Improving the multi-objective evolutionary optimization algorithm for hydropower reservoir operations in the California Oroville–Thermalito complex

This study demonstrates the application of an improved Evolutionary optimization Algorithm (EA), titled Multi-Objective Complex Evolution Global Optimization Method with Principal Component Analysis and Crowding Distance Operator (MOSPD), for the hydropower reservoir operation of the Oroville–Thermalito Complex (OTC) – a crucial head-water resource for the California State Water Project (SWP). In the OTC's water-hydropower joint management study, the nonlinearity of hydropower generation and the reservoir's water elevation–storage relationship are explicitly formulated by polynomial function in order to closely match realistic situations and reduce linearization approximation errors. Comparison among different curve-fitting methods is conducted to understand the impact of the simplification of reservoir topography. In the optimization algorithm development, techniques of crowding distance and principal component analysis are implemented to improve the diversity and convergence of the optimal solutions towards and along the Pareto optimal set in the objective space. A comparative evaluation among the new algorithm MOSPD, the original Multi-Objective Complex Evolution Global Optimization Method (MOCOM), the Multi-Objective Differential Evolution method (MODE), the Multi-Objective Genetic Algorithm (MOGA), the Multi-Objective Simulated Annealing approach (MOSA), and the Multi-Objective Particle Swarm Optimization scheme (MOPSO) is conducted using the benchmark functions. The results show that best the MOSPD algorithm demonstrated the best and most consistent performance when compared with other algorithms on the test problems. The newly developed algorithm (MOSPD) is further applied to the OTC reservoir releasing problem during the snow melting season in 1998 (wet year), 2000 (normal year) and 2001 (dry year), in which the more spreading and converged non-dominated solutions of MOSPD provide decision makers with better operational alternatives for effectively and efficiently managing the OTC reservoirs in response to the different climates, especially drought, which has become more and more severe and frequent in California.     

OPAH a model for optimal design of multipurpose small hydropower plants

The investment in small hydropower plants requires the analysis of hydrological, technical, operational, budgetary, economical and financial aspects. The analysis of each possible configuration demands the joint action of several technicians, consuming substantial time and money. During initial design of the project, simplified procedures are usually adopted which may compromise the quality of the base configuration.In this paper we will present a global overview of the OPAH model, which was developed to surpass these limitations. This global model performs the optimization of project configuration. This model uses non-linear programming optimization to analyze the multipurpose operation of the hydropower plant. It uses a numeric simulation model of unsteady flow under pressure to analyze the hydraulic circuit. It uses an economical and financial simulation model that takes in to account the project risk associated to hydrologic and market variability, the financial capacity of the investor and the fiscal aspects.     

Building a research network to better understand climate governance in the Great Lakes

Climate-driven disturbances threaten the sustainability of coastal communities in the Great Lakes Basin. Because such disturbances are unpredictable, their magnitude, number and intensity are changing, and they occur at varying temporal and spatial scales. Consequently, communities struggle to respond in effective ways. The expected intensification of climate-driven disturbances will require that community capacity and governance structures match the spatial and temporal scales of these disturbances, as the most sustainable social and economic systems will be those that can respond at similar frequencies to key natural system drivers. The Climate Governance Variability in the Great Lakes Research Coordination Network (CGVG-RCN) was recently established to address questions about the relationship between climate-driven disturbances and community response. The objective of this short communication is to introduce the ideas behind the CGVG-RCN, outline its goals, and facilitate engagements and collaboration with social and natural scientists interested in social-ecological systems in the Great Lakes Basin.     

Long-term and seasonal nitrate trends illustrate potential prevention of large cyanobacterial biomass by sediment oxidation in Hamilton Harbour,Lake Ontario

Several studies have shown that large, experimental additions of nitrate (NO₃) to eutrophic systems can mitigate large populations of nuisance cyanobacteria and that high NO₃ concentrations can oxidize anoxic sediments. These studies are consistent with observations from numerous aquatic systems across a broad trophic range showing development of reduced surficial sediments precedes the formation of large cyanobacteria populations. We use 50+ years of data to explore whether high NO₃ concentrations may have been instrumental both in the absence of large populations of cyanobacteria in eutrophic Hamilton Harbour, Lake Ontario in the 1970s when total phosphorus (TP) and total nitrogen (TN) concentrations were high, and in delaying large populations until August and September in recent decades despite much lower TP and TN. Our results indicate that large cyanobacteria population events do not occur at the central station in July-September when epilimnetic NO₃ > 2.2 mg N L^?1. The results further suggest that remedial improvements to wastewater treatment plant oxidation capacity may have been inadvertently responsible for high NO₃ concentrations > 2.2 mg N L^?1 and thus for mitigating large cyanobacteria populations. This also implies that large cyanobacteria populations may form earlier in the summer if NO₃ concentrations are lowered.     

A detection problem: Sensitivity and uncertainty analysis of a land surface temperature approach to detecting dynamics of water use by groundwater-dependent vegetation

Sustainable management of groundwater-dependent vegetation (GDV) requires the accurate identification of GDVs, characterisation of their water use dynamics and an understanding of associated errors. This paper presents sensitivity and uncertainty analyses of one GDV mapping method which uses temperature differences between time-series of modelled and observed land surface temperature (LST) to detect groundwater use by vegetation in a subtropical woodland. Uncertainty in modelled LST was quantified using the Jacobian method with error variances obtained from literature. Groundwater use was inferred where modelled and observed LST were significantly different using a Student's t-test. Modelled LST was most sensitive to low-range wind speeds (<1.5 m s⁻¹), low-range vegetation height (<=0.5 m), and low-range leaf area index (<=0.5 m² m⁻²), limiting the detectability of groundwater use by vegetation under such conditions. The model-data approach was well-suited to detection of GDV because model-data errors were lowest for climatic conditions conducive to groundwater use.     

Use of flow-normalization to evaluate nutrient concentration and flux changes in Lake Champlain tributaries, 1990–2009

The U.S. Geological Survey evaluated 20 years of total phosphorus (P) and total nitrogen (N) concentration data for 18 Lake Champlain tributaries using a new statistical method based on weighted regressions to estimate daily concentration and flux histories based on discharge, season, and trend as explanatory variables. The use of all the streamflow discharge values for a given date in the record, in a process called “flow-normalization”, removed the year-to-year variation due to streamflow and generated a smooth time series from which trends were calculated. This approach to data analysis can be of great value to evaluations of the success of restoration efforts because it filters out the large random fluctuations in the flux that are due to the temporal variability in streamflow. Results for the full 20 years of record showed a mixture of upward and downward trends for concentrations and yields of P and N. When the record was broken into two 10-year periods, for many tributaries, the more recent period showed a reversal in N from upward to downward trends and a similar reversal or reduction in magnitude of upward trends for P. Some measures of P and N concentrations and yields appear to be related to intensity of agricultural activities, point-source loads of P, or population density. Total flow-normalized P flux aggregated from the monitored tributaries showed a decrease of 30 metric tons per year from 1991 to 2009, which is about 15% of the targeted reduction established by the operational management plan for the Lake Champlain Basin.     

Global sensitivity analysis of outputs over rice-growth process in ORYZA model

Dynamic crop models usually have a complex structure and a large number of parameters. Those parameter values usually cannot be directly measured, and they vary with crop cultivars, environmental conditions and managements. Thus, parameter estimation and model calibration are always difficult issues for crop models. Therefore, the quantification of parameter sensitivity and the identification of influential parameters are very important and useful. In this work, late-season rice was simulated with meteorological data in Nanchang, China. Furthermore, we conducted a sensitivity analysis of 20 selected parameters in ORYZA_V3 using the Extended FAST method. We presented the sensitivity results for four model outputs (LAI, WAGT, WST and WSO) at four development stages and the results for yield. Meanwhile, we compared the differences among the sensitivity results for the model outputs simulated in cold, normal and hot years. The uncertainty of output variables derived from parameter variation and weather conditions were also quantified. We found that the development rates, RGRLMN and FLV0.5 had strong effects on all model outputs in all conditions, and parameters WGRMX and SPGF had relative high effects on yield in cold year. Only LAI was sensitive to ASLA. Those influential parameters had unequal effects on different outputs, and they had different effects at four development stages. With the interaction effects of parameter variation and different weather conditions, the uncertainty of model outputs varied significantly. However, the weather conditions had negligible effects on the identification of influential parameters, although they had slight effects on the ranks of the parameters' sensitivity for outputs in the panicle-formation phase and the grain-filling phase, including yield at maturity. The results suggested that the influential parameters should be recalibrated in priority and fine-tuned with higher accuracy during model calibration.     

Experimental and numerical research on portable short-throat flume in the field

The use of portable short-throat flume in the field is an emerging technique developed for water discharges measurement of inlet in the field. Based on the principle of critical flow and RNG k–ε three-dimensional turbulence model along with the TruVOF technique, experiments and corresponding simulations were performed for 16 working conditions on the 76 mm width flume with discharges up to 40.01 L/s to determine its hydraulic performance. Hydraulic performance of the flume obtained from simulation analyses were later compared with observed results based on time-averaged flow field, flow pattern, Froude number and velocity distribution. Comparison yielded a solid agreement between results from two methods with relative error below ±10%. Regression models developed for upstream depth versus discharge under different working conditions were satisfying with the relative error of 9.16%, which met the common requirements of flow measurement in irrigation areas. Compared to the long-throat flume, head loss of portable short-throat flume in the field was significantly less. Further, head loss under the free flow condition was less than that under the submerged flow condition of portable short-throat flume with a flat base in the field.     

Coastal trapped waves in the southern Caspian Sea

Previous studies reported coastal trapped waves (CTWs) in the Caspian Sea (CS). This study deals with the generation mechanisms, the temporal and spatial variability of CTWs in this area, and their transformations during propagation from the origin to the destination using recent measurements and high-resolution numerical simulations. CTWs are observed at all stations with periods of 2–6 days after northerly storms. The Absheron Peninsula, old Sefidrud delta, and Nur coasts were identified as the CTWs prone regions. The generation of CTWs in these locations was confirmed using numerical experiments. The propagation away from the generating location of CTWs was analyzed using a representative real wind storm. In the west part of the CS, the generation mechanism of CTWs is mainly similar to the barotropic Kelvin waves; in contrast, it is similar to the continental shelf waves in the southern shelves. The results can be used to study the contribution of generated CTWs to the transport of sediment and biological materials in all large lakes.