Extreme Hydrological Events Research Articles

Multitemporal Relationships Between the Hydroclimate and Exports of Carbon, Nitrogen, and Phosphorus in a Small Agricultural Watershed

AbstractAgriculture affects the biogeochemical cycles of carbon, nitrogen, and phosphorus, leading to a deterioration of surface water quality. The increasing magnitude of climate change raises questions about potential additional or mitigating effects of climate change on this deterioration. One way to understand these potential effects is to cross‐analyze the dynamics of nutrient concentrations and hydroclimatic variables at multiple time scales. Here, we used a 16‐year data set, from a 5 km2 agricultural watershed in France with a temperate oceanic climate, that contains a daily record of nutrient concentrations and hydroclimatic variables from 2002–2017. We calculated Mann‐Kendall and Theil‐Sen tests, Fourier transforms, and daily hydroclimatic distributions associated with extreme stream concentrations to investigate long‐term trends, seasonal dynamics and their interannual variations, and the daily time scale, respectively. Dynamics of dissolved organic carbon (DOC) and nitrate (NO3) concentrations displayed opposite patterns at the three temporal scales, while soluble reactive phosphorus concentrations showed decoupled dynamics, related more to extreme hydrological events. Climate and past agricultural changes seem to have a synergetic effect that leads to long‐term NO3 decrease and DOC increase. Precipitation and, to a greater extent, watershed wetness controlled seasonal and event‐driven dynamics.

Functional Diversity of Riparian Woody Vegetation Is Less Affected by River Regulation in the Mediterranean Than Boreal Region.

River regulation may filter out riparian plants often resulting in reduced functional diversity, i.e., in the range of functions that organisms have in communities and ecosystems. There is, however, little empirical evidence about the magnitude of such reductions in different regions. We investigated the functional diversity patterns of riparian woody vegetation to streamflow regulation in boreal Sweden and Mediterranean Portugal using nine plant functional traits and field data from 109 sampling sites. We evaluated changes in mean plant functional traits as well as in indices of multidimensional functional traits, i.e., functional richness (FRic) and functional redundancy (FRed) within regions and between free-flowing and regulated river reaches. We found that regulation significantly reduced functional diversity in Sweden but not in Portugal. In Sweden, the increased magnitude of variations in water flow and water level in summer, the prolonged duration of extreme hydrological events, the increased frequency of high-water pulses, and the rate of change in water conditions were the likely main drivers of functional diversity change. Small riparian plant species with tiny leaves, poorly lignified stems, and shallow root systems were consistently associated with regulated sites in the boreal region. In Portugal, the similar functional diversity values for free-flowing and regulated rivers likely stem from the smaller streamflow alterations by regulation combined with the species legacy adaptations to the Mediterranean natural hydrological regimes. We conclude that streamflow regulation may reduce the functional diversity of riparian woody vegetation, but the magnitude of these effects will vary depending on the adaptations of the local flora and the patterns of streamflow disturbances. Our study provides insights into functional diversity patterns of riparian woody vegetation affected by regulation in contrasting biomes and encourages further studies of the functional diversity thresholds for maintaining ecosystems.

Advances in Hydrologic Forecasts and Water Resources Management

The impacts of climate change on water resources management as well as the increasing severe natural disasters over the last decades have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resources management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modelling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has the great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modelling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; and (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue can not only advance water sciences but can also support policy makers toward more sustainable and effective water resources management.

Assessment of CFSR and CMADS Weather Data for Capturing Extreme Hydrologic Events in the Fuhe River Basin of the Poyang Lake

AbstractEvaluating the accuracy of gridded weather data is important because these data significantly affect the results of hydrologic simulations. In this study, we evaluated the applicability of Climate Forecast System Reanalysis (CFSR) and China Meteorological Assimilation Driving Datasets for the Soil and Water Assessment Tool (SWAT) model (CMADS) datasets for capturing the hydrologic extreme events in the Fuhe River Basin (FRB) of the Poyang Lake, a typical humid area in eastern China. First, both the CFSR and CMADS temperature and precipitation data obtained from 2008 to 2013 were validated using ground‐based meteorological station data. Then, the SWAT model was driven by the CFSR and CMADS datasets for hydrologic predictions. The results show that both CFSR and CMADS temperature data are of high quality. The CMADS data underestimate precipitation, whereas CFSR data overestimate precipitation. Both datasets have their own advantage and disadvantage to detect extreme rainfall events. For the FRB case study, SWAT models driven by two datasets yield good streamflow simulation results. The CMADS‐driven model performs slightly better than CFSR‐driven model in predicting extreme streamflow events in the simulation time‐period (2009–2013). In general, both the CFSR and CMADS data can be used to obtain satisfactory simulation results for hydrologic predictions. They provide alternatives that enable quickly implementing a hydrologic model in data‐scarce areas.

Environmental damage associated with severe hydrologic events: a LiDAR-based geospatial modeling approach

Increasingly, extreme hydrologic events are causing flooding and infrastructure damages in excess of one billion dollars per event. Hurricane storm surge is most frequently implicated; however, rainfall dominated events may have more damaging and costly impacts. Additionally, the environmental impacts and consequences of such events are not often considered in estimates of flood damage or in mitigation efforts. This paper integrates geographic information systems, floodplain analysis, observed flood level data, and public sources of pollutant releases to describe the environmental impacts of severe hydrologic events and identify infrastructure vulnerabilities with an emphasis on environmental facilities. Observed high water marks from recent significant flooding events, coupled with LiDAR data, were used to create high-resolution inundation maps. The degree of inundation of facilities with the potential to cause environmental impacts, such as wastewater treatment facilities, landfills, and Superfund sites, was modeled. The results indicated that rainfall-based flooding events could cause substantially more inundation of environmental facilities compared to surge-based flooding. Additionally, 100 and 500-year floodplain mapping was not sufficient to identify facilities at risk of inundation or spillage. The results from the study enable the determination of locations and facilities that are highly susceptible to environmental pollution due to flooding that would be candidates for increased resilience planning.

Panorama brasileiro da relação entre leptospirose e inundações

A leptospirose é uma das doenças de veiculação hídrica que mais preocupam o setor de saúde no Brasil. Portanto, o objetivo deste artigo foi, por meio de levantamento de trabalhos existentes, identificar, analisar e descrever os fatores socioeconômicos, ambientais e climáticos que podem estar diretamente relacionados ao aumento dos casos de leptospirose. Por meio de pesquisa nas bases de dados de periódicos CAPES e LILACS, o presente trabalho selecionou 43 artigos que trataram de leptospirose e inundações no Brasil. A maior parte desses trabalhos relacionou a ocorrência de eventos hidrológicos extremos ao aumento do número de casos de leptospirose; os demais trabalhos relacionam outros fatores como acúmulo de resíduos, falta de drenagem urbana, atividades laborais, entre outros

Trends and variability of precipitation extremes in the Peruvian Altiplano (1971–2013)

AbstractPrecipitation extremes have been investigated throughout the last decades in different regions of the Andes. However, little attention has been paid to the Altiplano region (Central Andes), especially to the Peruvian Altiplano (PA) that represents a complex area and is highly vulnerable to extreme events, such as floods and droughts, driven by the strong variability of precipitation. This study focuses on the analysis of 11 extreme precipitation indices (EPIs) in the period 1971–2013. In this context, commonly used statistical trend and break analyses were applied and a false discovery procedure was used in order to reduce the number of artificial significant tests. Additionally, the relative dominance of precipitation frequency and intensity in interannual precipitation datasets was determined. Finally, the correlation between EPIs and six oceanic‐atmospheric indices were analysed. The results indicate that there is no significant global trend towards wet or dry conditions in the PA, although a signal of a more slightly decrease of precipitation is presented in the Southern PA. Additionally, interannual variability of total precipitation is mainly dominated by precipitation frequency. The Central Tropical Pacific sea surface temperature plays a major role for the maximum and average length of wet periods as well as for total precipitation. This finding is particularly relevant for the southwestern PA. Our results have important implications for risk management and adaptation planning related to extreme hydrological events in the PA.

Short-Term and Medium-Term Drought Forecasting Using Generalized Additive Models

Forecasting extreme hydrological events is critical for drought risk and efficient water resource management in semi-arid environments that are prone to natural hazards. This study aimed at forecasting drought conditions in a semi-arid region in north-eastern South Africa. The Standardized Precipitation Evaporation Index (SPEI) was used as a drought-quantifying parameter. Data for SPEI formulation for eight weather stations were obtained from South Africa Weather Services. Forecasting of the SPEI was achieved by using Generalized Additive Models (GAMs) at 1, 6, and 12 month timescales. Time series decomposition was done to reduce time series complexities, and variable selection was done using Lasso. Mild drought conditions were found to be more prevalent in the study area compared to other drought categories. Four models were developed to forecast drought in the Luvuvhu River Catchment (i.e., GAM, Ensemble Empirical Mode Decomposition (EEMD)-GAM, EEMD-Autoregressive Integrated Moving Average (ARIMA)-GAM, and Forecast Quantile Regression Averaging (fQRA)). At the first two timescales, fQRA forecasted the test data better than the other models, while GAMs were best at the 12 month timescale. Root Mean Square Error values of 0.0599, 0.2609, and 0.1809 were shown by fQRA and GAM at the 1, 6, and 12 month timescales, respectively. The study findings demonstrated the strength of GAMs in short- and medium-term drought forecasting.

Evaluating the performance of climate models in reproducing the hydrological characteristics of rainfall events

ABSTRACT Rainfall events largely control hydrological processes occurring on and in the ground, but the performance of climate models in reproducing rainfall events has not been investigated enough to guide selection among the models when making hydrological projections. We proposed to compare the durations, intensities, and pause periods, as well as depths of rainfall events when assessing the accuracy of general circulation models (GCMs) in reproducing the hydrological characteristics of observed rainfall. We also compared the sizes of design storm events and the frequency and severity of drought to demonstrate the consequences of GCM selection. The results show that rainfall and extreme hydrological event projections could significantly vary depending on climate model selection and weather stations, suggesting the need for a careful and comprehensive evaluation of GCM in the hydrological analysis of climate change. The proposed methods are expected to help to improve the accuracy of future hydrological projections for water resources planning.

Particle-attached riverine bacteriome shifts in a pollutant-resistant and pathogenic community during a Mediterranean extreme storm event

Rivers are representative of the overall contamination found in their catchment area. Contaminant concentrations in watercourses depend on numerous factors including land use and rainfall events. Globally, in Mediterranean regions, rainstorms are at the origin of fluvial multipollution phenomena as a result of Combined Sewer Overflows (CSOs) and floods. Large loads of urban-associated microorganisms, including faecal bacteria, are released from CSOs which place public health – as well as ecosystems – at risk. The impacts of freshwater contamination on river ecosystems have not yet been adequately addressed, as is the case for the release of pollutant mixtures linked to extreme weather events. In this context, microbial communities provide critical ecosystem services as they are the only biological compartment capable of degrading or transforming pollutants. Through the use of 16S rRNA gene metabarcoding of environmental DNA at different seasons and during a flood event in a typical Mediterranean coastal river, we show that the impacts of multipollution phenomena on structural shifts in the particle-attached riverine bacteriome were greater than those of seasonality. Key players were identified via multivariate statistical modelling combined with network module eigengene analysis. These included species highly resistant to pollutants as well as pathogens. Their rapid response to contaminant mixtures makes them ideal candidates as potential early biosignatures of multipollution stress. Multiple resistance gene transfer is likely enhanced with drastic consequences for the environment and human-health, particularly in a scenario of intensification of extreme hydrological events.

Governing complexity and environmental justice: lessons from the water crisis in Metropolitan São Paulo (2013-2015)

The paper presents a discussion on the water crisis that occurred between 2013 and 2015 in the Metropolitan Region of São Paulo, the lack of integrated natural resources planning, and the reaction of social actors affected by the crisis. The region was affected by an extreme hydrological and climatological event, which was combined with the unsustainable management of water resources. The paper addresses, initially, the dynamics of water governance in the region, and the main aspects related to water availability and climate dependence that caused the water crisis. Then, we present an analysis of the process that led to the water crisis and its main developments, which is based on the follow-up of the different moments of the crisis and dialogues with its relevant stakeholders. The results indicate the relevance of emphasizing issues on matters such as the lack of transparency and highlight the role of societal initiatives. We conclude the paper with a proposition to discuss governance processes that can contribute to the development of more effective initiatives in order to reduce the impact of this visible change in water regimes, strengthen transparent management, and promote a more democratic interaction between social actors and the government.

Flow regimes control the establishment of invasive crayfish and alter their effects on lotic macroinvertebrate communities

Abstract Invasive non‐native species (INNS) threaten biodiversity and ecosystem functioning globally. However, there remains a pressing need to understand the environmental factors controlling the dispersal, successful establishment and subsequent ecological impacts of INNS for receiving ecosystems. Here, we examine how region‐wide flow regime magnitudes facilitate the successful establishment of an invasive crayfish species (Pacifastacus leniusculus, signal crayfish) in England (UK). We also consider the interactive effects of invasive crayfish with flow regime variations on the structural and functional diversity of macroinvertebrate communities. Low‐flow magnitudes increased the likelihood of P. leniusculus establishment, with 80% of recorded invasion dates falling in years with flow magnitudes below average (low‐ and low‐moderate flow classes), whilst only 1.6% occurred in high‐flow years. Temporal trajectories of structural and functional macroinvertebrate responses in invaded rivers demonstrated reduced diversity compared to control rivers. Lower taxonomic and functional richness measures typically coincided with periods of low discharge in invaded rivers and were greatest during regionally high‐flows. Macroinvertebrate communities displayed significant structural and functional responses to the interaction between invasive crayfish and flow regime variations. Specifically, a number of low‐ and high‐flow indices yielded significant associations, highlighting the role of extreme hydrological events in shaping INNS effects on receiving ecosystems. We also detected greater ecological effects of invasive crayfish under hydrologically stable conditions. Importantly, and for the first time, we observed that invasive crayfish reversed macroinvertebrate community responses to flow regime cues (e.g. discharge fall rate and minimum flows in the preceding 180 days). Synthesis and applications. Results from this study indicate that low‐flow events facilitate the spread/establishment of invasive crayfish and correspond with greater ecological effects for receiving ecosystems. Given that low‐flow events are predicted to increase in intensity, duration and frequency over the 21st century, our results highlight the potential threat that invasive crayfish may pose under future hydroclimatic changes. Managing river flow regimes effectively (including maintaining higher flow events and flow variability) is likely to be vital in conserving ecological diversity following crayfish invasion.

An approach for flood assessment by numerical modeling of extreme hydrological events in the Zat watershed (High Atlas, Morocco)

ABSTRACT Arid and semi-arid areas are often subject to sudden and flash floods, causing extended damages to the population and infrastructures. This paper presents a method for flood assessment in the Zat watershed (sub basin of the Tensift catchment) via 10-minute numerical modeling using the HEC-HMS numerical model. To illustrate the calibration and the validation process four flood events recorded during (2011-2014) were used and two different validation methods were adopted. The comparative analysis of simulation results obtained during the calibration and validation showed a good compliance with measured data. A Nash-Sutcliff of 82.38% on average over the four events, and an R2 of 0.65 are considered as satisfactory results for the correlation between the initial soil moisture conditions and the Curve Number. As part of the future steps, this approach could be extrapolated to other watersheds with similar contexts, both in Morocco and in other Mediterranean regions

Reconstruction of Late Holocene Extreme Hydrological Events of the Valentin Bay Coast, the Sea of Japan

Reconstruction of Late Holocene Extreme Hydrological Events of the Valentin Bay Coast, the Sea of Japan

A Vision for Hydrological Prediction

IMproving PRedictions and management of hydrological EXtremes (IMPREX) was a European Union Horizon 2020 project that ran from September 2015 to September 2019. IMPREX aimed to improve society’s ability to anticipate and respond to future extreme hydrological events in Europe across a variety of uses in the water-related sectors (flood forecasting, drought risk assessment, agriculture, navigation, hydropower and water supply utilities). Through the engagement with stakeholders and continuous feedback between model outputs and water applications, progress was achieved in better understanding the way hydrological predictions can be useful to (and operationally incorporated into) problem-solving in the water sector. The work and discussions carried out during the project nurtured further reflections toward a common vision for hydrological prediction. In this article, we summarized the main findings of the IMPREX project within a broader overview of hydrological prediction, providing a vision for improving such predictions. In so doing, we first presented a synopsis of hydrological and weather forecasting, with a focus on medium-range to seasonal scales of prediction for increased preparedness. Second, the lessons learned from IMPREX were discussed. The key findings were the gaps highlighted in the global observing system of the hydrological cycle, the degree of accuracy of hydrological models and the techniques of post-processing to correct biases, the origin of seasonal hydrological skill in Europe and user requirements of hydrometeorological forecasts to ensure their appropriate use in decision-making models and practices. Last, a vision for how to improve these forecast systems/products in the future was expounded, including advancing numerical weather and hydrological models, improved earth monitoring and more frequent interaction between forecasters and users to tailor the forecasts to applications. We conclude that if these improvements can be implemented in the coming years, earth system and hydrological modelling will become more skillful, thus leading to socioeconomic benefits for the citizens of Europe and beyond.

Uncertainty quantification and propagation in bivariate design flood estimation using a Bayesian information-theoretic approach

Copula-based statistical model has been extensively used to characterize the joint probability behaviors of extreme hydro-climatic design events, such as bivariate design floods. However, parameter uncertainty, not desirably but inevitably, accompanies the copula-based design flood estimation (CDFE) model which makes the inference results of design flood ambiguous. In this paper, we develop a Bayesian information-theoretic (BIT) approach to disclose design flood uncertainty arising from parameter uncertainty in CDFE model and furthermore examine how the parameter uncertainty is propagated to design flood estimation. Two catchments located in the Yellow River Basin, China, are selected as study regions. The research we have done indicates that design flood uncertainty is considerably large under parameter uncertainty. Worse still, the uncertainty in design flood increases along with the return period, thus making the design flood inference more ambiguous. Specifically, shape and scale parameters of marginal distributions have the largest contribution to the design flood uncertainty, followed by copula parameter, finally the location parameter of marginal distribution. Furthermore, the interaction between some parameters has dominant effect on design flood uncertainty compared with the individual effect of these parameters. These findings will enable better understanding the design flood uncertainty under parameter uncertainty. Moreover, the proposed BIT approach also offers a promising technical reference for design estimation of other types of extreme hydrological events, not limited to the design flood.

Tree-ring based, regional-scale reconstruction of flash floods in Mediterranean mountain torrents

In small mountain catchments of the Mediterranean basin, heavy and intense rainfalls produce frequent flash floods that can cause economic damage and even fatalities in the often densely populated valley areas. To reduce future damage of such events, the application of mitigation strategies aimed at hydrological control and disaster risk reduction is essential. However, to reach this goal, flash flood frequency and magnitude need to be characterized in space and time. This task is highly challenging in areas where existing records are either lacking, short or highly incomplete. In poorly or completely ungauged catchments, tree-ring based flash flood reconstruction has proven useful to overcome this limitation and is now considered a valuable, alternative approach to extend flow records back in time. Tree-ring based reconstructions of past flash floods have been employed widely in many different geographic contexts worldwide, but were less frequently used in Mediterranean torrents, and not at all in Southern Italy so far. Here, we present a regional flash flood reconstruction from five poorly gauged mountain catchments in Calabria (southern Italy) to reconstruct both the timing and the magnitude of five extreme flash flood events of the last 60 years. We show that the return periods of these events ranged between 5 and 30 years based on hydraulic (Manning’s equation) and hydrological (rational formula) approaches. Validation of the reconstructed discharge values was done by using direct water depth measurements (obtained from a gauging station). Our results suggest that the combination of different methods allows a reliable reconstruction of extreme hydrological events by easy-to-survey parameters in ungauged torrents of Mediterranean environments. We also demonstrate that tree-ring approaches have the potential to be applied in ungauged (or poorly gauged) Mediterranean mountain catchments as well so as to improve records of the frequency and magnitude of past flash flood activity.

Spatiotemporal Relationships of Phytoplankton Blooms, Drought, and Rainstorms in Freshwater Reservoirs

Algal blooms, especially those composed of toxic phytoplankton, are a global threat to eutrophic and mesotrophic freshwater reservoirs. While extreme hydrologic events such as flooding and drought have been shown to control bloom onset and success, the spatiotemporal dynamics of these relationships are still unclear for mesotrophic reservoirs. In this study, the relationships between hydrologic events and phytoplankton in Lake Allatoona and Lake Lanier, Georgia, United States, were characterized using historical and satellite datasets from 2008 to 2017 and statistical modeling. Results showed that the impact of stormflow and rainstorm events varied systematically from riverine to lacustrine reaches of the two reservoirs on weekly and monthly scales. Precipitation duration and stormflow were the most significant and best-fitting predictors of algal bloom biomass in deeper reaches of the two reservoirs, suggesting that algal blooms in more lacustrine environments may be better equipped for wet and stormy regimes than has been previously hypothesized.

Satellite Gravimetry Improves Seasonal Streamflow Forecast Initialization in Africa

AbstractWest Africa is one of the poorest regions in the world and highly vulnerable to extreme hydrological events due to the lack of reliable monitoring and forecast systems. For the first time, we demonstrate that initial hydrological conditions informed by satellite‐based terrestrial water storage (TWS) estimates improve seasonal streamflow forecasts. TWS variability detected by the Gravity Recovery and Climate Experiment (GRACE) satellites is assimilated into a land surface model during 2003–2016 and used to initialize 6‐month hindcasts (i.e., forecasts of past events) during West Africa's wet seasons. We find that GRACE data assimilation (DA) generally increases groundwater and soil moisture storage in the region, resulting in increased evapotranspiration and reduced total runoff. Total runoff is particularly lower at the headwaters of the Niger River, positively impacting streamflow simulations and hindcast initializations. Compared to simulations without GRACE‐DA, hindcasts are notably improved at locations draining from large basin areas, in particular, over the Niger River basin, which is consistent with GRACE's coarse spatial resolution. The long memory of groundwater and deep soil moisture, two main TWS components updated by GRACE‐DA, is reflected in prolonged improvements in the streamflow hindcasts. Model accuracy at Niamey, Niger, the most populated city where streamflow observations are available, improved up to 33% during the flood season. These new findings directly contribute to ongoing developments in food security, flood potential forecast, and water‐related disaster warning systems for Africa.

Water Tracks Enhance Water Flow Above Permafrost in Upland Arctic Alaska Hillslopes

AbstractUpland permafrost regions occupy approximately one third of the Arctic landscape. In upland regions, hydrologic fluxes are influenced by water tracks, curvilinear features on hillslopes that preferentially fill with and route water in response to snowmelt and rainfall when the soil above continuous permafrost thaws in the summer. As continued warming of the Arctic may alter hydrologic cycling leading to increased frequency of extreme hydrologic events like drought and flooding as well as modification of biogeochemical cycling, it is imperative to untangle the interplay between precipitation, runoff, and subsurface flow as water is routed from upland Arctic regions to the Arctic Ocean. This study quantifies how ground surface temperatures affect groundwater discharge from hillslopes with water tracks in the upland Arctic by employing a three‐dimensional, physically based subsurface flow model with variable saturation and freeze and thaw capabilities that is calibrated to field measurements from the Upper Kuparuk River watershed on the North Slope of Alaska, USA. Model analysis indicates that higher ground surface temperatures along water track hillslopes promote increases in groundwater discharge where water tracks act as conduits for large‐recharge events and continue to discharge groundwater into the autumn after the adjacent hillslope has frozen. Simulating the conditions that distinguish water tracks from their hillslope watersheds changes subsurface water storage and ground thermal responses but does not alter the total magnitude of groundwater discharge outside of parameter uncertainty. These findings suggest that water tracks play a complex and critical role in hydrologic cycles of the upland Arctic.