Water Resources Management Problems Research Articles

An Approach to Optimizing the Water Resources Management Problem in a Fuzzy Environment

An Approach to Optimizing the Water Resources Management Problem in a Fuzzy Environment

Water Resources Management Issues in the Danube River Basin District—Examples from Serbia

This paper aims to present water resources management problems in Serbia and recommend possible solutions. Key issues involve water quality and water quantity. Water quality is endangered by organic pollution from different sources and low degree of waste water treatment. Incomplete exploration of water resources availability as well as their inadequate exploitation are the biggest problems related to water quantity. Other problems involve lack of harmonized legislation, insufficient investments in water resources management, inadequate water price, low level of services, the lack of an effective integral water management system, illegal construction in the areas of water sources and potentially floodplains as well as lack of monitoring. In order to deal with these problems and overcome or mitigate their consequences, complex of measures should be implemented in the frame of interdisciplinary and transdisciplinary national and international projects.

Optimal operation of reservoir systems using the Wolf Search Algorithm (WSA)

Abstract Optimizing hydropower plants is complex due to nonlinearity, complexity, and multidimensionality. This study introduces and evaluates the performance of the Wolf Search Algorithm (WSA) for optimizing the operation of a four-reservoir system and a single hydropower system in Iran. Results indicate WSA could reach 99.95 and 99.91 percent of the global optimum for the four-reservoir system and single reservoir system, respectively. Comparing the results of WSA with a genetic algorithm (GA) also indicates WSA's supremacy over GA. Thus, due to its simple structure and high capability, WSA is recommended for use in other water resources management problems.

The sustainability of rainwater harvesting for supplying domestic water demand in Yogyakarta City

Yogyakarta city has a problem of water resources management along with the rapid development in this region. Rainwater harvesting (RWH) can be an alternative choice in urban water resources management. This study aims to determine the best RWH scenario as a sustainable water supply to meet domestic water demand in Yogyakarta City. The method used is the Sustainability Index with 3 parameters including reliability, resilience and vulnerability. Each parameter is a derivative of a water balance simulation of the RWH system using the data range in the period 2006–2015. This study compares the percentage of roof usage in the RWH system and the level of domestic water demand. The results of this study indicate that the RWH scenario by utilizing 50 %–75 % of the roof area can be ideally meet up to 80 % of domestic water needs in Yogyakarta City. RWH scenario with 100 % roof usage can meet all domestic water needs well. This study shows that the RWH system can have a positive impact on the management and sustainability of water resources in Yogyakarta City.

A Two-Stage Approach Integrating SOM- and MOGA-SVM-Based Algorithms to Forecast Spatial-temporal Groundwater Level with Meteorological Factors

To obtain accurate and effective forecasts of groundwater level, a two-stage approach integrating Self-Organizing Maps (SOM-), Multi-Objective Genetic Algorithm and Support Vector Machine (MOGA-SVM-based) algorithms is developed herein using the optimal input combinations of meteorological factors in a complex spatial-temporal groundwater system. In the first stage, an SOM-based clustering method is used to separate distinct and meaningful spatial groundwater zones. In the second stage, a temporal analysis model integrating MOGA with SVM is developed to identify the optimal input combinations. An actual application is conducted using the Choushui River Alluvial Fan in Taiwan as the case study; it currently has over-pumping and land subsidence problems. The MOGA-SVM model is compared with an existing model based on the SVM to demonstrate the superiority of the proposed approach. Moreover, the effective meteorological factors in different spatial zones can be determined by using the proposed approach to show the spatial characteristics, and these factors can significantly improve the forecasting performance, especially for long lead-time forecasting. In conclusion, the proposed spatial-temporal approach is applicable to a huge and complex groundwater system; it provides an alternative to the existing model for water resources management problems.

Water erosion prediction at a national scale for South Africa

Erosion is a major soil degradation problem in South Africa, confronting both land and water resource management throughout the country. Given the increasing threat of soil erosion, a need to improve techniques of estimating the soil-erosion risk at a national scale was identified by the National Department of Agriculture and forms the basic premise of this study. Principles and components of the Revised Universal Soil Loss Equation are applied here since the model combines sufficient simplicity for application on a national scale with a comprehensive incorporation of the main soil-erosion factors. Indicators of erosion susceptibility of the physical environment, including climate erosivity, soil erodibility and topography were improved over earlier assessments by feeding current available data into advanced algorithms. Two maps are presented: an actual erosion-risk distribution, and a potential erosion-risk map that excludes the vegetation cover factor. Actual soil-erosion risk, which relates to the current risk of erosion under contemporary vegetation and land-use conditions, was accounted for by regression equations between vegetation cover and MODIS-derived spectral index. The area of land with a moderate to severe potential risk is found to total approximately 61 m. ha (50%). Although more than 91 m. (75%) are classified as having only a very low to low actual risk, approximately 26 m. ha (20%) of land is eroded at a rate greater than a soil-loss tolerance of 10 t/ha·yr, showing the potential to target erosion control to problem areas. The Eastern Cape, Limpopo and KwaZulu-Natal Provinces have the highest erosion potential. Comparison of potential and actual erosion risk indicates that over 26 m. ha (>30% of national land) could be subject to high erosion risk without maintenance or careful management of the current vegetation cover and land use. Although the distribution of the actual erosion risk broadly follows that outlined previously, this study provides an advance on previous assessments of erosion; results are validated more comprehensively than before, and show an overall accuracy of 77%. The paper also describes many of the limitations inherent in regional erosion studies.

The α-Representation Inexact T2 Fuzzy Sets Programming Model for Water Resources Management of the Southern Min River Basin under Uncertainty

In this study, a new α-representation of the inexact T2 fuzzy sets programming model (α-RITF2SP) is proposed for water resources planning under uncertainties. The developed model is a hybrid of inexact type-2 (T2) fuzzy sets (FSs) optimal programming based on α-cuts and α-planes (z-slices) algorithms, and both can be used in problems of water resource management without a loss of generality. Therefore, this novel method represents a complementary method to combine both of these algorithms to make inexact T2FSs methods easier and faster for users under uncertainties. This method provides not only a reduction in computations when computing fuzzy functions, but also a map of the primary variable of T2FSs in the secondary membership function. The α-RITF2SP is applied to a real case study of the operation of water resource systems in the southern Min River basin that involves three cities: Xiamen, Zhangzhou, and Quanzhou. The results of the water allocations and benefits have been analyzed. The symptoms of results indicate the higher profit with a higher wastewater treatment rate. It also represents that this model has enhanced abilities and it is relevant and practical as well as can serve as a guide for the development of this regional economy.

Application of Artificial Neural Networks for Identifying Optimal Groundwater Pumping and Piping Network Layout

The simulation-optimization approach is often used to solve water resource management problem although repeated use of the simulation model enhances the computational load. In this study, Artificial Neural Network (ANN) and Bagged Decision Trees (BDT) models were developed as an approximator for Analytic Element Method (AEM) based groundwater flow model. Developed ANN and BDT models were coupled with Particle Swarm Optimization (PSO) model to solve the well-field management problem. The groundwater flow model was developed for the study area and used to generate the dataset for the training and testing of the ANN & BDT models. These coupled ANN-PSO & BDT-PSO models were employed to find the optimal design and cost of the new well-field system by optimizing discharge & co-ordinate of wells along with the cost effective layout of piping network. The Minimum Spanning Tree (MST) based model was used to find out the optimal piping network layout and checking the hydraulic constraints in the piping network. The results show that the ANN & BDT models are good approximators of AEM model and they can reduce the computational burden significantly although ANN model performs better than BDT model. The results show that the coupling of piping network model with simulation-optimization model is very significant for finding the cost effective and realistic design of the new well-field system.

Irrigation Management Based on Reservoir Operation with an Improved Weed Algorithm

Water scarcity is a serious problem throughout the world. One critical part of this problem is supplying sufficient water to meet irrigation demands for agricultural production. The present study introduced an improved weed algorithm for reservoir operation with the aim of decreasing irrigation deficits. The Aswan High Dam, one of the most important dams in Egypt, was selected for this study to supply irrigation demands. The improved weed algorithm (IWA) had developed local search ability so that the exploration ability for the IWA increased and it could escape from local optima. Three inflows (low, medium and high) to the reservoir were considered for the downstream demands. For example, the average solution for the IWA at high inflow was 0.985 while it was 1.037, 1.040, 1.115 and 1.121 for the weed algorithm (WA), bat algorithm (BA), improved particle swarm optimization algorithm (IPSOA) and genetic algorithm (GA). This meant that the IWA decreased the objective function for high inflow by 5.01%, 5.20%, 11.65% and 12% compared to the WA, BA, IPSOA and GA, respectively. The computational time for the IWA at high inflow was 22 s, which was 12%, 18%, 24% and 29% lower than the WA, BA, IPSOA and GA, respectively. Results indicated that the IWA could meet the demands at all three inflows. The reliability index for the IWA for the three inflows was greater than the WA, BA, IPSOA and GA, meaning that the released water based on IWA could well supply the downstream demands. Thus, the improved weed algorithm is suggested for solving complex problems in water resources management.

Trans-boundary water conflicts between Bangladesh and India: water governance practice for conflict resolution

Bangladesh and India Sharing fifty-four trans-boundary rivers water that flows from India to Bangladesh. Bangladesh is mostly dependent on India for their water and has no control over the water shed management policy of the rivers. Being a smaller, weaker military and economy than India, Bangladesh cannot influence the watershed management policies and face floods and water scarcity, reducing yield production and fish productivity, an ecological imbalance in estuarine areas, saline water intrusion in the southwestern part of Bangladesh and reduced navigation. Water governance is the combination of the political, social, economic and administrative system, which manage the water resources and provide services in the different level of society. Based on the water governance definition the researchers find out the different stakeholder in the management of water governance and the lack of practices of the theoretical concept of water governance and try to indicate the possibilities of the better solutions (Conflict or cooperation) of this trans-boundary water conflicts between both countries. The paper also compared the present negotiation process with different kinds of modes of wicked problem in water resource management. The study recommends few suggestions to minimize the conflict over the utilization of trans-boundary water resources management for example, a hydro-community like EU water framework Directive that is based on the soft power of peer review rather than a penalizing measure.Int. J. Agril. Res. Innov. & Tech. 8 (1): 79-84, June, 2018

Robust fractional programming approach for improving agricultural water-use efficiency under uncertainty

Water-use efficiency and uncertainty treatment are foci in the modeling of agricultural water management systems. To address these challenging issues, a robust fractional programming (RFP) method that coupled fractional programming with robust optimization was developed in this study to improve agricultural water-use efficiency under uncertainty. RFP improved upon the fractional programming by being able to tackle highly uncertain information without known distributions. It also extended the capability of the robust optimization method in addressing ratio optimal problems. To demonstrate its effectiveness and applicability, RFP was applied to a long-term agricultural water resources management problem in arid north-west China, where water scarcity and low water-use efficiency hindered local development. It generated benefit- and risk-explicit plans for crop pattern adjustments. Vegetables were recommended as the preferred crop. A number of scenarios combining different fluctuation and protection levels were analyzed and interpreted with practical implications. It was observed that higher water-use efficiency could be achieved through reducing parametric uncertainty and risk-aversion levels. Simulation experiments validated that the benefits claimed by the RFP model were sufficiently conservative and could be reliably achieved. The comparisons of RFP results against the baseline operations and those from two other alternatives demonstrated that, RFP could result in higher resource-use efficiency and controllable system-violation risks. The developed approach is also applicable to other optimization problems aiming at enhancing resource-use efficiency under uncertainty.

Optimal water resource management for sustainable development of the chemical industrial park under multi-uncertainty and multi-pollutant control.

Two major concerns over the chemical industrial park (CIP) operations are high consumption of water resources and large amount of pollutant emissions. This study develops an interval chance-constrained programming model for industrial water resources management (ICCP-IWM) with consideration of multi-uncertainty and multi-environmental constraints. Uncertainties expressed as intervals and probability distributions are merged in the ICCP-IWM framework. The developed model is used to solve a real-world water resource management problem in the Shenyang Chemical Industrial Park to demonstrate its capacity and effectiveness, where the objective is to minimize the system cost of water pathways and pollutant-emission control under a series of constraints. Interval solutions with respect to water resources allocation, wastewater management, and pollutant emissions could be generated. Results indicate that a lower violation risk leads to an increased strictness of the constraints, then to a higher system cost; conversely, a higher violation risk results in a lower system cost, at the expense of an increase in the risk. These findings would be recommended by the decision-makers because of their applicability for practical decision process providing the optimal strategy for sustainable water resource management under multiple uncertainties.

A fuzzy multi-stakeholder multi-criteria methodology for water allocation and reuse in metropolitan areas.

In this paper, a fuzzy decision making methodology is proposed to find a socially optimal scenario for allocating effluent of wastewater treatment plants and urban and suburban runoffs to agricultural regions and recharging aquifers. The presented methodology named modified fuzzy social choice (MFSC) considers multi-stakeholder multi-criteria problems under uncertainties inherent in a decision making process utilizing a fuzzy ranking method and the fuzzy social choice (FSC) theory. A set of water and wastewater allocation scenarios are proposed for water quantity and quality management of the study area, while six main stakeholders with conflicting utilities and different negotiation powers are involved. The proposed methodology is applied to Tehran metropolitan area, the capital city of Iran with the population of about 8 million people, to examine its applicability and effectiveness. The results shows that using fuzzy multi-stakeholder multi-criteria decision making method considering equal and different negotiation powers can lead to different outcomes. Based on the results, the MFSC method, which considers a number of decision makers having different negotiation powers, degrees of importance of decision making criteria, and some important uncertainties, performs more promising in real water resources management problems.

The use of an integrated variable fuzzy sets in water resources management

Abstract. Based on the evaluation of the present situation of water resources and the development of water conservancy projects and social economy, optimal allocation of regional water resources presents an increasing need in the water resources management. Meanwhile it is also the most effective way to promote the harmonic relationship between human and water. In view of the own limitations of the traditional evaluations of which always choose a single index model using in optimal allocation of regional water resources, on the basis of the theory of variable fuzzy sets (VFS) and system dynamics (SD), an integrated variable fuzzy sets model (IVFS) is proposed to address dynamically complex problems in regional water resources management in this paper. The model is applied to evaluate the level of the optimal allocation of regional water resources of Zoucheng in China. Results show that the level of allocation schemes of water resources ranging from 2.5 to 3.5, generally showing a trend of lower level. To achieve optimal regional management of water resources, this model conveys a certain degree of accessing water resources management, which prominently improve the authentic assessment of water resources management by using the eigenvector of level H.

Trash-polluted irrigation: characteristics and impact on agriculture

Trash pollution has been a problem in sustainable water resources management. Trash pollutes not only rivers, lakes and seas, but also irrigation canals and rice fields. This study aimed to identify the characteristics of solid waste (type, time of occurrence and sources of trash) and its impact on agriculture. The study was conducted in four irrigation areas, namely Gamping, Merdiko, Nglaren and Karangploso in Bantul District, Yogyakarta Special Region. We applied the Irrigation Rapid Trash Assessment (IRTA) as our field survey instrument. The results showed that trash was found throughout irrigation canals and rice fields, and the occurrence was influenced by water flow, time and farmer activities. The irrigation was dominantly polluted by plastic trash (52.2%), biodegradable waste (17.91%) and miscellaneous trash (12.3%). The IRTA score showed that Gamping Irrigation Area was at marginal condition, bearing a high risk of disturbing the operation and maintenance of the irrigation canals as well as farmers’ health. Trash in irrigation also generated technical impact of the irrigation operation and maintenance, environmental quality, and social life. This research also offered environmental policy integration approach and water-garbage governance approach as an alternative solution to manage water resources and agriculture in a sustainable manner, under the pressure of increasing amount of trash.

An Approach for Supporting Problem Structuring in Water Resources Management and Planning

The watershed committees in Brazil often face difficulties to find out consensus solution for problems in water resources management and planning, due to multiple participants with different backgrounds, differences of opinion, conflict of interests and differences in perceiving and interpretation of problem and solution. This situation results in conflicts and consequently put activities of committees at risk. The Problem Structuring Methods – PSMs are techniques to structure problems and analyze similar type of problems. PSMs offer a way of representing the situation to provide clarity to participants in understanding the problem and lead to converging on potential agreeable actions for at least partial resolutions. This paper presents a group decision approach for supporting water resources management and planning, based on the use of the PSM Strategic Options Development and Analysis – SODA, which performs the cognitive mapping of individuals. The approach promotes a common understanding about a complex situation under investigation, assisting the group in identification of a course of actions for solving the problem. The approach is intended to support Brazilian watershed committees and it was applied to the committee of the Paraiba River watershed in northeastern Brazil. Using this approach, the committee identified inadequate watershed management as a major issue that must be undertaken in order to achieve mitigation of watershed degradation.

Handling Uncertain Gross Margin and Water Demand in Agricultural Water Resources Management using Robust Optimization

In this paper, an application of Robust Optimization in agricultural water resource management problem under gross margin and water demand uncertainty is presented. Water resource management is a series of activities that includes planning, developing, distributing and managing the use of water resource optimally. Water resource management for agriculture can be one of the efforts to optimize the benefits of agricultural output. The objective function of agricultural water resource management problem is to maximizing total benefits by water allocation to agricultural areas covered by the irrigation network in planning horizon. Due to gross margin and water demand uncertainty, we assume that the uncertain data lies within ellipsoidal uncertainty set. We employ robust counterpart methodology to get the robust optimal solution.

Game-based analysis of energy-water nexus for identifying environmental impacts during Shale gas operations under stochastic input

Environmental issues have become some of the greatest challenges encountered across the life cycle Shale gas operations, and mostly involve the management, disposal, and spill of flowback and produced (FP) waters during the process of hydraulic fracturing. This study evaluates Shale gas resources, addresses water resource management problems, and identifies the corresponding environmental implications of FP waters under uncertainty. Multiple tools, including structural optimization, process design, cost analysis, environmental assessment, and stochastic technology, are integrated into a general modeling framework based on game theory. This mathematic framework corresponds to a dominant-subordinate-interactive problem, where two major participants are identified as the downstream decision maker at the dominant level (e.g., power generation sector) and the upstream decision maker at the subordinate level (e.g., Shale gas producer). The Monte Carlo technique is used for simulating the estimated ultimate recovery (EUR) of a single well. Thereafter, the developed model is applied to a special case study of the Marcellus Shale play in Beaver County, Pennsylvania. Multiple decisions regarding gas production, processing, water management, as well as electricity generation would been examined under different probability levels. Results indicate that the changes in violation levels would lead to distinct environmental and economic performances of the supply chain. A lower probability level of the EUR value would correspond to an increased reliability on fulfilling the system demands, and then to higher economic benefits and freshwater supply; conversely, a higher probability level of the EUR value would result in lower economic benefits and lower freshwater supply, and the risk of violating the EUR value would also increase.

Statistical Modeling of Monthly Rainfall in Selected Stations in Forest and Savannah Eco-climatic Regions of Nigeria

Objective: Nigerian agriculture is mainly rain-fed and highly dependent on weather especially rainfall. Therefore modeling of monthly rainfall in some selected stations in Nigeria was undertaken in this study. Methodology: Data (rainfall) spanning a period of 30 years (1981-2010) for fourteen stations which were collected from the Nigerian Meteorological Agency (NIMET) were utilized. Autoregressive Integrated Moving Average (ARIMA) and Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used. The accuracy and trend of time series was analyzed to give the monthly rainfall prediction for the succeeding year. The results showed that the model fitted into the data well and the stochastic seasonal fluctuation was successfully modeled. Rainfall was minimal in January, February, March and December over the selected stations in northern, Nigeria but increased progressively in strength and amount in the months of June, August and September over the stations in South west, and June and September over the stations in South -south, Nigeria. The highest rainfall of 230 mm was recorded in September over Warri and the lowest rainfall of 52 mm was recorded in August over Maiduguri. The rainfall recorded over the selected stations in South-south stations was visibly higher than what was recorded over the stations in the northern and the South-west stations. In northern Nigeria, the peak monthly mean rainfall amount of 91 mm was observed in August and rainfall amount was very low in January (0.0 mm), February (0.0 mm), March (0.0 mm) and December (0.0 mm). Over South-west, the Peak monthly mean rainfall amount of 215 mm was observed in June and September and rainfall amount was very low in January (0.0 mm) and December (0.0 mm). Over the stations in South-south, the Peak monthly mean rainfall amount of 325 mm was experienced on September and rainfall amount is very low in December (0.0 mm). Conclusion: The study concluded that Seasonal Autoregressive Integrated Moving Average (SARIMA) model was a proper method for modeling and predicting the monthly rainfall. The results are useful for forecasting the pattern of rainfall in the study area and provide information that would be helpful for decision makers in formulating policies to mitigate the problems of water resources management, soil erosion, flooding and drought.

Mathematical programming approach for optimal allocation in the wastewater management

Water is a valuable natural resource with very high importance, specifically in areas with water shortage. During the previous years, the limitations in water availability in various areas make the solution of water problems actually crucial and significant. The objective and the aims of the present work are: 1) to make a short review of the operations research methods that are used to solve water resources management problems; 2) proposed a new mathematical approach for solving allocation problem; 3) to examine the basic ideas and proposed solution with the help of the real life problem in the water resource management. More exactly, the basic idea of the project is the development and implementation of an optimisation model that selects the quantities of water to be supplied from various sources and the quantities of water to be allocated to various users with the condition that each water capacity allocated to each user in order to optimise the total water availability, taking into account priorities in the demand and use of the resource, as well as sustainability considerations.