Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana

Chase, Katherine J.; Haj, Adel E.; Regan, R. Steven; Viger, Roland J.

doi:10.1016/j.ejrh.2016.06.001

Cited by 12 publications

(5 citation statements)

References 11 publications

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“…By 1980, 14 largeand medium-sized reservoirs were built in the upstream area of the Yongding River basin, and the total capacity was 5.28 billion m 3 . Although construction of water conservation facilities played an important role in defending against floods and ensuring the safety of industrial and agricultural production and people's lives and property, the facilities could change the time and spatial distribution of runoff [36].…”

Section: Influence On Runoff On Water Conservancy Project Constructionmentioning

confidence: 99%

Runoff Changes Based on Dual Factors in the Upstream Area of Yongding River Basin

Hou

Peng

et al. 2018

Pol. J. Environ. Stud.

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Section: Influence On Runoff On Water Conservancy Project Constructionmentioning

confidence: 99%

Runoff Changes Based on Dual Factors in the Upstream Area of Yongding River Basin

Hou

Peng

et al. 2018

Pol. J. Environ. Stud.

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“…Ray et al () showed decreases in runoff ranging from 6% to 20% by 2050 compared to the 20th Century average based on the multi‐model average projections for the Upper Colorado River Basin. Chase et al () found mean annual streamflows projected to increase (11%–21%) for Middle Musselshell River and Cottonwood Creek in Montana for years 2021–2038, 2046–2063, and 2071–2088.…”

Section: Discussionmentioning

confidence: 99%

Impact of Climate and Land Use Change on Streamflow and Sediment Yield in a Snow‐Dominated Semiarid Mountainous Watershed

Khatri

Strong

Stackelberg

et al. 2019

J American Water Resour Assoc

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This study investigates the impact of climate and land use change on the magnitude and timing of streamflow and sediment yield in a snow‐dominated mountainous watershed in Salt Lake County, Utah using a scenario approach and the Hydrological Simulation Program — FORTRAN model for the 2040s (year 2035–2044) and 2090s (year 2085–2094). The climate scenarios were statistically and dynamically downscaled from global climate models. Land use and land cover (LULC) changes were estimated in two ways — from a regional planning scenario and from a deterministic model. Results indicate the mean daily streamflow in the Jordan River watershed will increase by an amount ranging from 11.2% to 14.5% in the 2040s and from 6.8% to 15.3% in the 2090s. The respective increases in sediment load in the 2040s and 2090s is projected to be 6.7% and 39.7% in the canyons and about 7.4% to 14.2% in the Jordan valley. The historical 50th percentile timing of streamflow and sediment load is projected to be shifted earlier by three to four weeks by mid‐century and four to eight weeks by late‐century. The projected streamflow and sediment load results establish a nonlinear relationship with each other and are highly sensitive to projected climate change. The predicted changes in streamflow and sediment yield will have implications for water supply, flood control and stormwater management.

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“…The magnitude and slope of the future change in streamflow depend substantially on the hydro-climate. For example, Chase et al [39] reported that two out of seven watersheds of eastern and central Montana would experience a decrease in the mean annual streamflow in the future, while the rest of the watersheds would experience an increase (decrease) in mean annual streamflow for the period 2021-2038 (2071-2088). Apart from the mean streamflow, the frequency of minor flooding over the near-term and mid-term future is also expected to increase under two RCPs along the coastal United States [40].…”

Section: Discussionmentioning

confidence: 99%

Streamflow Simulation Using Bayesian Regression with Multivariate Linear Spline to Estimate Future Changes

Bhowmik

Seo

Sahoo³

2018

Water

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Statistical models for hydrologic simulation are a common choice among researchers particularly when catchment information is limited. In this study, we adopt a new statistical approach, namely Bayesian regression with multivariate linear spline (BMLS) for long-term simulation of streamflow on a Hydroclimate Data Network (HCDN) site in the United States. The study aims to: (i) evaluate the performance of the BMLS model; (ii) compare the performance of climate model outputs as predictors in hydrologic simulation; and (iii) estimate the changes in streamflow caused by anthropogenic climate change which is defined as the projected change in precipitation and temperature under different greenhouse gas emission scenarios. Performance of the BMLS model is compared with climatology for the validation period. Results suggest that the BMLS model forced with observed monthly precipitation and average temperature exhibits information that is not presented in the climatology of the validation period. Later, we consider Coupled Model Intercomparison Project Phase 5 (CMIP5) historical and hindcast runs to simulate streamflow at the HCDN site. The study found that sea-surface temperature-initialized decadal hindcast runs are performing no better than 20th century historical runs regarding hydrologic simulation. Finally, the changes in mean and variability in streamflow at the HCDN site are estimated by forcing the model with CMIP5 future projections for the period 2000-2049.

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Potential effects of climate change on streamflow for seven watersheds in eastern and central Montana

Cited by 12 publications

References 11 publications

Runoff Changes Based on Dual Factors in the Upstream Area of Yongding River Basin

Runoff Changes Based on Dual Factors in the Upstream Area of Yongding River Basin

Impact of Climate and Land Use Change on Streamflow and Sediment Yield in a Snow‐Dominated Semiarid Mountainous Watershed

Streamflow Simulation Using Bayesian Regression with Multivariate Linear Spline to Estimate Future Changes

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