Grey water footprint of crop in Riau Province

The escalating severity of the water problem poses a potential threat to the prospects of sustainable development in the future. The grey water footprint is an indicator of the need for fresh water to mix and dilute pollutants and maintain air quality according to water quality standards. The evaluation of the grey water footprint (GWF) serves as a valuable measure in the mitigation and management of water contamination. The main objective of this study is to determine the grey water footprint associated with crop production along the Kampar Watershed and develop strategies to mitigate pollution levels. The grey water footprint is calculated using a water footprint assessment method. The finding show that the grey water footprint of rice farming (17.01 m3/ton) is larger than the maize (9.51 m3/ton), this indicate that necessary to improve water management on rice and maize agriculture. The water footprint performance scores of rice and corn plants are both in the poor category with scores of 11.93 and 45 respectively. To improve grey water performance and reduce air pollution, it can be done by using fertilizer according to plant needs, replacing inorganic fertilizer with organic fertilizer, implementing practices conventional tillage and maintain soil moisture.


Introduction
The notion of water footprint is a constituent of a broader set of footprint concepts that has been formulated within the field of environmental studies in recent decades.The water footprint divided in to three components, namely green water footprint, blue water footprint, and grey water footprint.The term "grey water footprint" (GWF) component pertains to the number of contaminated waters linked to the production of goods and services.It is measured as the volume of water needed to decrease pollutants to a level where the condition of the surrounding water remains higher than the established water quality standards [1,2].The agricultural industry is among the five largest sectors that contribute grey water globally [3].In the context of crop production, grey water is necessary to determine the appropriate degree of dilution required to lower nitrate and phosphate (fertiliser) levels, as well as pesticide levels, in order to meet the agreed-upon requirements and prevent their leaching from soils.
The calculation of the grey water footprint may be derived by dividing the pollutant content of the disparity between the maximum allowable concentration and the natural background concentration [1].A limited number of studies have been conducted to assess measurements of the grey water footprint.In some study, the impact of nitrogen application on the grey water footprint in irrigated agricultural production [4].Qin [5] examined The assessment of the Grey Water Footprint from the perspective of water pollution sources in China.In their study, Ariyani [6] conducted an analysis of the grey water footprint associated with rice-straw pulp.The study conducted by Meng [2] focuses on the quantification and evaluation of the grey water footprint in the region of Yantai.
The decrease of the grey water footprint (GWF) is imperative because to the escalating water pollution linked to crop production and the constrained capacity of fresh water assimilation.The application of fertiliser can have a substantial impact on the water footprint of agriculture due to the leaching of nutrients into groundwater and the discharge of these nutrients into streams.The Grey Water Footprint Score (GWFS) evaluates the water performance of a crop in water management for fertilisation practices.It is determined by comparing the actual water footprint of the crop to the yearly reference level of water footprint (WF').

Study area
The present study was carried out inside the Kampar watershed, located in Riau Province, encompassing two administrative districts, namely Kampar and Pelalawan Regencies.The Kampar Regency comprises four sub-districts, specifically XIII Koto Kampar, East Kampar, Kampar Kiri, and Kampar Kiri Hilir.Pelalawan Regency encompasses four sub-districts, specifically Langgam, Pelalawan, Teluk Meranti, and Kuala Kampar.The Kampar Watershed is home to eight districts that serve as prominent hubs for the cultivation of agricultural crops, including paddy and maize.

Analysis method
The grey water footprint (GWF) in the field of agriculture can be determined through a calculation that involves quantifying the volume of water required for assimilating fertilizers that enter ground or surface water.This calculation is achieved by multiplying the leaching-runoff fraction (α, %) by the rate at which chemicals are applied (Appl, kg/m 3 ).The result is then divided by the difference between the maximum acceptable concentration of nitrogen (cnat, kg/m 3 ) and the natural concentration of nitrogen in the receiving water body (cnat, kg/m 3 ).Finally, this value is divided by the actual yield (Y, ton/ha), as presented in Equation (1) by Hoekstra [7].The primary contributor to non-point source pollution of surface and subterranean water bodies is the leaching or runoff of nutrients from agricultural fields [8].
When considering instances of water pollution caused by point sources, it is observed that chemicals are directly released into a surface water body as wastewater discharge.In such cases, the water footprint of the pollutant (GWF) can be approximated by dividing the pollutant load (L, in mass/time) by the difference between the ambient water quality standard for that specific pollutant (cmax, measured in mass per unit volume) and its natural concentration in the receiving water body (cnat, measured in mass per unit volume) as represented by Equation ( 2).
The grey water footprint score (GWFS) data conducted from equation (3) are subsequently categorised into three distinct groups in order to assess the effectiveness of the GWFS [9].

Results and discussion
The grey water footprint refers to the amount of freshwater that is utilised for the purpose of absorbing and assimilating a specific load of pollutants.The utilisation of pesticides and artificial fertilisers leads to the occurrence of agricultural contamination.The primary reason for nitrogen fertiliser being the predominant contributor to water pollution is its high solubility, facilitating its entry into aquatic ecosystems.Additionally, the sheer quantity of nitrogen fertiliser applied further exacerbates its impact, rendering it the principal pollutant in water bodies.Hence, nitrogen fertiliser emerged as the primary source of pollution.It is important to note that the grey water calculation in this study only considers water pollution caused by fertiliser usage, disregarding the impacts of agricultural methods and climatic conditions.In addition, the impact of pesticides on water quality is also disregarded.According to Table 1, the quantity of residue generated in the rice growing technique surpasses that of maize in both districts.The resultant residue will exert an influence on both flora and the surrounding ecosystem.The application of fertiliser should be tailored to meet the specific requirements of the plant.In accordance with the findings of Rosadi [11], the provision of fertiliser tailored to the specific requirements of plants has been shown to promote enhanced agricultural productivity, hence exerting a direct influence on the availability of food resources.

Total grey water footprint for crop production in Kampar and Pelalawan District
The present study revealed that the grey water footprint in the Pelalawan district had a higher magnitude in relation to maize farming, but in the Kampar district, it was observed to be more significant in the context of rice cultivation (Figure 3).According to Figure 3, the water footprint (WF) of grey water in maize farming in Pelalawan district is measured at 6.23 m 3 /ton, which surpasses the WF of grey water in maize farming in Kampar district, recorded at 3.28 m 3 /ton.In comparison, the water footprint (WF) of rice cultivation in Pelalawan district is 2.49 m 3 /ton, which is lower than the water footprint of rice farming in Kampar district, which is 14.52 m 3 /ton.The variation seen can be attributed to the influence exerted by the implementation of a specific agricultural system.A decrease in output levels is associated with an increase in the grey water footprint [12,13].Conversely, increased production yields have the potential to diminish the significance of the grey water footprint.The high agricultural output outcomes can be attributed to either the high WF blue value or the presence of efficient irrigation facilities [14].

Total grey water footprint for crop production in Kampar Watershed
Based on the results of the analysis, it was found that the total value of the gray water footprint in rice and corn farming in the Kampar watershed (Figure 4).According to the data presented in Figure 4, the total grey water footprint (WF) in rice cultivation amounts to 17.01 m 3 per ton, surpassing the corresponding value of 9.51 m 3 per ton observed in maize cultivation.According to the research conducted by Rao [15], it has been shown that the utilisation of grey water in rice production, at a rate of 39 m 3 per ton, surpasses that of maize cultivation, which stands at 36 m 3 per ton.Furthermore, the water footprint (WF) value associated with this practice significantly exceeds the average national WF value of India.Deng [16] observed a similar phenomenon, wherein rice plants have a comparatively higher water footprint (WF) in grey terms when compared to other plant species.Rice is identified as one of the primary agricultural products that significantly to pollution.The consumption of grey water is contingent upon the quantity of residue, specifically fertiliser, utilised [3].The utilisation of fertilisers has the potential to make a substantial contribution to grey water footprint (WF) due to the process of nutrient leaching into groundwater and subsequent runoff into rivers.

Grey Water Footprint Score (GWFS) and Performance production in Kampar Watershed
Grey water footprint is not enough to describe the application performance of water use for fertilisation in agricultural systems, for this reason it is necessary to calculate WFS.The WFS and the performance of each plant found in this study are presented in Figure 5.

Figure 5. Grey water footprint score performance on paddy and maize in Kampar watershed
According to Figure 5, the water consumption technique employed by farmers in the Kampar watershed for fertilisation in rice and maize farming is categorised as inadequate, as evidenced by respective scores of 11.93 for rice and 12.45 for maize.The suboptimal score and performance of the grey water footprint seen in this investigation can be attributed to the utilisation of rather substantial leftovers.This disease is expected to exert a detrimental influence on the environment.The utilisation of inefficient fertilisation application techniques can result in the wastage of fertilisers into water bodies, hence diminishing the water quality in the surrounding areas and downstream regions.The primary source of river water pollution and land degradation stems from residues resulting from agricultural activities [4,17,18].
The transportation of nutrient residues resulting from fertilisation practices, including the application of urea fertiliser, will be facilitated through irrigation systems.Urea (CO (NH2)2) undergoes hydrolysis to yield ammonium nitrate, which is then absorbed by plants in the form of ammonium (NH4 + ) and nitrate (NO3 -) [19][20][21].In the event that these nutrients are not taken up by plants, they may be carried into irrigation canals and water bodies, such as rivers.There exists a correlation between the residual nitrogen present in the discharge channel and the irrigation practices in the upper Kampar Watershed.Urea cocrystal has a beneficial function in delivering a well-balanced nitrogen supply and enhancing crop productivity in a manner that is more ecologically sustainable compared to the use of urea alone.The utilisation of alternative fertilisers has the potential to effectively mitigate nitrogen (N) loss, particularly in the form of nitrous oxide (N2O) emissions, while also substantially enhancing nitrogen usage efficiency in sorghum cultivation [22].Due to incomplete uptake by crops, a portion of the nutrients present in artificial fertilisers ultimately finds its way into both groundwater and surface water sources.The leaching of nitrates from agricultural land can result in both the eutrophication of surface water and the contamination of drinking water sources derived from surface and groundwater.Quantifying the precise contribution of nitrogen fertilisers to the contamination of surface water is a challenging task due to the presence of several nitrogen sources in most water bodies.Furthermore, the transformation of nitrogen in soil into gaseous or immobile forms might vary depending on climatic conditions [23].Achieving optimal utilisation of nitrogen fertiliser can be accomplished through the modification of cultivation techniques, with a primary focus on cultivating varieties that possess superior nitrogen absorption efficiency.This approach enables the attainment of high crop yields while minimising input requirements [24][25][26].The utilisation of fertilisers has been found to have detrimental effects on local surface water resources, resulting in pollution.However, these impacts can be mitigated by the implementation of a targeted fertiliser application management strategy.The potential for leaching-induced nitrates loss can be mitigated by ensuring that the nitrogen levels provided are either smaller than or equivalent to the crop's absorption capacity [27,28].
In addition, the substitution of inorganic fertilisers utilised in agricultural systems with organic alternatives, such as manure, can enhance the efficacy of grey water and mitigate the consequent water pollution.The implementation of conventional tillage, can be utilised as a method to mitigate water pollution per unit of agricultural output [4].This approach involves the monitoring of soil moisture levels, with the aim of reducing leaching of pollutants into water bodies [9].

Conclusions
The research revealed that maize growing exhibited the highest grey water impact within the Pelalawan District.In contrast to the Kampar district, rice emerges as the primary source responsible for the substantial grey water footprint.In the Kampar watershed, the grey water footprint scores for rice and maize were found to exhibit suboptimal performance, as indicated by respective scores of 11.93 and 12.45.
In order to enhance future research endeavours, it is recommended that the methodology employed for the computation of GWF, as presented in this study, be subject to further refinement.The range of criteria considered for the determination of water quality in the context of GWF analysis could be expanded to incorporate more pollutants.The impact on GWF extends beyond the influence of nitrate-nitrogen and COD, encompassing nitrogen and phosphorus as well.In future research, it is recommended to utilise these supplementary factors as multiple proxies for the calculation of the Global Water Footprint (GWF).Hence, it is imperative to assess the effectiveness of the grey WF strategy and its utilisation in policymaking.

Figure 1 .
Figure 1.Research location of Kampar watershed

Figure 3 .
Figure 3.Total grey water footprint for crop production in Kampar and Pelalawan District

Figure 4 .
Figure 4. Total grey water footprint for crop production in Kampar Watershed

Table 1 .
Nutrients, namely nitrogen (N), phosphorus (P), and potassium (K), are essential for optimal plant growth.Consequently, it is crucial to carefully consider the availability and requirement of fertilisers in plants.The cultivation of rice and corn within the Kampar watershed involves the application of urea and NPK (Phonska) fertilisers.The data indicates that around 15% of fertiliser residue is generated at the research site.The amount of residue in rice and corn farming in Kampar and Pelalawan Regencies is obtained from the multiplication of harvest area, harvest frequency, and fertilizer requirements.Harvest area data was obtained from the Riau Province Central Statistics Agency (2018)[10].Harvest frequency was obtained from survey results, while data on fertilizer use was obtained from the provisions of the National Standardization Agency.Table1presents the data regarding the quantity of residue that is discarded during rice and corn planting at the research site.The amount of residue wasted from rice and maize farming in Kampar and Pelalawan Regencies 4 3.1.Fertiliser used in rice and maize farming