Research ArticleENVIRONMENTAL STUDIES

Changes in water consumption linked to heavy news media coverage of extreme climatic events

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Science Advances  25 Oct 2017:
Vol. 3, no. 10, e1700784
DOI: 10.1126/sciadv.1700784
  • Fig. 1 Volume of newspaper articles discussing water- and drought-related issues in California and drought classification as represented by the PDSI.

    (A) Media coverage for the entire study period, highlighting heavy coverage of the later drought. (B) Zoomed-in view of media coverage before January 2014, before the first spike in coverage but including coverage of the start of the recent historic drought. Prominent drought events are as follows: (1) June 2008: Governor Schwarzenegger’s emergency proclamation for selected Central Valley counties; (2) February 2009: Governor Schwarzenegger declares Drought State of Emergency; (3) January 2014: Governor Brown declares Drought State of Emergency; (4) July 2014: Outdoor water conservation regulation; (5) December 2014: Rain event; and (6) April 2015: Mandatory statewide water use restrictions.

  • Fig. 2 Public interest as measured by Google searches for the term California drought and news media coverage of water- and drought-related issues in California.

    The inset figure shows the high correlation between the two metrics, where the black line figure is 1:1. Google search data is provided by Google Trends on a relative 1 to 100 scale. The number of newspaper articles from nine sources was transformed to match the scale of the search data set.

  • Fig. 3 Actual and predicted water use trends in BAWSCA service areas.

    (A) Performance of the pooled models compared to measured demand. (B to D) Model performance for each service area cluster. Red shading indicates dry periods and blue shading indicates wet periods, as defined by PDSI.

  • Fig. 4 Breakpoints as identified by the BFAST method on trend and seasonal components of seasonally decomposed water use.

    (A) Breakpoints for SFR customers. (B) Breakpoints for COMM-IRR customers. The short dashed vertical lines in both plots denote trend breakpoints, whereas the long dashed vertical line in (A) denotes a seasonal breakpoint. The y-axis Vt represents the average water use WUt minus the seasonal component St, that is, the trend Tt plus the residual component εt (see Materials and Methods). Red lines show 95% confidence intervals.

  • Table 1 SFR water demand model outputs.

    *P < 0.05, **P < 0.01, ***P < 0.001.

    Pooled modelCluster A model
    (highest income,
    high WU)
    Cluster B model
    (medium income,
    medium WU)
    Cluster C model
    (lowest income,
    medium WU)
    Model information
      Number of observations1200180660360
      F statistic301.2***
    (df = 7; 1192)
    101.9***
    (df = 7; 172)
    204.5***
    (df = 7; 652)
    108.4**
    (df = 7; 352)
    Coefficients
      Intercept1.417***2.057***1.749***2.462***
      Temperature (°C)0.082***0.132***0.073***0.054***
      Precipitation (mm)−3.5 × 10−6−4.2 × 10−4−1.3 × 10−4−9.3 × 10−5
      PDSI−0.012**−0.007−0.006−0.003
      Average price [2015$/hundred cubic feet (CCF) water]−0.058***−0.005−0.035***−0.077***
      Unemployment rate (%)−0.031***−0.041**−0.036***−0.018***
      Median household income (2015$/$1000)0.009***0.001*0.005***0.002**
      Number of newspaper articles about the
    California drought from nine sources
    −0.0018***−0.0015***−0.0016***−0.0011***
    Model performance metrics
      Adjusted R20.640.800.680.68
      RMSE12.911.74.03.1
      PBIAS−7.0%−2.1%−1.9%−1.3%
      AIC583.218.2−265.2−323.8
  • Table 2 Slopes between Redwood City water use trend breakpoints.
    SFR customers with AMI
    Time period [year (week)]2010 (26)–2011 (23)2011 (23)–2013 (10)2013 (10)–2014 (5)2014 (5)–2016 (1)
    Slope−0.322−0.074−0.191−0.346
    COMM-IRR customers with AMI
    Time period [year (week)]2010 (26)−2011 (24)2011 (24)–2013 (6)2013 (6)–2016 (1)
    Slope−8.76−1.23−2.99

Supplementary Materials

  • Supplementary Materials

    This PDF file includes:

    • Demand modeling
    • Breakpoint analysis
    • fig. S1. BAWSCA service areas.
    • fig. S2. K-means clustering of service areas.
    • table S1. BAWSCA service area cities and proxies used for unemployment.

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