Results for trend and breakpoint analyses from: Losing flow in free-flowing Mediterranean-climate streams
Data files
Sep 15, 2023 version files 36.26 KB
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Carlson_et_al_meta-data_and_results.xlsx
28.55 KB
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README.md
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Abstract
Stream drying is happening globally, with significant ecological and social consequences. Most examples of stream drying come from systems influenced by dam operations or those with highly exploited aquifers. Stream drying is also thought to be happening due to climate change, but examples are surprisingly limited. We explored flow trends from the five Mediterranean-climate regions with a focus on unregulated streams with long-term gauge records. We found consistent evidence of decreasing discharge trends, increasing zero-flow days, and steeper downward discharge trends in smaller basins. Beyond directional trends, many systems recently shifted flow state, including some streams that shifted from perennial to intermittent flow states. Our analyses provide evidence of stream drying consistent with climate change, but also highlight knowledge gaps and challenges in empirically and statistically documenting flow regime shifts. We discuss the myriad consequences of losing flow and propose strategies for improving detection and adapting to flow change.
README: Meta-data and results for our trend and breakpoint analyses
https://doi.org/10.5061/dryad.d7wm37q6m
To document flow change, we compiled gauge records from five Mediterranean-climate regions of the world, including California (U.S.), Chile, South Africa, Spain, and Western Australia. For each gauge, we downloaded daily discharge records from public sources (see Open Research Statement and WebTable 1). Next, we limited our analysis to gauges located in Mediterranean-climates zones by retaining the subset of gauges located in Köppen-Geiger climate classes Csa, Csb, Csc (i.e., areas with a dry summer) using maps from Beck et al. 2018. Second, we identified gauges located in minimally disturbed basins. In the US and Australia, we used “reference” gauges identified by the USGS and Bureau of Meteorology, respectively. In South Africa, Chile, and Spain - where reference gauges have not been designated by agencies - we instead used aerial image analysis of upstream watershed conditions to identify basins with no evidence of significant reservoirs or large water infrastructure projects. We note that our determination of “reference-quality” gauges in Spain [excluding Catalonia] is consistent with Messager et al. 2021. Third, we identified gauges with daily data from 1980-2019 (i.e., most recent 40 years in common across the five regions) and no more than one year of missing data.
Overall, we identified 158 gauges that met our criteria for inclusion (i.e., Mediterranean-climate, reference-quality, 40 years of data from 1980-2019, and no more than one year of missing data, see WebPanel 1 and WebFigure1). To reduce noise in zero-flow conditions, we defined “zero flows” as flows < 0.1 cfs. Finally, for our analysis of zero-flow trends, we used a liberal definition of “intermittent” and included the subset of streams with ≥ to 1 day/year of zero-flow on average, i.e., ≥ 40 days across the 40 year study, following Messager et al. 2021.
Using the population of gauges that met our criteria for inclusion, we conducted trend analyses on daily discharge (for each gauge in our population) and on the annual number of zero-flow days (for the subset of intermittent gauges) across the time series by means of non-parametric Mann-Kendall tests (McLeod 2022).
We next explored evidence of flow regime shifts. Specifically, we conducted a breakpoint analysis on the zero-flow days per year using the ‘strucchange’ package in R (Zeileis et al. 2002). We constrained the analysis to test for evidence of a maximum of one breakpoint (indicating a state shift).
The meta-data used to run our trend and breakpoint analyses, and the results of those analyses, are presented in this file.
References
Beck HE, Zimmermann NE, McVicar TR, et al. 2018. Present and future Köppen-Geiger climate classification maps at 1-km resolution. Sci Data 5: 180214.
McLeod, A.I. (2022). "Kendall: Kendall Rank Correlation and Mann-Kendall trend test". R package version 2.2.1. Available at: http://cran.r-project.org/package=Kendall.
Messager ML, Lehner B, Cockburn C, et al. 2021. Global prevalence of non-perennial rivers and streams. Nature 594: 391–7.
Zeileis A, Leisch F, Hornik K, Kleiber C (2002). “strucchange: An R Package for Testing for Structural Change in Linear Regression Models.” Journal of Statistical Software, 7(2), 1–38. doi:10.18637/jss.v007.i02
Description of the data and file structure
This data file includes columns for meta-data for our analyses ("region", "ID", "latitude", "longitude", "drainage_area_km2", "NA_count"), as well as the results of our trend analyses ("discharge_tau", "discharge_p_value", "zeros_tau", "zeros_p_value") and the results of our breakpoint analyses ("total_zero_flow_days", "BreakpointTime", "MeanZerosBefore", "MeanZerosAfter"). Further detail is provided below.
- Region - specifies the Mediterranean-climate region from where the data originated (AU - Australia; CA - California, USA; CH - Chile; SA - South Africa; SP - Spain);
- ID - regional ID associated with each gauge record;
- latitude - latitude of gauge site;
- longitude - longitude of gauge site;
- drainage_area_km2 - drainage area upstream of each gauge, standardized to units of km2;
- discharge_tau - trend on daily discharge across the time series by means of non-parametric Mann-Kendall tests;
- discharge_p_value - p-value associated with the trend analysis on daily discharge across the time series by means of non-parametric Mann-Kendall tests;
- zeros_tau - trend on number of annual zero-flow days across the time series by means of non-parametric Mann-Kendall tests;
- zeros_p_value - p-value associated with the trend analysis on the annual number of zero-flow days across the time series by means of non-parametric Mann-Kendall tests;
- NA_count - a check that we included only gauge records with less than one year of missing data (i.e., for all gauge records included in our analyses, the count of missing data or "NAs" < 365);
- total_zero_flow_days - the total number of zero-flow days across the time series, used to identify the subset of "intermittent" and "perennial" gauges (we used a liberal definition of “intermittent” and included the subset of streams with ≥ to 1 day/year of zero-flow on average, i.e., ≥ 40 days across the 40 year study, following Messager et al. 2021);
- BreakpointTime - we conducted a breakpoint analysis on the zero-flow days per year and constrained the analysis to test for evidence of a maximum of one breakpoint (indicating a state shift). For the subset of gauges showing evidence of a state shift, we report the year (ranging from the 1st to the 40th year across the time series) associated with the shift as the "BreakpointTime";
- MeanZerosBefore - For the subset of gauges showing evidence of a state shift, we further report the mean number of zero-flow days before the state shift;
- MeanZerosAfter - For the subset of gauges showing evidence of a state shift, we further report the mean number of zero-flow days after the state shift.
Sharing/Access information
The gauge data sets utilized for this research were retrieved from the following sources:
- Australia - Australian Government, Bureau of Meteorology, Water data online (http://www.bom.gov.au/waterdata);
- California, USA - USGS National Water Information System, USGS Water Data for California (https://waterdata.usgs.gov/ca/nwis/);
- Chile - CAMELS-CL explorer (CR)2 (https://camels.cr2.cl/) from Alvarez-Garreton et al. 2018;
- South Africa - Republic of South Africa, Department Water and Sanitation, Hydrological Services - Surface Water (https://www.dws.gov.za/Hydrology/Verified/hymain.aspx);
- Spain - Centro de Estudios Hidrográficos (CEDEX) (https://ceh.cedex.es/anuarioaforos/default.asp) and Agència Catalana de l’Aigua: https://aplicacions.aca.gencat.cat/sdim21/seleccioXarxes.do.
Methods
To document flow change, we compiled gauge records from five Mediterranean-climate regions of the world, including California (U.S.), Chile, South Africa, Spain, and Western Australia. For each gauge, we downloaded daily discharge records from public sources. Next, we limited our analysis to gauges located in Mediterranean-climates zones by retaining the subset of gauges located in Köppen-Geiger climate classes Csa, Csb, Csc (i.e., areas with a dry summer) using maps from Beck et al. 2018. Second, we identified gauges located in minimally disturbed basins. In the US and Australia, we used “reference” gauges identified by the USGS and Bureau of Meteorology, respectively. In South Africa, Chile, and Spain - where reference gauges have not been designated by agencies – we instead used aerial image analysis of upstream watershed conditions to identify basins with no evidence of significant reservoirs or large water infrastructure projects. We note that our determination of “reference-quality” gauges in Spain [excluding Catalonia] is consistent with Messager et al. 2021. Third, we identified gauges with daily data from 1980-2019 (i.e., most recent 40 years in common across the five regions) and no more than one year of missing data.
Overall, we identified 158 gauges that met our criteria for inclusion (i.e., Mediterranean-climate, reference-quality, 40 years of data from 1980-2019, and no more than one year of missing data, WebPanel 1, WebFigure1). To reduce noise in zero-flow conditions, we defined “zero flows” as flows < 0.1 cfs. Finally, for our analysis of zero-flow trends, we used a liberal definition of “intermittent” and included the subset of streams with ≥ to 1 day/year of zero-flow on average, i.e., ≥ 40 days across the 40 year study, following Messager et al. 2021.
Using the population of gauges that met our criteria for inclusion, we conducted trend analyses on daily discharge (for each gauge in our population) and on the annual number of zero-flow days (for the subset of intermittent gauges) across the time series by means of non-parametric Mann-Kendall tests.
We next explored evidence of flow regime shifts. Specifically, we conducted a breakpoint analysis on the zero-flow days per year using the ‘strucchange’ package in R. We constrained the analysis to test for evidence of a maximum of one breakpoint (indicating a state shift).