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Contents

FOREWORD

ACKNOWLEDGMENTS

ABSTRACT

1. INTRODUCTION

1.1 Assessment of measures to ensure food security

1.2 Concepts for calculating water productivity

2. MATERIAL AND METHODS

3. RESULTS

3.1 Objectives of the studies

3.2 Assessment approach

3.3 Life cycle approach

3.4 Water flows

3.5 Livestock species

3.6 System boundaries (inclusion of water flows)

3.7 Databases and modelling

3.8 Accounting for groundwater depletion, water scarcity, adaptation to climate change and nutritional water productivity

4. DISCUSSION

4.1 Goal of studies

4.2 Including or excluding background processes in water input

4.3 Consideration of precipitation

4.4 Including transpiration or evapotranspiration as water input

4.5 Including different livestock outputs

4.6 Addressing uncertainties

5. CONCLUSIONS

6. OUTLOOK

REFERENCES

APPENDIX

Figures

Figure 1. Main objectives of 50 water productivity studies relating water input to generated output in livestock production systems at different scales of analysis

Figure 2. The relationship between inputs and outputs relationships in livestock water productivity studies at different scales of analysis

Figure 3. System boundary and most important water flows at the farm scale.

Figure 4. An analysis of impact assessment in 15 livestock water productivity studies based on the LCA or including 3-4 stages of LCA. The studies shown cover the main objectives ‘quantification of water flows’ and/or ‘Impact assessment’

Figure 5. An analysis of water flows in the livestock water productivity studies

Figure 6: Studies using water from transpiration and studies using both transpiration and evapotranspiration as the input for water productivity analysis of livestock pro-duction systems.

Figure 7. Livestock species respectively. other output included in the LWP studies relating water input to output of livestock production systems

Figure 8. Water productivity in beef production systems.

Figure 9. Water productivity in dairy farming

Figure 10. Water productivity in a) sheep/wool production and b) poultry production systems

Figure 11. Water productivity in a) swine production and b) goat production systems

Figure 12. An analysis of system boundaries defined in the livestock water productivi-ty studies.

Figure 13. An analysis of the system boundary-related aspects of the livestock water productivity studies at different scales of analysis

Figure 14. Development of a concept for the improvement of water use in global livestock production, based on the consistent appli-cation of a water productivity (WP) assessment on farm scale, to reduce uncertainties on regional and global scale

Tables

Table 1. Studies to improve water productivity

Table 2. List of countries and number of studies of water productivity in livestock production.

Table 3. Location of studies that considered the use of purchased feed

Table 4. Examples of the LWP studies classified by input over output and output over input definition used to assess water productivity of livestock production systems

Foreword

This report is the result of a collaboration between the Land and Water Division (NSL) and the Animal Production and Health Division (NSA) on the methodology to assess water productivity of livestock supply chains. Despite the focus on feed crops and livestock sectors, the conclusions drawn in this report are also relevant to better understand, quantify and assess water use and its productivity in different food production systems.

With increasing water scarcity amplified by growing inter-sectoral competition and climate change, water stress is fast becoming the most significant limiting factor in food production systems, and adversely impact on rural livelihoods and food and nutrition security. Despite this, freshwater withdrawals for agriculture production are estimated to increase by 2050 to satisfy the increased demand for food (FAO, 2017a). Opportunities for quality food and productive use of water and other resources to nourish and, in other ways, benefit the poor as well as the society at large (i.e., multiple wins outcome) exist, but need to be better included in policy and development actions. Based on current trends, there will be a need to harness the water resource potential through a combination of efforts, such us better coordination in the management of water across sectors and make better use of water resources in line with the SDGs (e.g. SDG 2 and 6.4).

FAO is the custodian agency of 21 Sustainable Development Goal (SDG) indicators under the Post 2015 Agenda. FAO’s Strategic Programme in making agriculture, forestry and fisheries more productive and sustainable underscores the importance of an integrated approach for the efficient use of natural resources, including water resources. The FAO Land and Water Division leads the enhancement of agricultural productivity and advance the sustainable use of land and water resources through their improved management, development and conservation. In this regard, FAO promotes innovative approaches and best practices for sustainable water management for agriculture. The FAO Animal Production and Health Division promotes sustainability in livestock systems and provides tools and guidelines.

Overall, there are several challenges on the use of water productivity concept in complex multi-step production-consumption chains such as livestock sourced produce. There is an increase in the number of studies focusing on analysis and improvements of water use in food production systems in recent years. However, despite broad acceptance in the scientific community, the harmonization of water productivity and efficiency indicators for livestock production systems has not yet been pursued. There exist numerous challenges to achieving a consistent and coordinated application of water productivity analysis to complex multi-step production-consumption chains such as livestock-sourced produce.

This work between FAO technical units relied on contributions from external partners already involved in the FAO Livestock Environmental Assessment and Performance (LEAP) Partnership. This report represents a building block for a suite of tools and approaches in support of sustainable water management and nutrition sensitive agricultural practices and their operationalization at the field level.

Acknowledgments

The Land and Water Division (NSL) and the Animal Production and Health Division (NSA) would like to express their appreciation to all those who contributed to the preparation of this technical paper, through the provision of their time, expertise and other relevant information. This report was prepared under the coordination of Paulo Dias (FAO/NSL) and Camillo De Camillis (FAO/NSA). Special appreciation goes to Sasha Koo-Oshima (FAO/NSL), Henning Steinfeld (FAO/NSA), Paulo Dias (FAO/NSL), Jan Lundqvist (Stockholm International Water Institute (SIWI)) and Jennie Barron (Swedish University of Agricultural Sciences (SLU)) for their substantive review of the manuscripts, to Marlos De Souza (FAO/NSL) for having ensured coherence with previous FAO work, and to Ruth Raymond for the language editing. The Land and Water Division (NSL) would also like to acknowledge the financial resources provided by the Sustainable Agriculture Programme Management Team (SP2) of FAO to support this technical discussion paper.

Abstract

The assessment of water productivity in livestock supply chains has a critical role to play in developing productive and sustainable food production systems worldwide.

In particular, the evaluation of water productivity improvement options is key to addressing growing food demand and the projected impacts of climate change under conditions where the availability of land and water resources is increasingly limited.

In this report, we review current applications of water productivity in livestock supply chains in order to primarily shape the foundations for an assessment methodology enabling to inform decisions in sustainable water management and nutrition sensitive agricultural practices at the producer level.

The report builds on the findings of the consensus building process on methodology coordinated by the FAO LEAP Partnership that resulted in the report Water use in livestock production systems and supply chains – Guidelines for assessment (Version 1).

The FAO LEAP guidelines succeeded to build common ground in terminology and methodology relative to three water use assessment approaches (i.e. water footprinting according to ISO 14046: 2016; volumetric/virtual water footprint methodology by the Water Footprint Network; and water productivity assessment framework conceptualized by Molden (1997)).

While consensus was achieved on how to assess blue water scarcity footprint of livestock production, the three assessment approaches were found to compete in application when it comes to livestock water productivity. FAO LEAP guidelines provided no recommendations on how to select the approach depending on the specific objectives of the water productivity study. In addition, while agreement was found on the classification of water flows in blue and green for the water footprint assessments, no consensus was found on the classification of water flows for water productivity assessment studies in line with the concept by Molden (1997).

This report reviews 50 studies analyzing livestock water productivity carried out in various regions of the world from 1993 to the present time.

We found that there was no consistency in the methods and approaches used to assess water productivity in livestock production chains. The studies varied widely in terms of their assessment goals, methodology, and the sources of water used for the analysis. The main methodological differences were the inclusion or exclusion of background processes, such as water input and the treatment of precipitation in accounting for water use in livestock production processes. Another key issue was the missing uncertainty assessment, which can be classified as input data uncertainty or model uncertainty, such as value choices impact on uncertainty.

The studies were analyzed from different angles (assessment goals, system boundaries, methodological approaches, water flows, modelling tools, databases, livestock species and the main findings in each of the studies) with the ultimate goal of developing additional knowledge to fill gaps in consensus from the FAO LEAP process.

The review hence represents a milestone towards a consistent and coordinated application of water productivity analysis of livestock production systems worldwide.

1. Introduction

1.1 ASSESSMENT OF MEASURES TO ENSURE FOOD SECURITY

Increasing population and economic prosperity are putting enormous pressure on limited land and water resources worldwide. Water is a key input in food and feed production, supporting global food demands and underpinning global food security. Yet water is an increasingly scarce resource in many parts of the world, its availability varying widely over temporal and spatial scales (Thoma, 2016). In addition, other challenges, such as climate change and increasing competition with other users (e.g. for urbanization, industrial growth and environmental water flow requirements) are exacerbating water scarcity and its effects on food production and the health of freshwater ecosystems. In several regions, changing rainfall patterns and water levels in local water bodies jeopardize agricultural sustainability, leading to reductions in food production (Parry et al., 2004). This has been further complicated by a decline – since 1990 – in the yield growth of the most important agricultural crops due to shifts in funding for agricultural research and development (Alston, Beddow and Pardey, 2009). High quality water must be ensured to produce livestock. However, livestock production can lead to water pollution (e.g. eutrophication) through manure deposition and nutrient loss from livestock production systems to receiving waters. Guidelines on nutrient cycles in livestock production systems are available from the Livestock Environmental Assessment and Performance Partnership (LEAP) (FAO, 2018a).

In order to develop strategies for farming systems to cope with water scarcity and climate change, we need to better understand, quantify and assess water use and its productivity in different food production systems (Comprehensive Assessment of Water Management in Agriculture, 2007). Animal products are estimated to consume about one-third of the water used in agriculture worldwide (Mekonnen and Hoekstra, 2012). The relative share of water used by animal products is expected to grow, due to changes in economic prosperity and consumption patterns, particularly in developing countries. Although most of the water used in livestock production is consumed to produce feed, the use of water for cleaning, cooling and drinking should not be overlooked, due to the particular relevance of this mostly potable technical water’ and its exacerbated competition with other sectors e.g. industrial and municipal uses.

The amount of drinking water used by livestock depends on factors such as climatic conditions, the intensity of animal husbandry, the age of the animals, and the amount and type of feed that they consume (OMAFRA, 2015; Higham et al., 2017a,b). For example, depending on their level of milk production, dairy cows drink between 68-155 litres of water each per day (OMAFRA, 2015), while swine drink between 2.6-22 litres per day (Meehan et al., 2015); small ruminants drink between 2-12 litres per day (DAF, 2014) and poultry drink between 0.05-0.77 litres per day. A reliable water supply is necessary to provide both drinking water and cooling water for barns. In some systems, water supply losses (e.g. evaporation from open storages, wallows and leakages from supply networks of irrigation, and other service water) can be high and contribute substantially to non-beneficial, unproductive water use (Wiedemann, McGahan and Murphy, 2017b; Wiedemann et al., 2015a; Higham et al., 2017a).

Water use generally refers to the utilization of water in households, industry, and agriculture. The term ‘water use’ also relates to human activity. This includes, but is not limited to, water withdrawal, water release or other activities in the drainage basin that impact water flows and/or quality, including in-stream uses such as fishing, recreation and transportation. The term ‘water consumption’ describes water removed from, but not returned to the same drainage basin. Water consumption can be caused by evaporation, transpiration, integration into a product, or release into a different drainage basin (e.g. interbasin transfer) or to the sea. The term ‘water withdrawal’ is the removal of water – by humans –from any water body or drainage basin, either temporarily or permanently (ISO 14046:2014).

Our review examined three types of water flows: ‘technical water,’ ‘evapotranspiration water stemming from precipitation’ and ‘waste water.’ Technical water includes tap water and irrigation water, which can be withdrawn from surface water or groundwater bodies. Tap water includes water flows that are provided by all technical means other than irrigation water. Evapotranspiration water stemming from precipitation refers to the precipitation stored in the soil or temporarily found on the soil or in vegetation. Fresh water resources can also be categorized as ‘blue water’ and ‘green water’ based on their nature. Fresh water stored in water bodies, such as water in lakes, rivers and groundwater, is called blue water. The fresh water that is stored as soil moisture from infiltrated rainfall and used by vegetation is called green water.

Researchers and water managers devote significant efforts and investments to developing comprehensive and practical approaches to analyzing and improving water flows, uses and consumption at various levels (FAO, 2017b). Since agriculture is the largest water-consuming sector globally, the water productivity of farming systems must be improved for agriculture to be sustainable (FAO, 2012). The concept of water productivity – generally defined as the ratio of generated output to input of water (Bouman, 2007) – is “a key performance indicator of water use in food production systems” (Perry, 1999, Davies and Bennett, 2015). An increase in water productivity can be achieved either through increased output with the same amount of water input, i.e. “more crop per drop”, or through the same output with less water input, i.e. “less water per crop” or a combination of both approaches (Bossio, Geheb and Critchley, 2010; Molden and Sakthivadivel, 1999; Prochnow et al., 2012; Renault and Wallender, 2000).

1.2 CONCEPTS FOR CALCULATING WATER PRODUCTIVITY

In a broad sense, water productivity measures the value or benefit (product or services) derived per unit of water used. The methodology underpinning the assessment of water productivity has evolved rapidly in recent years. As a result, there are a large number of studies that focus on analysing and improving water productivity in food production systems.

Higher water productivity means that more products and services can be produced with the same amount of water or that the same number of products and services can be produced with less water. Traditionally, the notion of water use efficiency has been commonly used assessing water use in agricultural production systems. However, water use efficiency (WUE) and water productivity (WP) are two different concepts. In general, WUE refers to the ratio (or percentage) of water that is productively consumed by a plant. For example, if the WUE is 80 percent, it means that eight of the ten mm of irrigation water applied to a crop is used through plant root uptake and the rest (two mm) is lost to drainage below the root zone or due to unproductive soil evaporation. As noted previously, WP refers to the ratio of output generated to water consumed. For example, WP is 50 kg/m^3, if 50 kg grain is produced per 1 m³ of water consumed. Moreover, the WP offers a conceptual framework that can be defined using different terms for the numerator (e.g. biomass, harvestable yield, economic value) and denominator (e.g. transpiration, evapotranspiration, irrigation, water inflows) (Molden, 1997).

There are numerous challenges to achieving a consistent and coordinated application of water productivity analysis to complex multi-step production-consumption chains such as livestock-sourced produce. Although the denominator is always the unit of water consumed, various studies utilize different kinds of water use to estimate WP values, including biomass: transpiration; biomass: evapotranspiration; or biomass: water inflows, which makes it difficult to compare water productivity in different livestock production systems (Descheemaeker, Amede and Haileslassie, 2010). Similarly, the variation in the type of output product (e.g. dry meat, fresh meat, protein value, calorific value, etc.), creates an array of WP values.

The key factors to be considered in WP accounting can be summarized as:

• the focus on direct water use in livestock production vs. water demand for production inputs, often referred to as indirect water use, such as for feed crop production;

• the types of water used (i.e. blue water, green water, waste water);

• the inclusion of transpiration vs. evapotranspiration as water input;

• the inclusion of different livestock outputs; and

• the different goals and scales of the studies.

In parallel to the scientific community making use of the water productivity approach initially conceptualized by Molden (1997), two other scientific communities (i.e. the life cycle assessment (LCA) also part of the Life Cycle Initiative whose Secretariat is hosted by UN Environment; and the Water Footprint Network) started somewhat to also focus on efficiency and water productivity.

Provided the proliferation of methods to assess water footprints of products, ISO developed the standard ISO 14046:2016 mostly involving LCA experts.

Building also on ISO 14046:2016, the FAO LEAP Partnership made an additional attempt to harmonize methods to assess water use in livestock production and related supply chains. The three scientific communities were actively engaged in the technical dialogue. Thirty-one experts were selected by governments and other LEAP partners to work together and build common ground on terminology and methodology. The report ‘Water use in livestock production systems and supply chains – Guidelines for assessment (Version 1)’ was launched in 2019 after two face-to-face meetings and a number of reviews by peers.

All LEAP experts agreed that, while the focus of the report was mostly on feed and livestock, the methodology set is also relevant for assessment of other agricultural sectors and their products.

While LEAP built common ground on the methodology to assess blue water scarcity footprint and made an attempt to refine the water productivity framework conceptualized by Molden (1997), no guidance was provided on how to select the approach depending on the specific objectives of the water productivity study. No harmonization in application was hence pursued for water productivity analyses among the water footprinting according to ISO 14046: 2016; the volumetric/virtual water footprint methodology by the Water Footprint Network; and the water productivity assessment framework conceptualized by Molden (1997). In addition, while agreement was found on the classification of water flows in blue and green for water footprint assessments, the suitability of such classification for water flows was questioned for water productivity assessment studies in line with the concept by Molden (1997). The three communities instead agreed that the location and timing of the water input are of critical importance in assessing water use and its associated environmental impacts (Perry, 2014), since the impacts vary largely over space and time (FAO, 2019).

Moving from the outcomes of FAO LEAP process, this report presents the results of a review of livestock water productivity (LWP) studies in order to identify best practices and opportunities for a consistent WP methodology and to suggest application contexts where a water productivity approach is best suited. In particular, the review focuses on those studies that are relevant for sustainable water management and nutrition sensitive agricultural practices at producer level.

The report consists of six sections. Following this introduction, which explains basic concepts (e.g. the definition of water productivity and major challenges in its calculation), the second section (Material and methods) describes the review of studies on water productivity in livestock production systems and provides an overview of categorization criteria. The third section (Results) describes the different water assessment approaches used in the studies and evaluates their effectiveness. The fourth section (Discussion) elaborates on the main challenges in assessing LWP and Section 5 (Conclusions) summarizes the main findings of the review. Finally, in Section 6 (Outlook), the report provides recommendations for advancing the development of water productivity analysis of livestock supply chains worldwide.

2. Material and methods

This review is based on a systematic search and analysis of technical literature on livestock water productivity. It involved an extensive literature search and evaluation of methodologies for assessing water productivity in livestock production systems worldwide. In addition, relevant findings of research organizations, e.g. the International Center for Tropical Agriculture (CIAT), the National Institute of Agricultural Technology (INTA) and Agribenchmark were taken into account in the study (Ríos et al., 2012; Quintero, 2014). The life cycle analysis-based water footprint approach (LCA-WF) aims to quantify the potential impacts generated by a human activity on a wide range of environmental issues (climate change, human respiratory impacts, land use, freshwater, etc.) over the entire life cycle of a product or service. A water footprint WF is the fraction of those impacts that relate to fresh water. The main difference between the LCA-WF and WP approaches is that LCA-WF (indeed, any LCA-based studies) should include environmental impact assessment in addition to volumes of water (inventory), since these do not represent potential environmental problems (Boulay, Hoekstra and Vionnet, 2013). The LCA-WF metric provides an understanding of the pressures exerted by the livestock production system in order to reduce its contribution to water scarcity. The WP methodology measures outputs (products and services derived) in relation to inputs (i.e. volume of water used) to support potential decrease of water used per unit produced by the livestock production systems. Hence, the LCA-WF complements the WP metric. It was decided to include LCA-WF in the review because it provides useful information on potential improvements to water consumption and its environmental impacts, as can be seen in several studies.

The livestock water use studies were screened and selected for their relevance. Because the review focused on water consumption by livestock, we only selected those studies concerned with that purpose. In addition, the accounting of groundwater depletion, adaptation to climate change, and nutritional water productivity in the LWP studies were also reviewed and analysed. A total of fifty studies were selected for the review (see Table A4 in the Appendix to this report), of which all but one were published after the year 2000, the majority in the last decade.

We created a review database, using the following criteria to describe the studies:

• scope and objective(s) of the study (a brief description of the assessment goals);

• assessment approach (references and formulas used in the assessment);

• life cycle approach (reliance on life cycle approach, including ISO standards);

• water flows (description of the water inputs and outputs);

• livestock species included in the studies and the main findings;

• system boundaries; and

• databases and modelling (description of the databases and models used).

The LWP studies database was then used to review and analyse the LWP studies with regard to their scope and objectives, assessment approach, system boundaries, livestock species, water flows included or excluded, and accounting of groundwater depletion, water scarcity, adaptation to climate change, and nutritional water productivity values. We also identified commonly used databases and modelling tools, and reviewed how the studies addressed uncertainties that can originate from the choice and use of input data and models for the analysis.

3. Results

The review identified clear differences in the scope and objectives, methodological approaches, water flows accounting, system boundaries, and modelling tools and databases used in water productivity assessments of livestock production systems. The main differences and issues arising from the review are discussed below.

3.1 OBJECTIVES OF THE STUDIES

The livestock water productivity studies were reviewed for their main objectives and scale of analysis, ranging from farm- to regional/national to global. The main objectives of the studies were the quantification of water flows (5 out of 50), impact assessment (11 out of 50), method development (9 out of 50), improvement of water productivity (9 out of 50), and raising awareness (4 out of 50) (See Figure 1). Some of the studies (14 out of 50) had other main goals, for example the analysis of spatial variability of livestock water productivity (Haileslassie et al., 2009) or the comparison of conventional and organic farming systems (Palhares and Pezzopane, 2015).

Figure 1 demonstrates that the five LWP studies that focused on the quantification of water flows were all conducted at the farm scale. The nine impact assessment-focused studies were conducted from the farm scale to the regional scale. Studies focused on method development were conducted at all scales. Two of the studies, one at the regional scale and one at the farm scale, had a joint focus on Impact assessment and method development. The studies concerned with improving water productivity were conducted exclusively at the farm level (See Table 1). Two of these studies included method development among their objectives. The four studies focused on raising awareness ranged from the national scale to the global scales; one of these also included an objective on method development.

Table 1 describes the objectives and results of the nine studies whose main focus was the improvement of water productivity in livestock production systems.

3.2 ASSESSMENT APPROACH

Figure 2 classifies the LWP studies according to the basic water input and water output formula used, i.e. input over output or output over input, together with the scale of the analysis. Farm output over water input is defined as water productivity (WP) accounting (i.e. kg/m³), and water input over farm output is defined as water footprint accounting (WF) (i.e. m³/kg). The classification indicates that 35 studies used the WF accounting definition and 15 studies used the water productivity definition. The WF accounting studies were conducted at all three scales, from farm- to national/ regional to global. The WP studies were conducted mainly at the farm scale, with two exceptions: Renault and Wallender (2000), global scale, and Singh et al. (2004), regional and farm scales.

The review also analysed the specific water flows used to calculate water input in the livestock water productivity studies (See Figure 3). The inclusion of these water flows was handled differently in the various studies (see Section 3.4). Details can be found in the study papers. Water consumption for the transport of feed, production of fertilizers/pesticides and production of all building materials was not included, due to its small contribution to water input. Off-farm water flows are marked with dashed lines in Figure 3. The terminology follows standardized water input terminology (see Table A1 in the Appendix).

3.3 LIFE CYCLE APPROACH

Fifteen of the LWP studies used a life cycle approach, according to ISO 14044, or included three to four LCA stages in the assessment.

LCA-based methods are used to assess water use along the entire livestock production value chain (excluding distribution, livestock product use stage, and end-of-life). Water flow is characterized in relation to local water stress scarcity in the areas where water use occurs. The LCA water footprint inventory analysis quantifies inputs and outputs related to water use for products, processes or organizations (ISO 14046:2014). The final results of the studies are reported and compared in terms of water impact equivalents (H_2O-e) per unit produced, i.e. litre H_2O-e / kg. An example for the water scarcity impact assessment (3rd stage of LCA) is the reporting and comparing of quantified water in terms of water impact equivalents e.g. 172 ± 53 L H_2O-e scarcity-weighted water/kg wholesale pork of an Australian national herd (Wiedemann, McGahan and Murphy, 2017b).

Figure 4 classifies the 15 LCA-based studies according to the water impact assessment method used and the scale of analysis. Ten studies distributed over the farm, regional/ national and global scales used a water scarcity stress index to measure the contribution of water consumption to water scarcity (e.g. based on Pfister, Koehler and Hellweg (2009). Five studies did not carry out water impact assessments, but conducted a life cycle inventory (LCI) analysis. One of the studies in this group (Wiedemann, 2014) additionally assessed changes in consumptive water use in response to a land use change from grassland to forest.

3.4 WATER FLOWS

Interestingly, the review identifies clear differences in the water flows included or excluded in the calculation of WP of livestock production systems. Most of the LWP studies under review can be divided into three water flows categories (See Figure 5): technical water, evapotranspiration water stemming from precipitation and waste water.

Fifteen LWP studies were solely concerned with technical water. One study only included evapotranspiration water stemming from precipitation (van Breugel et al., 2010). The other 34 studies included both evapotranspiration water from precipitation and technical water. Eleven LWP studies considered waste water. Peters et al. (2010) took water quality aspects into account as well (runoff and animal urination/excretion) to classify water use/LCI data in the Australian red meat sector.

The 34 studies that accounted for evapotranspiration water stemming from precipitation were further characterized by the inclusion of either evapotranspiration or transpiration as a water input (See Figure 6). Only four studies at the farm level used water transpired by feed (transpiration) as the denominator, while the rest used water evapotranspired by livestock feed production. These four studies applied the methodology of Prochnow et al., 2012), which intentionally deviates from commonly used methods for estimating water use in agriculture. The authors define water input as the sum of plant transpiration originating from precipitation plus all water inflows via technical means plus an additional quantity of indirect water use. In contrast to commonly used methods, Prochnow et al. (2012) excludes evaporation and includes transpiration as the denominator in the assessment of water productivity on a mixed crop-livestock farm. Furthermore, the four studies included only the fraction of irrigation water that is subject to infiltration or evapotranspiration (e.g., Chapagain and Orr, 2008), another deviation from commonly used methods. All water withdrawn for the farm’s sake was considered water input, not just transpired irrigation water. Irrigation water withdrawal, distribution, and application are technical processes partly or entirely controlled by the farmers.

Prochnow et al. (2012) suggested that all irrigation water managed by the farmers is assumed to be inputs to the production process. The authors argue that the inclusion of technical water as water input enables the farmers to assess and reduce any unproductive water losses in their production systems. Furthermore, the farmers pay for all withdrawn water, not only for the fraction used by the plants. For example, they have to pay e.g. for the technical infrastructure of the irrigation structure, the energy to pump the water and, potentially, for the withdrawn water – improvements in these elements can translate into direct cost savings. On the other hand, reductions in irrigation technical water supply does not necessarily lead to ‘real’ water savings as this depends on the return flow to reusable (fresh good quality groundwater) or non-reusable sources (e.g. saline groundwater) (Perry, Steduto and Karajeh, 2017).

Interestingly, the LWP studies under review also included different water outputs as a numerator for quantifying livestock water productivity. See Table A2 in the Appendix for an accounting of different water outputs covered in the water productivity studies.

3.5 LIVESTOCK SPECIES

Nearly half (46 percent) of the LWP studies focused on beef cattle and dairy farms. Sheep, poultry, swine and goats were investigated in more than 5 percent of the studies – sheep were studied in 11 cases, poultry were studied in eight cases, swine were studied in seven cases, and goats in five cases (See Figure 7). Two studies (Haileslassie et al., 2009; Descheemaeker, Amede and Haileslassie, 2010) looked at mixed-crop-livestock farming systems, although they gave no indication of the specific animals involved, whereas three studies (Hoekstra and Chapagain, 2006, 2007; Hoekstra et al., 2011) were overview studies that calculated, for example, the volumetric water footprint accounting studies of nations and therefore did not include a breakdown of individual animal species.

Figures 8-11 summarize the main results of the LWP studies with regard to the livestock species concerned. Unfortunately, methodological differences (e.g. using different outputs and inclusion of transpiration or evapotranspiration or grey water in water input) produce non-comparable results. Details can be found in the study publications. Information on the number of studies conducted in different countries around particular livestock species are included as well (studies presenting an overview of multiple nations were excluded).

Table 2 lists the countries and number of studies of water productivity for different livestock production systems. Beef production studies were carried out in the following countries: Australia (five studies), United States (two studies), Ethiopia (one study), Canada (one study), China (one study), Germany (one study), Morocco (one study), Nile basin (one study), United Kingdom of Great Britain and Northern Ireland (one study), Uruguay (one study). Five studies presented an overview of multiple nations. Eleven of the eighteen beef production studies were conducted in countries/regions that are among the top seven producers of beef (United States, China, Australia, and European Union) according to data from the USDA (2017). See Figure 8.

The sum of the used water flows in the LCA-based studies by Peters et al. (2010), Wiedemann (2014), and Wiedemann et al. (2015a, 2016a) report the water inventory values quantified as inputs and outputs related to water use for products, processes or organizations (ISO 14046:2014) (See S ection 3.3).

The dairy farming water productivity studies were carried out in the following countries: Germany (four studies), India (three studies), Australia (one study), Belgium (one study), Canada (one study), South Africa (one study), United Kingdom of Great Britain and Northern Ireland (one study), Panama (one study), Nicaragua (one study), United States of America (one study). Seven studies presented an overview on multiple nations. Six of the 15 dairy farming studies were conducted in countries belonging to the top nine producers of milk (India, Germany and the UK) (FAOSTAT, 2017). See Figure 9.

The sheep production studies were carried out in the following countries: United Kingdom of Great Britain and Northern Ireland (two studies), Australia (five studies), Canada (one study), China (one study), Ethiopia (one study), Nile Basin[1] (one study). Four studies gave information on multiple nations. Seven studies presented an overview on multiple nations. Eight of the twelve studies were conducted in countries belonging to the top ten producers of sheep worldwide (China, Australia and UK) (FAOSTAT, 2017). See Figure 10a.

The poultry production studies were conducted in the following countries: Australia (one study), Brazil (one study), Canada (one study), China (one study), Ethiopia (one study), Germany (one study), United Kingdom of Great Britain and Northern Ireland (three studies), USA (one study). Four studies presented an overview of multiple nations. Three of the studies were conducted in countries belonging to the top four producer countries (China, United States and Brazil)[2] (FAOSTAT, 2017). See Figure 10b.

The studies by Wiedemann et al. (2015b, 2015c), Wiedemann, McGahan and Murphy (2017a) and Ridoutt et al. (2012) report the water inventory values, quantified as inputs and outputs related to water use for products, processes or organizations (ISO 14046:2014). The final results of the studies are reported and compared in terms of water impact equivalents (H2O-e) per unit produced (see Section 3.3).

The swine production studies were carried out in the following countries: Australia (two studies), China (one study), United Kingdom of Great Britain and Northern Ireland (one study), USA (one study). Four studies presented an overview of multiple nations. Two of the swine production studies were conducted in the main swine-producing countries (China and United States) (FAOSTAT, 2017). See Figure 11a.

The goat production studies were carried out in the following countries: China (one study), Ethiopia (one study), Nile Basin (one study). Four studies presented an overview on multiple nations. China and Ethiopia are among the top ten producers of goats (FAOSTAT, 2017). See Figure 11b.

Intensity of the animal production system in the studies

Seven studies defined the production systems under examination as involving intensively managed agriculture (e.g. Beckett and Oltjen, 1993; Palhares, Morelli and Junior, 2017 or Wiedemann et al., 2015a) and eight studies were concerned with different levels of farm intensity, e.g. intensive, grazing and small-scale farms (e.g. Sultana et al., 2015) or organic and conventional farms (e.g. Palhares, Morelli and Junior, 2017). However, most of the studies did not define the management intensity of the animal production system under examination. Of note is the fact that Mekonnen and Hoekstra (2012) found a difference in water productivity on intensively and extensively managed farms. Although intensive animal production systems often used less water than extensive systems, there was a greater volume of grey water in the intensive systems (Mekonnen and Hoekstra, 2012). For this reason, the definition of the level of system intensity could provide additional key information in livestock water productivity studies.

3.6 SYSTEM BOUNDARIES (INCLUSION OF WATER FLOWS)

The review analysed the comprehensiveness of the scope of the LWP studies and their definition of system boundary. Of particular interest were the production inputs included in the assessment. We were concerned with the extent to which the studies focused on farm-level livestock production without reference to the water flows tied to production inputs generated outside of the farm boundary.

Unfortunately, system boundaries were not always clearly documented. Over half of the studies (58 percent) defined the system boundaries as ‘cradle-to-farm gate.’ Fifteen percent set ‘country’ as the boundary. ‘Farm + processing’ was defined as the boundary in 18 percent of the studies (See Figure 12).

Thirty-two of the studies included water flows linked to purchased feed (See Table 3). Eighteen studies did not include such flows; these were mainly farm-level studies and reflect the fact the feed is often produced on-farm (See Table 3 and Figure 13). It should be noted, however, that this is not common to all farming systems. According to FAO (2016b), the use of purchased inputs is often found in dairy and beef production systems in Southern Africa, North America, South America and Europe.

Several studies included water flows linked to activities beyond feed processing. Twelve of the studies included water flows for meat and milk processing. Three studies included electricity, fuel, fertilizers and dairy chemicals (Ridoutt et al., 2010; Sultana et al., 2014, 2015). Two studies included water demand for farm buildings (Eady, Viner and MacDonnell, 2011; Döring et al., 2013)

3.7 DATABASES AND MODELLING

The LWP studies used a variety of databases and models, both existing and purpose-built. Key variables included farm data, data on plant parameters, data on water withdrawal, climate data, soil data and international trade data. Many studies used LCA databases such as ecoinvent (Ecoinvent, 2016) and GABI (GABI, 2016). Software and models were applied to model evapotranspiration or transpiration, feed intake and drinking water demand in livestock. A list of all databases and models/ software used in the studies can be found in Table A3 in Appendix A.

3.8 ACCOUNTING FOR GROUNDWATER DEPLETION, WATER SCARCITY, ADAPTATION TO CLIMATE CHANGE AND NUTRITIONAL WATER PRODUCTIVITY

Groundwater

The LWP studies took groundwater depletion into account at various levels of complexity. Srairi et al. (2016) found limited pressure by livestock on groundwater in dual-purpose cattle systems in northern Morocco since the animal production relied mainly on precipitation and/or virtual water contained in off-farm feed resources (purchased feed). Meul, Nevens and Reheul (2009) calculated a specific indicator to assess whether farmers used rainwater, surface water or shallow groundwater as alternatives to deep groundwater and drinking water (usually retrieved from purified deep groundwater).

Water scarcity assessment

Palhares and Pezzopane (2015) applied the Blue Water Scarcity Index (BWSI) of Hoekstra et al. (2012) to identify areas of unsustainable water consumption violating environmental flow requirements (BWSI>1), as well as the fraction of water use occurring in such areas. The index thus sums the water volumes used in areas with BWSI > 1. Wiedemann et al. ( 2015a, 2015b, 2016a, 2016b), Wiedemann, McGahan and Murphy (2012, 2017a, 2017b) and Ridoutt et al. (2010) used the Water Stress Index (WSI) of Pfister et al. (2009), which is a method for assessing the environmental impacts of freshwater consumption based on the withdrawal-to-availability ratio. The indicator is scaled between 0.01 and 1 and is highly correlated with the BWSI. It includes a monthly variability factor for water availability based on precipitation patterns. The method further considers damages to human health, ecosystem quality, and resources. The final results of the studies were reported and compared on the impact equivalents (H2O-e) per unit produced (See Section 3.3).

Climate change

Only two of the studies looked at adaptation to climate change. Wiedemann (2014) considered using afforestation on farms to mitigate climate change, but determined that land use change leads to an increase in consumptive water use. Haileslassie et al. (2011b) calculated the water productivity of dairy cow production and analysed the extent to which improving LWP could increase a farming system’s resilience to climate change.

Approaches enabling assessment of nutrients produced per drop of water use

As described earlier in the Section 1.2, water productivity assessment offers a conceptual framework for measuring the value or benefit (products or services) derived per unit of water used. Variation in the type of output product used (e.g. dry meat, fresh meat, protein value, calorific value, etc.) creates an array of WP values.

This section describes approaches that enable us to assess nutrients per drop. The purpose was to understand the extent to which the approaches have been used for assessing alternative feeding systems for livestock or policies on sustainable food systems.

Four studies calculated nutritional water productivity, which determines nutrient-based output per unit of water use. One of these studies was conducted on a global scale (Renault and Wallender, 2000) and three at the farm scale (Prochnow et al., 2012; Drastig et al., 2016; Krauß et al., 2015a). Renault and Wallender (2000) calculated nutritional water productivity to account for the main nutrients needed by humans. Prochnow et al. (2012), Drastig et al. (2016), and Krauß et al. (2015a) calculated water productivity on metabolizable food energy base. The food energy output was calculated from the amount of food commodities sold and their specific food energy content. However, none of these studies assessed alternative feeding systems for livestock or policies on sustainable food systems.

1 Burundi, Democratic Republic of the Congo, Egypt, Eritrea, Ethiopia, Kenya, Rwanda, Sudan, Tanzania, and Uganda

2 The fourth country is the Russian Federation.

4. Discussion

It is evident from the review results presented above that there was no consistency in the methods and approaches used to assess water productivity in livestock production systems. The studies had various objectives, ranging from improving water productivity, to impact assessment, to raising awareness. They were concerned with different sources of water. Some of the studies chose to include background processes as water input, while others did not. System boundaries were seen by some as being at the level of the farm, and by others as covering the entire supply chain. Different studies treated the inclusion or exclusion of water stemming from precipitation in different ways A summary of the studies is provided in Table A4 in the Appendix.

4.1 GOAL OF STUDIES

Despite some efforts to improve the consistency of LWP assessments, there is still a lack of clear consensus as to how this should be done. The assessment approaches fall into three main categories:

• volumetric/virtual water footprint (WFPa), e.g. Hoekstra et al., (2011) based on the virtual water concept (Allen, 1998);

• water scarcity footprint (WFPb) LCA-based/ISO 14046:2014;

• water productivity (WP) e.g. Rockström and Barron, (2007); Descheemaeker, Amede and Haileslassie (2010); Molden et al. (2010); Kebebe et al. (2015); Haileslassie et al. (2009).

Most of the LWP studies whose objective was raising awareness and impact assessment used the water input over output definition to calculate water productivity (See Table 4). This includes all studies using the ‘WFPa’ and ‘WFPb’ methods. About 15 of the studies used output over input to calculate the water productivity. All of these studies, used the ‘WP’ method.

Five of the WFPa studies focused on awareness raising and were conducted at the national and global scales. Wichelns (2017) stated that a volumetric water footprint, which does not account for water scarcity, can provide meaningful guidance on water policies, investments and water allocations. It can also be used to compare different water flows occurring in a small region. Four WFPa studies were conducted at the farm level. Ríos et al. (2012) carried out the first volumetric water footprint calculation of dairy farming in a region in Nicaragua, and Quintero (2014) calculated the volumetric water footprint of milk production on farms in Panama with high, medium or low levels of technology. Palhares and Pezzopane (2015) assessed the volumetric water footprint of a conventional and an organic dairy production system and identified the components and processes that used the greatest amount of water. Palhares, Morelli and Junior (2017) determined the volumetric water footprint of beef feedlot to farm gate and evaluated the impact of roughage concentrate ratio on the green water footprint.

Eleven WFPb studies focused on impact assessment and were conducted at the farm, regional and global levels. The main purpose of these studies was to quantify water consumption throughout the life cycle of livestock products and to evaluate its potential impacts on the environment with respect to regional water scarcity. The studies examined technical water use along the value chain to calculate the local impacts of water scarcity (Pfister et al., 2009). Following Wichelns (2017), these impacts and potential remedies must be evaluated at local and regional levels by scientists and public officials charged with determining the policies and investments needed to ensure the wise and sustainable use of water resources.

Most of the water used in agriculture comes from precipitation, which in the LCA studies is not generally considered to have an environmental impact (the impacts are mostly associated with land use). Hence, the LCA-based studies focused on the potential environmental consequences of using technical (blue) water. Although not considered in most of the LWP studies, it may be possible to achieve an improvement in water productivity by reducing the use of technical water and using even more precipitation water then previously.

Eight of the WP studies focused on improving water productivity, taking into account both technical water and precipitation. These studies were conducted exclusively at the farm scale. Following Ran et al. (2016), multiple benefits derived from livestock can be included in the assessment of water use utilizing the WP method, which can include the assessment of farming measures or a combination of measures. According to Descheemaeker (2012), livestock water productivity can be improved by:

• improving feed quantity and quality;

• improving animal health;

• increasing access to drinking points;

• reducing unproductive water losses;

• improving marketing of livestock products;

• increasing the use of precipitation water for feed production.

4.2 INCLUDING OR EXCLUDING BACKGROUND PROCESSES IN WATER INPUT

A key consideration is whether to include only on-farm water consumption in the assessment of livestock water productivity or to include water consumption throughout the entire supply chain.

Including or excluding background processes as part of water input

The LWP studies take various approaches to the relevance of purchased feed, fertilizers, pesticides, antibiotics, and building of stables in assessing the water consumption of livestock. Some studies included water use from off-farm plant production processes on the global and national scales (e.g. Hoekstra et al., 2011; Hoekstra and Chapagain, 2006; Zeng et al., 2012; Owusu-Sekyere, Jordaan and Chouchane, 2017), the national and regional scales (e.g. Sultana et al., 2015; Brown, Schreier and Lavkulich, 2009; Atzori et al., 2016; Hoekstra and Chapagain, 2007) and the farm scale (e.g. Palhares and Pezzopane, 2015; Krauß et al., 2015a, 2015b; Drastig et al., 2016). Other studies followed the ISO 14046 standard, and sum-up water flow as part of Inventory Analysis (LCI) (See Figure 13). These studies don’t report the sum of total water used but report only the numbers that present water impact equivalents expressed in litre H2O-e (Wiedemann et al., 2012, 2015a, 2015b, 2015c, 2016a; Wiedemann, McGahan and Murphy, 2017a, 2017b; Ridoutt et al., 2010).

Including or excluding water for meat/milk processing as part of water input

The studies also differ in their treatment of meat/milk processing in the water consumption of livestock. Ten studies included water used in meat/milk processing and purchased feed as an input (e.g. on the global and national scale: Hoekstra et al., 2011; Hoekstra and Chapagain, 2006; Chapagain and Hoekstra, 2003, 2004; Chapagain and Orr, 2008). At the farm level, Prochnow et al., 2012, Palhares and Pezzopane, 2015, Wiedemann et al., 2015b and Wiedemann, McGahan and Murphy, 2012, 2017a, 2017b included water use from meat/milk processing and purchased feed as an input. Two studies included meat and/or milk processing but not purchased feed as a water input (Drastig et al., 2010; Becket and Oltjen, 1993). Other studies investigating meat or milk production included neither purchased feed nor meat/milk processing as a water input (e.g. Atzori et al., 2016; Palhares, Morelli and Junior, 2017; Eady, Viner and MacDonnell, 2011).(See Figure 13).

4.3 CONSIDERATION OF PRECIPITATION

“Regarding the [feed production process], most of the grain and fodder crops used in the three red meat supply chains we studied in Australia are produced by dryland cropping. In other locations, where surface water supplies are more readily available, such as the USA, irrigation of cattle fodder is more common. So, whereas the treatment of rain is a methodological issue relevant to all studies relating water use to the production of red meat, the availability of irrigation water can be characterized as a fundamental difference between the infrastructures of red meat production systems in different locations” (Peters et al., 2010).

The LWP studies took a range of approaches to including precipitation in the water consumption of livestock (See Figure 5). Some studies focused on specific aspects where precipitation was not relevant, e.g. water demand in dairy farm buildings (Döring et al., 2013) or the effects of irrigated pasture management and intensification of on-farm production parameters (Beckett and Oltjen, 1993); these studies excluded precipitation. LCA studies also excluded the water flows stemming from precipitation (e.g. Peters et al., 2010; Wiedemann et al., 2015a, 2015b, 2016a, 2016b; Wiedemann, McGahan and Murphy, 2012, 2017a, 2017b). Ridoutt et al. (2010) make the argument that flows stemming from precipitation may not be relevant to potential impacts associated with water scarcity.

According to Peters et al. (2010), a hydrology-based approach to calculating rain inputs to livestock production may provide a better estimate of the water flows stemming from precipitation’s contribution to purchased feed. The typical metabolic calculations include water needed for the maintenance of vegetation, which maintains soil structure and prevents erosion, rather than just the metabolic needs of livestock.

The rest of the LWP studies included precipitation water in the analysis. In agriculture, most water productivity studies aim to optimize the use of added technical water resources, including available precipitation water. From a hydrological perspective, this distinction is not ideal, since the resources (technical water and water stemming from precipitation) are not mutually exclusive. Water flows from one source to the other. However, it is still useful to make the distinction since these two resources are managed differently and their use impacts the environment in markedly different ways (Ran et al., 2013). According to Lannerstad (2012), livestock water figures must be analysed from both a green and a blue perspective. Ridoutt and Pfister (2010) argue that the potential harm associated with consuming green water derived from natural rainfall onto agricultural lands is not equivalent to that associated with blue water withdrawn from surface and groundwater resources. A shift in thinking about water resource development and management is needed, including around the question of bridging the strict division between rain-fed and irrigated agriculture (Rockström et al., 2010).

Green water on pastures

In the case of grazed pastures, the selection of water flows included in water consumption needs to be further considered. One approach would take all irrigation water and the evapotranspiration of the entire pasture of field-grown feed systems into account. Another approach would only include the water used to produce the consumed feed. The second method is more often found in the LWP studies, assuming that the ungrazed share of the pasture is outside the system boundaries.

4.4 INCLUDING TRANSPIRATION OR EVAPOTRANSPIRATION AS WATER INPUT

The LWP studies take a variety of approaches to including transpiration or evapotranspiration as inputs to the water consumption of livestock. The issue of how to deal with soil evaporation and transpiration from infiltrated precipitation is highly controversial among scientists concerned with estimating water use in plant production. Hydrologists balance water inflows and outflows at different scales, such as in fields or watersheds, and thus have to include evapotranspiration (e.g., Molden and Sakthivadivel, 1999). From an agricultural perspective, many scientists consider either evapotranspiration (e.g., Peden, Taddesse and Haileslassie, 2009; Descheemaker, Amede and Haileslassie, 2010) or transpiration (e.g., Bouman, 2007; Moore, Robertson and Routley, 2011) when evaluating water productivity at various scales (Bessembinder et al., 2005). The virtual water concept generally includes evapotranspiration (e.g., Hoekstra and Hung, 2002; Chapagain and Hoekstra, 2003, 2004; Chapagain et al., 2006). LCA-based studies aim at environmental impact assessment and generally exclude precipitation (Peters et al., 2010) or include only the difference between evapotranspiration of the crop and a reference vegetation: “Change in evaporation caused by land-use change is considered water consumption” (ISO14046:2014).

Four of the LWP studies included only transpiration as a water input to livestock production (Prochnow et al., 2012; Krauß et al., 2015a, 2015b; Drastig et al., 2016). In WP studies, a distinction is made between water transpired by feed plus the amount incorporated in the plant, and water evaporated from soil and free water surfaces (Haileslassie et al., 2011b). The unproductive transpiration of weeds is not mentioned in LWP studies. For calculating the farm water productivity (FWP, Prochnow et al., 2012), it is suggested to include only the fraction of precipitation that contributes to plant biomass generation. This fraction corresponds to the transpiration of the feed crops. The rationale is that the total amount of precipitation is the product of a natural process over which farmers have no influence. They can only affect, within certain limits, the fraction of precipitation that infiltrates into the soil and how much of this fraction is transpired by plants. Prochnow et al. (2012) excluded soil evaporation from the water input as it is not involved in biomass generation and should be minimized.

In the WFPa-based methods, evaporation is considered the unproductive part of evapotranspiration and, as a ‘loss,’ it is recommended to include it in the calculation. The idea is that all water use should be captured in the equation. All improvements resulting from reducing unproductive evaporation are reflected in volumetric/virtual water footprint accounting studies (e.g. Hoekstra et al., 2011).

The use of different definitions of water productivity (biomass/transpiration, biomass/ evapotranspiration, biomass/water inflows) (Bouman, 2007; Cook, Andersson and Fisher, 2009), results in meaningful accounting differences.

4.5 INCLUDING DIFFERENT LIVESTOCK OUTPUTS

The LWP studies also differed with regard to the inclusion of livestock outputs (See Table A2 in the Appendix). These outputs can be grouped into three categories:

• in physical terms as mass of livestock products, (e.g. kg beef (meat), ton animal end of its life span, kg fresh meat, live weight, carcass weight, hot standard carcass weight);

• total food energy contained in the products of the farm, (e.g. output energy, food protein);

• on a monetary basis as total farm revenues (e.g. output revenues).

The use of monetary values to unify the livestock outputs can result in misleading comparisons of the indicators between areas with differing market conditions. Standard definitions and methodology are needed (Haileslassie et al., 2009; Peden, Taddesse and Haileslassie, 2009; Descheemaeker, Amede and Haileslassie, 2009). For large ruminants and swine, the system boundary and the reference flow unit should align. Therefore, if the study extends from cradle-to-farm gate, the reference flow is live weight. If the study extends to meat processing, the unit is going to be either bone-in or boneless meat, and this should be clarified to ensure that the mass of livestock products is correct.

4.6 ADDRESSING UNCERTAINTIES

Assessments of complex systems are generally affected by uncertainty, which can be classified as input data uncertainty, model uncertainty and choice uncertainties, which are usually not reported in LCA studies (Verones et al., 2017). The same holds true for water productivity or water footprint studies. A recent UNEP report on guiding LCA (Frischknecht and Jolliet, 2017) suggested reporting quantitative uncertainty data whenever possible, while acknowledging the fact that this is not practicable in most cases. The report further proposed that the uncertainty induced by variability (e.g. by using country or annual average information) should be reported separately from other uncertainties in order to identify the potential to improve the assessment with more detailed models.

Input data uncertainty refers mainly to measured or modelled parameters retrieved from other studies and includes, for example, precipitation, which can vary significantly when modelling on global scale (e.g. Scherer and Pfister, 2016). Model uncertainty adds uncertainty on top of the input data, as discussed in Lassche, 2013 and Scherer and Pfister (2016), since different models provide different results. Pfister et al. (2011) provide lower and upper estimates for irrigation water consumption for the global crop production model, which even on a global total of irrigation water demand, deviate by more than a factor of two. It mainly reflects the model uncertainty of irrigation intensity. Based on these and other results, water inventory flows have been assigned a high uncertainty by default (in the range of +/-40 percent for the 95 percent interval) in the largest LCA inventory database that includes water flows and balance for ~10 000 industrial and agricultural processes (Pfister et al., 2016).

If water scarcity is assessed, the uncertainty of water flows and scarcity models need to be propagated through the whole model and this might lead to non-significant differences when there is weak data quality (Pfister and Scherer, 2015). However, uncertainty information and contribution to variance analysis can be used to identify where better input data quality is needed to improve the assessment of water productivity in livestock production. The problem mainly applies to livestock supply chain analysis, where better data is often not available or cannot be improved. In the foreground, processes like farm level estimates, improved monitoring and measurement techniques might help to reduce uncertainties and thus improve the robustness of the study.

In summary, it is important to report uncertainties, if possible, quantitatively or at least qualitatively. Additionally, this uncertainty information needs to be included in the assessment and interpretation in order to evaluate the significance of different water accounts and productivities.

5. Conclusions

The livestock water productivity studies under review vary widely in terms of their objectives, methodology, scope and water flows accounting. This review generated additional knowledge to refine the methodology for water productivity analysis in the FAO LEAP guidelines on water use assessment.

The use of the water footprinting WFPa method has succeeded in raising global awareness about the topic of water use in agriculture. Interest in the water footprint grew rapidly after its introduction in academic literature. In 2007, companies, in particular food and beverage companies, became increasingly aware of their water dependence and the water-related risks facing their companies (WFN, 2019).

Aggregated water flows are irrelevant at the global level; local sources and timing are the critical issues for water use and the development of strategies to manage water wisely on farms (Perry, 2014). It is essential that local and regional water users and policymakers assess water use and its associated water scarcity conditions in their domains, and implement appropriate policies, incentives, and strategies to ensure that water is managed judiciously (Wichelns, 2017). Regional-level water impact assessment supports efforts to compare, value, and possibly negotiate quantities and sources of water for on-farm consumption as well as alternative uses. The LCA-based WFPb method can be used to analyse water impacts mainly on a regional scale and taking solely technical water into account. This follows the argument that only technical water flow may be relevant in contributing to local water scarcity. As a third step, the WP method can be applied in the assessment of farming measures to improve precipitation and technical water productivity in livestock production. Strengthening the FAO LEAP guidelines on water use assessment by adding a refined and coherent approach to assessing water productivity in livestock supply chains could lead to a benchmark for water productivity values for specific species and production intensities in specific regions (see Figure 14). Examples of water productivity indicator suites can be found in Prochnow et al. (2012). The authors propose that livestock water productivity be calculated on different output bases (mass, monetary, energy), and that the water productivity of (feed) crops, the level of water utilization, and the specific inflow of technical water are separately reported and assessed.

To inform decisions on nutrition sensitive agricultural practices at the producer level, the authors propose that livestock water productivity be calculated having nutrients as output basis.

We also suggest that:

• Farm water productivity describes the ratio of farm output to water input, where the water input is the total of those water inflows into the farm system that can be assigned to the generation of farm output: the sum of plant transpiration originating from precipitation, which is the fraction of precipitation that contributes to crop growth, plus all water inflows via technical means as well as an additional quantity of water used in the supply chains.

• Farm output is expressed on a mass basis, food energy basis, and monetary basis.

• The degree of water utilization characterizes the relationship between productive water and the total water inflow into the farm system, where productive water comprises those water flows that directly contribute to biomass generation via plant and animal metabolism, i.e. water taken up and transpired by plants, drinking water for animals, and water taken in by animals with feed.

• It is necessary to explore the regional and temporal variation in the water productivity indicators and their range, depending on the farming system. For example, it seems obvious that the indicators will have different values for rainfed or irrigated agriculture and for cash crop farms as compared to mixed crop-livestock systems.

• A matrix of water productivity indicators at farm scale can assist farmers in understanding the water flows and utilization on their farms and in optimizing water use by adapting agronomic measures and improved farm management practices.

6. Outlook

Progress has been made recently in the field of assessing water demand in agriculture, and its related impacts on water scarcity, through the development of ISO 14046:2014 ‘Environmental management – water footprint – principles, requirements and guidelines’ and ISO/TR 14073:2016 ‘Environmental management – water footprint – illustrative examples on how to apply ISO 14046.’ Recently, the Technical Advisory Group (TAG) on Water Footprinting of the Livestock Environmental Assessment and Performance (LEAP) Partnership at FAO produced guidelines to complement the ISO assessment framework with water scarcity impact assessment methods. The development of clear guidelines on water footprinting can support water management solutions through the identification of hotspots of water use in livestock supply chains (FAO, 2019). However, there remain key questions about including different water flows as water inputs, and determining how to reduce uncertainties in data inputs and models used for accounting water flows in livestock production systems.

The treatment of precipitation at the farm level should be further discussed in relation to the development of a consistent and coherent approach to assessing water productivity in livestock production systems. Descheemaeker et al. (2013) stated that it would be useful to think of rain as the ultimate source of water for all agroecosystems. Following this, the improvement of precipitation water productivity should be assessed and precipitation water included in water productivity analysis for livestock production systems. Including water input linked to purchased feed in the assessment is also crucial, due to the fact that excluding these indirect water flows may overstate water productivity. The purchase of feed would then result in higher water productivities, because the water needed to produce the feed and to generate the output is not included in the assessment. A matrix of water productivity indicators at the farm scale can assist farmers to understand the water flows and water utilization on their farms. Using a suite of indicators for WP is problematic for meaningfully aggregating them into one metric. Water productivity can be calculated for the whole farm, for feed crops, and for livestock. Direct water productivity and direct and indirect water productivity should be distinguished (FAO, 2019). Water productivity should be determined for individual inputs and sub-processes within the system (e.g. feed water productivity) and optionally for the overall livestock production system. According to Lannerstad (2012), livestock water figures should also be analysed from a green and blue water perspective. The FAO LEAP Guidelines of the Water TAG propose a method for adding information on the percentage of green and blue water used, with each water productivity indicator seen as part of a suite of metrics (FAO, 2019).

Improving our knowledge about how water is used at the farm level can help us to better understand the global water demand around livestock production (See Figure 14), which will assist in the implementation of international policies to decrease water scarcity.

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