Frequent Rain Research Articles

Future Winter Precipitation Decreases Associated With the North Atlantic Warming Hole and Reduced Convection

AbstractClimate projections in the North Atlantic region suffer from great uncertainties, and projections of precipitation are given with a large spread. Some of this uncertainty is related to projections of the North Atlantic warming hole (NAWH). The Community Earth System Model version 2 (CESM2) projects a relatively strong and extensive NAWH, with future sea surface cooling extending to Northern Scandinavia. This study investigates the relatively large winter precipitation decrease projected by CESM2 in the northeastern North Atlantic region, reinforced in a regional model. Three future scenarios from CESM2 are dynamically downscaled with the Weather Research and Forecast model. A methodology to separate convective and orographic from stratiform precipitation is applied to explore the physical mechanisms. Changes in stratiform precipitation closely relate to storm‐track changes, which varies between the scenarios. Convective precipitation decreases by up to 50% over the Norwegian Sea at the end of the century, which is robust across the scenarios. This is explained by the underlying reduced sea surface temperatures of the NAWH, leading to reduced evaporation and reduced convective activity and intensity. The orographic precipitation maximum over the Scandinavian mountains is shifted upstream, likely affected by increased static stability and flow blocking, which also relates to the NAWH. This shift is possibly also explained by more frequent rain versus snow, as well as reduced cross‐barrier wind speeds. This study contributes to highlight the importance of focusing future research efforts on the NAWH, in order to constrain future climate projections in this region.

Precipitation trend increases the contribution of dry reduced nitrogen deposition

Given the leveling off in oxidized nitrogen emissions around the world, the atmospheric deposition of reduced nitrogen (NHx = NH3 + NH4+) has become progressively critical, especially dry deposition, which presents great threats to plant growth. A combination of historical deposition data of measured wet NHx and modeled dry NHx in China suggests that dry NHx deposition has been increasing substantially (4.50% yr−1, p < 0.05) since 1980. Here, chemical transport model (WRF-EMEP) results indicate that variation in NH3 emissions is not a dominant factor resulting in the continually increasing trends of dry NHx deposition, while climate change-induced trends in precipitation patterns with less frequent light rain and more frequent consecutive rain events (with ≥2 consecutive rainy days) contribute to the increase in dry NHx deposition. This will continue to shift NHx deposition from wet to dry form at a rate of 0.12 and 0.23% yr−1 (p < 0.05) for the period of 2030–2100 in China under the RCP4.5 and RCP8.5 scenarios, respectively. Further analysis for North America and Europe demonstrates results similar to China, with a consistent increase in the contribution of dry NHx deposition driven by changing precipitation patterns from ~30% to ~35%. Our findings, therefore, uncover the change of precipitation patterns has an increasing influence on the shifting of NHx deposition from wet to dry form in the Northern Hemisphere and highlight the need to shift from total NHx deposition-based control strategies to more stringent NH3 emission controls targeting dry NHx deposition in order to mitigate the potential negative ecological impacts.

An Increase in Precipitation Driven by Irrigation over the North China Plain Based on RegCM and WRF Simulations

Abstract Anthropogenic land-use change, irrigation, is considered to strongly modulate the hydroclimate at the regional scale by directly triggering evaporative cooling as the preliminary local effect. However, subsequent interactions with the background climate are highly nonlinear, which introduces diverse and unexpected consequences. The North China Plain (NCP) is one of the regions where irrigation has expanded the most rapidly since the twentieth century. The scarce rainfall in this region makes it necessary for irrigation to supplement the level of soil water for agricultural production. In this study, we quantify the effect of irrigation on the regional climate in China. Two regional climate models, WRF and RegCM, are used to mimic the large-scale practice of irrigation on the NCP. The results of our experiments show consistent cooling and moistening effects centered over the NCP across all experiments. Although the moisture budget and wind field pattern demonstrate that the vertical downdraft and low-level divergence could inhibit rainfall, the humidification dominates the climatic response in the dry April–June and increases the amount of precipitation significantly and consistently in the NCP region and the surrounding area in northern China. The enhanced CAPE increases sharply on some “calm days” when the vertical moisture advection is small, especially during the afternoon, triggering frequent light rains convectively by destabilizing the atmosphere. The consistent response to irrigation in two different models that employ structurally different land surface schemes could enhance the robustness of the physical mechanism behind the precipitation increase in the heavily irrigated region of NCP.

კატასტროფული წყალმოვარდნები ქ. თბილისის მიდამოებში

Catastrophic floods of the river are described. Kura and its tributaries, which caused enormous damage and casualties. It is noted that the increase in damage is caused by an increase in the frequency of high rains, strong anthropogenic changes in the underlying surface, as well as a decrease in the infiltration capacity of the soil and the water permeability of river channels. Under the conditions of global warming, the expected increase in the intensity of precipitation will cause more frequent catastrophic floods. In order to ensure safety and reduce losses, appropriate preventive measures should be taken.

Remote monitoring of short‐term body mass variation in savanna ungulates

AbstractLarge herbivores in seasonal environments often experience mass variation due to temporal changes in the availability of critical resources like water and forage, as well as due to breeding events. Yet the documentation of mass variation in mammals of highly seasonal savanna habitats, which host the highest densities of grazing ungulates globally, has rarely been explored. Here, we showcase a method to evaluate seasonal mass variation in bovids. Our method used mineral‐baited scales and camera traps to enable us to track the body mass of three species through a period of wet and dry seasons in a South African savanna ecosystem. To illustrate one potential application of the method, we related body mass data to time, weather and resource availability. This showed that individuals altered their body masses markedly between seasons with, for example, female Kudu (Tragelaphus strepsiceros) gaining, on average, &gt;21 kg over the 15‐week wet‐season period in 1 year. These changes were positively related to factors such as vegetation productivity (assessed using NDVI) and the frequency of rains. This method enables easy, non‐lethal and non‐invasive acquisition of mass data. The equipment is easy to deploy concurrently over large areas. Monitoring by this method has a variety of possible applications, potentially providing a useful early‐warning indicator of body condition to inform management, or providing information about ecological states, such as parturition or the reproductive effort of males. Given the longer and harsher dry seasons experienced in many arid systems in recent decades, and projected in future, this method may provide a straightforward means of monitoring long‐term body condition in animals as a result of environmental change.

Climate Impacts of Convective Cloud Microphysics in NCAR CAM5

Abstract We improved the treatments of convective cloud microphysics in the NCAR Community Atmosphere Model version 5.3 (CAM5.3) by 1) implementing new terminal velocity parameterizations for convective ice and snow particles, 2) adding graupel microphysics, 3) considering convective snow detrainment, and 4) enhancing rain initiation and generation rate in warm clouds. We evaluated the impacts of improved microphysics on simulated global climate, focusing on simulated cloud radiative forcing, graupel microphysics, convective cloud ice amount, and tropical precipitation. Compared to CAM5.3 with the default convective microphysics, the too-strong cloud shortwave radiative forcing due primarily to excessive convective cloud liquid is largely alleviated over the tropics and midlatitudes after rain initiation and generation rate is enhanced, in better agreement with the CERES-EBAF estimates. Geographic distributions of graupel occurrence are reasonably simulated over continents; whereas the graupel occurrence remains highly uncertain over the oceanic storm-track regions. When evaluated against the CloudSat–CALIPSO estimates, the overestimation of convective ice mass is alleviated with the improved convective ice microphysics, among which adding graupel microphysics and the accompanying increase in hydrometeor fall speed play the most important role. The probability distribution function (PDF) of rainfall intensity is sensitive to warm rain processes in convective clouds, and enhancement in warm rain production shifts the PDF toward heavier precipitation, which agrees better with the TRMM observations. Common biases of overestimating the light rain frequency and underestimating the heavy rain frequency in GCMs are mitigated.

Development of Slow-Release Fertilizer from Animal Origin Wastes: Sustainable Organic Agriculural Perspective

Improved crop quality and quantity is the main target of soil fertilization in conventional agriculture. However, in organic agriculture, adding nutrients to the soil is the threshold replenishment of nutrients lost through every crop. Mineral fertilizers provide essential macro and microelements to plants for their active growth and development. Unfortunately, these kinds of fertilizers easily run off from plant vicinity because of frequent watering and rain. This leads to the recurrent application of fertilizers, which causes severe environmental problems. To resolve these issues many researchers developed different slow-release fertilizers, which can provide nutrients to plants for an extended period. However, slow-release fertilizers are much more expensive than normal mineral fertilizers. The present work attempts to develop new slow-release fertilizer using mariculture waste mussel shell and cow urine. Significant macronutrient adsorption was observed in the shell saturation experiment and the leaching experiment proves that shell powder after nutrient impregnation with urine had a slow nutrient-releasing capacity. The formation of struvite crystals is another highlight of this study, which provides a long-term nutrient supply in the soil. BET analysis confirms the nutrient scrubbing and releasing ability of shell powder. Independently cow urine and mussels shells are used in agriculture for different purposes. Mussel shells are regularly used to reduce soil acidity and cow urine is applied to plants as a cheap nitrogen supplement in a diluted manner. However, cow urine components quickly run off from the plant root proximity. Nutrient impregnated shell powder has both characters of mussel shell powder and cow urine and it is truly formed from animal origin waste products. Because of no usage of synthetic chemicals, new slow-release fertilizer couldn’t make any environmental problems.

Improving Field Moisture Monitoring of Recycled and Virgin Aggregates

The structural capacity of pavement foundation is altered by moisture conditions. Reliable moisture monitoring of geomaterials throughout pavement service life is critical for asset management by transportation agencies. Improved moisture sensing enables transportation officials and practitioners to better understand performance of complex recycled materials under frequent extreme rain events. Although moisture sensing for geomaterials has improved significantly, there are still challenges when using sensors in recycled materials that may contain unhydrated cement, aged asphalt, or both. Challenges include the development of calibration functions that account for the presence of recycled materials and robust installation procedures, as technology was developed mostly for agricultural practices. In this study, a series of experiments were conducted to suggest improvements for installation techniques and data interpretation of soil moisture and water potential sensors. Suggested installation guidelines minimize wash-out and erosion potential at the soil–sensor interface. Experimental results indicate a strong bilinear relation between dielectric of recycled materials and water content, with a region of relatively small change governed by dielectric permittivity of air and a region of rapid change controlled by dielectric permittivity of water. Moreover, it was found that dielectric permittivity is not significantly affected by aggregate internal structure as dielectric for a specific moisture content for different compaction degrees is relatively similar. Furthermore, soil water characteristic curves obtained using the water potential sensor and improved installation technique compare reasonably well with laboratory results obtained with traditional equipment. Reliability of both moisture and water potential sensors was improved with the suggested guidelines.

Characteristics of Extreme Rainfall Events in North Sumatra

Extreme rain is an event that has an impact on various sectors of life. Therefore, this study aims to determine the spatial and temporal characteristics of extreme rain events in North Sumatra Province in the time period between 1991-2020. In accordance with the WMO recommended rain index, the frequency and intensity of rain were calculated using 50 rain stations spread across North Sumatra where the data had passed the quality control test for empty data. Spatial patterns were analyzed by mapping the climatological mean of the indices then for trend patterns were tested using the Mann-Kendal non-parametric test. The results showed that extreme rainfall events with low frequency and intensity occurred on the east coast while high frequency and intensity occurred in mountainous areas. Based on the temporal trend test, it shows that in general an insignificant trend dominates in this area. Significant and consistently increasing trends are only found at several points, namely in the districts of Deli Serdang (5 station), Batu Bara (1 station), Humbang Hasundutan (1 station), Langkat (2 station), Labuhan Batu Utara (1 station), Medan (1 station), Pematang Siantar (1 station) and Serdang Bedagai (1 station). Meanwhile, a significant and consistently decreasing trend was found in Asahan Regency (1 station), Simalungun (2 station), North Tapanuli (1 station), and North Labuhan Batu (1 station).

Impacts of Climate Change on Extreme Climate Indices in Türkiye Driven by High-Resolution Downscaled CMIP6 Climate Models

In this study, the latest release of all available Coupled Model Intercomparison Project Phase 6 (CMIP6) climate models with two future scenarios of Shared Socio-Economic Pathways, SSP2-4.5 and SSP5-8.5, over the period 2015–2100 are utilized in diagnosing climate extremes in Türkiye. Coarse-resolution climate models were downscaled to a 0.1° × 0.1° (~9 km) spatial resolution using the European Centre for Medium-Range Weather Forecasts Reanalysis 5-Land (ERA5-Land) dataset based on three types of quantile mapping: quantile mapping, detrended quantile mapping, and quantile delta mapping. The temporal variations of the 12 extreme precipitation indices (EPIs) and 12 extreme temperature indices (ETIs) from 2015 to 2100 consistently suggest drier conditions, in addition to more frequent and severe precipitation extremes and warming temperature extremes in Türkiye, under the two future scenarios. The SSP5-8.5 scenario indicates more severe water stress than the SSP2-4.5 scenario; the total precipitation decreases up to 20% for Aegean and Mediterranean regions of Türkiye. Precipitation extremes indicate a decrease in the frequency of heavy rains but an increase in very heavy rains and also an increasing amount of the total precipitation from very heavy rain days. Temperature extremes such as the coldest, warmest, and mean daily maximum temperature are expected to increase across all regions of Türkiye, indicating warming conditions by up to 7.5 °C by the end of the century. Additionally, the coldest daily maximums also exhibit higher variability to climate change in the subregions Aegean, Southeastern Anatolia, Marmara, and Mediterranean regions of Türkiye while the mean daily maximum temperature showed greater sensitivity in the Black Sea, Central Anatolia, and Eastern Anatolia regions.

Evaluation of waterlogging tolerance and responses of protective enzymes to waterlogging stress in pumpkin.

Waterlogging caused by short and severe, or prolonged precipitation can be attributed to global warming. Pumpkin plants are drought-tolerant but not tolerate to waterlogging stress. Under frequent rain and waterlogging conditions, the production of pumpkins is of lower quality, sometimes rotten, and harvest failure occurs in severe cases. Therefore, it is of great significance to assess the waterlogging tolerance mechanism of pumpkin plants. In this study, 10 novel pumpkin varieties from Baimi series were used. The waterlogging tolerance level of pumpkin plants was evaluated by measuring waterlogging tolerance coefficient of biomass and physiological indices using waterlogging stress simulation method. The criteria to evaluate the waterlogging tolerance capacities of pumpkin plants were also explored. Using principal component and membership function analysis, waterlogging tolerance levels of the pumpkin varieties were ranked as follows: Baimi No. 10>; Baimi No. 5>; Baimi No. 1>; Baimi No. 2>; Baimi No. 3>; Baimi No. 7>; Baimi No. 9>; Baimi No. 6>; Baimi No. 4>; Baimi No. 8. Based on the results, Baimi No. 10 was identified with strong waterlogging tolerance and Baimi No. 8 with weak waterlogging tolerance. The responses of malondialdehyde (MDA), proline, key enzymes responsible for anaerobic respiration, and antioxidant enzymes to waterlogging stress were studied in pumpkin plants. The relative expression levels of related genes were determined using real-time fluorescence quantitative PCR technique. The aim of our study was to assess the waterlogging tolerance mechanism of pumpkin plants, thus laying a theoretical foundation for breeding waterlogging-tolerant varieties in the future. After flooding stress treatment, the antioxidant enzyme activities, contents of proline and alcohol dehydrogenases of Baimi No. 10 and Baimi No. 8 displayed an increase followed by a decrease. All indices of Baimi No. 10 were higher than Baimi No. 8. MDA contents gradually increased, with the content being higher in Baimi No. 8 than Baimi No. 10. The activities of pyruvate decarboxylases (PDCs) in Baimi No. 8 and Baimi No. 10 exhibited a decrease initially, followed by an increase, and then a decrease again. The PDC activity in Baimi No. 8 was generally higher than Baimi No. 10. The relative expression levels of genes encoding superoxide dismutase, peroxidase, catalase, and ascorbate peroxidase were consistent with their corresponding enzyme activities. During the early stage of flooding stress, pumpkin plants waterlogging tolerance was improved by enhancing the expression levels of antioxidant enzyme encoding genes and increasing the antioxidant enzyme activities.

Exploring the Potential of Portable Spectroscopic Techniques for the Biochemical Characterization of Roots in Shallow Landslides

In the present work, Raman, Fourier Transform Infrared (FTIR) and elemental Laser-Induced Breakdown Spectroscopy (LIBS) spectroscopic techniques were used for the assessment of the influence of plant root composition towards shallow landslide occurrence. For this purpose, analyses were directly carried out on root samples collected from chestnut forests of the Garfagnana basin (northern Apennines, Italy) in different areas devoid and affected by shallow landslides due to frequent heavy rain events. Results have highlighted a correlation between the biochemical constituents of wooden roots and the sampling areas. In particular, different content of lignin/cellulose, as well as minerals nutrients, have been detected in roots collected where shallow landslides occurred, with respect to more stable areas. The results achieved are in line with the scientific literature which has demonstrated the link between the chemical composition of roots with their mechanical properties and, in particular, tensile strength and cohesion. Finally, portable spectroscopic instrumentations were employed without the need for either any sample preparation for Raman and LIBS spectroscopy or minimal preparation for FTIR spectroscopy. This novel and fast approach has allowed achieving information on the content of the major constituents of the root cell, such as cellulose and lignin, as well as their mineral nutrients. This approach could be reasonably included among the vegetation protection actions towards instability, as well as for the evaluation of shallow landslide susceptibility, combining geological, vegetational and biochemical parameters with sustainability.

A Route Search System to Avoid the Danger to Life in Dynamic Inundation

In recent years, the frequency of torrential rains has increased due to abnormal weather conditions. Torrential rains have caused extensive flooding damage in many areas. As delays in evacuation can pose a threat to life, a quick search for safe evacuation routes has become more important than ever before. In this study, we constructed a new system for searching evacuation routes that incorporates a function that varies the weight of each road in the route search depending on the distance from the flooded area D and the distance that the flood area extends in 10 min D′ (i.e., the flood’s inundation speed). We conducted multiple hypothetical flood simulations with different locations of levee breaches and shelters in the study site (Obihiro City, Japan). Then, we compared the results with the conventional system that does not include the proposed function. The results showed that the system proposed in this study increased the number of successful evacuees by up to 2.16 times compared to the conventional system. In our system, the weight function is set to the Cd power of D/D′; increasing the model parameter Cd selects a route that detours more of the flooded area. The model parameter Cd that maximizes the number of successful evacuees is roughly constant, regardless of the locations of the levee breaches or shelters in the study site.

Numerical investigation of the effect of dust shields on accumulation of dust over PV panels

Dust accumulation on photovoltaic panels represents a major challenge for the operation of solar panels especially in the regions known by their high rate of dust and low frequency of rain. The objective of this study is to minimize dust accumulation on PV panels operating street light posts using dust shields. A novel dust shield having the same width of the panel, and subtending an angle of 120° with the panel, is proposed for dust mitigation. Numerical simulations are carried out to evaluate the influence of the dust shield on dust accumulation over the panel’s surface. It is found that using a dust shield decreases the dust deposition rate by more than 44%. Moreover, extending the panel’s surface at the lower edge with an extension plate together with the dust shield decreases the dust deposition rate better than using a dust shield only. Also, the effect of adding an air gap between the shield and the added extension plate is investigated, and it is found that the air gap induces air drafts over the panel’s surface, which acts as an air barrier that obstructs the approach of dust particles to the panel’s surface. These drafts get stronger as the air gap thickness increases, accordingly, less particles deposit on the panel. Finally, it is found that using a dust shield with a length smaller than the panel’s length in addition to an extension plate together and increasing the thickness of the air gap is an effective and efficient solution for dust mitigation, such that the percentage decrease in the dust deposition rate that might be more than 88%.

Developing an intelligent cloud attention network to support global urban green spaces mapping

Urban green spaces (UGS) play an important role in understanding of urban ecosystems, climate, environment, and public health concerns. Satellite derived UGS maps provide an efficient and effective tool for urban studies and contribute to targets and indicators of the sustainable development goals, at the global level, set by the United Nations. However, clouds create a challenging issue in optical satellite image processing, leading to significant uncertainty in UGS mapping. In this study, we propose an automatic UGS mapping method by integrating satellite images with crowdsourced geospatial data while aiming to reduce the uncertainty caused by cloud contamination. The proposed method consists of three parts: (1) auxiliary data pre-processing module; (2) cloud attention intelligent network (CAI-net); and (3) non-cloud scenes classification module. The auxiliary data pre-processing module was used to convert crowdsourcing geospatial data into auxiliary maps. The CAI-net was proposed to retrieve detailed UGS classes within clouds from satellite image patches and auxiliary maps, while non-cloud scenes classification module was used to extract UGS from satellite image patches. The proposed method was applied to generate spatial continuous global UGS map products, considering the uncertainty caused by cloud contamination. The results show the proposed method yielded a high-quality global UGS map with average overall accuracy as high as 92.96% when satellite images had cloud coverage ranging from 0% to 50%. The geospatial AI, specifically CAI-net, can provide more accurate UGS mapping regardless of different geographical and climatic conditions of the study areas, which is especially significant for humid tropical and subtropical regions with frequent clouds and rains.

Analyzing future rainfall variations over southern malay peninsula based on CORDEX-SEA dataset

Gridded rainfall datasets based on various data sources and techniques have emerged to help describe the spatiotemporal features of rainfall patterns over large areas and have gained popularity in many regional/global climatic analyses. This study explored future variations of rainfall characteristics over peninsula Malaysia and Singapore region based on rainfall indices of PRCPTOT, Rx1day, Rx5day, R95pTOT, R1mm, and R20mm, under 9 CORDEX-SEA RCM datasets with RCP8.5 emission scenario. A monthly quantile delta mapping method (MQDM) was adopted for bias-correction of the RCM modelled data. It was indicated that all the studied rainfall indices have long-term variations both temporally and spatially. Generally, the further the future, the higher the variability and uncertainty of indices. For the study region, the relative increments of the medians from RCM models averaged over all climatic zones in the far future are 40.3%, 25.9%, and 4.7% for Rx1day, Rx5day and R95pTOT, respectively. The annual rainfall amount (PRCPTOT) in the long run would likely increase mainly in the northeast coastal zone and drop in most of other areas over the peninsula, with the median being -5.9% averaged over all zones. The frequency of wet days (R1mm) would generally drop over the whole peninsula, with the median averaged over all zones being -6.8% in the far future. The frequency of heavy rains (R20mm) would overall decrease (by -3.4% in average in the far future) but might still notably increase in the northeast zone (NE) at both annual and southwest monsoon. The extreme conditions implied from individual RCM models could be more alarming. The study result could be useful in revealing the essential spatiotemporal variations of rainfall over the peninsula from short- to long-term futures and supporting large-scale flood risk assessment and adaptation planning.

STUDY OF TIDAL INFLUENCE ON FLOODING IN KECAMATAN SELAKAU

Kecamatan Selakau has a considerable risk of flooding, which occurs every year. Because it has a low topography, its location on the coast is undoubtedly greatly influenced by tides and is prone to tidal flooding. In an effort to anticipate and reduce the duration and frequency of rain by arranging the drainage system through technical study activities on drainage channels, especially on the Nyirih River drainage channel, which empties directly into the Selakau River.This research aims to examine the effect of the Selakau River's tides on the Nyirih River's drainage flow and the combination of tides and rainfall on the incidence of flooding in the Nyirih River channel. The research methodology used is the descriptive method. Hydrological analysis using the maximum daily rainfall data from Tebas Station. Then the Nyirih River water level tidal readings and the design discharge data are used in the hydrodynamic model analysis.Based on the analysis results using the HEC-RAS Version 6.1.0 software, the water level elevation from sta is at the highest tide conditions without rain. 0+000 to sta. 1 + 466,682 has exceeded the elevation of the existing channel cross-section so that it experiences inundation with a height of 0.02 m–0.4 m, and at sta. 1 + 694,439 to sta. 2 + 073.878, the water level is still below the existing cross-sectional elevation of the channel, so no inundation occurs. It shows that there is no effect or increase in water level elevation that occurs for the highest tide combination conditions with rainfall return periods of 2, 5, 10, and 20 years, and it is the same as the highest tide conditions without rain, which experience inundation with a height of 0.02 m-0.4 m. Normalization is inefficient and unsuccessful in decreasing floods since sea tides extensively impact the Nyirih along the river channel.

Changes in extreme precipitation over Mpologoma catchment in Uganda, East Africa

Changes of five Extreme Precipitation Indices (EPIs) over Mpologoma catchment were examined. The EPIs were obtained from the long-term (1948–2016) gridded (0.25° × 0.25°) Princeton Global Forcing (PGF) daily precipitation dataset. The number of days with precipitation intensity greater than 5 mm/day (NWD5) and 10 mm/day (NWD10) were part of the five EPIs. Trend and variability analyses were by the nonparametric technique based on the cumulative sum of the difference between exceedance and non-exceedance counts of data. The simple multiplicative bias correction method was employed to bias correct the PGF dataset using observed rainfall from nine weather stations. The number of wet days were decreasing although insignificant (p > 0.05). On the other hand, the annual total precipitation considering days with rainfall intensities greater than 5 mm/day (SPre5) exhibited a significant (p < 0.05) decrease. However, annual maxima rainfall (ANMS) increased even though insignificant. This indicates that less frequent rains are received over the study area but some events having high intensity. The insights from the findings of this study constitute a good baseline for predictive planning of water resources management applications across Mpologoma catchment.

High dimensional model representation for flood fragility analysis of highway bridge

Climate changes and global warming have increased the frequency and severity of rains, hence the vulnerability of structures due to floods. Bridges are the most affected components of the transportation infrastructure affected by floods. Analysis in a probabilistic framework is required for reliable performance assessments of bridges. However, the detailed performance assessment of bridges requires consideration of the uncertainties in geometry, material properties, and flood loading. The random structural responses due to flood loading can be obtained by stochastic analysis; conventionally, this is carried out using Monte Carlo Simulations (MCS). Due to the high computational cost required for MCS, non-statistical methods like High Dimensional Model Representation (HDMR) can be a feasible alternative to MCS. The present study is an application of the HDMR method to develop metamodels for the flood response of the highway bridge, considering the uncertainties. The structural responses due to flood at the sampling points of the HDMR are obtained by conducting finite element analysis. The HDMR could predict the random bridge responses due to flood loading fairly well compared to other popular response surface methods (like Central Composite Design, Box Behnken Design, and Full Factorial Design) with significantly fewer simulations. HDMR provides a flood response metamodel, as a function of the sensitive random parameters, with a substantial reduction in the computational effort. The efficiency of the HDMR method can be attributed to the ability of HDMR to model the nonlinear flood responses in terms of the statistical properties of random variables. The metamodels for the pier drifts developed are further utilized to generate flood fragility curves. The HDMR metamodels are found to simplify the fragility computations.

Flash Flood Risk Assessment Due to a Possible Dam Break in Urban Arid Environment, the New Um Al-Khair Dam Case Study, Jeddah, Saudi Arabia

Recent years have seen an increase in floods with severe damage due to the intensity and frequency of rains. One of the periodic hydrological problems affecting Jeddah city, the second-biggest city in Saudi Arabia, is unexpected flash flooding. In dam breaks, water that has been retained is released uncontrollably. This study is related to a flood simulation methodology after a possible break of the New Um Al-Khair Dam, a dam built in 2012 outside residential areas, to replace the Old Um Al-Khair Dam built inside a residential area, which broke in January 2011. In fact, we simulated the impact on flood wave propagation in the study area through the use of GIS techniques coupled with hydrological/hydraulic modeling tools and the development of a flood inundation model. Planning a good emergency response in the future is possible by analyzing a supposed disaster. Based on the likelihood that there will be a flood and the corresponding inundation depth, a flood risk matrix is created as a quantitative tool to estimate flood damage, which is crucial to decision-makers. Negligible, low, moderate, high, and very high-risk categories are assigned according to that flood risk matrix. The results indicated a low to very high risk for 5 years, 50 years and 100 years return periods and a negligible to very high risk for a 200 years return period. To estimate the extent of damage, a quantitative summary of the results has been outlined graphically in order to visualize the scope of the inundation areas.