Research Article

Water Use Efficiency and Influencing Factors in Dairy Farms: A Case Study from Yogyakarta, Indonesia

Meita Puspa Dewi1,4, Tri Anggraeni Kusumastuti2*, Nafiatul Umami3

1Doctoral Study Program, Faculty of Animal Science, Universitas Gadjah Mada, Jl. Fauna No. 3 Bulaksumur, Yogyakarta, Indonesia; 2Department of Livestock Socioeconomics, Faculty of Animal Science, Universitas Gadjah Mada, Jl. Fauna No. 3 Bulaksumur, Yogyakarta, Indonesia; 3Department of Animal Nutrition and Feed Science, Faculty of Animal Science, Universitas Gadjah Mada, Jl. Fauna No. 3 Bulaksumur, Yogyakarta, Indonesia; 4Study Program of Agribusiness, Universitas Nahdlatul Ulama Yogyakarta, Jl. Ringroad Barat, Banyuraden, Gamping, Sleman, Yogyakarta, Indonesia.

Received | April 26, 2025; Accepted | June 12, 2025; Published | June 26, 2025

*Correspondence | Tri Anggraeni Kusumastuti, Department of Livestock Socioeconomics, Faculty of Animal Science, Universitas Gadjah Mada, Jl. Fauna No. 3 Bulaksumur, Yogyakarta, Indonesia; Email: trianggraeni@ ugm.ac.id

Citation | Dewi MP, Kusumastuti TA, Umami N (2025). Water use efficiency and influencing factors in dairy farms: A case study from yogyakarta, Indonesia. Adv. Anim. Vet. Sci. 13(7): 1620-1631.

DOI | https://dx.doi.org/10.17582/journal.aavs/2025/13.7.1620.1631

ISSN (Online) | 2307-8316; ISSN (Print) | 2309-3331

Copyright: 2025 by the authors. Licensee ResearchersLinks Ltd, England, UK.

This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

INTRODUCTION

The demand for fresh milk in Indonesia is rising due to population growth, increased middle-class incomes and heightened awareness of milk’s significance in a healthy diet (Marangoni et al., 2019; Pereira, 2014). Fresh milk production in Yogyakarta Province is 3,774,410 tons in 2024, while the demand for fresh milk in Yogyakarta Province is very high, namely 31,238,153 tons (BPS, 2024). The milk production only meets 12.00% of the total milk needs of Yogyakarta Province. Limited national milk production is a challenge for national dairy farms. Therefore, milk production that has not met the national milk demand is met through a milk import policy, namely importing skim milk (Hendriyanto et al., 2021).

Indonesia’s milk production showed a low productivity rate of 12.88 liters daily (Asmara et al., 2016). Furthermore, Asmara et al. (2016) stated that dairy farming in Indonesia is dominated by small-scale dairy farms with ownership of 2-3 cattle. Badan Pusat Statistik (2023) noted that the number of dairy cattle companies by legal entity in Indonesia in 2020 amounted to 19 PT, then in 2021 amounted to 18 PT. Erwidodo et al. (2022) report that small-scale dairy farmers who are cooperative members contribute 64% to national milk production, while medium-scale farmers account for 28% and large-scale farmers for 8%. One of the main factors influencing the low milk production of small-scale dairy farms is the limited population of dairy cows, especially in livestock centers such as Yogyakarta. In addition, limited natural resources, especially clean water, are also a significant obstacle to increasing milk production. The availability of water plays a very important role in the livestock maintenance process, such as sanitation of pens, livestock drinking water and washing production equipment. Astutik et al. (2020) showed that water scarcity in livestock areas has direct implications for decreasing milk productivity due to decreasing standards of cleanliness and livestock comfort.

Water is one of the important renewable resources in producing milk, drinking water, cleaning equipment, and cleaning livestock on dairy farms (Carra et al., 2022). Suranindyah et al. (2015) emphasized the importance of water usage in the maintenance of dairy cows, particularly during the milking process, which encompasses sanitation procedures before and after milking. Effective milking hygiene practices encompass sanitizing the floor, drinking and feeding troughs, washing the cow, cleaning and drying the udder post-wash, discarding the initial milk flow, and rinsing the floor with water after milking. Abbas et al. (2019) indicated that ongoing drought conditions in Pakistan resulted in a reduction of the lactation period for dairy cows, as well as a decline in both the quality and quantity of milk production. Abbas et al. (2019) stated that farmers regard drought as a significant climatic threat that negatively impacts all aspects of milk production, affecting both the volume and quality of milk generated. Climate change has adversely affected cattle productivity due to contaminated water sources, inferior feed quality, and increased vulnerability to livestock diseases.

The application of eco-efficiency in terms of renewable resources water needs to be considered because water is a critical factor in the productivity of dairy farming. The main idea of eco-efficiency lies in “doing more with less.” This means that greater production levels should be accompanied by less waste and optimal use of input resources (Pérez Urdiales et al., 2016). The livestock subsector supports the Sustainable Development Goals, one of which is SDGs 6, which focuses on clean water and proper sanitation. SDGs 6 on dairy farming, namely ensuring that increasing the efficiency of water use is one of the keys to reducing water stress (United Nations, 2023). Clean water is essential for life, without its adverse effects on the health, food security, and livelihoods of families around the world. The Sustainable Development Goals (SDGs) develop a universal collaboration structure for events related to water and sanitation (Kushwaha et al., 2023).

Sleman District is the largest district, contributing 92.23% of Yogyakarta Special Region Province’s dairy cattle population. The dairy cattle population in Sleman Regency in 2022 amounted to 3,812 dairy cows (BPS, 2022). Dairy cattle production centers in Sleman Regency are located in Cangkringan and Pakem Subdistricts (BPS, 2022). These sub-districts rely on dairy cows for their livelihoods. Farmers own more than 90% of dairy farms in Sleman Regency with 2-4 heads per farmer (Widiati, 2018). Dairy farms in Sleman Regency consist of small-scale businesses (1-2 cattle), medium-scale businesses (3-4 cattle), and large-scale businesses (more than four cattle) (Kusumastuti et al., 2017).

One of the factors contributing to low milk production in dairy farms Sleman Regency is the scarcity of water resources. This is due to the fact that livestock must consume an increased amount of water in addition to the forage feed they consume in order to produce milk. According to Kusumastuti et al. (2017), the average daily milk production of dairy cows in Sleman Regency is approximately 10.95 liters per cow. Whereas for Friesin Holstein dairy cows milk production can reach 25 liters/cow/day (Dezetter et al., 2017). Based on initial observations, during the dry season the average livestock is not washed so that in terms of cleanliness is reduced. The majority of farmers, however, gather rainfall in water reservoirs during the rainy season in order to store it for the dry season. Therefore, it is important to manage water wisely to avoid inefficiency so that it can reduce total production costs.

Water is one of the resources needed in livestock farming, especially in dairy farming. The increasing demand for food limits the demand for water in the livestock sector. Competition for freshwater resources results from increasing population, changing consumption habits, and climate change (Heinke et al., 2020; Cosgrove and Loucks, 2015). Factors influencing water use include livestock ownership, water costs, business experience, formal education, milk sales, and pen type. Livestock density and water demand are strongly correlated. Livestock density is a key factor influencing total water consumption by livestock in watersheds (Kebebe et al., 2015; van Breugel et al., 2010). The cost of water influences the quantity of water use demanded by households and various sectors. Longer farming experience increases monthly milk production, water use efficiency and income generation (Yeamkong et al., 2010). Farmers with higher formal education can maintain high production cows more accurately, resulting in more efficient use of input resources especially water (Yeamkong et al., 2010; Kebebe et al., 2015). Therefore, it is important to know the factors that affect water use in order to use water efficiently. The research objective is to calculate the water usage on dairy farms, analyze the efficiency of water use by dairy cows, and determine the factors that influence the water consumption of dairy farms in Sleman Regency. This research can assist policymakers in formulating policies for managing water availability for dairy cattle in Sleman Regency.

MATERIALS AND METHODS

Research Area

Research occurred from July to November 2024. The multistage sampling method was used to determine the location in this study. Sleman District is the largest district, contributing 92.23% of the total dairy cow’s population in the Special Region of Yogyakarta. The dairy cattle population in Sleman Regency amounted to 3,812 in 2022 (BPS, 2022). Dairy cattle production centers in Sleman Regency are in the Cangkringan and Pakem Subdistricts. Furthermore, the stratified sampling method was used to determine how many respondents were in one sub-district, as shown in Table 1.

 

Table 1: Determination of the number of farmer respondents in each sub-district.

Location	Number of farmers (population)	Percentage number of dairy farmers (%)*	Number of respondents (sample)
Cangkringan	1,346	87.57	246
Pakem	191	12.43	34
Total	1,537	100	280

 

*Calculation of the percentage number of dairy farmers in each sub-district = population of farmers per sub-district/total farmers multiplied by 100%.

 

The sample was determined by purposive sampling of 280 respondents whose initial farmers’ data was obtained from cooperatives in Sleman Regency. The cooperatives taken were Sarono Makmur Livestock Cooperative, Samesta Cooperative, and UPP Kaliurang Cooperative. The data on most of the livestock group members were taken from the three cooperatives. Furthermore, from 280 respondents, the average livestock ownership was; Livestock ownership (heads/farmers) below the average or equal to the low business scale, above the average is in the high business scale The distribution map of livestock groups used in the research and the water sources used are shown in Figure 1. Based on the distribution map of dairy cattle farmer groups and water sources, it shows that in Cangkringan and Pakem sub-districts there are 33 dairy cattle farmer groups, of which 24 groups are in Cangkringan sub-district and 9 groups are in Pakem sub-district. Dairy cattle farmer groups are widely spread in the Cangkringan area with an altitude of 600 meters above sea level and close to river springs. The rivers used as water sources for dairy cattle farms are the Boyong River, Kuning River, Tangkil River, and Bebeng River. Factors that influence uneven distribution are the availability of water (close to springs), altitude and availability of forage for dairy cattle.

 

Data Collection Technique

The current research employed a combination of primary and secondary data sources. Data was collected directly from the field. Participants were surveyed utilizing standardized questionnaires to gather data. Primary data collected from 280 respondents included measurement of water input resources on dairy farms based on business scale, including characteristics of dairy farmers (education, age, main occupation, quantity of family members, and business experience), activities of dairy farm input resource utilization (percentage of farmers who are efficient and inefficient in utilizing water input resources). In addition, livestock ownership, such as the number of dairy cattle, breed, age, and type of dairy cattle (bulls, lactating cows, dry cows, young bulls, young females, male calves, and female calves), was identified.

Direct measurements were taken by sampling five respondents in low-scale businesses and 5 respondents in high-scale businesses. Water use measurements are identified using the flow rate of tap water used by farmers. It was recorded in 1 minute how much water volume was collected in the bucket (liter/second). If the water flow rate is known, the frequency of farmers using tap water is identified so that the amount of water used in a day is known (Kononoff and Clark, 2017; Monteiro et al., 2024).

Measurement of water efficiency is measured from water use and standard water requirements of dairy cattle (L/AU/Day). Water input resources are inefficient if water use is less or more than the standard. Efficiency calculation formula (L/AU/Day) (Nagypál et al., 2020; Monteiro et al., 2024; Pérez Urdiales et al., 2016):

Water use efficiency (L/AU/Day) = Difference between water use and standard water requirements of dairy cattle.

Noted;

Water inefficiency is defined as using less water than the average and standard deviation of water requirements. Water use is considered inefficient if it exceeds the average and standard deviation of water requirements. If water use falls within the average and standard deviation of water requirements, it is categorized as efficient.

Economic efficiency is assessed by minimizing the overall cost of water utilization. This total cost encompasses various factors, including the water systems installation, the construction of water reservoirs, the depreciation of equipment, the acquisition of PVC pipes, and monthly subscription fees for water service. Costs are analyzed on both low and high business operations scales.

Data Analysis

Primary data includes livestock ownership, water use, water efficiency, and total costs, which are then tabulated and grouped into two groups farmers: 1) Low business scale and 2) high business scale. Additionally, an independent sample t-test was employed to examine the differences between the business scales. The difference is substantial (H0 is rejected) when t-count exceeds t-table. If the t count is less than the t-table, we accept H0, indicating no significant difference.

The factors that influence water use are analyzed using multiple linear regression with the following mathematical model:

Y = α + β1X1+ β2X2+ β3X3+β4lX4 + D1 + D2+ e

Description;

Y: Water use (Liters/Day)

X1: Water cost (IDR/Month)

X2: Business Experience (Years)

X3: Formal education (Score)

X4: Milk sales (IDR/Month)

D1 =Dummy of the business scale

0: Low

1: High

D2: Dummy of cage type

0: Individual

1: Colony

α: Intercept (constant)

b: Regression coefficient

e: residual/disturbing error

A classical assumption test is performed to obtain unbiased or BLUE (Best Linear Unbiased Estimation) results to achieve accurate parameter results. The tested classical assumptions include linearity, normality, multicollinearity, and heteroskedasticity.

RESULTS AND DISCUSSION

Characteristics of the Small-Scale Dairy Farms

The management of a community dairy farm is determined by its managers, namely the farmers. To get an idea of the characteristics of the farmers, it is important to know their background in community dairy farming. Based on the average livestock ownership, the scale of the livestock business is divided into 2, namely low business scale (number of livestock ≤ 5 heads) and high business scale (> 5 heads). The characteristics of the farmers observed in this research are displayed in Table 2.

The average age of farmers, both low and high scale, is almost the same, around 53 years. Being relatively old, the awareness of eco-efficiency in input resources is relatively low. This is because the older they get, the longer and slower they are to adopt innovation, and they are more inclined only to carry out hereditary activities. This aligns with findings from Gusti et al. (2022), who stated that older farmers usually have a relatively poor understanding but have an advantage in recognizing the condition of farmland. From the aspects of age and experience, the older the farmer, the more experienced they will be, so they will be better at managing their business. On the other hand, the older the farmer, the more their physical abilities will decline, so they will need help from family members. Farmer characteristics, including education level and household size, age, quantity of extension received, and risk-taking propensity, are internal factors that impact the adoption of innovation. Older farmers do not have the physical strength to implement farming practices that will increase productivity (Mulatmi et al., 2016; Kebebe et al., 2015).

 

Table 2: Characteristics of dairy farmer respondents in Sleman Regency.

Components	Scale of business
	Low (n=195)%	High (n=85)%
Age (Years)	53.52	53.92
Formal education
Elementary School	58.97	57.14
Junior High School	16.92	21.43
Senior High School	23.08	20.24
Higher Education	1.03	1.19
Non-formal Education
Feed processing	26.79	41.18
Livestock maintenance	24.29	27.06
Waste treatment	8.21	5.88
No training	40.71	25.88
Dairy farming experience (years)
<10 years	16.43	2.35
10-20 years	41.79	42.35
>20 years	41.79	55.29
Number of family members
1 to 3	58.57	60.00
4 to 5	35.00	31.76
>5	6.43	8.24
Main occupation
On-farm	75	69
Non-Farm	25	31
Livestock group members	100	100

 

The formal and non-formal education level determines farmers’ ability to manage cattle. The majority of the farmers surveyed have an elementary school education. This aligns with research by Fadillah et al. (2023), which stated that the average education of dairy farmers in Indonesia is elementary school. Small-scale dairy farms are the majority of dairy farmers in Indonesia, with an average of just three dairy cows and a daily production of 14.8 litres per cow.

The average formal education of farmers is elementary school and is supported by non-formal education through extension and training on feed processing, livestock maintenance and waste processing. Based on Table 2, the most informal training attended by high-scale farmers is feed processing (41.18%), while the most low-scale farmers do not have any training (40.71%). This shows that informal training on the application of efficient water use has not been widely carried out on dairy farms in Sleman Regency. There needs to be training on the introduction of water needs in dairy cows, water sources and quality, water saving techniques and livestock waste management. According to Kusumastuti et al. (2017), access to training on high-scale dairy farms was 87% compared to low-scale farms, which was only 53%. According to Mills et al. (2021), training consisting of presentations, live demonstrations, and group discussions helps transfer dairy farm maintenance skills.

Farmers at both scales averaged over 20 years of experience. More extended farming experience indicates better knowledge and skills in farm management. The average business experience of more than 20 years is inherited, so farmers consider livestock a business investment (Kusumastuti et al., 2017; Mills et al., 2021).

The quantity of family members among farmers can influence their business operations, as it determines the availability of labor to assist in their activities. The number of family members will affect labor availability during business operations. The findings indicated that the labor utilized by the respondent farmers in their dairy cattle enterprises was derived from family labor. Kebebe et al. (2015) stated that family labor is very important, considering that low income limits the recruitment of hired labor. In small-scale dairy cattle businesses, family labor is still used to run the business to reduce production costs and maximize income. In agriculture, most of the labor comes from the farmer’s family, consisting of the father as the head of the family, his wife, and children.

The main occupation as a farmer is higher on the low scale (75%) than on the high scale (69%). This is because farmers rely only on dairy farming on a low business scale, owning 2 to 3 heads and low capital. Farmers on a high business scale have other businesses used for dairy capital. Kusumastuti et al. (2017) stated that most dairy farmers in Sleman Regency have a main job as farmers, and the rest have non-agricultural jobs such as sand miners, construction workers, and traders. According to Mills et al. (2021), the income of people in rural areas, the majority of farmers and breeders, is the primary job providing income to meet life’s needs.

The composition of dairy cattle ownership is shown in Table 3. Since the purchase of milk generated by lactation cattle is the primary source of income for dairy farmers, the quantity of lactating cows significantly impacts their revenue. The mean of lactating cows in small and large farms is still relatively low, ranging from 1 to 3. However, if we look at the ratio of ownership of lactating and dry cattles, in high-scale farms, the ratio of ownership of lactating and dry cows is 67.89% and 32.10%, while in low-scale farms, it is 58% and 42%. According to Fauzan (2021), a good percentage of lactating cows is more than 60%, so the livestock business is profitable and efficient. The percentage of lactating cows is an crucial factor in making sure the income of the livestock business. At a large business scale, the percentage of ownership of lactating and dry cows is efficient compared to small-scale dairy farms.

 

Table 3: Composition of dairy cattle ownership in Sleman District.

Components	Scale of business
	Low		High
	Head	AU	Head	AU
Dairy bulls	1.00±0.00	1.00±0.00	1.71±0.99	1.71±0.99
Lactation	1.50±0.65	1.50±0.65	2.94±2.17	2.94±2.17
Dry	1.12±0.32	1.12±0.32	1.39±0.61	1.39±0.61
Young Bull	1.00±0.00	0.50±0.00	1.22±0.44	0.61±0.22
Heifer	1.12±0.32	0.56±0.16	1.83±0.92	0.92±0.46
Male Calf	1.12±0.32	0.28±0.08	1.48±0.77	0.37±0.19
Female Calves	1.23±0.45	0.31±0.11	1.87±0.99	0.47±0.25
Average total ownership	3.42±1.21a	2.29±0.82a	8.63±4.09b	4.83±2.79b

 

a,b: Different superscripts on the same line and category indicate a difference (P<0.05); AU: Animal Unit.

 

 

Water Use in Dairy Cattle Farming

In Sleman Regency, the local community has collaborated to obtain water from the Boyong, Yellow, Tangkil, and Bebeng rivers, which dairy farmers utilize during the research period. A water subscription fee of IDR 100,000 was established at registration, encompassing installation costs. The water flow diagram on dairy farms in Sleman Regency is shown in Figure 2. Based on the water flow diagram (Figure 2), it shows that the water source used is river water, which is piped through PVC pipes to the main reservoir and then distributed to dairy cattle pens (individual and colony pens). Water for household needs is obtained from river water sources, with a small amount coming from muncipal waterworks. The water for dairy cattle is used for various purposes, including cleaning the cages twice daily, cleansing the cows’ udders, and providing drinking water for the cattle. In Glagahharjo Village, Cangkringan, particularly in the Srunen, Singlar, and Gading sub-villages, most farmers do not bathe the cows before milking due to water scarcity.

 

Table 4: Water use on dairy farms in Sleman Regency in October 2024.

Types of water use	Water usage (L/AU/Day)		Water demand standard (L/AU/Day)
	Low	High
Cleaning the pens	5.12a	10.22b	300
Washing of appliances	4.89a	11.23b	200
Washing the cattle	50.20a	55.15b	400
Drinking water	35.44a	40.40b	70

 

a,b: Different superscripts on the same line indicate differences (P<0.05); L/AU/Day: Liter/Animal Unit/Day (Dairy cattle water usage and demand unit per liter per animal unit per day). (Some sources of water demand standards: Kononoff and Clark, 2017; Krauß et al., 2016; Schütz et al., 2021).

 

In contrast, farms in the Boyong area predominantly bathe cattle before milking. According to Monteiro et al. (2024), the classification of water can be based on its source and quality, with blue water referring to drinking water, green water indicating rainwater that has not flowed, and dirty water signifying water that has been used for various purposes but can still be used for other purposes without further treatment. Suranindyah et al. (2015) underscored the pivotal role of water in the management of dairy cattle, particularly in the milking process, where hygienic milking procedures are paramount. After washing, clean and dry the udder, remove the first milk flow, disinfect the floor, water the troughs, and water the floor after milking. According to Golher et al. (2021), reproduction, milk production and feed intake are affected by the status of available water. Water use can also be indirectly impacted by a number of management techniques, including feeding, water availability, livestock husbandry, and water quality.

The water payment for individual farms is based on the amount of water used, with a cost of IDR 500.00 per litre or IDR 5,000.00 per m3 of water. However, unlike farms in colony/group pens, the water payment is only IDR 5,000.00 per month for each farmer. Thus, a water subscription in a colony pen is cheaper than individual pens on each farm. The cost of water subscription (Table 5) for a small livestock farm (1-5 dairy cattle) is IDR 24,929.73/month, which is significantly different from a large livestock farm (>5 head of livestock) which is IDR 30,397.59/month. This is because the number of livestock significantly affects water consumption. The more livestock there are, the more water is used, especially for watering the livestock. According to Krauß et al. (2016), milk contains approximately 85% water, so each milk produced requires two and a half litres of water. The amount of water used for feed represents a more significant portion of dairy water use than the total amount used in the barn.

 

Table 5: Water eco-efficiency in dairy farms in Sleman Regency in October 2024.

Types of water use	Water usage (L/AU/Day)		Water demand standard (L/AU/Day)	Water deficit (L/AU/Day)
	Low business scale	High business scale		Low business scale	High business scale
Cleaning the pens	5.12a	10.22b	300±25.16	294.88b	289.78a
Washing of appliances	4.89a	11.23b	200±26.45	195.11b	188.77a
Washing the cattle	50.20a	55.15b	400±76.37	349.8b	344.85a
Drinking water	35.44a	40.40b	70±8.63	34.56b	29.6a

 

a,b: Different superscripts on the same line indicate a difference (P<0.05). (Some sources of water demand standards: Kononoff and Clark, 2017; Krauß et al., 2016; Schütz et al., 2021).

 

Table 6: Percentage of water reuse of dairy farms in Sleman District.

Livestock business scale	n	Average water reuse (%)	Standard deviation	Sig
Low business scale	195	28a	5.2	0.009
High business scale	85	44b	7.5

 

a,b: Different superscripts on the same column indicate a difference (P<0.05); Average water reuse (%): Average percentage of water reused out of total water used.

 

Based on Table 6, the percentage of water reuse for high business scale is higher (44%) compared to low business scale (28%) with P value <0.05. This shows that large-scale dairy farms are less polluting in wastewater management because most water is reused and used as needed. According to Takeuchi and Tanaka (2020), recycling water is a practical way to save water, minimize the environmental impact, and save money and energy on water resource management. Voulvoulis (2018) stated that water reduction and reuse are recommended as alternate strategies to guarantee the availability of water resources in areas with water scarcity where water demand outpaces water supply. Adopting water reuse on a large scale can benefit significantly from changing to a circular economy. According to Andriamanohiarisoamanana et al. (2022), most farmers are interested in having a biodigester for biogas if it meets the requirements regarding the number of livestock they have. The majority of small-scale farmers are not willing to use biogas. This is not the case for large-scale farmers, who, on average, are willing to pay for a biodigester for cooking purposes.

The water use of dairy farms in Sleman Regency is shown in Table 4. The number of animals (AU) significantly impacts the water used. On a low scale (average of 2.29 AU cattle), the water used for livestock bathing is 50.20 L/AU/Day less. On a high scale (average of 4.83 AU cattle), the total water used for livestock bathing is 55.15 L/AU/Day. At the time of the research, no one at either the low or high scale used clean water for watering forage. The forage land is far from people’s homes, and trim is around the barn. Most water is used for cleaning stalls and bathing cattle, and the least for cleaning tools. According to Kusumastuti et al. (2017), bathing dairy cattle on smallholder farms is done once a week due to limited water availability during the dry season. Wastewater from the milking process, equipment washing, stall cleaning, and cattle bathing is discharged directly into the cattle pasture around the stalls. According to Monteiro et al. (2024), dairy farming requires large amounts of water, which can significantly impact production costs and potential negative environmental impacts. Dairy farms use water for cooling, drinking, washing cattle, washing appliances, and irrigation. The judicious use of water is essential for enhancing forage and livestock production, particularly in light of the depletion of freshwater resources. Nagypál et al. (2020) indicate that precipitation, extreme weather events like droughts and floods, and increasing average air temperatures will affect water availability, reducing the quantity of water accessible to humans from natural ecosystems.

Eco-efficiency of Water Use

Based on research that has been conducted, dairy farmers experience water shortages in the dry season. If there is a water shortage, some farmers do not bathe the cattle during milking and only clean the udder area. If water supply is insufficient, most farmers buy water at IDR 5,000.00 per m3, which is transported in barrels by pickup trucks. This is inefficient because dairy farms depend highly on clean water for drinking and livestock maintenance to ensure hygienic milk. According to Tamminen et al. (2024) and Jensen and Vestergaard (2021) stated that in hot environmental temperatures, water is essential for dairy cattle and must be provided at all times (ad libitum). In the dry season, many dairy cattle are given limited drinking water, which causes decreased milk production. In addition to water, heat stress during the dry season lowers health and welfare in addition to milk production. According to Umami et al. (2022) stated that water availability continued to decline to 1200 m3/year in 2020, slowing infrastructure development in water resource management, the lack of available storage for rainwater runoff, and the implementation of eco-efficient that is less than optimal are the main challenges.

Based on Table 5, water use for dairy farming at the time of the research was still far below the water requirement standard. This is due to inefficiency in water use due to lack of water supply. The use of water for drinking water for livestock on dairy farms in Sleman Regency was low and high at 35.44 and 40.40 L/AU/day, respectively. This is very far from the standard for providing drinking water for livestock, which is 70 L/AU/day (Kononoff and Clark, 2017). 87% of the milk produced by dairy cattle is water. Every 1 litre of milk needs 5 litres of water (Krauß et al., 2016). Milk composition is also affected by water deficit. There is an increase in milk lactose, urea, sodium, and titratable acidity, which can alter milk quality and suitability for processing into dairy products. Prolonged water restriction can result in decreased body weight and body condition scores, further compromising animal welfare (Casamassima et al., 2018). Water restriction leads to physiological stress, as evidenced by increased osmolality, sodium, urea, glucose, and albumin concentrations in the blood (Jaber et al., 2019). In terms of milk production, one of the causes of low milk production in private dairy farms is lack of water. Dairy cow milk production in Sleman Regency is 10 litres/head/day (Kusumastuti et al., 2017). The use of water for bathing livestock has the largest portion in water use. On a low business scale, the use of water for bathing livestock is (50.20 L/AU/Day) from a total water use of (95.65 L/AU/Day) so the portion is 52.48%, and on a high business scale (55.15 L/AU/Day) from a total water use of (117 L/AU/Day) so that the portion for bathing livestock on a high scale is 47.13%. Average water use for bathing livestock (52,68 L/AU/day) is lower than the standard use (400 L/AU/day). Dairy farms in Sleman Regency experience water shortages, so the cattle are not bathed, resulting in poor hygiene and inefficiency in water use. Suranindyah et al. (2015) stated that cow milking at the Sleman Regency Dairy Farm was considered poor because the farmers did not bathe the cattle or clean the floors and feed troughs before milking. Hand washing was carried out at the same time as cleaning the udder. The udder was not dried after washing. This unhygienic preparation for milking caused the milk quality to be poor.

Based on the research results, there is inefficiency in water use where there is a deficit of water when compared to the standard water requirement. The water deficit in a low-scale business is higher, at 874.35 litres/AU/day, compared to a high-scale business of 853 litres/AU/day. The higher the business scale, the more efficient it is regarding water input resources. According to Hansen et al. (2019), dairy farming can meet the needs of farming families if they own more than 10 head of cattle, thus categorizing it as efficient farming. The higher the business scale, the more efficient the dairy farm. Kusumastuti et al. (2017) stated that the larger the business scale, the greater the use of water for livestock rearing, but more water is used to water feed crops than for livestock rearing. Water use in the dry season is emphasized more for watering crops than for livestock rearing to reduce feed costs in the dry season. The amount of water needed by livestock does not increase with the number of cattles (Krauß et al., 2016; Kusumastuti et al., 2017). Animal welfare suffers when dairy cattle are dehydrated, for instance, if they are not given adlibitum to drinking water. On average, dairy cattles with adlibitum to drinking water yield 1.7 L more milk per head per day than dairy cattles with restricted access (Daros et al., 2019; Wagner et al., 2018).

 

Table 7: Total cost of water in Sleman District dairy farms.

Cost	Low business scale	High business scale
Installation cost	100,000	100,000
Water reservoir	1,000,000	800,000
Installation depreciation cost (IDR/year)	73,000	72,000
PVC Pipe	800,000	700,000
Watercost(IDR/year)	299,156.76	364,771.08
Total Cost	2,272,156.76b	2,036,771.08a

 

a,b: Different superscripts on the same line indicate there is a difference (P<0.05).

 

The cost of installing the water installation and subscription is shown in Table 7. The total cost on a low business scale is higher (P<0.05) than on a high business scale. This shows that in terms of economic efficiency, a high business scale is more efficient than a low business scale. According to Miciula et al. (2024), economic efficiency is an effort not to waste costs and aims to achieve the best results with available resources and technology. In general, economic efficiency is the capacity to use available resources to maximise effectiveness and minimise waste to accomplish particular goals. Datta et al. (2019) stated that dairy farms with more than 10 head of cattle can make a profit and meet the needs of the farmer’s family.

Multiple Linear Regression Analysis of Factors Affecting Water Use

To ensure the research findings are BLUE (Best Linear Unbiased Estimator), the classical assumption test aims to determine and assess the validity of the regression model. The regression equation model must first be tested for classical assumptions before being analyzed with regression techniques. The linearity value in this study is <0.05. Therefore, it can be said that there is a linear relationship between the independent and dependent variables. The normality test results indicate a significance value of 0.20 > 0.05, suggesting that the residual value is typically distributed. Each independent variable has a tolerance value greater than 0.1 and a VIF value less than 5, according to the multicollinearity assumption test, showing that multicollinearity is not the problem. The results of the heteroscedasticity assumption test using Glejser analysis indicate that the significant value of all independent variables is above 0.05. The Glejser test criterion stipulates that if sig> 0.05, there is no heteroscedasticity.

After fulfilling the classical assumption test, a hypothesis test was conducted to analyze the factors influencing water use on Sleman Regency dairy farms. The study’s independent variables encompass the cost of water, business experience, formal education, and milk sales, while the dependent variable is water use on dairy farms. The data for this analysis was derived from primary data and direct measurements of dairy farms in Sleman Regency in 2024.

 

Table 8: Results of multiple linear regression analysis of factors affecting water use of dairy farms in Sleman District.

No.	Independent variable	Regression coefficient	SE	T	Sig
	Constant	2.67	0.64	4.13
1	Water cost (IDR/Month)	-0.05	0.037	-1.56	0.11
2	Business experience (Years)	0.06	0.041	1.66	0.09
3	Formal education (Score)	0.07	0.082	0.902	0.36
4	Milk sales (IDR/Month)	0.22	0.037	5.901	0.001***
5	Scale of business	0.80	0.056	14.307	0.001***
6	Type of cage	-0.07	0.071	-0.954	0.34
	R2	0.78
	Adjusted R Square	0.60
	F total	67.72
	F Significance	0.001

 

Table 8 shows that the adjusted R2 value is 0.60. This indicates that 60% of water use (Y) is influenced by water costs (X1), business experience (X2), formal education (X3), milk sales (X4), business scale (D1), and type of pen (D2). However, other factors that are not part of the model also impact the remaining 40%. Less than the significance level established at a = 0.05, the F test produced an Fcount value of 67.72 with a significance of 0.001. As a result, the hypothesis can be proven and the research model is viable. Hair et al. (2014) stated that the Adjusted R² value of 0.60 can be considered quite strong in social research because many external factors influence the dependent variable and not all of them can be included in the model.

The constant value is 2.67, which means that if the six independent variables studied do not exist, water usage is valued at 2.67. Based on the analysis results obtained, significance (P<0.05). These results indicate that together (simultaneously), water cost, business experience, formal education, milk sales, size of business, and type of pen affect water use in dairy farms. The milk sales regression coefficient of 0.22 indicates that a one-liter increase in milk sales will result in a 0.22-liter rise in water use, assuming other variables remain constant. This relatively small coefficient value indicates that there is a positive relationship between milk sales and water use, but the effect is relatively weak. This means that an increase in milk sales does not significantly drive an increase in water use when compared to other variables that have a greater influence, such as business scale. The regression coefficient value for milk sales (0.22) is lower than the business scale (0.80). This means that business scale has a 4 times greater influence on water use than milk sales. Van Breugel et al. (2010) stated that the population of dairy cattle is a determinant of overall water consumption by livestock.

The business scale has a very clear and positive effect on water use (P<0.001). This implies that either a decrease in the number of livestock (AU) will decrease water use, or an increase in AU will increase water use. According to this study’s research, an increase in the number of livestock must also be balanced with water availability because dairy cows are very dependent on water. Golher et al. (2021) state that several factors affect dairy cattle’s water intake, either directly or indirectly. Internal factors encompass environmental elements such as season, ambient temperature, humidity, wind speed, and precipitation, in addition to livestock-related aspects including breed, body size, physiological stage, age, health, stress, and ecological adaptation. These elements have a significant impact on how much water dairy cattle consume. Nevertheless, several management techniques, including housing, feeding methods, husbandry style, and water availability and quality, can also have an indirect impact.

Milk sales significantly affect water use (P<0.001). The higher the monthly milk sales turnover, the more water is used. This is because the higher the milk sales (IDR/month), the more farmers will increase their productivity by ensuring that the amount of drinking water is sufficient and not limited because it partly determines the quantity of milk from dairy cows. This aligns with the research conducted by Lestari et al. (2015), which stated that there is a clear and positive relationship between the application of GDFP (Good Dairy Farming Practice) and milk sales, with a correlation coefficient value of 0.51 (a significant relationship). Increased implementation of GDFP correlates positively with elevated milk sales levels. Good Dairy Farming Practice performs a crucial role as it seeks to operate a dairy business in accordance with established procedures, ensure the health of cows, guarantee the production of safe and nutritious dairy products for consumption, and mitigate environmental impact. According to Cortez-Arriola et al. (2014), milk sales are related to water use on dairy farms. Milk sales increase as livestock density increases.

Water efficiency in several types of milking activities, such as cleaning tools, bathing livestock, watering livestock, and cleaning stalls, has an impact on economic efficiency. This is because the quality and quantity of dairy products decrease due to water shortages, which impact economic efficiency. One solution that has been implemented for dairy farmers is to buy water in drums by car, but not all farmers can afford to buy water. Another solution farmers have implemented is collecting rainwater during the rainy season. Suggestions for an efficient water use strategy are: 1) Subsidies for the construction of reservoirs to increase water reserves during the dry season, 2) collect rainwater with a reservoir, 3) use an automatic drinking water system (adlibitum), 4) plant drought-resistant fodder (Cosgrove and Loucks, 2015; Finley, 2016). Potential water savings by using water according to standard needs, reducing energy costs and labor efficiency. Potential for increasing sustainability in water use by conserving water resources, establishing regulations for more efficient water use, applying progressive water tariffs, developing clean water distribution, conserving and reusing technologies such as wastewater treatment, rainwater harvesting (Borgert and Enedir, 2024; Zavala et al., 2016).

CONCLUSIONS AND RECOMMENDATIONS

The research findings indicate that a significant portion of water utilized for the maintenance of dairy cattle, specifically 50%, is primarily allocated for the washing of livestock. The scale of the business and milk sales have a positive and very real effect on water use (P<0.01). Water use is inefficient, where water use is far below the standard water requirements for dairy cattle maintenance. There is an inefficient use of water where the use of water in low and high scale businesses is still far below the standard water requirements for the maintenance of dairy cattles. Urgent government action is needed to resolve water deficit in Sleman Regency dairy farms, such as regulation of water use for the livestock sector to make it more efficient, rainwater harvesting during the rainy season, using an automatic drinking water system and water subsidies.

ACKNOWLEDGMENTS

We would like to thank the Indonesian Education Scholarship, the Center for Higher Education Funding and Assessment, and the Indonesian Endowment Fund for Education for their generous research funds, which allowed the study project to be completed on schedule and successfully.

NOVELITY STATEMENT

The novelty of this research is as a source of information on water use in dairy farms, efficiency of water use and factors that influence water use. Water deficit in dairy farms are a consideration for farmers and the government to meet water needs in order to increase the productivity of dairy farms in Sleman Regency.

AUTHOR’S CONTRIBUTIONS

The research concept was developed by Meita Puspa Dewi, Tri Anggraeni Kusumastuti and Nafiatul Umami. Meita Puspa Dewi conducted field research. Meita Puspa Dewi, Tri Anggraeni Kusumastuti and Nafiatul Umami analyzed the field data and wrote the manuscript’s final draft.

Conflict of Interest

There are no conflicting interests, according to the authors.

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