1. the List of Target Commodities 2

electronic supplementary material

Contents

1. The list of target commodities 2

2. A prediction model of undernourished population 4

2.1 Modelling procedures for non-linear multiple regression analysis 4

2.2 Results of the regression analysis 4

3. Comparison of CFs at midpoint based on different Water Scarcity Indices (WScI) 5

4. Estimated agricultural water shortage 7

1. The list of target commodities

Commodities on food production and food supply were classified as shown in Table S1, S2 and S3 in accordance with the classification of commodities in FAOSTAT (FAO 2013). Only agricultural commodities that freshwater consumption data for production were available in Mekonen and Hoekstra (2010) were selected as targets. For animal products, aquatic products (fish, seafood) were excluded because the target of this study is the shortage of agricultural water.

Table S1 Classification of agricultural food commodities (crops)

Commodity group name / Commodity name
Cereals – Excluding Beer - / Wheat
Rice
Barley
Maize
Rye
Oats
Millet
Sorghum
Cereals, other
Starchy roots / Potatoes
Sweet potatoes
Roots, other
Sugar crops / Sugar cane
Sugar beet
Pulses / Beans
Peas
Pulses, other
Oil crops / Soyabeans
Groundnuts
Sunflowerseed
Rape and Mustardseed
Cottonseed
Palmkernels
Olives
Oilcrops, other

Table S2 Classification of agricultural food commodities (vegetables, fruits, stimulants and spices)

Commodity group name / Commodity name
Vegetables / Tomatoes
Onions
Vegetables, other
Fruits / Oranges, Mandarines
Lemons, Limes
Grapefruit
Citrus, other
Bananas
Apples
Pineapples
Dates
Grapes
Fruits, other
Stimulants / Coffee
Cocoa beans
Tea
Spices / Pepper
Pimento
Cloves
Spices, other

Table S3 Classification of animal food commodities

Commodity group name / Commodity name
Meat / Bovine meat
Mutton and Goat meat
Pigmeat
Poultry meat
Meat, other
Animal fats / Butter, Ghee
Fats, Animals
Eggs / Eggs
Milk / Milk

2. A prediction model of undernourished population

2.1 Modelling procedures for non-linear multiple regression analysis

To predict the undernourished population in each country, non-linear multiple regression analysis was performed by setting two explanatory variables (daily average dietary energy consumption per capita and Gini coefficient of dietary energy consumption).

As the first step, outlier data were excluded from the analysis based on the results of a Smirnov-Grubbs test. Subsequently, the optimal line shapes for the relationships between undernourished population rate and each explanatory variable were determined based on the results of preliminary conducted single regression analyses for five typical line shapes (linear, cumulative power, exponential, logarithm, and logistic). Finally, regression parameters were determined using the backward step for selecting appropriate explanatory variables (Motoshita et al. 2010).

2.2 Results of the regression analysis

The line shape of regression and the appropriateness of each variable (t-value, P-value and variable inflation factor) are shown in Table S4. Both explanatory variables shows strong correlation with the level of undernourished population and seemed to be relevant explanatory variables. In particular, average daily dietary energy consumption was highly correlated (as shown in the high t-value). This suggests that the effect of changes in average daily dietary energy consumption will increase exponentially in more vulnerable countries.

Table S4 The appropriateness of each explanatory variable

Regression line shape / t-value / P-value / VIF
Average daily dietary energy consumption / Exponential / 33.17 / 0.00 / 4.15
Gini coefficient of dietary energy consumption / Linear / 4.67 / 0.00 / 1.86

3. Comparison of CFs at midpoint based on different Water Scarcity Indices (WScI)

Water Scarcity Indices (WScI) of Pfister et al. (2009) and Boulay et al. (2011) can be applied to the calculation of CFs based on the user-specific approach employed in this study. The map of CF ranks based on two indices are shown in Fig. S1 in comparison with that of CF ranks based on the generic approach. The correlation between the CF ranks of both cases when applying Water Scarcity Indices (WScI) from Pfister et al. (2009) and Boulay et al. (2011) are shown in Fig. S2.

Fig. S1 Comparison of the CF ranks at the midpoint in both the generic approach and user-specific approach, based on different Water Scarcity Indices (WScI)

Fig. S2 Correlation of the CF ranks in the user-specific approach when applying different Water Scarcity Indices (WSI: Pfister et al. 2009; Alpha: Boulay et al. 2011) to the CF calculation

The coefficient of variance of CFs was also larger in the case of the user-specific approach (3.18) based on the Water Scarcity Index (Alpha) of Boulay et al. (2011) than in that of the generic approach (1.21) used by Boulay et al. (2011) and applying the Water Scarcity Index of Pfister et al. (2009). As described in the paper, when comparing both CFs in the generic approach (Boulay et al. submitted), the similarity of both indices (WSI: Pfister et al. 2009 and Alpha: Boulay et al. 2011) on water stress was already apparent. Thus, the ranking of the CFs in both the user-specific approaches applied in this study (based on WSI and Alpha) was fairly similar on the whole (Fig. S1 and S2). However, inconsistencies in the CF ranks revealed by both methods could be seen in some countries (Fig. S2).

4. Estimated agricultural water shortage

The amount of freshwater shortage was determined based on Eq.(15) in comparison with the minimum demand and actual supplied water to agriculture as mentioned in section 4.1.1. In Table S5, annual water consumption, the shortage of agricultural water and over consuming rate are shown for better understanding the result in Fig.5 and Table 1.

Table S5a The volume of annual water consumption, the shortage of agricultural water and over consuming rate in each country

Region / Country / Annual water consumption [Gm3/yr] / The shortage of agricultural water [Gm3/yr] / Over consuming rate* [%]
East Mediterranean / Afghanistan / 17 / 0 / 0
Europe / Albania / 2.85 / 0 / 0
Africa / Algeria / 25.06 / 25.06 / 100
Europe / Andorra / NA / NA / NA
Africa / Angola / 12.2 / 7.62 / 62.5
America / Antigua and Barbuda / NA / NA / NA
America / Argentina / 96.65 / 0 / 0
Europe / Armenia / 2.21 / 0 / 0
West Pacific / Australia / 90.56 / 0 / 0
Europe / Austria / 6.99 / 0 / 0
Europe / Azerbaijan / 9.97 / 0 / 0
America / Bahamas / NA / NA / NA
East Mediterranean / Bahrain / 0.16 / 0 / 0
South-East Asia / Bangladesh / 113.9 / 0 / 0
America / Barbados / 0.22 / 0.09 / 40.9
Europe / Belarus / 10.25 / 0.21 / 2
Europe / Belgium / 14.31 / 6.29 / 44
America / Belize / 0.79 / 0 / 0
Africa / Benin / 12.41 / 0.18 / 1.5
South-East Asia / Bhutan / 0.74 / 0 / 0
America / Bolivia / 11.32 / 0 / 0
Europe / Bosnia and Herzegovina / NA / NA / NA
Africa / Botswana / 0.66 / 0.66 / 100
America / Brazil / 278.36 / 0 / 0
West Pacific / Brunei Darussalam / NA / NA / NA
Europe / Bulgaria / 21.11 / 0 / 0

* Over consuming rate in terms of agricultural water shortage

Table S5b The volume of annual water consumption, the shortage of agricultural water and over consuming rate in each country

Region / Country / Annual water consumption [Gm3/yr] / The shortage of agricultural water [Gm3/yr] / Over consuming rate* [%]
Africa / Burkina Faso / 18.22 / 0.35 / 1.9
Africa / Burundi / 7.34 / 0 / 0
West Pacific / Cambodia / 20.5 / 0 / 0
Africa / Cameroon / 23.19 / 2.23 / 9.6
America / Canada / 122.68 / 0 / 0
Africa / Cape Verde / 0.36 / 0.36 / 100
Africa / Central African Republic / 4.59 / 0 / 0
Africa / Chad / 16.9 / 0.31 / 1.8
America / Chile / 8.79 / 0 / 0
West Pacific / China / 893.23 / 0 / 0
America / Colombia / 38.19 / 0 / 0
Africa / Comoros / NA / NA / NA
Africa / Congo / 37.21 / 2 / 5.4
West Pacific / Cook Islands / NA / NA / NA
America / Costa Rica / 6.23 / 0 / 0
Africa / Côte d'Ivoire / 60.83 / 0 / 0
Europe / Croatia / NA / NA / NA
America / Cuba / 25.01 / 0 / 0
Europe / Cyprus / 0.7 / 0.7 / 100
Europe / Czech Republic / 14.27 / 0 / 0
South-East Asia / Democratic People's Republic of Korea / 16.75 / 0 / 0
Africa / Democratic Republic of the Congo / NA / NA / NA
Europe / Denmark / 9.38 / 0 / 0
East Mediterranean / Djibouti / NA / NA / NA
America / Dominica / NA / NA / NA
America / Dominican Republic / 11.06 / 0.54 / 4.9
America / Ecuador / 21.3 / 0 / 0
East Mediterranean / Egypt / 58.57 / 0 / 0
America / El Salvador / 6.29 / 0.84 / 13.4
Africa / Equatorial Guinea / NA / NA / NA

* Over consuming rate in terms of agricultural water shortage

Table S5c The volume of annual water consumption, the shortage of agricultural water and over consuming rate in each country

Region / Country / Annual water consumption [Gm3/yr] / The shortage of agricultural water [Gm3/yr] / Over consuming rate* [%]
Africa / Eritrea / NA / NA / NA
Europe / Estonia / NA / NA / NA
Africa / Ethiopia / 44.67 / 0 / 0
West Pacific / Fiji / 1.53 / 0 / 0
Europe / Finland / 7.16 / 0 / 0
Europe / France / 116.52 / 0 / 0
Africa / Gabon / 1.3 / 0.44 / 33.8
Africa / Gambia / 1.37 / 0.99 / 72.3
Europe / Georgia / 4.62 / 0 / 0
Europe / Germany / 91.85 / 0 / 0
Africa / Ghana / 42.45 / 1.28 / 3
Europe / Greece / 19.84 / 0 / 0
America / Grenada / NA / NA / NA
America / Guatemala / 12.44 / 0 / 0
Africa / Guinea / NA / NA / NA
Africa / Guinea-Bissau / NA / NA / NA
America / Guyana / 2.48 / 0 / 0
America / Haiti / 6.89 / 5.1 / 74
America / Honduras / 7.29 / 0 / 0
Europe / Hungary / 16.65 / 0 / 0
Europe / Iceland / 0.15 / 0 / 0
South-East Asia / India / 1012.72 / 0 / 0
South-East Asia / Indonesia / 264.97 / 0 / 0
East Mediterranean / Iran (Islamic Republic of) / 88.02 / 0 / 0
East Mediterranean / Iraq / 27.87 / 0 / 0
Europe / Ireland / NA / NA / NA
Europe / Israel / 2.41 / 2.41 / 100
Europe / Italy / 83.87 / 0 / 0
America / Jamaica / 2.14 / 1.2 / 56.1
West Pacific / Japan / 54.37 / 8.74 / 16.1

* Over consuming rate in terms of agricultural water shortage

Table S5d The volume of annual water consumption, the shortage of agricultural water and over consuming rate in each country

Region / Country / Annual water consumption [Gm3/yr] / The shortage of agricultural water [Gm3/yr] / Over consuming rate* [%]
East Mediterranean / Jordan / 1.77 / 1.77 / 100
Europe / Kazakhstan / 39.11 / 0 / 0
Africa / Kenya / 23.51 / 7.87 / 33.5
West Pacific / Kiribati / NA / NA / NA
East Mediterranean / Kuwait / 0.27 / 0.27 / 100
Europe / Kyrgyzstan / 7.16 / 0 / 0
West Pacific / Lao People's Democratic Republic / 7.69 / 0 / 0
Europe / Latvia / 1.27 / 0.27 / 21.3
East Mediterranean / Lebanon / 2.24 / 2.24 / 100
Africa / Lesotho / NA / NA / NA
Africa / Liberia / 4.41 / 1.62 / 36.7
East Mediterranean / Libyan Arab Jamahiriya / 6.89 / 3.6 / 52.2
Europe / Lithuania / 3.08 / 0 / 0
Europe / Luxembourg / NA / NA / NA
Africa / Madagascar / 22.73 / 0 / 0
Africa / Malawi / 13.64 / 1.27 / 9.3
West Pacific / Malaysia / 58.25 / 0 / 0
South-East Asia / Maldives / NA / NA / NA
Africa / Mali / 24.88 / 0 / 0
Europe / Malta / 0.09 / 0.09 / 100
West Pacific / Marshall Islands / NA / NA / NA
Africa / Mauritania / 2.65 / 1.85 / 69.8
Africa / Mauritius / 0.92 / 0 / 0
America / Mexico / 111.42 / 0 / 0
West Pacific / Micronesia (Federated States of) / NA / NA / NA
Europe / Monaco / NA / NA / NA
West Pacific / Mongolia / NA / NA / NA
East Mediterranean / Morocco / 38.39 / 4.18 / 10.9
Africa / Mozambique / 20.55 / 4.29 / 20.9
South-East Asia / Myanmar / 75.91 / 0 / 0

* Over consuming rate in terms of agricultural water shortage

Table S5e The volume of annual water consumption, the shortage of agricultural water and over consuming rate in each country

Region / Country / Annual water consumption [Gm3/yr] / The shortage of agricultural water [Gm3/yr] / Over consuming rate* [%]
Africa / Namibia / 1.15 / 1.07 / 93
West Pacific / Nauru / NA / NA / NA
South-East Asia / Nepal / 18.84 / 0 / 0
Europe / Netherlands / 8.21 / 8.21 / 100
West Pacific / New Zealand / NA / NA / NA
America / Nicaragua / 5.51 / 0 / 0
Africa / Niger / NA / NA / NA
Africa / Nigeria / 251.01 / 11.09 / 4.4
West Pacific / Niue / NA / NA / NA
Europe / Norway / 3.17 / 0.76 / 24
East Mediterranean / Oman / 0.97 / 0 / 0
East Mediterranean / Pakistan / 166.19 / 0 / 0
West Pacific / Palau / NA / NA / NA
America / Panama / 2.77 / 0.85 / 30.7
West Pacific / Papua New Guinea / 8.31 / 0 / 0
America / Paraguay / 11.87 / 0 / 0
America / Peru / 17.58 / 0 / 0
West Pacific / Philippines / 113.7 / 0 / 0
Europe / Poland / 37.29 / 0 / 0
Europe / Portugal / 12.59 / 0 / 0
East Mediterranean / Qatar / 0.2 / 0 / 0
West Pacific / Republic of Korea / 23.11 / 13 / 56.3
Europe / Republic of Moldova / 8.67 / 0 / 0
Europe / Romania / 41.86 / 0 / 0
Europe / Russian Federation / 272.64 / 0 / 0
Africa / Rwanda / 8.37 / 0.81 / 9.7
America / Saint Kitts and Nevis / NA / NA / NA
America / Saint Lucia / NA / NA / NA
America / Saint Vincent and the Grenadines / NA / NA / NA
West Pacific / Samoa / NA / NA / NA

* Over consuming rate in terms of agricultural water shortage