Annual Peak Research Articles

Electricity market modeling considering a high penetration of flexible heating systems and electric vehicles

The electrification of the heating and transportation sectors is a major building block in Germany’s effort to reduce carbon dioxide emissions. The additional loads and flexibilities resulting from the anticipated large-scale integration of the heating and transportation sectors necessitate an adequate representation in electricity market modeling. First, the paper presents a comprehensive modeling approach of the heating sector in a pan-European electricity market simulation considering both small-scale building heat pumps and large-scale conversion units with thermal energy storages in district heating networks. The operation of small-scale building heat pumps is emulated using an electro-thermal 1R1C building model integrated into the economic dispatch formulation while the operation of units in district heating networks is restricted by additional constraints resulting from the combined heat and power output, local heat load coverage and possible heat power transfer between heating networks. The transportation sector is mapped using previously published models by the authors including both controlled and fast charging processes. Subsequently, the load shift potentials resulting from the market-integration of the heating and transportation sectors and their impact on the pan-European electricity market with focus on Germany based on the three target years 2030, 2040 and 2045 are examined. Furthermore, by applying a Monte Carlo simulation to map possible future primary energy source prices a major uncertainty dimension is addressed. Considering the current German electricity market design, the integration of the two sectors lead to a moderate increase in future annual electricity demands and a substantial increase in market-based peak load. The resulting annual peak load from power-to-heat devices account to 22 GW (2030), 53 GW (2040) and 102 GW (2045) and from electric vehicles to 12 GW (2030), 36 GW (2040) and 96 GW (2045) for the target years. Further results demonstrate the larger load-shift potentials of electric vehicles compared to building heat pumps by comparing the weighted annual average market price of the flexible loads. The primary fuel price uncertainty is examined based on the 0.25, 0.50 and 0.75 quantiles for the target years which result in annual average electricity market price spreads of over 2.16 (2030), 2.97 (2040) and 3.44 (2045) between the 0.25 and 0.75 quantile scenarios.

Seasonality of Deaths Due to Heart Diseases among Cancer Patients.

Background and Objectives: Cancer patients are at increased short- and long-term risk of cardiac toxicity and mortality. It is well-known that cardiac morbidity and mortality follows a seasonal pattern. Here we address the question of whether heart disease-related fatalities among cancer patients also follow a seasonal pattern. Materials and Methods: We performed a retrospective analysis of seasonality of deaths due to heart diseases (n = 503,243) in patients with newly diagnosed cancer reported during the period from 1975 to 2016 in the US's largest cancer registry-the Surveillance, Epidemiology, and End Results (SEER) database. Seasonality was assessed through a classical cosinor model assuming a single annual peak. Results: We identified a significant seasonal peak in the first half of November. A peak with identical features was for all subgroups of patients defined based on demographic characteristics. This was also the case when analysis was performed on subgroups defined by the type of malignancy. Only patients with acute leukemias, pancreatic cancer and nervous system malignancies did not have a seasonal pattern in heart disease-related fatalities. Conclusion: the rate of heart disease-related fatalities after cancer diagnosis follows a seasonal pattern similar to that observed for the general population, albeit with an earlier peak in November. This suggests that close monitoring of the cardiovascular system in cancer survivors must be particularly active from late autumn and during the entire winter period.

Analysis of flood frequency using plotting position methods and Gumbel’s method: Vaigai River basin, Southern India

<p>Estimation of annual peak flood flow has considerable financial influence, as this can pave numerous ways for water resources planning, design of hydraulic structures, and sustainable management of these valuable resources at an optimum benefit. Six standard plotting position methods coupled with Linear Log-regression Model (LLM) are employed for the Return Period (RP) of 15, 20, 25, 30, 60, and 1000 years to forecast peak flood flow magnitudes and for this daily annual peak flood flow data for the periods of 24 years were used to illustrate the proposed methods. Another method, Gumbel's Analytical Approach (GAA), is also used to forecast the peak flood flow magnitude for the same RP, and it was taken as the benchmark to compare all the six methods of plotting position. The degree of accuracy of the plotting position is based on the coefficient of determination R2. The R2 values for Adamowski, Hazen, Beard, Chegodajev, Tukey, and Benard, are 0.9073, 0.9284, 0.9119, 0.9111, 0.9135, and 0.9111, respectively. Out of the six-plotting position methods, Hazen method predicted a very closer value in comparison with GAA. It is advantageous to have the additional method to forecast peak flood flow for longer RP. The achieved result assuredly facilitates effective planning, regulation, and maintenance of huge reservoirs across the frequent occurrence of floods in river basin areas, considering safety and particularly downstream inhabited areas to save loss of human life, animals, damages to properties, and an impair of cultivated crops.</p>

Application of thermal energy storage with electrified heating and cooling in a cold climate

Ground source heat pumps (GSHPs) have been shown to be an effective means of decarbonizing building heating and cooling, but the operation of these systems at scale presents challenges to sites and the grid due to increases in peak demand. In this study, we investigate how the use of Thermal Energy Storage (TES), in the form of stratified water storage, could reduce the peak daily demand associated with GSHP systems and thus improve their cost effectiveness. This system was compared to a Combined Heat and Power (CHP) plant, to investigate the potential cost and emissions impacts of electrification on large energy users transitioning from high efficiency fossil fuel equipment. This study builds on previous research by using a significant campus area, and investigating the various impacts of an electrified system versus a state of the art fossil fuel system. An established method of TRNSYS modeling is used for the heat pumps and borehole heat exchangers (BHEs), along with the TES. The GSHP system with TES is modeled to follow industry standards and sized to provide an optimal balance of capital and operating costs. Costs were investigated for a unique large energy user rate structure, as well as for a more common generalized rate structure. The results show that the addition of TES to the GSHP system could reduce operating costs by 4.5%, but still incurs a 5.64% cost increase from the baseline CHP system. It is also shown, however, that a tactical integration of heat pumps into the CHP system is the most cost effective solution, only increasing the operating costs by 4.71%. Likewise, the impacts of different rate structures are highlighted, with the TES only resulting in 0.75% cost savings under the generalized utility rate. Furthermore, it is shown that thermal storage has great potential for demand reduction, with the addition of storage incurring a decrease of 7–22% in annual peak demand kW, dependent on the rate structure.

Impact of hydropower reservoirs on floods: evidence from large river basins in Austria

ABSTRACT In this study the impact of hydropower reservoirs on floods is systematically assessed for eight heavily modified river basins in Austria. Since little discharge data from prior to the construction is available, unaffected annual peak discharges downstream of the reservoirs were estimated by transposing the peak runoff of an unaffected catchment, considering the spatial proximity, the catchment area and the temporarily corresponding precipitation conditions. Comparing the observed and estimated discharge, results show significant reductions not only at gauges directly affected by the reservoir but also farther downstream at receiving rivers. The propagation of the flood peak reduction downstream is also related to catchment area and reservoir characteristics. Extreme events with return periods greater than 30 years show a noteworthy flood peak reduction of over 33% on average. These findings show that reservoirs primarily constructed for hydropower generation also contribute significantly to flood control and flood mitigation.

Floodplain Mapping Using Hydraulic Simulation and Geographic Information System

Objectives- A flood is a strangely high stage in a river generally, the level at which the river overflows its banks inundates the adjacent area. Flood occurs due to intense rainfall, dense population, industrialization, illegal settlement along riverbanks, bank erosion, high tide, and urbanization, and it causes harmful damage to human beings and properties. It can be taken care of by adopting flood risk measures. One of the measures is the development of flood inundation maps. Hence in the current study, flood inundation maps are developed with the integration of GIS and HEC-RAS along the Bhīma River reach in Maharashtra, India. Methods: In this study, using the series of annual peak discharges, flood flows were estimated for different recurrence intervals. Inundated areas marked along the Bhīma River represent peak flows of 25 years and 100 years return periods using HEC-RAS, ArcGIS handling of spatial data, and HEC-GEORAS for the interfacing between HEC-RAS and ArcGIS. Simulation for 2, 5, 10, 25, 50, and 100-year return periods is done, and inundation maps have been developed for the 100-years reoccurrence interval. Findings:The analysis on the left and right banks has been done using water surface elevations generated from the HEC-RAS model. The significant findings revealed that the left bank representing the east side of the river is more vulnerable to water spills than the right bank representing the west side of the river. The flooded areas along the Bhīma River are 32.4 km2 and 43.82 km2 for 25-year and 100-year reoccurrence intervals, respectively. Generally, this study revealed that urban and agricultural areas downstream of river reach are more susceptible to flooding. Novelty: The developed inundation map will help the local authority in effective decision-making and disaster management in flooding situations, especially on the left bank side of Bhīma River. Obtained water surface elevations and flood inundation depths can help to decide the necessity of structural measures that can reduce the deteriorating effects of flooding Keywords: Inundation map; flood frequency; DEM; Sensitivity analysis; Return Period; HEC-RAS

Epidemiological Characteristics of Varicella under Different Immunisation Strategies in Suzhou Prefecture, Jiangsu Province.

Background: The varicella vaccine is excluded from the Chinese national immunisation programme but is included in the local expanded programme on immunisation (EPI) in the Suzhou Prefecture. This study investigated the epidemiological characteristics of the varicella cases during the implementation of different immunisation strategies in the Suzhou Prefecture, Jiangsu Province. Methods: In this study, we used descriptive statistics. Information on reported instances from 2012 to 2021 was first retrieved. Data on varicella cases were collected from the China Information System for Disease Control and Prevention (CISDCP). Similarly, information on vaccinated children was obtained from the Jiangsu Province Vaccination Integrated Service Management Information System (JPVISMIS). The census data in this study was procured from the Suzhou Bureau of Statistics. Results: From 2012 to 2021, a total of 118,031 cases of varicella were reported in Suzhou, and the average annual reported incidence was 91.35 per 100,000. The average yearly incidence after implementing the two-dose varicella vaccination decreased by 41.57% compared with the implementation of one dose. This study demonstrates two annual incidence peaks, a small peak between April and July and a prominent peak between October and January. It is also possible that this seasonal distribution is related to the geography of Suzhou. The average annual reported incidence between districts with a statistically significant difference (χ2 = 98.077, p < 0.05). The one-dose varicella vaccination coverage gradually increased from 55.34% in 2012 to 89.06% in 2021 and the two-dose varicella vaccination coverage gradually increased from 0.27% in 2012 to 82.17% in 2021. Conclusions: Administering the varicella vaccine in the local EPI has significantly decreased the incidence rate and the total number of cases. A two-dose vaccination schedule is still the best vaccination strategy for varicella vaccine effectiveness.

Hybrid LSTM–BPNN-to-BPNN Model Considering Multi-Source Information for Forecasting Medium- and Long-Term Electricity Peak Load

Accurate medium- and long-term electricity peak load forecasting is critical for power system operation, planning, and electricity trading. However, peak load forecasting is challenging because of the complex and nonlinear relationship between peak load and related factors. Here, we propose a hybrid LSTM–BPNN-to-BPNN model combining a long short-term memory network (LSTM) and back propagation neural network (BPNN) to separately extract the features of the historical data and future information. Their outputs are then concatenated to a vector and inputted into the next BPNN model to obtain the final prediction. We further analyze the peak load characteristics for reducing prediction error. To overcome the problem of insufficient annual data for training the model, all the input variables distributed over various time scales are converted into a monthly time scale. The proposed model is then trained to predict the monthly peak load after one year and the maximum value of the monthly peak load is selected as the predicted annual peak load. The comparison results indicate that the proposed method achieves a predictive accuracy superior to that of benchmark models based on a real-world dataset.

Respiratory Virus Surveillance Among Children with Acute Respiratory Illnesses - New Vaccine Surveillance Network, United States, 2016-2021.

The New Vaccine Surveillance Network (NVSN) is a prospective, active, population-based surveillance platform that enrolls children with acute respiratory illnesses (ARIs) at seven pediatric medical centers. ARIs are caused by respiratory viruses including influenza virus, respiratory syncytial virus (RSV), human metapneumovirus (HMPV), human parainfluenza viruses (HPIVs), and most recently SARS-CoV-2 (the virus that causes COVID-19), which result in morbidity among infants and young children (1-6). NVSN estimates the incidence of pathogen-specific pediatric ARIs and collects clinical data (e.g., underlying medical conditions and vaccination status) to assess risk factors for severe disease and calculate influenza and COVID-19 vaccine effectiveness. Current NVSN inpatient (i.e., hospital) surveillance began in 2015, expanded to emergency departments (EDs) in 2016, and to outpatient clinics in 2018. This report describes demographic characteristics of enrolled children who received care in these settings, and yearly circulation of influenza, RSV, HMPV, HPIV1-3, adenovirus, human rhinovirus and enterovirus (RV/EV),* and SARS-CoV-2 during December 2016-August 2021. Among 90,085 eligible infants, children, and adolescents (children) aged <18 years† with ARI, 51,441 (57%) were enrolled, nearly 75% of whom were aged <5 years; 43% were hospitalized. Infants aged <1 year accounted for the largest proportion (38%) of those hospitalized. The most common pathogens detected were RV/EV and RSV. Before the emergence of SARS-CoV-2, detected respiratory viruses followed previously described seasonal trends, with annual peaks of influenza and RSV in late fall and winter (7,8). After the emergence of SARS-CoV-2 and implementation of associated pandemic nonpharmaceutical interventions and community mitigation measures, many respiratory viruses circulated at lower-than-expected levels during April 2020-May 2021. Beginning in summer 2021, NVSN detected higher than anticipated enrollment of hospitalized children as well as atypical interseasonal circulation of RSV. Further analyses of NVSN data and continued surveillance are vital in highlighting risk factors for severe disease and health disparities, measuring the effectiveness of vaccines and monoclonal antibody-based prophylactics, and guiding policies to protect young children from pathogens such as SARS-CoV-2, influenza, and RSV.

Variation characteristics of high flows and their responses to climate change in permafrost regions on the Qinghai-Tibet Plateau, China

River flow characteristics in permafrost regions on the Qinghai-Tibet Plateau (QTP) have changed rapidly with the intensification of global warming. However, the specific change characteristics and their responses to changes in influencing factors remain unclear. Based on the multi-year flow data of several typical basins in the QTP permafrost regions, combined with the flow duration curve and percentile flow, this study analyzed the variability of annual peak discharge, Q5, Q10, and Q30 (5%, 10%, and 30% percentile flows in the flow duration curve, respectively) and their response relationships with different climate change factors. In addition, the corresponding relationships between different percentile high flows and annual hydrographs were analyzed. The results indicate that, in the context of global warming, changes in the high flows in permafrost regions are bidirectional, either rising or falling, or both. Moreover, the responses of different percentile high flows to climate change are seasonally distinct. Spring high flows are more sensitive to changes in air temperature and normalized difference vegetation index (NDVI), and summer and autumn high flows are more susceptible to corresponding changes in seasonal average precipitation and rainfall intensity. In addition, different percentile high flows can be used to predetermine the level of annual flood events. Among them, the largest, the larger, and all other general flood events during the annual flood season, can be defined by Q5, Q10, and Q30, respectively. The analysis of different high flows combined with the flow duration curve is essential for the further clarification of the hydrological processes in permafrost regions. The prudent utilization of water resources benefits the sustainable development of human society.

Spatiotemporal Analysis of Online Purchase of HIV Self-testing Kits in China, 2015-2017: Longitudinal Observational Study.

BackgroundSince the introduction of HIV self-testing by UNAIDS in 2014, the practice has been extensively implemented around the world. HIV self-testing (HIVST) was developed in China around 2015, and the online purchase of HIVST kits through e-commerce platforms has since become the most important delivery method for self-testing, with advantages such as user-friendliness, speed, and better privacy protection.ObjectiveUnderstanding the spatiotemporal characteristics of online HIVST kit purchasing behavior and identifying potential impacting factors will help promote the HIV self-testing strategy.MethodsThe online retail data of HIVST kits from the 2 largest e-commerce platforms in China from 2015 to 2017 were collected for this study. The Bayesian spatiotemporal hierarchical model was used to investigate the spatiotemporal characteristics of online purchased HIVST kits. Ordinary least squares regression was used to identify potential factors associated with online purchase, including GDP per capita, population density, road density, HIV screening laboratory density, and newly diagnosed HIV/AIDS cases per 100,000 persons. The q statistics calculated by Geodetector were used to determine the interactive effect of every 2 factors on the online purchase.ResultsThe online purchase of HIVST kits increased rapidly in China from 2015 to 2017, with annual peak sales in May and December. Five economically superior regions in China, Pearl River Delta, Yangtze River Delta, Chengdu and surrounding areas, Beijing and Tianjin areas, and Shandong Peninsula, showed a comparatively higher spatial preference for online purchased HIVST kits. The GDP per capita (P<.001) and the rate of newly diagnosed HIV/AIDS cases per 100,000 persons (P<.001) were identified as 2 factors positively associated with online purchase. Among the factors we investigated in this study, 2 factors associated with online purchase, GDP per capita and the rate of newly diagnosed HIV/AIDS cases per 100,000 persons, also displayed the strongest interactive effect, with a q value of 0.66.ConclusionsIndividuals in better-off areas are more inclined to purchase HIVST kits online. In addition to economic status, the severity of the HIV epidemic is also a factor influencing the online purchase of HIVST kits.

Seasonal Landslide Activity Lags Annual Precipitation Pattern in the Pacific Northwest

AbstractSeasonal variations in landslide activity remain understudied compared to recent advances in landslide early warning at hourly to daily timescales. Here, we learn the seasonal pattern of monthly landslide activity in the Pacific Northwest from five heterogeneous landslide inventories with differing spatial and temporal coverage and reporting protocols combined in a Bayesian multi‐level model. We find that landslide activity is distinctly seasonal, with credible increases in landslide intensity, inter‐annual variability, and probability marking the onset of the landslide season in November. Peaks in landslide probability in January and intensity in February lag the annual peak in mean monthly precipitation and landslide activity is more variable in winter than in summer, when landslides are rare. For a given monthly rainfall, landslide intensity at the season peak in February is up to 10 times higher than at the onset in November, underlining the importance of antecedent seasonal hillslope conditions.

Science and the evolving management of environmental hazards at Yosemite National Park

US national park managers must address a complex portfolio of foreseen and unforeseen challenges that arise in part from a dual mandate to preserve nature and facilitate visitation. To deal with resource management challenges, managers can identify potential pathways toward a solution through the use of science to inform policy and guide actions. The way science has been applied has evolved over the course of the National Park Service’s history, in large part due to the prevailing societal context and ways of thinking about the environment, and relatedly as a necessity to mitigate the impact from development and anthropogenic climate change. Landscape-scale environmental hazards are a fitting proxy to recount the changing use of science and policy because biophysical processes become most hazardous at the interface of infrastructure and the natural environment, where people are most exposed. This paper synthesizes modern administrative and environmental histories of hazards in Yosemite National Park from the late19th century to the early 21st century through archival records and long-term data, including significant events and trends in wildland fire, tree mortality (falls), extreme floods, and rockfalls and slides. Findings confirm increased severity and extent of wildland fire, correlations between periods of drought and high rates of tree mortality, warmer precipitation events lead to earlier annual peak streamflow, and connections between periods of prolonged cold with rockfalls, and prolonged precipitation with slides. These hazards exist as an interconnected system in the context of high seasonal visitation, and while there are averages of seasonal conditions over time, there are no “normal” years.

Macrophyte habitat architecture and benthic-pelagic coupling: Photic habitat demand to build up large P storage capacity and bio-surface by underwater vegetation

Macrophytes play an important role in shallow lakes if large standing crop can be achieved. Here we stress the role of submerged macrophytes for benthic-pelagic coupling in the shallow oxbow lake Alte Donau (Austria) during restoration triggered by sufficient light availability (12% surface ambient light, photic&amp;gt;12% depth, zoptimum) in both, the benthic and the pelagic habitat. Focusing on zoptimum, rather than on minimum light requirement (euphotic depth), seemed to be more meaningful to follow the macrophyte development. After phosphate precipitation treatment, the photic&amp;gt;12% pelagic habitat accounted for more than half of the total water volume in summer, while the achievement of the same photic&amp;gt;12% conditions for half of the total sediment surface area was delayed by 8 years. A delay of light exposure on the lake bottom area compared to the lake water volume is given by the basin morphometry, but the time span that is required for passing this delay depends on the efficiency of restoration measures. The 8-year delay for Alte Donau means that lake restoration focusing on macrophyte re-establishment was difficult to stimulate due to insufficient light exposure at the lake bottom. A further increase of photic&amp;gt;12% conditions to more than 3/4 size of both pelagic and benthic habitat, however, eventually stimulated sustained macrophyte growth. With the onset of this large macrophyte biomass yield, the phosphorus storage pool of submerged macrophytes exceeded the annual peak concentration of total phosphorus of the whole lake water by about one order of magnitude for the first time. Further, the submerged macrophyte bio-surface exceeded the size of lake bottom surface, also by about one order of magnitude. Our results support that macrophytes can act as a significant sink of phosphorus by retaining this nutrient at least during the growing season. We further see the immensely large macrophyte bio-surface as a vast spatial dimension for an additional habitat for freshwater biota. Therefore, we conclude that mature submerged macrophyte formations need to be considered not only as biomass yield, but create a unique macrophyte habitat architecture as a third main component in the network between benthic (lake bottom) and pelagic (lake water) habitat.

Interactions between multiple environmental factors and associations with generalized anxiety disorder in Nurses’ Health Study II

Background and Aim: Built and natural environments are linked to lower anxiety. Results are mixed due to heterogeneous study populations and definitions of anxiety. We longitudinally examined associations between generalized anxiety disorder (GAD) symptoms and exposure to residential greenness, walkability, and neighborhood socioeconomic status (nSES) and their interactions in the Nurses’ Health Study II. Methods: 79,838 participants completed the 7-item GAD Assessment (GAD-7) in 2013 and/or 2017. GAD-7 scores for both time points were dichotomized at a clinically-relevant cutoff (GAD-7 &amp;#x2265; 5), indicating at least mild anxiety symptoms. Annual average and peak (July) greenness were assigned to residential addresses using Landsat-based Normalized Difference Vegetation Index (NDVI) at 270m and 1230m buffers. Walkability was calculated from summed z-scores of 2010 Census population density, Tiger/Line shapefile road intersection density, and Infogroup business density. nSES z-scores were linked using 2010 Census data. We employed generalized estimating equations (GEE) for individual and joint exposure models to estimate odds ratios (OR) and 95% confidence intervals (95% CI) adjusted for sociodemographic and lifestyle risk factors for anxiety. Results: Interquartile range increases in peak 270m NDVI (OR: 0.98, 95% CI: 0.96, 1.00), peak 1230m NDVI (OR: 0.97, 95% CI: 0.95, 1.00), and nSES z-score (OR: 0.97 95% CI: 0.95, 0.99) were protective. Higher walkability (OR: 1.02, 95% CI: 1.01, 1.03) was associated with elevated odds of anxiety symptoms. Interaction models showed substantial heterogeneity. For example, peak 270m NDVI was more protective in lower nSES areas (lowest quintile OR: 0.94, 95% CI: 0.90, 0.98, highest quintile OR: 1.01, 95% CI: 0.96, 1.06). The adverse association observed with walkability was stronger in higher NDVI areas. Conclusion: Higher residential NDVI and nSES and lower walkability were associated with decreased odds of anxiety symptoms. Interactions between these contextual factors identified subpopulations that could benefit from improved residential built and natural environments.

Explaining the Flood Behavior for the Bridge Collapse Sites

Given the increasing intensity and frequency of flood events, and the casualties and cost associated with bridge collapse events, explaining the flood behavior for the collapse sites would be of great necessity. In this study, annual peak flows of two hundred and five watersheds, associated with two hundred and ninety-seven collapse sites, are analyzed. Generalized Extreme Value distribution together with other statistical analyses are used to derive and analyze the shape parameters of the distributions which represent the extremeness of flood events. Random forest mechanism is employed in order to identify the predictor variables (and the associated importance levels) for the shape parameters. Peak flows are also classified in order to find the extremes and the associated return periods. The results indicate that most of the bridge collapse sites across different physiographic regions, i.e., Appalachian Highland, Central Lowland, Coastal Plain, and Interior Highlands, exhibit common characteristics such as (a) variation of important predictor variables, (b) human interference, (c) extremeness of flood events similar to the regions with hydrologic heterogeneity, and (d) frequent occurrence of extreme flows. These results indicate a commonality in flood behavior, as stems from specific settings, for the collapse sites studied. The findings instigate the revisiting of the bridge design practices and guidelines and provide some basis to assess the risk of future collapse.

Climate impact emergence and flood peak synchronization projections in the Ganges, Brahmaputra and Meghna basins under CMIP5 and CMIP6 scenarios

The densely populated delta of the three river systems of the Ganges, Brahmaputra and Meghna is highly prone to floods. Potential climate change-related increases in flood intensity are therefore of major societal concern as more than 40 million people live in flood-prone areas in downstream Bangladesh. Here we report on new flood projections using a hydrological model forced by bias-adjusted ensembles of the latest-generation global climate models of CMIP6 (SSP5-8.5/SSP1-2.6) in comparison to CMIP5 (RCP8.5/RCP2.6). Results suggest increases in peak flow magnitude of 36% (16%) on average under SSP5-8.5 (SSP1-2.6), compared to 60% (17%) under RCP8.5 (RCP2.6) by 2070–2099 relative to 1971–2000. Under RCP8.5/SSP5-8.5 (2070–2099), the largest increase in flood risk is projected for the Ganges watershed, where higher flood peaks become the ‘new norm’ as early as mid-2030 implying a relatively short time window for adaptation. In the Brahmaputra and Meghna rivers, the climate impact signal on peak flow emerges after 2070 (CMIP5 and CMIP6 projections). Flood peak synchronization, when annual peak flow occurs simultaneously at (at least) two rivers leading to large flooding events within Bangladesh, show a consistent increase under both projections. While the variability across the ensemble remains high, the increases in flood magnitude are robust in the study basins. Our findings emphasize the need of stringent climate mitigation policies to reduce the climate change impact on peak flows (as presented using SSP1-2.6/RCP2.6) and to subsequently minimize adverse socioeconomic impacts and adaptation costs. Considering Bangladesh’s high overall vulnerability to climate change and its downstream location, synergies between climate change adaptation and mitigation and transboundary cooperation will need to be strengthened to improve overall climate resilience and achieve sustainable development.

In Situ Flood Frequency Analysis Used for Water Resource Management in Kelantan River Basin

One of the most prevalent and traditional uses of statistics in hydrology is flood frequency analysis. The flood can occur practically everywhere and is considered the leading cause of natural disaster death worldwide. This study aims to apply the flood frequency analysis of the Kelantan streamflow site to identify the optimal distribution that best fits the flood frequency data from the goodness-of-fit test (GOF). Five distributions were applied in this study; namely lognormal (LG), generalized extreme value (GEV), generalized Pareto (GP), log-Pearson three (L3) and generalized logistic (GL) distribution. to obtain the parameter estimates. The distribution performance evaluation is then performed utilizing the GOF and efficiency evaluations. The results indicate that the generalized GP distribution is the best possible function for determining the annual peak flow at the Kelantan streamflow site.

Can Distributed Intermittent Renewable Generation Reduce Future Grid Investments? Evidence from France

Abstract This paper estimates the relationship between investments in five distributed generation technologies and hourly net withdrawals from over 2,000 electricity distribution networks in France between 2005 and 2018. We find that investments in distributed wind and solar generation have little or no impact on the annual peak of hourly net withdrawals from the distribution grid, while investments in hydroelectric and thermal distributed generation significantly reduce it. An optimistic analysis of the impact of investments in battery storage suggests that high levels are required for distributed wind and solar to deliver similar reductions in the annual peak of hourly net withdrawals. Our results imply that public policies favoring distributed wind and solar generation over utility-scale generation cannot be rationalized by savings in future grid investments.

Functional fluvial landforms of the Pantanal: Hydrologic trends and responses to climate changes

Large-scale fluvial landforms emerge from iterative processes that sculpt Earth's surface. Tectonics, climate variability and erosion are major recurrent processes reshaping fluvial landforms ending up in self-affine patterns. In the case of the Pantanal, the largest wetland in South America, its depositional tract can be subdivided as fluvial megafans, interfans and the main trunk system. Here we provide an outlook of their origins by means of self-affine landforms and on the feedback of climate changes over landform functionalities. Climate variability modulates the magnitude of interannual fluvial discharge and sediment load from highlands to plains, affects groundwater recharge, as well as the subsidence and generation of accommodation in the depositional tract through river avulsion. Scenarios are envisaged by analyzing long-term summer rainfall intensity and the number of dry days in autumn/winter over the Upper Paraguay River Basin, and annual flood peaks measured at fluvial gauge stations in the Paraguay River at Ladário (Brazil) and Asunción (Paraguay). The frequency distributions of the annual flood peaks are found unimodal for Asunción and bimodal for Ladário, which suggests an unknown water supply at Asunción, likely from Pilcomayo River and Pantanal's groundwater. The latter might play a delayed role on Pantanal's hydrologic functioning at 20–40 years timescales. Besides the Paraguay River flood peaks, summer rainfall intensity and the number of dry days in autumn/winter are quasi-periodic at interannual and decadal scales. Cross-correlations analyses indicate a long-range memory between river floods and rainfall intensity, and 15–20 years lag between river floods and the number of dry days in drought seasons. Trends analysis suggests that summer rainfall intensity and the number of dry days in autumn/winter have been consistently increasing by about 0.6 mm/day/decade and 1 day/decade, respectively. Therefore, magnifications of fluvial discharge and sediment load at wet seasons and water deficits at drought seasons are anticipated. Such a scenario indicates extreme dry cycles over all self-affine functional landforms, particularly on abandoned lobes relying exclusively on rainwater, whereas extremes of rainfall intensity at rivers headwaters may amplify the risks of large-scale avulsions at active lobes of the fluvial megafans. In contrast, active lobes of megafans, interfans and the main trunk river system emerge as hotpots for wildlife refuge and ecosystem services.