Closing the yield gap while ensuring water sustainability

We follow the methods in Davis et al (2017b) and Davis et al (2018) to calculate the crop water requirement at yield gap closure (see supplementary materials is available online at stacks.iop.org/ERL/13/104002/mmedia). A crop's water requirement is the amount of water needed by a crop to satisfy its evapotranspirative demand and to avoid a water-stressed condition. This demand can be satisfied by precipitation (i.e., green water) and supplemented through irrigation (i.e., blue water) if precipitation is insufficient. We considered 16 major crops (barley, cassava, groundnuts, maize, millet, oil palm, potatoes, rapeseed, rice, rye, sorghum, soybeans, sugar beet, sugar cane, sunflower, and wheat) which account for 73% of the planet's cultivated areas and 70% of global crop production (Food and Agricultural Organization of the United Nations 2017).

The current (year 2000) extent of crop-specific irrigated areas and planting and harvesting dates came from Portmann et al (2010). The current blue water consumption for a crop in a given pixel was then calculated as the product of the blue water requirement of that crop and its respective irrigated harvested area (Portmann et al 2010).

For each of the 16 major crops, we also calculated the additional volumes of blue water required to close the crop yield gap (i.e., to reach the maximum attainable yield) (Mueller et al 2012). In this yield gap closure scenario, given the uncertainty in determining where and to what extent cropping frequency can be increased through irrigation expansion, we assumed that current cropping practices will be implemented. This analysis was carried out for all cultivated lands around the world in which irrigation could substantially improve yields. In many humid areas where most of the crop water requirements can be met by precipitation, investments in irrigation infrastructures would not be justified by the modest increase in crop production induced by irrigation. Therefore, in these places we assume that farmers will likely continue to focus their efforts on rainfed agriculture. With this in mind, we assumed that a given crop and pixel will be irrigated under yield gap closure if the ratio between the blue and the total crop water requirements (units: mm yr⁻¹) was greater than a critical value of 0.10 (i.e., Blue Water/(Blue Water + Green Water) > 0.10) (Dell'Angelo et al 2018) (figure S1). This assumption is based on the rationale that in the wettest environments the development of irrigation infrastructure will not be economically justifiable given the marginal increases in yield it would likely bring. We also used thresholds of 0.00 and 0.20 to examine the sensitivity of our results to this threshold assumption (table 1).

For each pixel (5 arcminute), current blue water consumption for irrigation was then summed with estimates of annual municipal and industrial freshwater consumption (Hoekstra and Mekonnen 2012) to determine the current total blue water consumption of humanity. This analysis was repeated for blue water consumption under yield gap closure—where we assumed constant consumption from municipal and industrial uses—to calculate the total blue water consumption of humanity under yield gap closure. The blue water consumption (BWC) of humanity at a 5 × 5 arcminute resolution was then aggregated to a 30 × 30 arcminute resolution, the resolution of the global renewable blue water availability (BWA) analysis (see following section of methods).

The global distribution of annual renewable BWA (at 30 arcminute resolution) was calculated following the methods by Mekonnen and Hoekstra (2016), whereby the value of BWA in a grid cell was expressed as the sum of the local BWA in that cell (BWA_loc) and the net blue water flow from the upstream grid cells defined as the local renewable water availability in the upstream cells (BWA_up) minus the blue water consumption BWC of human activities (i.e., agriculture, municipal, and industrial) in the upstream cells (BWC_up). Blue water consumption was calculated as explained in section 2.2 (see also supplementary materials). The net renewable blue water flows (combined surface and subsurface) were calculated using the upstream-downstream routing 'flow accumulation' function in ArcGIS^®, where the subscript i denotes the cells upstream from the cell j under consideration:

$$\begin{eqnarray}&&{{\rm{BWA}}}_{{j}}=\,{{\rm{BWA}}}_{{\rm{loc}},{j}}+\displaystyle {\sum }_{{i}=1}^{{n}}({{\rm{BWA}}}_{{\rm{up}},{i}}-{{\rm{BWC}}}_{{\rm{up}},{i}}).\end{eqnarray} \tag{ 1 }$$

Local renewable BWA (surface + groundwater) was calculated as the local blue water flows generated in that grid cell minus the environmental flow requirement. Local blue water flows are calculated in every grid cell as the difference between precipitation and evapotranspiration—using estimates by Fekete et al (2002)—and therefore they account for surface and subsurface runoff generated in that cell as well as for aquifer recharge. We assumed that a fraction (y) of blue water flows is allocated to maintain environmental flows and that the remaining fraction (1 − y) is considered blue water locally available for human needs, BWA_loc (Pastor et al 2014, Steffen et al 2015). Environmental flow is defined as the minimum runoff that is required to sustain ecosystem functions. For irrigation to be sustainable, these minimum flow requirements need to be met even during dry season and low flow conditions (Richter et al 2012, Pastor et al 2014). Three flow regimes were considered: low, intermediate, and high corresponding to less than 25th percentile, between 25th and 75th percentile, and greater than 75th percentile of annual runoff, respectively (Rosa et al 2018). Following Steffen et al (2015) in each pixel the estimated blue water flow (Fekete et al 2002) was multiplied by the environmental flow fraction, y, associated with the corresponding flow regime (table S1, Pastor et al 2014) to calculate the environmental flows. Environmental flows were then subtracted from the local blue water flows to calculate the local BWA (BWA_loc). Thus, BWA_loc accounts only for renewable blue water resources that can be sustainably used for human activities and excludes both environmental flows and the (unsustainable) depletion of groundwater stocks.

To calculate the upstream to downstream water availability we used the flow direction raster (at 30 arcminute resolution) from the World Water Development Report II (Vörösmarty et al 2000a, 2000b). Runoff estimates were obtained from the Composite Runoff V1.0 database (Fekete et al 2002). Finally, we defined unsustainable irrigation as occurring when BWC is equal to or exceeds BWA, a condition that would imply the depletion of either environmental flows or groundwater stocks (or both).

For each of the 16 crops, calorie and protein production under current (Monfreda et al 2008) and yield gap closure (Mueller et al 2012) scenarios were assessed as the product of the crop yield value (tonne ha⁻¹), the crop harvested area (ha) (Monfreda et al 2008), and the calorie or protein content (kcal tonne⁻¹; tonne protein tonne⁻¹). Caloric content for each crop was taken from D'Odorico et al (2014), and crop-specific protein content was assessed as the ratio of per capita protein supply (g protein cap⁻¹ day⁻¹) to per capita food supply (g cap⁻¹ day⁻¹) from FAOstat (Food and Agricultural Organization of the United Nations 2017) (table S2). The number of people that can be potentially fed was assessed according to a previous global average estimate of 3343 vegetal kcal cap⁻¹ day⁻¹ (Davis et al 2017b).

Our results are based on the assumption that in the yield gap closure scenario a given crop and pixel will be irrigated if the ratio between the blue and the total crop water requirements is greater than a critical value of 0.10 (Dell'Angelo et al 2018). This assumption is based on the fact that, if blue water is needed to meet less than 10% of the crop water requirements, farmers will likely decide that the cost of improving irrigation systems will exceed the cost of reduced agricultural production from crops that are slightly water stressed. This ratio certainly depends on a host of factors including crop type, cost of irrigation infrastructure, access to water, farmer access to capital or credit, additional revenue from higher crop yields, market incentives, government policies, food needs, and interannual rainfall variability. The 10% threshold is here used as a conservative estimate, based on the fact that for major staple crops irrigation is found to be typically developed in areas in which green water consumption contributes to at most 80% of the total water consumption (i.e., irrigation infrastructure is found in areas where more than 10% of crop water requirements come from irrigation because it does not rain enough) (Rost et al 2008, Tuninetti et al 2015) (see table S7 for crop-specific values). Moreover, we found that the ratio between the blue and the total crop water requirements is less than 0.10 for only 6% (1.51 × 10⁵ km²) of currently irrigated lands (see table S7 for crop specific values of currently irrigated areas with a ratio BW/(BW + GW) < 0.1). We also performed a sensitivity analysis to analyze how our results would vary with different BW/(BW + GW) threshold values and we found that there is only a modest ±10% change in blue water consumption in the yield gap closure scenario when this ratio is reduced to zero or increased to 0.20 (table 1). Thus our estimates of irrigation water use in the yield gap closure yield scenario are robust with respect to the assumption that irrigation is not performed in areas where rainfed agriculture undergoes a water deficit smaller than 10%.

Our assessment is based on temporal averages and does not account for interannual and seasonal variability in river discharge and crop water requirements. For example, some irrigated areas might only experience unsustainable irrigation water demand in dry years or during dry periods of the year (Brauman et al 2016). Our model considers only short-range transport (∼50 km) of freshwater, without accounting for interbasin freshwater transfer projects like the South-to-North Water Diversion Project in China (Zhao et al 2017), the California State Water Project, and the Great Man Made River Project in Libya (Sternberg 2016). It also does not consider large water supply networks within the same basin that distribute water across hundreds of kilometers (at distances greater than the 50 km resolution of our model) such as the Nile and Indus basin channel networks. Moreover, because information on actual irrigation water use is limited, our model may produce instances where blue water demand in current irrigated lands cannot be fully met as a result of inadequate infrastructure or insufficient irrigation pumping capacity. The goal of this study is to provide biophysical estimates of crop water requirements that can be used to understand a farmer's average water needs. Our model also does not account for future potential changes in cropping frequency and crop types that could be enabled by additional irrigation infrastructure (Ray and Foley 2013, Rufin et al 2018).

Crop choice and cropping frequency are decisions primarily driven by economics, and farmers will likely decide to produce the most profitable crop under a change to irrigated conditions. Indeed, it remains difficult to estimate where and to what extent cropping frequency can be increased. Because we assume current cropping patterns and frequencies, our estimates of water consumption for certain areas may be conservative, as the expansion of irrigation may allow for an additional cropping season. On the other hand, our assumption of 100% yield potential in non-water-stressed conditions might overestimate water consumption under yield gap closure. Indeed, producers do not necessarily attempt to avoid water stress, but maximize their profit. This is usually not achieved by fully removing water and nutrient limitations to crop growth (i.e., maximum yield) because it may require an inefficient application of inputs (including water) that are not compensated by yield increases (Cassman 1999). Moreover, our biophysical model does not consider potential additional water demand from losses from irrigation infrastructure (e.g., losses from irrigation canals) and water use to control soil salinity. Future water consumption in agriculture will also be affected by climate change, which will alter both water availability and crop evapotranspiration (e.g., Katul et al 2012, Elliott et al 2014).

Lastly, the dataset on crop production under yield gap closure (Mueller et al 2012) relied on a statistical climate-binning approach to estimate the extent to which crop yields could be increased under improved management practices and inputs. Following the approach of Monfreda et al (2008)—the data we used to estimate current (circa 2000) crop production—Mueller et al (2012) developed gridded crop-specific maps of current crop yields and controlled for rainfall and temperature in order to develop yield distributions and estimate attainable yields. Because this yield gap closure dataset—which we also used here—relies on year 2000 yield data to estimate potential yields, it is likely that our estimates of potential crop production are conservative to a certain extent, as yields have been (slowly) increasing since the turn of the century because of new crop cultivars and improved management (Ray et al 2013), though, climate change could have a negative impact on potential yield growth in many regions of the world (Urban et al 2017).

We estimate that the current irrigation water consumption for major crop production is 847 km³ yr⁻¹ (table 2). This agrees well with previous estimates by Siebert and Döll (2010) (1180 km³ yr⁻¹) and Hoekstra and Mekonnen (2012) (899 km³ yr⁻¹). Our assessment shows that 40% of this volume of irrigation water is currently consumed at the expense of environmental flows (i.e., the minimum flows needed to sustain ecosystem functions in streams and rivers) (Jägermeyr et al 2017) or groundwater stocks. Not surprisingly, some of the world's major agricultural baskets such as the US High Plains and California's Central Valley, the North China Plain, the Murray-Darling Basin of Australia, and the Indo-Gangetic Basin consistently exhibit unsustainable water use, where blue water consumption exceeds its local availability (see figure 1(a)). In these regions, irrigation is depleting groundwater stocks (Konikow and Kendy 2005, Wada et al 2010, Gleeson et al 2012, Scanlon et al 2012, Famiglietti 2014, Rodell et al 2018) and diminishing environmental flows (Brauman et al 2016, Mekonnen and Hoekstra 2016, Jägermeyr et al 2017).

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To enhance crop yields, irrigation will need to expand into primarily rainfed agricultural areas where productivity is constrained by access to water resources. Investments in irrigation infrastructure, however, can only be justified if they induce a substantial increase in production, a condition that can be expressed by ratios between irrigation water and total water requirements greater than a critical value, typically taken equal to 0.10 (Dell'Angelo et al 2018). We estimate that this condition is met in 44% (i.e., 4.53 × 10⁶ km²) of the cultivated lands currently used for rainfed agriculture (figure 1). To expand and intensify irrigation over these lands, global blue water consumption for agriculture would need to increase by 760 km³ yr⁻¹. Doing so would enhance global food calorie production by 54% (5.00 × 10¹⁵ kcal yr⁻¹)—consistent with earlier estimates (Foley et al 2011)—and increase vegetal protein production by 51% (121 × 10⁶ tonnes yr⁻¹) (table 2, table S3).

In many places, however, these irrigation water requirements and the associated increases in food production can be sustainably met without depleting environmental flows and groundwater stocks. For only those rainfed areas with adequate freshwater resources, sustainable irrigation expansion would require an additional 408 km³ yr⁻¹. Though more limited in extent, this sustainable yield gap closure would still realize large increases in calorie (+37%, or 3.38 × 10¹⁵ kcal yr⁻¹) and protein (+34%, or 82 × 10⁶ tonnes protein yr⁻¹) production—enough to feed an additional 2.77 billion people. Overall, this means that 54% of the water needed to expand and intensify irrigation and 68% of the associated increase in calorie and protein production could be attained sustainably within the limits of renewable BWA (table 2). In this scenario of sustainable yield gap closure, half of the calorie production would rely on irrigation water. In addition, we find that opportunities to close the yield gap by sustainably expanding irrigation exist only in 26% of currently rainfed cultivated lands (green areas in figure 1(b)). Maximizing yields by sustainably expanding irrigation into these primarily rainfed lands (as opposed to intensifying irrigation in currently irrigated croplands) would require 82% of the sustainable additional blue water consumption, while contributing to 69% of the potential increase in calorie and protein production (table 2; table S3).

If current unsustainable blue water consumption (336 km³ yr⁻¹) and crop production (1.19 × 10¹⁵ kcal yr⁻¹) practices were eliminated, sustainable irrigation expansion and intensification (336 km³ yr⁻¹ and 72 km³ yr⁻¹, respectively) would still enable a substantial net increase in sustainable calorie (+24%, or 2.19 × 10¹⁵ kcal yr⁻¹) and protein (+22%, or 53 × 10⁶ tonnes protein yr⁻¹) production (table 2). In this scenario, total sustainable blue water consumption for irrigation would reach 919 km³ yr⁻¹ (551 km³ yr⁻¹ from current irrigation with additional 408 km³ yr⁻¹ from irrigation intensification and expansion). Moreover, an intensification of irrigation over currently irrigated lands would shift 0.14 × 10⁶ km² of irrigated croplands from sustainable to unsustainable water consumption practices.

Under sustainable yield gap closure, we found at least a doubling of calorie production for 50 countries, 29 of which are in Africa (e.g., Nigeria, Ethiopia, Eritrea, Democratic Republic of Congo, Tanzania, and Mozambique) (figure 2). We also found at least a doubling of protein production for 54 countries—most of which occur in the developing world (examples include 30 African countries, Mongolia, Cambodia, and Afghanistan) (table S3 and S6). Collectively, China, the United States, India, Russia, Brazil, and Nigeria can contribute to about 46% of the global increase in food calorie production associated with the sustainable intensification and expansion of irrigation (figure 3). China, the world's top food calorie producer, has the greatest potential to sustainably increase crop production by intensifying and expanding irrigation, thereby feeding an additional 382 million people. India and Russia also have great opportunities to sustainably increase calorie production to feed 261 and 222 million people, respectively (figure 3). Africa, currently only sparsely irrigated (Burney et al 2013), currently produces enough calories to feed 400 million people—making it the continent with the largest gap between crop production and demand (van Ittersum et al 2016). An increase in yields through investments in irrigation expansion could sustainably feed an additional 450 million people and substantially reduce the continent's dependence on food imports.

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Sustainable irrigation could increase national food self-sufficiency in countries that today meet large fractions of their domestic food demand through international trade (D'Odorico et al 2014). For example, net food importing countries (such as Mexico, Iran, Germany and Italy), would experience a greater than 15% increase in calorie production. This in turn could reduce their exposure to economic and environmental shocks to the global food system that occur beyond their borders (Suweis et al 2015, Oki et al 2017).