Comment on “Future streamflow regime changes in the United States: assessment using functional classification” by Manuela I. Brunner et al.

Abstract. Streamflow regimes are changing and expected to further change under the influence of climate change, with potential impacts on flow variability and the seasonality of extremes. However, not all types of regimes are going to change in the same way. Climate change impact assessments can therefore benefit from identifying classes of catchments with similar streamflow regimes. Traditional catchment classification approaches have focused on specific meteorological and/or streamflow indices, usually neglecting the temporal information stored in the data. The aim of this study is 2-fold: (1) develop a catchment classification scheme that enables incorporation of such temporal information and (2) use the scheme to evaluate changes in future flow regimes. We use the developed classification scheme, which relies on a functional data representation, to cluster a large set of catchments in the conterminous United States (CONUS) according to their mean annual hydrographs. We identify five regime classes that summarize the behavior of catchments in the CONUS: (1) intermittent regime, (2) weak winter regime, (3) strong winter regime, (4) New Year's regime, and (5) melt regime. Our results show that these spatially contiguous classes are not only similar in terms of their regimes, but also their flood and drought behavior as well as their physiographical and meteorological characteristics. We therefore deem the functional regime classes valuable for a number of applications going beyond change assessments, including model validation studies or predictions of streamflow characteristics in ungauged basins. To assess future regime changes, we use simulated discharge time series obtained from the Variable Infiltration Capacity hydrologic model driven with meteorological time series generated by five general circulation models. A comparison of the future regime classes derived from these simulations with current classes shows that robust regime changes are expected only for currently melt-influenced regions in the Rocky Mountains. These changes in mountainous, upstream regions may require adaption of water management strategies to ensure sufficient water supply in dependent downstream regions. Highlights. Functional data clustering enables formation of clusters of catchments with similar hydrological regimes and a similar drought and flood behavior. We identify five streamflow regime clusters: (1) intermittent regime, (2) weak winter regime, (3) strong winter regime, (4) New Year's regime, and (5) melt regime. Future regime changes are most pronounced for currently melt-dominated regimes in the Rocky Mountains. Functional regime clusters have widespread utility for predictions in ungauged basins and hydroclimate analyses.

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Functional Classification of Coastal Ecological Systems of the United States

Geological Society of America Memoirs - Environmental Framework of Coastal Plain Estuaries ◽

10.1130/mem133-p9 ◽

1972 ◽

pp. 9-28 ◽

Cited By ~ 3

Author(s):

H. T. ODUM ◽

B. J. COPELAND

Keyword(s):

United States ◽

The United States ◽

Ecological Systems ◽

Functional Classification

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Future streamflow regime changes in the United States: assessment using functional classification

10.5194/hess-2020-54 ◽

2020 ◽

Author(s):

Manuela I. Brunner ◽

Lieke A. Melsen ◽

Andrew J. Newman ◽

Andrew W. Wood ◽

Martyn P. Clark

Keyword(s):

Climate Change ◽

United States ◽

Time Series ◽

General Circulation ◽

Classification Scheme ◽

The United States ◽

Hydrologic Model ◽

Temporal Information ◽

Large Set ◽

Regime Changes

Abstract. Streamflow regimes are changing and expected to further change under the influence of climate change with potential impacts on flow variability and the seasonality of extremes. However, not all types of regimes are going to change in the same way. Climate change impact assessments can therefore benefit from identifying classes of catchments with similar streamflow regimes. Traditional catchment classification approaches have focused on specific meteorological and/or streamflow indices usually neglecting the temporal information stored in the data. The aim of this study is two-fold: (1) develop a catchment classification scheme that allows for the incorporation of such temporal information and (2) use the scheme to evaluate changes in future flow regimes. We use the developed classification scheme, which relies on a functional data representation, to cluster a large set of catchments in the conterminous United States (CONUS) according to their mean annual hydrographs. We identify five regime classes that summarize the behavior of catchments in the CONUS: (1) Intermittent regime, (2) weak winter regime, (3) strong winter regime, (4) New Year's regime, and (5) melt regime. Our results show that these spatially contiguous classes are not only similar in terms of their regimes, but also their flood and drought behavior, as well as their physiographical and meteorological characteristics. We therefore deem the functional regime classes valuable for a number of applications going beyond change assessments including model validation studies or the prediction of streamflow characteristics in ungauged basins. To assess future regime changes, we use simulated discharge time series obtained from the Variable Infiltration Capacity hydrologic model driven with meteorological time series generated by five general circulation models. A comparison of the future regime classes derived from these simulations with current classes shows that robust regime changes are expected only for currently melt-influenced regions in the Rocky Mountains. These changes in mountainous, upstream regions may require the adaptation of water management strategies to ensure sufficient water supply in dependent downstream regions.

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Evolving Monetary/Fiscal Policy Mix in the United States

The American Economic Review ◽

10.1257/aer.102.3.167 ◽

2012 ◽

Vol 102 (3) ◽

pp. 167-172 ◽

Cited By ~ 35

Author(s):

Francesco Bianchi

Keyword(s):

United States ◽

Monetary Policy ◽

Fiscal Policy ◽

Regime Change ◽

The United States ◽

Policy Mix ◽

Structural Shocks ◽

Regime Changes ◽

The Law ◽

Fiscal Authority

A micro-founded model that allows for changes in the monetary/fiscal policy mix and in the volatility of structural shocks is fit to US post-WWII data. Agents are aware of the possibility of regime changes and their beliefs have an impact on the law of motion of the macroeconomy. The results show that the '60s and the '70s were characterized by a prolonged period of active fiscal policy and passive monetary policy. The appointment of Volcker marked a change in the conduct of monetary policy, but it took almost ten years for the fiscal authority to start accommodating this regime change.

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Functional data clustering as a powerful tool to group streamflow regimes and flood hydrographs

10.5194/egusphere-egu21-375 ◽

2021 ◽

Author(s):

Manuela Irene Brunner ◽

Reinhard Furrer ◽

Eric Gilleland

Keyword(s):

United States ◽

Functional Data ◽

Data Clustering ◽

The United States ◽

Continuous Functions ◽

Climate Impact ◽

Large Set ◽

Functional Clustering ◽

Clustering Approach ◽

Streamflow Regime

<p>Grouping catchments according to their seasonal streamflow or flood behavior can be essential in regionalization studies, climate impact assessments, or model choice and evaluation. Classical clustering approaches often rely on a selection of indices derived from streamflow/flood hydrographs to identify groups of similar hydrographs and ignore valuable information provided through the temporal (auto-)correlation pattern. To exploit this temporal information, we propose a functional clustering approach to identify catchments with similar streamflow regimes or flood hydrographs. Functional data clustering expresses hydrograph shapes as continuous functions by projecting them onto a set of basis functions (here B-splines) and clusters the resulting basis coefficients using classical clustering algorithms such as hierarchical or k-means clustering. <br>We apply this functional clustering approach to (1) a large set of catchments in the United States in order to identify regions with similar streamflow regimes and (2) a large set of catchments in Switzerland in order to identify regions with similar flood reactivity. We show that both the streamflow regime and flood reactivity regions are not only similar in terms of their streamflow/hydrograph behavior but also in terms of physiography and climate. We use the streamflow regime clusters derived using functional data clustering to assess future streamflow regime changes in the United States and demonstrate that they are beneficial in climate impact assessments, e.g. to indicate which types of catchments are particularly prone to future change. Further, we use the flood reactivity regions in a regionalization study to derive design hydrographs in ungauged catchments. We conclude that functional clustering approaches are beneficial in climate impact assessments and regionalization studies and might potentially also be valuable to cluster other types of hydrological phenomena such as drought events or long-term streamflow behavior.</p>

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Changing suspended sediment in United States rivers and streams: linking sediment trends to changes in land use/cover, hydrology and climate

Hydrology and Earth System Sciences ◽

10.5194/hess-24-991-2020 ◽

2020 ◽

Vol 24 (2) ◽

pp. 991-1010

Author(s):

Jennifer C. Murphy

Keyword(s):

United States ◽

Land Use ◽

Suspended Sediment ◽

Land Management ◽

Best Management Practices ◽

The United States ◽

Sediment Runoff ◽

Systematic Change ◽

Rivers And Streams ◽

Streamflow Regime

Abstract. Sediment is one of the leading pollutants in rivers and streams across the United States (US) and the world. Between 1992 and 2012, concentrations of annual mean suspended sediment decreased at over half of the 137 stream sites assessed across the contiguous US. Increases occurred at less than 25 % of the sites, and the direction of change was uncertain at the remaining 25 %. Sediment trends were characterized using the Weighted Regressions on Time, Discharge, and Season (WRTDS) model, and decreases in sediment ranged from −95 % to −8.5 % of the 1992 concentration. To explore potential drivers of these changes, the sediment trends were (1) parsed into two broad contributors of change, changes in land management versus changes in the streamflow regime, and (2) grouped by land use of the watershed and correlated to concurrent changes in land use or land cover (land use/cover), hydrology and climate variables and static/long-term watershed characteristics. At 83 % of the sites, changes in land management (captured by changes in the concentration–streamflow relationship over time; C–Q relationship) contributed more to the change in the sediment trend than changes in the streamflow regime alone (i.e., any systematic change in the magnitude, frequency or timing of flows). However, at >50 % of the sites, changes in the streamflow regime contributed at least a 5 % change in sediment, and at 11 sites changes in the streamflow regime contributed over half the change in sediment, indicating that at many sites changes in streamflow were not the main driver of changes in sediment but were often an important supporting factor. Correlations between sediment trends and concurrent changes in land use/cover, hydrology and climate were often stronger at sites draining watersheds with more homogenous, human-related land uses (i.e., agricultural and urban lands) compared to mixed-use or undeveloped lands. At many sites, decreases in sediment occurred despite small-to-moderate increases in the amount of urban or agricultural land in the watershed, suggesting conservation efforts and best-management practices (BMPs) used to reduce sediment runoff to streams may be successful, up to a point, as lands are converted to urban and agricultural uses.

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21st Century Slowdown: The Historic Nature of Recent Declines in the Growth of the Immigrant Population in the United States

MIGRATION LETTERS ◽

10.33182/ml.v15i3.362 ◽

2018 ◽

Vol 15 (3) ◽

pp. 409-422 ◽

Cited By ~ 1

Author(s):

Peter Norlander ◽

Todd A Sørensen

Keyword(s):

United States ◽

Immigration Policy ◽

Census Data ◽

The United States ◽

Immigrant Population ◽

Sharp Decline ◽

Migration Rates ◽

Regime Changes ◽

Relative Scarcity ◽

Potential Precursor

We document that the slowdown in the growth of the immigrant population in the United States since 2000 is the largest observed using Census data since 1870. Non-parametric tests reveal that the sharp decline is similar in magnitude to changes in migration growth rates that followed the two major historical regime changes in U.S. immigration policy. Migration rates are slowing across nearly all age, sex, educational and country of origin categories that we examine. We find that the stock of adult migrants under age 30 is smaller in 2015 than in 2000, a potential precursor to a declining overall stock, as was seen around the introduction of the national quotas regime in 1920. Heterogenous changes have led to slower declines for men than women, and an increase in the relative scarcity of low-skilled labor. Approximately half of the overall decline is due to falling Mexican immigration.

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