100-year Rainfall Research Articles

Assessing Soil Erosion in Bireuen District Aceh using USLE and GIS Models

Intensive land use in various fields allows land degradation to occur. One form of land degradation is soil erosion. This research aims to get an overview of the distribution of soil erosion in Bireuen Regency on various land uses. This research uses a descriptive survey research method with the Universal Soil Loss Equation (USLE) method approach and Geographic Information Systems. This research was conducted from June to August 2024, and the research area covered 17 sub-districts in the Bireuen district. To generate erosion distribution, data such as 10-year rainfall, land use type and soil biophysics were used. These data were obtained from BMKG, the World Rainfall Data Centre (CHRIPS), the Geospatial Information Agency, and DEMNAS. The data was then analyzed using the USLE equation and Arc GIS.10.8 software. The results of data analysis obtained that the distribution of soil erosion rates in Bireuen Regency consists of 0-20 tonnes/ha/year covering 84,297 ha, 20-60 tonnes/ha/year covering 41,327.34 ha, 60-180 tonnes/ha/year covering 32,954.82 ha, 180-480 tonnes/ha/year covering 17050.34 ha, and > 480 tonnes/ha/year covering 3,502.48 ha. Based on the classification of erosion hazard classes, the Bireuen Regency area has erosion at a very light-heavy level. The government and other stakeholders must apply sufficient soil conservation technology to produce sustainable land use.

Dynamic Analysis and Hazard Assessment of Debris Flows in Donghaolitaogao

Utilizing the FLO-2D software, the motion processes of debris flows in Donghaolitaogao under 20-year, 50-year, and 100-year return periods of rainfall are analyzed, revealing that as the rainfall return period increases, the debris flow velocity, accumulation depth, and accumulation area all significantly expand. Specifically, under the 20-year, 50-year, and 100-year rainfall conditions, the maximum debris flow velocities are 1.85 m/s, 1.95 m/s, and 1.99 m/s, respectively, while the maximum accumulation depths are 1.31 m, 1.33 m, and 1.35 m, and the total accumulation areas are 27,267.8 m2, 31,500.6 m2, and 33,901.3 m2, respectively. Using the depth of debris flow and the product of debris flow depth and velocity as evaluation indicators, the debris flow hazard assessment indicates that the Donghaolitaogao debris flow is primarily characterized by low- and medium-risk areas, with high-risk areas scattered sporadically along the central part of the channel. Moreover, as the rainfall return period increases, the area of high-risk zones continues to expand, gradually accounting for a larger proportion of the total hazard zone.

Spatially seamless and temporally continuous assessment on compound flood risk in Hong Kong

Compound flooding results from the simultaneous occurrence of extreme storm surges, sea level rise, and heavy rainfall. These events often lead to impacts significantly more severe than those caused by any individual flood-inducing factor alone. However, the limited and sparse data from tidal gauges hampers precise risk assessment at ungauged sites in coastal cities. Our study addresses this gap by integrating ensemble machine learning with Bayesian inference, offering a comprehensive spatial–temporal analysis of compound flood risk from 1979 to 2022 in Hong Kong. We developed an ensemble machine learning approach within the Bayesian hierarchical modeling framework to achieve spatial–temporal continuity in the estimation of extreme storm surges and mean sea level at sites without tidal gauge stations. Results show a significant yearly increase in maximum storm surge levels by 3 mm and a significant rise in mean sea level of 25 mm per decade in Hong Kong. Our analysis also indicates a significant increase in daily heavy rainfall intensity. Furthermore, in 14.54 % of cases, extreme storm surges coincided with heavy rainfall, while 13.69 % of heavy rainfall events occurred alongside extreme sea level conditions. The copula-based joint analysis reveals significant positive correlations among these extreme events. Our findings further reveal that the return level for a 100-year heavy rainfall event increases dramatically from 126.36 mm in the univariate case to 261.16 mm in the trivariate scenario, underlining the escalated risk associated with compound flooding. Similarly, for storm surge extremes, trivariate analysis reveals elevated risk during compound flood events, with the return level rising from 1.18 m (univariate scenario) to 1.40 m (trivariate scenario) for a 100-year return period. These spatial–temporal maps and comprehensive compound flood risk assessments offer crucial insights for addressing the multi-hazard flood risk in coastal urban areas.

Characteristics of debris flow dynamics and prediction of the hazardous area in Bangou Village, Yanqing District, Beijing, China

Abstract Debris flow is one of the most common types of geological disasters in China. Owing to the influence of topography, geomorphology, geological conditions, human activity, and rainfall debris flow disasters frequently occur in the mountainous areas of Beijing. The research on debris flow in the Beijing area focuses on rainfall and risk evaluation, material sources, and early warning and prevention of debris flow. However, there are few studies on the development characteristics of single-gully debris flow and the prediction of hazardous areas in the Beijing area. Therefore, we chose the debris flow of Bangou Village in Yanqing District of Beijing as the research object. We analyzed the recharge conditions in the ditch domain and predicted the extent of the hazardous area around the gully, providing suggestions for control measures. The dynamic reserves of the loose deposits in the debris flow gully, currently in the development stage, were estimated as 15.48 × 104 m3, representing four supply sources: artificial deposits, alluvium and diluvium, residual slope deposits, and collapse. The peak flow is 24.49 m3/s for a 10-year rainfall event, 27.64 m3/s for a 20-year rainfall event, 31.79 m3/s for a 50-year rainfall event, and 34.93 m3/s for a 100-year rainfall event. The total amounts of solids washed out by a debris flow from the preceding events are 0.70 × 104 m3, 0.79 × 104 m3, 0.91 × 104 m3, and 1.00 × 104 m3, respectively. The size of the debris flow is small, with a maximum hazardous area of 0.2810 km2. We conclude that a small debris flow outbreak in the Bangou Village gully is possible. We expect that the results of this study will provide basic information and help improve debris flow research in Beijing.

Robustness of machine learning algorithms to generate flood susceptibility maps for watersheds in Jordan

The study examined three machine learning algorithms (MLAs): random forest (RF), support vector machine (SVM), and artificial neural networks (ANN) for generating flood susceptibility maps in two watersheds in Jordan. Both were selected because they represent two climatic regimes: desert and mountainous areas. Because of a shortage of past floods location, a physical model was utilized to generate them based on simulations of 100-year rainfall. 10,000 of them were selected randomly and used for MLAs training and testing. During training, thirteen flood influential factors were identified. Out of them, the distance to stream, elevation, and topographic wetness index have shown an overwhelming effect in Zarqa Ma’in watershed (they gained 50% of IGR), while the distance to stream, stream density, and elevation have an overwhelming effect in Al-Buaida watershed (they gained 44% of IGR). For flood susceptibility mapping, RF outperformed the other two algorithms for both watersheds and was thus selected for susceptibility mapping. The maps were classified into five classes, and 11% of Al-Buaida watershed fell into high to very high classes, while 5.2% of Zarqa Ma’in watershed fell within these classes. In conclusion, MLAs were able to produce susceptibility maps efficiently, and they can form an alternative to physical modeling.

Analysis of water migration in an earthen landfill cover with recycled construction waste

In this study, numerical analysis was conducted to investigate the effects of particle sizes on water migration in a three-layer landfill cover system using recycled concrete aggregates (RCAs). This cover system consists of a top fine recycled concrete (FRC) aggregate layer and a middle coarse recycled concrete aggregate layer overlying a bottom silty refuse soil layer. Numerical simulations were performed to back analyse a flume model test data and further evaluate the particle size effects of RCAs on the effectiveness of the cover system. With the increase in rainfall duration, surface runoff reduced, while the lateral diversion increased pronouncedly. Nonetheless, no significant percolation is observed through the cover system using RCAs during 100-year extreme rainfall with different durations. Based on the results, the d10 of FRC is recommended to be from 0.2 to 0.5 mm.

Integration of Building Information Modeling and Stormwater Runoff Modeling: Enhancing Design Tools for Nature-Based Solutions in Sustainable Landscapes

Building information modeling (BIM) has been used by the architectural and engineering disciplines to streamline the building design, construction, and management process, but there has been much more limited experience in extending the application to landscape design and implementation. This study integrated BIM software (Autodesk InfraWorks 2024.1) with a dynamic, process-oriented, conceptual hydrologic/hydraulic model (PCSWMM 2023, version 7.6.3665) to enhance the analytical tools for sustainable landscape design. We illustrate the model integration through a case study that links an existing nature-based solution (NbS) development, the PTT Metro Forest Park, Bangkok, Thailand, with theoretical new-build NbS for an adjacent property. A BIM school building was virtually situated on an empty lot beside the Metro Forest Park and seven NbS scenarios were run with design storms having 2-year, 5-year, and 100-year return intervals. The combination of a rain garden, permeable pavement, a retention pond, and a green roof was effective in sustainably managing runoff from the theoretical new-build site discharging to the Metro Forest. NbS design characteristics such as rain garden substrate depth and green roof area were optimized using the hydrologic/hydraulic model. Model results showed that even with the 100-year rainfall event, the existing Metro Forest pond storage capacity was sufficient so that flooding on the property would not occur. The consideration of connectivity between NbS features is facilitated by the modeling approach, which is important for NbS planning and assessment at a regional scale.

Probabilistic modeling of dam failure scenarios: a case study of Kanlikoy Dam in Cyprus

One of the most perilous natural hazards is flooding resulting from dam failure, which can devastate downstream infrastructure and lead to significant human casualties. In recent years, the frequency of flash floods in the northern part of Nicosia, Cyprus, has increased. This area faces increased risk as it lies downstream of the Kanlikoy Dam, an aging earth-fill dam constructed over 70 years ago. In this study, we aim to assess potential flood hazards stemming from three distinct failure scenarios: piping, 100-year rainfall, and probable maximum precipitation (PMP). To achieve this, HEC-HMS hydrologic model findings were integrated into 2D HEC-RAS hydraulic models to simulate flood hydrographs and generate flood inundation and hazard maps. For each scenario, Monte Carlo simulations using McBreach software produced four hydrographs corresponding to exceedance probabilities of 90%, 50%, 10%, and 1%. The results indicate that all dam breach scenarios pose a significant threat to agricultural and residential areas, leading to the destruction of numerous buildings, roads, and infrastructures. Particularly, Scenario 3, which includes PMP, was identified as the most destructive, resulting in prevailing flood hazard levels of H5 and H6 in the inundated areas. The proportion of inundated areas in these high hazard levels varied between 52.8% and 57.4%, with the number of vulnerable structures increasing from 248 to 321 for exceedance probabilities of 90% and 1%, respectively. Additionally, the number of flooded buildings ranged from 842 to 935, and 26 to 34 km of roads were found to be inundated in this scenario. These findings revealed the need for authorities to develop comprehensive evacuation plans and establish an efficient warning system to mitigate the flood risks associated with dam failure.

Evacuation information methodology that combined a flooded environment and pedestrian behavioral model

Disaster information influences decision-making. Wireless internet and location-based services, aided by recent technological advances, have laid the foundation for providing personalized disaster information. Despite the provision of simple disaster forecasts and warnings, provision of specific evacuation actions (“where” and “how,” i.e., location and reachability of safe areas) and location-based personalized information that consider real-time disaster situations are a pressing priority. Thus, this study proposed and developed a three-step methodology for providing disaster information during floods that combined a flooded environment and pedestrian behavioral model, namely, 1) prediction of the flooded environment, 2) analysis of evacuation routes based on the movement time of evacuees according to the flood depth, and 3) provision of evacuation information by selecting the optimal evacuation route. This model was demonstrated in the Gangnam Station area in Seoul, Korea. Flooded environment prediction modeling of the target area was performed by applying the 100-year rainfall design to the Storm Water Management Model. The optimal evacuation route, according to the flood depth, was selected by applying the behavioral model (movement time calculation formula) for each evacuee derived through an evacuation behavior experiment. The pre- and post-flooding age- and gender-wise total evacuation distance and time were compared and analyzed. Post-flooding, the evacuation distance and time increased by 168.3% (381.34 m) and 172.3% (3.16 min) on average, respectively, indicating that evacuees must travel farther and longer. The analysis of post-flooding evacuation route change types revealed changes in evacuation distance and time in cases where shelters and evacuation routes and time were significantly different depending on evacuee characteristics (age and gender). This indicated that specific and visual disaster information can be provided according to evacuees’ age and gender using the proposed methodology. This study can serve as the basis for designing an advanced and personalized disaster information system that can provide specific evacuation actions to aid fast evacuation decision-making during floods.

Evaluation of GPM IMERG-FR Product for Computing Rainfall Erosivity for Mainland China

Satellite precipitation products (SPPs) have emerged as an alternative to estimate rainfall erosivity. However, prior studies showed that SPPs tend to underestimate rainfall erosivity but without reported bias-correction methods. This study evaluated the efficacy of two SPPs, namely, GPM_3IMERGHH (30-min and 0.1°) and GPM_3IMERGDF (daily and 0.1°), in estimating two erosivity indices in mainland China: the average annual rainfall erosivity (R-factor) and the 10-year event rainfall erosivity (10-yr storm EI), by comparing with that derived from gauge-observed hourly precipitation (Gauge-H). Results indicate that GPM_3IMERGDF yields higher accuracy than GPM_3IMERGHH, though both products generally underestimate these indices. The Percent Bias (PBIAS) is −55.48% for the R-factor and −56.38% for the 10-yr storm EI using GPM_3IMERGHH, which reduces to −10.86% and −32.99% with GPM_3IMERGDF. A bias-correction method was developed based on the systematic difference between SSPs and Gauge-H. A five-fold cross validation shows that with bias-correction, the accuracy of the R-factor and 10-yr storm EI for both SPPs improve considerably, and the difference between two SSPs is reduced. The PBIAS using GPM_3IMERGHH decreases to −0.06% and 0.01%, and that using GPM_3IMERGDF decreases to −0.33% and 0.14%, respectively, for the R-factor and 10-yr storm EI. The rainfall erosivity estimated with SPPs with bias-correction shows comparable accuracy to that obtained through Kriging interpolation using Gauge-H and is better than that interpolated from gauge-observed daily precipitation. Given their high temporal and spatial resolution, and timely updates, GPM_3IMERGHH and GPM_3IMERGDF are viable data products for rainfall erosivity estimation with bias correction.

Estimation of possible locations for green roofs and bioswales and analysis of the effect of their implementation on stormwater runoff control

IntroductionThe objectives of this study are twofold. The first is to identify potential green infrastructure construction sites by building rooftops and sidewalks. The second is to analyze internal flooding for a wide range of drainage areas and to quantitatively evaluate the effectiveness of stormwater runoff control.MethodsThe target area has approximately 600 ha with a runoff coefficient of 0.71. Using Arc GIS Desktop 10.8.1, this study has identified green roofs and bioswales that would be highly beneficial in capturing large amounts of rainfall. In addition, Info Works ICM was used for the inundation analysis, which can simultaneously calculate the flow in sewer pipelines and above-ground inundation flow. Runoff coefficients were calculated for each land use using the urban land use subdivision mesh data with 100 m unit. This study targeted a 10-year probability rainfall (total rainfall: 86.3 mm, maximum hourly rainfall: 52.3 mm/h, duration: 3 h) with a middle concentrated rainfall waveform obtained from past experiments in the d4PDF database of ensemble climate prediction contributing to global warming.ResultsThe amount of land availability for green roofs and bioswales was about 1 and 0.1% of the drainage area, respectively. The runoff coefficients for green roofs only, bioswales only, with and without introduction of both green roofs and bioswales were 70.34, 70.87, 70.28, and 70.93%, respectively. The difference in runoff coefficients was about 0.65 percentage points even when both were constructed. As a result of inundation analysis, the reduction was 2.5% for the maximum waterlogged area, 1.5% for the flooded area, and 0.7% for the average depth of waterlogging divided by the maximum waterlogged area. The construction of green roofs and bioswales in the same area or downstream of the area shows little mitigation effect when flooding occurs in an area near the downstream end of the sewer network.DiscussionAlthough this study has mainly discussed the stormwater runoff control aspect, the most important feature of green infrastructure is its multifunctionality. In terms of utilizing and promoting green infrastructure, it is important to visualize its multifaceted effects and share them with many stakeholders.

Updating catastrophe models to today’s climate – An application of a large ensemble approach to extreme rainfall

As climate change unfolds, extreme weather events and natural hazards relevant for the insurance industry may change in frequency and intensity. In order to guarantee risk-adequate pricing, risk modelers have to ask themselves the question whether a certain ‘hazard’ parameter based on past observations and calibrated on past data is still valid or needs to be updated. Using the example of heavy rainfall between 3 h and 72 h as a proxy for flash flooding, we apply a unique high-resolution single model initial-condition large ensemble. We outline a methodology by which risk modelers can assess whether, where and by how much updating the hazard component of their risk model is needed. Therefore, we compare two time periods: 1980–1999 (as an example for a typical baseline period) and 2015–2034 (representing a 20-year period centered around today). We argue that assessing changes over the full ensemble space is vital for (i) the identification of homogeneous regions where a certain signal emerges, and (ii) the quantification of risk changes in the tail of the extreme value distribution that may still be hidden in the mean response to climate change. In the example case of 3-hourly 50-year rainfall return levels, we find a significant increase between 1980 and 1999 and 2015–2034 over 44 % of European land area. We also identify specific risk regions such as northwestern Spain where changes in the very tail (100-year rainfall return level) already emerge before more common extremes (1-year rainfall return level). Failing to detect and consider these tail changes or assuming equal changes for common and rare extremes may therefore lead to an under- or overestimation of the true level of risk today.

A combined stability function to quantify flood risks to pedestrians and vehicle occupants

With the increase of the frequency and severity of flooding events, coupled with population growth, the risks posed to people from flooding is ever more apparent. This paper proposes a methodology to examine the risks posed to vehicles' occupants and pedestrians simultaneously in an urban context. Through considering stability functions of a range of vehicle types and pedestrian, a risk assessment profile for a vehicle occupant was derived. Using a historical 1-in-20-year rainfall flood event that took place in the city of Exeter (UK) in 2014, and a synthetic 1 in 100-year rainfall flood event, the potential risks posed to vehicle occupants were analysed. The results showed that for these events the potential risks posed to people travelling by car and caught in flood waters were likely to be more severe if they were to remain within their vehicles than if they were to exit said vehicles. Analysis of the changes in risk over time further revealed that if a vehicle was to become immobilised in flood water, they would only have a short timeframe (~10 min) before the level of risk increases. This is a critical finding, highlighting that remaining inside an immobilised vehicle during flood event and waiting for assistance may increase the level the risk the individual is exposed to, with the results showing the significance of such studies in reducing the risk of flooding to people.

Decoding the enigma of 100-year record-breaking rainfall over Tamil Nadu using wavelet analysis

There have been increasing trends of short-intensive rainstorm events, which lead to urban flood disasters in many coastal areas of India. The relationship between regional rainfall and global large-scale climate indices has shown high teleconnections in terms of recurrence and covariance. We have examined the teleconnection between the November and December 2015 rainstorm events (100-year record breaking rainfall) with the Oceanic Nino Index using the dataset from the Indian Meteorological Organisation (NEMR) and National Oceanic and Atmospheric Administration (ONI). The study has found out not only the existence of the cause-and-effect relationship but also the recurrences of these high rainfall events. The climatological trend of northeast monsoon rainfall (NEMR) and Oceanic Nino Index (ONI) is calculated, and the correlation for a period of 71 years (1951–2021) is quantified using Pearson's correlation method. We observed that Chennai, Nagapattinam, Cuddalore, Kancheepuram, Thiruvarur, and adjoining coastal districts are more prone to torrential rains during El Niño years as compared to La-Niña years which is unusual but not exceptional. Wavelet analysis is performed on the NEMR and ONI signals to decipher the teleconnections at different temporal scales. Wavelet coherence shows an in-phase relationship between the ONI and NEMR signal and high covariance (0.8–0.9 at 5% significance level using Monte Carlo generated noise), between the two in 2015 the year which broke the 100 years rainfall record for Chennai. The study highlights the crucial linkage (cause and effect relationship) between the regional rainstorms and the large-scale global index (ONI), and wavelet analysis can explain the distant relationship in the northeast monsoon. The study provides quantified insights especially in the present era of climate change, where the hydrological extremes are persistent. The study does not only connect ONI with NEMR but also quantifies the in-phase strength of the relationship which can guide the scientific community towards accurate predictions and develop disaster mitigation strategies.

Evaluation of urban flooding and potential exposure risk in central and southern Liaoning urban agglomeration, China

Urban flooding is an important natural hazard that affects urban security in the context of global climate change and urbanization. The simulation of stormwater inundation and risk assessment in urban environments is critical for the sustainable development of urban agglomerations. However, few studies have focused on rainstorm flooding at the urban agglomeration scale. In this study, the Central and Southern Liaoning Urban Agglomeration (CSLN) was selected a case study. A method was proposed to assess the urban flooding and potential exposure risk. The urban flooding of CSLN was characterized by the average flooding depth (AFD) of each sub-catchment, and exposure risk was indicated by potential regional and population exposure risk. The results illustrate that the AFD increased with an increase in the rainfall return period, especially in the urban core. The AFD of each city in the CSLN ranged from 10 to 80 mm, and there were strong differences among cities. The spatial distribution of urban flooding in the nine cities presented aggregation characteristics, and hotspots were mainly concentrated in the old urban districts. The potential regional exposure risk tended to increase as the rainfall return period increased from 10 to 100 years; however, there were significant differences among cities. Among them, the area of potential regional exposure risk in Shenyang was the largest, increasing from 365 km2 under a 10-year rainfall return period to 463 km2 under a 100-year rainfall return period. The largest proportion of potential regional exposure risk was in Anshan, which increased from 3% under 10-year to 13.8% under 100-year rainfall return periods. Most cities had some potential population exposure risk. More residents in populous cities, such as Shenyang and Dalian, were subject to higher exposure risks. However, Benxi, Anshan, and Tieling had a high proportion of severely affected areas, although the size of their cities is much smaller than that of Shenyang and Dalian. Urban flooding and potential exposure risk were apparently higher in the business and government zones than in the industrial and greenspace zones. These methods and results may provide references for rainstorm flooding mitigation through urban planning in urban agglomeration areas.

Coastal and River Embankment Performance at Cengkareng Drain Estuary Under Compound Hazards Conditions Using HEC-RAS 2D

Jakarta is prone to pluvial, fluvial, and coastal flooding due to its geographical location and topography. In response to this problem, the Indonesian government has implemented several master plans, including the National Capital Integrated Coastal Development (NCICD). This ongoing program encompasses the construction of coastal and river embankment that stretch all over the coast of Jakarta. Since many coastal areas in Jakarta are residential or industrial, evaluating this performance of embankment has become crucial for effective flood management. The findings of this research can also support the development of other locations where NCICD embankment plan and enhance coastal resilience. Therefore, this research assessed the effectiveness of coastal and river embankment at Cengkareng Drain, a vital floodway in Jakarta, during extreme events that occur simultaneously. To simulate flooding events, two-dimensional HEC-RAS features were used to numerically calculate the area and depth of inundation. The simulation required geometry, terrain, land cover, and unsteady flow data. For the flow boundary conditions, a 100-year design rainfall, HHWL (Highest High Water Level), and 100-year design wave were considered to represent estuary conditions accurately. The simulation result showed that the maximum water level influenced by these factors was +3.145 mMSL, while the planned embankment top elevation was +3.40 mMSL. Furthermore, without the NCICD embankment, the simulation showed an inundation area of 1212.37 ha, which was reduced to 1111.22 ha after their implementation, leading to a decrease of 101.15 ha. This reduction significantly decreases potential damage to property and infrastructure, particularly in densely populated areas. The simulation also showed a reduction of 86.49 hectares or 66.22% in the inundation area with a depth exceeding 1 meter. These findings demonstrate the effectiveness of embankment in reducing the inundation area without any overtopping incidents.

Non-stationarity in extreme rainfalls across Australia

Future flooding is likely to exceed current design flood levels which are based on historical extreme rainfall characteristics. The Clausius-Clapeyron relationship explains the intensification of extreme rainfalls as approximately 7% per one degree warming as atmospheric water holding capacity increases with temperature. Therefore, to prepare for a future warmer climate, we need to develop methodologies to project future rainfall intensities across the range of durations and exceedance probabilities used in engineering design. However, the studies that have investigated changes in extreme rainfalls across Australia have had disparate results and are not spatially or temporally comprehensive – hampering our understanding of changes in extreme rainfalls across different durations and exceedance probabilities.This study investigates the impact of climate change on rainfalls from the annual maximum to the 1 in 100-year rainfall across a range of storm durations for the continent of Australia. We find increases in short duration (<1 h) annual maximum rainfall are greater than increases in long duration (>1 h) annual maxima across Australia from 1967 to 2021. These results are consistent regardless of the data period or data set chosen for analysis. We estimate events rarer than the annual maxima through fitting non-stationary Generalize Extreme Value models. We find that events of rarer severity have increased more than frequent events. Further, we identify the parameterisation of a model with non-stationary location and scale parameters to capture the changes in historic design quantiles that are consistent with our physical understanding of rainfall intensification, empirical quantile changes, and historical trends. We conclude that trends in annual maxima are best represented by non-stationary models that incorporate changes in both location and scale parameters, not by solely varying either location or scale parameters.

Impact of Climate Variability on Rainfall Characteristics in the Semi-Arid Shashe Catchment (Botswana) from 1981–2050

Futuristic rainfall projections are used in scale and various climate impact assessments. However, the influence of climate variability on spatial distribution patterns and characteristics of rainfall at the local level, especially in semi-arid catchments that are highly variable and are not well explored. In this study, we explore the influence of climate variability on the spatial distribution and rainfall characteristics at a local scale in the semi-arid Shashe catchment, Northeastern Botswana. The LARS-WG, Long Ashton Research Station Weather Generator downscaling method, three representative scenarios (RCP 2.6, RCP 4.5, and RCP 4.5), three trend detection methods (Mann-Kendall, Sen’s slope, and innovative trend analysis) and L-moment method were used to assess climate change impacts on rainfall. Two data sets were used; one with 40 years of observed data from 1981–2020 and the other with 70 years from 1981–2050 (40 years of observed and 30 years of projected data from 2021–2050). Generally, the study found trend inconsistencies for all the trend detection methods. In most cases, Sen’s Slope has a high estimate of observed and RCP 2.6, while ITA overestimates rainfall totals under RCP 4.5 and RCP 8.5. The trend is increasing for annual total rainfall in most gauging stations while decreasing for annual maximum rainfall. The catchment is homogeneous, and Generalized Logistic distribution is the dataset’s best-fit distribution. Spatial coverage of a 100-year rainfall between 151–180 mm will be 81% based on observed data and 87% based on projected data under RCP 2.6 scenario when it happens. A 200-year rainfall between 196–240 mm under RCP 4.5 and 8.5 has high spatial areal coverage, at least 90% of the total catchment. The outcomes of this study will provide insightful information for water resource management and flood risk assessment under climate change. There is a need, however, to assess the transferability of this approach to other catchments in the country and assess the performance of other advanced modelling systems, such as machine learning, in this region.

ANALISIS SALURAN DRAINASE AKIBAT GENANGAN DI KECAMATAN ILIR TIMUR II KOTA PALEMBANG

Changes in land use in an area greatly affect water absorption. Inundation occurred in Ilir Timur II Subdistrict, Palembang City due to lack of maintenance of drainage channels and changes in land conversion which was originally land into a water catchment area, now it is a concrete or residential area. During the rainy season, water will fill residents' spaces in the form of puddles and floods, which will continue to increase surface runoff in the area. The impact of the inundation is very disturbing and detrimental to various parties. The purpose of this study is to determine the peak discharge, analyze existing drainage, and plan a new secondary drainage design. The data used are primary data, namely channel length measurement data, channel slope, and existing channel dimension measurement data. While the secondary data used is in the form of 10-year rainfall data obtained from two rain posts, namely the rain post in Sako District and the rain post in Ilir Barat I District, as well as land use data in the Fruit Watershed of Palembang City covering an area of 1222.89 hectares. Then carry out an analysis of changes in land use currently and calculation of peak discharge to plan the dimensions of the new secondary drainage channel. The current peak discharge (Qp) calculation results in the studied area are 24.4 m3/s. For the calculation of channel dimensions, it is planned to have a rectangular cross-section with channel dimensions at sta 0.00 - 672.80 m, namely the channel dimension height is 4.5 m, the channel width is 4.5 m, and the guard height (f) is 0.30 m. From the results of analysis and calculations it is known that with the dimensions of the new drainage design there will be no runoff along the secondary canal. It is hoped that this can be a reference in planning the drainage rearrangement in Ilir Timur II District to reduce frequent inundation.

Assessment of industrial by-products as amendments to stabilize antimony mine wastes

The spread of antimony from mine wastes to the environment represents a matter of great concern due to its adverse effects on impacted ecosystems. There is an urgent need for developing and adopting sustainable and inexpensive measures to deal with this type of wastes. In this study the Sb leaching behavior of mine waste rocks and mine tailings derived from the exploitation of Sb ore deposits was characterized using standard batch leaching tests (TCLP and EN-12457-4) and column leaching essays. Accordingly, these mine wastes were characterized as toxic (>0.6 mg Sb L−1) and not acceptable at hazardous waste landfills (>5 mg Sb kg−1), showing also an ongoing Sb release under prolonged leaching conditions. Two industrial by-products were evaluated as amendments to stabilize them, namely deferrisation sludge (DFS) and a by-product derived from the treatment of aluminum salt slags (BP–Al). Mine wastes were amended with different doses (0–25%) of DFS or BP-Al and the performance of these treatments was evaluated employing also batch and column leaching procedures. The effectiveness of DFS to immobilize Sb was much higher than that exhibited by BP-Al. Thus, treatments with 25% BP-Al showed Sb immobilization levels of approximately 33–53%, whereas treatments with 5 and 25% DFS already attained Sb immobilization levels up to approximately 80–90 and 90–99%, respectively. Mine tailings amended with 5% DFS and mine waste rocks amended with 25% DFS decreased their leachable Sb contents below the limit for non-hazardous waste landfill acceptance (<0.7 mg Sb kg−1). Likewise, these DFS treatments were able to revert their toxic characterization. Moreover, the 25% DFS treatment showed to be a long-lasting stabilizing system, efficient at least during a leaching period equivalent to 10-year rainfall with a great Sb leaching reduction (close to 98%). After this long-term leaching process, DFS-treated mine wastes kept their non-hazardous and non-toxic characterization. The amorphous Fe (oxyhydr)oxides composing DFS were responsible for the important Sb removal capacity showed by this by-product. Thus, when DFS was applied to mine wastes mobile Sb was importantly fixed as non-desorbable Sb, showing also a considerable Sb removal capacity in presence of strong competing anions such as phosphate. The application of DFS as amendment presents a great potential to be used as a sustainable long-term stabilizing system of Sb mine wastes.