Scatterplot of estimated PET for California in 2005, using the Hamon and Blaney-Criddle metrics.

<p>Each dot represents one year in a particular combination of GCM and greenhouse gas emissions Scenario. Note that the strong linear correlation between the two means that when either of these two metrics are statistically related to irrigation use, the quantitative predictions of the effect of climate change are quite similar. Other states also show a linear correlation, with R² ranging from 0.75 to 0.93.</p

Withdrawal ratios by state.

<p>The ratio of irrigation withdrawals in 2090 to irrigation withdrawals in 2005 if the mix of irrigation technologies stays the same as today (open circles) or if the current trend away from surface irrigation continues into the future (grey squares). A ratio of more than one indicates withdrawals will increase, while a value of less than one indicates withdrawals will decrease. Data points are labeled using the standard two-digit abbreviation for US states (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065589#pone-0065589-g003" target="_blank">Figure 3</a>), staggered so that labels do not overlap.</p

The effect of climate change on the Hamon estimate of PET (top) and the Blaney-Criddle estimate of PET (bottom).

<p>Both panels are colored with 5 equal interval categories that linearly span the range of the pixel values, with areas of less increase in PET being yellow and areas of greater increase in PET being red.</p

The effect of climate change on irrigation water use by United States agriculture.

<p>A.) Historical and future trends in U.S. mean moisture deficit. Displayed is the irrigated area weighted average, which is most directly relevant to irrigation rate. For each climate change scenario, the projected moisture deficit at the climate of the ensemble median is shown. The grey area shows the range of fraction irrigated for climate of the 20^th and 80^th quintiles of the ensemble. B.) Historical and future trends in the fraction of agriculture irrigated. C.) Historical and future trends in the irrigation rate. The blue area shows the effect of climate change on irrigation rates if the current mix of irrigation equipment persists over time; the green area shows the effect of climate change if the observed (1985–2005) trend away from relatively inefficient surface irrigation continues over time. D.) Historical and future trends in total irrigation withdrawals. Note the confidence intervals of the blue (current mix of irrigation equipment) and green (decreased use of surface irrigation) areas overlap after 2030.</p

Regression coefficients that predict the proportion of agricultural area that is irrigated, logit transformed.

<p>Only the final, best fit model is shown. Greek letters correspond to the regression parameters discussed in section 2.3.</p

The effect of climate change on irrigation by states.

<p>A.) Projected increase in irrigated area by 2090 under the A1B scenario, ensemble median. Most states have an increase in irrigated area under all emission scenarios in more than 80% of the GCMs in the ensemble; those that have a decrease in some cases are marked high uncertainty. B.) Projected increase in irrigation rate by 2090 under the A1B scenario, ensemble median. Most states have an increase in irrigation rate under all emission scenarios in more than 80% of the GCMs in the ensemble; those that have a decrease in some cases are marked high uncertainty.</p

Currently wet states will have significant increases in irrigated area.

<p>The relationship between the proportion of agricultural land irrigation in 2005 and the predicted proportion of water withdrawals in 2090 (median A1B scenario of the GCM ensemble) that will come from fields not currently irrigated. A few states with significant agricultural area are labeled, using standard two-digit abbreviation for US states (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0065589#pone-0065589-g003" target="_blank">Figure 3</a>). Three states are excluded from this graph, because climate change will have a net decrease on irrigated area there (Massachusetts, Connecticut, and Rhode Island).</p

Scatterplot of change in PET for California between 2005 and 2090, using the Hamon and Blaney-Criddle metrics.

<p>Each dot represents one year in a particular combination of GCM and greenhouse gas emissions scenario. Note that the strong linear correlation between the two means that when either of these two metrics are statistically related to irrigation use, the quantitative predictions of the effect of climate change are quite similar. Other states also show a linear correlation, with R² ranging from 0.74 to 0.93.</p

The fraction of agricultural land irrigated in U.S. states in 2005 as a function of moisture deficit.

<p>Note the logarithmic scale on both axes. The size of circle is proportional to the irrigation rate (m³ha⁻¹); states with high moisture deficit have higher irrigation rates. The fitted regression line is shown for the middle 90% of the data range.</p

Regression coefficients that predict the irrigation rate (m³ha⁻¹), log transformed.

<p>Only the final, best fit model is shown. Greek letters correspond to the regression parameters discussed in section 2.3.</p