Individual Storm Events Research Articles

Re-processing Datawell Directional Waverider MkIII heave data affected by breaking waves

Observations of nearshore waves are essential for coastal management, planning and operations. However, shallow water deployments often encounter breaking waves, causing anomalous measurements that are rejected during quality control. A new methodology for re-processing wave data containing breaking waves has been developed, utilising data from the National Network of Regional Coastal Monitoring Programmes of England which operates 37 Datawell Directional Waverider MkIII buoys. Heave data affected by breaking waves is reviewed, anomalous heaves removed, and the remaining data re-processed. Validation through a two-stage process confirms that re-processed wave parameters closely match those derived from the established Datawell processing and ensures strong agreement between parameters derived from shorter re-processed records and full-length data. Applying this new approach to all measured storm wave data, 7.3% (928.5 hours) of storm wave data is recovered across the 37 sites. At some sites, the retention of additional storm wave data has considerable impacts on significant wave height (Hm0) return periods. At five sites, the 1 in 100 year return period increased by over one meter. The enhanced dataset now includes more individual storm events and more complete records of storm events, providing a more robust foundation for coastal management and planning.

Dynamics of Barred Coast at Different Temporal Scales (by the Example of Vistula Spit in the Baltic Sea)

According to fundamental concepts, the morphodynamic system of an accumulative sandy coast with underwater bars exhibits cyclic behavior across various time scales. This raises the question: which factor is more significant for the dynamics of a given coast—individual storms or seasonal changes in wave activity? While observations and studies addressing this issue have primarily been conducted on oceanic coasts, there is a lack of comparable data for fetch-limited areas. Monitoring of the bottom topography along the west coast of Vistula Spit (Baltic Sea) revealed a cyclic behavior in morphology, transitioning from a straightened external bar to its connection with the shore. Analysis of field measurement results indicated that seasonal variations in wave intensity do not significantly impact coastal relief. Furthermore, it was found that the complete cycle of underwater bar evolution lasts approximately two years, during which the coast profile maintains a stable shape at the stage of the straightened external bar. The identification of the primary factor influencing coastal evolution can be characterized by the Dean number (Ω), which combines wave parameters (wave height and period) with sediment fall velocity. Utilizing ERA5 wave reanalysis data, we compared the variability of Ω values on both annual and monthly scales. The analysis revealed that for the section of the coast under consideration, there is no clearly dominant evolutionary factor; rather, the coast is influenced approximately equally by individual storm events and seasonal fluctuations in wave energy. Modeling storm-induced bed profile deformations using the CROSS-PB model demonstrated that the position of the external underwater bar remains nearly constant even during intense and prolonged storms. It is concluded that under specific conditions—determined by a combination of sediment size, coastal slope, and wave regime characteristics—the coast can remain stable, exhibiting minimal response to relatively strong storms and seasonal variations in wave energy. Such coasts are characterized by an absence of a dominant evolutionary factor as indicated by fluctuations in the Dean parameter, allowing their morphodynamic cycles to span several seasons. This type of morphodynamics in coastal accumulative relief appears to be typical for conditions found in fetch-limited areas, such as regional and semi-closed seas.

Data-driven modelling of coastal storm erosion for real-time forecasting at a wave-dominated embayed beach

Emergency managers have an increasing need for tools to enhance preparedness to extreme coastal storms and support disaster risk reduction measures. With the emergence of Early Warning Systems (EWSs) for coastal storm hazards, a fundamental challenge is the accurate prediction of sandy beach erosion at lead times of days to weeks corresponding to an approaching storm event. This work presents a data-driven modelling approach to predict storm-driven beach erosion (shoreline change) using a large dataset of 276 individual storm events at Narrabeen-Collaroy Beach, SE Australia. Correlation analysis between individual storm characteristics and shoreline response at three locations along the embayment with varying exposure to the prevailing waves indicates that cumulative storm wave energy is the dominant driver of storm erosion at this site. This is followed by the pre-storm beach width, storm wave direction and to a minimal extent, storm wave period and water levels. A multi-linear regression model of storm erosion is developed and found to accurately predict shoreline change due to individual storm events (RMSE = 3.7 m–6.4 m). This work highlights the value of high-frequency shoreline data for storm erosion forecasting and provides a framework for real-time forecasting applications.

Understanding compound extreme precipitations preconditioned by heatwaves over China under climate change

Compared with individual heatwaves or storm events, the compound extreme precipitations preconditioned by heatwaves (CHEPs) usually amplify their adverse repercussions on both ecosystems and society. However, little is known about the physical mechanisms of generations, especially considering precipitation types triggered by various factors and synoptic patterns. By classifying extreme precipitations based on duration, we conduct an event-based analysis and comprehensively assess CHEPs using the machine learning-constrained framework and binning scaling methods over China. We find the fraction of CHEPs to total extreme short-duration/long-duration precipitations (ESDPs/ELDPs) has substantially increased by 18%/15% from 1979 to 2021, when using dry-bulb temperature to identify heatwaves. More notably, the hotspots of CHEPs are generally consistent with those of ESDPs. The ESDPs play a dominant role in shaping CHEPs episodes, which are governed by enhancing atmospheric instability due to preconditioned heatwaves. The horizontal moisture advection and transient vertical dynamic motion of moisture, which are paramount to LDPs, is not significantly enhanced by the overheating atmosphere, leading to a small fraction of LDPs to CHEPs. In addition, the intensity of ESDPs tends to increase with air temperature at higher rates than that of ELDPs. As short-duration storms may trigger severe flash floods, ample attention should be paid to the escalating risks of CHEPs under climate change.

Modeling the potential impact of storm surge and sea level rise on coastal archaeological heritage: A case study from Georgia.

Climate change poses great risks to archaeological heritage, especially in coastal regions. Preparing to mitigate these challenges requires detailed and accurate assessments of how coastal heritage sites will be impacted by sea level rise (SLR) and storm surge, driven by increasingly severe storms in a warmer climate. However, inconsistency between modeled impacts of coastal erosion on archaeological sites and observed effects has thus far hindered our ability to accurately assess the vulnerability of sites. Modeling of coastal impacts has largely focused on medium-to-long term SLR, while observations of damage to sites have almost exclusively focused on the results of individual storm events. There is therefore a great need for desk-based modeling of the potential impacts of individual storm events to equip cultural heritage managers with the information they need to plan for and mitigate the impacts of storm surge in various future sea level scenarios. Here, we apply the Sea, Lake, and Overland Surges from Hurricanes (SLOSH) model to estimate the risks that storm surge events pose to archaeological sites along the coast of the US State of Georgia in four different SLR scenarios. Our results, shared with cultural heritage managers in the Georgia Historic Preservation Division to facilitate prioritization, documentation, and mitigation efforts, demonstrate that over 4200 archaeological sites in Georgia alone are at risk of inundation and erosion from hurricanes, more than ten times the number of sites that were previously estimated to be at risk by 2100 accounting for SLR alone. We hope that this work encourages necessary action toward conserving coastal physical cultural heritage in Georgia and beyond.

Rainfall frequency analysis using event-maximum rainfalls – An event-based mixture distribution modeling approach

Rainfall frequency analysis, an essential work for water resources management, is often conducted by using the annual maximum rainfall series. For rainfall stations with short record lengths and outliers presence, the use of annual maximum series for rainfall frequency analysis may yield design rainfall estimates of higher uncertainties. Moreover, for regions with cyclostationary climate patterns, the annual maximum rainfalls may be caused by different prevalent storm types, which differ in terms of their occurrence frequency and storm rainfall characteristics. In this study, we propose a novel event-maximum-rainfall-based mixture distribution modeling approach for rainfall frequency analysis. By considering the event-maximum rainfalls of individual storm events, the sample size for parameter estimation increases, and the uncertainty of design rainfall estimates reduces. Mixture distribution modeling enables a thorough investigation of the contributing probabilities of different storm types to the annual maximum rainfall. Through rigorous stochastic simulation, we demonstrated the superiority of the proposed approach over the conventional annual maximum rainfall approach. The proposed approach was applied to four representative rainfall stations in Taiwan, and the results revealed that the proposed approach is more robust than the conventional annual maximum rainfall approach. The results provide insights into the contributions of individual storm types to the annual maximum rainfall.

The influence of spatial patterns in rainfall on shallow landslides

Understanding how rainfall events influence the pattern and magnitude of landslide response is an important research focus from geomorphological and hazard planning perspectives. Few studies quantitatively relate spatial patterns in rainfall and landslides, largely due to difficulties in acquiring landslide inventories and data on rainfall patterns for individual storm events. However, the increasing availability of frequent, high-resolution satellite imagery and weather radar is overcoming these impediments. Here, we aim to a) identify which factors most influence susceptibility to shallow landslides at the event scale and b) assess how the spatial density of landslides varies in relation to rainfall. We combine landslide inventories spanning study areas located across the upper North Island of New Zealand with rainfall estimates from weather radar to assess the influence of different explanatory variables using a logistic regression model. We found land cover and slope exert the largest influence on landslide susceptibility ahead of intra-event rainfall intensities and pre-event rainfall accumulations. Of the rainfall variables, maximum 12-h rainfall normalised by the 10-y recurrence interval intensity and the 10-d pre-event accumulation normalised by mean annual rainfall had the most influence on susceptibility. Forest cover reduced the sensitivity of landslide spatial density to variations in slope, rainfall, and rock type, in contrast to pasture. We observed a 3.5-fold increase in mean landslide density once the maximum 12-h intensity was ≥25 % above the 10-y recurrence interval intensity for pastoral land on weak sedimentary rocks. This threshold is consistent with the increase in 12-h rainfall by late century under the highest levels of projected warming in New Zealand, which suggests that the landslide response to storm rainfall could be significantly amplified by climate change. Our study demonstrates the insights gained from combining event inventories with spatial rainfall data to better understand factors influencing landslide susceptibility.

Reforesting degraded hillslopes with exotic pines in Trinidad and Tobago: Infiltration, repellency and implications for runoff and recharge

In the Caribbean, planting resilient, fast growing exotic pine trees have commonly been used to reforest degraded landscapes. However, little is currently understood about how these practices alter soil water movement and subsequently runoff and recharge. We monitored the surface soil water repellency, hydraulic conductivity, and subsurface soil moisture response to individual storm events in an exotic pine plantation and native forest in the dry and wet seasons. During the wet season, neither forest had a repellent soil surface, and the hydraulic conductivity in the exotic pines (48 mm h−1) were not significantly higher than the native forest (36 mm h−1). The speed and magnitude of the soil moisture response did not differ substantially between both forests in the wet season. However, during the mid dry season, a threshold soil moisture level was reached in the pines which triggered the development of repellent/hydrophobic conditions across all locations. Repellency reduced the surface hydraulic conductivity to 1.6 mm h−1, which in turn severely reduced the soil moisture response to rainfall. Our findings illustrate that throughout most of the year, the exotic pine plantation does not have a substantial negative impact on runoff or recharge. Only under the driest conditions do they negatively affect these processes. Our work also highlights the importance of characterising soil water repellency, hydraulic conductivity, and subsurface soil water responses over longer time periods to account for temporal variability.

MINErosion 4: Using measurements from a tilting flume-rainfall simulator facility to predict erosion rates from post-mining catchments/landscapes in Central Queensland, Australia

The use of draglines to remove overburden in Queensland opencut mines, results in landscapes that consist of long parallel tertiary overburden spoil-piles that are generally highly saline, dispersive, and highly erodible. The height of these spoil-piles may exceed 50–60 m above the original landscapes and the slopes are at the angle of repose of around 75% or 37°. Legislation and public opinion require that these highly disturbed open-cut post-mining landscapes should be satisfactorily rehabilitated into an approved post-mining land use with acceptable erosion rates. Therefore, these slopes must be reduced before the landscape can be rehabilitated. The most expensive component of the rehabilitation process is the re-shaping and preparation of the overburden to create a suitable landscape for vegetation growth. As soils and overburden varies greatly in their erodibilities, the extent and cost of earthworks can be minimized, and rehabilitation failures avoided, if soil erosion from designed landscapes can be predicted using laboratory-based parameters prior to construction of these landscapes. This paper describes the development of a model for that purpose.A catchment or landscape erosion model MINErosion 4 was developed by upscaling the existing hillslope model MINErosion 3 (So, et al., 2018) and integrate it with both ESRI ArcGIS 10.3 or QGIS 3.16 (freeware), to predict event based and mean annual erosion rate from a postmining catchment or landscape. MINErosion 3 is a model that can be used to predict event and annual erosion rates from field scale hillslopes using laboratory measured erodibility parameters or routinely measured soil physical and chemical properties, and to derive suitable landscape design parameters (slope gradient, slope length and vegetation cover) that will result in acceptable erosion rates. But it cannot be used to predict the sediment delivery from catchments or landscapes. MINErosion 4 was validated against data collected on three instrumented catchments (up to 0.91 ha in size) on the Curragh mine site in Central Queensland. The agreement between predicted (Y) and measured (X) values were very good with the regression equation of Y = 0.92X and an R2 value of 0.81 for individual storm events, and Y = 1.47X and an R2 value of 0.73 for the average annual soil loss. This is probably the first time that a catchment scale erosion is successfully predicted from laboratory measured erodibility parameters.

Alongshore Variable Accretional and Erosional Coastal Foredune Dynamics at Event to Interannual Timescales

AbstractNatural and constructed dunes are increasingly being utilized to buffer flooding impacts from storms and rising sea levels along sandy coastlines. However, a lack of data at the appropriate spatial and temporal resolution often precludes isolating the total magnitude, specific timing, and alongshore variability of volumetric coastal dune changes resulting from both wave and wind‐driven processes. Here mobile terrestrial lidar data from 46 collections along a 6.5 km stretch of sandy beach and dunes in Duck, NC, USA are used to assess the magnitude and drivers of alongshore variable dune responses between 2012 and 2020. Despite numerous major storm events which impacted the dunes over this time period, the dunes grew volumetrically both in nourished and un‐nourished sections of the study site. Growth of the dunes was seasonally and spatially variable with the largest total growth recorded in the Fall, coinciding with a period of frequent windy storms but also the highest total water levels, and along the regions with the lowest gradient βbeach. The vertical accretion patterns of these wind‐blown sediments are shown to vary depending on the dune management style, specifically, if dunes were not managed, sand fenced, or artificially constructed. Dune erosion also occurred episodically within the study period, with the steepest sloped beach sections likely to be the most impacted during individual storm events.

Influence of Rainfall and Tree Traits on Stem Flow Production of Selected Urban Tropical Trees

Stem flow is small but important fraction of intercepted precipitation channeled through a tree canopy to the base of the trunk. Given increased impervious covers in cities, quantification of stem flow is necessary for a holistic understanding of hydrology in urban ecosystems. The values of urban treesare increasingly being recognized over the decades and authorities have invested in urban green infrastructure including urban forestry. However, knowledge related to rainfall redistribution by urban trees and reduce storm water are yet to be discovered for topical tree species. Therefore, this study aimed study the effect of canopy traits on stem flow percent and funneling ratios for isolated urban trees in a tropical wet climate. The stem flow of 21 individual trees (7 species with 3 replicates) located in University of Sri Jayewardenepura, Sri Lanka were measured from August 2019 to November 2019 by installing SF collars at diameter at breast height (dbh). The stem flow was measured for 20 individual storm events started with dry canopy condition. Gross precipitation was recorded using an automated weather station located in an open area in University premises. All trees produced stemflow for storm events larger than 4 mm. Felicium decipiens generated the highest stem flow and Pterocarpus marsupium Roxburgh generated the lowest among studied species. While F. decipiens showing negative correlation between rainfall and stem flow others showed positive correlation. In all species, crown volume, dbh and bark thickness showed negative relationship with stem flow. However, individual-tree stem flow percent and funneling ratio values were variable, even for similar rain depths, suggesting that meteorological factors play a role. Our findings highlight the need of careful species selection for urban forestry and importance of infiltration capacity at the base of urban trees when integrating storm water management with vegetation and soils in cities.
 Keywords: Stem flow percent, Funneling ratio, Urban hydrology, Urban forestry, Storm water management

Seasonal flashiness and high frequency discharge events in headwater streams in the North Carolina Piedmont (United States)

AbstractFirst‐order streams are rarely the focus of research even though they play an important hydrological and ecological role in upland landscapes and may be more susceptible to human impacts than larger streams. We studied 16 first‐order streams in the North Carolina Piedmont to examine relationships between land use, discharge, flashiness and conductivity in the headwaters of the Rocky River and McDowell Creek. Stream gauges were installed on each of the 16 headwater streams to provide constant monitoring of stream depth, temperature and specific conductance. Rating curves were created for each site using models that combined field measured and Manning's calculated discharge. Initial attempts to measure flashiness using the Richards‐Baker Index (RBI) indicated that it is not a good proxy for flashiness in small streams because its use of median daily flows do not capture fluctuations that occur over short time periods. Instead, we developed a new method that focused on the number of days each stream flows above its 99th percentile flow (DMQ99). We also examined individual storm events across multiple seasons. We found that headwater streams in the Piedmont are flashier than more commonly gauged second and third order streams because first‐order streams are more directly connected to the landscape. Streams located in suburban areas tend to be flashier than streams in forested areas as a result of the increase in impervious surfaces and the reduction of evapotranspiration (ET) caused by development. Additionally, we found that all streams become flashier in the winter when ET is lower, suggesting important feedbacks between physical and biological systems. All streams experience periodic extreme conductivity events, indicating significantly impaired ecological conditions. More developed basins generally have higher maximum specific conductance compared with less developed basins although streams have significant natural variability as well. Overall, our results indicate that first‐order streams in the Piedmont are highly impacted by development and that extra caution should be exercised when altering landscapes near small streams.

Hydrologic processes regulate nutrient retention in stormwater detention ponds

Managed stormwater ponds are abundant in urban landscapes in much of the world, performing vital but under-studied functions for attenuation of urban runoff and nutrient pollution. Water quality improvements are widely assumed to arise from settling of nutrients and other contaminants bound to particulates, with less consideration of hydrological and biogeochemical processes. To inform improved management of ponds for nutrient retention, we studied three mature urban detention ponds in the Twin Cities, MN, USA using continuous monitoring of pond hydrology and concentrations of nitrogen and phosphorus, coupled with periodic measurement of physiochemical conditions in the ponds. Across the three sites, annual nutrient retention was high for both nitrogen (>58%) and phosphorus (>48%) despite expectations of poor performance for phosphorus due to old age and internal loading linked to hypolimnetic anoxia. Both annual and event-scale analyses suggested strong hydrologic controls on nutrient retention, with retention for individual storm events strongly regulated by antecedent pond storage capacity. Events with net nutrient export occurred primarily due to low volume retention rather than relatively high outflow concentrations. Together these results suggest that understanding and improving pond hydrologic function is crucial to improving managed stormwater pond performance for meeting downstream water quality goals.

Seasonal Hydroclimate Recorded in High Resolution δ18O Profiles Across Pinus palustris Growth Rings

AbstractRainfall amount and intensity are increasing under anthropogenic climate change, but many instrument records span less than a century. The oxygen isotopic composition of tree‐ring cellulose (δ18Ocell) reflects local source water, climate, and tree physiology. The patterns of δ18Ocell within tree‐rings has the potential to extend pre‐instrument climate records with subannual resolution, but the influences on intra‐ring δ18Ocell profiles are unexplored in many settings. In this study, high‐resolution δ18Ocell profiles were analyzed on three longleaf pine trees growing in a native savanna in Louisiana, United States. The time series covers a wide range of rainfall conditions from 2001 to 2008 C.E. with a total of 421 δ18Ocell analyses. The δ18Ocell values for individual years are well correlated with each other both within and between trees (r = 0.71–0.78). We used principal components analysis and k‐means clustering to differentiate δ18Ocell profiles into two groupings: symmetrical δ18Ocell profiles versus asymmetrical profiles that have depressed latewood δ18Ocell values. The slope of latewood δ18Ocell profiles and mean δ18Ocell values of latewood tissue correlate with total June‐November precipitation. We hypothesize that poorly drained soils in the study area mediate the influence of any individual storm event: in dry years, 18O‐depleted signals from convective storms are moderated by subsequent evaporative enrichment of standing water, whereas in wet years, increased humidity and frequent re‐supply of 18O‐depleted water overrides evaporative enrichment effects, resulting in low δ18Ocell of latewood. These results suggest that δ18Ocell proxies for tropical storm occurrence need to account for soil conditions at the site of tree growth.

Synoptic Causes and Socio-Economic Consequences of a Severe Dust Storm in the Middle East

Dust storms represent one of the most severe, if underrated, natural hazards in drylands. This study uses ground observational data from meteorological stations and airports (SYNOP and METARs), satellite observations (MODIS level-3 gridded atmosphere daily products and CALIPSO) and reanalysis data (ERA5) to analyze the synoptic meteorology of a severe Middle Eastern dust storm in April 2015. Details of related socio-economic impacts, gathered largely from news media reports, are also documented. This dust storm affected at least 14 countries in an area of 10 million km2. The considerable impacts were felt across eight countries in health, transport, education, construction, leisure and energy production. Hospitals in Saudi Arabia, Qatar and the UAE experienced a surge in cases of respiratory complaints and ophthalmic emergencies, as well as vehicular trauma due to an increase in motor vehicle accidents. Airports in seven countries had to delay, divert and cancel flights during the dust storm. This paper is the first attempt to catalogue such dust storm impacts on multiple socio-economic sectors in multiple countries in any part of the world. This type of transboundary study of individual dust storm events is necessary to improve our understanding of their multiple impacts and so inform policymakers working on this emerging disaster risk management issue.

Event-Based Stable Isotope Analysis of Precipitation Along a High Resolution Transect on the South Face of O‘ahu, Hawai‘i

While the influence of elevation and seasonal variation on isotopic composition has been studied on Maui, Hawai‘i Island, and O‘ahu (Scholl et al. 1996, Scholl et al. 2002, Scholl et al. 2007, Dores et al. 2020, Fackrell et al. 2020, Tachera et al. 2021), this work is the first to investigate event-based precipitation in detail on the island of O‘ahu. The stable isotopic composition of water has been used to track the movement of water within the hydrosphere, to investigate the type and origin of a rainfall event, and elevation of collection, among other characteristics. Here, we present a high-resolution study of the stable isotopes δ2H and δ18O of precipitation along a compact land-to-sea transect in Waikīkī, a southwest facing region on O‘ahu. The study provides a unique, in-depth investigation into the nature of individual storm events, and how they contribute to a larger seasonal climatic pattern. Monthly precipitation samples were collected at three sites along the transect from December 2017 to March 2019 and event-based samples were collected at the Makai site from October 2018 to February 2019. Storm direction, temperature, and relative humidity were recorded for each event-based sample. Results suggest that evaporative conditions at different elevations influence the isotopic composition of precipitation, either through net addition as moisture recycling, or net loss of evaporated water. The spatial distribution of these patterns from site to site illustrates the extreme heterogeneity of Hawaiian watersheds.

A multi-sensor evaluation of precipitation uncertainty for landslide-triggering storm events.

Extreme precipitation can have profound consequences for communities, resulting in natural hazards such as rainfall‐triggered landslides that cause casualties and extensive property damage. A key challenge to understanding and predicting rainfall‐triggered landslides comes from observational uncertainties in the depth and intensity of precipitation preceding the event. Practitioners and researchers must select from a wide range of precipitation products, often with little guidance. Here we evaluate the degree of precipitation uncertainty across multiple precipitation products for a large set of landslide‐triggering storm events and investigate the impact of these uncertainties on predicted landslide probability using published intensity–duration thresholds. The average intensity, peak intensity, duration, and NOAA‐Atlas return periods are compared ahead of 177 reported landslides across the continental United States and Canada. Precipitation data are taken from four products that cover disparate measurement methods: near real‐time and post‐processed satellite (IMERG), radar (MRMS), and gauge‐based (NLDAS‐2). Landslide‐triggering precipitation was found to vary widely across precipitation products with the depth of individual storm events diverging by as much as 296 mm with an average range of 51 mm. Peak intensity measurements, which are typically influential in triggering landslides, were also highly variable with an average range of 7.8 mm/h and as much as 57 mm/h. The two products more reliant upon ground‐based observations (MRMS and NLDAS‐2) performed better at identifying landslides according to published intensity–duration storm thresholds, but all products exhibited hit ratios of greater than 0.56. A greater proportion of landslides were predicted when including only manually verified landslide locations. We recommend practitioners consider low‐latency products like MRMS for investigating landslides, given their near‐real time data availability and good performance in detecting landslides. Practitioners would be well‐served considering more than one product as a way to confirm intense storm signals and minimize the influence of noise and false alarms.

Unit hydrograph identification based on fuzzy regression analysis

A methodology has been developed to treat the uncertainties of the unit hydrograph rainfall-runoff transformation based on the fuzzy linear regression model. The components of the unit hydrograph are proposed to be symmetric triangular fuzzy numbers. The main idea is to develop a fuzzified version of the widely—used unit hydrograph. The input of the model is the effective rainfall (which is a set of crisp numbers) and the output is the runoff (which is a set of fuzzy numbers). The problem of determining the fuzzy components of the unit hydrograph is transformed into a linear optimization approach based on the fuzzy linear regression of Tanaka. The condition applied is that the data must be included in the fuzzy band of discharge produced by the fuzzy unit hydrograph. However, some modifications of the widely-used fuzzy regression are proposed in order to be compatible with the unit hydrograph implementation. The model was tested based on twenty real rainfall-runoff events, the conclusion being that it works well in the case of an individual storm event. However, the consideration of many storms seems to be required in order to increase the applicability of the produced fuzzy hydrograph to other storms in such a way that the fuzziness is increased. Several measures of suitability are proposed in order to check the efficiency of the proposed method. Several other useful comments according to the comparison with other unit hydrograph considerations are made.

Arctic concentration–discharge relationships for dissolved organic carbon and nitrate vary with landscape and season

AbstractClimate change is intensifying the Arctic hydrologic cycle, potentially accelerating the release of carbon and nutrients from permafrost landscapes to rivers. However, there are limited riverine flow and solute data of adequate frequency and duration to test how seasonality and catchment landscape characteristics influence production and transport of carbon and nutrients in Arctic river networks. We measured high frequency hydrochemical dynamics at the outlets of three headwater catchments in Arctic Alaska over 3 years. The catchments represent common Arctic landscapes: low‐gradient tundra, low‐gradient and lake‐influenced tundra, and high‐gradient alpine tundra. Using in‐situ spectrophotometers, we measured dissolved organic carbon (DOC) and nitrate (NO3−) concentrations at 15‐min intervals through the flow seasons of 2017, 2018, and 2019. These high‐frequency data allowed us to quantify concentration–discharge (C‐Q) responses during individual storm events across the flow season. Differences in C‐Q responses among catchments indicated strong landscape and seasonal controls on lateral DOC and NO3− flux. For the two low‐gradient tundra catchments, we observed consistent DOC enrichment (transport‐limitation) and NO3− dilution (source‐limitation) during flow events. Conversely, we found consistent NO3− enrichment and DOC dilution in the high‐gradient alpine catchment. Our analysis revealed how high flow events may contribute disproportionately to downstream export in these Arctic streams. Because the duration of the flow season is expected to lengthen and the intensity of Arctic storms are expected to increase, understanding how discharge and solute concentration are coupled is crucial to understanding carbon and nutrient dynamics in rapidly changing permafrost ecosystems.

Stormflows Drive Stream Carbon Concentration, Speciation, and Dissolved Organic Matter Composition in Coastal Temperate Rainforest Watersheds

AbstractStream water carbon concentrations can be highly dynamic on the time scales of both individual storm events and seasonal hydroclimatic shifts. We collected stream water daily over a 6‐day storm from three headwater subcatchments of varying landcover (poor fen, forested wetland, and upland forest) and the catchment outlet to evaluate how precipitation events impact the concentration and speciation of carbon (organic vs. inorganic) as well as the composition of dissolved organic matter (DOM) exported laterally from coastal temperate rainforest catchments. Dissolved and particulate organic carbon concentrations increased during the storm at all sites, while dissolved inorganic carbon concentrations were diluted during peak flows. These results highlight the importance of quantifying all forms of lateral carbon export when evaluating the role of storms in catchment‐scale carbon cycling. Isotopic hydrograph separation using stream water δ18O showed that percent new water was significantly related to carbon concentration and form providing a clear link between stream water sources (i.e., recent event water) and soil carbon source areas that become connected to surface water during storms. Furthermore, ultrahigh‐resolution mass spectrometry showed that stream water DOM exported from the upland forest contained the greatest molecular diversity of the three landscape types and had the largest changes in composition over the storm suggesting that the wetland‐dominated subcatchments were less compositionally diverse with regard to soil DOM pools active during the storm. Overall, this study provides insight into hydro‐biogeochemical drivers that control lateral carbon export from forested catchments in a region where an increasing fraction of precipitation is falling as rain.