AGRIVITA Journal of Agricultural Science. 2022. 44(3): 459-469
AGRIVITA
Journal of Agricultural Science
www.agrivita.ub.ac.id
459
INTRODUCTION
Agricultural lands belong as one of the areas that result in high rates of soil and water loss, and as such proper land management needs to be implemented in order to be able to reduce soil and water loss (Mayerhofer, Meißl, Klebinder, Kohl, & Markart, 2017).
The application of mulch on agricultural lands, in addition to being able to reduce the growth of weeds, is also helpful in protecting the soil surface from rainfall and erosion (Parhizkar et al., 2021).
The mulch that is commonly utilized in agricultural lands is plastic mulch. Plastic mulch is a sheet of plastic covering cultivated plants’ land zone.
Plastic mulch used as soil cover can shield and protect the soil surface from erosion, maintain moisture content and soil structure, and prevent the development of pests and weeds. However, plastic mulch is classified as a kind of inorganic plastic. Therefore, it belongs to a kind of environmentally unfriendly material (Ren et al.,
2021; Zhang, Miles, Gerdeman, LaHue, & DeVetter, 2021; Zhu et al., 2021).
Biogeotextile is a geosynthetic material made from an organic, water-permeable, and degradable material and created through a process similar to textile.
One kind of biogeotextile is made from the mendong (Javanese fimbry, Fimbristylis umbellaris) plant, which is a kind of grass that grows plentifully on the island of Java (Sukardi, Effendhi, & Setyawan, 2021). It has been the case that the utilization of mendong has not been maximal, as it is only made into mats and handicrafts that have now shifted to materials from mining products, such as plastic. Thus, the utilization of mendong as a raw material for biogeotextile becomes an opportunity that needs to be developed (Ferina, Rosariastuti, & Supriyadi, 2017). The advantage of mendong biogeotextile mulch compared to plastic mulch is that it is more permeable, thus allowing water to be absorbed into the soil and maintain the hydrological cycle (Effendie, 2020).
ARTICLE INFO Keywords:
Agriculture
Mendong biogeotextile mulch Plastic mulch
Rice straw mulch Article History:
Received: March 9, 2022 Accepted: September 15, 2022
*) Corresponding author:
E-mail: riyanto_haribowo@ub.ac.id
ABSTRACT
This research aims to determine the type of mulch material that effectively reduces the risk of erosion on agricultural lands and gives minimum detrimental impacts on water quality. The S12 Advanced Environmental Hydrology System used for rainfall simulator. Rainfall intensity was set up based on the daily annual maximum rainfall data. Meanwhile, the land slope is according to research site contour. This research was designed to compare the conditions of soil without mulch (WM) and Rice Straw Mulch (RSM), Mendong Biogeotextile Mulch (MBM), and Plastic Mulch (PM). The observed quality parameters were Dissolved Oxygen (DO), pH, and Total Dissolved Solids (TDS). Statistical analysis involved a three-way analysis of variance (ANOVA) with the aid of SPSS 26 software. Based on the smallest mean values for the amount of surface runoff discharge (mean 1.10), amount of sediment yield (mean 0.650), change in pH (mean 7.48), and TDS (mean 0.24) value, it can be concluded that MBM is the most optimal to be utilized as soil cover for agricultural lands. The performance of MBM is better than RSM and PM.
ISSN: 0126-0537Accredited First Grade by Ministry of Research, Technology and Higher Education of The Republic of Indonesia, Decree No: 30/E/KPT/2018
Cite this as: Haribowo, R., Asmaranto, R., Kusuma, L. T. W. N., & Amrina, B. G. (2022). Assessment of mulch material effect on surface runoff, soil loss, and water quality in an agricultural region. AGRIVITA Journal of Agricultural Science, 44(3), 459-469. http://doi.org/10.17503/agrivita.v41i0.3727
Assessment of Mulch Material Effect on Surface Runoff, Soil Loss, and Water Quality in an Agricultural Region
Riyanto Haribowo1*), Runi Asmaranto1), L. Tri Wijaya Nata Kusuma2) and Berlian Gari Amrina1)
1) Water Resources Engineering Department, Faculty of Engineering, Universitas Brawijaya, Malang, East Java, Indonesia
2) Industrial Engineering, Faculty of Engineering, Universitas Brawijaya, Malang, East Java, Indonesia
Straw mulch effectively reduces the possibility of erosion with consideration of the amount of sediment yield that occurs (Amrina, Haribowo, & Yuliani, 2020;
Haribowo, Asmaranto, Kusuma, & Amrina, 2021).
The usage of straw as mulch has its own advantages compare plastic mulch, because organic materias are needed to maintain soil fertility by protecting and improving the function of microorganisms in the soil, thereby being able to improve nutrient availability in soil and effectivity of fertilization, thus increasing plant production (Lucas-Borja et al., 2019; Yang et al., 2021).
Of the various kinds of mulch that are often utilized, it becomes necessary to study the kinds of mulch that are the most effective to reduce the amounts of surface runoff discharge and soil loss while still maintaining the water quality of the discharge.
One of the methods that is quite effective for finding out about erosion is to conduct research on erosion itself. One way to conduct research on soil erosion is in the laboratory using a rainfall simulator tool (Boulange, Malhat, Jaikaew, Nanko, & Watanabe, 2019; Corona et al., 2013; Mayerhofer, Meißl, Klebinder, Kohl, &
Markart, 2017; Parhizkar et al., 2021). Based on the rainfall model and actual conditions of agricultural lands, this research aims to determine the kind of mulch material that is effective in reducing the risk of erosion on agricultural lands and mitigating detrimental effects on the quality of the runoff water that enters the river.
MATERIALS AND METHODS
The selected agricultural region as the model is located in Sumber Brantas Village in Bumiaji Sub District, City of Batu. The region of Sumber Brantas Village is 541.1364 hectares and it is situated at an elevation of 1400-1700 m.a.s.l with high rainfall.
Meanwhile, the modeling was carried out at the Hydrology Laboratory of the Department of Water Resources Engineering in Universitas Brawijaya, Indonesia. Rainfall modeling utilized Armfield’s S12 Advanced Environmental Hydrology System Rainfall Simulator tool (Armfield, 2021; Haribowo, Asmaranto, Kusuma, & Amrina, 2021; Yao, 2020) (Fig. 1). The rainfall intensity in the laboratory model is adjusted with the usage of daily annual maximum rainfall data at the selected location of agricultural lands. The research was conducted from April until September 2021.
For this study, the utilized daily annual maximum rainfall data were from 2008-2020 and taken from the nearest rain station, the Junggo rain station in Bumiaji Sub-District, Batu. The maximum rainfall was 105 mm
(1.96 l/minute), while the minimum rainfall was 64 mm (1.2 l/minute) (Haribowo, Asmaranto, Kusuma,
& Amrina, 2021). Due to the limitations of the rainfall simulator, there was a decrease of rainfall intensity in the model by 13%. The maximum rainfall intensity became 91 mm (1.7 l/minute) and the minimum rainfall intensity was 54 mm (1 l/minute); this rainfall intensity is classified in the category of heavy rainfall (Aldrian &
Susanto, 2003).
The flow of surface runoff discharge carries off a portion of sediments and the substances contained in the soil. The soil used in the experiment was taken from Sumber Brantas Village in Bumiaji Sub-District, City of Batu (Pemerintah Kota Batu, 2017). The soil type was silty loam, which was found from the results of soil type weight analysis, grain size distribution analysis, sieve analysis, and hydrometric analysis (Amrina, Haribowo,
& Yuliani, 2020; Haribowo, Asmaranto, Kusuma,
& Amrina, 2021). The utilized slope values for the analysis of surface runoff discharge were 9% and 15%
(Amrina, Haribowo, & Yuliani, 2020). The comparative assessment of the use of mulch in this study is only relevant to silt loam soils.
This research involved the comparison between soil conditions with and without mulch covers (WM).
The evaluated mulch covers were RSM (Parhizkar et al., 2021; Yang et al., 2021), MBM (Effendie, 2020), and PM (Ren et al., 2021; Zhang, Miles, Gerdeman, LaHue, & DeVetter, 2021; Zhu et al., 2021) (Fig. 1).
Each of the treatments and variations was repeated three times. The water quality criteria referred to Government Regulation Number 82 of the Year 2001 on the Management of Water Quality and Control of Water Pollution (Pemerintah Pusat, 2001). Horiba U-50 multi-parameter water quality checker was utilized to measure DO, pH, and TDS for the quality of runoff water (Horiba, 2021). After drying, to determine the dry weight, the amounts of sediments for each treatment were weighed (Mayerhofer, Meißl, Klebinder, Kohl, &
Markart, 2017). The results for sediment yield were obtained from the amount of soil caught by the sieve.
The level of effectiveness for each kind of mulch was analyzed using a three-way variance analysis method (ANOVA). Next, the Bonferroni method was utilized to analyze the same or different samples for each treatment, allowing comparisons between treatments and treatment groups (Woods, Iacoboni, Grafton, & Mazziotta, 1996). Meanwhile, statistical testing utilized Statistical Package for the Social Sciences (SPSS 26) software as the analysis tool (Maric, de Haan, Hogendoorn, Wolters, & Huizenga, 2015).
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RESULTS AND DISCUSSION Analysis of Runoff Discharge
The treatments were repeated three times with changes to the land slope and rainfall intensity.
Meanwhile, the land was treated with WM, RSM, MBM and PM. The utilized land slopes were 9%
and 15%. The utilized rainfall intensities were 1.7 l/minute and 1 l/minute. Accordingly, for each treatment, 48 amounts of surface runoff discharge were obtained.
The average amount of surface runoff discharge for the rainfall intensity of 1 l/minute with a land slope of 9% for WM, RSM, MBM, and PM soils were 0.8, 0.6, 0.8, and 0.7 l/minute, respectively.
The average amount of surface runoff discharge for the rainfall intensity of 1.7 l/minute with a land slope of 9% for WM, RSM, MBM, and PM soils were 0.8, 0.9, 0.9; and 0.9 l/minute, respectively. While,
the average amount of surface runoff discharge for the rainfall intensity of 1 l/minute with a land slope of 15% for WM, RSM, MBM, and PM soils were respectively 1.3, 1.5, 1.1, and 1.4 l/minute. Then, the average amount of surface runoff discharge for the rainfall intensity of 1.7 l/minute with a land slope of 15% for WM, RSM, MBM and PM soils were respectively 1.5; 1.6; 1.6; and 1.4 l/minute (Fig.
2). The simulation results found that the amount of relative surface runoff discharge did not change significantly. The change in surface runoff discharge significantly occurred due to the change in the gradient of the land slope. With a slope of 9%, the average surface runoff discharge was 0.8 l/minute, while with a slope of 15%, the average surface runoff discharge was 1.4 l/minute. Mulch is an important factor in reducing soil erosion, as it provides a cover that reduces the impact of raindrops striking the soil directly (Parhizkar et al., 2021).
Fig. 1. Rainfall simulator and kinds of mulch cover
Rainfall simulator tool Rice straw mulch (RSM)
Mendong biogeotextile mulch (MBM) Plastic mulch (PM)
From the results of normality testing, RJ = 0.990 with P-value > 0.1, which is greater than 0.05, and thus the variable was declared to have normal distribution. Meanwhile, from the results of homogeneity testing, the significance value was found to be 0.921 (≥ 0.05), indicating that the variance of the population was homogenous. Based on the results of three-way ANOVA, the significance value of mulch was 0.635 (< 0.05), which means that it did not significantly affect surface runoff discharge.
Meanwhile, the significance value of rainfall intensity and slope was 0.00 (< 0.05), which means that the two parameters significantly influenced the surface runoff discharge. Considering the amount of surface runoff discharge, the kind of mulch cover did not give any significant effects. This is in line with several reports that mulch does not cause significant changes toward surface runoff discharge. Surface runoff discharge relatively has a closer relationship to land slope and rainfall intensity (Fig. 2) (Lucas- Borja et al., 2019; Robichaud, Lewis, Wagenbrenner, Ashmun, & Brown, 2013; Robichaud et al., 2013).
From the results of analysis with the Bonferroni method for the usage of mulch toward surface runoff, the mean values for RSM, WM, PM, and MBM were
respectively 1.15; 1.12; 1.11; and 1.10. RSM had the largest mean value reflecting the largest surface runoff discharge. Meanwhile, MBM had the smallest mean value, referring to the smallest surface runoff discharge. Therefore, it can be concluded that based on the amount of surface runoff discharge, MBM is the kind of mulch that is the most effective in reducing the surface runoff discharge.
Erosion Analysis
The occurrence process of erosion is determined by hydrology factors, particularly rainfall intensity, topography, soil characteristics, vegetative land cover, and land use. In this research, the modeling was carried out at laboratory scale by comparing the magnitude of rainfall intensity, land slope, and mulch usage to represent vegetation on land. In the simulation, when rain occurs, rainwater falling onto the land enters the soil (infiltration); after the land becomes saturated, the excess flowing water becomes the surface runoff. This surface runoff carries away or wears away soil on the land’s surface, usually called erosion. The soil that is carried away was then captured in the prepared filtering fabric, while the water was measured as the runoff discharge in the recording tool.
Remarks: WM: soil without mulch; PM: Plastic Mulch; RSM: Rice Straw Mulch; MBM: Mendong Biogeotextile Mulch Fig. 2. The amount of surface runoff discharge for each treatment
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The amount of sediment yield that resulted had a direct relationship with rainfall intensity and land slope. As rainfall intensity and land slope increases in value, sediment yield also increases in amount. For WM soil with a land slope of 9%, the average amount of sediment yield for a rainfall intensity of 1 l/minute was 0.49 g, while for a rainfall intensity of 1.7 l/minute, the average amount of sediment yield increased up to 2.45 g. For a land slope of 15%, the average amount of sediment yield for a rainfall intensity of 1 l/minute was 2.73 g, while for a rainfall intensity of 1.7 l/minute, the average amount of sediment yield increased up to 3.60 g (Fig. 3).
The relationship between rainfall intensity and land slope toward sediment yield was also applied to treat soil with mulch cover. The average amount of sediment yield for RSM for a land slope of 9%, from 0.55 g at a rainfall intensity of 1 l/minute, increased up to 1.55 g at a rainfall intensity of 1.7 l/minute. For a land slope of 15%, the average amount of sediment yield at a rainfall intensity of 1 l/minute was 0.83 g, which increased up to 1.55 g at a rainfall intensity of 1.7 l/minute. The average amount of sediment yield for PM for a land slope of 9% at a rainfall intensity of 1 l/minute was 0.45 g, while at a rainfall intensity of 1.7 l/minute, the average amount of sediment yield increased up to 1.44 g. For a land slope of 15%, the average amount of sediment yield at a rainfall intensity of 1 l/minute was 0.59 g, while at a rainfall intensity of 1.7 l/minute, the average amount of sediment yield increased up to 2.49 g. The average amount of sediment yield for MBM for a land slope
of 9%, at a rainfall intensity of 1 l/minute was 0.71 g, which increased up to 0.77 g at a rainfall intensity of 1.7 l/minute. For a land slope of 15%, the average amount of sediment yield at a rainfall intensity of 1 l/
minute was 0.73 g, which increased up to 0.87 g at a rainfall intensity of 1.7 l/minute (Fig. 3).
From the results of normality testing, RJ
= 0.997 with P-value > 0.1, which is greater than 0.05, and thus the variable was declared to have normal distribution. Meanwhile, from the results of homogeneity testing, the significance value was found to be 0.892 (≥ 0.05), indicating that the variance of the population was homogenous. From the results of analysis by three-way ANOVA, it was found that all the variables were independent (type of mulch, rainfall intensity, and land slope) with a value of 0.00 (< 0.05) toward the amount of sediment yield. This indicates that the three factors possess significance toward the change in the amount of sediment yield (Wang et al., 2021; Xiao, Zhao, & Kuhn, 2019; J. H. Yang et al., 2022; Z. Yang et al., 2022).
Testing was conducted based on Bonferroni method to determine the magnitude of each kind of mulch’s influence on the amount of sediment yield. The results of testing based on Bonferroni method for the usage of mulch against the amount of sediment yield led to the mean values for each kind of mulch. The mean values for WM, RSM, PM, and MBM were respectively 2.32; 0.85; 0.75; and 0.65. MBM had the smallest mean value, which meant that it had the most optimal ability to hold back erosion compared to the other kinds of mulch.
Fig. 3. Amount of sediment yield for each treatment
Analysis of Water Quality on Surface Runoff Discharge
When rain occurs, and soil in this modeling that has been saturated, surface runoff will occur.
The rainwater runoff that overflows the land’s surface and carries off an amount of substances contained in the soil will certainly affect the water quality in the downstream region (Amrina, Haribowo, & Yuliani, 2020). Based on Regulation of the Governor of East Java Number 61 of Year 2010 on the Establishment of Water Classes on River Water, Article 4 Point D states that the Brantas River from its source in Sumber Brantas Village in Bumiaji Sub-District up to the Pendem Bridge in Malang Regency according to the classification of water quality is established as Class I. Thus, in this research, the classification of water quality is Class I (Pemerintah Provinsi, 2010). Meanwhile, the criteria of water quality refers to Government Regulation Number 22 of Year 2021 on the Organization of Protection and Management of the Environment (Pemerintah Pusat, 2021). The water quality parameters that were measured with the Water Quality Checker Horiba tool were water temperature, Dissolved Oxygen (DO), pH, and Total Dissolved Solids (TDS).
Dissolved Oxygen (DO)
Dissolved oxygen in a body of water plays a very important role in the process of nutrient absorption by living creatures in water. The primary source of oxygen in a body of water is from a diffusion process from ambient air and the results of photosynthesis by organisms living in the body of water.
The average DO concentration value for WM soil runoff was 4.17 mg/l. A DO value within 4-6 mg/l is categorized in the water quality criteria of Class II (Pemerintah Provinsi, 2010). The results of measuring the DO of the runoff of RSM soil also did not indicate a major influence from rainfall intensity and land slope.
The average value of DO concentration for the runoff of RSM soil was 3.88 mg/l. Based on the regulation, a DO value within 3-4 mg/l belongs in the water quality criteria of Class III. As with the other treatments, the results of measuring the DO of runoff of PM and MBM soils also did not indicate a major influence from rainfall intensity and land slope. The average value of DO concentration for the runoff of PM soil was 4.00 mg/l, while for MBM soil, it was 3.99 mg/l.
The runoff for PM soil belongs in the water quality criteria of Class II, while for MBM soil belongs in the water quality criteria of Class III (Fig. 4) (Pemerintah Provinsi, 2010).
Remarks: WM = soil without mulch, PM = Plastic Mulch, RSM = Rice Straw Mulch, MBM = Mendong Biogeotextile Mulch
Fig. 4. DO values for each treatment
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Remarks: WM = soil without mulch, PM = Plastic Mulch, RSM = Rice Straw Mulch, MBM = Mendong Biogeotextile Mulch
Fig. 5. pH values for each treatment
Fig. 6. TDS values for each treatment
From the results of normality testing, RJ = 0.916 with P-value < 0.01, which is less than 0.05, and thus the variable was declared not to have normal distribution. Meanwhile, from the results of homogeneity testing, the significance value was found to be 0.000 (< 0.05), indicating that
the variance of the population was homogenous.
Therefore, the value of DO concentration does not meet the requirements for conducting three-way ANOVA testing. The differing magnitudes of the DO value in this modeling may have depended on the time of measurement with the Horiba water
quality checker. The DO value was large when the measurement tool is inserted into the containment tub when the runoff still flowed. Meanwhile, the DO value was small when the measurement is conducted at the time the runoff stopped flowing. As such, the DO value in this modeling is not affected by land slope, rainfall intensity, and treatments of mulch usage.
pH The pH value of a body of water may become an indicator of the presence of chemical balance and can affect the availability of chemical elements and nutrients that are useful for the lifecycle of aquatic vegetation. In addition, the pH of the water also plays an important role for the lifecycle of water fauna such as fish and other organisms that live in the water.
Fig. 5 shows that the pH values of runoff from the treatments were still within 6-9, with an average of 7.5. This means that the pH of the water was still normal. For the treatments, the factors of rainfall intensity, land slope, and usage of mulch did not cause major changes in the pH of the runoff.
From the results of normality testing for pH, RJ = 0.993 with P-value > 0.1, which is greater than 0.05, and thus the variable has normal distribution.
From the results of homogeneity testing for pH, it was found that the P-value was 0.658 (> 0.05), indicating that the population variance was homogenous.
Through analysis by three-way ANOVA, the p-values for land slope and rainfall intensity were obtained, being 0.805 and 0.725 (> 0.05), meaning that the two factors did not significantly influence changes in pH. Meanwhile, the p-value for kinds of mulch was 0.000 (< 0.05), which means that changes in the kind of mulch significantly affected changes in pH. The results of this research are in line with several studies that stated that the usage of mulch can cause changes in pH (Hanum & Van Der Maesen, 1997; Korkanç & Şahin, 2021; Liu et al., 2021; Wang et al., 2017).
Total Dissolved Solids (TDS)
TDS are the solids that are of smaller sizes than suspended solids. These solids are composed of organic and inorganic substances that dissolve in water, minerals, and their salts. TDS in high concentrations can reduce water clarity, significantly decrease the photosynthesis process, and create compounds with toxic substances and heavy metals.
Fig. 6 shows that a greater rainfall intensity (1.7 l/minute) had a greater concentration of TDS, but regarding the land slope, its effect on TDS concentration is not an evidence. For a slope of 9%
and WM soil, a rainfall intensity of 1 l/minute had an average TDS of 185.67 mg/l and a rainfall intensity of 15% had an average TDS of 238.67 mg/l.
Meanwhile, for a slope of 15%, at a rainfall intensity of 1 l/minute, the TDS concentration was 186.67 mg/l, and at a rainfall intensity of 1.7 l/minute, the TDS concentration was 238.00 mg/l. For RSM soil and a slope of 9%, a rainfall intensity of 1 l/minute had an average TDS of 243.00 mg/l, and a rainfall intensity of 1.7 l/minute had an average TDS of 265.33 mg/l. Then, for a land slope of 15%, at a rainfall intensity of 1 l/minute, the TDS concentration was 246.33 mg/l, and at a rainfall intensity of 1.7 l/minute, the TDS concentration was 278.00 mg/l.
For PM soil with a slope of 9%, a rainfall intensity of 1 l/minute had an average TDS concentration of 276.00 mg/l and a rainfall intensity of 1.7 l/minute had an average TDS concentration of 288.33 mg/l.
Meanwhile, for a land slope of 15%, at a rainfall intensity of 1 l/minute, the TDS concentration was 259.00 mg/l, and at a rainfall intensity of 1.7 l/minute, the TDS concentration was 264.00 mg/l. Finally, for MBM soil and a slope of 9%, a rainfall intensity of 1 l/minute had an average TDS concentration of 235.33 mg/l and a rainfall intensity of 1.7 l/minute had an average TDS concentration of 261.00 mg/l.
Then, for a slope of 15%, at a rainfall intensity of 1 l/minute, the TDS concentration was 234.67 mg/l, and at a rainfall intensity of 1.7 l/minute, the TDS concentration was 292.67 mg/l (Fig. 6).
The results of normality testing for TDS found that RJ = 0.990 with P-value > 0.1, which is greater than 0.05, and thus the variable has normal distribution. The results of homogeneity testing for TDS found that the P-value was 0.892 (> 0.05), indicating that the population variance was homogenous. Based on the results of normality testing for TDS, it was found that the P-values for the variables of type of mulch and rainfall intensity were 0.000 (< 0.05). The results showed a significant effect toward the change in TDS due to the two factors of mulch type and rainfall intensity (Zhang, Miles, Gerdeman, LaHue, & DeVetter, 2021). Meanwhile, the p-value for land slope was 0.902 (> 0.05). This indicated that there were no significant effects toward the change in TDS due to the land slope.
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From the results of analysis by the Bonferroni method for the usage of mulch toward TDS, it was found that the mean values for WM, RSM, PM, and MBM soils were respectively 0.21; 0.25; 0.28; and 0.24. WM soil had the smallest mean of 0.21, which meant that it had the smallest influence toward water turbidity. The case of TDS without mulch being smaller compared to with mulch usage may be because the mulch material itself has a greater TDS compared to the TDS of the soil (Iqbal et al., 2020). Among the utilized kinds of mulch cover, soil with RSM had the largest mean value of 0.28.
Meanwhile, soil with MBM had the smallest mean value of 0.24, which means that it had the smallest influence toward water turbidity.
CONCLUSION
In this research, the change in surface runoff discharge occurs due to changes in the land slope and rainfall intensity. There is an increase in surface runoff discharge by 175% if changes occur to land slope. Meanwhile, there is an increase in surface runoff discharge by 114% due to changes in rainfall intensity. The change in the amount of sediment yield is directly proportional to rainfall intensity and land slope. As rainfall intensity and land slope increase, the amount of sediment yield will also increase.
There is an increase in the sediment yield amount by 200-300% for changes in rainfall intensity and by 133-237% for changes in land slope. Changes in land slope and rainfall intensity do not significantly affect changes toward DO. For pH, change occurs due to the change in the kind of mulch.
Meanwhile, the change in TDS is more due to a present influence from the changes in the kind of mulch and rainfall intensity. From the results of analysis with the Bonferroni method, MBM has the smallest mean value for the reduction of surface runoff discharge (mean 1.10), reduction of sediment yield (mean 0.650), change in pH (mean 7.48), and change in TDS concentration (mean 0.24).
Therefore, it can be concluded that from the kinds of mulch that were utilized, MBM is the kind of mulch that is the most optimal to be utilized for reducing surface runoff discharge, decreasing the sediment yield amount, and minimizing changes toward water quality. The results of this research still only apply at the laboratory scale, and therefore in the future, a study will be conducted on the field with the usage of MBM to find out the magnitude of its effectiveness at the scale of the real world.
ACKNOWLEDGEMENT
Deep gratitude and appreciation are expressed toward Universitas Brawijaya for providing grants to support the research (Hibah Doktor Lektor Kepala, contract number: 23/UN10.
F07/PN/2021; April 27th, 2021). Gratitude is also expressed to Azra Lindu Aji and Tazkia Tasya for their valuable technical support for this research and their assistance in collecting plant data.
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