О конъюнктивном употреблении разделительных союзов (на материале польского и русского языков)

The author considers the problem of conjunctive use of disjunctive conjunctions in the perspective of functional grammar. In the first part of the article, the author verifies the logical approach to conjunctions, especially disjunctive conjunctions. The linguistic meaning of a conjunction is defined as information on the credibility or applicability of a (semantically) compound sentence under condition [10, 01], which means an alternative participation of referents in the described situation. In the following chapters, the author analyzes several language facts, namely sentences that contain a disjunctive relationship and which nevertheless express the general meaning of conjunction. The author explains these phenomena by the fact that in such sentences there are the types of configurations of conjunction with the exponents of other semantic categories: quantification and modality.

Conditional Operation Rules For Optimal Conjunctive Use of Surface And Groundwater

The current study presents an efficient method for deriving precise operation rules from all subsystems of a distributed conjunctive use system (CUS), including aquifer, river, and reservoir. Distributed aquifer simulation has been performed using the URM method. Given that the historical flow time series can only represent one of the possible situations in the future and its use to determine the performance of the CUS is certainly not very reliable, in this study, river flow uncertainties are implicitly considered. To develop the operation rules, the time series of river flow were generated using autoregressive model. Then, the operation optimization model of the system was implemented with the objective function of minimizing water shortage for different river flow time series. 70% of the data was used for model training and 30% for model validation. Finally, using the decision tree algorithm (M5Rules), the conditional operation rules were extracted and compared with the single linear regression operation rules. Using five efficiency criteria CC, MAE, RMSE, RAE, and RRSE, the comparison of conditional and single linear regression operating rules has been done. The results showed that the the conditional operation rules reduces relative absolute error by a minimum of 39% and a maximum of 71%. If the system is operated according to the conditional rules, in the worst case, the amount of water shortage imposed will be 16.61 MCM over ten years.

Hybrid optimization model for conjunctive use of surface and groundwater resources in water deficit irrigation system

The Increasing demand for food production with limited available water resources poses a threat to agricultural activities. Conventional optimization algorithm increases the processing stage and it performed with in the space, which is allocated from user. Therefore, the proposed work is utilized to design with better performance results. The conjunctive allocation of water resources maximizes the net benefit of farmers. In this study, a novel hybrid optimization model developed is first of its kind to resolve the sharing of water resources conflict among different reaches based on a genetic algorithm (GA), bacterial foraging optimization (BFO) and ant colony optimization (ACO) to maximize the net benefit of the water deficit Sathanur reservoir command. The GA-based optimization model considered crop-related physical and economic parameters to derive optimal cropping patterns for three different conjunctive use policies and further allocation of surface and groundwater for different crops are enhanced with the BFO. The allocation of surface and groundwater for the head, middle and tail reaches obtained from BFO is considered as an input to the ACO as a guiding mechanism to attain an optimal cropping pattern. Comparing the average productivity values, Policy 3 (3.665 Rs/m3) has better values relating to Policy 1 (3.662 Rs/m3) and Policy 2 (3.440 Rs/m3). Thus, developed novel hybrid optimization model (GA-BFO-ACO) is very promising for enhancing farmer's net income and can be replicated in other irrigated regions to overcome chronic water problems. The productivity value of policy 3 was 6.54% greater than that of policy 2, whereas that of policy 1 was 6.45% greater. Overall, the comparison shows the better performance analysis of various optimization is done successfully.

Impact of Natural and Anthropogenic Stresses on Surface and Groundwater Supply Sources of the Upper Awash Sub-Basin, Central Ethiopia

Improving water security is critical to delivering the best outcomes for development. In Ethiopia, the upper Awash sub-basin supports expanding urban and industrial areas, with increasing water demands. Studies have preferentially focused either on surface water hydrology or on groundwater characterization. However, novel tools are required to support the conjunctive use of surface and groundwater for competing users under potential climate change impacts. In this paper, we present research based on a WEAP-MODFLOW link configured for four catchments in the upper Awash sub-basin (Akaki, Melka Kunture, Mojo, and Koka). The Akaki catchment supplies water for Addis Ababa city. Unlike most surface water hydrological models, both supply (surface water and groundwater) and demand (domestic, industrial, and livestock) are modeled. The tool was used to evaluate the impacts of population growth, leakage, expansion of surface and groundwater supply schemes, and climate change scenarios up to the year 2030. Considering the high population growth rate scenario for Addis Ababa city, the unmet domestic water demand may increase to 760 MCM in 2030. Water leakage through poor water supply distribution networks contributed about 23% of the unmet water demand. Though not significant compared with population and water loss stresses, climate change also affect the supply demand condition in the basin. Planning for more groundwater abstraction without considering additional surface water reservoir schemes will noticeably impact the groundwater resource, with groundwater levels projected to decline by more than 20 m. Even more groundwater level decline is observed In the Akaki catchment, where Addis Ababa city is located. Conjunctive use of surface and groundwater not only boosts the supply demand situation in the basin but will lift off some of the stresses from the groundwater resources. Even under the likely increase in temperature and low precipitation climate scenarios, the conjunctive use resulted in a significant increase in domestic water demand coverage from 26% for the reference condition to 90% in 2030, with minimum effect on the groundwater resources. To improve water security conditions through sustainable utilization of both surface and groundwater resources, policy responses need to consider surface and groundwater conjunctive use. Minimizing water leakage should also be given the highest priority.

A review of conjunctive GW-SW management by simulation–optimization tools

The conjunctive use of groundwater and surface water (GW-SW) resources has grown worldwide. Optimal conjunctive water use can be planned by coupling hydrologic models for the simulation of water systems with optimization techniques for improving management strategies. The coupling of simulation and optimization methods constitutes an effective approach to determine sustainable management strategies for the conjunctive use of these water resources; yet, there are challenges that must be addressed. This paper reviews (1) hydrologic models applied for the simulation of GW-SW interaction in the water resources systems, (2) conventional optimization methods, and (3) published works on optimized conjunctive GW-SW use by coupling simulation and optimization methods. This paper evaluates the pros and cons of GW-SW simulation tools and their applications, thus providing criteria for selecting simulation–optimization methods for GW-SW management. In addition, an assessment of GW-SW simulation–optimization tools applied in various studies over the world creates valuable knowledge for selecting suitable simulation–optimization tools in similar case studies for sustainable water resource management under multiple scenarios.