Optimal Design of Multitype Groundwater Monitoring Networks Using Easily Accessible Tools          下载免费PDF全文

Thomas Wöhling  Andreas Geiges  Wolfgang Nowak 《Ground water》2016,54(6):861-870

Monitoring networks are expensive to establish and to maintain. In this paper, we extend an existing data‐worth estimation method from the suite of PEST utilities with a global optimization method for optimal sensor placement (called optimal design) in groundwater monitoring networks. Design optimization can include multiple simultaneous sensor locations and multiple sensor types. Both location and sensor type are treated simultaneously as decision variables. Our method combines linear uncertainty quantification and a modified genetic algorithm for discrete multilocation, multitype search. The efficiency of the global optimization is enhanced by an archive of past samples and parallel computing. We demonstrate our methodology for a groundwater monitoring network at the Steinlach experimental site, south‐western Germany, which has been established to monitor river—groundwater exchange processes. The target of optimization is the best possible exploration for minimum variance in predicting the mean travel time of the hyporheic exchange. Our results demonstrate that the information gain of monitoring network designs can be explored efficiently and with easily accessible tools prior to taking new field measurements or installing additional measurement points. The proposed methods proved to be efficient and can be applied for model‐based optimal design of any type of monitoring network in approximately linear systems. Our key contributions are (1) the use of easy‐to‐implement tools for an otherwise complex task and (2) yet to consider data‐worth interdependencies in simultaneous optimization of multiple sensor locations and sensor types.  相似文献   

Bayesian model averaging assessment on groundwater management under model structure uncertainty   总被引：1，自引：1，他引：0  

Frank T.-C. Tsai 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(6):845-861

This study introduces Bayesian model averaging (BMA) to deal with model structure uncertainty in groundwater management decisions. A robust optimized policy should take into account model parameter uncertainty as well as uncertainty in imprecise model structure. Due to a limited amount of groundwater head data and hydraulic conductivity data, multiple simulation models are developed based on different head boundary condition values and semivariogram models of hydraulic conductivity. Instead of selecting the best simulation model, a variance-window-based BMA method is introduced to the management model to utilize all simulation models to predict chloride concentration. Given different semivariogram models, the spatially correlated hydraulic conductivity distributions are estimated by the generalized parameterization (GP) method that combines the Voronoi zones and the ordinary kriging (OK) estimates. The model weights of BMA are estimated by the Bayesian information criterion (BIC) and the variance window in the maximum likelihood estimation. The simulation models are then weighted to predict chloride concentrations within the constraints of the management model. The methodology is implemented to manage saltwater intrusion in the “1,500-foot” sand aquifer in the Baton Rouge area, Louisiana. The management model aims to obtain optimal joint operations of the hydraulic barrier system and the saltwater extraction system to mitigate saltwater intrusion. A genetic algorithm (GA) is used to obtain the optimal injection and extraction policies. Using the BMA predictions, higher injection rates and pumping rates are needed to cover more constraint violations, which do not occur if a single best model is used.  相似文献   

Practical aspects of calibrating and selecting unit hydrograph-based models for continuous river flow simulation     

IAN LITTLEWOOD 《水文科学杂志》2013,58(5):795-811

Abstract

A continuous simulation rainfall-streamflow modelling approach that identifies unit hydrographs for total streamflow has been applied to an 11-year record from a national hydrometric monitoring network catchment in the UK. The model is of the parametrically parsimonious conceptual model (PPCM) type that can make efficient use of rainfall, streamflow and air temperature data readily available from established national and regional monitoring networks. A multiple split-sample model calibration and simulation analysis is presented that reveals some guiding principles for calibrating and applying PPCMs generally. The inadequacy of a one-dimensional objective function for calibrating best PPCMs is demonstrated. A two-dimensional objective function approach is superior but is shown to be unreliable in some cases, confirming the need for additional critical inspection of other model performance statistics, model parameters and time series plots as an integral part of the model calibration process. A strong tendency evident from the multiple split-sample analysis is that, for the catchment studied, models that fit relatively well in calibration mode perform relatively poorly in simulation mode.  相似文献   

Space–time forecasting of groundwater level using a hybrid soft computing model     

Madhumita Sahoo  Tanmoy Das  Komal Kumari 《水文科学杂志》2017,62(4):561-574

Forecasting of space–time groundwater level is important for sparsely monitored regions. Time series analysis using soft computing tools is powerful in temporal data analysis. Classical geostatistical methods provide the best estimates of spatial data. In the present work a hybrid framework for space–time groundwater level forecasting is proposed by combining a soft computing tool and a geostatistical model. Three time series forecasting models: artificial neural network, least square support vector machine and genetic programming (GP), are individually combined with the geostatistical ordinary kriging model. The experimental variogram thus obtained fits a linear combination of a nugget effect model and a power model. The efficacy of the space–time models was decided on both visual interpretation (spatial maps) and calculated error statistics. It was found that the GP–kriging space–time model gave the most satisfactory results in terms of average absolute relative error, root mean square error, normalized mean bias error and normalized root mean square error.  相似文献   

Numerical groundwater modelling as an effective tool for management of water resources in arid areas     

Mohamed El Alfy 《水文科学杂志》2013,58(6):1259-1274

Abstract

Groundwater, possibly of fossil origin, is used for water supply in some arid regions where the replenishment of groundwater by precipitation is low. Numerical modelling is a helpful tool in the assessment of groundwater resources and analysis of future exploitation scenarios. To quantify the groundwater resources of the East Owienat area in the southwest of the Western Desert, Egypt, the present study assesses the groundwater resources management of the Nubian aquifer. Groundwater withdrawals have increased in this area, resulting in a disturbance of the aquifer’s natural equilibrium, and the large-scale and ongoing depletion of this critical water reserve. Negative impacts, such as a decline in water levels and increase in salinity, have been experienced. The methodology includes application of numerical groundwater modelling in steady and transient states under different measured and abstraction scenarios. The numerical simulation model developed was applied to assess the responses of the Nubian aquifer water level under different pumping scenarios during the next 30 years. Groundwater management scenarios are evaluated to find an optimal management solution to satisfy future needs. Based on analysis of three different development schemes that were formulated to predict the future response of the aquifer under long-term water stress, a gradual increase in groundwater pumping to 150% of present levels should be adopted for protection and better management of the aquifer. Similar techniques could be used to improve groundwater management in other parts of the country, as well as other similar arid regions.