Occurrence Of Heavy Rainfall Research Articles

The effect of flood on seasonal dynamics of Haemaphysalis (Acari: Ixodidae) tick vectors in Western Ghats forest area of Kerala, South India

Aim: Climate and weather conditions play a crucial role in the dynamics and distribution of ticks and tick-borne diseases. In this study, we explored the influence of a heavy rainfall (flood) occurrence on the seasonal activity and density of host-seeking Haemaphysalis tick vectors in Wayanad district, Kerala, India. Methodology: Wayanad district in Kerala state was selected as the study area. Ticks were collected from December 2017 to May 2019, monthly for five consecutive days by dragging method. Tick density was analyzed with climate data obtained from the meteorological station. Results: The total number of ticks collected post-flood decreased to 59% in Kurichiyad (site 1) and 63% in Muthanga (site 2), and the seasonal nymphal peak density was shifted. A seasonal peak of tick activity was normally observed from December to February. This peak occurrence was missing after flood in the study areas created with waterlogging and vegetation overgrowth. Interpretation: The present study revealed the effect of flood events in the study sites with significant differences in the abundance of five Haemaphysalis tick species during pre and post-flood periods and forest and wildlife habitats. This difference in the changing climatic conditions and increasing annual flood seasons in the Western Ghats may shift this region's ticks questing activity and tick-borne disease ecology.

Dynamic Pricing for Sensor-Cloud Platform in the Presence of Dumb Nodes

The presence of dumb nodes in sensor-cloud environment leads to degraded system performance. In this article, we consider the presence of dumb nodes in the sensor-cloud platform, and thereafter, propose a dynamic pricing scheme, while considering the existence of such nodes in the networks. The existing literature addresses the problem of pricing in sensor-cloud with the assumption of an ideal environment with normally functioning sensor nodes. The proposed pricing model considers the realistic existence of dumb nodes in sensor-cloud platforms. Further, the dumb behavior of a sensor node is dynamic in nature, as it is dependent on environmental conditions such as the occurrence of heavy rainfall, high temperature, and the presence of fog. However, in the absence of such adverse environmental conditions, the erstwhile dumb nodes resume normal behavior. The permanent removal of a dumb node from sensor-cloud is not always a feasible solution. When a dumb node is assigned to a virtual sensor, the existing pricing scheme in sensor-cloud charges same as other normal nodes. Thus, in such a situation, a user pays the normal price for a dumb node to the Sensor-Cloud Service Provider (SCSP). Consequently, the sensor owner of dumb node earn same profit as the owner of a normal node. Therefore, we formulate a scheme for <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Dynamic pricing in sensor-cloud environment in the presence of dumb nodes</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">DISCLOUD</i> ). As the presence of dumb nodes in sensor-cloud affects the Quality of Service (QoS), we propose a scheme considering QoS of the sensor-cloud. The proposed scheme, DISCLOUD, enables profit maximization of the SCSP, while considering the price required to be paid by end-user based on QoS.

On the utilization of RDCA method for detecting and predicting the occurrence of heavy rainfall in Indonesia

Accurate prediction of heavy rainfall events is crucial to mitigate hydrometeorological disasters. The real-time cloud observation by weather satellites Himawari-8 has enabled researchers to develop a nowcasting method (short-term prediction) to identify rainfall events in advance, namely the Rapidly Developing Cumulus Area (RDCA) method. The RDCA index, which is the product of the RDCA method, is the probability of occurrence of heavy rainfall. It has been evaluated and successfully utilized in Japan. However, the performance of the RDCA in the tropics has not been assessed yet. Indonesia —as a tropical country consisting of abundant islands— exhibits distinct climate and convective systems due to its geographical characteristics. Different temporal resolution of Himawari-8 data between Japan region (2.5 min) and the tropics (10 min) may also result in different RDCA performance. Therefore, it is important to conduct an evaluation study before operating the RDCA in Indonesia. By performing spatial comparison and using dichotomous and probabilistic verifications with rain gauges at various thresholds, this study finds that the RDCA is able to detect and predict rainfall events in Indonesia. The best lead time is 10 min but the predictive signals extend up to 30 min in advance; it is shorter than that observed in Japan. Lighter rainfall has higher predictability compared with heavier rainfall. The predicted heavy rainfall events show good accuracy, probability of detection, and brier score. The RDCA index and rainfall intensity appear to have a good correlation, where light (heavy) rainfall is better predicted by low (high) RDCA indices. It confirms the usefulness of varying RDCA index in contrast to the classic dichotomous RDCA index. This study reveals the positive prospects of RDCA in Indonesia. We also discuss some future challenges and give possible recommendations regarding an operational RDCA system. This study will benefit the development of early warning systems in Indonesia.

Analysis on the Development Situation of Geo-Hazards Based on Statistical Methods in Mainland China in Recent Years

In recent years, many geo-hazards were triggered by the frequent occurrences of sudden and regional extreme heavy rainfall, earthquake events, and human society and economic activities during urbanization, for example, the development of underground space. The authoritative data on geo-hazards that occurred in recent years in mainland China were collected. We analyzed the correlation of the conditions of triggering geo-hazards and the spatial and temporal characteristics based on the statistical data. From the findings, geo-hazards in China were controlled by numerous factors including topography, formation lithology, slope structure, fault, and geomorphic evolution. The geo-hazards depict the concentration and zonation distribution characteristics. The most occurred geo-hazards in China are landslides, collapses, and debris flow, and most are small to medium in scale. Heavy rainfall is the major triggering factor, and geo-hazards’ spatial distribution strongly correlates with spatial and temporal rainfall distribution. Finally, due to ongoing mitigation efforts, the development trend of casualties and economic losses caused by geo-hazards has shown a decreasing trend.

Proposal, application and partial validation of a simplified expression evaluating the stability of sandy slopes under rainfall conditions

One of the major causes of landslide triggering of sandy slopes is heavy rainfall occurrences. The present study (a) clarifies the mechanism of rainfall-induced failures of sandy slopes and (b) based on this mechanism proposes a simplified expression predicting the instability. The proposed expression in some aspects has a form similar to others previously proposed, but the novelty of the present study is that, by analysis, it is specified (a) in which type of soil it can be applied exclusively, (b) which is the depth of the sliding surface and (c) which drainage condition corresponds to the strength parameter and how to measure this parameter. In order to achieve this, first a simplified expression is proposed assessing the stability, based on the assumptions that (i) the problem can be treated as one-dimensional under drained conditions and (ii) temporary water flow exists just above a relatively impermeable inclined layer. Furthermore, the paper gives typical values of model parameters and predictions of the proposed equation. Next, it discusses the drained assumption used to obtain the proposed equation and the manner in which to measure the soil friction angle, needed in the proposed equation. Partial validation of the proposed equations is also performed at six well-documented landslides at two sites: Jiuzhaigou Park, China and Sifnos island, Greece, where geotechnical investigations are performed in order to establish the soil properties. Finally, it proposes, based on the developed equation, (i) a methodology assessing the stability of sandy slopes under rainfall conditions and (ii) mitigation measures.

Water pressure evolution and structural failure characteristics of tunnel lining under hydrodynamic pressure

With the frequent occurrence of heavy rainfall, the lining cracking, leakage, and buckling collapse accidents of water-rich mountain tunnels are becoming increasingly prominent. A large amount of surface water rushing into the tunnel in a short time and exceeding the drainage capacity of the tunnel is an important reason for the occurrence of water pressure diseases. To ascertain the failure characteristics of the lining structure under the condition of surface rainfall recharge and tunnel drainage, we designed a seepage model test system. The evolution law of water pressure behind lining, vertical displacement of invert and failure characteristics of structure under water pressure were studied. On this basis, the influence of the optimized drainage tunnel structure on the water pressure of the lining was further studied. The results show that the water pressure of the lining invert cannot be effectively reduced through the drainage system when the conventional drainage scheme is adopted, and the invert deforms and gradually cracks and fails under the action of hydrodynamic pressure. The cracking sequence of the lining structure is the invert center, the sidewall foot, the vault, and the sidewall. The type of cracks is mainly longitudinal, supplemented by circumferential and oblique. When the optimized drainage scheme is adopted, the water pressure at the bottom of the invert and the uplift displacement of the structure are significantly reduced, ensuring the safety of the lining structure.

Spatiotemporal patterns of synchronous heavy rainfall events in East Asia during the Baiu season

Abstract. Investigating the synchrony and interdependency of heavy rainfall occurrences is crucial to understand the underlying physical mechanisms and reduce physical and economic damages by improved forecasting strategies. In this context, studies utilizing functional network representations have recently contributed to significant advances in the understanding and prediction of extreme weather events. To thoroughly expand on previous works employing the latter framework to the East Asian summer monsoon (EASM) system, we focus here on changes in the spatial organization of synchronous heavy precipitation events across the monsoon season (April to August) by studying the temporal evolution of corresponding network characteristics in terms of a sliding window approach. Specifically, we utilize functional climate networks together with event coincidence analysis for identifying and characterizing synchronous activity from daily rainfall estimates between 1998 and 2018. Our results demonstrate that the formation of the Baiu front as a main feature of the EASM is reflected by a double-band structure of synchronous heavy rainfall with two centers north and south of the front. Although the two separated bands are strongly related to either low- or high-level winds, which are commonly assumed to be independent, we provide evidence that it is rather their mutual interconnectivity that changes during the different phases of the EASM season in a characteristic way. Our findings shed some new light on the interplay between tropical and extratropical factors controlling the EASM intraseasonal evolution, which could potentially help to improve future forecasts of the Baiu onset in different regions of East Asia.

English

The climate risk concept is crucial for agricultural production in vulnerable regions. In this work the climate conditions that influence the climate risk for rice crop in Casamance are presented. The future occurrence of drought and extreme precipitation conditions in the most critical phases of the rice plant evolution has been evaluated. Regional climate models (RCMs) outputs projections from CORDEX under two scenarios emissions (RCP4.5 and RCP8.5) in the mid of the twenty-first century were used to highlight the change in four extreme climate indices in the germination (JJ) and the flowering (Oct) stages of the rice plant in the Casamance region. The results suggest a potential risk in rice crop yield losses in the germination phase due to persistent drought conditions in the mid-twenty-first century namely in the low Casamance and the Middle Casamance; also increasing future occurrence of heavy rainfall may cause juvenile rice plant submersion that could contribute to rice production reduction. The flowering stage will present less climate risk situation in the future; the distribution of drought conditions seems to follow the normal north-south distribution; however hazardous extreme conditions could be expected in the future. There is a need to better plan agronomic and water management policies. &nbsp; Key words: Regional climate model, future projection, extreme precipitation, climate risk, rice crop, Casamance.

Analysis of extreme rainfall in Oti River Basin (West Africa)

Abstract Understanding how extreme rainfall is changing locally is a useful step in the implementation of efficient adaptation strategies to negative impacts of climate change. This study aims to analyze extreme rainfall over the middle Oti River Basin. Ten moderate extreme precipitation indices as well as heavy rainfall of higher return periods (25, 50, 75, and 100 years) were calculated using observed daily data from 1921 to 2018. In addition, Mann–Kendall and Sen's slope tests were used for trend analysis. The results showed decreasing trends in most of the heavy rainfall indices while the dry spell index exhibited a rising trend in a large portion of the study area. The occurrence of heavy rainfall of higher return periods has slightly decreased in a large part of the study area. Also, analysis of the annual maximum rainfall revealed that the generalized extreme value is the most appropriate three-parameter frequency distribution for predicting extreme rainfall in the Oti River Basin. The novelty of this study lies in the combination of both descriptive indices and extreme value theory in the analysis of extreme rainfall in a data-scarce river basin. The results are useful for water resources management in this area.

Future rainfall and temperature changes in Brazil under global warming levels of 1.5ºC, 2ºC and 4ºC

The present study analyzes the impacts of global warming of 1.5ºC, 2ºC, and 4ºC above pre-industrial levels in the Brazilian territory. Climate change projected among the different global warming levels has been analyzed for rainfall, temperature and extreme climate indices. The projections are derived from the global climate model HadGEM3-A, from the High-End cLimate Impacts and eXtremes (HELIX) international project, from the United Kingdom, forced by sea surface temperature and sea ice concentration of a subset of six CMIP5 (Coupled Model Intercomparison Project phase 5) global climate models and considering the RCP 8.5 (Representative Concentration Pathways) emissions scenario throughout the 21st century. Projections indicate robust differences in regional climate characteristics. These differences include changes: in the minimum and maximum air temperature close to the surface to all the country’s regions, in extremes of heat, particularly in northern Brazil, in the occurrence of heavy rainfall (Southern and Southeastern regions), and in the probability of droughts and rain deficits in some regions (Northern and Northeastern Brazil).

Climate change and its influence on occurrence and distribution of Anthrax in Bangladesh

Background: Anthrax is a serious infectious disease of human and animals. It is caused by the gram positive spore forming bacteria Bacillus anthracis. This study assessed the interrelationship between climate change and occurrence of anthrax outbreaks in Bangladesh. Methods & Materials: Meteorological daily data from 35 meteorological observatory stations across the country were collected from Bangladesh Meteorological Department, Dhaka and anthrax outbreak data were collected from Department of Livestock Services (DLS), Bangladesh from 2010 to 2014. The data were entered into a spreadsheet program (Excel 2007, Microsoft) and transferred into STATA/SE 13.0 for data analysis. Descriptive statistical analysis, Pearson correlation and regression analysis were applied. Results: The highest monthly outbreak number was 1,100 in September 2013 and the second highest was >800 in May 2010. The average, maximum and minimum temperature were recorded as 26.02333, 30.1 and 16.8 °C; humidity were 79.82%, 87.4% and 67.9%; rainfall were 5.988333, 19.5 and 0 mm; cloud coverage were 3.47, 6.5 and 0.6 h/day and wind speed were 2.45 knot, 3.9 knot and 1.4 knot, respectively over the country. There was a significant positive correlation (p < 0.05) among the outcome series and temperature (°C), rainfall (in mm), cloud coverage (in hour) and wind speed (knot). In case of temperature (°C), predicted anthrax outbreak = −130 + 14.836X temperature. When temperature increases by 1 °C, anthrax outbreak increases by 14.836. There was a peak of outbreaks each year in the summer and rainy season, March to September. Predicted anthrax outbreak for rainfall (in mm) = 199.4629 + 9.452X rainfall; for cloud coverage (1 h/day) = 128.75 + 36.69X cloud coverage and for wind speed (knot) = −6.0879 + 107.0X wind speed. When rainfall increases by 1 mm, cloud coverage increases by 1 h/day and wind speed increases by 1knot, anthrax outbreak increases by 9.452, 36.69021 and 107.0019, respectively. Conclusion: The results of the present study showed that increasing the ambient temperature and the occurrence of heavy rainfall as well as cloud coverage and wind speed acceleration in the monsoon season significantly contribute to the anthrax outbreaks in Bangladesh.

The climatological impact of the upper-tropospheric Rossby wave propagation on the Red Sea trough in winter

There is a prominent feature in the climate of the northeast Africa that, once activated, may cause heavy rainfall occurrence in large parts of the eastern Mediterranean (EM) and the Arabian Peninsula. The feature is Red Sea Trough (RST) which is an inverted trough of low pressure at lower troposphere wave over the northeast Africa and the Red Sea. This study investigates the way Rossby wave propagation in the upper troposphere may change the circulation of the lower troposphere and thus the surface weather in the northeast Africa, the Red Sea and the EM regions on a monthly time scale. The interaction between the wave activity flux at the 300 hPa level and the lower tropospheric circulation is investigated with consideration of the meteorological quantities at different levels of the troposphere in a wide region from the western North Atlantic to the EM. For this, two critical phases of the wave activity flux are defined. The critical positive (negative) phase corresponds to the months during which the amount of wave activity entering the region of study is higher (lower) than the climatological mean plus (minus) one standard deviation. The results show that during the critical positive phase, in the northeast Africa, the mean meridional circulation is strengthened throughout the troposphere. Further consequences of the positive phase are the strengthening and interconnection of the divergence cores of the Atlantic and Mediterranean storm tracks, strengthening of the RST and thus locally-unstable conditions leading to higher monthly precipitation in large parts of the study region.

Effect of Heavy Rainfall on Nitrogen and Phosphorus Concentrations in Rivers at River-net Plain

To understand the quantitative effect of heavy rain on nitrogen and phosphorus pollution in river-net plain, daily observations of nutrient concentrations in two rivers, flowing into Lake Taihu, were conducted from 1st September, 2017 to 31st August, 2019. The daily rainfall was recorded by auto-recording meteorological stations located on the two rivers and the Taihu Laboratory for Lake Ecosystem Research. Intensive sampling in different sections of the two rivers during Super Typhoon Lekima was also conducted in August 2019. Using these datasets, the influence of heavy rainfall on various forms of nitrogen and phosphorus concentrations in the rivers, and its environmental effects, were analyzed. The results showed that 16 heavy rainfall events (19 d) were observed in two years, 50% of which occurred in the summer season. In addition, heavy rainfall accounted for as much as 41.33% of the total rainfall over the entire year. After the period of heavy rainfall, the concentrations of various forms of nitrogen and phosphorus increased, and the particulate P generally exhibited the fastest response, usually peaking on the day of heavy rainfall. In contrast, the peaks of N were delayed for 2-5 days with the occurrence of heavy rain. In general, the duration of the increase in the concentration of nutrients in the study river caused by heavy rainfall was short (usually 1-2 days), and sometimes was lower than the concentration before the rains. The Dapu River exhibited a slower response to heavy rains than the Yincun River because it has a larger and longer catchment area than the Dapu River. In addition, the effect of heavy rain on N and P concentrations was also strongly influenced by the land-use situation around the river basin. The increase of nitrogen in the reach, affected by agricultural non-point sources, was dominated by granular nitrogen, and the increase of nitrogen in the reach affected by urban non-point sources was dominated by dissolved nitrogen. The increase of phosphorus was dominated by granular phosphorus in the entire process. The conclusions of this study are as follows:In the plain river network area, the fluctuations of nitrogen and phosphorus concentrations in the river water body caused by heavy rainfall are small, and the response of various forms of nitrogen and phosphorus are significantly affected by the local environmental background. Therefore, the water quality generally exhibited limited variation. Due to the large proportion of water entering the lake during heavy rainfall events, a high level of the nutrient loading was also observed, and the occurrence of heavy rainfall was occasional. The short-term effect of heavy rainfall on the nitrogen and phosphorus loading entering the lake in the river channel in the plain river network area is therefore, also significant, and requires further investigation.

Radiocesium levels in contaminated forests has remained stable, even after heavy rains due to typhoons and localized downpours

In recent years, Japan has suffered serious damage due to natural disasters such as earthquakes, heavy rains due to tropical storms (typhoons) and localized downpours. To assess the chronological changes in the attenuation of external exposure doses and environmental radiation contamination due to the rainfall associated with typhoons and heavy rains during October to December 2019 in Fukushima, we measured environmental radiation levels in forest areas along the Mt Okura hiking trail in Tomioka Town, Fukushima Prefecture, near the Fukushima Daiichi Nuclear Power Station. We confirmed that (1) current ambient dose rates of 0.38–0.95 μSv/h in most forest areas were 79.9–84.7% higher than in residential areas; (2) the number of sites along the hiking trail where 137Cs was detected was limited (1.1–4.7%); and (3) individual dose rates of 0.21–0.34 μSv/h were lower than ambient dose rates. These findings suggest that radiocesium has remained stable in natural forests that have not been decontaminated even though current levels are low, despite the occurrence of heavy rainfall associated with Super Typhoon Hagibis in 2019 and localized downpours. Hiking while managing exposure to environmental contamination using a personal dosimeter may be the safest model for spending time of leisure activities.

Role of Boundary Layer Jet in the Occurrence and Development of Warm-sector Heavy Rainfall over South China: a Case Study

Warm-sector heavy rainfall which occurred at the coastal area of southern China on 8 June 2015 was associated with a boundary layer jet (BLJ). The initiation and maintenance mechanism of the BLJ is further investigated based on the Weather Research and Forecasting (WRF) model simulations and reanalysis data. The results showed that the BLJ developing at night transported moisture to the coastal area of Guangxi in southern China, which lead to the instability of the atmosphere over the coastal areas of Guangxi. The terrain blocking and lifting the southerly with abundance of water vapor is the major trigger mechanism in present case. As the BLJ weakened and vanished after midday, the amount of rainfall decreased correspondingly. Based on the numerical model sensitivity test with different parameterization schemes, the key role of the BLJ for the occurrence and development of the warm-sector heavy rainfall is further verified.

Relationships Between Jianghuai Meiyu Anomaly and the Collaborative Evolution of Wave Trains in the Upper and Lower Troposphere in Mid-July of 2020

Based on the ECMWF reanalysis dataset (ERA5), SST , OLR and the daily precipitation data, the relationship between the Meiyu anomaly in the Yangtze-Huaihe river basin (YHB) and the collaborative evolution of wave trains in the upper and lower troposphere in the mid-July of 2020 is analyzed. The results show that the key circulation background for the long-lasting Meiyu season in the summer of 2020 is the coexistence and collaborative evolution of the Silk-Road (SR) wave train in the upper troposphere and the – + Pacific-Japan (PJ) wave train in the middle-lower troposphere, which is in favor of the movement towards each other of the South Asia high (SAH) and the western Pacific subtropical high (WPSH), resulting in the upper-level divergence over the YHB where is the right side of the jet entrance area. The WPSH strengthens and extends westward, transporting abundant water vapor to the YHB from the Western Pacific and South China Sea. Meanwhile, the meridional circulation develops at the middle and high latitudes, which is in favor of cold-dry air and warm-moist air strongly interact over the YHB, leading to the long-lasting Meiyu season. The coordinative evolution of the SR and PJ wave trains not only affects the persistence and intensity of precipitation in the YHB, but also can be regarded as a precursor signal for the occurrence of persistent heavy rainfall to some extent. The wave-activity flux dispersing eastward along the upper-level jet is beneficial to the development and maintenance of the SR wave train, and the poleward dispersing wave-activity flux is related to the development and maintenance of the PJ wave train. Additionally, along with the weakening El Nino in 2019, the anomalous convection caused by the warm SST in the Western Pacific warm pool is conducive to the formation and maintenance of the PJ wave train. The abnormal convection caused by the warm SST in the Indian Ocean and the east coast of the tropical Atlantic may affect the SR wave train. These are also one of the reasons for the long Meiyu season in 2020.

Advanced risk-based event attribution for heavy regional rainfall events

Risk-based event attribution (EA) science involves probabilistically estimating alterations of the likelihoods of particular weather events, such as heat waves and heavy rainfall, owing to global warming, and has been considered as an effective approach with regard to climate change adaptation. However, risk-based EA for heavy rain events remains challenging because, unlike extreme temperature events, which often have a scale of thousands of kilometres, heavy rainfall occurrences depend on mesoscale rainfall systems and regional geographies that cannot be resolved using general circulation models (GCMs) that are currently employed for risk-based EA. Herein, we use GCM large-ensemble simulations and high-resolution downscaled products with a 20-km non-hydrostatic regional climate model (RCM), whose boundary conditions are obtained from all available GCM ensemble simulations, to show that anthropogenic warming increased the risk of two record-breaking regional heavy rainfall events in 2017 and 2018 over western Japan. The events are examined from the perspective of rainfall statistics simulated by the RCM and from the perspective of background large-scale circulation fields simulated by the GCM. In the 2017 case, precipitous terrain and a static pressure pattern in the synoptic field helped reduce uncertainty in the dynamical components, whereas in the 2018 case, a static pressure pattern in the synoptic field provided favourable conditions for event occurrence through a moisture increase under warmer climate. These findings show that successful risk-based EA for regional extreme rainfall relies on the degree to which uncertainty induced by the dynamic components is reduced by background conditioning.

Frequency Trend Analysis of Heavy Rainfall Days for Germany

Climate change is expected to affect the occurrence of heavy rainfall. We analyzed trends of heavy rainfall days for the last decades in Germany. For all available stations with daily data, days exceeding daily thresholds (10, 20, 30 mm) were counted annually. The Mann–Kendall trend test was applied to overlapping periods of 30 years (1951–2019). This period was extended to 1901 for 111 stations. The stations were aggregated by natural regions to assess regional patterns. Impacts of data inconsistencies on the calculated trends were evaluated with the metadata and recent hourly data. Although the trend variability depended on the chosen exceedance threshold, a general long-term trend for the whole of Germany was consistently not evident. After 1951, stable positive trends occurred in the mountainous south and partly in the northern coastal region, while parts of Central Germany experienced negative trends. The frequent location shifts and the recent change in the time interval for daily rainfall could affect individual trends but were statistically insignificant for regional analyses. A case study supported that heavy rains became more erosive during the last 20 years. The results showed the merit of historical data for a better understanding of recent changes in heavy rainfall.

Preliminary result of capturing the signature of heavy rainfall events using the 2-d-/4-d water vapour information derived from GNSS measurement in Hong Kong

Apart from the well-known applications like positioning, navigation and timing (PNT), Global Navigation Satellite System (GNSS) has manifested its ability in many other areas that are vital to society largely. With the dense setting of the regional continuously operating reference station (CORS) networks, monitoring the variations in atmospheric water vapour using a GNSS technique has become a focus in the field of GNSS meteorology. Most previous studies mainly concentrate on the analysis of relationship between the two-dimensional (2-d) Precipitable Water Vapour (PWV) and rainfall while the three-dimensional (3-d) variations of atmospheric water vapour derived from the GNSS tomographic technique are more rarely discussed. In this work, we investigate changes in the emerging field of GNSS technology for monitoring changes in 2-d/3-d atmospheric water vapour during rainfall period. The signature of atmospheric water vapour variation was captured using the ground-based GNSS observations from the CORS network of Hong Kong which presents the particularity of being dense. In addition, the corresponding rain gauges and radiosonde stations are also used. Our analysis of the 2-d PWV/3-d water vapour profiles changes during the arrival, occurrence and depression of heavy rainfall shows that: (i) PWV increases before the arrival of heavy rainfall (ii) and decreases to its average value after the depression of rainfall; (iii) rainfall leads to an anomalous variation in relative humidity and temperature while their trends are totally opposite; (iv) atmospheric water vapour presents unstable conditions with intense vertical convective and horizontal convergence motions and hydrometeors are formed before the arrival of rainfall. This study indicates the potential of using GNSS technique to monitor spatio-temporal variations of atmospheric water vapour during rainfall period, which provides a better understanding of the mechanism of convection and rainfall induced by the extreme weather events.

Reservoir Lake Effects on Eroded Littoral Systems: The Case of the Bay of Marbella, Southern Spain

Del Río, J.L.; Malvárez, G., and Navas, F., 2020. Reservoir lake effects on eroded littoral systems: The case of the Bay of Marbella, southern Spain. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 443-447. Coconut Creek (Florida), ISSN 0749-0208.The Bay of Marbella, in Western Costa del Sol (southern Spain), is one of the most artificialized coastal areas of the Mediterranean. Environmental factors, such as geology and climatic conditions, have supported a great variety of industrial activities over time. However, tourism industry positioned Marbella as an internationally renowned destination demanding the rapid artificialisation of its hinterland between the 1970s and the 1990s, relying such process on natural resources -mainly water- for urban sprawl. Small reservoir lakes were constructed in the 19th century for iron melting and irrigation industries, but the greatest water management infrastructure for the development of the tourism industry, La Concepción Dam, was constructed in the 1970s in the lower reaches of the Rio Verde, the main river in the area. Although a significant amount of water is stored in the dam, the presence of steep slopes and the likely occurrence of heavy rainfall during winter generate torrential water runoff with high energy and high rates of sediment yield. The dam performs as a sediment trap and has induced the annulment of the main source of sediment supply to the littoral system, inducing severe coastal erosion processes which have not been successfully tackled yet. This paper presents a first order estimate of sediment yield in the Río Verde watershed introducing sediment budget stored within La Concepción reservoir. Results show that potential high sediment yield rates estimated in the Rio Verde watershed might have reached La Concepción Dam and might have contributed to the siltation of the reservoir lake and direct coastal erosion. Whilst recognised as the main culprit, no action is undertaken by the decision-makers to extract and reutilise sediments silting coastal dams.