PMID- 25688523
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20150515
LR  - 20150316
IS  - 1879-1026 (Electronic)
IS  - 0048-9697 (Linking)
VI  - 515-516
DP  - 2015 May 15
TI  - Reliability-oriented multi-objective optimal decision-making approach for 
      uncertainty-based watershed load reduction.
PG  - 39-48
LID - S0048-9697(15)00160-6 [pii]
LID - 10.1016/j.scitotenv.2015.02.024 [doi]
AB  - Water quality management and load reduction are subject to inherent uncertainties 
      in watershed systems and competing decision objectives. Therefore, optimal 
      decision-making modeling in watershed load reduction is suffering due to the 
      following challenges: (a) it is difficult to obtain absolutely "optimal" 
      solutions, and (b) decision schemes may be vulnerable to failure. The probability 
      that solutions are feasible under uncertainties is defined as reliability. A 
      reliability-oriented multi-objective (ROMO) decision-making approach was proposed 
      in this study for optimal decision making with stochastic parameters and multiple 
      decision reliability objectives. Lake Dianchi, one of the three most eutrophic 
      lakes in China, was examined as a case study for optimal watershed nutrient load 
      reduction to restore lake water quality. This study aimed to maximize reliability 
      levels from considerations of cost and load reductions. The Pareto solutions of 
      the ROMO optimization model were generated with the multi-objective evolutionary 
      algorithm, demonstrating schemes representing different biases towards 
      reliability. The Pareto fronts of six maximum allowable emission (MAE) scenarios 
      were obtained, which indicated that decisions may be unreliable under unpractical 
      load reduction requirements. A decision scheme identification process was 
      conducted using the back propagation neural network (BPNN) method to provide a 
      shortcut for identifying schemes at specific reliability levels for decision 
      makers. The model results indicated that the ROMO approach can offer decision 
      makers great insights into reliability tradeoffs and can thus help them to avoid 
      ineffective decisions.
CI  - Copyright (c) 2015 Elsevier B.V. All rights reserved.
FAU - Dong, Feifei
AU  - Dong F
AD  - College of Environmental Science and Engineering, Key Laboratory of Water and 
      Sediment Sciences (MOE), Peking University, Beijing 100871, China.
FAU - Liu, Yong
AU  - Liu Y
AD  - College of Environmental Science and Engineering, Key Laboratory of Water and 
      Sediment Sciences (MOE), Peking University, Beijing 100871, China; Institute of 
      Water Sciences, Peking University, Beijing 100871, China. Electronic address: 
      yongliu@pku.edu.cn.
FAU - Su, Han
AU  - Su H
AD  - College of Environmental Science and Engineering, Key Laboratory of Water and 
      Sediment Sciences (MOE), Peking University, Beijing 100871, China.
FAU - Zou, Rui
AU  - Zou R
AD  - Tetra Tech, Inc., 10306 Eaton Place, Ste 340, Fairfax, VA 22030, USA; Yunnan Key 
      Laboratory of Pollution Process and Management of Plateau Lake-Watershed, Kunming 
      650034, China.
FAU - Guo, Huaicheng
AU  - Guo H
AD  - College of Environmental Science and Engineering, Key Laboratory of Water and 
      Sediment Sciences (MOE), Peking University, Beijing 100871, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20150214
PL  - Netherlands
TA  - Sci Total Environ
JT  - The Science of the total environment
JID - 0330500
OTO - NOTNLM
OT  - Back propagation neural network
OT  - Multi-objective evolutionary algorithm
OT  - Pareto fronts
OT  - Stochastic
OT  - Tradeoff analysis
EDAT- 2015/02/18 06:00
MHDA- 2015/02/18 06:01
CRDT- 2015/02/18 06:00
PHST- 2014/12/07 00:00 [received]
PHST- 2015/02/05 00:00 [revised]
PHST- 2015/02/07 00:00 [accepted]
PHST- 2015/02/18 06:00 [entrez]
PHST- 2015/02/18 06:00 [pubmed]
PHST- 2015/02/18 06:01 [medline]
AID - S0048-9697(15)00160-6 [pii]
AID - 10.1016/j.scitotenv.2015.02.024 [doi]
PST - ppublish
SO  - Sci Total Environ. 2015 May 15;515-516:39-48. doi: 
      10.1016/j.scitotenv.2015.02.024. Epub 2015 Feb 14.