Variable Streamflow Response to Forest Disturbance in the Western US: A Large‐Sample Hydrology Approach

Goeking, Sara A.; Tarboton, David G.

doi:10.1029/2021wr031575

Cited by 12 publications

(10 citation statements)

References 68 publications

(144 reference statements)

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“…The aridity index is used to describe the dry conditions within catchments, and the uneven spatiotemporal distribution of precipitation and leakage losses in the catchment cannot be accurately estimated, hindering the simulation of flooding in arid regions (Jahanshahi et al., 2022). LAI is a vegetation‐related indicator, which directly affects hydrological processes such as evapotranspiration and interception in a catchment (Goeking & Tarboton, 2022). Latitude is the fundamental factor affecting atmosphere circulation patterns, and the distribution of solar radiation on the Earth's surface decreases from the equator to the poles forming various climatic zones (Merz et al., 2021).…”

Section: Resultsmentioning

confidence: 99%

“…Inspired by the Köppen‐Geiger classification, we used physical descriptors of catchments to describe their hydrological similarities (Sawicz et al., 2011). The physical descriptors refer to 15 indicators related to topography, climate, vegetation and soil, all of which help identify the hydrological similarity of the catchments (Goeking & Tarboton, 2022; Jahanshahi et al., 2022; Merz et al., 2021). Global catchments are ranked by one of the above metrics and divided into 20 equal parts, while the median of NSE is calculated for each interval.…”

Section: Methodsmentioning

confidence: 99%

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Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins

Tang

Sun

Liu

et al. 2023

Water Resources Research

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Global hydrological stations are unevenly distributed, with sparse hydrometeorological observation networks in developing countries and dense ones in developed countries (Ma et al., 2021). Moreover, observations over some regions are not publicly available for policy reasons (Feng et al., 2021). Thus, PUB is challenging for the hydrological sciences (Tsai et al., 2021). World Bank statistics show that river monitoring networks cannot meet current needs in 78% of low-and middle-income countries and 86% of least-developed countries. Precise streamflow PUB is essential for both water management and policy decision-makers (Cho & Kim, 2022;Merz et al., 2021;Tellman et al., 2021).Traditional PUB primarily based on catchment hydrological similarity, whereby parameters are migrated from adjacent or similar catchments a regression function is constructed between physical descriptors of the catchment and model parameters for streamflow PUB (Guo et al., 2021). Bao et al. (2012) found that a similarity-based approach outperformed a regression-based approach in 55 catchments in China. Gou et al. (2021) successfully constructed a high-quality natural runoff dataset in China using a variable infiltration capacity (VIC) macroscale hydrologic model and multiscale parameter regionalization techniques. In recent years, the geophysical community has shown great interest in deep learning, with relevant research exploding exponentially in the society of exploration geophysics and the American Geophysical Union (X X Zhu et al., 2017). Long Short-Term Memory (LSTM) neural networks are widely used in hydrology, because of their excellent simulation performance and suitability for streamflow forecasting (

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins

Tang

Sun

Liu

et al. 2023

Water Resources Research

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“…Cumulative effects of fire on land surface hydrology are often associated with significantly enhanced streamflow (Williams et al., 2022) and reduced evapotranspiration (ET) (Ma et al., 2020; Maina and Siirila‐Woodburm, 2020). However, fire impacts on hydrology are heterogenous at the scale of individual catchments because fire‐induced changes to hydrologic processes depend on complex interactions among many factors including: burn area and severity, catchment size, human management (e.g., of reservoirs and forests), vegetation, soil type, meteorology, and topography (Atchley et al., 2018; Goeking & Tarboton, 2020, 2022; Niemeyer et al., 2020; Partington et al., 2022; Pugh & Gordon, 2013; Spence et al., 2020). Effects of fire on soil—increased bulk density by decreasing macropores, reduced infiltration capacity by sealing pore space with ash and sediment, and formation of a hydrophobic layer at the soil surface which tends to reduce hydraulic conductivity and sorptivity —are generally associated with higher runoff efficiency (the ratio of runoff ( Q ) to precipitation ( P ); that is, Q / P ), drier top soils, and wetter subsoils (Ebel, 2020; Ebel & Martin, 2017; Martin & Moody, 2001; Moody et al., 2008; Shakesby & Doerr, 2006; Stoof et al., 2012).…”

Section: Introductionmentioning

confidence: 99%

Evaluating Noah‐MP Simulated Runoff and Snowpack in Heavily Burned Pacific‐Northwest Snow‐Dominated Catchments

Abolafia‐Rosenzweig,

He,

Chen

et al. 2024

JGR Atmospheres

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Terrestrial hydrology is altered by fires, particularly in snow‐dominated catchments. However, fire impacts on catchment hydrology are often neglected from land surface model (LSM) simulations. Western U.S. wildfire activity has been increasing in recent decades and is projected to continue increasing over at least the next three decades, and thus it is important to evaluate if neglecting fire impacts in operational land surface models (LSMs) is a significant error source that has a noticeable signal among other sources of uncertainty. We evaluate a widely used state‐of‐the‐art LSM (Noah‐MP) in runoff and snowpack simulations at two representative fire‐affected snow‐dominated catchments in the Pacific Northwest: Andrew's Creek in Washington and Johnson Creek in Idaho. These two catchments are selected across all western U.S. fire‐affected catchments because they are snow‐dominated and experienced more than 50% burning in a single fire event with minimal burning outside of this event, which allows analyses of distinct pre‐ and post‐fire periods. There are statistically significant shifts in model skills from pre‐to post‐fire years in simulating runoff and snowpack. At both study catchments, simulations miss enhancements in early‐spring runoff and annual runoff efficiency during post‐fire years, resulting in persistent underestimates of annual runoff anomalies throughout the 12‐year post‐fire analysis periods. Enhanced post‐fire snow accumulation and melt contributes to observed but unmodeled increases of spring runoff and annual runoff efficiency at these catchments. Informing simulations with satellite observed land cover classifications, leaf area index, and green fraction do not consistently improve the model ability to simulate hydrologic responses to fire disturbances.

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“…As such, we focused on hydrologic metrics with established linkages to Pacific salmon performance and viability, including peak flows, summer low flows and maximum summer temperature (Ward et al, 2015;Warkentin et al, 2022;Zillig et al, 2021). This focus differs from other recent work emphasizing hydrological processes and their responses to forest disturbance (Buma & Livneh, 2017;Goeking & Tarboton, 2022).…”

Section: Introductionmentioning

confidence: 99%

Forestry impacts on stream flows and temperatures: A quantitative synthesis of paired catchment studies across the Pacific salmon range

Naman,

Pitman,

Cunningham

et al. 2024

Ecol Sol and Evidence

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Forestry is pervasive across temperate North America and may influence aquatic environmental conditions such as flows and temperatures, as well as important species such as Pacific salmon (Oncorhynchus spp.). While there have been many large‐scale forestry experiments using paired catchment designs, these studies have yet to be quantitatively synthesized. Thus, it remains unclear whether forestry impacts are consistent, context‐dependent or unpredictable. This study aims to quantitatively synthesize forestry impacts on streamflow and temperature, through a systematic review and synthesis of paired catchment studies across the range of Pacific salmon. Specifically, we investigated whether generalizable relationships exist between forestry intensity (percent watershed harvested) and impacts to streamflow and temperature. We also examined whether watershed features (climate, hydrology and lithology) and harvest method mediated forestry impacts. We extracted information from 35 unique paired‐catchments from California to Alaska. Forestry had strong impacts on peak and low flows and maximum summer water temperatures, but responses were quite variable. Across all catchments, forestry elevated peak flows ~20% (n = 31 catchments), reduced low flows ~25% (n = 13 catchments) and increased maximum summer temperatures ~15% (n = 35 catchments) on average. However, these impacts were variable and were not predictable based on forestry intensity, thus broader stressor–response relationships were not supported. Forestry impacts on peak flows and maximum summer temperatures varied spatially. Peak flow impacts increased with northward latitude and temperature impacts decreased with eastward longitude. However, the magnitude of impacts were unrelated to other watershed attributes, which included climate (precipitation and aridity), rain versus snow hydrology, elevation and bedrock lithology. Harvest method and riparian buffer presence also had no detected effects on forestry impacts across studies and statistical models explained a low proportion of variation overall. Collectively, our results indicate that forestry can have substantial impacts on key environmental conditions; however, the magnitude of impact was variable and could not be clearly linked to easily measured watershed characteristics. This implies that forestry impacts may not be broadly predictable. Probabilistic risk models based on distributions of potential impacts may therefore be more useful for watershed management in data‐poor situations.

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Variable Streamflow Response to Forest Disturbance in the Western US: A Large‐Sample Hydrology Approach

Abstract: Such research is based on a combination of paired watershed experiments (e.g., Brown et al., 2005;Moore et al., 2020), post-hoc analysis of streamflow data in unpaired watersheds where streamflow can be modeled as a function of climatic observations (e.g.,

Cited by 12 publications

References 68 publications

Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins

Optimal Postprocessing Strategies With LSTM for Global Streamflow Prediction in Ungauged Basins

Evaluating Noah‐MP Simulated Runoff and Snowpack in Heavily Burned Pacific‐Northwest Snow‐Dominated Catchments

Forestry impacts on stream flows and temperatures: A quantitative synthesis of paired catchment studies across the Pacific salmon range

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