Rising Temperatures Drive Lower Summer Minimum Flows Across Hydrologically Diverse Catchments in British Columbia

Water Resources Research, Journal Year: 2025, Volume and Issue: 61(2)

Published: Feb. 1, 2025

Abstract Excessively low stream flows harm ecosystems and societies, so two key goals of low‐flow hydrology are to understand their drivers predict severity frequency. We show that linear regressions can accomplish both across diverse catchments. analyze 230 unregulated moderate high relief catchments rainfall‐dominated, hybrid, snowmelt‐dominated, glacial regimes in British Columbia, Canada, with drainage areas spanning 5 orders magnitude from 0.5 55,000 km 2 . Summer decreasing rainfall‐dominated hybrid but have been stable remain snowmelt or glacial‐dominated. However, we find since 1950 approximately one third snowmelt‐dominated transitioned a rain‐snow regime. The declines dominantly driven by summer precipitation temperature, only weakly influenced winter storage. apply this understanding create regression models the minimum flow using monthly temperature data. These outperform distributed process‐based for every common goodness‐of‐fit metric; performance improvement is mostly result abandoning requirement simulate all parts annual hydrograph. Using these reconstruct streamflow droughts anomalies 1901 2022. reproduce recent drying trends catchments, also present conditions comparable those seen hundred years ago. anomalously last century were caused large deficits while current rising temperatures despite near‐normal precipitation.

Language: Английский

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Conceptual approach for a holistic low‐flow risk analysis

Hydrological Processes, Journal Year: 2024, Volume and Issue: 38(6)

Published: June 1, 2024

Abstract Low‐flow events, characterized by a significant water deficiency in river systems, have profound impacts on various users and ecology. Recent low‐flow events Europe had severe economic ecological consequences such as disruptions to hydropower production, irrigation bans, constraints navigation complete drying. These highlight the urgent need for effective risk management demand holistic analysis basis. The existing approaches often focus hydrological aspects, utilizing indices Standardized Runoff Index (SRI) or . However, these lack information regarding impacts. Other consider parts of approach but special economy; general, no assessment is made. This study introduces conceptual analysis. provides continuous long‐term simulation capture behaviour therefore avoids complex definition scenarios. In this approach, analysed using combination analyses that cover all aspects from occurrence consequences. Meteorological used generate synthetic weather data time series, which are transformed into runoff series Based results, hydrodynamic quantifies levels, temperatures, flow velocities along river. terms socio‐economic results represent damage values. Finally, values summed divided number years considered For testing demonstration purposes, presented partly applied proof‐of‐concept at Selke catchment, small catchment Germany. presented, evaluated, discussed.

Language: Английский

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Rising temperatures drive lower summer minimum flows across hydrologically diverse catchments

EarthArXiv (California Digital Library), Journal Year: 2024, Volume and Issue: unknown

Published: May 25, 2024

Excessively low stream flows harm ecosystems and societies, so two key goals of low-flow hydrology are to understand their drivers predict severity frequency. We show that simple linear regressions can accomplish both across diverse catchments. analyse 230 unregulated moderate high relief catchments rainfall-dominated, hybrid, snowmelt-dominated, glacial regimes in British Columbia, Canada, with drainage areas spanning 5 orders magnitude from 0.5 55,000 km2. find summer decreasing rainfall-dominated hybrid dominantly driven by precipitation temperature, only weakly influenced winter storage. apply this understanding create regression models the minimum flow using monthly temperature data. These outperform distributed process-based for every common goodness-of-fit metric; performance improvement is mostly a result abandoning requirement simulate all parts annual hydrograph. use these reconstruct streamflow droughts, environmental threshold transgressions, anomalies 1901-2022. reproduce recent drying trends catchments, but also present conditions comparable those seen almost one hundred years ago. However, anomalously last century were caused severe deficits while current declines being rising temperatures during period above-average precipitation.

Language: Английский

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Deep learning-based water quality index classification using stacked ensemble variational mode decomposition

Environmental Research Communications, Journal Year: 2024, Volume and Issue: 6(6), P. 065005 - 065005

Published: June 1, 2024

Abstract Water is crucial to human survival in general, and determining the WQI (water quality index) one of primary aspects. The existing water classification models are facing various challenges gaps that impeding their effectiveness. These include limited data availability, intricate nature systems, spatial temporal variability, non-linear relationships, sensor noise, error, interpretability, explainability. It imperative address these improve accuracy efficacy ensure they continue serve as reliable tools for monitoring safeguarding quality. To solve issues, this paper proposes a Stacked Ensemble efficient long short-term memory (StackEL) model an index classification. At first, raw input pre-processed rescale using normalization one-hot encoding. After that, process known variational mode decomposition (VMD) applied get at intrinsic functions (IMFs). Consequently, feature selection performed extended coati optimization (EX-CoA) algorithm select most significant attributes from selection. Here, publicly available datasets, namely dataset Kaggle, used perform effectively. further perfect proposed prediction model, Dwarf Mongoose (DMO) method implemented. Several measures effectiveness examined. When compared other models, suggested can achieve high 98.85% dataset.

Language: Английский

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Cataloging and Testing Flood Risk Management Measures to Increase the Resilience of Critical Infrastructure Networks

Smart Cities, Journal Year: 2024, Volume and Issue: 7(5), P. 2995 - 3021

Published: Oct. 16, 2024

Critical infrastructure (CI) networks face diverse natural hazards, such as flooding. CI network modeling methods are used to evaluate these enabling the analysis of cascading effects, flood risk, and potential risk-reducing measures. However, there is a lack linkage between analytical multisectoral, structural, nonstructural This deficiency impedes development (CIN) models robust tools for active risk management. operators have significant expertise in managing implementing flooding-related measures within their sectors. The objective this study bridge gap application CIN consideration three steps. first step conducting literature review stakeholder interviews Central Europe on second culmination findings comprehensive catalog detailing tailored five sectors, with generalized category spanning each phase disaster management cycle. third validation catalog’s utility proof-of-concept along Vicht River Western Germany model-based measure improves options available residual Additionally, approach presented here allows disruption duration recovery capability, thus linking concept resilience.

Language: Английский

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Evaluating the Teaching Effectiveness of Business English Courses in Colleges and Universities Based on the DPSIR Model

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract This paper takes the drive and pressure of teachers students in process English teaching as basis evaluation, focuses on state two influence well feedback teaching, constructs a framework for evaluating effectiveness business based model “Drive, Pressure, State, Influence, Response”. After rounds expert consultation, number evaluation indicators was reduced from 34 to 21. Finally, index system constructed by combining weight calculation hierarchical analysis method. The data show that A3 (state factors) > A1 (driving force A5 (response A2 (pressure A4 (influence factors), comprehensive score courses colleges universities is 3.5944, which indicates grade university located range between medium good. study aims promote digital innovation reform their effects.

Language: Английский

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