Abstract
This paper presents the development of fuzzy set–based performance measures for an irrigation reservoir system to answer questions on how likely a system is to fail (fuzzy reliability), how quickly it is likely to recover from failure (fuzzy resiliency), and how severe the consequences of failure are likely to be (fuzzy vulnerability). The failure/success state of the system is defined as a fuzzy event. A fuzzy set with an appropriate membership function is defined to describe both the working and failed states, to account for the system being in partly working and partly failed state. Failure of the irrigation reservoir system is related to the evapotranspiration deficit of the crops in a period. Application of the performance measures is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India. The reservoir operation is simulated using three different reservoir operating policy models: steady-state policy obtained using a fuzzy stochastic dynamic programming (FSDP) model, steady-state policy obtained using a classical stochastic dynamic programming (SDP) model, and yearly operating policy using a conceptual operating policy (COP) model. All reservoir operating policy models consider the integration of the reservoir operation policy at 10-day time periods with water allocation decisions on a daily basis by maintaining the storage continuity and soil moisture balance. Inclusion of fuzziness in the performance measure gives realistic solutions by capturing uncertainties in the reservoir operating policy models.
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Information & Authors
Information
Published In
Journal of Irrigation and Drainage Engineering
Volume 143 • Issue 5 • May 2017
Copyright
©2017 American Society of Civil Engineers.
History
Received: Jun 14, 2016
Accepted: Sep 30, 2016
Published online: Jan 23, 2017
Discussion open until: Jun 23, 2017
ASCE Technical Topics:
- Analysis (by type)
- Artificial intelligence and machine learning
- Business management
- Case studies
- Computer programming
- Computing in civil engineering
- Dynamic models
- Engineering fundamentals
- Failure analysis
- Fuzzy logic
- Hydraulic engineering
- Hydraulic structures
- Irrigation
- Irrigation engineering
- Irrigation systems
- Management methods
- Methodology (by type)
- Models (by type)
- Practice and Profession
- Quality control
- Research methods (by type)
- Reservoirs
- Simulation models
- Water and water resources
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