Establishment of turbidity forecasting model and early-warning system for source water turbidity management using back-propagation artificial neural network algorithm and probability analysis.

The purpose of this study is to establish a turbidity forecasting model as well as an early-warning system for turbidity management using rainfall records as the input variables. The Taipei Water Source Domain was employed as the study area, and ANOVA analysis showed that the accumulative rainfall records of 1-day Ping-lin, 2-day Ping-lin, 2-day Fei-tsui, 2-day Shi-san-gu, 2-day Tai-pin and 2-day Tong-hou were the six most significant parameters for downstream turbidity development. The artificial neural network model was developed and proven capable of predicting the turbidity concentration in the investigated catchment downstream area. The observed and model-calculated turbidity data were applied to developing the turbidity early-warning system. Using a previously determined turbidity as the threshold, the rainfall criterion, above which the downstream turbidity would possibly exceed this respective threshold turbidity, for the investigated rain gauge stations was determined. An exemplary illustration demonstrated the effectiveness of the proposed turbidity early-warning system as a precautionary alarm of possible significant increase of downstream turbidity. This study is the first report of the establishment of the turbidity early-warning system. Hopefully, this system can be applied to source water turbidity forecasting during storm events and provide a useful reference for subsequent adjustment of drinking water treatment operation.

Evolutionary analysis of rainstorm momentum and non-stationary variating patterns in response to climatic changes across diverse terrains.

This study aims to analyze time-series measurements encompassing rainstorm events with over a century of datasets to identify rainstorm evolution and dimensional transitions in non-stationarity. Rainstorm events are identified using partial duration series (PDS) to extract changes in rainstorm characteristics, namely maximum intensity (MAXI), duration (D), total rainfall (TR), and average rainfall intensity (ARI), in response to climate change. Ensemble empirical mode decomposition is used for trend filtering and non-stationary identification to explore spatiotemporal insight patterns. Trend models for the first-second-order moments of rainstorm characteristics are used to formulate the identified mean-variance trends using combined multi-dimensional linear-parabolic regression. Best-fitting combinations of various distributions (probability density functions) and trend models for multiple characteristic series are identified based on the Akaike information criterion. We analyze the dimensional transition in rainfall non-stationarity based on sensitivity analysis using PDS to determine its natural geophysical causes. The integrated methodology was applied to the data retrieved from nine weather stations in Taiwan. Our findings reveal rainstorm characteristics of "short D but high rainfall intensity" or "lower MAXI but high TR" across multiple stations. The parabolic trend of the first-order moment (i.e., mean) of ARI, D, and TR appears at the endpoint of the mountain ranges. Areas receiving monsoons and those on the windward plain show a rising parabolic trend in the first- and second-order moments (i.e., mean-variance) characterizing MAXI, implying that the occurrence frequency and magnitude of extreme MAXI increases. Non-stationary transitions in MAXI appear for mountain ranges exposed to the monsoon co-movement effect on both windward and leeward sides. Stations in the plains and rift valleys show upgraded and downgraded transitions in the non-stationary dimensions for D, respectively.

Multi-order analytical solving computation of rainstorm causal decomposition during typhoons using a designed key-lock quasi-Newton optimizing derivation.

To precisely identify multi-dimensional spatiotemporal rain-making parameters, generate an approximate Hessian matrix, and solve the nonlinear ill-posed problem, this study uses composite logical tangent hyperbolic functions to construct the rain-generating simulation model as nonlinear algebraic equations with designed key-lock quasi-Newton optimization for deriving multi-order objective functional derivatives for rainstorm causal decomposition into advanced functional, analytical solution (lock) and Newton's conditional constraints. Specifically, the rank-two approximate structure of the Levenberg-Marquardt and Broyden-Fletcher-Goldfarb-Shanno quasi-Newton algorithms are modified as the symmetric rank-four structure to efficiently calculate a positive definite stable Hessian and solve the constrained nonlinear rain-making threshold. The model projects various rain-making factors into multi-rank loading scores, characterizing rain-generating mechanisms and causal components as associated DNAs. To accelerate/modify directional convergence, avoid local minimum, and detect global optimum, the devised vectorized limited switchable step sizes are optimized using advanced double-bracketing approaches combined with candidate parameters' correction vectors (key) and referenced step-size distributions solved by Newton's constrained analytical solution to reduce heterogeneous differences and eliminate the conventional overestimated Hessian. The identified rain-making DNAs reveal that typhoons with similar DNAs move in similar directions. Specifically, rain-making DNAs in Taipei Category 1 were correlated with wind force/direction and cloud height along PCs 1, 3, 4, and 7, and those in Category 2 were correlated with cloud-cover distribution along PCs 1, 2, and 5. The identified rain-making thresholds of typhoons with constant direction/structure showed a weaker steady state, whereas the unsteady rest produced multi-peak rainfall hydrographs. Rain evolution analysis reveals that cloudy rainbands, carried by the wind field, move along the Tamsui River valley when traveling between northeast and south-southeast of Taipei; converge with gradient and geostrophic winds when traveling between east-northeast and southwest; merge with southwest monsoon when traveling between west-southwest and northeast of Kaohsiung.

Real-time discharge measurement in tidal streams by an index velocity.

Discharge measurement in a tidal stream is always a difficult task. Owing to the complex flow conditions, discharge measurement in tidal streams has to be finished quickly, and must be highly efficient in order to yield an accurate measurement of real-time discharge. Measuring the discharge of tidal streams is done in three steps: (1) establishing the stage and cross-sectional area relation, (2) estimating the index velocity by using a velocity distribution equation based on the probability concept, (3) establishing the relationship between the index and mean velocities. Then the cross-sectional area and mean velocity can be estimated by the gage height and index velocity, respectively. The discharge of tidal streams is computed as the product of the cross-sectional area and mean velocity. The velocity distribution of the Taipei Bridge and Guan-du Bridge in the Tanshui River were established and analyzed to demonstrate the use of discharge measurement by index velocity for estimating the discharge of this tidal stream. The results reveal no large difference between the discharges measured by the conventional methods and the index velocity. This pilot study proposed a cost-effectiveness and efficient method. It is an easy, quick, and accurate model for measuring the real-time discharge of a tidal stream. It makes automatic, real-time, and continuous monitoring of the discharge in a tidal stream become possible.

Applying the Taguchi method to river water pollution remediation strategy optimization.

Optimization methods usually obtain the travel direction of the solution by substituting the solutions into the objective function. However, if the solution space is too large, this search method may be time consuming. In order to address this problem, this study incorporated the Taguchi method into the solution space search process of the optimization method, and used the characteristics of the Taguchi method to sequence the effects of the variation of decision variables on the system. Based on the level of effect, this study determined the impact factor of decision variables and the optimal solution for the model. The integration of the Taguchi method and the solution optimization method successfully obtained the optimal solution of the optimization problem, while significantly reducing the solution computing time and enhancing the river water quality. The results suggested that the basin with the greatest water quality improvement effectiveness is the Dahan River. Under the optimal strategy of this study, the severe pollution length was reduced from 18 km to 5 km.

Multireservoir real-time operations for flood control using balanced water level index method.

This paper presents a real-time simulation-optimization operation procedure for determining the reservoir releases at each time step during a flood. The proposed procedure involves two models, i.e., a hydrological forecasting model and a reservoir operation model. In the reservoir operation model, this paper compares two flood-control operation strategies for a multipurpose multireservoir system. While Strategy 1 is the real-time joint reservoir operations without using the balanced water level index (BWLI) method, Strategy 2 involves real-time joint reservoir operations using the BWLI method. The two strategies presented are formulated as mixed-integer linear programming (MILP) problems. The idea of using the BWLI method is derived from the HEC-5 program developed by the US Army Corps of Engineers. The proposed procedure has been applied to the Tanshui River Basin system in Taiwan using the 6h ahead forecast data of six typhoons. A comparison of the results obtained from the two strategies reveals that Strategy 2 performs much better than Strategy 1 in determining the reservoir real-time releases throughout the system during flood emergencies in order to minimize flooding, while maintaining all reservoirs in the system in balance if possible. Consequently, the proposed model using the BWLI method demonstrates its effectiveness in estimating real-time releases.