Higher Peak Discharge Research Articles

Nitrogen‐Doped Graphene Oxide Nanoribbon Supported Cobalt Oxide Nanoparticles as High‐Performance Bifunctional Catalysts for Zinc–Air Battery

Developing high‐performance, high‐stability, and low‐cost nonprecious metal catalysts to enhance the performance of zinc–air batteries (ZABs) holds significant importance. A bifunctional catalyst consisting of cobalt oxide (CoO) nanocrystals on nitrogen‐doped reduced graphene oxide nanoribbons (N‐rGONR) as a novel substrate is successfully synthesized in this work. This synthesized bifunctional catalyst exhibits mesoporous structure, and remarkable synergistic effects between CoO nanocrystals and N‐rGONR, demonstrating excellent activity and durability in both oxygen reduction reactions and oxygen evolution reactions. Notably, the resulting aqueous electrolyte ZABs show a high discharge peak power density of 196 mW cm−2, a high specific capacity of 615.9 mAh g−1, and long‐time stability for 648 h. Furthermore, the assembly of 1D and 2D flexible solid‐state ZABs fabricated using this bifunctional catalyst exhibits stable electrochemical performance, even under severe deformation. These results underscore the considerable promise of implementing the CoO@N‐rGONR catalyst structure in next‐generation advanced energy storage and conversion devices.

Response times as explanatory variable for export of dissolved organic carbon (DOC) from small forested catchments

Rising trends in the concentrations of dissolved organic carbon (DOC) are observed in many inland waters, including the headwater catchment of the Große Ohe river in the Bavarian Forest National Park (Germany). During flood events, DOC is mobilized via different hydrological pathways, affecting the hydrochemistry of aquatic ecosystems and the viability of drinking water supply. In our field experiments we observed different phases of DOC mobilization during six intensively studied rainfall-runoff events with contrasting antecedent wetness conditions. We propose response time diagrams to link the different phases of DOC mobilization to different response times along a hillslope-riparian-zone-transect. Depending on the antecedent wetness conditions, the hillslope and riparian zone participated differently to phases of the runoff event and shaped the flow hydrograph and DOC export at the catchment outlet. The hillslope always responded with little time delay to precipitation events regardless of the antecedent wetness condition. In contrast, response times in the riparian zone varied. For wet antecedent conditions we observed little delay between the hillslope- and riparian zone peak response, which caused high peak discharge, fast DOC mobilization and high DOC export from the catchment. In contrast, for dry antecedent conditions, the riparian zone response was significantly lower and much delayed. This led not only to attenuated peak discharge but also to larger time lags between the flow hydrograph- and the DOC concentration peak. The combination of low runoff rates and delayed DOC concentration peaks resulted into lower DOC export from the catchment. Thus, the antecedent wetness condition and response times of the hillslope and riparian zone are important indicators for DOC export in the catchment.

Economic Loss due to the Failure of a Cascade Dam: A Study Case in the Saguling-Cirata-Jatiluhur Dam

A dam break event can cause heavy loss in the affected area due to the lack of a mitigation system. Therefore, modeling the possibility of a dam break occurrence requires a risk analysis. The Saguling Dam, Cirata Dam, and Jatiluhur Dam make a cascade dam and is one of the country's most valuable assets. This study simulates a flood induced by the failure of this cascade dam. The dam break is simulated using HEC-HMS 4.6 with several dam-break scenarios due to overtopping and piping. The scenario with the highest peak discharge is then used to simulate the overland flow using HEC-RAS 5.0.7, representing the most extreme condition when the dam break occurs. The generated flood induced by the dam break hit seven regencies with a total affected area of 1,596.59 km2. Moreover, an economic analysis is conducted. The result states that the most affected regency by economic losses is Karawang Regency, and the least affected is Subang Regency. The financial analysis, conducted using the ECLAC method, shows that the extent of inundation influences economic losses due to flooding, the distribution of depth, and the land cover of the affected area. This study hopes to assist in developing a mitigation plan for future possible dam breaks and provide a recommendation for decision-makers for developing land use areas.

A new method for detailed discharge and volume measurements of debris flows based on high-frequency 3D LiDAR point clouds; Illgraben, Switzerland

Debris flows are one of the most dangerous landslide types in mountainous regions. Their destructiveness is strongly controlled by their high peak discharge, which can be orders of magnitude larger than for floods. In order to reduce the associated hazards, detailed field measurements of natural debris flows are required to better constrain discharge and volume of these events. In this study, we used a high-frequency 3D LiDAR (light detection and ranging) scanner in combination with video cameras to measure key properties of a debris flow that occurred in the Illgraben catchment (Switzerland). Based on the LiDAR and video data, we directly measured i) front velocity ii) surge velocity iii) surface velocity and iv) cross-sectional area at sub-second intervals. We then estimated discharge and volume using these direct measurements and considering different channel bed geometry scenarios. We compared our results to estimates based on conventional methods and found that these more established methods substantially underestimate the (peak) discharge and volume for this event. Our results will be assessed in the future by analyzing more events, but our LiDAR-based method has the potential to provide much more detailed information on hazard-related debris-flow parameters, which will have important implications for understanding debris-flow processes and ultimately reducing their risk.

Spatial and temporal variability of saturated areas during rainfall-runoff events

Abstract Spatially distributed hydrological model Mike SHE was used as a diagnostic tool to provide information on possible overland flow source areas in the mountain catchment of Jalovecký Creek (area 22.2 km2, elevation range 820–2178 m a.s.l.) during different rainfall-runoff events. Selected events represented a sequence of several smaller, consecutive events, a flash flood event and two large events caused by frontal precipitation. Simulation of hourly runoff was better for runoff events caused by heavy rainfalls of longer duration than for the flash flood or consecutive smaller runoff events. Higher soil moisture was simulated near the streamflow network and larger possibly saturated areas were located mainly in the upper parts of mountain valleys. The most pronounced increase in the areal extent of possibly saturated areas (from 6.5% to 68.6% of the catchment area) was simulated for the event with high peak discharge divided by a short rainfall interruption. Rainfall depth exceeding 100 mm caused a large increase in the potentially saturated areas that covered subsequently half of the catchment area or more. A maximum integral connectivity scale representing the average distance over which individual pixels were connected varied for the selected events between 45 and 6327 m.

Floods and droughts: a multivariate perspective

Abstract. Multivariate or compound hydrological-extreme events such as successive floods, large-scale droughts, or consecutive drought-to-flood events challenge water management and can be particularly impactful. Still, the multivariate nature of floods and droughts is often ignored by studying individual characteristics only, which can lead to the under- or overestimation of risk. Studying multivariate extremes is challenging because of variable dependencies and because they are even less abundant in observational records than univariate extremes. In this review, I discuss different types of multivariate hydrological extremes and their dependencies, including regional extremes affecting multiple locations, such as spatially connected flood events; consecutive extremes occurring in close temporal succession, such as successive droughts; extremes characterized by multiple characteristics, such as floods with jointly high peak discharge and flood volume; and transitions between different types of extremes, such as drought-to-flood transitions. I present different strategies to describe and model multivariate extremes and to assess their hazard potential, including descriptors of multivariate extremes, multivariate distributions and return periods, and stochastic and large-ensemble simulation approaches. The strategies discussed enable a multivariate perspective on hydrological extremes, which allows us to derive risk estimates for extreme events described by more than one variable.

Observation‐Constrained Projection of Flood Risks and Socioeconomic Exposure in China

AbstractAs the planet warms, the atmosphere's water vapor holding capacity rises, leading to more intense precipitation extremes. River floods with high peak discharge or long duration can increase the likelihood of infrastructure failure and enhance ecosystem vulnerability. However, changes in the peak and duration of floods and corresponding socioeconomic exposure under climate change are still poorly understood. This study employs a bivariate framework to quantify changes in flood risks and their socioeconomic impacts in China between the past (1985–2014) and future (2071–2100) in 204 catchments. Future daily river streamflow is projected by using a cascade modeling chain based on the outputs of five bias‐corrected global climate models (GCMs) under three shared socioeconomic CMIP6 pathways (SSP1‐26, SSP3‐70, and SSP5‐85), a machine learning model and four hydrological models. We also utilize the copula function to build the joint distribution of flood peak and duration, and calculate the joint return periods of the bivariate flood hazard. Finally, the exposure of population and regional gross domestic product to floods are investigated at the national scale. Our results indicate that flood peak and duration are likely to increase in the majority of catchments by 25%–100% by the late 21st century depending on the shared socioeconomic pathway. China is projected to experience a significant increase in bivariate flood risks even under the lowest emission pathway, with 24.0 million dollars/km2 and 608 people/km2 exposed under a moderate emissions scenario (SSP3‐70). These findings have direct implications for hazard mitigation and climate adaptation policies in China.

Ag Anchored Atomically Around Nanopores of Porous Co(OH)2 for Efficient Bifunctional Oxygen Catalysis

AbstractVarious clean energy storage and conversion systems highly depend on rational design of efficient electrocatalysts for oxygen reactions. Increasing both gas molecular diffusion and intrinsic activity is critical to boosting its efficiency for bifunctional oxygen electrocatalysis. However, controllable synthesis of catalysts that combines gas molecular diffusion and intrinsic activity remains a fundamental challenge. Herein, a two‐step synthetic strategy is adopted to fabricate a composite oxygen reduction reaction (ORR)/oxygen evolution reaction (OER) bifunctional catalyst (P‐Ag‐Co(OH)2), of which, atomic Ag is anchored in reactive oxygen atoms around nanopores of Co(OH)2 nanosheets. Abundant nanopores provide enough gas molecular diffusion channels, and the special Ag‐O‐Co‐OH catalytic groups around nanopores display high intrinsic catalytic activity, which jointly result in an excellent ORR/OER performance. In alkaline electrolyte, P‐Ag‐Co(OH)2 displays a high half‐wave potential (0.902 V versus RHE) for ORR, and a low overpotential (235 mV at 10 mA cm−2) for OER, which is superior to non‐noble catalysts in previous studies and Pt/C (Ir/C) catalyst. At the same time, the single‐cell zinc‐air battery is prepared with an extremely high discharge peak power density of 435 mW cm−2 and excellent discharge–charge cycle stability.

High Entropy Oxide (CrMnFeNiMg)3 O4 with Large Compositional Space Shows Long-Term Stability as Cathode in Lithium-Sulfur Batteries.

The repeated formation and irreversible diffusion of liquid-state lithium polysulfides (LiPSs) are the primary challenges in the development of high-energy-density lithium-sulfur battery (LSB). An effective strategy to alleviate the resulting polysulfide loss is critical for the stability of LSBs. In this regard, high entropy oxides (HEOs) appear as a promising additive for the adsorption and conversion of LiPSs owing to the diverse active sites, offering unparalleled synergistic effects. Herein, we have developed a (CrMnFeNiMg)3 O4 HEO as a functional polysulfide trapper in LSB cathode. The adsorption of LiPSs by the metal species (i. e., Cr, Mn, Fe, Ni, and Mg) in the HEO takes place through two different paths and leads to enhanced electrochemical stability. We demonstrate that the optimal sulfur cathode with the (CrMnFeNiMg)3 O4 HEO attains a high peak and reversible discharge capacities of 857 mAh g-1 and 552 mAh g-1 , respectively, at a cycling rate of C/10, a long cycle life of 300 cycles, and a high rate performance at the cycling rates from C/10 to C/2.

Spring floods and their major influential factors in the upper reaches of Jinsha River basin during 2001–2020

Study regionThe upper reaches of Jinsha River basin (UJSB) in the northeastern Tibetan Plateau. Study focusSpring floods in the UJSB have posed increasingly severe challenges to reservoirs operation and water resources management due to increased climatic variability under global warming. In this study, spring floods in the region were investigated for 2001–2020 based on station data and multisource remote sensing products. We seek to understand: 1) the characteristics including the peaks, the frequency, and duration of spring floods, 2) how snowfall and rainfall affect spring floods. New hydrological insights for the regionLate May has seen most of the highest spring flood discharge, while some springs have experienced multiple peaks. Extreme spring floods were identified in the years 2012, 2013, 2019, and 2020, with the highest peak discharge (1365.83 m3/s) and longest flood duration (47 days) in 2019. Spring snowmelt dominated the extreme spring floods in most years while the floods in 2012 and 2020 were results of combined snowmelt and rainfall. We defined Snow Water Volume (SWV) as an indicator of the precondition for high spring flood. The key regions contributing to spring floods in the UJSB were concentrated around the Tongtianhe sub-basin and the northern parts of Batang–Zhimenda sub-basin where the SWV was large. The enhanced Westerly jets in winters brought about large snowfall and extended snow cover in the UJSB which can be released as floods triggered by rapid increase in air temperature in the coming spring.

Quantifying the Effect of the Built Environment on Surface Runoff using GIS and Remote Sensing: A Case Study of Ibex Hill-Lusaka

Flash floods are short-period floods with a high peak discharge. Flash floods may be brought about by an increase in rainfall coupled with the rise of impervious surfaces. Accurate estimation of surface runoff and flood depth is therefore a vital task in coming up with ways to intercept and manage excess surface runoff. The study was carried out in Salama Park – Ibex Hill of Lusaka City with a total area of 1,074,822m2. The research focused on quantifying the surface runoff for the years 2019 to 2021 using the Soil Conservation Curve Number (SCS-CN) method, Remote Sensing and GIS. The excess runoff was calculated to range between 306.787mm to 600.419mm and the flood depth computed ranged between 1.665m to 3.260m. The relevance of this study is to understand the mechanisms and examine the impact of excess surface runoff on the built environment as well as its associated consequences.

Landscape and climate conditions influence the hydrological sensitivity to climate change in eastern Canada

Hydrological conditions in cold regions have been shown to be sensitive to climate change. However, a detailed understanding of how regional climate and basin landscape conditions independently influence the current hydrology and its climate sensitivity is currently lacking. This study, therefore, compares the climate sensitivity of the hydrology of two basins with contrasted landscape and meteorological characteristics typical of eastern Canada: a forested boreal climate basin (Montmorency) versus an agricultural hemiboreal climate basin (Acadie). The physically based Cold Regions Hydrological Modelling (CRHM) platform was used to simulate the current and future hydrological processes. Both basin landscape and regional climate drove differences in hydrological sensitivities to climate change. Projected peak SWE were highly sensitive to warming, particularly for milder baseline climate conditions and moderately influenced by differences in landscape conditions. Landscape conditions mediated a wide range of differing hydrological processes and streamflow responses to climate change. The effective precipitation was more sensitive to warming in the forested basin than in the agricultural one, due to reductions in forest canopy interception losses with warming. Under present climate, precipitation and discharge were found to be more synchronized in the greater relief and slopes of the forested basin, whereas under climate change, they are more synchronized in the agricultural basin due to reduced infiltration and storage capacities. Flow through and over agricultural soils translated the increase in water availability under a warmer and wetter climate into higher peak discharges, whereas the porous forest soils dampened the response of peak discharge to increased available water. These findings help diagnose the mechanisms controlling hydrological response to climate change in cold regions forested and agricultural basins.

Debris Flow Hazard Assessment in District Chitral, Eastern Hindu Kush, Pakistan

The aim of this study is debris flow risk zonation using geological and hydrometeorological indicators in district Chitral, Hindu Kush Region Northwest Pakistan. The research is based on secondary data. Multi criteria Analysis (MCA) in Geographical Information System (GIS) environment was used to achieve the objective of the study. The geological and hydrometeorological parameters were analyzed by making five classes of each parameter. The classes are ranked as most favorable and least favorable with numerical weights. The weights were assigned in accordance to their importance in debris flow occurrence. Then weighted overlay analysis techniques were applied to develop composite map representing the importance of each factor. Debris flow risk zonation map was resulted into four classes very high risk zones, high risk zone, moderate zone, low risk zone. The geology of the study area is diverse with frequents earthquakes. Similarly the forest cover is decreasing due to anthropogenic activities. The area is also characterized by long cold winters with frost action. These factors are destabilizing the slope. During summer season rain storm event results high surface runoff and peak discharge in the perennial and non-perennial channels which results flood and debris flow. These events result human life loss and disruption. The main villages located in very high risk zone are Mulkoh, Mastuj, Reshun, Shegram, Terich Gol, Rogar, Asurat, Boni, Brep and Rech Tockhow. They have been frequently affected by hazard in the past decade. Out of the total area, very high risk zone is expanded over 8%, high risk zone is expanded over16%, moderate risk zone is 29% and the rest is low risk zone. This study has highlighted the risk zones which will help disaster management authorities and policy makers to reduce the risk of debris flow in future.

Flash Flood Susceptibility Assessment Based on Morphometric Aspects and Hydrological Approaches in the Pai River Basin, Mae Hong Son, Thailand

Flash floods are water-related disasters that cause damage to properties, buildings, and infrastructures in the flow path. Flash floods often occur within a short period of time following intense rainfall in the high, mountainous area of northern Thailand. Therefore, the purpose of this study is to generate a flash flood susceptibility map using watershed morphometric parameters and hydrological approaches. In this study, the Pai River basin, located in Mae Hong Son in northern Thailand, is divided into 86 subwatersheds, and 23 morphometric parameters of the watershed are extracted from the digital elevation model (DEM). In addition, the soil conservation service curve number (SCS-CN) model is used to estimate the precipitation excess, and Snyder’s synthetic unit hydrograph method is used to estimate the time to peak and time of concentration. With respect to the rainfall dataset, in this study, we combined CHIRPS data (as satellite gridded precipitation data) with rainfall data measured within the study area for the runoff analysis. According to the analysis results, 25 out of 86 subwatersheds are classified as highly susceptible areas to flash floods. The similarities in the morphometric parameters representing watersheds in highly flash flood-susceptible areas indicate that this categorization included areas with high relief, high relief ratios, high ruggedness ratios, high stream frequencies, high texture ratios, high annual runoff, high peak discharge, low elongation ratios, and low lemniscates ratios.

Flash Flood Assessment and Management for Sustainable Development Using Geospatial Technology and WMS Models in Abha City, Aseer Region, Saudi Arabia

Abha city is distinguished by urbanization, infrastructure, deepening watercourses, and changes in runoff flow which encourage flash floods in the urban zones of many villages in the region. AlMahalah village is prone to flash flooding due to its geographic location near the outlet of convergence streams of significant flow. The Geographic Information System (GIS), Remote Sensing (RS), Water Modeling System (WMS), and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) were used to assess the effects of flash floods on AlMahala village. Precipitation data from 1978 to 2020 was statistically processed and analysed to provide more information about flash flood hazards. With a 3-h lag time in both watersheds, the higher peak discharge in Wadi Abha than in Wadi Al Akkas indicates that flooding was a primary concern in Wadi Abha. With an average yearly rainfall of 520 mm, the hydrograph simulation from 1 to 5 April 2020 would contribute to the junction (outlet) point of AlMahala village with a peak discharge rate of 474.14 m3/s. The vegetation cover increased by 243 km2 in 2020 compared to 2016. The HEC-RAS model was used to calculate the water depth, velocity, and elevation of the water surface with and without dam installation. The study provides the administration with practical and reasonable procedures for avoiding flash flood destruction in urban areas.

Flood monitoring and community based flash flood warning system for Nasiri River, West Seram, Maluku

ABSTRACT On 1st of August 2012, two successive flash floods hit Nasiri hamlet in Maluku archipelago, Indonesia. The floods destroyed 61 houses and swept some of them down into the sea. A monitoring and community-based early warning system (MCBEWS) was developed 2 years later. This paper presents the approach, development, and implementation of the system. There are two components, namely community capacity-building and the establishment of telemetric monitoring. The flood warning system considers two causes: extreme rainfall and landslide dam breaks. Raising awareness, workshops, training, and disaster organisation establishment appeared to effectively increase flood disaster preparedness capacity and community commitment. The adoption of a rainfall depth vs. intensity chart method for issuing flood warnings seems to be promising. The presence of an unusual flow reduction in the record during extreme rainfall indicates damming at the upstream of the record station due to landslides. Possible landslide dams near the downstream to the middle reaches might provide dangerous high peak discharge flash floods with short warning times.

Variation of uncertainty of drainage density in flood hazard mapping assessment with coupled 1D\u20132D hydrodynamics model

Coupled 1D–2D hydrodynamic models are widely utilized in flood hazard mapping. Previous studies adopted conceptual hydrological models or 1D hydrodynamic models to evaluate the impact of drainage density on river flow. However, the drainage density affects not only river flow, but also the flooded area and location. Therefore, this work adopts the 1D–2D model SOBEK to investigate the impact of drainage density on river flow. The uncertainty of drainage density in flood hazard mapping is assessed by a designed case and a real case, Yanshuixi Drainage in Tainan, Taiwan. Analytical results indicate that under the same return period rainfall, reduction in tributary drainages in a model (indicating a lower drainage density) results in an underestimate of the flooded area in tributary drainages. This underestimate causes higher peak discharges and total volume of discharges in the drainages, leading to flooding in certain downstream reaches, thereby overestimating the flooded area. The uncertainty of drainage density decreases with increased rainfall. We suggest that modeling flood hazard mapping with low return period rainfalls requires tributary drainages. For extreme rainfall events, a lower drainage density could be selected, but the drainage density of local key areas should be raised.

Glacier surging controls glacier lake formation and outburst floods: The example of the Khurdopin Glacier, Karakoram

Ice dammed glacial lake outburst floods (GLOFs) associated with surge glaciers are increasing in response to climate change. Predicting the phenomenon to protect downstream communities remains challenging around the globe. Surge-type glaciers are characterized by unsteady movements and frequent frontal advances, which cause natural hazards by obstructing river channels, forming ice-dammed lakes, which can cause GLOFs, posing threats downstream. The determination of the surge characteristics, timing and evolution of lakes and GLOFs is fundamental to flood control and disaster management. In this study, the case of the Khurdopin Glacier (Karakoram) is used to elucidate key behavioral characteristics of surging glaciers that usefully can be applied to understand the GLOF hazard from glaciers worldwide. Seven surge periodical cycles associated with the Khurdopin Glacier that occurred at intervals of 19–20 years between 1880 and 2020 were investigated using a GLOF dataset. The ice flow dynamics of three surge events that occurred between 1970 and 2020 were analyzed using high-resolution satellite imagery. The results indicate that the maximum and minimum surge velocities control the conduit development that drains lakes resulting in a number of GLOFs. A surge between 1998 and 2002 generated six GLOFs. A subglacial drainage model was developed to estimate the timing of the peak discharge in GLOF hydrographs. The results show that conduit melt enlargement becomes the dominant drainage process at one-third of the rising limb. These floods' high peak discharges and short durations are primarily due to the higher lake water temperature, which controls the conduit enlargement rate. Based on the current study results, the proposed model can be adopted worldwide for surge-type glaciers. The initiation of the main surge period, which leads to lake formation, can be anticipated, as the pre-surge period can be identified using remote-sensing analysis. The timing of ice-dammed lake formation and GLOFs can be estimated, providing residents and authorities time to take precautionary measures and thus limiting damage downstream.

Review on Co-factors Triggering Flash Flood Occurrences in Indonesian Small Catchments

Flash flood is defined as “a flood of short duration with a relatively high peak discharge,” which leaves little time to take action to reduce property damage and the risk to life. Flash floods occur not only because of heavy rainfall but some co-factors that can trigger it. This study aims to determine the co-factors that trigger the flash flood. Observations are carried out using a descriptive-qualitative approach of five small catchments in Indonesia, namely Bahorok Catchment (Langkat, North Sumatra), Kalijompo, and Kalipakis Catchment (Jember, East Java), Nasiri Catchment (Western Seram, Maluku), Wasior Catchment (Wondama Bay, West Papua). The dominant co-factors are related to rainfall IDF, morphological characteristics (slope, channel properties, flow pattern), geological conditions (rock, soil, structure, geohydrology), catchment conditions (vegetation, land use). Flash floods generally occur due to landslides in the upstream part of the river. Debris consisting of water, rock, and tree trunks can stem the river’s flow and form natural dams. In five flash flood cases under investigation, the causes of a flash flood triggered by heavy rainfall and the morphological characteristics are 60% and 40%, respectively. The quantitative measure of each co-factor that triggers flash floods is essential for further research to identify flash flood symptoms.

Microporous Fe–N4 cataysts derived from biomass aerogel for a high-performance Zn–air battery

Developing inexpensive catalysts with plentiful active sites and high surface area to accelerate the oxygen reduction reaction (ORR) is of great significance for metal–air batteries. Nevertheless, it is still a challenge to balance the content of active sites and the high surface area of catalysts, especially in a versatile and economical way. Herein, a single-atom Fe catalyst was prepared by pyrolyzing biomass aerogels that anchor iron ions through coordination reactions. With the synergistic effect of a large surface area and a high Fe content, the optimized catalyst FeNC-900-8 shows excellent ORR activity and stability. The Zn–air battery with catalyst FeNC-900-8 as the cathode delivers a high peak power density and discharge voltage. This work offers a facile strategy to develop single-atom catalysts with a high surface area and a moderate metal content for high-performance ORRs.