From Water Allocation to Food Security: Irrigation System Optimization through Deterministic Dynamic Programming in the Gembolo Irrigation Area
DOI:
10.29303/jppipa.v11i12.12630Published:
2025-12-25Downloads
Abstract
Inefficient irrigation water distribution remains a critical barrier to achieving optimal crop productivity and ensuring food security in rural Indonesia. This study focuses on the Gembolo Irrigation Area, Mojokerto Regency, by applying Deterministic Dynamic Programming (DDP) to optimize water allocation under a Rice–Rice–Secondary Crop (RTTG) rotation. The comprehensive integration of hydrological, climatological, and cropping data was employed to construct a DDP model that synchronizes irrigation supply with crop water demand across nine irrigation structures (G1–G9). The optimization results reveal significant improvements: irrigated area expanded by 254 ha, cropping intensity increased from 277 to 300%, and farmers’ net income rose by IDR 5.3 billion compared to the existing allocation scheme. These findings demonstrate the capacity of DDP to enhance water-use efficiency while strengthening the resilience and sustainability of rural agricultural systems. The study highlights the importance of data-driven optimization as a decision-support framework for advancing integrated irrigation management and rural development.
Keywords:
Dynamic programming Irrigation optimization Rural development Sustainable agricultureReferences
Abdullah, S., Sarwoprasodjo, S., & Hapsari, D. R. (2023). Participatory Communication to Strengthen Farmers’ Empowerment and Adaptation in Facing the Impacts of Climate Change. HABITAT, 34(3), 245–255. https://doi.org/10.21776/ub.habitat.2023.034.3.22 DOI: https://doi.org/10.21776/ub.habitat.2023.034.3.22
Ali, M. H., & Talukder, M. S. U. (2008). Increasing Water Productivity in Crop Production—A Synthesis. Agricultural Water Management, 95(11), 1201–1213. https://doi.org/10.1016/j.agwat.2008.06.008 DOI: https://doi.org/10.1016/j.agwat.2008.06.008
Allen, R. G., Pereira, L. S., Raes, D., & Smith, M. (1998). Crop Evapotranspiration: Guidelines for Computing Crop Water Requirements (FAO Irrigation and Drainage Paper No. 56). Rome: FAO.
Archibald, T. (2018). Review of Mathematical Programming Applications in Water Resource Management under Uncertainty: Trends, Methods and Research Gaps. Water Resources Management, 32(7), 2197–2229. https://doi.org/10.1007/s11269-018-1926-2
Atasa, D., Widayanti, S., Laily, D. W., & Toiba, H. (2024). Horticultural Farmer’s Perceptions and Adaptations to Climate Change in East Java, Indonesia. HABITAT, 35(1), 115–122. https://doi.org/10.21776/ub.habitat.2024.035.1.11 DOI: https://doi.org/10.21776/ub.habitat.2024.035.1.11
Barker, R., & Molle, F. (2004). Evolution of Irrigation in South and Southeast Asia (Comprehensive Assessment Research Report 5). Colombo, Sri Lanka: International Water Management Institute (IWMI).
Bidang Sumber Daya Air, Dinas PUPR Kabupaten Mojokerto. (2025). Laporan Tahunan Pengelolaan Irigasi dan Sumber Daya Air Kabupaten Mojokerto Tahun 2025. Mojokerto: Dinas PUPR Kabupaten Mojokerto.
BMKG Juanda. (2025). Laporan Data Klimatologi Tahunan Stasiun Meteorologi Kelas I Juanda. Surabaya: Badan Meteorologi, Klimatologi, dan Geofisika.
Delgoda, D., Malano, H., Saleem, S. K., & Halgamuge, M. N. (2017). A Novel Generic Optimization Method for Irrigation Scheduling under Multiple Objectives and Multiple Hierarchical Layers in a Canal Network. Advances in Water Resources, 105, 28–44. https://doi.org/10.1016/j.advwatres.2017.04.025 DOI: https://doi.org/10.1016/j.advwatres.2017.04.025
Djaman, K. (2018). Crop Evapotranspiration, Irrigation Water Requirement and Water Productivity for Maize in New Mexico. Water, 10(4), 405. https://doi.org/10.3390/w10040405 DOI: https://doi.org/10.3390/w10040405
Fan, Y. (2023). A Model Coupling Water Resource Allocation and Canal Operation for Improved Distribution. Water Resources Management. https://doi.org/10.1007/s11269-023-03437-9 DOI: https://doi.org/10.1007/s11269-023-03437-9
Fan, Y., Chen, H., Gao, Z., & Chang, X. (2023). Canal Water Distribution Optimization Model Based on Water Supply Conditions. Computers and Electronics in Agriculture, 205, 107565. https://doi.org/10.1016/j.compag.2022.107565 DOI: https://doi.org/10.1016/j.compag.2022.107565
FAO. (2021). The State of Food Security and Nutrition in the World 2021. Rome: Food and Agriculture Organization of the United Nations. https://doi.org/10.4060/cb4474en DOI: https://doi.org/10.4060/cb4474en
Guo, S. (2018). A Multi-Objective Hierarchical Model for Irrigation Scheduling at Network Level. Sustainability, 11(1), 24. https://doi.org/10.3390/su11010024 DOI: https://doi.org/10.3390/su11010024
Handini, W. (2024). Prototype Design of Micro Hydro Power with Irrigation Water in Rice Fields Based on IoT. Jurnal Penelitian Pendidikan IPA, 10(9). https://doi.org/10.29303/jppipa.v10i9.3126 DOI: https://doi.org/10.29303/jppipa.v10i9.8553
Jamal, A., Cai, X., Qiao, X., Garcia, L., Wang, J., Amori, A., & Yang, H. (2023). Real-Time Irrigation Scheduling Based on Weather Forecasts and Data Assimilation. Water Resources Research, 59, e2023WR035810. https://doi.org/10.1029/2023WR035810 DOI: https://doi.org/10.1029/2023WR035810
Jin, L., Huang, G., & Fan, Y. (2012). A Hybrid Dynamic Dual Interval Programming for Irrigation Water Allocation under Uncertainty. Water Resources Management, 26(5), 1183–1200. https://doi.org/10.1007/s11269-011-9953-4 DOI: https://doi.org/10.1007/s11269-011-9953-4
Karamouz, M., & Houck, M. H. (1992). Optimization and Simulation of Multiple Reservoir Systems. Journal of Water Resources Planning and Management. https://doi.org/10.1061/(ASCE)0733-9496(1992)118:1(71) DOI: https://doi.org/10.1061/(ASCE)0733-9496(1992)118:1(71)
Kassing, R. (2020). Optimal Control for Precision Irrigation of a Large-Scale Center Pivot System. Water Resources Research. https://doi.org/10.1029/2019WR026989 DOI: https://doi.org/10.1029/2019WR026989
Kodoatie, R. J., & Sjarief, R. (2010). Pengelolaan Sumber Daya Air Terpadu. Yogyakarta: Andi Offset.
Laskookalayeh, M., Javanrud, N., & Jalili, M. (2022). Optimization of Irrigation Programming for Different Water Allocation Strategies at Network Level: Method and Application. Water Resources Management. https://doi.org/10.1007/s11269-024-03938-1 DOI: https://doi.org/10.1007/s11269-024-03938-1
Li, Q. (2020). Multistage Stochastic Programming Modeling for Farmland Management under Uncertainty. PLoS ONE, 15(8), e0233723. https://doi.org/10.1371/journal.pone.0233723 DOI: https://doi.org/10.1371/journal.pone.0233723
Li, Y. P., Huang, G. H., Nie, S. L., & Liu, L. (2012). Inexact Multistage Stochastic Integer Programming for Water Resources Management under Uncertainty. Journal of Hydrology, 420–442, 225–239. https://doi.org/10.1016/j.jhydrol.2011.12.025 DOI: https://doi.org/10.1016/j.jhydrol.2011.12.025
Liao, X., Meng, C., Cai, B., & Zhao, W. (2020). Interval-Parameter Two-Stage Stochastic Programming Model of Ecological Water Replenishment Scheme. Water, 12(6), 1520. https://doi.org/10.3390/w12061520 DOI: https://doi.org/10.3390/w12061520
Linker, R. (2021). Stochastic Model-Based Optimization of Irrigation Scheduling. Agricultural Water Management, 243, 106480. https://doi.org/10.1016/j.agwat.2020.106480 DOI: https://doi.org/10.1016/j.agwat.2020.106480
Liu, X., & Yang, D. (2021). Irrigation Schedule Analysis and Optimization under the Different Combination of P and ET0 Using a Spatially Distributed Crop Model. Agricultural Water Management, 256, 107084. https://doi.org/10.1016/j.agwat.2021.107084 DOI: https://doi.org/10.1016/j.agwat.2021.107084
Mushthofa, M., Suripin, S., & Wulandari, D. A. (2025). Literature Review: Water Spinach Variety KK-09 for Irrigation Optimization in Dry Land. Jurnal Penelitian Pendidikan IPA, 11(9), 48–57. https://doi.org/10.29303/jppipa.v11i9.11380 DOI: https://doi.org/10.29303/jppipa.v11i9.11380
Paudyal, G. N. (1990). Two-Step Dynamic Programming Approach for Optimal Water Allocation in a Run-of-the-River Type Irrigation Project. Water Resources Management, 4(1), 1–14. https://doi.org/10.1007/BF00431143 DOI: https://doi.org/10.1007/BF00431143
Pereira, L. S., Allen, R. G., Smith, M., & Raes, D. (2015a). Crop Evapotranspiration Estimation with FAO56: Past and Future. Agricultural Water Management, 147, 4–20. https://doi.org/10.1016/j.agwat.2014.07.031 DOI: https://doi.org/10.1016/j.agwat.2014.07.031
Pereira, L. S., Paredes, P., Rodrigues, G. C., & Neves, M. (2015b). Modeling Evapotranspiration and Crop Water Productivity in Irrigation Scheduling, Supporting Water Productivity Analysis. Agricultural Water Management, 147, 13–26. https://doi.org/10.1016/j.agwat.2014.05.002 DOI: https://doi.org/10.1016/j.agwat.2014.05.002
Prastyo, D., Suhartono, S., & Susanto, H. (2021). Optimization of Irrigation Benefits Using Dynamic Programming Method in Banyuwangi, Indonesia. Simetris: Jurnal Teknik Mesin, Elektro dan Ilmu Komputer, 12(1), 45–56. https://doi.org/10.24176/simet.v12i1.4920
Santosa, R. R. A., Pratiwi, E. P. A., & Istiarto, I. (2025). Establishing Semantok Reservoir Operation Rules to Obtain the Highest Crop Intensity in Semantok Irrigation Area. Jurnal Penelitian Pendidikan IPA, 11(8), 1180–1192. https://doi.org/10.29303/jppipa.v11i8.11669
Sunantara, I. M., & Ramirez, J. A. (2017). A Two-Stage Stochastic Programming Model for Seasonal and Intraseasonal Irrigation Water Management. Computers and Electronics in Agriculture, 134, 160–172. https://doi.org/10.1016/j.compag.2016.12.009 DOI: https://doi.org/10.1016/j.compag.2016.12.009
Suryadi, F. X. (2014). Water Management for Rice Cultivation: Issues and Challenges in Indonesia. Irrigation and Drainage, 63(2), 155–165. https://doi.org/10.1002/ird.1812 DOI: https://doi.org/10.1002/ird.1812
Suryana, A. (2018). Strategi Ketahanan Pangan di Indonesia: Tantangan dan Prospek. Forum Penelitian Agro Ekonomi, 36(1), 1–12. https://doi.org/10.21082/fae.v36n1.2018.1-12 DOI: https://doi.org/10.21082/fae.v36n1.2018.1-12
Valiantzas, J. D. (2013). Simplified Forms for the Standardized FAO-56 Penman–Monteith Reference Evapotranspiration Using Limited Weather Data. Journal of Hydrology, 505, 13–23. https://doi.org/10.1016/j.jhydrol.2013.09.005 DOI: https://doi.org/10.1016/j.jhydrol.2013.09.005
Yakowitz, S. (1992). Dynamic Programming Applications in Water Resources. Journal of Hydrology, 138(1–2), 267–281. https://doi.org/10.1016/0022-1694(92)90198-D
Yang, Y., Hu, J., Porter, D., Marek, T., & Heflin, K. (2020). Deep Reinforcement Learning-Based Irrigation Scheduling. Transactions of the ASABE, 63(3), 549–556. https://doi.org/10.13031/trans.13633 DOI: https://doi.org/10.13031/trans.13633
License
Copyright (c) 2025 Mokhamad Rusdha Maulana, Lily Montarcih Limantara, itojo Tri Juwono
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).
