Fuzzy-stochastic-based violation analysis method for planning water resources management systems with uncertain information

Abstract:Optimal water allocation within a river basin still remains a great modeling challenge for engineers due to various hydrosystem complexities, parameter uncertainties and their interactions. Conventional deterministic optimization approaches have given their place to stochastic, fuzzy and interval-parameter programming approaches and their hybrid combinations for overcoming these difficulties. In many countries, including Mediterranean countries, water resources management is characterized by uncertain, imprecise and limited data because of the absence of permanent measuring systems, inefficient river monitoring and fragmentation of authority responsibilities. A fuzzy-boundary-interval linear programming methodology developed by Li et al. (2010) is selected and applied in the Alfeios river basin (Greece) for optimal water allocation under uncertain system conditions. This methodology combines an ordinary multi-stage stochastic programming with uncertainties expressed as fuzzy-boundary intervals. Upper-and lower-bound solution intervals for optimized water allocation targets and probabilistic water allocations and shortages are estimated under a baseline scenario and four water and agricultural policy future scenarios for an optimistic and a pessimistic attitude of the decision makers. In this OPEN ACCESSWater 2015, 7 6428 work, the uncertainty of the random water inflows is incorporated through the simultaneous generation of stochastic equal-probability hydrologic scenarios at various inflow positions instead of using a scenario-tree approach in the original methodology.

Section: Limitations Of the Applied Methodology And Corresponding Chamentioning

confidence: 98%

mentioning

confidence: 99%

Optimizing Water Allocation under Uncertain System Conditions for Water and Agriculture Future Scenarios in Alfeios River Basin (Greece)—Part B: Fuzzy-Boundary Intervals Combined with Multi-Stage Stochastic Programming Model

Bekri

Disse

Yannopoulos

2015

“…Effective planning of water pollution control for watersheds plays an important role for national and/or regional sustainable development [2][3][4]. In fact, decisions in water pollution control are often made on the basis of uncertain information (i.e., various uncertainties) existing in system components and their interactions [5,6]. The major sources of uncertainty in water pollution control are the random characteristics of natural processes (e.g., precipitation and climate change) and stream conditions (e.g., stream flow, water supply, and point/nonpoint source pollution), the errors in estimated modeling parameters, and the imprecision of system objectives and constraints [7].…”

Section: Introductionmentioning

confidence: 99%

A Semi-Infinite Interval-Stochastic Risk Management Model for River Water Pollution Control under Uncertainty

Liu

Huang

et al. 2017

Abstract:In this study, a semi-infinite interval-stochastic risk management (SIRM) model is developed for river water pollution control, where various policy scenarios are explored in response to economic penalties due to randomness and functional intervals. SIRM can also control the variability of the recourse cost as well as capture the notion of risk in stochastic programming. Then, the SIRM model is applied to water pollution control of the Xiangxihe watershed. Tradeoffs between risks and benefits are evaluated, indicating any change in the targeted benefit and risk level would yield varied expected benefits. Results disclose that the uncertainty of system components and risk preference of decision makers have significant effects on the watershed's production generation pattern and pollutant control schemes as well as system benefit. Decision makers with risk-aversive attitude would accept a lower system benefit (with lower production level and pollutant discharge); a policy based on risk-neutral attitude would lead to a higher system benefit (with higher production level and pollutant discharge). The findings can facilitate the decision makers in identifying desired product generation plans in association with financial risk minimization and pollution mitigation.

“…For example, water flow may be related to errors in acquired data, variations in spatial and temporal units, and incompleteness or impreciseness of observed information in water resources management [18]. Fuzzy programming (FP) is effective to deal with decision problems under fuzzy goal or constraints caused by imprecision and vagueness, when the quality and quantity of uncertain information is often not satisfactory enough to be presented as probabilistic distribution [19,20]. However, since many other uncertain components (e.g., economic data, allocation target, and trading ratio) are often not straightforward enough to be expressed as probability/possibility distributions, interval-parameter programming (IPP) can be introduced to deal with uncertainties due to limited data availabilities existing in the model's left-and/or right-hand sides, where interval numbers are acceptable as its uncertain inputs [6,7,21].…”

Section: Introductionmentioning

confidence: 99%

A Mix Inexact-Quadratic Fuzzy Water Resources Management Model of Floodplain (IQT-WMMF) for Regional Sustainable Development of Dahuangbaowa, China

Zeng

Yang

et al. 2015

Abstract:In this study, a mix inexact-quadratic fuzzy water resources management model of floodplain (IQT-WMMF) has developed, through incorporating techniques of credibility-constrained programming (CP), two-stage programming (TP), interval-parameter programming (IPP) and quadratic programming (QP) within a general framework for limited data availability. The IQT-WMMF can provide an effective linkage between system benefit and the associated economic penalty attributed to the violation of the pre-regulated water target under limited data availabilities expressed probabilistic distributions and interval values; meanwhile, imprecise and no-linear economic data would be resolved. The developed method is applied to a real case of planning water resources in the Dahuangbaowa floodplain, China, with the aim to develop a sustainable water resources management in the study region. A number of scenarios with wet land expansion strategies under various credibility levels are analyzed, implying that different policies can lead to varied water-allocation patterns, system benefits, and system-failure risks. The results discover that water deficits and flood damages have brought negative effects on economic development synchronously, which need to effective plans to reduce losses of shortages and floods for achieving higher system benefits. Tradeoffs between economic benefit and system-failure risk can support generating an increased robustness in risk control for water resources allocation under uncertainties, which is beneficial to adjust the current water-allocation sustainably. OPEN ACCESSWater 2015, 7 2772