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Developing a Conjunctive Use Optimization Model for Allocating Surface and Subsurface Water in an Off-Stream Artificial Lake System
(2016-08-01)
Pan, Chen-Che
;
Chen, Yu-Wen
;
Chang, Liang-Cheng
;
Huang, Chun-Wei
;
土木工程學系
This work develops a rule curve-based conjunctive use management model for optimizing the operating rules for a lake-groundwater system with off-stream storage lakes. The proposed procedure is a simulation-optimization approach that embeds an Artificial Neural Network ( ANN) instead of a groundwater numerical model into a genetic algorithm ( GA). The direct physical exchange between lake water with groundwater is simulated using the ANN model, which is a reduced version of a full numerical model, MODFLOW with an LAK3 module. By applying the ANN model, the proposed procedure can reduce the computational burden that is induced by the nonlinear exchange. An operating rule-based optimal conjunctive use management model for the Gaopin Artificial lakes system in Taiwan was thus developed using the proposed framework. A set of optimal solutions involves rule curves and a discount ratio. Simulation results demonstrate that the embedded ANN model can accurately simulate the nonlinear exchange of a lake with groundwater. The embedded ANN model is less computationally complex than the numerical model. This work demonstrates a methodology for reducing the computational burden of the optimal conjunctive use management model that is associated with an internal nonlinear system by using the ANN reduced model. Specifically, the concept of, and results obtained using the developed operating rule-based model incorporating five artificial lakes and considering the nonlinear exchange of those lakes with the groundwater system provides a valuable practical reference for solving related conjunctive use problems.
High Recharge Areas in the Choushui River Alluvial Fan (Taiwan) Assessed from Recharge Potential Analysis and Average Storage Variation Indexes
(2015-04-01)
Tsai, Jui-Pin
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Chen, Yu-Wen
;
Chang, Liang-Cheng
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Kuo, Yi-Ming
;
Tu, Yu-Hsuan
High recharge areas significantly influence the groundwater quality and quantity in regional groundwater systems. Many studies have applied recharge potential analysis (RPA) to estimate groundwater recharge potential (GRP) and have delineated high recharge areas based on the estimated GRP. However, most of these studies define the RPA parameters with supposition, and this represents a major source of uncertainty for applying RPA. To objectively define the RPA parameter values without supposition, this study proposes a systematic method based on the theory of parameter identification. A surrogate variable, namely the average storage variation (ASV) index, is developed to calibrate the RPA parameters, because of the lack of direct GRP observations. The study results show that the correlations between the ASV indexes and computed GRP values improved from 0.67 before calibration to 0.85 after calibration, thus indicating that the calibrated RPA parameters represent the recharge characteristics of the study area well; these data also highlight how defining the RPA parameters with ASV indexes can help to improve the accuracy. The calibrated RPA parameters were used to estimate the GRP distribution of the study area, and the GRP values were graded into five levels. High and excellent level areas are defined as high recharge areas, which composed 7.92% of the study area. Overall, this study demonstrates that the developed approach can objectively define the RPA parameters and high recharge areas of the Choushui River alluvial fan, and the results should serve as valuable references for the Taiwanese government in their efforts to conserve the groundwater quality and quantity of the study area.
Groundwater Simulations and Uncertainty Analysis Using MODFLOW and Geostatistical Approach with Conditioning Multi-Aquifer Spatial Covariance
(2017-03-01)
Lin, Yu-Pin
;
Chen, Yu-Wen
;
Chang, Liang-Cheng
;
Yeh, Ming-Sheng
;
Huang, Guo-Hao
This study presents an approach for obtaining limited sets of realizations of hydraulic conductivity (K) of multiple aquifers using simulated annealing (SA) simulation and spatial correlations among aquifers to simulate realizations of hydraulic heads and quantify their uncertainty in the Pingtung Plain, Taiwan. The proposed approach used the SA algorithm to generate large sets of natural logarithm hydraulic conductivity (ln(K)) realizations in each aquifer based on spatial correlations among aquifers. Moreover, small sets of ln(K) realizations were obtained from large sets of realizations by ranking the differences among cross-variograms derived from the measured ln(K) and the simulated ln(K) realizations between the aquifer pair Aquifer 1 and Aquifer 2 (hereafter referred to as Aquifers 1-2) and the aquifer pair Aquifer 2 and Aquifer 3 (hereafter referred to as Aquifers 2-3), respectively. Additionally, the small sets of realizations of the hydraulic conductivities honored the horizontal spatial variability and distributions of the hydraulic conductivities among aquifers to model groundwater precisely. The uncertainty analysis of the 100 combinations of simulated realizations of hydraulic conductivity was successfully conducted with generalized likelihood uncertainty estimation (GLUE). The GLUE results indicated that the proposed approach could minimize simulation iterations and uncertainty, successfully achieve behavioral simulations when reduced between calibration and evaluation runs, and could be effectively applied to evaluate uncertainty in hydrogeological properties and groundwater modeling, particularly in those cases which lack three-dimensional data sets yet have high heterogeneity in vertical hydraulic conductivities.
Estimating Hydraulic Conductivity Fields in Composite Fan Delta Using Vertical Electrical Sounding
(2018-11-01)
Chen, You-Cheng
;
Tsai, Jui-Pin
;
Chang, Liang-Cheng
;
Chang, Ping-Yu
;
Lin, Helen
Hydraulic conductivity (K) is crucial for groundwater studies and is conventionally obtained through pumping tests, which are costly due to well installation, resulting in a limited amount of data. Recent studies have addressed this limitation by estimating K through the integration of a pumping-test K and electrical resistivity measurements. While this approach is suitable for local areas, it cannot readily be applied to determine K fields for the composite fan delta. This study proposes and demonstrates an advanced method to estimate the K's spatial distribution of a composite fan delta. The proposed method included data classification, linear regression, and kriging interpolation. Data classification was conducted using a physical-based zonation method. The K and formation factor (F) data pairs were classified into several groups. Linear regression was used to develop K-F mapping for each group. The regression results showed a good correlation between K and F in each group. These K-F mappings were verified by additional pumping tests. These results indicate that estimation errors were between 7 m/day and 58 m/day, and the correlation coefficient of each data group was greater than 0.8. Based on these regression equations and ordinary kriging method, the detailed K spatial distribution of the study area was derived. According to these results, the proposed method is efficient and economical to delineate K's spatial features for regional groundwater systems and can benefit groundwater-related studies.
Effects of the Grain Size on Dynamic Capillary Pressure and the Modified Green-Ampt Model for Infiltration
(2018-01-01)
Tsai, Yi-Zhih
;
Liu, Yu-Tung
;
Wang, Yung-Li
;
Chang, Liang-Cheng
;
Hsu, Shao-Yiu
Darcy-scale capillary pressure is traditionally assumed to be constant. By contrast, a considerable gap exists between the measured and equilibrium capillary pressures when the same moisture saturation is considered with a high flow rate, and this gap is called the dynamic effect on the capillary pressure. In this study, downward infiltration experiments of sand columns are performed to measure cumulative infiltration and to calculate the wetting front depth and wetting front velocity in sands with different grain sizes. We estimate the equilibrium capillary pressure head or suction head at the wetting front using both the classical Green-Ampt (GAM) and modified Green-Ampt (MGAM) models. The results show that the performance of MGAM in simulating downward infiltration is superior to that of GAM. Moreover, because GAM neglects the dynamic effect, it systematically underestimates the equilibrium suction head in our experiments. We also find that the model parameters (alpha) over cap and beta of MGAM are affected by the grain size of sands and porosity, and the dynamic effect of the capillary pressure increases with decreasing grain size and increasing porosity.
臺灣地區地下水區水文地質調查及地下水資源評估-地下水補注潛勢評估與地下水模式建置(1/4)
(2009)
張良正
;
Chang, Liang-Cheng
;
國立交通大學土木工程研究所
水資源的保育是國家重要政策之一，地下水源的保護更是刻不容緩的工作，其中水文地質調查、地下水資源評估、地下水補注機制分析與現地水力試驗與監測則為必要的工作。經濟部自民國80 年起，分三期共十七年執行「臺灣地區地下水觀測網整體計畫」，已於臺灣九個地下水區及恒春和澎湖地區，進行水文地質調查研究及地下水觀測井建置工作，並建立完成臺灣地區水文地質基本資料、地下水監測系統、水文地質資料庫及岩心庫等。然而為提高地下水天然補注區範圍劃定及補注量評估之精確度，尚需補充更詳細之地下水層蓄水參數、水文地質基本資料及長期地下水水質和水位觀測數據，再結合地下水水位歷線分析，進行地下水補注潛勢評估及建立地下水流數值模式。本計畫係依據「臺灣地區地下水區水文地質調查及地下水資源評估計畫」（98 年至101 年）實施進度規劃，進行濁水溪沖積扇及屏東平原地下水區之全區地下水補注潛勢評估與地下水模式建置，並逐年達成下列目標： (1) 建立地下水區全區之地下水補注潛勢評估作業程序。 (2) 完成濁水溪沖積扇地下水主要補注區劃分。 (3) 完成屏東平原地下水主要補注區劃分。 (4) 完成濁水溪沖積扇地下水補注量、抽水量及補注潛勢評估。 (5) 完成屏東平原地下水補注量、抽水量及補注潛勢評估。本計畫所得成果可供主管機關劃定地下水水源保護區之依據，並可藉此對保護區土地利用及水土污染防治提出適當的管制辦法，使地下水資源管理朝向永續利用的目標跨出一大步。
Applying Multiobjective Genetic Algorithm to Analyze the Conflict among Different Water Use Sectors during Drought Period
(2010-09-01)
Chang, Liang-Cheng
;
Ho, Chih-Chao
;
Chen, Yu-Wen
;
土木工程學系
;
Department of Civil Engineering
Water deficits often occur during the drought season and may cause water conflicts among various water use sectors. The reservoir rule curve operation is commonly used to avoid extreme water shortage during droughts in Taiwan. When applying the rule curve operation, the water supply discounting ratio for different sectors implies a trade-off of water deficit impact among sectors. This study therefore develops a multiobjective water resource management model to evaluate the trade-off curve of water deficit impact between irrigation and public sectors to facilitate negotiation between the sectors for obtaining acceptable discounting ratios. The study uses the shortage index to assess water deficit impact. The proposed model integrates operating rules, the stepwise optimal water allocation model, and the convex hull multiobjective genetic algorithm to solve the multiobjective regional water allocation planning problem. The computed trade-off curve, noninferior solutions, provides relevant information to facilitate negotiating water-demand transfer. The results reveal that when decision makers prefer specified water use, the discounting ratio of another competing water use at the low buffer zone should be limited on the lower bound.
Using a hybrid approach to optimize experimental network design for aquifer parameter identification
(2010-10-01)
Chang, Liang-Cheng
;
Chu, Hone-Jay
;
Lin, Yu-Pin
;
Chen, Yu-Wen
;
土木工程學系
This research develops an optimum design model of groundwater network using genetic algorithm (GA) and modified Newton approach, based on the experimental design conception. The goal of experiment design is to minimize parameter uncertainty, represented by the covariance matrix determinant of estimated parameters. The design problem is constrained by a specified cost and solved by GA and a parameter identification model. The latter estimates optimum parameter value and its associated sensitivity matrices. The general problem is simplified into two classes of network design problems: an observation network design problem and a pumping network design problem. Results explore the relationship between the experimental design and the physical processes. The proposed model provides an alternative to solve optimization problems for groundwater experimental design.
An Integrating Approach for Conjunctive-Use Planning of Surface and Subsurface Water System
(2011-01-01)
Chang, Liang-Cheng
;
Ho, Chih-Chao
;
Yeh, Ming-Sheng
;
Yang, Chao-Chung
;
土木工程學系
This study proposes an integrated approach to assess the performance of a conjunctive-use surface and subsurface water system. System dynamics serves as the main framework of the proposed conjunctive-use model, simulating the interaction between surface and subsurface water and the impact of various conjunctive-use alternatives on the system as a whole. This study assumes natural groundwater recharge as a water source to the system, and estimates its volume using geographic information system (GIS) tools, a groundwater simulation model (MODFLOW), and a parameter identification model (UCODE). This study assesses various conjunctive-use alternatives and analyzes the frequency of water shortage to illustrate how the recharge rate affects water supply reliability under the conjunctive-use framework. Simulation results indicate that conjunctive-use with artificial recharge indeed reduces the frequency of extreme water shortages. Results also reveal that artificial recharge is necessary to maintain groundwater conservation without overusing river flow. Although this study focuses on southern Taiwan, the proposed concepts and procedure are applicable to other areas with a similar conjunctive-use framework.
Integration of Optimal Dynamic Control and Neural Network for Groundwater Quality Management
(2012-03-01)
Chang, Liang-Cheng
;
Chu, Hone-Jay
;
Hsiao, Chin-Tsai
;
土木工程學系
;
Department of Civil Engineering
This study integrates an artificial neural network (ANN) and constrained differential dynamic programming (CDDP) to search for optimal solutions to a nonlinear time-varying groundwater remediation-planning problem. The proposed model (ANN-CDDP) determines optimal dynamic pumping schemes to minimize operating costs and meet water quality requirements. The model uses two embedded ANNs, including groundwater flow and contaminant transport models, as transition functions to predict groundwater levels and contaminant concentrations under time-varying pumping. Results demonstrate that ANN-CDDP is a simplified management model that requires considerably less computation time to solve a fine mesh problem. For example, the ANN-CDDP computing time for a case involving 364 nodes is 1/26.5 that of the conventional optimization model.

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