Managing Irrigation Sediment Barriers in a Tropical Volcanic Basin through Mathematical Model

: Volcanic eruptions transport substantial amounts of sediment into river systems. It damages irrigation structures that depend on the nearby river for water delivery, reducing the conveyance efficiency. This study aims to propose an efficient approach for the management of sand traps as the main sediment barriers in irrigation networks within the Progo-Opak-Serang (POS) Volcanic Basin. It is accomplished by a measurable approach: a mathematical framework executed with the Hydrologic Engineering Center’s River Analysis System (HEC-RAS). This study focuses on selected sand traps: Badran, Blawong, and Pengasih. The results show that the calibrated and validated Manning’s coefficients of Badran, Blawong, and Pengasih Sand Traps are 0.014, 0.020, and 0.025, respectively. The combination of Thomas as a sorting method, Rubey as a fall velocity method, and Laursen as a transport function can represent the transport parameters of the sand traps within the POS Basin. The recommended flushing discharge and duration for Badran, Blawong, and Pengasih Sand Traps are 4, 4.4, and 1.9 m 3 /s and 150, 50, and 45 min, respectively, while the flushing frequency is 4, 3, and 3 times a year. The existing sand trap performance in Badran is less effective, while that of Blawong and Pengasih is less efficient. This study assists in improving food production and security by promoting sustainable irrigation systems.


INTRODUCTION
The surface irrigation system plays an essential role in sustaining food production in Southeast Asia 1 specifically for rice, which is a staple food. 2,3However, it faces challenges regarding its five pillars, including water availability, infrastructure, management system, management institutions, and human capital. 4,5The current condition has been exacerbated by land use and climate change (LU&CC) issues that globally affected the river basin in terms of altered hydrological processes, which are closely associated with the availability of water resources and the longterm sustainability of the surrounding ecosystem. 6−9 In Indonesia, high soil erosion rates and sediment yields are significant concerns in most river basins. 10This tropical country has a total of 458 Watersheds, out of which 60 are classified as severely heavy, 222 as critical, and 176 as potentially critical in terms of soil erosion rates. 11−14 Out of the 133 river basins in Indonesia, 127 are volcanic river basins. 15,16−19 Mount Merapi, renowned as one of the most active volcanoes globally, regularly undergoes mild and massive eruptions.Mount Merapi, along with four other volcanoes, resides in the Progo-Opak-Serang (POS) River Basin, which spans the Special Region of Yogyakarta and the Central Java Province.The simultaneous presence of substantial soil erosion rates and the existence of volcanoes amplifies the sediment yield in this basin.According to ref 16, the average rate of erosion for the POS Basin in the past decade was 180 tons/ ha/year, with a sediment yield of 51 tons/ha/year.On the other hand, the River Basin Organization of Serayu Opak, which manages this basin, indicated that the erosion rate for the POS Basin in 2010 was 235 tons/ha/year. 20The erosion rate of the POS basin might be classified as moderate to heavy. 16,21he viability of irrigation networks relies predominantly on rivers for their water provision. 22−25 Sedimentation can also diminish the efficiency of irrigation conveyance, ultimately leading to a decline in rice production. 26−29 Sand traps facilitate the deposition of sediment carried by irrigation intakes, consequently ensuring that the flow entering the primary irrigation channel remains devoid of sediment.Sediment deposition occurs within a certain time frame known as the operational period and terminates with the removal of the deposited sediment, either by returning it to the river or by a process known as the flushing period. 25,29ffective and efficient functioning of sand traps can enhance the efficacy of irrigation conveyance, serving as an indirect strategy for adapting to climate change. 1,30,31In Indonesia, the management of sand traps has generally been insufficient, with the existing approach being subjective and without a definitive basis.A robust approach is necessary to manage sand traps to ensure their reliable use for the operation and maintenance of irrigation networks.Particularly inside the volcanic river basin, the irrigation network is highly susceptible to sedimentation.
Similar studies on the management of sand traps in irrigation networks are scarce, specifically in volcanic basins.Prior research has solely focused on evaluating the performance of sand traps using analytical calculations or mathematical models without offering guidance on practical and efficient management strategies.Nindito et al. (2008) employed three-dimensional numerical modeling to simulate the behavior of sand trap in Sapon Weir, Indonesia.The sedimentation process was mathematically described, and the efficacy of trapping sediment depends on the incoming material's properties and the flow parameters. 32 Serede et al. (2015) conducted a study on the Mwea Irrigation Scheme in Kenya and determined that the Hydrologic Engineering Center's River Analysis System (HEC-RAS) can serve as an effective decision support system for the optimal management and maintenance of irrigation systems. 33,34idaryanto (2018) evaluated the effectiveness of sand traps at Pendowo and Pijenan Weirs, Indonesia.The performance of sand traps can be assessed by their capacity to hydraulically deposit and discharge sediment during regular flushing operations. 35−29 It needs to be enriched with several models of other sand traps in the basin to formulate comprehensive and interconnected management.This study aims to provide a method for effectively managing sand traps as the primary sediment barrier in irrigation networks.This will be achieved using a quantifiable methodology: a mathematical model implemented with HEC-RAS.This study can serve as a valuable resource for the management of sand traps in irrigation networks located in volcanic river basins.Reliable and sustainable management of irrigation networks can contribute to the enhancement of food production and security.

Study Area.
The study was conducted in the POS River Basin, a volcanic basin in Indonesia under the jurisdiction of the River Basin Organization of Serayu-Opak (BBWS SO).The POS Volcanic Basin encompasses an area of 5,241 km 2 and spans the Special Region of Yogyakarta (63%) and Central Java Province (37%).It is commonly referred to as a cross-provincial river basin. 16Indonesia is home to a total of 147 volcanoes with 76 of them presently active.These volcanoes are distributed among the islands of Java, Lesser Sunda, Sumatra, and Celebes. 36Within the POS Volcanic Basin, there are five noticeable volcanoes: Mount Sindoro (3,136 mMSL), Mount Sumbing (3,240 mMSL), Mount Telomoyo (1,894 mMSL), Mount Merbabu (3,142 mMSL), and Mount Merapi (2,986 mMSL), which is renowned as one of the most active volcanoes globally. 16,37ount Merapi has exhibited frequent volcanic eruptions, with the level of activity intensifying over the past two decades.In 2010, the eruption of Merapi was highly explosive, attaining a volcanic explosivity index (VEI) of 4 out of 7. 38,39 The volcanic eruptions have resulted in significant sedimentation, pyroclastic activity, and debris flows, posing a threat to life and property in the downstream region.Mount Merapi is situated at coordinates 7°32.5′South and 110°25.5′East.The elevation is 2,986 mMSL and 3,079 m above the city of Yogyakarta. 37,40The POS Volcanic Basin comprises three watersheds: Progo, Opak, and Serang, with respective areas of 2,640 km 2 , 2,344 km 2 , and 256 km 2 .It is characterized by a combination of mountainous and low-lying terrain.The Progo and Opak Watersheds encounter specific challenges associated with the volcanic eruptions of Mount Merapi, in addition to other connected concerns including the watershed's susceptibility, land usage discrepancies, and inappropriate land and water conservation practices. 20Figure 1 depicts the map of the POS Volcanic Basin.

Selection of Sediment Barriers.
As defined in the Indonesian irrigation design standard, sediment barriers known as sand traps frequently appear at the beginning of irrigation networks. 41,42Figure 2 displays the typical layout of a sand trap.Within the POS Volcanic Basin, numerous irrigation schemes (I.S.) extract water from the river.Four criteria were used to identify sand traps as the research subject.The first criterion is the significance of irrigated areas; 12 I.S. within the POS Basin have substantial areas, including 3 central government authority I.S. and 9 provincial government authority I.S. 41,42 (the detailed description can be seen in the Supporting Information).The second criterion is the significance of sediment yield, as mapped in the previous study. 16The three largest sediment yields were found at the inlet of Badran, Kalibawang, and Blawong I.S with amounts of 253 tons/ha/year, 180 tons/ha/year, and 63 tons/ ha/year, respectively.The third criterion is the availability of sand traps in I.S., as not all I.S. have sand traps due to improper design.Sand traps are present at Badran, Kalibawang, and Blawong.The fourth criterion pertains to the representativeness of the watersheds.Each watershed within the POS Basin is represented by only one sand trap.Badran and Kalibawang are within the Progo Watershed, whereas Blawong is inside the Opak Watershed.Based on the consideration of the second and fourth criteria, we chose Badran instead of Kalibawang to represent the Progo Watershed, and we included the Pengasih Watershed to represent the Serang Watershed.−29 Hence, this study specifically examines three selected sand traps: Badran, Blawong, and Pengasih (Figure 1).

Methodological
Framework.Scheme 1 shows the two primary aspects of this study framework: field measurements and modeling with HEC-RAS 6.2. 43Geometric data are crucial for sand trap hydraulic modeling.The two conditions are filled and empty.First, the geometry is measured at the end of the operational period when the sand trap storage is full of sediment and, second, at the beginning of the operational period when it is empty.We also measured discharge and water surface elevations under the first and second conditions.All data from the first condition was used for hydraulic calibration and the second for hydraulic validation.After hydraulic validation, the model can be used to calibrate sediment transport using the data from the flushing period when bed changes were measured.We needed grain size distribution and specific gravity for each crosssection; therefore, we examined sediment samples.In the second part, we simulated the sand traps during the operational and flushing periods.We included sediment load monitoring and biweekly irrigation water requirements for the operational period.
Since HEC-RAS boundary conditions include the sand trap's rating curve, sediment load monitoring is crucial.We generated rating curves for three sand traps based on field measurements to indicate the relationships between flows (Q st ) in m 3 /s and total loads (Qs st ) in tons/day (see the Supporting Information).We also monitored discharges and the water temperature.Finally, we simulated sand trap sediment transport during operational and flushing periods to recommend the flushing frequency, discharge, and duration.In addition to the modeling results, the recommendation considers four additional relevant factors: the availability of river water, the demand for irrigation water, the cropping pattern, and the seasons.
2.4.Mathematical Modeling Using HEC-RAS.Mathematical models are being used to comprehend the hydraulic characteristics of intricate and expansive irrigation networks, particularly for assessing and enhancing system efficiency. 33,34his research replicates sand trap flow and sedimentation in irrigation networks using HEC-RAS version 6.2.It enables the simulation of the water surface profile in stable rivers, turbulent river flows, and sediment load estimation. 44−46 It is suitable for assessing the hydraulic steady-state conditions of the canal.Thus, it can serve as a decision support system by guaranteeing the optimum operation and maintenance of irrigation systems. 34The computation of water surface profiles involves solving the energy equation using an iterative approach known as the standard step method, which calculates the profiles from one cross-section to the next (see eq 1). 47The energy head loss (h e ) between two cross-sections consists of friction losses and losses due to contraction or expansion, and the length of the reach (L) is determined by applying eqs 2 and 3.
where Z 1 , Z 2 = elevation of the main channel inverts; Y 1 , Y 2 = depth of water at cross-sections; V 1 , V 2 = average velocities (total discharge/total flow area); α 1 , α 2 = velocity weighting coefficients; g = gravitational acceleration; h e = energy head loss; L = discharge weighted reach length; S f = representative friction slope between two sections; C = expansion or contraction loss coefficient; L lob , L ch , L rob = cross-section reach lengths specified for flow in the left overbank, main channel, and right overbank, respectively; and Q Q Q lob ch rob + + = arithmetic averages of the flows between sections for the left overbank, main channel, and right overbank, respectively.
HEC-RAS typically involves five modeling steps: starting a new project, entering geometric data, entering flow data and boundary conditions, performing hydraulic calculations, and viewing and publishing results. 48,49In hydraulic calibration and validation, we carried out analysis using steady flow data, with the main input being discharge during the operational period.In contrast, we employed quasi-unsteady flow involving the sediment data module in sediment transport calibration and sand trap simulations during operational and flushing periods.
The sediment routing methods in HEC-RAS solve the sediment continuity equation, also referred to as the Exner equation (see eq 4). 50−52 Sediment transport can be calibrated during the flushing period, as this condition provides bed change data that can be used as a comparison parameter.The flushing period commences whenever the sand trap reaches its maximum capacity, indicating that it is filled with sediment.The sand trap's performance during the flushing period can be evaluated by considering the flushing discharge and duration.We can assess the flushing effectiveness by examining the channel bed's state following the flushing process.If the sediment volume is completely depleted, it indicates that the flushing process was successful in removing the sediment.In addition, it is necessary to evaluate the efficiency of the flushing process by considering the duration employed.The shorter the duration, the higher the level of efficiency.
where B = channel width; n = channel elevation; λ p = active layer porosity; t = time; x = distance; and Q s = transported sediment load.
Sediment transport calibration aims to calibrate the model by fitting the transport parameters including sorting, fall velocity, and transport function.HEC-RAS 6.2 has three sorting methods (Thomas/Exner 5, active layer, and Copeland/Exner 7), seven fall velocity methods (Rubey, Toffaleti, Van Rijn, Report 12, Dietrich, Soulsby, and Wu and Wang), and eight transport functions (Meyer Peter Muller/MPM), Toffaleti, MPM-Toffaleti, Yang, Wilcock Crowe, Soulsby, Van Rijn, and Wu).The model was calibrated using 168 transport parameter combinations.Table 1 shows the data and the beginning and boundary conditions.The 168 scenarios were divided into 21 groups containing simulations of a sorting method (from 3) and a fall velocity method (from 7) combined with eight transport functions.The model ran based on the field flushing duration.Performance indicators (root-mean-square error/RMSE), mean absolute error/MAE), and Nash-Sutcliffe efficiency/NSE) were used to select the most satisfying transport parameters from the 21 best-performing channel beds compared to the measured channel bed after flushing.The operational period of the sand trap begins after the flushing period ends, and the sand trap stores sediment during this time.The mathematical modeling during this period aims to estimate when the capacity is met; it is important to recommend flushing frequency per year.Simulations of the sand trap during flushing and operation differed significantly.Table 1 shows the flushing and operational data for sand trap modeling.
2.5.Collected Data.Field measurements required for collecting primary data have been mentioned in the methodological framework.Measurements were carried out on the three selected sand traps (Badran, Blawong, and Pengasih) from December 2022 to June 2023, with summary data as in Table 2.This data is the basis for modeling sand traps in operational and flushing periods, the typical layout of which is indicated in Figure 3.When formulating recommendations for the sand trap flushing framework, we also considered data on the supply and demand of water in each irrigation area.The data on water availability is based on the average river discharge at each weir over a 10-year period (2010−2020), while the planting plan for 2022 determines the irrigation water requirements.Data was obtained from the River Basin Organization of Serayu-Opak and the Government of the Special Region of Yogyakarta.

Hydraulic Calibration and Validation.
Manning's bed roughness coefficient, weir and gate coefficients on inline structures, and contraction and expansion coefficients are unknown.We approximated contraction and expansion coefficients using the default values of 0.1 and 0.3 from observations that the channel geometry transitions gradually.Cross-sections following inline constructions have factors of 0.6 and 0.8 for abrupt transition conditions based on the HEC-RAS Hydraulic Reference Manual. 47When modeling the inline structures, we set the entrance and exit loss coefficients and coefficients of weirs and gates.HEC-RAS suggests coefficients for each structural type.The acceptable discharge coefficient for the sluice gate flow is 0.5−0.7,and the broad crested weir flow is 1.38−1.71.We tried applying those coefficients in inline structures, but we had no notable results.Manning's bed  53 In the case of hydraulic models, the geometry of the channel, boundary conditions, and Manning's coefficient determine the quality of the model and its outputs. 54−59 In addition to reference tables, field data can be utilized to calculate Manning's values.Badran's sand trap appeared to have a sandmixed gravel bottom with concrete walls.Manning's coefficient table in the HEC-RAS hydraulic reference gives minimum, normal, and maximum values of 0.011, 0.013, and 0.015 for lined or built-up channels using trowel finish concrete, respectively.Reference Manning's coefficients for all three sand traps can be justified in Table 3. Hydraulic calibration through adjusting Manning's coefficient dramatically influences model sensitivity.The calibration approach in Badran used 12 Manning's coefficient values, including 0.030, 0.025, and 10 others from 0.020 to 0.011.The determination of these numbers is based on the reference Manning's values reported in Table 3, and we also included numerous Manning values beyond the reference range to confirm that the calibrated values were not definitely outside the reference range.Those Manning's values were combined with the measured discharge and geometry when the sand trap was filled 3 months after the previous flushing.The calibration parameter (the water surface profile) compares the modeling and field measurements.Chart 1a compares observed and estimated water surface elevations using 12 Manning coefficient values.The channel bed profile indicated upstream (left) to downstream (right) places.It is evident that Manning's coefficient does not fall within the range of 0.025−0.030.The two Manning's coefficient values (0.030 and 0.025) produce water surface elevations that differ greatly from actuality.The remaining Manning's coefficient values, 0.020−0.011,produce similar results.
Performance indicators are used to estimate Manning's coefficient value that creates water surface elevations closest to the measurement result.A Manning's value of 0.014 produces the most favorable results, with RMSE, MAE, and NSE of 0.0020, 0.0017, and 0.8688, respectively.A data set with similar parameters from measurements when the sand trap is nearly empty or 3 days after the previous flushing period was used to During the operational period, water and sediment flow from the irrigation intake to the irrigation primary channel.However, during the flushing period, they are directed toward the flushing gate of the sand trap to be returned to the river.We employed a similar procedure to Blawong and Pengasih Sand Traps, and it was found that Manning's coefficient yields the most desirable results, as the performance indicators indicate are 0.020 and 0.025, respectively (RMSE: 0.0088, MAE: 0.0073, NSE: 0.9295 based on Blawong's validation, RMSE: 0.0221, MAE: 0.0168, NSE: −0.9833 based on Pengasih's validation).Hence, Manning's coefficients of 0.014, 0.020, and 0.025 accurately reflect the actual field conditions of Badran's, Blawong's, and Pengasih's Sand Traps, respectively.They can be used as parameters for simulating the Blawong Sand Trap during operational and flushing periods.The value of 0.025 falls outside the range recommended by the HEC-RAS hydraulic reference but is still deemed acceptable.The detailed results for Blawong and Pengasih are included in the Supporting Information.

ACS ES&T Water
The Pengasih Sand Trap, similar to the Blawong, removed sediment well with flushing.Chart 4a shows that Thomas (Exner 5) sorting, Rubey fall velocity, and MPM-Toffaleti transport functions produce the most accurate profile (RMSE: 0.0075, NSE: 0.0024, MAE: 0.9998).Chart 4b demonstrates that 1.90 m 3 /s discharge generated the best results (RMSE: 0.007, MAE: 0.002, NSE: 0.999).The results failed to demonstrate any significant changes in channel bed adhesion to flushing; all profiles are close to the Pengasih Sand Trap's empty channel bed.Discharges within the range 1.1−3.0m 3 /s are suitable for flushing the Pengasih sand trap.Practically, it can be adjusted to river water availability.As shown in Chart 4c, we examined the historical bed elevation at the noteworthy cross-section in the Pengasih Sand Trap (RS.133.6) based on a discharge of 1.9 m 3 / s.After 45 min, the sediment is completely removed.The recommended flow rate for flushing the Pengasih Sand Trap is between 1.1 and 3.0 m 3 /s, depending on river water conditions.The recommended flushing duration is 45 min.Thus, the current method is effective yet inefficient.The suggested duration from this study can be implemented.
The transport parameters of three sand traps in the POS Volcanic Basin were calibrated and are found to be broadly similar, as indicated in Table 4.The fall velocity of all three sand traps is exactly identical, namely, Rubey.The sorting method employed by Badran and Pengasih is Thomas (Exner 5), but Blawong's method is an active layer.Badran and Blawong are suitable for the Laursen (Copeland) for the transport function, but Pengasih's is MPM-Toffaleti.Previous research revealed that the optimal combination of transport parameters for the Pengasih sand trap consisted of Thomas (Exner 5) as the sorting method, Rubey as the velocity method, and Laursen (Copeland) as the transport function. 25,29This work utilized the more up-to-date HEC-RAS 6.2 software, in contrast to previous studies that used HEC-RAS 4.1, for sand trap modeling.HEC-RAS 6.2 introduced a new transport function known as MPM-Toffaleti.Nevertheless, the outcomes of employing Laursen (Copeland) as the transport function, along with Thomas as the sorting method and Rubey as the fall velocity method, remained satisfactory for both the Pengasih and Blawong Sand Traps.The performance indicators for Blawong were indicated as follows: RMSE: 0.046, MAE: 0.025, NSE: 0.994.Similarly, for Pengasih, they were RMSE: 0.084, MAE: 0.020, and NSE: 0.971.It can be concluded that the combination of Thomas (Exner 5) as the sorting method, Rubey as the fall velocity method, and Laursen (Copeland) as the transport function can represent the transport parameters of sand traps in the POS Volcanic Basin.

Mathematical Modeling in the Operational
Period.The Badran Sand Trap can hold up to 950 m 3 of sediment.We need to assess the point at which that level of capacity is reached.Chart 5a, b displays Badran's bed configuration and volume change on a bi-weekly basis.Chart 5a illustrates the process of sediment deposition, with data points shown on a bi-weekly basis.The conspicuous deposition is depicted in a dark blue hue, symbolizing the arrangement of the December 31 period.The sediment accumulates beyond the capacity of the sand trap.Chart 5b facilitates the observation of the sediment volume that accumulates in the sand trap every 2 weeks.The data indicates that for the period from April 1, the amount of sediment volume captured is 1,089.09m 3 .Simply explained, the sand trap reaches its maximum capacity during that period.
The capacity of the Blawong Sand Trap is 134 m 3 , whereas the capacity of the Pengasih Sand Trap is 84 m 3 .Chart 5c displays the bed configuration and cumulative volume change of Blawong at intervals of 2 weeks, while Chart 5e shows the same for Pengasih.Additionally, Chart 5d,f depicts the bed configuration and cumulative volume change of Pengasih.The majority of the sediment in Blawong is deposited in the upstream section of the sand trap.The cause of the issue is attributed to design oversight in the construction.Initially, the channel is undergoing both an expansion in width and an increase in depth.Subsequently, a discharge measuring device exists that is incapable of operating effectively.The building exhibits a resemblance to the Parshall flume but is experiencing subsidence, resulting in the absence of critical flow.Hence, that structure is unsuitable for quantifying the flow discharge across the sand trap.Due to the predominant deposition of sediment in the initial section of the sand trap, it is unable to be adequately stored in the sand trap storage, as depicted in Chart 5c.Nevertheless, the assessment of volume change continues to pertain to the capacity of the sand trap.Chart 5d shows that the Blawong Sand Trap reached its maximum capacity on October 16, with a total sediment volume of 135.59 m 3 .In Pengasih, sediment adequately fills the storage tank according to the modeling outcomes.The maximum capacity was reached during the period of November 1, with a total sediment volume of 84.10 m 3 .
3.4.Management of Irrigation Sediment Barriers.In practical terms, there is no specific reference to the act of flushing sand traps.The field operators flush them at their own discretion.Based on observations, the operator flushes the Badran Sand Trap four times a year.In Pengasih, the operator flushes the sand trap three times a year.Furthermore, in Blawong, the operator performs sand trap flushing at a higher frequency, ranging from every 2 weeks to 1 month.The recommendation of the flushing efficiency can support the efficiency of irrigation management.During the flushing process, the operator must interrupt the distribution of water to the irrigation networks.Operating the intake gates manually also requires exertion.Based on the modeling above, it is recommended to flush the sand traps approximately three times each year for Badran, starting from April 1.For Blawong and Pengasih, it is recommended that the sand traps be flushed once per year.The Blawong Sand Trap was flushed on October 16, and that of Pengasih was conducted on November 1.Nevertheless, it is crucial to consider additional significant factors, such as (i) the availability of river water, (ii) the demand for irrigation water, (iii) the cropping pattern, and (iv) the seasons.The water balance is one of the factors to be considered.It means flushing may occur when there is more water available than needed for irrigation and flushing.It guarantees sufficient water is accessible to meet the irrigation requirements and carry out the flushing process.Chart 6a−c illustrates the water balance, recommended flushing discharge, cropping pattern, and flushing periods.Chart 6a demonstrates that the river water is consistently enough in Badran to meet the irrigation water requirement throughout the year.However, it may not always be able to sustain flushing, especially during the period from September to October.The water availability refers to the mean bi-weekly river discharge at Badran Weir over a period of 10 years.In Indonesia, the water allocation management is scheduled on a bi-weekly basis to align with the paddy growing phase.Rice cultivation typically follows a cropping pattern with three distinct planting seasons (PS), commonly referred to as "musim tanam (MT)" in Bahasa.The cropping sequence of the Badran Irrigation Scheme consists of PS 1 (paddy) from October to January, PS 2 (paddy) from February to May, and PS 3 (paddy) from June to September.The planting seasons culminate in harvest time.The periods of flushing, as determined by the modeling result, are depicted in Chart 6a using black-dotted lines.The periods cannot be appropriately implemented since the third period coincides with the October 1 period, during January to April, and PS 3 (secondary crops) from May to August.The secondary crops often grown in the POS Basin include corn, chili, shallot, and sugar cane; they are also referred to as "palawija" in Bahasa.According to the modeling outcome, it is recommended to perform the flushing during the period of October 2, as shown by the black-dotted line in Chart 6b.However, the October 2 period occurs only 2 months after the preceding harvest time during the dry season.Typically, at that time, the irrigation networks in Indonesia are intentionally drained to make it easier to conduct surveys and perform maintenance tasks.The drying process occurs from the weir, which includes sand traps, to the tertiary irrigation network.Hence, it is recommended to advance the flushing period by 2 months, specifically on August 2.In addition, it is necessary to carefully plan additional flushing activities, especially during the rainy season, to anticipate and prepare for an unexpected increase in the amount of sediment being carried.It is advisable to carry out additional flushing periods in Blawong at the completion of PS 2 (April 2) and PS 3 (December 2) or align them with the harvest times.Practically, there are no defined intervals for flushing the Blawong sand trap.The operator performs the flushing procedure at intervals of 2 weeks to 1 month.It suggests that the sand trap management in Blawong is inefficient.
Throughout the year in Pengasih, there is a limited availability of river water to meet the irrigation demand and flushing mechanism, especially during the months of July to September.As mentioned earlier, the most suitable discharge rate for flushing the Pengasih Sand Trap, based on the modeling results, is 1.9 m 3 /s.However, discharges ranging from 1.1 to 3.0 m 3 /s are also considered to be appropriate.The cropping pattern of the Pengasih Irrigation Scheme consists of PS 1 (paddy) throughout the months of November to February, PS 2 (paddy) from March to June, and PS 3 (secondary crops) from July to October.According to the modeling outcome, it is recommended to perform the flushing during the time of November 1, as shown by the black-dotted line in Chart 6c.With respect to the five factors under consideration, that time frame is deemed to be suitable.Moreover, it is advisable to incorporate supplementary flushing periods into the Pengasih Sand Trap.Similar to the Blawong Sand Trap, this system must anticipate unpredictable sediment inflow during the rainy season and enable surveys and maintenance operations across the whole irrigation network during the dry season.The dry season in Indonesia typically spans from October to March.The additional flushing periods should be carried out at the end of PS 1 (February 2) and PS 2 (June 2).These events align with the harvest time, during which the paddy field does not require irrigation.Currently, the operator performs sand trap flushing on a quarterly basis.The sand trap management in Pengasih is deemed efficient.
Recommendations regarding the management of sediment barriers, specifically sand traps, need to be communicated to the government in charge of irrigation, dam operators, operations and maintenance officers, and Water Users' Associations (WUA) through group discussion forums.In Indonesia, there is a coordination and communication institution between representatives of the government, WUA, and irrigation network users, which is called the Irrigation Commission. 60,61Based on the Regulation of the Minister of Public Works and Public Housing Number 17/PRT/M2015, irrigation commissions are categorized into provincial, interprovincial, and district/city levels.The duties of the irrigation commission include formulating a policy plan to maintain and improve the condition and function of irrigation to be proposed to the Minister; formulating an annual plan for the provision, distribution, and delivery of irrigation water for agriculture and other needs which is then proposed to the Minister; formulating maintenance and rehabilitation plans for irrigation networks to be forwarded to the Minister; discussing and providing considerations in overcoming problems in irrigation areas due to drought, floods, and other natural disasters; providing input and considerations in efforts to maintain the reliability and sustainability of the irrigation system; and others. 62his study will be valuable for sediment management and planning of operation and maintenance activities, particularly in volcanic river basins.These topics can be further explored and developed at local irrigation commission hearings, which take place biannually.This can enhance the efficiency of the irrigation network, hence contributing to the improvement of the irrigation functionality.WUA and irrigation network users will directly experience the positive impact of enhancements in the conditions and functionality of irrigation networks.On the other hand, WUA performance is also important in improving services and sustainability of irrigation systems; these two elements are intricately interconnected. 63,64−67 This can immediately enhance the well-being and quality of life of farmers.Implementing this mathematical framework for irrigation management on a nationwide scale will contribute to the attainment of a reliable and sustainable irrigation system.Dependable and enduring irrigation systems on a worldwide scale can aid in improving food production and security as well as achieving sustainable development goals, namely, goals 1 (eradicating poverty), 2 (eliminating hunger), and 6 (ensuring clean water and sanitation).Collaboration among the local irrigation commission, the International Commission on Irrigation and Drainage (ICID), and all relevant parties is necessary for these initiatives.

CONCLUSIONS
This study aims to propose an effective strategy for managing sand traps as the primary sediment control device in irrigation networks throughout the POS Volcanic Basin, Indonesia.It will be accomplished by utilization of a measurable approach: a mathematical framework executed with the HEC-RAS.The model was divided into two distinct periods, namely, operational and flushing, and is implemented in three research focal areas, namely, Badran, Blawong, and Pengasih were selected using four criteria (significance of the irrigated area, significance of sediment yield, availability of sand traps in irrigation schemes, and representativeness of watersheds).The results show that the calibrated and validated Manning's coefficients of Badran, Blawong, and Pengasih Sand Traps are 0.014, 0.020, and 0.025, respectively.The combination of Thomas (Exner 5) as a sorting method, Rubey as a fall velocity method, and Laursen (Copeland) as a transport function can represent the transport parameters of sand traps in the POS Volcanic Basin.The recommended flushing discharge and duration for Badran, Blawong, and Pengasih Sand Traps are 4 m 3 /s, 4.4 m 3 /s, and 1.9 m 3 /s and 150, 50, and 45 min, respectively.The existing sand trap performance in Badran is less effective, while that of Blawong and Pengasih is less efficient.The recommended

Figure 1 .
Figure 1.Map of the POS Volcanic Basin as a study area.The Basin comprises three watersheds: Progo, Opak, and Serang.Within this basin, there are five volcanoes that are currently active.Among them is Mount Merapi, which holds the distinction of being one of the most active volcanoes globally.

Figure 2 .
Figure 2. Typical layout of sand trap as sediment barrier in the irrigation network.In managing sand traps, there are two periods: operational and flushing.During the operational period, the sand trap's flushing gate remains closed, enabling the flow of water and sediment into the primary irrigation channel.Scheme 1. Methodological Framework a

Figure 3 .
Figure 3.Typical layout of sand trap geometric modeling.There are two distinct categories of geometry modeling: operational and flushing periods.During the operational period, water and sediment flow from the irrigation intake to the irrigation primary channel.However, during the flushing period, they are directed toward the flushing gate of the sand trap to be returned to the river.
Period.The investigation at Badran showed that the downstream section of the sand trap accumulated sediment after 110 min of flushing at 3.24 m 3 /s.The remaining sediment constitutes 10% of the initial sediment that was accumulated prior to the flushing process.The operator then manually removed sediment.Transport parameters calibration is needed to simulate the flushing mechanism accurately.The simulations evaluate current flushing discharge and duration and recommend the best ones.The channel bed measurements before flushing and 21 Badran simulated channel bed profiles are shown in Chart 2a.The graph shows that Thomas (Exner 5) sorting, Rubey fall velocity, and Laursen (Copeland) transport functions yield the best results.RMSE, MAE, and NSE are 0.0752, 0.0466, and 0.9916.These values are compared to those of the flushed channel bed.Using calibrated transport parameters, we simulated the model with 23 discharge values for 110 min.The goal was to identify the discharge that best matched the empty channel bed profile.The discharge varied from 2.5 to 4.5 m 3 /s, with a 0.1 m 3 /s increment.Analyzing the field flushing discharge of 3.24 m 3 /s revealed the variation.Simulation results are shown in Chart 2b.The most satisfactory result is 4.0 m 3 /s, as shown by the RMSE, MAE, and NSE values of 0.092, 0.035, and 0.988, respectively.The flow rate was used to observe the bed elevation time series at the noteworthy cross-section of the Badran sand trap.As shown in Chart 2a, the channel bed profile before flushing shows that the sediment accumulated most at station 90.Thus, the Badran Sand Trap's prominent crosssection was RS. 90.Chart 2c graphs bed elevation time series at RS. 90.As the sediment drains, the graph shows elevation changes until the horizontal line of stability is reached.After 150 min or 2.5 h, the sediment is completely removed.Badran sand trap flushing should be 4.0 m 3 /s and 150 min.According to the Chart 1. Hydraulic Calibration and Validation in the Operational Period: (a) Calibration of Badran's; (b) Validation of Badran's a The graphs show water surface profiles from modeling at various n values and observations.Left is upstream; right is downstream.Bed channel profiles were also plotted.recommendations and measured outcomes, the existing technique is more efficient but less effective.Hydraulic flushing should remove all sediment volumes without operator cleaning.After 60 min of flushing at 3.37 m 3 /s, the Blawong Sand Trap was depleted of sediment.The channel bed measured after flushing was identical to the empty one.It indicates that the flushing procedure was sufficiently successful in eliminating the sediment.Channel bed measurements before and after flushing and 21 Blawong simulated channel bed profiles are shown in Chart 3a.The active layer sorting method, Rubey fall velocity method, and Laursen (Copeland) transport function produce the most desirable profile.This combination produces 0.0378, Chart 2. Mathematical Modeling Results of Badran Sand Trap in the Flushing Period: (a) Sediment Transport Calibration (21 Groups from 168 Scenarios); (b) Sediment Transport Simulation (23 Discharges); (c) Time Series of Bed Elevation at the Prominent Cross-Section (RS.90) Resulting from the Most Satisfactory Discharge (4.0 m 3 /s) 0.0209, and 0.9963 for RMSE, MAE, and NSE, respectively.Based on calibrated transport parameters, Chart 3b shows that 4.40 m 3 /s yielded the best results from 23 discharges over 60 min (RMSE: 0.027, MAE: 0.015, NSE: 0.995).The results reveal no significant differences in channel bed representation after flushing.All results resemble the Blawong Sand Trap's empty channel bed.Thus, 2.5−4.5 m 3 /s is acceptable for flushing the sand trap.Practically, it can be adjusted to river water availability.Chart 3c shows the bed elevation temporal progression at the crucial cross-section in the Blawong Sand Chart 3. Mathematical Modeling Results of Blawong Sand Trap in the Flushing Period: (a) Sediment Transport Calibration (21 Groups from 168 Scenarios); (b) Sediment Transport Simulation (23 Discharges); (c) Time Series of Bed Elevation at the Prominent Cross-Section (RS.92.05) Resulting from the Most Satisfactory Discharge (4.4 m 3 /s) Trap (RS.92.05) using the specified discharge rate of 4.40 m 3 /s.After 50 min, the sediment is completely removed.Thus, we recommend flushing the Blawong Sand Trap at 2.5−4.5 m 3 /s, depending on the river's water availability.Additionally, flushing should last 50 min.It appears that the existing method is effective but inefficient.The study's recommended period is applicable in the field.

Chart 4 .
Mathematical Modeling Results of Pengasih Sand Trap in the Flushing Period: (a) Sediment Transport Calibration (21 Groups from 168 Scenarios); (b) Sediment Transport Simulation (23 Discharges); (c) Time Series of Bed Elevation at the Prominent Cross-Section (RS.133.6)Resulting from the Most Satisfactory Discharge (1.9 m 3 /s)

Chart 5 .
Mathematical Modeling Results of Sand Traps in the Operational Periods: (a) Bi-Weekly Bed Configuration of the Badran Sand Trap; (b) Bi-Weekly Cumulative Volume Change of the Badran Sand Trap; (c) Bi-Weekly Bed Configuration of the Blawong Sand Trap; (d) Bi-Weekly Cumulative Volume Change of the Blawong Sand Trap; (e) Bi-Weekly Bed Configuration of the Pengasih Sand Trap; (f) Bi-Weekly Cumulative Volume Change of the Pengasih Sand Trap which insufficient water availability exists.Thus, it is necessary to advance the periods by 1 month, as depicted by the red-dotted lines.It implies that the recommended flushing frequency of the Badran Sand Trap is four times a year and is based on consideration of the five factors mentioned.The periods are similar to those in practice in the field.It implies that the sand trap management in Badran is efficient.The river water in Blawong is consistently accessible to meet the needs of irrigation and flushing.As previously stated, the optimal discharge rate for flushing the Blawong Sand Trap is 4.4 m 3 /s.However, discharge rates between 2.5 and 4.5 m 3 /s are also considered to be appropriate.The cropping pattern of the Blawong Irrigation Scheme consists of PS 1 (paddy) throughout the months of September to December, PS 2 (paddy) from Chart 6. Determination of Flushing Frequency Based on Five Considered Factors: (a) Badran; (b) Blawong; (c) Pengasih a They plot irrigation water demand, river water availability, modeling-recommended flushing discharges, modeling-recommended flushing time, and five-factor-based flushing time.The planting seasons are also set.

Table 1 .
Data to Model the Sand Trap in the Flushing and Operational Periods

Table 2 .
Collected Data from the Field Measurements Helley Smith equipment to measure bedload and Nansen bottle to grab water samples.The samples were tested using the total suspended solids method to compute the suspended load st : flow in the sand trap, Qs st : total sediment load in the sand trap) https://doi.org/10.1021/acsestwater.4c00116ACS EST Water XXXX, XXX, XXX−XXX F roughness coefficient, n, defines channel bottom conditions.Manning's coefficient represents the roughness or friction the channel applies to the flow.It is one of the most essential parameters in hydrological computations, indicating energy loss in open channels.

Table 3 .
Justification of Manning's Coefficients Compared to the Validated Values

Table 4 .
Comparison of Transport Parameters in the POS Volcanic Basin