2.2. Study Area and Animal Production System Data
The study area was Lajeado Tacongava watershed (
Figure 1) which is located in the Northeast region of the Rio Grande do Sul State, Southern Brazil. With an area of 149.78 km
2, the watershed is partially comprised of four cities with tradition in agriculture and livestock production: União da Serra, Serafina Correa, Montauri, and Guaporé. Farms with more than 50 fattening pigs and more than 1000 broilers were investigated. Criteria for farms selection were defined according to the environmental license classification [
27] and economic viability.
Figure 1 shows the location of farms in the watershed.
Between June 2019 and March 2020, we surveyed 78 farms (37 pig production and 41 poultry farming). Information related to farm-basic data (name, address, location, family workforce details, agricultural activities), environmental farm conditions (type of soil, water supply, water resources located on the farm, wastewater and solid waste management), and animal production features (current herd, the period of the production cycle, breeding systems, type of diet, initial and finishing weight) was collected.
The herd of pigs located on the farms within the Lajeado Tacongava watershed area ranged from 240 to 1150 head farm
−1cycle
−1, with a total herd of 55,071 head year
−1 for pig. For broiler, it ranged from 7500 to 85,000 head farm
−1cycle
−1 with a total herd of 6,108,600 head year
−1. Animal production is performed in a vertical integration system, where companies define initial and finishing animal weight according to the market demands. The first stages of the animals’ life are neither performed on the farms nor in the watershed. Piglets are born on a farm where they spend 28 days in the weaning stage and 35 days in a farm nursery stage until achieving the weight for starting the finishing stage in the last farm [
28]. In this paper, the first stage of a pig’s life is called pig pre-chain. Broilers, as well, are born in a hatchery and after that, they are transported to the finishing farm.
Figure 2 presents the stages, animal performance indicators, and water flows of the two animal production chains addressed in this study.
Broilers and pigs were considered mixed between males and females. The mortality rate for broilers was considered 3.5% per cycle [
29] and for pigs, it was null in the finishing stage. Feed compositions for fattening broilers (64% maize and 27% soybean meal) [
30,
31] and pigs (75% maize and 25% soybean) [
32,
33] were established for different stages of growth as shown in the
supplementary material (Table S1). Pig pre-chain feed composition for weaning (75% maize and 25% soybean) and nursery (54% maize and 24.3% soybean) were also defined [
28]. Companies provide animal feed to the farms and diets are specific for each stage of life. For this reason, the daily amount of feed and the type of diet were standardized for all farms (
Table S1).
Table 1 shows the input data sources to calculate the water productivity indicators.
2.3. Calculation of Water Productivity
WP was calculated for broilers in the fattening stage (WP
indirect+direct,broiler,Farm) and pigs (WP
indirect+direct,pig,Farm) for pre-chain and fattening production stages accounting for direct and indirect water inflows, according to the FAO [
1] and presented in
Section 2.1.
The boundaries of the system were cradle-to-farm gate which involved feed and meat production at farm level. This study applied a bottom-up approach where farm specific data was used to calculate a detailed WP. In this study, WP was calculated in three references units in order to increase comparability with other studies. They were expressed on a mass basis (WP
indirect+direct,broiler,Mass,Farm (Equation (1)); WP
indirect+direct,pig,Mass,Farm (Equation (2))) (kg Carcass Weight (CW) m
−3), food energy basis (WP
indirect+direct,broiler,Energy,Farm (Equation (3)); WP
indirect+direct,pig,Energy,Farm (Equation (4))) (MJ m
−3) and monetary basis (WP
indirect+direct,broiler,Mon,Farm (Equation (5)); WP
indirect+direct,pig,Mon,Farm (Equation (6))) (R
$ m
−3).
Legend to above equations:
WPindirect+direct,broiler,Mass,Farm is water productivity of chicken meat produced on mass base (kg Carcass Weight m−3);
WPindirect+direct,pig,Mass,Farm is water productivity of pork meat produced on mass base (kg Carcass Weight m−3);
WPindirect+direct,broiler,Energy,Farm is water productivity of chicken meat produced on food energy base (MJ m−3);
WPindirect+direct,pig,Energy,Farm is water productivity of pork meat produced on food energy base (MJ m−3);
WPindirect+direct,broiler,Mon,Farm is water productivity of chicken meat produced on a monetary base (R$ m−3);
WPindirect+direct,pig,Mon,Farm is water productivity of pig meat produced on a monetary base (R$ m−3);
Qdirect+indirect,broiler,Farm is water consumption for broiler in fattening stage production (m3 year−1);
Qdirect+indirect,pig,Farm is water consumption for pig production in fattening and pre-chain stages (m3 year−1).
WP was also reported with fractions of green and blue water consumed (% blue water/% green water) as defined by the FAO [
1]. Water consumption (Q
indirect+direct,broiler,Farm (Equation (7)); Q
indirect+direct,pig,Farm (Equation (8))) was calculated according to the consumed water, assigned to the generation of output for the stages assessed.
Legend to above equations:
Qindirect_direct,broiler,Farm is the total water consumed for broiler purchased feed production + water consumed for broiler production (m3 year−1) considering broiler fattening stage;
Qindirect_direct,pig,Farm is the total water consumed for pig purchased feed production + water consumed for pig production (m3 year−1) considering pig fattening and pre-chain stages;
Q
indirect,broiler,Feed is the total water consumed (evapotranspiration (ET); fresh matter (FM)) for purchased broiler feed production (m
3 year
−1). It was based on the ratio of the yield of the field (cropland) for producing broiler feed and the ET from the field (from harvest of the previous crop through to harvest of the crop) [
1];
Q
indirect,pig,Feed is the total water consumed (ET; FM) for purchased pig (fattening and pre-chain stages) feed production (m
3 year
−1). It was based on the ratio of the yield of the field (cropland) for producing pig feed and the ET from the field (from harvest of the previous crop through to harvest of the crop) [
1];
Qdirect,broiler,Animal is the total water consumed for broiler drinking (m3 year−1);
Qindirect+direct,pig,Animal is the total water consumed for pig drinking in pre-chain and fattening stages (m3 year−1);
Qdirect,broiler,Housing is the total water consumed for services (cooling, cleaning) (m3 year−1) for broiler production;
Qindirect+direct,pig,Housing is the total water consumed for services (cleaning) (m3 year−1) for a pig in pre-chain and fattening stages production.
Feed crop water productivity WP
indirect,Feed of broiler WP
indirect,broiler,Feed and pig WP
indirect,pig,Feed was calculated according to Equations (9) and (10), respectively.
Legend to above equations:
WPindirect,broiler,Feed is water productivity of broiler feed consumption (kgFM m−3);
WPindirect,pig,Feed is water productivity of pig feed consumption (fattening and pre-chain stages) (kgFM m−3).
Water demand for broiler feed produced for supplying pre-chain was neglected because broilers are transported to the farms a few hours after they were born.
WP
indirect,Feed was calculated for crops addressed to animal feed in two different crop rotations produced in three sites located in two crop producer regions (
Figure 3): Center West, Primavera do Leste city (Mato Grosso State—MT) and South, Vacaria city (Rio Grande do Sul State—RS) and Cascavel city (Paraná State—PR). Throughout the paper, cities are abbreviated with RS for Vacaria, MT for Primavera do Leste, and PR for Cascavel.
The first crop rotation comprised soybean (fs–soy) and
safra (fm–
safra) intercropping with fallow and the same crops intercropping with ryegrass (
safra: rm–
safra; soy: rs–soy) where soy is produced one year and in the next year maize is produced in the same field driving to one crop harvest per year.
Safrinha (smf–
safrinha) harvested after soybean (smf–soy) intercropping with fallow compose the second crop rotation which represents two crops harvested per year (soy and maize). As suggested by Flach et al., [
26], modeling water productivity of double cropping was applied in this study. The last crop rotation was not analyzed in Vacaria—Rio Grande do Sul state, because the climate characteristics are not favorable to
safrinha production in the region.
Water consumed for animal feed production (Q
indirect,Feed) was calculated as actual evapotranspiration (ET) of the crops through the modeling software AgroHyd Farmmodel [
20], which is based on the FAO’s 56 dual crop coefficient method [
44]. This method requires calculating (a) the reference evapotranspiration (ET0), (b) the potential crop transpiration (Tc), and (c) the actual transpiration (Tact) from the different datasets for climate, plants, and soil containing regional climate data, plant-specific parameters, and regional soil data. In the calculation presented in this study (d), the actual evapotranspiration of the individual crop is calculated as the sum of Tact and the actual Evaporation (Eact).
- (a)
With regional climate data ET0, a grass reference surface was calculated using the FAO Penman-Monteith equation.
- (b)
To model Tc, the ET0 was adjusted for the individual crop with plant-specific parameters (e.g., the plant-specific basal crop coefficient (K
cb)). Plant-specific parameters are provided in
Table S2.
- (c)
The calculation of Tact incorporates the effect of daily water stress due to water-limited conditions by linking the datasets on plants, soil, and climate on Tc. A water stress coefficient (Ks) incorporated water stress and reduced Tc to Tact. To determine the water stress coefficient (Ks), a simple tipping bucket approach was combined with regional soil and precipitation data. The equation for Tact (mm) applied here was:
For adjustment on specific climatic conditions, the calculated K
cb values were improved using the formula of K
cb,adj
where RH
min is the minimum relative humidity, u
2 the wind speed at 2 m height (m s
−1), and h the mean plant height during the mid or late season stage (m) for 20% ≤ RH
min ≤ 80%.
If the amount of soil water drops below a critical value, the crop is water-stressed [
45]. To calculate the water stress coefficient, values of total available soil water in the root zone, readily available soil water in the root zone, and the root zone depletion are needed. Ks is given by:
where Ks is the water stress coefficient (0–1), Dr is the root zone depletion (mm), TAW is the total available soil water in the root zone (mm), and RAW is the readily available soil water in the root zone (mm). The maximum value of Ks of 1 shows the absence of soil water stress.
The total available soil water TAW (mm) can be calculated by the difference between water content at field capacity θ
FC (m
3 m
−3) and water content at wilting point θ
WP (m
3 m
−3). This value is multiplied by the effective rooting deep Zr (mm).
Soil classification of USDA is available in the modeling system and clay soil was used. For this type of soil, the model considered a soil water content at field capacity of 0.396 (m
3 m
−3) and soil water content at a wilting point of 0.248 (m
3 m
−3) [
44]. The readily available soil water content is described as
p is a tabular value (
Table S2) describing the average fraction of TAW that can be depleted from the root zone, without causing moisture stress for the crop. It can be adjusted with the formula
In order to determine water availability for evapotranspiration, a root zone depletion Dr was calculated using a daily water balance using a simple tipping bucket approach:
where Dri (mm)is the root zone depletion at the end of day i, Dri-1 (mm) the root zone depletion at the end of the previous day i − 1, Pi (mm) the precipitation on day i, Tacti (mm) the actual transpiration on day i, Ii the interception on day i (mm), and DPi (mm) is the water loss out of the root zone by deep percolation on day i.
After heavy precipitation or irrigation, the soil water content in the root zone might exceed field capacity. The difference between the content which exceeded the field capacity and the soil water at field capacity is called deep percolation. Deep percolation is given by
with Pi as precipitation on day i (mm), Ii for the interception on day I (mm), dPi for deep percolation on day i (mm), Dri-1 for water content in the root zone at the end of the previous day, i − 1 (mm), Iri for irrigation on day i, and Tacti for transpiration on day i. For the instant calculation of the values of DP and Dr for day i = 1 were approximated.
The rainfall interception calculation used here was based on the work of von Hoyningen-Hüne [
46] and Braden [
47]. The approach was implemented in several agro-hydrological models of different complexity for the estimation in particular of the interception for agricultural crops, e.g., the physical-based model SWAP [
48]. The authors measured the interception of precipitation for various crops. The general formula for canopy interception proposed is
where I is the intercepted precipitation (mm), P is the gross precipitation (mm d
−1), a is an empirical coefficient (mm day
−1), and cf is the soil cover fraction (1 × 10
−0.
385 LAI (-)). For increasing precipitation amounts, the amount of intercepted precipitation asymptotically reached the saturation amount a × LAI. We assumed a = 0.25 (mm day
−1) for the agricultural crops.
The calculation of the actual evapotranspiration of the individual crop ET(mm) was based on the previous three calculation steps (a, b, and c) of the actual transpiration (Tact) and the calculation of the actual evaporation (Eact) according to the procedures of the FAO 56 dual crop coefficient method [
44]
The actual evapotranspiration (ET) was considered as water consumed for animal feed production (Qindirect,Feed). A polygon with an area of 1 ha was defined as the modeling area for each crop analyzed and it was assumed that maize and soybean were produced at least one year before animal consumption (the year 2018).
Indirect water consumption (ET) was calculated considering the mean annual crop yield (CY) for maize and soy produced in each region (RS, PR, and MT) in a period of 10 years (2008–2018), obtained from the Brazilian Statistics Bureau [
36], as shown in
Table 2. The highest state mean annual crop yield attained for each region in 10 years was assumed to be the potential highest mean annual yield (HY) (
Table 2). The annual mean variation of CY and HY are shown in
Table 2 with the standard variation (SE) and their variation along the years analyzed is shown in the
supplementary material (Tables S3 and S4, respectively).
The sowing period was defined according to the Climate Risk Agricultural Zoning and the soil type was defined according to a normative instruction established by MAPA—Brazilian Ministry of Agriculture, Livestock, and Food Supply [
49]. Soil types for all sites analyzed (
Figure 3) had a clay content higher than 35% [
39,
40], with a classification of clay soil [
50]. Data on sowing and harvest and vegetation period are also shown in
Table 2.
Table 2.
Maize and soy produced on the sites analyzed and crop rotations from 2008 to 2018 (CR: crop rotation, CY: current annual mean of crop’s yield, HY: highest annual mean of crop’s yield, SE: standard deviation).
Table 2.
Maize and soy produced on the sites analyzed and crop rotations from 2008 to 2018 (CR: crop rotation, CY: current annual mean of crop’s yield, HY: highest annual mean of crop’s yield, SE: standard deviation).
Production Region | CR—Main Crop | Sowing Date 1 | Harvest Date | Vegetation Period (days) 2 | Mean CY (t FM ha−1) 3 ± SE | Mean HY (t FM ha−1) 3 ± SE |
---|
Mato Grosso State City: Primavera do Leste | fm—safra | 21 September | 24 January | 125 | 7.6 ± 0.71 | 9.3 ± 1.07 |
fs—soy | 22 October | 15 January | 85 | 3.1 ± 0.77 | 3.8 ± 0.34 |
smf—soy |
smf—safrinha | 16 January | 4 June | 140 4 | 5.7 ± 0.07 | 7.3 ± 1.14 |
Paraná State City: Cascavel | fm—safra | 24 September | 24 January | 125 | 10.1 ± 1.03 | 11.7 ± 1.02 |
rm—safra |
fs—soy | 30 October | 23 January | 85 | 3.4 ± 0.36 | 4.1 ± 0.53 |
rs—soy |
smf—soy |
smf—safrinha | 24 January | 12 June | 1404 | 5.1 ± 1.14 | 7.6 ± 1.20 |
Rio Grande do Sul State City: Vacaria | fm—safra | 15 October | 17 February | 125 | 7.1 ± 1.33 | 10.3 ± 1.83 |
rm—safra |
fs—soy | 15 November | 8 February | 85 | 2.9 ± 0.6 | 4.0 ± 0.53 |
rs—soy |
Climate data, such as precipitation (mm), minimum and maximum temperature (°C), sunshine hours (h), relative humidity (%), and wind speed (km h
−1), was taken in monthly mean values in five climate stations from the INMET (National Institute of Meteorology, Brazil) located near the sites analyzed [
37]. Data recorded on climate stations located in Mato Grosso State (Poxoréo), Paraná State (Campo Mourão; Maringá), and in Rio Grande do Sul State (Santa Maria; Vacaria) were uploaded in the modeling software. The distribution of precipitation per crop cycle had a large variation around the sites analyzed, where availability for summer crops (
safra and soybean) ranged from 1218 mm year
−1 to 2679 mm year
−1 and for winter crop (
safrinha), ranged from 432 mm year
−1 to 994 mm year
−1 [
37]. The annual mean precipitation is presented in
Figure 3.
Alvares et al. [
38] showed that the analyzed feed crop production regions have different climate classifications according to the Köppen climate classification. Vacaria city, in RS, has a climate classification of Cfb (subtropical climate, without a dry season and with a temperate summer); Cascavel city, in PR, has a climate classification of Cfa (subtropical climate, without a dry season and with a hot summer) while Primavera do Leste city, in MT, has a climate classification of Aw (tropical climate, with a dry winter).
Water consumed for animal drinking (Q
direct,broiler,Animal; Q
indirect+direct,pig,Animal) (m
3 year
−1) was calculated according to Palhares [
41]. Water consumed for services (Q
direct,broiler,Housing; Q
indirect+direct,pig,Housing) accounted for water inflows used for cleaning pig [
43] and broiler [
42] facilities and for cooling, which was calculated only for broilers [
42]. It was considered that the cooling system is activated whenever the temperature inside the stable is higher than 24 °C [
29]. According to data on the maximum temperature in the watershed [
37], the system was activated for 1420 h in 2019. The water consumption for animal drinking, cleaning, and cooling is shown in
Table S5.