Search Results (122)

Evaluation of seismic risk by capturing the influences of strong motion duration and frequency contents of ground motion through probabilistic approaches is the main element of this study. Unlike most existing studies that mainly focus on intensity measures such as peak ground acceleration or spectral acceleration, this work highlights how duration and frequency characteristics critically influence dam response. To achieve this, a total of 45 ground motion records, categorized by strong motion duration (long, medium, and short) and frequency content (low, medium, and high), were selected from the PEER database. Nonlinear numerical dynamic analysis was performed by scaling each ground motion from 0.05 g to 0.5 g, with the drift ratio at the dam crest used as the Engineering Demand Parameter. It is revealed that long-duration and low-frequency ground motions induced significantly higher drift demands. The fragility analysis was conducted using a lognormal distribution considering extensive damage threshold drift ratio. Finally, the probabilistic seismic risk was carried out by integrating the site-specific hazard curve and fragility curves which yield the height risk for long durations and low frequencies. The outcomes emphasize the importance of ground motion strong duration and frequency in seismic performance and these findings can be utilized in the dam safety evaluation. Full article

Intensity–duration–frequency (IDF) curves, which relate rainfall intensity (i), storm duration (d), and return period (T), are cornerstone tools for planning, designing, and operating hydraulic works. Since Sherman’s pioneering formulation in 1931, many modern implementations have systematically omitted the duration-shifting parameter C, causing predicted intensities to diverge to infinity as $d\to 0$. This mathematical paradox becomes especially problematic under extreme hydrological regimes and convective storms exceeding 300 mm/h, where an accurate curve fit is critical. Here, we first review conventional IDF curve fitting techniques and their limitations. We then introduce IDF-GtzLo, a novel, intuitive formulation that reinstates and calibrates C directly from observed storm statistics, ensuring finite intensities for all durations. Applied to 36 automatic weather stations across Mexico, our method reduces the root mean square error by 23 % compared to the classical model. By eliminating the infinite intensity paradox and improving statistical performance, IDF-GtzLo offers a more reliable foundation for hydrological risk assessment and the design of infrastructure resilient to climate-driven extremes. Full article

Modeling heavy rainfall patterns is essential for designing hydraulic structures, planning land use and water resources, and predicting disasters, among others. Usually, heavy rainfall is characterized by curves that relate the intensity, duration, and frequency (IDF), adjusted from the analysis of pluviograms. Alternatively, these equations can be adjusted using disaggregated daily rainfall data, whose reliability is currently questioned due to the use of common coefficients to disaggregate the maximum daily precipitation (h_day) into rainfall associated with shorter durations. This study proposes the Transformation of Maximum Daily Precipitation method (TMDP) using the maximum daily precipitation of the station of interest and the curve of heavy rainfall of the nearest location, denoting the local characteristic, to transform the h_day associated with a return period into rainfall intensities for shorter durations. The TMDP proved to be slightly superior to the most widely used rainfall disaggregation method in Brazil, particularly in regions with a higher density of data for the IDF equation. The TMDP is a potential tool for regions with low density of rainfall data, although it has limitations in regions where such data are scarce. Full article

Quantifying future changes in extreme events and associated flooding is challenging yet fundamental for stormwater managers. Along the U.S. Atlantic Coast, Eastern North Carolina (ENC) is frequently exposed to catastrophic floods from extreme rainfall that is typically associated with tropical cyclones. This study presents a novel approach that uses rainfall data from five dynamically and statistically downscaled (DD and SD) global climate models under two scenarios to visualize a potential future extent of flooding in ENC. Here, we use DD data (at 36-km grid spacing) to compute future changes in precipitation intensity–duration–frequency (PIDF) curves at the end of the 21st century. These PIDF curves are further applied to observed rainfall from Hurricane Matthew—a landfalling storm that created widespread flooding across ENC in 2016—to project versions of “Matthew 2100” that reflect changes in extreme precipitation under those scenarios. Each Matthew-2100 rainfall distribution was then used in hydrologic models (HEC-HMS and HEC-RAS) to simulate “2100” discharges and flooding extents in the Neuse River Basin (4686 km²) in ENC. The results show that DD datasets better represented historical changes in extreme rainfall than SD datasets. The projected changes in ENC rainfall (up to 112%) exceed values published for the U.S. but do not exceed historical values. The peak discharges for Matthew-2100 could increase by 23–69%, with 0.4–3 m increases in water surface elevation and 8–57% increases in flooded area. The projected increases in flooding would threaten people, ecosystems, agriculture, infrastructure, and the economy throughout ENC. Full article

This data descriptor presents a unique high-resolution rainfall dataset derived from 14 pluviograph stations across central Chile’s Mediterranean region, covering variable periods starting from between 1969 and 1992, up to 2009. The dataset provides continuous precipitation records at a 5 min temporal resolution, obtained through the digitization and processing of pluviograph strip charts using specialized software. This high temporal resolution is unprecedented for the region and enables detailed analysis of rainfall intensity, duration, and frequency patterns critical for hydrological research, climate studies, and water resource management in general. Each station’s data was subjected to quality control procedures, including manual validation and correction of digitization errors to ensure data integrity. The dataset reveals the significant temporal variability of rainfall in central Chile, capturing both short-duration high-intensity events and longer precipitation patterns. By making this dataset publicly available, we provide researchers with a valuable resource for studying rainfall behavior in a Mediterranean climate zone subject to significant climate variability and change. The dataset supports various applications, including the development of intensity–duration–frequency curves, analysis of rainfall erosivity, calibration of hydrological models, and investigation of precipitation trends in the context of climate change. Full article

This study presents a multi-temporal analysis of vegetation cover changes in the Guayepo stream watershed (Cartagena de Indias, Colombia) for 2000, 2010, and 2020 and their impact on surface runoff generation. Hydrological data from 1974 to 2019 were processed to model intensity–duration–frequency (IDF) curves and simulate heavy rainfall events using six storms of nine-hour duration. Following the Soil Conservation Service guidelines, these were used to estimate runoff flows for return periods of 25, 50, and 100 years via the curve number method in HEC-HMS. Vegetation cover was assessed using the CORINE land cover methodology applied to official land use maps. The analysis revealed a significant loss of natural vegetation: dense forest cover declined dramatically from 14.38% in 2000 to 0% in 2020, and clean pastures were reduced by 46%. In contrast, weedy pastures and pasture mosaics with natural areas increased by 299% and 136%, respectively, reflecting a shift towards more degraded land cover types. As a result of these changes, total runoff flows of the model increased by 9.7% and 4.3% under antecedent moisture conditions I and II, respectively, for the 100-year return period. These findings reveal ongoing degradation of the watershed’s natural cover, linked to expanding agricultural uses and changes in vegetation structure. The decline in forested areas has increased surface runoff, elevating flood risk and compromising the watershed’s hydrological regulation. The study suggests that integrated land management and ecological restoration strategies could be key in preserving hydrological ecosystem services and reducing the negative impacts of land use change. Full article

The study examines the impacts of climate change on the operation and capacity of the combined sewer network in the historic center of Thessaloniki, Greece. Rainfall data from three high-resolution Regional Climate Models (RCMs), namely (a) the Cosmo climate model (CCLM), (b) the regional atmospheric climate model (RACMO) and (c) the regional model (REMO), from the MED-CORDEX initiative with future estimations based on Representative Concentration Pathway (RCP) 4.5, are first corrected for bias based on existing measurements in the study area. Intensity–duration–frequency (IDF) curves are then constructed for future data using a temporal downscaling approach based on the scaling of the Generalized Extreme Value (GEV) distribution to derive the relationships between daily and sub-daily precipitation. Projected rainfall events associated with various return periods are subsequently developed and utilized as input parameters for the hydrologic–hydraulic model. The simulation results for each return period are compared with those of the current climate, and the projections from various RCMs are ranked according to their impact on the combined sewer network and overflow volumes. In the short term (2020–2060), the CCLM and REMO project a decrease in CSO volumes compared to current conditions, while the RACMO predicts an increase, highlighting uncertainties in short-term climate projections. In the long term (2060–2100), all models indicate a rise in combined sewer overflow volumes, with CCLM showing the most significant increase, suggesting escalating pressure on urban drainage systems due to more intense rainfall events. Based on these findings, it is essential to adopt mitigation strategies, such as nature-based solutions, to reduce peak flows within the network and alleviate the risk of flooding. Full article

Characterizing rainfall events with recurrence periods of 1–5 years is crucial for urban flood risk assessment and water management system design. Traditional hydrological frequency analysis methods inadequately describe the temporal structure and intensity distribution of rainfall. In this study, we analyzed 1580 independent rainfall events in central Hangzhou (1950–2023) using PCA dimension reduction and K-means++ clustering to investigate typical rainfall types across different recurrence periods. The integrated approach effectively captures temporal characteristics while reducing dimensionality and improving clustering efficiency. Our results indicate that concentrated single-peak rainfall with short duration and a mid-to-late peak dominates the region, with longer recurrence periods exhibiting higher intensity, shorter duration, and greater temporal concentration. Furthermore, cumulative distribution function (CDF) and probability density function (PDF) analyses were conducted on these typical rainfall types, quantifying their distributional characteristics and yielding precise mathematical expressions. These standardized rainfall curves provide direct applications for engineering design and hydrological modeling, enabling more accurate flood prediction and mitigation strategies for Hangzhou’s urban infrastructure. Full article

Prediction of the intensity of earthquake-induced motions at the ground surface attracts extensive attention from the geoscience community due to the significant threat it poses to humans and the built environment. Several factors are involved, including earthquake magnitude, epicentral distance, and local soil conditions. The local site effects, such as resonance amplification, topographic focusing, and basin-edge interactions, can significantly influence the amplitude–frequency content and duration of the incoming seismic waves. They are commonly predicted using site effect proxies or applying more sophisticated analytical and numerical models with advanced constitutive stress–strain relationships. The seismic excitation in numerical simulations consists of a set of input ground motions compatible with the seismo-tectonic settings at the studied location and the probability of exceedance of a specific level of ground shaking over a given period. These motions are applied at the base of the considered soil profiles, and their vertical propagation is simulated using linear and nonlinear approaches in time or frequency domains. This paper provides a comprehensive literature review of the major input parameters for site response analyses, evaluates the efficiency of site response proxies, and discusses the significance of accurate modeling approaches for predicting bedrock motion amplification. The important dynamic soil parameters include shear-wave velocity, shear modulus reduction, and damping ratio curves, along with the selection and scaling of earthquake ground motions, the evaluation of site effects through site response proxies, and experimental and numerical analysis, all of which are described in this article. Full article

Regular meteorological observations in Padua started in 1725 and have continued unbroken up to the present, making the series one of the longest in the world. Daily mean temperatures and precipitation amounts have recently been homogenized for the entire 1725–2024 period, making it possible to add new measurements without further work. Starting from the temperature series, the trends of cold and warm spells are investigated in this paper. The ongoing warming that started in the 1970s is extensively analyzed on the basis of the variability of the mean values and a magnitude index that captures both the duration and intensity of a spell and by investigating the frequency of extreme events by means of Intensity–Duration–Frequency curves. The periods with the greatest deviation from the climatological average are analyzed in detail: February 1740 and April 1755, the months with the largest negative and positive temperature anomalies, respectively, in the 300-year-long series. Moreover, the analysis of snow occurrences extracted from the original logs, together with the pressure observations from the long series of London and Uppsala, made it possible to evaluate the most typical synoptic situations leading to snow events in Padua for the whole period. Full article

It is essential to understand the characteristics of surface runoff generating processes under different heavy rainfall events in mountainous areas. The intensity and duration of precipitation play an important role in surface runoff processes. In this study, annual rainfall characteristics from 1987 to 2023 in the Taihang Mountains were analyzed using the Pearson-III frequency curve, homogeneity tests, and the Mann–Kendall (MK) test. Four surface runoff generation events between 2014 and 2023 were monitored. The contribution of rainfall to runoff variations was quantified through the double mass curve method. Results indicate a significant increase in the frequency of moderate and heavy rainfall events over the last decade. Spatial variability of rainfall and elevation effects in the Taihang Mountains becomes less pronounced when 24 h rainfall is below 50 mm. The two surface runoff processes in 2016 and 2023 were typical runoff resulting from excess rain, which belonged to the storm runoff. The two surface runoff processes in 2021 were runoff generation under saturated conditions. For runoff generation under saturated conditions, the contribution of rainfall was only 58.17%. When the runoff coefficient exceeded 0.5, the surface runoff generating processes were entirely determined by rainfall. This study suggested that for semi-arid regions, where rainfall is unevenly distributed over the seasons, more soil water is needed to maintain local and downstream water demand during the non-rainy season. The limitations of the study are the lack of research on factors other than rainfall that intrinsically affect the surface runoff generating process. Full article

The pastoral areas of Ethiopia are facing a recurrent drought crisis that significantly affects the availability of water resources for communities dependent on livestock. Despite the urgent need for effective drought early warning systems, Ethiopia’s pastoral areas have limited capacities to monitor variations in the intensity–duration–frequency of droughts. This study intends to drive drought intensity–duration–frequency (IDF) curves that account for climate-model uncertainty and spatial variability, with the goal of enhancing water resources management in Borana, Ethiopia. To achieve this, the study employed quantile delta mapping to bias-correct outputs from five climate models. A novel multi-model ensemble approach, known as spatiotemporal reliability ensemble averaging, was utilized to combine climate-model outputs, exploiting the strengths of each model while discounting their weaknesses. The Standardized Precipitation Evaporation Index (SPEI) was used to quantify meteorological (3-month SPEI), agricultural (6-month SPEI), and hydrological (12-month SPEI) droughts. Overall, the analysis of historical (1990–2014) and projected (2025–2049, 2050–2074, and 2075–2099) periods revealed that climate change significantly exacerbates drought conditions across all three systems, with changes in drought being more pronounced than changes in mean precipitation. A prevailing rise in droughts’ IDF features is linked to an anticipated decline in precipitation and an increase in temperature. From the derived drought IDF curves, projections for 2025–2049 and 2050–2074 indicate a significant rise in hydrological drought occurrences, while the historical and 2075–2099 periods demonstrate greater vulnerability in meteorological and agricultural systems. While the frequency of hydrological droughts is projected to decrease between 2075 and 2099 as their duration increases, the periods from 2025 to 2049 and from 2050 to 2074 are expected to experience more intense hydrological droughts. Generally, the findings underscore the critical need for timely interventions to mitigate the vulnerabilities associated with drought, particularly in areas like Borana that depend heavily on water resources availability. Full article

This is a database containing rainfall intensity–duration–frequency equations (IDF equations) for 6550 pluviographic and pluviometric stations in Brazil. The database was compiled from 370 different publications and contains the following information: station identification, geographic position, size and period of the rainfall series used, parameters of the IDF equations, and literature references. The database is available on Mendeley Data (DOI: 10.17632/378bdcmnc8.1) in the form of spreadsheets and vector files. Since the launch of the Pluvio 2.1 software in 2006, which included 549 IDF equations obtained in the country, this is the largest and most accessible database of IDF equations in Brazil. The data provided may be useful, among other purposes, for designing hydraulic structures, controlling water erosion, planning land use, and water resource planning and management. Full article

Climate change has the potential to significantly impact various aspects of Earth’s climate systems, including precipitation patterns, necessitating region-specific action plans. This study examines the Wadi Al Rummah region in Qassim province, Saudi Arabia, by analyzing Intensity-Duration-Frequency (IDF) curves across six locations, utilizing observed daily precipitation data from 1986 to 2014. The nonparametric quantile mapping method was employed to adjust the outputs of eight Regional Climate Models (RCMs) within the CMIP6 ensemble. These models were evaluated under four Shared Socioeconomic Pathways (SSPs), ranging from a stringent mitigation scenario to one with very high greenhouse gas emissions. Also, two statistical tests, namely the Kolmogorov-Smirnov and Chi-Square tests, were used to assess the best-fitting distribution to estimate the maximum rainfall values. Temporal disaggregation of daily precipitation data was performed using the K-nearest neighbors (KNN) method. The IDF curves were generated for both historical and three projected future periods using Gumbel distribution, which proved to be the best-fitting statistical model, using six return periods: 2, 5, 10, 25, 50, and 100 years. Results indicate that high-emission scenarios and longer timeframes exhibit greater uncertainty in IDF projections. Additionally, rainfall intensity is expected to increase over shorter durations, with significant increases observed in Buriydah and Nabhaniyah under SSP 8.5. In contrast, Al Rass, Badayea, and Al Mithnab show mixed trends, while Unaizah shows little to no significant change. These findings emphasize the need for sustainable development and adaptive strategies to mitigate risks in Qassim province, as climate impacts are projected to intensify, particularly in the short to long term. Full article

Acoustic monitoring facilitates the detailed study of herbivore grazing by generating a timeline of sound bursts associated with jaw movements (JMs) that perform bite or chew actions. The unclassified stream of JM events was used here in an observational study to explore the notion of “grazing time”. Working with shepherded goat herds in a wooded landscape, a horn-based acoustic sensor with a vibration-type microphone was deployed on a volunteer animal along each of 12 foraging routes. The software-generated timeline of unclassified JMs contained a total of 334,582 events. After excluding rumination bouts, minutely JM rates showed a broad, non-normal distribution, with an overall mean of 61 JM min⁻¹. The frequency distribution of inter-JM interval values scaled logarithmically, with a peak in the region of 0.43 s representing a baseline interval that generates the unconstrained, more-or-less regular, rhythm of jaw movement (≈140 JM min⁻¹). This rhythm was punctuated by interruptions, for which duration scaled logarithmically, and which were primarily related to the search phase of the intake process. The empirical time accumulation curve shows the contribution of the inter-JM interval to the total foraging time and provides a penetrating profile of how the animal interacted with the foraging environment. The sum total of time along a foraging route spent at a near-potential JM rate was only ≈1 h, whereas sub-potential rates containing intervals as long as ≈30 s accounted for the bulk of the foraging route. The dimensionless behavioral grazing intensity was defined as the product of the number of ingestive JMs performed and the baseline interval, divided by the duration of the foraging route (excluding rumination). Values were mostly <0.5 for the foraging routes examined. This has implications for how animal presence should be translated to grazing pressure and for how long animals need to forage to meet their nutritional requirements. Full article