Leveraging a time-series event separation method to disentangle time-varying hydrologic controls on streamflow – application to wildfire-affected catchments

Hydrology and earth system sciences, Journal Year: 2025, Volume and Issue: 29(1), P. 27 - 43

Published: Jan. 3, 2025

Abstract. Increasing watershed disturbance regimes, such as from wildfire, are a growing concern for natural resource managers. However, the influence of disturbances on event-scale rainfall–runoff patterns has proved challenging to disentangle other hydrologic controls. To better isolate effects, this study evaluates several time-varying controls patterns, including water year type, seasonality, and antecedent precipitation. accomplish this, we developed Rainfall–Runoff Event Detection Identification (RREDI) toolkit, an automated time-series event separation attribution algorithm that overcomes limitations existing techniques. The RREDI toolkit was used generate dataset 5042 events nine western US watersheds. By analyzing large dataset, type season were identified significant whereas moisture pinpointed limited control. Specific effects wildfire runoff response then demonstrated two burned watersheds by first grouping based controls, wet versus dry types. role should be considered in future analysis increasing changing wildfires streamflow. could readily applied investigate patterns.

Language: Английский

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Monthly Runoff Prediction Via Mode Decomposition-Recombination Technique

Water Resources Management, Journal Year: 2023, Volume and Issue: 38(1), P. 269 - 286

Published: Dec. 1, 2023

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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When good signatures go bad: Applying hydrologic signatures in large sample studies

Hydrological Processes, Journal Year: 2023, Volume and Issue: 37(9)

Published: Sept. 1, 2023

Abstract Hydrologic signatures are quantitative metrics that describe streamflow statistics and dynamics. Signatures have many applications, including assessing habitat suitability hydrologic alteration, calibrating evaluating models, defining similarity between watersheds investigating watershed processes. Increasingly, being used in large sample studies to guide flow management modelling at continental scales. Using involving 1000s of brings new challenges as it becomes impractical examine signature parameters behaviour each watershed. For example, we might wish check describing flood event characteristics correctly identified periods, values not been biassed by data errors, or human natural influences on interpreted. In this commentary, draw from our collective experience present case where naïve application fails identify These include unusual precipitation regimes, quality issues, use human‐influenced watersheds. We conclude providing guidance recommendations applying studies.

Language: Английский

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Impacts of agriculture and snow dynamics on catchment water balance in the U.S. and Great Britain

Communications Earth & Environment, Journal Year: 2024, Volume and Issue: 5(1)

Published: Nov. 22, 2024

The Budyko water balance is a fundamental concept in hydrology that links aridity to how precipitation divided between evapotranspiration and streamflow. While the model powerful, its ability explain temporal changes influence of human activities climate change limited. Here we introduce causal discovery algorithm explore deviations from balance, attributing them interventions such as agricultural snow dynamics. Our analysis 1342 catchments across U.S. Great Britain reveals distinct patterns: U.S., fraction irrigation alter predominantly through aridity-streamflow relationships, while Britain, are primarily driven by precipitation-streamflow notable with high cropland percentage. By integrating enhance understanding dynamics affect offering insights for management sustainability Anthropocene. influenced irrigation, driving dynamics, according an 1,342 catchments.

Language: Английский

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A Framework for Analysing Multi‐Timescales Evolution Patterns in Precipitation–Streamflow Relationship

Hydrological Processes, Journal Year: 2025, Volume and Issue: 39(1)

Published: Jan. 1, 2025

ABSTRACT The precipitation–streamflow relationship (PSR) is one of the most crucial aspects hydrological process studies. Previous studies have analysed changes PSR at specific timescales (e.g., annual or seasonal), overlooking characteristics across multiple and that occur over time. This study presented an integrated framework to address these issues from three perspective: inconsistencies, response sensitivity streamflow precipitation oscillation periods. monthly data representative reaches located in upper middle sections Yellow River Basin 1961 2021. results indicate proposed effectively reveals evolving patterns PSR. evolution vary different time scales. Notably, inconsistencies variations are significant manifest differently various timescales. These differences were particularly pronounced when comparing periods before after 2000. varied among periods, examination resonant period variability revealed a shift strong‐to‐weak resonance within 32–64‐month period, followed by weak‐to‐strong transition 128‐month period. has significantly enhanced our understanding provided valuable insights for managing processes changing environment.

Language: Английский

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Hydrological signatures in Brazilian catchments: a machine learning approach for spatial estimates

Hydrological Sciences Journal, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

This study investigates the estimation of hydrological signatures in Brazilian catchments using physical attributes and machine learning algorithms. Using CABra's dataset with 735 catchments, we tested 163 regression techniques, including Random Forest, Gradient Boosting, Support Vector Regression (SVR). A key aspect was algorithmic approach, providing models topographic (area, elevation, slope), climatic (precipitation, evapotranspiration, aridity index), soil (silt, clay, organic content), land cover without assuming correlations. enabled to uncover complex patterns. Cross-validation (k-fold) showed most were satisfactorily predicted (R2 > 0.7), suggesting their application ungauged basins. Climatic factors, like precipitation, crucial for predicting signatures, especially high-flow, while silt content latitude influenced low-flow baseflow. Slope basin dynamics, influencing flashiness index, important low-flow. CatBoost best model. The SHapley Additive exPlanation (SHAP) analysis highlighted importance variables low linear correlation.

Language: Английский

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Agriculture’s impact on water–energy balance varies across climates

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(12)

Published: March 17, 2025

Agriculture is a cornerstone of global food production, accounting for substantial portion water withdrawals worldwide. As the world’s population grows, so does demand in agriculture, leading to alterations regional water–energy balances. We present an approach identify influence agriculture on balance using empirical data. explore departure from Budyko curve catchments with agricultural expansion and their associations changes causal discovery algorithm. Analyzing data 1,342 across three Köppen-Geiger climate classes—temperate, snowy, others—from 1980 2014, we show that temperate snowy catchments, which account over 90% stations, exhibit distinct patterns. Cropland percentage (CL%) emerges as dominant factor, explaining 47 37% variance deviations respectively. In CL% shows strong negative correlation precipitation-streamflow (P-Q) strength (Spearman ρ = − 0.75 ), suggesting cropland exacerbates precipitation-driven deviations. A moderate aridity-streamflow (AR-Q) ( 0.42 ) indicates additional influences through aridity-driven interactions. similarly influential, positive P-Q 0.51 ). However, AR-Q 0.45 underscores role aridity secondary driver. While vegetation precipitation seasonality also contribute deviations, impacts are comparatively lower. These findings underscore need inclusion activities changing secure future supplies.

Language: Английский

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The impact of rainfall on productivity: Implications for Chinese manufacturing

Journal of Comparative Economics, Journal Year: 2025, Volume and Issue: unknown

Published: April 1, 2025

Language: Английский

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Exploring controls on precipitation-runoff dependencies: Implications for non-stationary and spatially heterogeneous analyses

Journal of Hydrology, Journal Year: 2025, Volume and Issue: unknown, P. 133333 - 133333

Published: April 1, 2025

Language: Английский

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