Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation

Suhardi Suhardi; Ahmad Munir; Haerani Haerani; Husnul Mubarak; Muhammad Tahir Sapsal; Reskiana Saefuddin; Anita Anita

doi:10.1515/opag-2022-0264

Article Open Access

Design of drainage channel for effective use of land on fully mechanized sugarcane plantations: A case study at Bone Sugarcane Plantation

, , , , , and

Published/Copyright: March 30, 2024

Published by

Become an author with De Gruyter Brill

Submit Manuscript Author Information Explore this Subject

From the journal Open Agriculture Volume 9 Issue 1

Abstract

Drainage in sugarcane cultivation in high-rainfall areas is of paramount importance because it affects sugarcane plants from planting, maintenance, and production. Poor drainage can damage plants and reduce productivity. This study was conducted at Bone Sugarcane Plantation, which typically has high annual rainfall; thus, drainage is necessary. The existing drainage channel cannot drain all surface runoff quickly and causes problems to sugarcane plants. Therefore, a study was conducted with the aim of designing the shape and size of drainage channels that can drain surface runoff quickly, have a strong structure, allows for an effective use of cultivated land by reducing headland for tractor turning, and maintains appropriate soil moisture. The research began by determining the saturated hydraulic conductivity of the soil using the Falling Head method. Surface runoff discharge was calculated using rational equations to determine the dimensions of the drainage channel. Rainfall intensity was determined from Intensity Duration Frequency curve which was constructed using Manonobe method. The results showed that the saturated hydraulic conductivity of the soil was 3.54 × 10⁻³ cm/s which is suitable with surface drainage. Rainfall intensity is estimated to be 201.33 mm/hour. The shape and dimensions of the drainage channel are parabolic with the largest width and depth of 1.70 m and 0.90, respectively. This study provides a practical method to solve drainage problems in sugarcane fields that apply full mechanization. In addition, the practical analysis used in this study can be adapted to analyze the design of drainage channel for other plantations or regions with similar constrains.

Keywords: surface drainage; parabolic shape; stable structure; full mechanization

1 Introduction

Drainage channels are an important infrastructure in sugarcane cultivation that can affect the planting activity and production. This is especially true in the current situation where rain intensity is unpredictable due to climate change which can significantly reduce production[1]. If there are problems with drainage, planting must be performed in furrows [2]. Good drainage can increase organic matter, which affects soil physical properties and nutrients [3], increase productivity [4,5,6], generate optimal sugarcane production [3], and increase water use efficiency [7,8]. Therefore, it is of paramount importance that drainage system is designed appropriately using not only hydrologic data but also land condition. A study reported by Tama et al. [9] employed only rainfall data to predict run-off discharge using W-Flow model and indicated good correlations between observed and simulated discharge. In our current study, we used both rainfall data and land conditions to generate rain intensity and determine run-off coefficient, respectively. Our research sites at Bone Sugarcane Plantations have an annual rainfall of >2000 mm/year [10]; therefore, artificial drainage is needed [11], and a correct drainage network system is needed [12].

In addition, to improve the drainage network, the type, shape, and size of drainage channels need to be designed to comply with important criteria such as structural stability, the ability to pass all surface runoff [13], submerged root prevention [14] to avoid damage to small sugarcane plants [15], good soil aeration, increased biological activity, and easy cultivation activities. For fully mechanized sugarcane cultivation system, it is important that the design of drainage system such as the slope of the channel walls [16] does not interfere with the movement of the machinery.

The use of mechanization equipment in sugarcane production is unavoidable because of the size of the plantation and the scarcity of labor [13,17]. In several countries, labor costs are relatively cheap [18], but it tend to increase [17] and the availability of labor force is scarce. In addition, the use of mechanization equipment increases productivity [3] and improves the efficiency of sugarcane production systems [19]. With the various advantages of mechanization in the management of sugarcane plantations, the design of drainage channels needs to consider the operation of this mechanized equipment, especially in the area where the equipment turns [20] which causes parts of the land close to the channel is unusable. In addition, the existing drainage channel in the plantation cannot maintain soil moisture at appropriate level that brings about an increase in temperature at root zone and causes flowering. This significantly reduces production and sugar yield.

Therefore, it is necessary to design a drainage system to develop a good sugarcane plantation drainage system to not only increase production and yield, but also provide drainage channels with good structural stability, have the ability to pass all surface runoff quickly, maintain soil moisture at root zone, and do not interfere with the operation of mechanization equipment. These important criteria must be adjusted to the conditions in sugarcane plantations. In accordance with these important criteria, the objective of this study was to design a drainage system that can pass all surface runoff, has a stable structure, and does not interfere with the operation of mechanization equipment.

2 Methodology

2.1 Determination of drainage channel type

Commonly used types of drainage are surface drainage and subsurface drainage. One of the considerations in selecting the type of channel is the physical properties of the soil, including its permeability [14]. Soil permeability parameter is the saturated hydraulic conductivity of the soil, which affects infiltration and surface runoff [21]. The saturated soil hydraulic conductivity was determined using a permeameter [22] in laboratory [23] using the falling-head method [23,24]. Saturated soil hydraulic conductivity (Ks) was determined using the following equation:

(1) Ks = a L At ln h 1 h 2 or Ks = α ln h 1 h 2 ,

where Ks is the saturated hydraulic conductivity of the soil (cm/s), A is the area of the soil sample in the ring (cm²), a is the cross section area of the measurement pipe (cm²), L is the length of the soil sample ring (cm), t is the time interval between readings (s), h ₁ is the initial water level (cm), h ₂ is the final water level (cm), and α is the slope constant of the graph, which is equivalent to aL/At. Hydraulic conductivity relates to the amount of infiltration and surface runoff.

2.2 Determining the size and shape of the drainage channel

The size of the drainage channel was determined based on peak discharge of the surface runoff. The peak discharge (Q _p) was determined using the rational method [25] as applied by several authors [26,27,28,29]:

(2) Q p = 0.278 C ro I A c ,

where Q _p is the peak surface runoff discharge (m³/s), C _ro is the runoff coefficient (dimensionless), I is the rainfall intensity during a given return period (mm/h), A _c is the catchment area (km²), and 0.278 is the unit conversion factor.

Runoff coefficient values were determined based on field conditions such as: (1) land tillage, (2) infiltration capacity, (3) land cover level, and (4) surface storage [29]. The land cover level can be predicted with fixel-based and object-based methods [30].

Rainfall intensity data in the research area was not available. Therefore, in the current study, these data were generated from rainfall data which were obtained from direct measurements using tipping bucket method as previously employed by several researchers [31]. More accurate rainfall information can be obtained from satellite data [9], but, unfortunately, we do not have access to such data. The rainfall data from the field measurement were then used to construct Intensity Duration Frequency (IDF) curve, from which the intensity was determined using the Mononobe method. The IDF curve was produced using the following steps [32]:

sorting daily maximum rainfall data in descending order;
calculating the probability of excess rainfall for each rainfall volume using the following equation:
(3) p = 1 T = rank m + 1 ,
where m is the number of observations, p is the probability of excess rainfall, and T is the suitable return period.
Transforming the rain volume data into rainfall intensity by dividing the volume with the suitable duration.
Constructing empirical plot of rainfall intensity distribution.

These steps were repeated for the desired duration. Subsequently, the appropriate rainfall distribution type was determined based on statistical parameters such as the mean ( x ̅ ), standard deviation (S), coefficient of variance (Cv), coefficient of skewness (Cs), and coefficient of kurtosis (Ck). [33,34] These statistical parameter were calculated using the following equations:

(4) X ̅ = 1 n ∑ i = 1 n xi ,

(5) S = ∑ i = 1 n ( log Xi − X ̅ ) 2 n − 1 ,

(6) Cv = S X ,

(7) Cs = n ( n − 1 ) ( n − 2 ) ( n − 3 ) S 3 ∑ ( X − X n ) 3 ,

(8) Ck = n ( n − 1 ) ( n − 2 ) ( n − 3 ) S 3 ∑ ( X − X n ) 3 .

These statistical parameters were used to determine the appropriate rainfall distribution. Several types of rainfall distributions were evaluated which include normal, log-normal, log Person III, and Gumbel distributions. The following are the equations for these four types of distributions, respectively [35,36]:

(9) X Tr = X ̅ + K Tr · S x ,

(10) log X Tr = log X ̅ + K Tr · S log X ,

(11) X Tr = X ̅ + S x · K T ,

where X _Tr is the maximum rainfall, X ̅ is the average rainfall, S _x is the standard deviation, and K _T is a frequency factor.

The frequency factor (K _T) in the above equation was calculated using the frequency factor equation [35,37]:

(12) K T = − 6 π 0.5772 + ln ln T T − 1 ,

where K _T is frequency factor and T is return period (years).

The rain intensity parameter was calculated using the Manonobe method with the following formula [27,28,38]:

(13) I = R 24 24 24 Tc 2 3 ,

where I is the rainfall intensity (mm/h), Tc is the time of concentration (h), and R ₂₄ is the daily maximum rainfall (mm). The concentration time was calculated using the Kirpich equation [39]:

(14) Tc = 0.0195 × L 0.77 × S 0.385 ,

where Tc is the concentration time (min), L is the main channel length (m), and S is the channel slope (m/m).

The channel size is based on the peak runoff discharge, where the designed channel size must be greater than or equal to the peak runoff discharge. Channel discharge was calculated using the following equation:

(15) Q = A × v ,

where Q is the discharge of the channel (m³/s), A is the cross-sectional area of the channel (m²), and v is the velocity of water flow in the drainage channel (m/s).

Flow velocity in the above equation was calculated using the Manning formula:

(16) v = 1 n × R 2 3 × S 1 2 ,

where v is the water flow rate (m/s), n is the Manning roughness coefficient, R is the hydraulic radius (m), and S is the channel-bed slope (m/m). Once the flow velocity was known, the width and depth of the channel were determined using a trial-and-error method.

The design of channel shape in this study considered the slope of the channel wall in relation to the channel stability [13] and the use of mechanization equipment [16]. In this case, two types of channels are commonly used, namely, trapezium and parabolic [13]. In this study, the parabolic type was utilized for its structural stability and easy movement of mechanization equipment. The cross-sectional area (A) of parabolic channel types was calculated using the following equation [40]:

(17) A = 2 3 d T w ,

where d is the depth of the flow, T _w is the width of the flow top, and z is the horizontal distance of the channel wall when d = 1.

A freeboard was added to the depth of the channel based on the Froude number (Fr) [41]:

Fr < 0.86 (sub-critical) has a freeboard of 30 cm.
Fr > 0.86 (super-critical) has a freeboard based on the equation:

(18) FB = C FB ( y + v 2 / 2 g ) ,

where FB is the freeboard (m), y is the maximum depth (m), v is the average speed (m/s), g is the acceleration owing to gravity (g = 9.81 m/s² or g = 32.2 ft/s²), and C _FB is conversion factor for freeboard (C _FB = 0.0508 for SI unit or C _FB = 1/6 for British unit).

3 Results and discussion

3.1 Overview of the research location

The Bone Sugar Plantation area consists of lowland and upland [42,43]. The lowland area is characterized by a relatively flat surface, medium to heavy soil texture (clay) [42], slope between 0 and 2% [44], and obstructed (poor) drainage. This condition causes massive amount of loss of sugarcane yield due to flooding [5], especially during years of high rainfall. The Bone Sugar Plantation area typically has rainfalls of above 2,000 mm/year. The following is the maximum daily rainfall data for the last 18 years [44].

The average rainfall ( x ̅ ), standard deviation (S), coefficient of variance (Cv), coefficient of skewness (Cs), and coefficient of kurtosis (Ck) obtained from rainfall data were 130.89, 44.61, 0.34, 0.78 and −0.61, respectively. Based on these statistical parameter values, the appropriate distribution model of the maximum daily rainfall was the Gumbel distribution because a Cs value ≤ 1.14 [45,46] and a Ck value ≤ 2.4 [45].

3.2 Suitable channel type

The channel type was determined based on data from saturated soil hydraulic conductivity measurements. The values of soil hydraulic conductivity at the four sampling points are listed in Table 1. The value of the measurement results of changes in water level in one of the soil samples from ArasoE IV block 5 is shown in Figure 1.

Table 1

Saturated hydraulic conductivity of soil in Bone Sugarcane Plantation

No.	Location	Hydraulic conductivity (Ks)		Classification of Soil texture
No.	Location	cm/s	m/d	Classification of Soil texture
1	ArasoE V/10	0.00002	0.02	Loamy clay
2	ArasoE III/9	0.00569	4.92	Medium sand
3	ArasoE IV/5	0.00174	1.50	Loam
4	Balieng IB/7	0.00027	0.23	Loamy clay

Figure 1

Graph of Ks measurement results for soil samples from the garden of ArasoE IV Block 5.

From the graph in Figure 1, the coefficient α in the falling-head equation was obtained. The value of α was used to calculate the saturated hydraulic conductivity using equation (1). The hydraulic conductivity value of the saturated soil of the Bone Sugarcane Plantation was as follows:

It is evident from Table 1 that Bone Sugarcane Plantation generally has extremely low hydraulic conductivities. A low hydraulic conductivity value (less than 25 mm/h) indicates small infiltration capacity [47]; thus, rainwater in the area generally becomes surface runoff [48]. Under these conditions, the appropriate drainage system is surface drainage [47].

3.3 IDF curve

IDF curves can be constructed to predict rainfall intensity for various return periods [32,49], which are commonly 2-, 5-, 10-, 25-, and 50-year return periods [49]. Based on the maximum daily rainfall data (Table 2), the IDF curves for 2-, 5-, 10-, 25-, and 50-year return period are presented in Figure 2.

Table 2

Maximum daily rainfall for the last 18 years

No.	Year	Max rainfall	No.	Year	Max rainfall
1	2009	75	10	2020	118
2	2015	78	11	2004	121
3	2012	91	12	2008	132
4	2016	94	13	2011	135
5	2014	99	14	2007	181
6	2010	107	15	2021	185
7	2006	110	16	2022	191
8	2013	110	17	2019	196
9	2017	110	18	2018	223

Figure 2

IDF curve.

The parameters of rain duration and rain intensity were used in the drainage design as they relate to the diversion of rainwater into streams and puddles that must be discharged through drainage system [50]. The IDF curve forms the equation used to estimate the rainfall intensity at the time of concentration, and is calculated using equation (15). The rainfall intensity values for each return period were as follows:

A 10-year return period was used to design drainage channels [51] and agricultural drainage system [25], including agricultural fields of less than 100 ha [52]. The rainfall intensity for the 10-year return period was 201.33 mm/h (Table 3).

Table 3

Rainfall intensity based on specific return period

Return period (years)	Equation		Rainfall intensity (mm/h)
Return period (years)	Intercept	Power	Rainfall intensity (mm/h)
5	801.26	−0.744	152.76
10	1056.00	−0.744	201.33
25	1226.10	−0.744	233.76
50	1440.00	−0.744	274.54
100	1598.00	−0.744	304.66

3.4 Runoff coefficient

The runoff coefficient is the sum of the effects of (1) land slope, (2) soil type, (3) land cover, and (4) drainage conditions. Bone Sugarcane Plantation is relatively flat (Cr = 0.11) with the predominant soil type is loam and clay, so infiltration is slow (Ci = 0.10). More than 90% of the land is well covered with sugarcane plants (Cv = 0.05), and there are existing well-defined small drainage channels (Cs = 0.09) [29]. Based on these conditions, the runoff coefficient (C) was calculated to be 0.35.

3.5 Discharge of surface runoff

The surface runoff discharge, based on the calculation results of the rational method, was 0.5 m³/s. This amount of surface runoff discharge must be released through the designed drainage channel.

3.6 Shape and size of drainage channels

The recommended vegetated channel shapes for sugar plantation land are parabolic and trapezoidal, because they are hydraulically stable and can pass all runoff from the plantation [13]. This shape can accommodate fully mechanized operation since mechanization equipment can operate safely because the wall slope is small [16], In addition, it is easy to construct using an excavator as has been done at Bone Sugarcane Plantations but without any analysis for the shape and size of the channels.

There are several factors that must be met by drainage design, namely slope, land area, and excess water discharge in the plantation. The following is the appropriate channel size based on the area and slope of the land in the area.

Drainage designs were categorized based on channel slopes of 1–4%, with land areas of 1–3 ha (Table 4). The drainage channel design was recommended for land slopes of 0–2%, because on these slopes, the land was susceptible to puddles, and the land did not have erosion potential, even with large runoff flow. Based on the data analysis and study results, the design of the drainage channel shape on the Bone Sugarcane Plantation land is parabolic. This is because the hydraulic performance of this shape is better than other channel shapes [53,54] and could drain all surface runoff. In addition, the slope of the channel wall was not steep so the channel wall is more stable and the mechanization equipment can operate without disturbance [16]. The diagram of the designed channel is shown in Figure 3.

Table 4

Drainage Channel Size Based on the Slope and Farm Size

No.	Slope channel (%)	1 ha farm area		2 ha farm area		3 ha farm area
No.	Slope channel (%)	Channel depth (m)	Channel width m)	Channel depth (m)	Channel width (m)	Channel depth (m)	Channel width (m)
1	1.00	0.40	1.25	0.40	1.70	0.50	1.70
2	2.00	0.35	1.25	0.40	1.40	0.40	1.70
3	3.00	0.30	1.15	0.35	1.35	0.40	1.50
4	4.00	0.30	1.10	0.30	1.35	0.35	1.50

Figure 3

Shape of drainage channel.

The depth of the channel structure requires the addition of 20% to the design depth for freeboard to prevent over-topping [55]. Based on peak discharge obtained from the rational equation, the largest channel size was 1.7 m wide and 0.60 m deep. The largest Froude number value at a depth of 0.5 m was 0.51 which indicated sub-critical flow. Therefore, a freeboard depth of 30 cm was added to the designed channel [41]. Thus, the largest channel size was 1.7 m wide with a depth of 0.90 m. This design is able to drain all surface runoff and does not interfere with the movement of mechanization equipment. The tractors used at Bone Sugarcane Plantation have a wheel center distance of 150 cm and a height of center of gravity of 62 cm. With a channel depth of 90 cm, the maximum slope of the tractor is 36.8^o when its tires reach the bottom of the channel. This slope is still safe for the tractor operation since its center of gravity is still within the baseline of tractor stability as suggested previously [56]. Nonetheless, it is recommended that the tractor is operated slowly under this condition to prevent accident due to the shift the center of gravity upward due to the slope of the tractor [20,56,57]. It is important to note that the condition where the tires of the tractor reach the deepest part of the channel during operation is sometime necessary to prevent a decrease in planting area due to the required head land for turning the tractor. In addition to the consideration for the movement of mechanization equipment, the depth of the channel is also limited to maintaining soil moisture so that soil temperature does not increase. Low soil moisture and high soil temperature can cause flowering of plants [58], including sugarcane [59]. Flowering sugarcane plants can cause a decrease in sugarcane productivity and sugar yield [60].

4 Conclusions

Based on the results of the study, it can be concluded that the appropriate drainage system applied to the Bone Sugar Plantation was surface drainage with parabolic shape. The largest width and depth of the designed channel were 1.7 m and 0.90 m, respectively. This shape and size of the channel did not disturb the movement of the mechanization equipment, and the channel walls were stable and able to drain all surface runoff. Restrictions were applied on the depth of the drainage channel in order to maintain soil moisture so that soil temperature does not increase because this can trigger sugarcane flowering which can lead to a decrease in sugarcane productivity and sugar yield. The results of this study can solve drainage problems in sugarcane fields that apply full mechanization in cultivation and harvest activities. In addition, the practical analysis used in this study can be adapted to analyze the design of drainage channel at other regions where field data on soil and rainfall intensity are scarcely available. There are some limitations of this study such as soil sampling was not conducted on the entire Bone Sugarcane Plantation, but only on land areas that have drainage problems. In addition, rain intensity data in the area was not available, so it was generated from rainfall data through the IDF curve. Therefore, for future study, it is suggested to collect these data to validate the results obtained in the current study.

Acknowledgments

The authors thank Ir. Andi Arwan (SEVP Operations PTPN XIV) for the appointment of researchers to carry out research on the design of the drainage system of the Bone sugarcane Plantations. Salary and research support are provided by Hasanuddin University.

Funding information: PT. Perkebunan Nusantara XIV is a company which provides research funding.
Conflict of interest: The authors state no conflict of interest.
Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

[1] Javan K, Mirabi M, Hamidi SA, Darestani M, Altaee A, Zhou J. Enhancing environmental sustainability in a critical region: climate change impacts on agriculture and tourism. Civ Eng J. 2023;9:2630–48. 10.28991/CEJ-2023-09-11-01.Search in Google Scholar

[2] Gravois K, Viator H, Reagan G, Beuzelin J, Griffin J, Tubana B, et al. Sugarcane Production Handbook. Louisiana: LSU Ag Center; 2014.Search in Google Scholar

[3] Hamdi H. Sustainability in sugarcane production: opportunities and limitations in SouthWest of Iran. Sugar Tech. 2016;18:642–6. 10.1007/s12355-016-0493-3.Search in Google Scholar

[4] Canning AD, Smart JCR, Dyke J, Curwen G, Hasan S, Waltham NJ. Constructed wetlands suitability for sugarcane profitability, freshwater biodiversity and ecosystem services. Environ Manage. 2023;71:304–20. 10.1007/s00267-022-01734-4.Search in Google Scholar PubMed PubMed Central

[5] Halbac-Cotoara-zamfir R, Farias-Ramirez AJ, de Miranda JH, Moreno-Pizani MA, Duarte SN, Paredes-Trejo FJ, et al. Simulation of subsurface drainage in the sugarcane crop under different spacing and drain depths. Land. 2022;11:1–20. 10.3390/land11050626.Search in Google Scholar

[6] Herdiansyah H, Negoro HA, Rusdayanti N, Shara S. Palm oil plantation and cultivation: Prosperity and productivity of smallholders. Open Agric. 2020;5:617–30. 10.1515/opag-2020-0063.Search in Google Scholar

[7] Jahani B, Soltani Mohammadi A, Nasseri AA, Van Oel PR, Sadeghi Lari A. Reduction of sugarcane water footprint by controlled drainage, in Khuzestan, Iran. Irrig Drain. 2017;66:884–95. 10.1002/ird.2148.Search in Google Scholar

[8] Morteza S, Vafaei M, Mohammadi AS, Naseri A, Van P. Investigation of sugarcane water footprint index components in free drainage, controlled drainage and water requirement conditions (Case study: Salman Farsi Agro-industry). Iran J Soil Water Res. 2022;52:2623–35. 10.22059/ijswr.2021.319562.668904.Search in Google Scholar

[9] Tama DR, Limantara LM, Suhartanto E, Devia YP. The reliability of W-flow run-off-rainfall model in predicting rainfall to the discharge. Civ Eng J. 2023;9:1768–78. 10.28991/CEJ-2023-09-07-015.Search in Google Scholar

[10] Riajaya PD, Pemanis BT, Kadarwati FT. Potensi Sumber Daya Iklim di Kabupaten Bone untuk Pengembangan Tanaman Tebu. Bul Tanam Tembakau, Serat Miny Ind. 2015;7:28. 10.21082/bultas.v7n1.2015.28-44.Search in Google Scholar

[11] Valipour M. How do different factors impact agricultural water management? Open Agric. 2016;1:89–111. 10.1515/opag-2016-0014.Search in Google Scholar

[12] Groot K de. Covariance structure analysis of health-related indicators for elderly people living at home, focusing on subjective sense of health. World Dev. 2018;1:1–15.Search in Google Scholar

[13] SASEX. Soil Conservation: A Guide to Farming Practices in the Sugarcane Industry; Mount Edgecombe, Natal: Experiment Station of the South African Sugar Association; 1974. p. 27.Search in Google Scholar

[14] Ghane E. Agricultural drainage. USA: Michigan State University; 2018. p. 1–8.Search in Google Scholar

[15] Ridge R, Reghenzani J. Drainage. Man Canegrowing. BSES; 2000. p. 227–39, https://elibrary.sugarresearch.com.au/bitstream/handle/11079/15541/Chapter11Drainage.pdf?sequence=31&isAllowed=y.Search in Google Scholar

[16] Wegener M, Yinggang O. Organization and profit-sharing in mechanized sugarcane harvesting: Is Australia’s experience relevant to China? Agric Eng Int CIGR J. 2015;2015:110–29.Search in Google Scholar

[17] Zhang M, Govindaraju M. Sugarcane production in China. Sugarcane – Technol Res. 2018;49:50–66. 10.5772/intechopen.73113.Search in Google Scholar

[18] Dagar H, Nimbrayan PK, Soni S, Kumar P. Sustainability of sugarcane cultivation and production in India – A review. Agric Mech Asia. 2021;51:1051–71.Search in Google Scholar

[19] Usaborisut P. Progress in mechanization of sugarcane farms in Thailand. Sugar Tech. 2018;20:116–21. 10.1007/s12355-018-0600-8.Search in Google Scholar

[20] Health and Safety Executive. Using tractors safely: A step-by-step guide. Free Leafl INDG185(rev3). 2013. p. 1–13, http://www.hse.gov.uk/pubns/indg185.pdf.Search in Google Scholar

[21] García-Gutiérrez C, Pachepsky Y, Ángel Martín M. Technical note: Saturated hydraulic conductivity and textural heterogeneity of soils. Hydrol Earth Syst Sci. 2018;22:3923–32. 10.5194/hess-22-3923-2018.Search in Google Scholar

[22] Dec D, Dörner J, Becker-Fazekas O, Horn R. Efecto de la densidad aparente sobre las propiedades hidráulicas de los suelos homogenizados y estructurados. Rev Cienc Suelo Nutr Veg. 2008;8:1–13.Search in Google Scholar

[23] Musa JJ, Gupa YU. An Overview of Methods Used in the Determination of Soil Hydraulic Conductivity. Al-Hikmah J Pure Appl Sci. 2019;7:22–30.Search in Google Scholar

[24] Setiawan BI. Pengukuran Konduktivitas Hidrolika Tanah Jenuh-Penentuan Diameter Pipa-Tegak (Standpipe) pada Metode Falling-Head. Keteknikan Pertan. 2005;19:139–41. 10.1108/f.2001.06919aab.019.Search in Google Scholar

[25] CVC. Handbook of Stormwater Drainage Design. North Rivers Local Gov. Lismore: AUS-SPEC-1\NSW; 2018.Search in Google Scholar

[26] ASCE, Rossmiller. Appendix A-1 : Runoff Peak Discharge Calculations; 1992. p. 2–9. https://www.maine.gov/dep/land/stormwater/stormwaterbmps/vol3/appendixa.pdf.Search in Google Scholar

[27] Grace A, Yudianto D, Fitriana F, No JC, Barat J. Optimasi Perencanaan Sistem Drainase Kawasan Industri Di Cikarang, Kabupaten Bekasi, Jawa Barat Design Optimization of Industrial Estate Drainage System in Cikarang, Bekasi Regency, West Java. J Tek Hidraul. 2022;13:103–12. 10.32679/jth.v13i2.712.Search in Google Scholar

[28] Hidayat R, Setiyadi S, Hutabarat LE. Evaluation of road drainage capacity to improve optimized road performance in Kebon Pala Area East Jakarta. IOP Conf Ser Earth Environ Sci. 2021;878:1–20. 10.1088/1755-1315/878/1/012051.Search in Google Scholar

[29] Thomason C. Hydraulic Design Manual, Notice: 2019-1 Section 12: Rational Method. Texas: Texas Department of Transportation; 2019.Search in Google Scholar

[30] Dibs H, Jaber HS, Al-Ansari N. Multi-fusion algorithms for detecting land surface pattern changes using multi-high spatial resolution images and remote sensing analysis. Emerg Sci J. 2023;7:1215–31. 10.28991/ESJ-2023-07-04-013.Search in Google Scholar

[31] Chaulya SK, Prasad GM. Slope failure mechanism and monitoring techniques. In Sensing and Monitoring Technologies for Mines and Hazardous Areas. Elseiver; 2016. p. 1–86. 10.1016/b978-0-12-803194-0.00001-5.Search in Google Scholar

[32] Shamkhi MS, Azeez MK, Obeid ZH. Deriving rainfall intensity-duration-frequency (IDF) curves and testing the best distribution using EasyFit software 5.5 for Kut city, Iraq. Open Eng. 2022;12:834–43. 10.1515/eng-2022-0330.Search in Google Scholar

[33] Anghel CG, Ilinca C. Parameter estimation for some probability distributions used in Hydrology. Appl Sci. 2022;12:1–25. 10.3390/app122412588.Search in Google Scholar

[34] Mustofa MJ, Kusumastuti DI, Romdania Y. Analisis Hidrologi dan Hidrolika pada Saluran Drainase Ramanuju Hilir Kotabumi (Menggunakan Program HEC-RAS). J Rekayasa Sipil dan Desain. 2015;3:303–12.Search in Google Scholar

[35] Amin MT, Izwan M, Alazba AA. A best-fit probability distribution for the estimation of rainfall in northern regions of Pakistan. Open Life Sci. 2016;11:432–40. 10.1515/biol-2016-0057.Search in Google Scholar

[36] Suadnya D, Sumarauw J, Mananoma T. Analisis Debit Banjir Dan Tinggi Muka Air. J Sipil Statik. 2017;5:143–50. https://ejournal.unsrat.ac.id/index.php/jss/article/view/29979.Search in Google Scholar

[37] Upomo TC, Kusumawardani R. Pemilihan distribusi probabilitas pada analisa hujan dengan metode goodness of fit test. J Tek Sipil dan Perenc. 2016;18:139–48. 10.15294/jtsp.v18i2.7480.Search in Google Scholar

[38] Majeed AR, Nile BK, Al-Baidhani JH, Chung MY, Loo VH. Analysis of intensity, duration, and frequency rain daily of Java Island using mononobe method. J Phys Conf Ser. 2021;1783:1–7. 10.1088/1742-6596/1783/1/012107.Search in Google Scholar

[39] Thomason C. Hydraulic Design Manual Notice: 2019-1 Section 11: Time of Concentration. Texas: Texas Department of Transportation; 2019.Search in Google Scholar

[40] FDOT. State of Florida Department of Transportation Drainage Manual. Florida: Florida Department of Transportation; 2023.Search in Google Scholar

[41] Payson A. CHAPTER 152: GRADING AND DRAINAGE. Cincinnati, Ohio: American Legal Publishing; 2023. https://codelibrary.amlegal.com/codes/payson/latest/overview.Search in Google Scholar

[42] Nurfatimah AA. Alur Produksi Gula Kristal Putih PTPN XIV Pabrik Gula Bone, Arasoe. Makassar: Politeknik ATI Makassar; 2022.Search in Google Scholar

[43] Sanjaya AR, Habibah S. Analisis Pengendalian Persediaan Bahan Baku Tebu Dalam Pembuatan Gula Pasir di Pabrik Gula Bone Arasoe. J Ilm Al-Tsarwah. 2019;2:125–39. 10.30863/al-tsarwah.v2i2.273.Search in Google Scholar

[44] Suhardi, Mubarak H, Rizal M. Desain Sistem Drainase Permukaan Lahan Pabrik Gula Bone. Makassar: Hasanuddin University; 2022.Search in Google Scholar

[45] Chattamvelli R, Shanmugam R. Gumbel Distribution. In: HandWiki [Internet]; 2021. p. 1–6. 10.1007/978-3-031-02435-1_11.Search in Google Scholar

[46] Fasdarsyah F. Analisis Curah Hujan Untuk Membuat Kurva Intensity-Duration-Frequency (Idf) Di Kawasan Kota Lhokseumawe. Teras J. 2014;4:22–30. 10.29103/tj.v4i1.28.Search in Google Scholar

[47] Ritzema H. Subsurface drainage. UNESCO-IHE MSc Programme Land and Water Development for Food Security. Wageningen: UNESCO-IHE; 2014.Search in Google Scholar

[48] Wahjunie ED, Baskoro DPT, Tarigan SD. Peranan Pergerakan Air Dalam-Tanah dalam Menurunkan Aliran Permukaan. J Ilmu Pertan Indones. 2021;26:292–300. 10.18343/jipi.26.2.292.Search in Google Scholar

[49] Chaibandit K, Konyai S. Using statistics in hydrology for analyzing the discharge of Yom river. APCBEE Procedia. 2012;1:356–62. 10.1016/j.apcbee.2012.03.059.Search in Google Scholar

[50] Sofia DA, Nursila N. Analisis intensitas, durasi, dan frekuensi kejadian hujan di wilayah Sukabumi. JTERA (J Teknol Rekayasa). 2019;4:85. 10.31544/jtera.v4.i1.2019.85-92.Search in Google Scholar

[51] Yang Y, Li M, Xiong M, Cao J. Return period for urban rainwater drainage networks based on the lowest total social investment method: A case study in Tianjin, China. Pol J Environ Stud. 2019;28:3993–9. 10.15244/pjoes/99105.Search in Google Scholar

[52] Ponce V. Return Period to be used for Hydrologic Design; 2008. https://ponce.sdsu.edu/return_period.html.Search in Google Scholar

[53] Han YC, Gao XP, Xu ZH. The best hydraulic section of horizontal-bottomed parabolic channel section. J Hydrodyn. 2017;29:305–13. 10.1016/S1001-6058(16)60740-0.Search in Google Scholar

[54] Yang Z, He W, Wang Y, Lou Z, Duan P. Research on the comprehensive optimization of the hydraulic performance and frost-heaving resistance of a parabolic channel. Water (Switz). 2020;12:1–15. 10.3390/W12092574.Search in Google Scholar

[55] Hussein T. Open channel flow. Irrigation and Drainage Engineering; 2019. p. 1–52. https://theconstructor.org/fluhttps://engineering.mu.edu.iq/wp-content/uploads/2019/09/WaterResources.pdf.Search in Google Scholar

[56] HOSTA (Hazardous Occupations Safety Training in Agriculture). Tractor stability, national safe tractor and machinery operation program. Pennsylvania; 2004. https://extension.psu.edu/tractor-stability-and-instability.Search in Google Scholar

[57] New Zealand Government. Safe use of tractors on farms. New Zealand; 2014. https://www.worksafe.govt.nz/topic-and-industry/agriculture/farm-vehicles/tractors/safe-use-of-tractors-guide/#lf-doc-35185.Search in Google Scholar

[58] Jaroensutasinee K, Jaroensutasinee M, Boonsanong P. Climatic factor differences and mangosteen fruit quality between on-and off-season productions. Emerg Sci J. 2023;7:578–88. 10.28991/ESJ-2023-07-02-020.Search in Google Scholar

[59] Mehareb EM, Salem ESR, Ghonema MA. Effects of environmental factors on sugarcane flowering under natural conditions in Egypt. Egypt J Plant Breed. 2016;20:1093–105. 10.12816/0046420.Search in Google Scholar

[60] Rao PS. Effects of flowering on yield and quality of sugarcane. Exp Agric. 1977;13:381–7. 10.1017/S0014479700008139.Search in Google Scholar

Received: 2023-12-11

Revised: 2024-01-23

Accepted: 2024-01-28

Published Online: 2024-03-30

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

https://doi.org/10.1515/opag-2022-0264

Keywords for this article

surface drainage; parabolic shape; stable structure; full mechanization

Creative Commons

BY 4.0