Identifying regional hotspots of heatwaves, droughts, floods, and their co-occurrences DOI Creative Commons
Marlon Vieira Passos,

Jung-Ching Kan,

Georgia Destouni

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: 38(10), P. 3875 - 3893

Published: July 30, 2024

Abstract In this paper we present a framework to aid in the selection of optimal environmental indicators for detecting and mapping extreme events analyzing trends heatwaves, meteorological hydrological droughts, floods, their compound occurrence. The uses temperature, precipitation, river discharge, derived climate indices characterize spatial distribution hazard intensity, frequency, duration, co-occurrence, dependence. relevant applied are Standardized Precipitation Index, Evapotranspiration Index (SPEI), Streamflow heatwave based on fixed (HWI $$_\textrm{S}$$ S ) anomalous temperatures $$_\textrm{E}$$ E ), Daily Flood (DFI). We selected suitable corresponding thresholds each estimated event detection performance using receiver operating characteristics (ROC), area under curve (AUC), accuracy, which is defined as proportion correct detections. assessed dependence Likelihood Multiplication Factor (LMF). tested case Sweden, daily data period 1922–2021. ROC results showed that HWI , SPEI12 DFI representing respectively (AUC > 0.83). Application these revealed increasing flood occurrence large areas but no significant change trend droughts. Hotspots with LMF 1, mostly concentrated Northern Sweden from June August, indicated drought-heatwave drought-flood positively correlated those areas, can exacerbate impacts. novel presented here adds existing hydroclimatic research by (1) local historical records extremes validate indicator-based hotspots, (2) evaluating hazards at regional scale, (3) being transferable streamlined, (4) attaining satisfactory demonstrated method, (5) generalizable various types.

Language: Английский

CAMELS-IND: hydrometeorological time series and catchment attributes for 228 catchments in Peninsular India DOI Creative Commons
Nikunj K. Mangukiya, Kanneganti Bhargav Kumar, Pankaj Dey

et al.

Earth system science data, Journal Year: 2025, Volume and Issue: 17(2), P. 461 - 491

Published: Feb. 5, 2025

Abstract. We introduce CAMELS-IND (Catchment Attributes and MEteorology for Large-sample Studies – India), a dataset containing hydrometeorological time series catchment attributes 472 catchments in Peninsular India, of which 228 have observed streamflow data available over 30 % the period between 1980 to 2020. India covers 15 interstate river basins defined by Central Water Commission (CWC), where flow water level datasets are several gauge stations through open-source Resources Information System (India-WRIS). However, many these lack reliable metadata, not an analysis-ready format large-sample hydrological studies. Therefore, we utilized their boundaries, characterized as with from Geospatial hydrologic analyses (GHI) (Goteti, 2023). For each catchments, provides mean meteorological forcings 41 years (1980–2020) 211 representing hydroclimatic land cover characteristics extracted multiple sources (including ground-based observations, remote sensing-based products, reanalyses datasets). follows same standards previously developed CAMELS USA, Chile, Brazil, Great Britain, Australia, Switzerland, Germany facilitate comparisons those countries inclusion global Notably, includes 19 forcings, including precipitation, maximum, minimum, average temperature, long-wave short-wave radiation flux, U V components wind, relative humidity, evaporation rates canopy soil surface, actual potential evapotranspiration, moisture four layers (covering depth up 3 m below ground) detailed also derived human influences, number dams utilization, total volume contents population density, increases urban agricultural studies understand influences on hydrology. Furthermore, predicted regionally trained long short-term memory (LSTM)-based model all can fill gaps or serve benchmark testing developing new models. envision that will provide strong foundation community-led effort toward gaining insights hydrologically distinct Indian solving pertinent issues related management, quantification risk assessment extremes, unraveling regional-scale functioning, climate change impact across India. The is at https://doi.org/10.5281/zenodo.14005378 (Mangukiya et al., 2024).

Language: Английский

Citations

1
ML4FF: A machine-learning framework for flash flood forecasting applied to a Brazilian watershed DOI
Jaqueline A. J. P. Soares, Luan Carlos de Sena Monteiro Ozelim, Luiz Bacelar

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 132674 - 132674

Published: Jan. 1, 2025

Language: Английский

Citations

0
Enhancing daily runoff prediction: A hybrid model combining GR6J-CemaNeige with wavelet-based gradient boosting technique DOI
Babak Mohammadi, Mingjie Chen, Mohammad Reza Nikoo

et al.

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133114 - 133114

Published: March 1, 2025

Language: Английский

Citations

0
Controls From Above and Below: Snow, Soil, and Steepness Drive Diverging Trends of Subsurface Water and Streamflow Dynamics DOI Creative Commons
Devon Kerins, Abigail S. Knapp,

Fiona S. Liu

et al.

Hydrological Processes, Journal Year: 2025, Volume and Issue: 39(4)

Published: April 1, 2025

ABSTRACT The importance of subsurface water dynamics, such as storage and flow partitioning, is well recognised. Yet, our understanding their drivers links to streamflow generation has remained elusive, especially in small headwater streams that are often data‐limited but crucial for downstream quantity quality. Large‐scale analyses have focused on characteristics across rivers with varying drainage areas, overlooking the dynamics shape behaviour. Here we ask question: What climate landscape regulate dynamic storage, path streams? To answer this question, used data a widely‐used hydrological model (HBV) 15 catchments contiguous United States. Results show aridity precipitation phase (snow or rain) land attributes topography soil texture key dynamics. In particular, steeper slopes generally promoted more streamflow, regardless aridity. Streams flat, rainy sites (< 30% snow) finer soils exhibited flashier regimes than those snowy (> coarse deeper paths. sites, less weathered, thinner shallower paths discharge was sensitive changes snow dampened flashiness overall. here indicate steepness modify shallow deep ultimately regulating response forcing. As change increases uncertainty availability, interacting features will be essential predict shifts improve resources management.

Language: Английский

Citations

0
A short history of philosophies of hydrological model evaluation and hypothesis testing DOI Creative Commons
Keith Beven

Wiley Interdisciplinary Reviews Water, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 3, 2024

Abstract This historical review addresses the issues of evaluation and testing hydrological models, with a focus on rainfall–runoff models. After discussion general philosophies modeling, nine different model are considered, focusing period modeling digital computers since 1960s. In addition, some discursions to discuss definitions calibration validation, how much data is needed for calibration, equifinality uncertainty, probabilities possibilities, ensembles, benchmarking. The paper finishes final discursion philosophical problem induction. article categorized under: Science Water > Methods Hydrological Processes

Language: Английский

Citations

2
Identifying regional hotspots of heatwaves, droughts, floods, and their co-occurrences DOI Creative Commons
Marlon Vieira Passos,

Jung-Ching Kan,

Georgia Destouni

et al.

Stochastic Environmental Research and Risk Assessment, Journal Year: 2024, Volume and Issue: 38(10), P. 3875 - 3893

Published: July 30, 2024

Abstract In this paper we present a framework to aid in the selection of optimal environmental indicators for detecting and mapping extreme events analyzing trends heatwaves, meteorological hydrological droughts, floods, their compound occurrence. The uses temperature, precipitation, river discharge, derived climate indices characterize spatial distribution hazard intensity, frequency, duration, co-occurrence, dependence. relevant applied are Standardized Precipitation Index, Evapotranspiration Index (SPEI), Streamflow heatwave based on fixed (HWI $$_\textrm{S}$$ S ) anomalous temperatures $$_\textrm{E}$$ E ), Daily Flood (DFI). We selected suitable corresponding thresholds each estimated event detection performance using receiver operating characteristics (ROC), area under curve (AUC), accuracy, which is defined as proportion correct detections. assessed dependence Likelihood Multiplication Factor (LMF). tested case Sweden, daily data period 1922–2021. ROC results showed that HWI , SPEI12 DFI representing respectively (AUC > 0.83). Application these revealed increasing flood occurrence large areas but no significant change trend droughts. Hotspots with LMF 1, mostly concentrated Northern Sweden from June August, indicated drought-heatwave drought-flood positively correlated those areas, can exacerbate impacts. novel presented here adds existing hydroclimatic research by (1) local historical records extremes validate indicator-based hotspots, (2) evaluating hazards at regional scale, (3) being transferable streamlined, (4) attaining satisfactory demonstrated method, (5) generalizable various types.

Language: Английский

Citations

0