Multi-method Modeling Framework for Support of Integrated Water Resources Management

Nikolic, Vladimir V.; Simonović́, Slobodan P.

doi:10.1007/s40710-015-0082-6

Cited by 43 publications

(17 citation statements)

References 36 publications

(38 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The components of the conceptual framework for this study transmit the requisite information to other participants directly as shown in Figure 2. According to the IWRM concept and to promote the theory of system view, this model will provide an authentic representation of the interactions between the physical environment and implementation of IWRM strategies (Nikolic & Milicevic 2012;Nikolic & Simonovic, 2015). The modeling paradigm encourages model scenarios to analyze different issues of "what-if" management (Nikolic & Simonovic, 2015).…”

Section: The Study Conceptual Frameworkmentioning

confidence: 99%

Synthesis of Attaining Sustainable Development Goal 6.5: A Case Study of Mano River

Yateh¹,

Lartey-Young²,

Boying³

et al. 2021

GEP

View full text Add to dashboard Cite

The Mano River is a transboundary river that runs through Côte d'Ivoire, Liberia, Guinea, and Sierra Leone. According to a 2018 United Nation report on Sustainable Development Goal (SDG) 6.5, which aims to improve the adoption of cohesive water resource management by 2030; the impact of this goal on the Mano River management is minimal. The research summarizes previous studies using an integrative literature review method, drawing general conclusions and identifying unsolved problems with respect to water resources management. The research finding demonstrated that existing water stress and poor management as exacerbated by socioeconomic practices in the region are the major threats to achieve SDG 6.5. As a result of these activities, long-term management of the river basins has become extremely difficult. The research informs a discussion to achieve cooperative water resource management, which is best achieved by shared collaboration and shared interests as described by SDG 6.5.

show abstract

Section: The Study Conceptual Frameworkmentioning

confidence: 99%

Synthesis of Attaining Sustainable Development Goal 6.5: A Case Study of Mano River

Yateh¹,

Lartey-Young²,

Boying³

et al. 2021

GEP

View full text Add to dashboard Cite

show abstract

“…Ticehurst et al, 2007), as well as different couplings of multiple methods (e.g. Nikolic and Simonovic 2015).…”

Section: Overcoming Data Limitationsmentioning

confidence: 99%

Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities

Badham

Elsawah

Guillaume

et al. 2019

Environmental Modelling & Software

View full text Add to dashboard Cite

The effectiveness of Integrated Water Resource Management (IWRM) modeling hinges on the quality of practices employed through the process, starting from early problem definition all the way through to using the model in a way that serves its intended purpose. The adoption and implementation of effective modeling practices need to be guided by a practical understanding of the variety of decisions that modelers make, and the information considered in making these choices. There is still limited documented knowledge on the modeling workflow, and the role of contextual factors in determining this workflow and which practices to employ. This paper attempts to contribute to this knowledge gap by providing systematic guidance of the modeling practices through the phases (Planning, Development, Application, and Perpetuation) and steps that comprise the modeling process, positing questions that should be addressed. Practice-focused guidance helps explain the detailed process of conducting IWRM modeling, including the role of contextual factors in shaping practices. We draw on findings from literature and the authors' collective experience to articulate what and how contextual factors play out in employing those practices. In order to accelerate our learning about how to improve IWRM modeling, the paper concludes with five key areas for future practice-related research: knowledge sharing, overcoming data limitations, informed stakeholder involvement, social equity and management of uncertainty.

show abstract

“…Typhoons with heavy rainfall and strong wind often cause severe floods and disasters. Providing protection from flood‐related disasters is essential for the typhoon‐prone areas, which is also one of the objectives in integrated water resources management (Fedra, ; Nikolic and Simonovic, ). Owing to the huge negative social impacts of typhoons, accurate typhoon forecasting is a priority of the operational weather forecast centres in the western North Pacific, especially in Taiwan (Hsiao et al , ).…”

Section: Introductionmentioning

confidence: 99%

Predictor selection method for the construction of support vector machine (SVM)‐based typhoon rainfall forecasting models using a non‐dominated sorting genetic algorithm

Yang

Lin

et al. 2018

Meteorological Applications

View full text Add to dashboard Cite

This study proposes a predictor selection method for constructing a support vector machine (SVM)‐based typhoon rainfall forecasting models using a fast elitist Non‐dominated Sorting Genetic Algorithm II (NSGA‐II). Based on SVMs, four rainfall forecasting models with different combinations of the three types of input variables (i.e. antecedent rainfalls, typhoon characteristics and local weather factors) were constructed for 1–6 hr‐ahead forecasting. An application to three rain gauge stations in the Yilan River basin, northeastern Taiwan, was conducted to demonstrate the superiority of the proposed predictor selection method. The results showed that the optimal combination of predictors for each SVM‐based rainfall forecasting model can be automatically and effectively determined by the proposed predictor selection method. The rainfall forecasting model using all three types of input variables performed better than the other three models, especially for long lead‐time forecasting. The construction of rainfall forecasting models is helpful to extend the lead time of flood forecasting. The optimal rainfall forecasting model can be further integrated with river hydraulic models or flood inundation models for flood forecasting to assist floodplain managers to take suitable precautionary measures during typhoon landfall.

show abstract

Multi-method Modeling Framework for Support of Integrated Water Resources Management

Cited by 43 publications

References 36 publications

Synthesis of Attaining Sustainable Development Goal 6.5: A Case Study of Mano River

Synthesis of Attaining Sustainable Development Goal 6.5: A Case Study of Mano River

Effective modeling for Integrated Water Resource Management: A guide to contextual practices by phases and steps and future opportunities

Predictor selection method for the construction of support vector machine (SVM)‐based typhoon rainfall forecasting models using a non‐dominated sorting genetic algorithm

Contact Info

Product

Resources

About