Maximum Daily Rainfall Research Articles

Utilizing statistical distribution tests to develop rainfall intensity–duration–frequency curves for enhanced hydrological analysis in Kirkuk city, Iraq

ABSTRACT Rainfall intensity is considered one of the basic factors in designing hydrological models based on rainstorm data. The objective of this research is to employ novel intensity–duration–frequency curves and develop empirical equations for rainfall intensity in the city of Kirkuk. The reduction formula adopted by the Indian Meteorological Department was used to divide the maximum daily rainfall for short periods of 0.5, 1, 2, 4, 6, 12, and 24 h. Three key methods of frequency analysis (lognormal distribution, log Pearson type III distribution, and Gumbel extreme value distribution) were utilized to formulate a statistical relationship based on rainfall intensity data from between the years 1981 and 2023 for a gauging station upstream of the Kirkuk city basin to provide the best data set for all periods of 100, 50, 25, 10, 5, and 2 years. Research has shown that the logarithmic distribution is the best fit for modelling the relationship between the annual maximum rainfall at Kirkuk station and duration of the rainfall. The goodness-of-fit results indicate that the lognormal distribution statistically outperforms other distribution models. Hence, the generated rainfall intensity, duration, and frequency curves that were developed led to estimating the intensity of precipitation to build forecasting and hydrological behaviour of the Kirkuk city basin.

Attributions of Rainfall Anomalies to Weather Systems and Their Spatial and Temporal Variabilities: A Case Study of Victoria in Southeast Australia

ABSTRACTAttributions of rainfall anomalies to weather systems and their spatio‐temporal variability in Victoria, southeast Australia are investigated with a multimethod weather type dataset and two popularly used gridded daily rainfall datasets for the period 1979–2015. The rainfall anomalies before, during and after the Millennium Drought (1997–2009) are compared to quantify the temporal variability of rainfall responses to weather type changes. The results show: (1) Three weather systems (Front, Cyclone and Thunderstorm) and their combinations contribute 89% of total rainfall; (2) Contributions of weather types to rainfall vary from month to month with winter season rainfall coming from more diverse weather types than summer rainfall; (3) The contributions of weather types to rainfall in three periods show temporal variabilities and there is a clear shift of contribution pattern after the Millennium Drought, such as front‐thunderstorm (FT) is now the largest contributor to rainfall compared with cyclone‐frontal‐thunderstorm (CFT) before and during the Millennium Drought; (4) A seasonal shift in the post‐drought period is found with higher rainfall in February and March and lower rainfall in September and October. The increased rainfall in February mainly results from Front–Thunderstorm (FT) and Thunderstorm‐only (TO), while rainfall declines in September from all weather types; (5) Several rainfall characteristics that are important for streamflow generation, such as rainfall intensity, probability of rainfall occurrence, number of rainfall days and the maximum daily rainfall, do depend on the weather types; (6) The results are similar with different rainfall datasets, but differences do exist, especially at the local scale. The conclusions of this study are drawn from an Australian case study but have implications for other regions to investigate the attributions of rainfall characteristic changes to weather systems.

PERBANDINGAN ANALISA DEBIT BANJIR PADA SUNGAI MENCONGAH KABUPATEN LOMBOK BARAT

Many unit hydrograph concepts are used to carry out the transformation from rainfall to flow discharge. The data needed to derive a measured unit hydrograph in the watershed under consideration is automatic rainfall data and discharge recording at certain observation points. A hydrograph can be described as a graphic presentation of one of the elements of flow and time. The purpose of the design flood discharge analysis is to evaluate the magnitude of the design flood discharge at various return periods of 2, 5, 10, 20, 25, 50, 100 years. This research is a case study using rainfall data for 10 years, namely 2014-2023. Next, an analysis of the maximum daily rainfall in the Mencongah watershed (watershed) was carried out, climatological data obtained from the relevant agencies. After analyzing the rainfall data obtained in the field, the maximum annual rainfall in the Mencongah watershed was obtained based on the results of data analysis from the Mencongah station, which was 229 mm, while the average rainfall was 167.9 mm, a large value.PMP (Probable Maximum Precipitation) on the Mencongah river is 85.37 mm, the design flood discharge with return periods of 2, 5, 10, 20, 25, 50 and 100 years using the Hapers method is obtained respectively: 72.21 m³; 180.525 m³, 361.05 mm, 722.101 m³, 902.626 m³, 1805.252 m³, 3610.504 m³,while the Melchior method discharge is 191,517 m³; 478,793 m³; 957,586 m³; 1915.171 m³; 2393,964 m³; 4787 m³; and 9575.855 m³

Increasing dam failure risk in the USA due to compound rainfall clusters as climate changes

A changing climate, with intensifying precipitation may contribute to increasing failures of dams by overtopping. We present the first analysis of rainfall sequences and events associated with recent hydrologic failures of 552 dams in the United States. We find that the maximum 1-day rainfall associated with failure was often not extreme compared to dam spillway design criteria, even when accounting for rainfall statistics changing with time at each site. However, the combination of the total rainfall 5 to 30 days prior and the maximum 1-day rainfall associated with dam failure is rare. Persistent atmospheric circulation patterns that lead to recurrent rainfall events, rather than just more moisture in the atmosphere is a possible reason. The probability of these compound precipitation risks has increased across much of the country. With over 90,000 aging dams still in service, the increasing likelihood of intense rainfall sequences raises concerns about future dam failures.

ANALISIS INTENSITAS CURAH HUJAN DAN KURVA IDF (INTENSITY-DURATION-FREQUENCY) METODE MONONOBE DI KOTA SALATIGA

Extreme rainfall in Indonesia has led to natural disasters in many areas including Salatiga City. Many human activities depend on the amount of rainfall that falls on the earth's surface. In the field of civil engineering, research on rainfall is very common because many activities related to civil engineering use rainfall data such as for water resource management, drainage development, dam construction and other building construction. This study aims to determine the amount of rainfall intensity and IDF curves in Salatiga City for return periods of 2 years, 5 years, 10 years, 25 years, 50 years and 100 years. The data used in this study is the maximum daily rainfall data collected from Salatiga Central Bureau of Statistics (BPS). The type of distribution selected in this study is the Log Pearson Type III probability distribution. The results of the analysis show that the highest rainfall intensity occurs at a short duration (5 minutes) in the 100-year return period of 106.66 mm/hour and the results of the IDF curve show that the shorter the rainfall time, the higher the rainfall intensity while the longer the rainfall time, the smaller the rainfall intensity at each return period T.

A Comprehensive Evaluation of Mean and Extreme Climate for the Conformal Cubic Atmospheric Model (CCAM)

Abstract This study evaluates the performance of the Conformal Cubic Atmospheric Model (CCAM) in dynamically downscaling fifth major global reanalysis produced by European Centre for Medium-Range Weather Forecasts (ECMWF) (ERA5) reanalysis data from 1985 to 2014, following a 5-yr spinup period. It focuses on daily maximum and minimum temperatures and daily precipitation, comparing CCAM to ERA5 and the Australian Gridded Climate Data (AGCD). The CCAM effectively reduces warm biases in daily minimum temperatures but struggles with cold biases in daily maximum temperatures, particularly in northern Australia during the wet season, possibly due to high-level cloud overestimation. Precipitation tends to be overestimated, especially in extreme rainfall events, though offset by an underestimation of low rainfall. The study showcases improvements in the annual minimum of daily minimum temperatures across most of Australia, while identifying challenges in forecasting cooler extreme temperatures. It adds value to annual maximum daily maximum temperatures in southern Australia but less so in the north. The analysis of the 5% annual exceedance probability (AEP5%) yields mixed results influenced by location and potential ocean temperature changes. Some coastal areas exhibit lost value, possibly linked to ocean temperature shifts. Furthermore, CCAM’s representation of maximum annual daily and 5-day rainfall reveals lost value, particularly in eastern Australia due to an overestimate of extreme rainfall. Despite the challenges of comparing a dynamical downscaling model like CCAM to ERA5, this study highlights its benefits in reducing biases, especially in temperature representation. Given the larger biases in phase 6 of Coupled Model Intercomparison Project (CMIP6) global climate models, CCAM appears suitable for dynamic downscaling in climate projections, emphasizing the need for ongoing model enhancements, including addressing biases related to ephemeral water bodies and extreme rainfall. Significance Statement This study critically assesses the performance of the Conformal Cubic Atmospheric Model (CCAM) in dynamically downscaling ERA5 reanalysis data from 1985 to 2014, offering valuable insights into climate modeling. Focusing on temperature and precipitation, CCAM proves effective in mitigating warm biases in daily minimum temperatures but encounters challenges with cold biases in daily maximum temperatures, particularly in northern Australia. The analysis reveals the overestimation of precipitation, especially in extreme events, yet identifies improvements in annual minimum daily minimum temperatures across Australia. The study underscores CCAM’s potential in reducing biases compared to CMIP6 global climate models, making it a promising tool for dynamic downscaling in climate projections. It emphasizes the necessity for ongoing model enhancements, particularly addressing biases related to ephemeral water bodies and extreme rainfall.

Characteristics of Overburden Damage and Rainfall-Induced Disaster Mechanisms in Shallowly Buried Coal Seam Mining: A Case Study in a Gully Region

Shallow coal mining in gully regions has resulted in significant subsidence hazards and increased the risk of surface water inflow into mining panels, compromising the sustainability of surface water management and underground resource exploitation. In this study, the chain disaster process caused by shallow coal seam mining and heavy rainfall is quantitatively analyzed. The findings reveal that shallow coal seam mining leads to the formation of caved and fractured zones in the vertical direction of the overlying rock. The fractured zone can be further classified into a compression subsidence zone and a shear subsidence zone in the horizontal direction. The shear subsidence zone is responsible for generating compression and shear deformations, intercepting rainfall runoff, and potentially triggering landslides, necessitating crack landfill treatments, which are critical for promoting sustainable mining practices. The HEC-RAS program was utilized to integrate annual maximum daily rainfall data across different frequencies, enabling the establishment of a dynamic risk assessment model for barrier lakes. Numerical simulations based on unsaturated seepage theory provide insights into the infiltration and seepage behavior of rainfall in the study area, indicating a significant increase in saturation within lower gully terrain. Precipitation infiltration was found to enhance the saturation of the shallow rock mass, reducing matric suction in unsaturated areas. Finally, the disaster chain is discussed, and recommendations for managing different stages of risk are proposed. This study offers a valuable reference for the prevention and control of surface water damage under coal mining conditions in gully regions.

Distribution of Rain Intensity: Daily Maximum Rainfall Data in The Province of South Sumatera and West Sumatera

The high intensity of rain in May 2024 caused flooding in the Sumatra region, especially Padang City and Palembang City. The region of West Sumatra is also known as the ethalae of disasters with frequent earthquakes, floods, and landslides. In Indonesia, many frequency analyses are conducted using the Gumbel distribution without testing data and clear hydrological reasons. It is feared that this method is considered as a routine way, thus causing the risk of unwanted deviations, resulting in many disasters and errors in the planning of water buildings. This research aims to determine and know the type of distribution that is representative for the maximum daily rainfall frequency in West Sumatra and South Sumatra Provinces as a reference for development and disaster mitigation in the region. The research location is in West Sumatra and South Sumatra. The data used for this study were taken from daily maximum rainfall data from rain stations for 35 to 40 years from 24 rain stations in West Sumatra Province, and 16 rain stations for South Sumatra region. This type of research is development research with the 4D development model (Define, Design, Develop, Disseminate). The development method consists of four different phases: Initial Investigation, Design, Realisation and Development. The data of each station was then organised into two types of data series, namely the annual maximum data series and the annual minimum data series. The results of this data series test are expected to follow one or more types of distributions commonly used in Hydrology and Drainage. The distribution results obtained for the South Sumatra region are Gama-III and LP-III, while for the West Sumatra region the distribution types are Gama-III, LP-III Normal Log and Gembel. The conclusion obtained is that West Sumatra does not have only one type of distribution. For the type of test using the SPSS.22 application, the results obtained are goodness of fit test, parametric test, Chi-Square test, Kolmogorov Smirnov test and Anderson-Darling test and Histrogram (visual) method.

Assessing the current and future trends of climate extremes at Zarima subbasin North Western Ethiopia

Climate extreme events in Ethiopia have increased, impacting the country’s agriculture dependent economy. Localized studies on rainfall extremes provides valuable insights to develop mitigation measures. This study focuses on the analysis of rainfall extremes for the observed (1984–2018) and the future mid time period (2031–2065) and end time period (2066–2100) projected under RCP4.5: moderate emissions reduction scenario aiming to stabilize greenhouse gas concentrations by the mid-21st century and RCP8.5: high emissions scenario with continued increase in greenhouse gas emissions throughout the twenty-first century. Trend analysis was done using R statistical software modified Man Kendell package. The result revealed that the observed total rainfall in wet days (PRCPTOT) showed insignificant declining trend across the subbasin. Under the RCP4.5 scenario, mid time period projections indicated increasing trends in PRCPTOT at Maytsebri, Adiremet and Debarik stations while decreasing trends expected at Ketema Niguse and Zarima stations. In the RCP4.5 end time period, Debarik and Zarima stations showed increasing trends while other stations exhibited decreasing trends. Under the RCP8.5 scenario, PRCPTOT showed insignificant decreasing trend except Ketema Niguse station which showed significant increasing trend during the mid time period. The observed annual maximum 1-day rainfall (RX1day) and annual RX5day rainfall had both positive and negative trends over subbasin. The RCP4.5 scenario projected declining trends in annual RX1day rainfall, while the RCP8.5 scenario projected increasing trends, except the end time projection of Debarik station. Consecutive dry days (CDD) increased and Consecutive wet days (CWD) decreased insignificantly in majority the subbasin. Projections indicated higher CDD and decreased CWD are expected in majority of the subbasin area. These finding implied that further investigation is required on the impact of climate extremes.

Design storm parameterisation for urban drainage studies derived from regional rainfall datasets: A case study in the Spanish Mediterranean region

ABSTRACT A significant amount of information on regional rainfall characteristics is available nowadays, allowing its use in hydrological applications. This article is motivated by the availability of regional studies regarding maximum daily rainfall and intensity–duration–frequency curves that can be coupled with the design storm concept for urban hydrology studies. This is accomplished through a convenient index describing temporal variability of rainfall. More precisely, a methodology for regionalising the two parameters (i0, φ) of the two-parameter gamma design storm (G2P) is developed herein. A three-step methodology is proposed for obtaining the two parameters (i0, φ) for a given location. The results obtained in a case study show coherence with previous studies concerning maximum rainfall statistics.

Towards evaluating the conditional probability of waterborne microbial risks associated with critical rainfall events following land application of animal waste — A focus on Irish pastures

ABSTRACT Modelling surface runoff and infiltration in an agricultural watershed is essential for understanding the nutrient cycle and water quality management. This research evaluates the critical rainfall events causing maximum surface runoff and infiltration. Empirical models such as Soil Conservation Service (SCS) curve number and Explicit Green-Ampt (EGA) were analysed for different soil hydraulic conditions and storm events with specific return periods. The present study forecasted the maximum daily rainfall and intensity as 113.6 mm and 19.9 cm h–1, respectively, considering a 100-year return period storm. The deterministic part of the model calculates the daily maximum surface runoff as 5.51 cm (from the SCS model). The EGA model revealed that the rainfall intensity of 0.143, 0.163, 0.175, 0.179, 0.181, 0.182, and 0.182 cm h−1 (duration of 24 h) was found critical for 1, 2, 5, 10, 25, 50, 100 year return period of the storm, respectively in different soil texture classes (sand, loamy sand, sandy loam, loam, silt loam, sandy clay loam, clay loam, silty clay soils). Exceptions imply for three occasions where the intensity of 0.407 cm h−1 and duration of 18 h produced maximum infiltration for silty clay loam, and intensity of 0.352 and 0.354 cm h−1 with 9 h rainfall (each) produced maximum infiltration for clay. The probabilistic model revealed that a daily storm event probability of 2.74 × 10–5 is associated with a simulated mean runoff depth of 0.69 cm and infiltration of 20.7 cm. Critical rainfall probabilities calculated in this study can be multiplied with the overall microbial/pollutant human health risk assessment framework to calculate conditional probability and better estimate microbial risk through the drinking water pathway. This study is very relevant for the wet climatic condition of Ireland, where most land use is pastures.

Enhancing adoption studies of LID-BMP’S for Storm Water Management Drainage (SWMD) national stadium in Jayapura, Indonesia

The essential of this paper is implementing Low Impact Development (LID) type stormwater Best Management Practices (BMP’s) to reduce stormwater run-off in urban areas. The case study taken is the development area of Jayapura National Stadium. The drainage system at the main stadium is divided into subsurface and surface drainage. Meanwhile, the development area will enhance the study of adopting several LID-BMP’s practices to manage and optimize the design to control stormwater run-off in the stadium before it is discharged into the urban drainage system. The methodology in this study is divided into data collection and planning. The data collected include daily maximum rainfall data, stadium master plan, soil investigation, macro drainage system, drainage master plan, and topography around the stadium. Meanwhile, planning includes calculating rainfall design, soil structure analysis, hydraulic planning, pipe dimensions, and planning for water storage. The rainfall design used is a 5-year return period with Log Person III, the best design from the suitability test analysis, which is 134.39 mm/day. The study examined drainage design effectiveness to control stormwater run-off on the drainage design at the main stadium and surrounding stadiums using the LID-BMP’s framework and compared them. The LID-BMP’s adoption study was to optimize the drainage design to obtain maximum run-off control that can reduce up to 7-10% of stormwater run-off due to design and soil structure. The results provided recommendations to the authorities to modify the current design to achieve the benefits.

Predicting Damage Characteristics of Heavy Rain Disasters Using Artificial Neural Network

Heavy rain disaster is a representative natural disaster in Korea, and causes considerable damage every year as a result of typhoons and heavy rain. Various preventive measures and reduction facilities have been introduced to reduce heavy rain damage, but damage continues to occur. Accurate damage prediction is necessary for preemptive response to heavy rain disasters. A prediction study of the damage characteristics of such disasters using machine learning was conducted. Artificial neural network (ANN) was applied as a machine learning technique, and damage data of the aforementioned disasters from 1999 to 2019 were used. Damage prediction using an ANN was analyzed in terms of total rainfall, maximum daily rainfall, and total damage amount. The prediction of the damage characteristics was most accurate for the total damage amount. Total and daily maximum rainfall are less correlated with the characteristics of various damage amounts, which may explain the low accuracy of the analysis.

Future Changes in Hydro-Climatic Extremes across Vietnam: Evidence from a Semi-Distributed Hydrological Model Forced by Downscaled CMIP6 Climate Data

Flood hazards have led to substantial fatalities and economic loss in the last five decades, making it essential to understand flood dynamics in a warming climate. This study reports the first comprehensive assessment of projected flood hazards across Vietnam. We used downscaled climate data from the CMIP6 initiative, involving a total of 20 climate models, and streamflow projection simulated using a semi-distributed hydrological model. The assessment covers seven near-natural catchments, each representing a climate zone of the country. To evaluate climate change impacts on floods, the study simultaneously analyzes changes in three indices: (i) the annual hottest day temperature, to represent temperature extremes; (ii) the maximum daily rainfall amount, to represent rainfall extremes; and (iii) the discharge value exceeding 5% in a year, to assess streamflow extremes. Changes in the selected indices (relative to the reference period from 1985 to 2014) are assessed under four emission scenarios (SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5) and two future time slices (2036–2065 and 2070–2099). Although the robustness (as indicated by multi-model agreement) and significance (identified through the statistical test) of the changes vary substantially, depending on the selected indices and assessed time slices, an overall increase is consistently identified across all of the assessed hydro-climatic extremes (up to 4.8 °C for temperature extremes, 43 mm for rainfall extremes, and 31% for streamflow extremes). The findings suggest a potential increase in flood risk across Vietnam in a warming climate, highlighting the urgent need for improved flood preparedness and investment to reduce economic loss and mortality in an uncertain future.

Hydrological Modelling with HEC-HMS in Krueng Peudada Sub-Watershed Bireuen Regency

The flood that occurred in Krueng Peudada was influenced by several factors, such as watershed conditions. Heavy rains caused Krueng Peudada to overflow so that a number of villages adjacent to the river were submerged. Based on these problems, to minimize the occurrence of flooding in Krueng Peudada building, namely by carrying out occurrence of flooding in Krueng Peudada to be used to obtain peak discharge as a reference in building planning in Krueng Peudada using HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modelling System). The benefit of the research is that the resulting model can be useful as a guide in calculating flood discharge considerations. The scope of this research includes the research location at Krueng Peudada using annual maximum daily rainfall data, calculating the return period of rainfall using of Gumbel probability distribution, Normal Log, Normal, and Pearson III Log as the basis for calculating the discharge and continuing the calculation of the hours with Manonobe and ABM. The results of calculations of the Nakayasu Synthetic Unit Hydrograph Method and running from HEC-HMS found that the flow that occurred in the Krueng Peudada two sub-watershed was 2903m3/second and 2723,0 m3/second, it can be concluded that in determining watershed management the flood discharge obtainded has error as much as 6,2%. The difference in the results obtained is due to the number of sub-watersheds in the watershed based on different flows and the value of the curve number for each area of the sub-watershed.

Quantifying impacts of precipitation scenarios projected under climate change on annual probability of rainfall-induced landslides at a specific slope

Because of climate change, the intensity, duration, and frequency of future extreme rainfalls are projected to increase in many regions worldwide according to results from global climate models (GCMs). As rainfall is a major triggering factor for landslides, the frequency and risks of landslides are expected to increase. Consequently, it is crucial to quantify the impacts of climate change on landslide risks at a specific site. This study develops a statistical downscaling method based on the generalized extreme value (GEV) distribution and a probabilistic method for assessing the annual probability of rainfall-induced landslides at a specific site under projected precipitation scenarios from GCMs. The GEV-based statistical downscaling method bridges the gap between site-specific extreme rainfall (e.g., annual maximum 1-day rainfall) projection for a future scenario and GCM outputs with large spatial and temporal scales. A physics-based slope model is also used to properly depict slope failure mechanisms. The results indicate that the projected increase in extreme rainfall due to climate change leads to increases in annual frequency of heavy rainstorms and the annual slope failure probability, which are primarily controlled by the increase in the standard deviation, instead of the mean, of future extreme rainfalls.

A Comparison of Spatial Interpolation Methods for Regionalizing Maximum Daily Rainfall Data in South Sulawesi, Indonesia

The aim of this research is to compare between the Inverse Distance Weighted (IDW) and Ordinary Kriging (OK) interpolation methods for regionalization of areas within the South Sulawesi province based on maximum daily rainfall. The data utilized consists of maximum daily rainfall data from 56 rain stations within the South Sulawesi from 1986 to 2021. The spatial interpolation methods applied include the power 2 IDW, and OK. Various semivariogram models, namely Spherical, Gaussian, and Exponential, are employed within the OK method. The selection of the best method is based on the smallest Root Mean Square Error (RMSE) and Mean Absolute Error (MAE) values. The findings of this research reveal that the optimal method for regionalization of maximum daily rainfall is the OK method with a Gaussian semivariogram model. The RMSE values for this method are 57.45, and the MAE values are 46.49. The results of the spatial interpolation demonstrate that the South Sulawesi is divided into four zones characterized by maximum daily rainfall (in mm) as follows: Zone I: less than 230 mm (Eastern and Southeastern regions), Zone II: 230-260 mm (Northern region), Zone III: 260-280 mm (Western region), and Zone IV: more than 280 mm (Southwestern region).

Rainfall characteristics during pre- and post-onset of local climate change in Aceh Besar District, Indonesia

Climate change caused by global warming, which is characterized by increasing temperatures on the earth’s surface, is the biggest problem in the world today. This study attempts to examine how local climate change has affected the characteristics of rainfall in Aceh Besar District, which is situated in the far north of Indonesia’s Sumatra Island. 2001 was assumed to be the onset of local climate change in the region. Using EasyFit, probability distribution that best fits the rainfall data during the pre- and post-onset of climate change is chosen. The results indicated that the annual rainfall amount has increased over the past decade. The probability of receiving an annual total rainfall exceeding the long-term average (1700 mm) has increased significantly after the local climate change. Meanwhile, although the lowest and highest amounts of annual maximum daily rainfall for pre- and post-onset periods remain the same, the frequency of the maximum daily rainfall in a year greater than 140 mm/day was doubled during the post-onset period. Consequently, local climate change has increased the expected amount of annual maximum daily rainfall for return periods of 2, 5, and 10 years.

Trend analysis of rainfall data using Mann-Kendall test and sen's slope estimator

Rainfall is the most important fundamental physical parameter among the climate, as this parameter determines the environmental condition of the particular region, which affects the agricultural productivity. Global warming or climate change, is one of the most important worldwide issues discussed among scientists and researchers. One of the consequences of climate change is the alteration of rainfall patterns and an increase in temperature. The drastic changes in rainfall pattern showed a significant impact on society, and therefore its up-to-date information is needed to estimate the spatial distribution and variability at all points of the territory. In this paper, a study on trend analysis of rainfall data observed at Anasi, Haliyal, Kadra, and Supa rain gauge stations in Karnataka, India, was carried out. For this purpose, the annual 1-day maximum rainfall (AMR) and annual total rainfall (ATR) series were generated from the daily rainfall data and used in trend analysis. A non-parametric Mann-Kendall (MK) test was applied to evaluate the presence of significant trend in AMR and ATR, while the rate of significant trend was computed by Sen's slope estimator (SSE). The MK test results indicated that there is a decreasing trend in AMR series of Anasi, Haliyal, Kadra, and Supa. The study showed that the rate of decreasing trend in the AMR series of Anasi, Haliyal, Kadra, and Supa is computed as 1.4 mm/year, 0.1 mm/year, 0.6 mm/year, and 0.2 mm/year, respectively. For the ATR series, the rate of decreasing trend for Anasi was computed as 23.8 mm/year, whereas 11.2 mm/year for Supa, whereas the rate of increasing trend was 4.3 mm/year for Haliyal and 2.2 mm/year for Supa. This paper illustrated the application of the MK test and SSE for analyzing the trend in AMR and ATR of Anasi, Haliyal, Kadra, with Supa and the results obtained from the study.

Changing Urban Temperature and Rainfall Patterns in Jakarta: A Comprehensive Historical Analysis

The increasing global population and in-country migration have a significant impact on global land use land cover (LULC) change, which reduces green spaces and increases built-up areas altering the near-surface radiation and energy budgets, as well as the hydrological cycle over an urban area. The LULC change can lead to a combination of hazards such as increasing urban temperatures and intensified rainfall, ultimately resulting in increased flooding. This present study aims to discuss the changing pattern in urban temperature, daily rainfall, and flooding in Jakarta. The daily urban temperature and daily rainfall were based on a 30-year dataset from three meteorological stations of Jakarta in the period between 1987 and 2013. The changing trend was analyzed by using the Mann–Kendall and the Pettitt’s tests. The relation between daily rainfall and flooding was analyzed using a 30-year flooding dataset collected from several sources including the international disaster database, research, and newspaper. The results show that there was an increasing trend in the daily temperature and the daily rainfall in Jakarta. The annual maximum daily temperature showed that an increasing trend started in 2001 at the KMY station, and in 1996 at the SHIA station. In general, the highest annual maximum daily temperature was about 37 °C, while the lowest was about 33 °C. Moreover, the maximum daily rainfall started increasing from 2001. An increase in the maximum daily rainfall was observed mainly in January and February, which coincided with the flood events recorded in these months in Jakarta. This indicates that Jakarta is not only vulnerable to high urban temperature but also to flooding. While these two hazards occur in distinct timeframes, there is potential for their convergence in the same geographical area. This study provides new and essential insights to enhance urban resilience and climate adaptation, advocating a holistic approach required to tackle these combined hazards.