instability phenomena. Landslide susceptibility assessment in the area around the city of Buzet was performed using a deterministic landslide susceptibility model in the LS-RAPID software. LS-RAPID was developed to analyze stability at one single location, but the performed analysis has shown that LS-RAPID can be used as a powerful tool in landslide susceptibility and hazard assessment on regional scale. The objective of this paper is to establish the influence of the runout potential on the enlargement of the landslide-susceptible zones, due to expansion of the failure area around the initial failure zone. Performed analysis of rainfall return periods shows the frequency of landslide occurrence and provides the possible correlation with the time component of landslide hazard in the area.

Multivariate drought frequency estimation using copula method in Southwest China

Drought over Southwest China occurs frequently and has an obvious seasonal characteristic. Proper management of regional droughts requires knowledge of the expected frequency or probability of specific climate information. This study utilized k-means classification and copulas to demonstrate the regional drought occurrence probability and return period based on trivariate drought properties, i.e., drought duration, severity, and peak. A drought event in this study was defined when 3-month Standardized Precipitation Evapotranspiration Index (SPEI) was less than −0.99 according to the regional climate characteristic. Then, the next step was to classify the region into six clusters by k-means method based on annual and seasonal precipitation and temperature and to establish marginal probabilistic distributions for each drought property in each sub-region. Several copula types were selected to test the best fit distribution, and Student t copula was recognized as the best one to integrate drought duration, severity, and peak. The results indicated that a proper classification was important for a regional drought frequency analysis, and copulas were useful tools in exploring the associations of the correlated drought variables and analyzing drought frequency. Student t copula was a robust and proper function for drought joint probability and return period analysis, which is important for analyzing and predicting the regional drought risks.

Methodology for climate change assessment of flood dynamics using deterministic hydrological model - Application to the Vugia-Thubon catchment - Vietnam

In recent years, Climate Change is commonly known as global warming and associated with sea level rise. Such process is one of the most serious challenges facing the human beings in the 21st century. Under the impact of these phenomena, extreme climatic phenomena are expected to be more frequent and serious, leading to natural disasters especially related to water. Flood risk represents a major issue especially for developing countries where the economy as well as the adaptation capacity against disaster is still poor. As shown in World Bank studies, with more than 70% of the population working in agriculture, inhabitants essentially concentrate at the coastal plain, Vietnam is one of the countries most heavily affected by the consequences of climate change. To get more understanding on the impact of this natural phenomenon to Vietnamese people, a methodology has been elaborated in order to assess different climate scenarios over a large catchment and flood dynamics. The simulations are based on a validated deterministic hydrological model which is integrating geology, soil, topography, river systems and climate variables. The validation of this model is obtained through measurements and observations made at different stations within the catchment. The actual climate in the period of 1998-2004 is properly reproduced by the model which provides a clear view about the flood processes. Future climate is obtained from downscaled GCM data that provide a scenario for 2094-2100 of hydrological variables. The new simulation allows to analyze the changes in the flood dynamics and to perform the frequency and the return period analysis. The approach allows providing an operational model for integrating the climate change within the engineering design activities dedicated to flood protection measures and resilience strategies.

Spatial analysis of meteorological drought return periods in China using Copulas

China is considered to be one of the most vulnerable drought-prone countries in the world, and it has recently suffered many severe droughts with large economic and societal losses. Drought events in China have been extracted using run theory based on the Standardized Precipitation Evapotranspiration Index, which covers the period 1961–2013 across 810 stations. The drought events are characterized by three variables: duration, severity and peak. Exponential, Weibull and Pareto functions are then selected to describe the marginal distribution of duration, severity and peak, respectively. The Gumbel–Hougaard Copula was used to construct the joint distribution of Duration–Severity and Duration–Peak, while the Clayton Copula and the Gaussian Copula are used to construct the joint distribution of Severity–Peak and Duration–Severity–Peak, respectively. The results indicate that the return period is dependent on spatial location, variable type and the combination of variables. For extreme droughts, trivariate ‘and’ return periods are longer, with an average of 42.1 years. The short return period is mainly distributed in southern China, especially on the border between Sichuan and Yunnan, the coastal regions of Guangdong, western Hunan and northern Jiangxi. Studies on the identification of spatial distributions of drought return periods across China have therefore been undertaken for drought mitigation and strategy planning.

Predicting return periods of hydrological droughts using the Pearson 3 distribution: a case from rivers in the Canadian prairies

The standardized series of monthly and weekly flow sequences, referred to as standardized hydrological index (SHI) series, from five rivers in the Canadian prairies were subjected to return period (Tr) analysis of drought length (L). The SHI series were truncated at drought probability levels q ranging from 0.5 to 0.05 with the intention of deducing drought events and corresponding drought lengths. The values of L were fitted to the Pearson 3, the gamma (2-parameter), the exponential (1-parameter), the Weibull 3 and the Weibull (2-parameter) probability density functions (pdfs). A priori assignment of one week or one month for the location parameter in the Pearson 3 pdf proved logical and also facilitated the rapid estimation of other parameters using either the method of moments or the method of maximum likelihood. The Pearson 3 turns out to be the most suitable pdf to describe and to estimate return periods of drought lengths. At the monthly and weekly time scales, it was inferred that the sample size (T, months or weeks) of SHI series could be treated equivalent to the return period of the largest recorded drought length. At the annual time scale, however, the sample size (T, years) should be modified using either the Hazen or the Gringorten plotting position formula to reflect the actual return period of the largest recorded drought length in years.Editor D. Koutsoyiannis; Associate editor E. Gargouri