A Decision Support System for Irrigation Management in Thailand: Case Study of Tak City Agricultural Production

Jewpanya, Parida; German, Josephine D.; Nuangpirom, Pinit; Maghfiroh, Meilinda Fitriani Nur; Redi, Anak Agung Ngurah Perwira

doi:10.3390/app122010508

Cited by 2 publications

(2 citation statements)

References 32 publications

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“…The main limitation of our approach is that it cannot deal with a large-scale number of nodes due to the growing complexity of the problem. It is necessary to consider a more sophisticated approach, such as heuristics or metaheuristics algorithms [27], [28]. Furthermore, the demand of each node might be best characterized as an uncertainty parameter using stochastic or fuzzy approaches.…”

Section: Discussionmentioning

confidence: 99%

Maximum covering location problem to select facility location for operation timbang in the City of Iloilo, Philippines

Redi¹,

Flame²,

Redioka³

et al. 2022

j. sist. manaj. ind.

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Operation Timbang (OPT) Plus is one of the Philippines’ programs that focuses on nutrition by conducting an annual assessment for 0-59 months old children in barangays to identify the malnutrition data in the area. The barangay is the smallest administrative entity in the Philippines. OPT is a plan of action that estimates the number of malnutrition individuals and identifies those who will get prioritized programs in the community. The Iloilo City Health Office conducted the program in seven districts in the Philippines. The office planned to establish a community centre and playground facility based on the priority/demand areas. Maximum Covering Location Problem (MCLP) is used for this study to determine the optimal location that covers the area. A Mathematical Programming Language (AMPL) is used to apply mathematical programming to the MCLP. The results can be used to identify the optimal facility and the maximum coverage of the demand points. The experiment showed that the facility located in Mandurriao District is the optimal facility location. For Underweight/Severely Underweight children, a maximum total of 646 are covered, and for the Overweight/Obese, 1,041 are covered for the chosen facility. In addition, the findings of the sensitivity analysis indicate that the building of the three facilities in the case study can offer 100 percent of the required coverage area.

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Section: Discussionmentioning

confidence: 99%

Maximum covering location problem to select facility location for operation timbang in the City of Iloilo, Philippines

Redi¹,

Flame²,

Redioka³

et al. 2022

j. sist. manaj. ind.

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“…Nel et al (2022) presented a framework for selecting applicable water allocation planning schemes and related DSS systems based on the characteristics and requirements of the water management situation. Jewpanya et al (2022) presented a DSS to identify the optimal cropping pattern and irrigation management in Thailand and concluded that the developed DSS shows good efficiency in irrigation management.…”

Section: Introductionmentioning

confidence: 99%

Investigating the compatibility of an irrigation decision support system with water rights and allocation in a selected irrigation network

Dehghanisanij,

Emami,

Nourjou

et al. 2024

Irrigation and Drainage

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It is necessary to use different planning models, including decision support systems (DSSs), to allocate water resources. For this purpose, in this study, an irrigation decision support system (IDSS) was developed to improve irrigation management in the farming fields of Mahabad Plain located to the south‐east of Lake Urmia. Next, the compatibility of the IDSS with the conditions of the Mahabad irrigation and drainage network, water and soil resources, meteorological data and soil moisture (SM) were investigated. The statistical indices of coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency (EF) and Wilmot agreement (d) were used to evaluate the adaptability of the IDSS. The results showed that the IDSS has reasonable compatibility with soil and water resources, crop yield and meteorological data. Irrigation scheduling provided by the IDSS led to a 13.9% reduction in water consumption and a 6.7% increase in crop yield. The IDSS estimated minimum and maximum temperature and sunshine hours to a satisfactory degree and relative humidity with an acceptable degree (NRMSE = 0.72–0.77) compared to regional synoptic station data. The performance of the IDSS in simulating SM is ranked from good to well (NRMSE = 0.75–0.83). The results indicate that the IDSS has a sufficient performance in estimating meteorological and soil moisture data with R2 = 0.90, RMSE = 4.65, NRMSE = 0.78, EF = 0.76 and d = 0.80. In addition, the IDSS provides the optimal irrigation schedule by considering the ability to deliver water from the irrigation and drainage network to the third‐grade canal and agricultural fields as the upstream condition.

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A Decision Support System for Irrigation Management in Thailand: Case Study of Tak City Agricultural Production

Cited by 2 publications

References 32 publications

Maximum covering location problem to select facility location for operation timbang in the City of Iloilo, Philippines

Maximum covering location problem to select facility location for operation timbang in the City of Iloilo, Philippines

Investigating the compatibility of an irrigation decision support system with water rights and allocation in a selected irrigation network

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