Advancing Hydrology through Machine Learning: Insights, Challenges, and Future Directions Using the CAMELS, Caravan, GRDC, CHIRPS, PERSIANN, NLDAS, GLDAS, and GRACE Datasets

Water, Journal Year: 2024, Volume and Issue: 16(13), P. 1904 - 1904

Published: July 3, 2024

Machine learning (ML) applications in hydrology are revolutionizing our understanding and prediction of hydrological processes, driven by advancements artificial intelligence the availability large, high-quality datasets. This review explores current state ML hydrology, emphasizing utilization extensive datasets such as CAMELS, Caravan, GRDC, CHIRPS, NLDAS, GLDAS, PERSIANN, GRACE. These provide critical data for modeling various parameters, including streamflow, precipitation, groundwater levels, flood frequency, particularly data-scarce regions. We discuss type methods used significant successes achieved through those models, highlighting their enhanced predictive accuracy integration diverse sources. The also addresses challenges inherent applications, heterogeneity, spatial temporal inconsistencies, issues regarding downscaling LSH, need incorporating human activities. In addition to discussing limitations, this article highlights benefits utilizing high-resolution compared traditional ones. Additionally, we examine emerging trends future directions, real-time quantification uncertainties improve model reliability. place a strong emphasis on citizen science IoT collection hydrology. By synthesizing latest research, paper aims guide efforts leveraging large techniques advance enhance water resource management practices.

Language: Английский

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Flood Frequency Analysis in West Africa

Journal of Flood Risk Management, Journal Year: 2025, Volume and Issue: 18(1)

Published: Jan. 17, 2025

ABSTRACT Devastating flood events are recurrently impacting West Africa. To mitigate impacts and reduce the vulnerability of populations, a better knowledge on frequency these is crucial. The lack reliable hydrometric datasets has hitherto been major limitation in analysis at scale Utilising recently developed African database, we perform annual maximum flow (AMF) time series, covering 246 river basins Africa, between 1975 2018. Generalized extreme value (GEV) Gumbel probability distributions were compared to fit AMF series with L‐moments, Maximum Likelihood (MLE) (GMLE) methods. Results indicated that GEV distribution GMLE method provided best results. Regional envelope curves entire region unprecedented data coverage have generated for first‐time providing insights estimation quantiles ungauged basins. correlation watershed properties shows significant correlations catchment area, groundwater storage, altitude topographic wetness index. findings from this study useful risk assessment design hydraulic infrastructures region, first step prior development regional approaches transfer information gauged sites catchments.

Language: Английский

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Shifted dominant flood drivers of an alpine glacierized catchment in the Tianshan region revealed through interpretable deep learning

npj Climate and Atmospheric Science, Journal Year: 2025, Volume and Issue: 8(1)

Published: Jan. 25, 2025

Language: Английский

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River flooding mechanisms and their changes in Europe revealed by explainable machine learning

Hydrology and earth system sciences, Journal Year: 2022, Volume and Issue: 26(24), P. 6339 - 6359

Published: Dec. 16, 2022

Abstract. Climate change may systematically impact hydrometeorological processes and their interactions, resulting in changes flooding mechanisms. Identifying such is important for flood forecasting projection. Currently, there a lack of observational evidence regarding trends mechanisms Europe, which requires reliable methods to disentangle emerging patterns from the complex interactions between drivers. Recently, numerous studies have demonstrated skill machine learning (ML) predictions hydrology, e.g., predicting river discharge based on its relationship with meteorological The relationship, if explained properly, provide us new insights into hydrological processes. Here, by using novel explainable ML framework, combined cluster analysis, we identify three primary that drive 53 968 annual maximum events around thousand European catchments. can be associated catchment-wide mechanisms: recent precipitation, antecedent precipitation (i.e., excessive soil moisture), snowmelt. results indicate over half studied catchments are controlled combination above mechanisms, especially moisture, dominant mechanism one-third Over past 70 years, significant been detected within number Generally, snowmelt-induced floods has decreased significantly, whereas driven increased. consistent expected climate responses, highlight risks seasonality magnitude. Overall, study offers perspective understanding weather extreme demonstrates prospect future scientific discoveries supported artificial intelligence.

Language: Английский

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Long-term variability in hydrological droughts and floods in sub-Saharan Africa: New perspectives from a 65-year daily streamflow dataset

Journal of Hydrology, Journal Year: 2022, Volume and Issue: 613, P. 128359 - 128359

Published: Aug. 22, 2022

Understanding hydrological variability is of crucial importance for water resource management in sub-Saharan Africa (SSA). While existing studies typically focus on individual river basins, and suffer from incomplete records, this study provides a new perspective trends flood drought characteristics (frequency, duration, intensity) across the entire SSA. This achieved by: i) creating 65-year long, complete daily streamflow dataset consisting over 600 gauging stations; ii) quantifying changes between 1950 2014; iii) evaluating how decadal influences historical trends. Results reconstructions using random forests provide satisfactory performance most SSA, except parts southern Africa. Using change-point trend analyses, we identify-three periods that characterise variations affecting extremes western central Africa, some Africa: 1950s–60s after 1980s–90s, when floods (droughts) tend to be more (less) intense, frequent persistent; 1970s–80s, are less (more) persistent. Finally, reveal significant all characteristics, which explain aperiodic increasing decreasing stresses considering multiple time-periods analysing recent trends, as previous assessments may have been unrepresentative long-term changes.

Language: Английский

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Varying Importance of Storm Types and Antecedent Conditions for Local and Regional Floods

Water Resources Research, Journal Year: 2022, Volume and Issue: 58(12)

Published: Dec. 1, 2022

Abstract Local and potentially more impactful regional floods are driven by a combination of precipitation‐triggering storms antecedent conditions. However, it is yet unclear how the importance these flood drivers their interplay differs between local events. Therefore, we assess differences in compounding United States using newly developed classification schemes for storm types Our results show that dominant type triggering frontal events, particular those related to mesoscale convective systems. The different varies season, with systems being most important summer, nonfrontal, extratropical cyclone‐related winter spring, tropical cyclones fall. comparison events shows relative only weakly floods, while conditions clearly distinct. Regional 75% cases wet some combined snowmelt, likely also develop under dry Over all regions seasons, often result conditions, which highlights role drivers. This finding suggests risk change assessments should account nature atmospheric land‐surface

Language: Английский

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Spatiotemporal variation in global floods with different affected areas and the contribution of influencing factors to flood-induced mortality (1985–2019)

Natural Hazards, Journal Year: 2022, Volume and Issue: 111(3), P. 2601 - 2625

Published: Jan. 1, 2022

Abstract Floods are great threats to human life and property. Extensive research has investigated the spatiotemporal variation in flood occurrence, while few have studied heterogeneity global events of different sizes, which may require coping strategies risk reduction policies. In this study, we analysed patterns with affected areas (classified three levels) during 1985–2019 examined contribution influencing factors flood-induced mortality using Geodetector. The results show that (1) increase frequency was mainly caused by Level II III floods, average area been increasing yearly since 1985. (2) America Africa, floods increased monotonically. At same time, I Europe Asia significantly. (3) For Asia, most deaths occurred floods; for mortality. (4) top contributing spatial were population, GDP per capita duration. each factor varied among types floods. Topographic (percentage mountainous area) magnified extreme heavy rainfall, especially indicates protection measures should be more targeted. addition, large-scale (Level III) highlights need transregional cooperation management.

Language: Английский

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Changes in Mediterranean flood processes and seasonality

Hydrology and earth system sciences, Journal Year: 2023, Volume and Issue: 27(15), P. 2973 - 2987

Published: Aug. 11, 2023

Abstract. Floods are a major natural hazard in the Mediterranean region, causing deaths and extensive damages. Recent studies have shown that intense rainfall events becoming more extreme this region but, paradoxically, without leading to an increase severity of floods. Consequently, it is important understand how flood changing explain absence trends magnitude despite increased extremes. A database 98 stations southern France with average record 50 years daily river discharge data between 1959 2021 was considered, together high-resolution reanalysis product providing precipitation simulated soil moisture classification weather patterns associated over France. Flood events, corresponding occurrence 1 event per year (5317 total), were extracted classified into excess-rainfall, short-rainfall, long-rainfall types. Several characteristics been also analyzed: durations, base flow contribution floods, runoff coefficient, total maximum rainfall, antecedent moisture. The evolution through time these seasonality analyzed. Results indicated that, most basins, floods tend occur earlier during year, mean date being, on average, advanced by month 1959–1990 1991–2021. This seasonal shift could be attributed frequency southern-circulation types spring summer. An extreme-event has observed, decrease before events. majority excess saturated soils, but their relative proportion decreasing time, notably spring, concurrent short rain For basins there positive correlation coefficients remaining stable dryer soils producing less lower In context increasing aridity, relationship likely cause magnitudes observed change These changes quite homogeneous domain studied, suggesting they rather linked regional climate than catchment characteristics. study shows even trends, properties may need accounted for when analyzing long-term hazards.

Language: Английский

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Controls on the Spatial and Temporal Patterns of Rainfall‐Runoff Event Characteristics—A Large Sample of Catchments Across Great Britain

Water Resources Research, Journal Year: 2023, Volume and Issue: 59(6)

Published: May 22, 2023

Abstract This study reveals the spatiotemporal variability of event characteristics and their controls from 290,743 rainfall‐runoff events across 431 Great Britain catchments. Metrics characterizing runoff coefficient, timescale normalized peak discharge mean, seasonality statistics are extracted to quantify characteristics. Using random forest models, we find climate attributes most influential in controlling spatial pattern, with land cover, geology soil properties also playing a critical role especially for explaining response. Rainfall (particularly rainfall depth) exhibit dominant on temporal dynamic at scale, while catchment initial state (antecedent moisture) determines its seasonal variations. Clear regional patterns observed Britain, influences anthropogenic activities local differences detected. Extremely low coefficient values (<0.05) but high typical Chalk catchments Southeast region. Flashy short (<10 hr) less response urban A large reservoir close gauge leads reduction flows, yet deviation is relatively small summer. The impact surface water abstractions not obvious our data set, whereas groundwater largely reflects geology. provides basis regionalization studies by revealing (dis)similarities emphasizes need further research into human

Language: Английский

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Spatial Sensitivity of River Flooding to Changes in Climate and Land Cover Through Explainable AI

Earth s Future, Journal Year: 2024, Volume and Issue: 12(5)

Published: April 30, 2024

Abstract Explaining the spatially variable impacts of flood‐generating mechanisms is a longstanding challenge in hydrology, with increasing and decreasing temporal flood trends often found close regional proximity. Here, we develop machine learning‐informed approach to unravel drivers seasonal magnitude explain spatial variability their effects temperate climate. We employ 11 observed meteorological land cover (LC) time series variables alongside 8 static catchment attributes model 1,268 catchments across Great Britain over four decades. then perform sensitivity analysis assess how 10% increase precipitation, 1°C rise air temperature, or 10 percentage point urban forest LC may affect varying characteristics. Our simulations show that precipitation urbanization both tend amplify significantly more high baseflow contribution low runoff ratio, which have lower values specific discharge on average. In contrast, rising temperature (in absence changing precipitation) decreases magnitudes, largest dry index. Afforestation also tends decrease floods groundwater contribution, summer. be used further disentangle joint multiple individual catchments.

Language: Английский

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