Frequency Of Heavy Rainfall Research Articles

Detection and Monitoring of Potential Geological Disaster Using SBAS-InSAR Technology

As a global geological environment problem, geological disasters are more likely to induce severe geological disasters and cause loss of personnel and property due to their suddenness and concealment, frequent heavy rainfall and regular extreme weather. In this paper, Sentinel-1A data and DEM data combined with short baseline synthetic aperture interferar (SBAS-InSAR) technology are used to analyze and calculate the spatial-temporal evolution characteristics of surface deformation in Zibo-Weifang area of Shandong Province during 2016–2019. Linear fitting of InSAR monitoring deformation results is performed using level monitoring data to verify the accuracy of the results. The findings indicate that surface deformation in most of the study area is relatively stable, but in some areas, especially near Lucun Town, the maximum negative deformation rate exceeds 80mm/a. Based on the surface deformation results, a total of 377 potential geological disasters are identified using an integrated multi-source stereo observation system of the sky and ground. This identification is done by observing optical remote sensing images and taking the absolute value of surface deformation rate greater than 10 mm/a as the judgment basis, along with ground investigation and review. Several typical geological disaster sites are screened and they are found to be in unstable state. The research results can provide scientific support for geological disaster prevention and control in Shandong Province.

Impact of Vegetation Differences on Shallow Landslides: A Case Study in Aso, Japan

Climate change has increased the frequency and scale of heavy rainfall, increasing the risk of shallow landslides due to heavy rainfall. In recent years, ecosystem-based disaster risk reduction (Eco-DRR) has attracted attention as one way to reduce disaster risks. Vegetation is known to increase soil strength through its root system and reduce the risk of shallow landslides. To reduce the risk of shallow landslides using vegetation, it is necessary to quantitatively evaluate the effects that vegetation has on shallow landslides. In this study, we constructed a generalized linear model (GLM) and random forest (RF) model to quantitatively evaluate the impact of differences in the vegetation, such as grasslands and forests, on the occurrence of shallow landslides using statistical methods. The model that resulted in the lowest AIC in the GLM included elevation, slope angle, slope aspect, undulation, TWI, geology, and vegetation as primary factors, and the hourly rainfall as a trigger factor. The slope angle, undulation, and hourly rainfall were selected as significant explanatory variables that contribute positively to shallow landslides. On the other hand, elevation and TWI were selected as significant explanatory variables that contribute negatively to shallow landslides. Significant differences were observed among multiple categories of vegetation. The probability of shallow landslide in secondary grasslands was approximately three times that of coniferous and broadleaf forests, and approximately nine times that of broadleaf secondary forests. The landslide probability of shrubs was approximately four times that of coniferous and broadleaf forests, and approximately ten times that of broadleaf secondary forests. The results of constructing the RF model showed that the importance was highest for the hourly rainfall, followed by geology, then elevation. AUC values for the GLM and RF model were 0.91 and 0.95, respectively, indicating that highly accurate models were constructed. We quantitatively showed the impact of differences in vegetation on shallow landslides. The knowledge obtained in this study will be essential for considering appropriate vegetation management to reduce the risk of future shallow landslides.

Effects of simulated extreme precipitation flooding on the degradation of anaerobic digestion effluent by algal-bacterial symbiosis system

Precipitation is directly affected by global warming among different extreme climate types. The moisture-holding capacity of the atmosphere increases by 7% with a temperature increase of 1 °C. A higher moisture content results in frequent and violent rainfall events, and the frequency and intensity of heavy rainfall and flooding events in certain countries and regions is gradually aggravated. Simulated extreme precipitation experiments with precipitation intensities of 50, 100, and 200 mm and precipitation time on 3th, 6 th, and 9 th day were set to study the effects of extreme precipitation and flooding events on the degradation performance of open algae–bacteria symbiotic (ABS) system for anaerobic digestion effluent (ADE). The experimental results showed that the precipitation time had an obvious impact on the open algae–bacteria symbiotic system. The daily COD (chemical oxygen demand) degradation rates in the algae–bacteria symbiotic system on the fourth day decreased from 12.64% (unaffected by precipitation) to 2.94, 2.38, and 1.90%, respectively, under the conditions of rainfall on the third day and precipitation intensities of 50, 100, and 200 mm. At the end of the experiments, the COD contents in the ADE increased from 355.09 mg/L (unaffected by precipitation) to 435.77, 413.67, and 403.54 mg/L, respectively. The degradation effects of COD, TN (total nitrogen), and TP (total phosphorus) in the open algae–bacteria symbiotic system were affected by extreme precipitation (200 mm) and flooding. On the third day of the heavy rainfall event, Actinobacteria, Proteobacteria, and Bacteroidetes were the most dominant phyla in the samples of the symbiotic system between algae and bacteria. Among them, the abundance of Proteobacteria and Bacteroidetes was the highest, accounting for 15.33, 21.33 and 19.97%, respectively. As the symbiotic system operated stably, their proportions decreased to 13.58, 12.13, and 17.85% on the ninth day. At the class level, the abundance of Beta-proteobacteria and Gamma-proteobacteria was relatively high in the samples of the symbiotic system. On the third day of the heavy rainfall event, they accounted for 8.99 and 7.11%, respectively. With the stable operation of the system, their proportions showed a decreasing trend, and on the sixth and ninth days, they were 7.03% and 6.01, 4.87 and 4.39%, respectively.

Assessment of weather events impacts on forage production trend of sorghum-sudangrass hybrid.

This study aimed to assess the impact of weather events on the sorghum-sudangrass hybrid (Sorghum bicolor L.) cultivar production trend in the central inland region of Korea during the monsoon season, using time series analysis. The sorghum-sudangrass production data collected between 1988 and 2013 were compiled along with the production year's weather data. The growing degree days (GDD), accumulated rainfall, and sunshine duration were used to assess their impacts on forage production (kg/ha) trend. Conversely, GDD and accumulated rainfall had positive and negative effects on the trend of forage production, respectively. Meanwhile, weather events such as heavy rainfall and typhoon were also collected based on weather warnings as weather events in the Korean monsoon season. The impact of weather events did not affect forage production, even with the increasing frequency and intensity of heavy rainfall. Therefore, the trend of forage production for the sorghum-sudangrass hybrid was forecasted to slightly increase until 2045. The predicted forage production in 2045 will be 14,926 ± 6,657 kg/ha. It is likely that the damage by heavy rainfall and typhoons can be reduced through more frequent harvest against short-term single damage and a deeper extension of the root system against soil erosion and lodging. Therefore, in an environment that is rapidly changing due to climate change and extreme/abnormal weather, the cultivation of the sorghum-sudangrass hybrid would be advantageous in securing stable and robust forage production. Through this study, we propose the cultivation of sorghum-sudangrass hybrid as one of the alternative summer forage options to achieve stable forage production during the dynamically changing monsoon, in spite of rather lower nutrient value than that of maize (Zea mays L.).

Kosi-Ganga-River-Creek 35 years’ Additive Time Series and Seasonal Analysis Using Remote Sensing Data.

Climate change effect can be observed around the globe but the most devastation is faced by economically weak and farmers in India. Kosi-Ganga-River-Creek area has witnessed frequent floods and heavy rainfall over the years. The study area is the creek where Kosi and Ganga river joins together in the Katihar district of Bihar, India. Two variables, total daily precipitation (PTot) and max daily air temperature (Tmax) (remote sensing climatological data) were fetched from ERA5 dataset using Google Earth Engine Coder to assess the climate change in the study area. The data shows stochastically fitting in further forecasting methods is as important to conduct as settings the approach reliability. This study applied exclusively time series analysis (such as decomposing a time series, seasonal subseries, and autocorrelation function (ACF) and lag time series) along with descriptive statistical analysis for both parameters of the dataset. The study found the changes in Tmax over the 30-year time period show significant variability in temperature. Tmax peaked during the year of 1990, 1995, 1998, 2004, 2008, 2012 and 2014 whereas a drop in Tmax before and after such rise was observed in the series pattern. The exponential increase in the seasonal monthly precipitation (Ptot) also correlates with the temperature increase. However, the increase is more during non-monsoon seasons like January, February and March. Although significant reduction in Ptot can be observed during May, June, July, August and September. The changes in Ptot and Tmax have caused severe damage to the agriculture and economy of the area. Thus it is essential to study climate change and forecast the probable changes in future along with other climatological conditions to mitigate the extreme weather effect. Without proper study, monitoring, assessment and management policies in Bihar will most likely continue to suffer due to agricultural losses, lively hood, life, economic losses and infrastructure.

Exploring an Integrated System for Urban Stormwater Management: A Systematic Literature Review of Solutions at Building and District Scales

Climate change has aggravated the frequency and severity of extreme weather events, particularly in flood-related hazards. Cities nowadays face significant challenges in stormwater management from frequent heavy rainfalls. Traditional urban drainage systems can no longer cope with large amounts of surface runoff; cities are searching for new ways to deal with urban stormwater. Green roofs and other nature-based solutions have been widely used for stormwater management by combining water purification and retention functions but have not yet fully solved the flood problems. This article aims to (1) explore the different aspects of urban water management, particularly the urban stormwater topic, and (2) identify the existing solutions and discuss the potential and barriers to integrated solutions implementation. By introducing the concept of four domains and finding the overlapping area to investigate, we analyzed different solutions to reduce rainwater runoff from the roof and ground level, aiming at building and district scales. This paper proves that further research direction could constitute an integrated system to work together for urban stormwater management.

Transcriptomic, Physiological, and Metabolomic Response of an Alpine Plant, Rhododendron delavayi, to Waterlogging Stress and Post-Waterlogging Recovery.

Climate change has resulted in frequent heavy and prolonged rainfall events that exacerbate waterlogging stress, leading to the death of certain alpine Rhododendron trees. To shed light on the physiological and molecular mechanisms behind waterlogging stress in woody Rhododendron trees, we conducted a study of Rhododendron delavayi, a well-known alpine flower species. Specifically, we investigated the physiological and molecular changes that occurred in leaves of R. delavayi subjected to 30 days of waterlogging stress (WS30d), as well as subsequent post-waterlogging recovery period of 10 days (WS30d-R10d). Our findings reveal that waterlogging stress causes a significant reduction in CO2 assimilation rate, stomatal conductance, transpiration rate, and maximum photochemical efficiency of PSII (Fv/Fm) in the WS30d leaves, by 91.2%, 95.3%, 93.3%, and 8.4%, respectively, when compared to the control leaves. Furthermore, the chlorophyll a and total chlorophyll content in the WS30d leaves decreased by 13.5% and 16.6%, respectively. Both WS30d and WS30d-R10d leaves exhibited excessive H2O2 accumulation, with a corresponding decrease in lignin content in the WS30d-R10d leaves. At the molecular level, purine metabolism, glutathione metabolism, photosynthesis, and photosynthesis-antenna protein pathways were found to be primarily involved in WS30d leaves, whereas phenylpropanoid biosynthesis, fatty acid metabolism, fatty acid biosynthesis, fatty acid elongation, and cutin, suberin, and wax biosynthesis pathways were significantly enriched in WS30d-R10d leaves. Additionally, both WS30d and WS30d-R10d leaves displayed a build-up of sugars. Overall, our integrated transcriptomic, physiological, and metabolomic analysis demonstrated that R. delavayi is susceptible to waterlogging stress, which causes irreversible detrimental effects on both its physiological and molecular aspects, hence compromising the tree's ability to fully recover, even under normal growth conditions.

Climate and dengue transmission in Grenada for the period 2010–2020: Should we be concerned?

The impacts of climate change on vector-borne and zoonotic diseases (VBZD) are well founded in some countries but remain poorly understood in Caribbean countries. VBZD impose significant burdens on individuals and healthcare systems, heightening the need for studies and response measures to address epidemics and persistent high prevalence of these diseases in any region. This study analyses the pattern of dengue case distribution in Grenada between 2010–2020 and investigates the relationship between rainfall and cases. The total number of dengue cases in the wet seasons (June to December) and dry seasons (January to May) were 1741 and 458, respectively, indicating higher prevalence of the disease in wet periods. The data also shows that rainfall was not consistently higher during the typical rainy season months. The observed patterns in 2013, 2018 and 2020 show, while these were the driest years, the number of cases were higher than in other years. Two factors may explain high number of cases in the drier years (1) frequent sporadic heavy rainfall and (2) poor water storage practices in dry season. With each 30 mm unit decrease in annual rainfall, the incidence rate ratio of dengue was reduced by a factor of .108 (89.2%). The work of the Vector Control Unit is shown to be effective in managing dengue in Grenada. The study highlights the need for year-round surveillance and interventions to control the mosquito population and dengue transmission.

Characteristics of water vapor isotopes and moisture sources for short-duration heavy rainfall events in Nanjing, eastern China

Short-duration heavy rainfall causes severe urban flooding, threatening urban security and socio-economic development. The lower reaches of the Yangtze River are one of the regions with the highest frequency of short-duration heavy rainfalls in China. In this study, hourly stable isotope compositions in water vapor (δ18Ov and d-excessv) are analyzed for nine short-duration heavy rainfall events during the summer monsoon season (June to September) from 2013 to 2021 in Nanjing, eastern China. The circulation patterns that lead to these events can be divided into four types: tropical cyclone, low-pressure vortex, cold front, and western North Pacific subtropical high. During these events, δ18Ov is enriched, ranging from −18.8 ‰ to −13.7 ‰ with a pre-storm increasing trend. This is largely caused by strongly isolated meso- and small-scale convections and the close proximity of oceanic moisture sources. The d-excessv shows three different variation patterns during rainfall events: increasing, decreasing, and irregular fluctuations. They each correspond to the increasing contribution of terrestrial moisture from eastern China, proximal oceanic moisture from China’s offshore waters (including the South China Sea, East China Sea, and Yellow Sea), and the mixing influence of these two moisture sources. Multiple patterns of the d-excessv variations reflect both importance of terrestrial moisture from eastern China and oceanic moisture from China’s offshore waters for summer short-duration heavy rainfall events in eastern China.

Divergent Urban Signatures in Rainfall Anomalies Explained by Pre‐Storm Environment Contrast

AbstractDiverse urban‐induced rainfall anomalies across different cities highlight the need for additional insights into land‐atmosphere interactions over complex urban environments. Based on empirical analyses of 144 warm‐season storms and high‐resolution numerical simulations over Nanjing, China, we show divergent patterns of urban‐induced rainfall anomalies for storms with contrasting synoptic conditions, despite of rainfall enhancement over downtown from a climatological perspective. We propose two simple gage‐based metrics to characterize both the thermal and turbulent conditions in pre‐storm environment, and classify storms into different groups. Our results show that elevated rainfall magnitudes and heavy rainfall frequency are equally expected in either downtown or suburb regions (upwind or downwind). This is mainly dictated by the relative dominance of urban‐induced thermal perturbations and mechanical turbulence (i.e., related to surface roughness) under different synoptic conditions. We develop four paradigms of urban rainfall modification, and thus provide a predictive understanding of rainfall anomalies in urban environments.

Towards a Combined Physical and Social Evaluation of Climate Vulnerability in Coastal Urban Megacities

Coastal urban megacities across Asia face significant risks from climate change, including coastal flooding, high temperatures, urban heat island impacts and air pollution. These hazards are associated with negative impacts on infrastructure, communities and the environment. To identify the current intensity of climate change impacts in coastal urban megacities, an integrated evaluation method is needed. Firstly, the present study assesses the climate change impacts of Guangzhou, a Chinese coastal urban megacity, for both physical and social aspects. This study includes 60 years of time-series data for 1960–2020 to examine temperatures, precipitation, humidity and air pollution in Guangzhou city. At the same time, a survey was conducted between April and July 2022 in this megacity and collected the views of 336 people on climate change and its associated environmental impacts. Secondly, the Ganzhou city results are compared with existing data from similar nearby cities to evaluate the diverse climate change trends. Results show that during 1961-1990, the city received the most rainfall in May, reaching 283.6 mm. From 1990 to 2020, June recorded the highest rainfall of 356.6 mm and shows an increase of 73 mm during that period. The very severe monsoon season brought an increased risk of flooding. Results also revealed that the warmest month is July, and the coldest month is January, and both months showed increased temperatures of 0.60 ℃. Comparison results revealed that Guangzhou is not the only city which scored increased highest temperatures; other nearby cities including Heyuan, Shantou and Shaoguan also scored increased highest temperatures. The survey reveals that the majority of respondents (75%) perceived the increased frequency of extreme weather, including typhoons, heavy rainfall and multiple days of hot weather, such as higher temperatures and an increased number of hot days. In the responses to the questions related to the heat island effect, more than 80% of residents are aware of the existence of the heat island and its impacts. People believe that the primary causes of the urban heat island problem are industrial production and anthropogenic heat generated by the city. These results will be helpful to local and national policy and decision makers to revise and/or develop new strategies to improve the environment and quality of life in coastal megacities, particularly Ganzhou.

Outbreak of Rice Panicle Blast in Jeonbuk Province of Korea in 2021

Rice panicle blast is one of the most serious diseases threatening stable rice production by causing severe damage to rice yields and quality. The disease is easy to occur under low air temperature and frequent heavy rainfall during the heading season of rice. In 2021, a rice panicle blast severely occurred in the Jeonbuk province of Korea. The incidence area of panicle blast accounted for 27.7% of the rice cultivation area of Jeonbuk province in 2021, which was 13.7-times higher than in 2019 and 2.6-times higher than in 2020. This study evaluated the incidence areas of rice panicle blast in each region of Jeonbuk province in 2021. The weather conditions during the heading season of rice, mainly cultivated rice cultivars, and the race diversity of the Jeonbuk isolates were also investigated. It will provide important information for the effective control of the rice panicle blast.

SOME ASPECTS OF THE LATEST FLOODING IN THE KHERSON REGION

Problem Description and Purpose of the Study. This article examines the problem of flooding of settlements in the Kherson region. The purpose of the study is to identify the latest risks of flooding of populated areas in the Kherson region and to formulate a list of measures aimed at reducing the threats and consequences of flooding. Data & Methods. The research used data from the Kherson Regional Center for Hydrometeorology; Main Department of the State Emergency Service of Ukraine in the Kherson Region; The Department of Civil Protection of the Kherson Regional State Administration, the Office of the Kakhovskaya HPP. Among the research methods, the comparative method, cartographic and geo-informational methods, correlational, expert method were used. Results. Kherson region has the largest share of irrigated land among all regions of Ukraine. This fact, as well as the presence of significant waterless areas, reductions in the relief with the release of groundwater and water loss along the main irrigation canals, leads to constant flooding of certain areas. The most affected areas arelocated in the paludal depressions and coastal lowlands. Due to the strengthening of the continentality of the climate, the precipitation regime is also changing. The territory is characterised by summer-autumn rains with daily precipitation above 30 mm, which causes sudden flooding of downgrades and rise of groundwater in these periods. In order to monitor the potential risk of flooding, it is proposed to monitor interdependence: the water level of the Kakhovka Water Reservoir – the level of groundwater. Although this dependence has a deferred character, thus it is confirmed every year. There are four irrigation systems in the region: North Crimean, Kakhovka, Inhulets and Pravoberezhia (Right-Bank). Each year, the area of irrigated land increases from 0.1 to 1.0 thousand hectares, which significantly increases the risks of flooding in combination with the frequency of heavy rainfall. In a number of settlements with a high probability of flooding, a system of vertical and horizontal drainage has been built, but it requires constant maintenance and usually does not cope with its tasks.

The features and probability forecasting of short–duration heavy rainfall in the Beijing-Tianjin-Hebei region caused by North China cold vortices

Based on hourly station precipitation data and ECMWF ERA5 reanalysis data from 2009 to 2019, this paper explores the temporal variations and spatial distribution of short–duration heavy rainfall (SDHR) induced by North China cold vortices (NCCV) over the Beijing-Tianjin-Hebei (BTH) region, and comparatively analyzes the characteristic of environmental parameters and then choose some predictors to make probability forecasting for short–duration heavy rainfall induced by North China cold vortices. Results show that short–duration heavy rainfall has obviously interannual, monthly and diurnal variations. Areas of high short–duration heavy rainfall frequency caused by North China cold vortices exhibit eastward movement, which generally locate along the mountain areas of the Beijing-Tianjin-Hebei region in the afternoon, and moves to the coastal areas of the Beijing-Tianjin-Hebei region after midnight. In general, short–duration heavy rainfall induced by North China cold vortices mainly occurs in 16:00–21:00 and around 02:00–05:00, showing a delayed peak time and a secondary peak time in recent years. Besides, short–duration heavy rainfall caused by North China cold vortices occurs fewer but more extremely over the northwestern and southern parts of the Beijing-Tianjin-Hebei region, more frequently and extremely over the border area of the Beijing-Tianjin-Hebei region, and more frequently but with moderate intensity over the coastal area of the Beijing-Tianjin-Hebei region. By comparing the distribution characteristics of some physical parameters for three categories of no precipitation, ordinary precipitation, and short–duration heavy rainfall weather induced by North China cold vortices, it is found that moisture and atmospheric instability conditions have great significance for the occurrence of short–duration heavy rainfall caused by North China cold vortices. Probability forecast for short–duration heavy rainfall caused by North China cold vortices is made based on ingredient method and fuzzy logic algorithms. The result shows the products have good performance, further implying the significance of the environmental parameters for forecasting short–duration heavy rainfall caused by North China cold vortices.

Response of White Cabbage (Brassica oleracea var. capitata) to Single and Repeated Short-Term Waterlogging

Climate change has a significant impact on the agricultural sector, negatively affecting plants’ growth and development, with predicted strong consequences on food availability in the future. Although we are experiencing more frequent and intense heavy rainfall events, a major contributor to field flooding, there is still not much known about the impact of these events on different crops. In this study, we investigated the effects of waterlogging on a model plant white cabbage (Brassica oleracea var. capitata f. alba), with the aim to follow its response to both single and recurrent short-term (72-h length) waterlogging, as well as to track difference in the sensitivity between plants in different growth stages (38- and 48-day-old plants). In our 22-day experiment, settled under fully controlled conditions (16 h day/8 h night, 25 °C day/20 °C night, 60–70% relative air humidity, 250 µmol m−2 s−1 photosynthetic active radiation), with the aim to more comprehensively recognize consequences of waterlogging on plants, we measured changes in plants on multiple levels: (i) within its morphological traits (number and length of leaves, leaf area, and blade width), (ii) within chlorophyll fluorescence and multispectral traits (20 parameters), (iii) following the levels of plant stress parameters (salicylic acid, abscisic acid, proline, and total polyphenols), and (iv) following changes in the plants’ elemental and mineral composition. According to our results, white cabbage was shown not to be very sensitive to waterlogging, with only plants exposed to repeated waterlogging showing signs of the congestion stress. These signs, observed in the changes of molecular stress parameters salicylic and abscisic acids, were not so clearly evident at the aboveground level. We did not observe changes in the plants’ morphologies, nor their photosynthetic performance. In addition, removal of waterlogging stress resulted in complete recovery of our model plants, suggesting a prompt adaptation response of white cabbage. With the projected increased frequency of occurrence of flooding events, it will become increasingly more important to recognize crops being highly sensitive to flooding with the aim to try to adapt to the changing climate.

Method for a new risk assessment of urban inundation: G-DEMATEL–AHP

Urban flooding disasters caused by frequent heavy rainfall threaten the safety of residents and socioeconomic development. Thus, risk evaluation of urban inundation is a vital component of sustainable urban development. Analytical hierarchical process (AHP) and decision-making trial and evaluation laboratory (DEMATEL) are common methods applied to flood risk evaluation. The former focuses on the relationship among different layers, while the latter reflects the relationship of factors in one layer. Moreover, the ambiguity in the decision-making process can be reduced by the uncertainty system. Therefore, the proposed method integrates grey theory and utilises the characteristics of DEMATEL to establish the AHP comparison matrix, particularly when the scores given by experts’ questionnaires are scattered. The method was applied to the risk assessment of urban inundation in Zhengzhou and verified by its flooding disaster sites that occurred during the 20 July storm in 2021 [1].•Developed approach merges grey theory, DEMATEL, and AHP methods;•Application of G-DEMATEL-AHP method in risk assessment of urban inundation;•The proposed method can increase the reliability of risk assessment results.

Detecting flood-type-specific flood-rich and flood-poor periods in peaks-over-threshold series with application to Bavaria (Germany)

Previous studies suggest that flood-rich and flood-poor periods are present in many flood peak discharge series around the globe. Understanding the occurrence of these periods and their driving mechanisms is important for reliably estimating future flood probabilities. We propose a method for detecting flood-rich and flood-poor periods in peak-over-threshold series based on scan-statistics and combine it with a flood typology in order to attribute the periods to their flood-generating mechanisms. The method is applied to 164 observed flood series in southern Germany from 1930 to 2018. The results reveal significant flood-rich periods of heavy-rainfall floods, especially in the Danube river basin in the most recent decades. These are consistent with trend analyses from the literature. Additionally, significant flood-poor periods of snowmelt-floods in the immediate past were detected, especially for low-elevation catchments in the alpine foreland and the uplands. The occurrence of flood-rich and flood-poor periods is interpreted in terms of increases in the frequency of heavy rainfall in the alpine foreland and decreases of both soil moisture and snow cover in the midlands.

Rainstorms drive export of aromatic and concurrent bio-labile organic matter to a large eutrophic lake and its major tributaries

Lakes are hotspots for global carbon cycling, yet few studies have explored how rainstorms alter the flux, composition, and bio-lability of dissolved organic matter (DOM) in inflowing rivers using high-frequency monitoring. We conducted extensive campaigns in the watershed of Lake Taihu and made daily observations for three years in its two largest inflowing tributaries, River Dapu and River Yincun. We found higher DOC, bio-labile DOC (BDOC), and specific UV absorbance (SUVA254) levels in the northwestern inflowing regions compared with the remaining lake regions. DOC and BDOC increased during rainstorms in River Dapu, and DOC declined due to local dilution and BDOC increased during rainstorms in River Yincun. We found that rainstorms resulted in increased DOM absorbance a350, SUVA254, and humification index (HIX) and enhanced percentages of humic-like fluorescent components, %polycyclic condensed aromatic and %polyphenolic compounds as revealed from ultrahigh-resolution mass spectrometry (FT-ICR MS), while spectral slope (S275-295) and the percentages of protein-like C1 and C3 declined during rainstorms compared with other seasons. This can be explained by a combined flushing of catchment soil organic matter and household effluents. The annual inflows of DOC and BDOC to Lake Taihu were 1.15 ± 0.18 × 104 t C yr−1 and 0.23 ± 0.06 × 104 t C yr−1 from River Dapu and 2.92 ± 0.42 × 103 t C yr−1 and 0.53 ± 0.07 × 103 t C yr−1 from River Yincun, respectively, and the fluxes of DOC and BDOC from both rivers increased during rainstorms. We found an elevated frequency of heavy rainfall and rainstorms in the lake watershed during the past six decades. We conclude that an elevated input of terrestrial organic-rich DOM with concurrent high aromaticity and high bio-lability from inflowing rivers is likely to occur in a future wetter climate.

Application and evaluation of SWAT-C model to predict TOC loading in the Hwangryong River Watershed

Objectives : This study aims to assess the applicability of the SWAT-C water quality model recently developed to predict in-stream Total Organic Carbon (TOC) in a watershed within South Korea.Methods : The SWAT-C model was tested in the Hwangryong River Watershed. SWAT-C is an advanced version of Soil and Water Assessment Tool (SWAT) to simulate carbon cycling at the watershed scale. The model was simulated for 11 years (2010-2020) consisting of 2-year warm-up (2010-2011), 6-year calibration (2012-2017), and 3-year validation (2018-2020) periods. SWAT-C was calibrated and validated against monthly streamflow and TOC loads. The model performance was evaluated using NSE (Nash-Sutcliffe efficiency), KGE (Kling-Gupta efficiency), and PBIAS (percent bias) Simulated Dissolve Organic Carbon (DOC) and Particulate Organic Carbon (POC) loads were also presented to see the major caron type loaded to the downstream.Results and Discussion : The calibration results showed that SWAT-C could depict streamflow and TOC loads with acceptance model performances (NSE > 0.5, KGE > 0.5 and PBIAS =< 25%). Especially, the seasonal variations of TOC loads were well simulated by SWAT-C. The TOC load was predicted to increase in the summer season with high precipitation and slightly lower in the other seasons. This seasonal pattern is likely caused by frequent heavy rainfall events in summer.Conclusion : This study demonstrated that SWAT-C model is applicable in South Korea with sufficient prediction accuracy. Thus, SWAT-C would serve as an efficient tool to monitor TOC loads in South Korea.

Comparisons of the Synoptic Characteristics of 14-Day Extreme Precipitation Events in Different Regions of Eastern China

How to predict and study persistent extreme precipitation events (PEPEs) with a prediction period of 1–2 weeks is an important scientific problem faced by the meteorological circles at home and abroad. Based on the accurate description of the flood range caused by 14-day PEPEs, the comprehensive analysis method was used to obtain the weather characteristics related to 14-day PEPEs (including abnormal trough/ridge, westerly jet, atmospheric river (AR) activity, teleconnections, etc.). First, we selected three regions in China, North China (NC), the Yangtze River valley (YRV), and South China (SC), analyzed their 14-day PEPEs in summer (June to August), and composited them into an average circulation (500 hPa geopotential height field) to compare the weather patterns related to PEPEs in these regions. Then, several variables are composited to understand the evolution of the atmospheric state before and during the occurrence of PEPEs. Finally, potential applications of several teleconnection types and composites in advance prediction are studied. The main findings include: the common weather signals during the occurrence of PEPEs are characterized by obvious and continuous a high-low-high saddle field circulation configuration (conducive to the formation of frequent heavy rainfall), active westerly jet (westerly jet is the controlling factor of precipitation), and enhanced water vapor transport (significantly increased atmospheric river activity). In this study, some key characteristics and development of PEPEs were identified, the formation mechanism of China’s 14-day PEPEs was revealed, the role of ARs in PEPEs was recognized, and the PEPEs precursor signal was extracted. Furthermore, PEPEs in different regions were also compared, which played an important role in understanding and predicting similar events.