Water Resources Problems Research Articles

River Suspended Sediment Prediction Using Various Multilayer Perceptron Neural Network Training Algorithms—A Case Study in Malaysia

Estimation of suspended sediment discharge in rivers has a vital role in dealing with water resources problems and hydraulic structures. In this study, a Multilayer Perceptron (MLP) feed forward neural network with four different training algorithms was used to predict the suspended sediment discharge of a river (Pari River at Silibin) in Peninsular Malaysia. The training algorithms are Gradient Descent (GD), Gradient Descent with Momentum (GDM), Scaled Conjugate Gradient (SCG), and Levenberg Marquardt (LM). Different statistical measures, time of convergence and number of epochs to reach the required accuracy were used to evaluate the performance of training algorithms. The analysis showed that SCG and LM performed better than GD and GDM. While the performance of the superior algorithms (i.e., SCG and LM) is similar, LM required considerably shorter time of convergence. It was concluded that both training algorithms SCG and LM could be recommended for suspended sediment prediction using MLP networks. However, LM was the faster (1/7 of SCG convergence time) of the two algorithms.

Markov Chain Models for Hydrological Drought Characteristics

Abstract Estimation of drought characteristics such as probabilities and return periods of droughts of various lengths is of major importance in drought forecast and management and in solving water resources problems related to water quality and navigation. This study aims at applying first- and second-order Markov chain models to dry and wet periods of annual streamflow series to reproduce the stochastic structure of hydrological droughts. Statistical evaluation of drought duration and intensity is usually carried out using runs analysis. First-order Markov chain model (MC1) for dry and wet periods is not adequate when autocorrelation of the original hydrological series is high. A second-order Markov chain model (MC2) is proposed to estimate the probabilities and return periods of droughts. Results of these models are compared with those of a simulation study assuming a lag-1 autoregressive [AR(1)] process widely used to model annual streamflows. Probability distribution and return periods of droughts of various lengths are estimated and compared with the results of MC1 and MC2 models using efficacy evaluation statistics. It is found that the MC2 model in general gives results that are in better agreement with simulation results as compared with the MC1 model. Skewness is found to have little effect on return periods except when autocorrelation is very high. MC1 and MC2 models are applied to droughts observed in some annual streamflow series, with the result that the MC2 model has a relatively good agreement considering the limited duration of the records.

Experimental and simulation study of a solar thermal driven membrane distillation desalination process

Being capable of directly utilizing solar thermal energy, the solar membrane distillation desalination system (SMDDS) has evolved as a promising green technology for alleviating the water resource problem. This paper reports the experimental and simulation study of a SMDDS which utilizes the air gap type membrane distillation. A laboratory system with automatic control function was established. A control scheme for fully automatic operation was designed using the PI (proportional–integral) control algorithm, which is robust and commonly employed by industries. The control structure adopted PI temperature control for the solar thermal and the membrane distillation subsystems. A dynamic mathematical model including the control algorithm for the overall system was developed, built on Aspen Custom Modeler® platform, and verified by the experimental results. The optimization analysis using the model reveals the operation strategy for maximum water production. Because of the unpredictable solar irradiation, the corresponding optimal dynamic operation cannot be pre-determined and implemented during system operation. However, the proposed PI control scheme could provide a fairly good level of performance, for example up to about 80% of the maximum water production for sunny day operation.

Nonlinear Analysis of Water Resources Awareness of Different Occupations in Heihe River Basin China

Based on sociological survey on the situation of water resources in Heihe River Basin China, using fractal theory, a nonlinear analysis of survey data was conducted according to different areas and different employments. A new concept, degree of water resources shortage (WRS), was introduced in this paper. We found that WRS had fractal charcateristics, and its fractal dimension (D) was a indicator to measure WRS, that is, the smaller the value of D, the higher the value of WRS. From upper reaches to lower reaches the change of WRS showes an exponential increase. D of farmer and herdsmen, office workers, cadres of the water sector was 0.3987, 0.72 and 0.4941 respectively. It showes that WRS of farmer and herdsmen is higest in all of sample. In order to solve the problem of water resources in Heihe River Basin, it is required to further enhance the people’s awareness of the water resources shortage.

The Current Situation and Sustainable Development of Water Resources in China

China is a water shortage country. The paper analyzes the current situation and problems of water resources in both urban and rural areas. To solve the problems, the paper puts forward five countermeasures and draws up structure chart. It shows specific contents and mutual relationships of each countermeasure clearly, and provides the basis for sustainable development of urban and rural water resources. It can be used in engineering practice effectively.

EPIC and APEX: Model Use, Calibration, and Validation

The Environmental Policy Integrated Climate (EPIC) and Agricultural Policy/Environmental eXtender (APEX) models have been developed to assess a wide variety of agricultural water resource, water quality, and other environmental problems. The EPIC model is designed to be applied at the field scale. APEX is a direct extension of EPIC that can also be applied to fields as well as to more complex multi-subarea landscapes, whole farms, and watersheds. This article describes key model components of EPIC and APEX, including different options for simulating surface runoff, evapotranspiration, soil erosion, and other processes. Field-scale calibration and validation procedures are then described for both models, with an emphasis on important calibration parameters and guidance regarding logical sequences of calibration steps. Additional calibration and validation guidance is further provided for applications of APEX at the landscape and watershed scales. Two calibration and validation case studies are presented: one for an EPIC plot study and one for an APEX study of a 35 ha field in north-central Missouri. Research and development needs for both models are also discussed.

Patterns in water quality on Canadian shores of Lake Ontario: Correspondence with proximity to land and level of urbanization

Spatially detailed surveys were conducted in 2008 over 97km of the Canadian coastline of Lake Ontario to describe patterns in water quality correlated with natural and anthropogenic features. Features of variability were used to infer lake-wide, regional, and location specific influences on nearshore water quality. Levels of solids, nutrients, major ions, Escherichia coli, and dissolved organic carbon were higher and more variable among tributary, embayment, and shoreside (0 to 1.2m depth) areas compared with the open nearshore (~3m depth to 5km offshore). A recurring pattern was a sharp drop in these features away from the shoreline with little or subtle decline beyond 1 to 3km into the nearshore. Conductivity and UV-induced fluorescence of organic material were used to detect discharges to the nearshore. Land-based influence on water quality was greatest in the urbanized Greater Toronto Area and the least over the less developed areas. Nearshore regions received inputs from the adjacent shoreline affecting water quality, the spatial extent of which was difficult to generalize, ranging from 10s of metres to several kilometres in breadth. Despite this, concentrations of total phosphorus, soluble reactive phosphorus, dissolved inorganic nitrogen, and silicate, when averaged over the entire nearshore, were typically similar to the open lake reflecting the broad distribution of the nearshore relative to the areas most influenced by adjacent lands. The development of environmental management to address water resource problems in the nearshore should proceed with awareness of the strong spatial dimensions that define nearshore water quality.

Polyvinyl Alcohol-Cellulose Acetate Composite Reverses Osmosis Membranes: I. Synthesis and Characterization

To overcome the high salinity water resources problem, reverse osmosis (RO) process is considered one of the most required techniques due to its high portable water quality produced. Optimization of membranes quality and function is still pursued and considered as of an important added value to the RO processes. In the present study, thin film PVA/CA+PEG membranes were prepared and the PVA layer was crosslinked by a varying maleic acid concentration at different reaction periods. The polymer composite is to be employed for the reverse osmosis process of brackish, saline and sea water purification. Optimization of reaction conditions and parameters such as salt rejection and water flux that affect on the membrane efficiency were verified. Structural and functional characterization of the PVA/CA composite membranes through Fourier Transform Infrared (FT-IR), thermogravimetric analysis (TGA), X-ray diffraction pattern, scanning electron microscopy (SEM), swelling behavior and membrane mechanical properties were monitored.

Performance of artificial neural network and regression techniques for simulation model in reservoir inter-relationships

In fact, the reservoir simulation is an essential step while developing the optimal operation policy for dam and reservoir. Generally, an accurate simulation for the reservoir characteristics should lead more reliable and robust optimization model for certain reservoir. The major challenge in the reservoir simulation is the non-linearity behavior of inter-relationships between the reservoir elevation, surface area and storage. The existing traditional modeling methods usually solve such problem in linear fashion, thus, it achieves relatively poor accurate simulation especially at extreme values, which affect the reliability of the optimization model. The use of artificial neural networks (ANNs) is becoming increasingly common in the analysis of hydrology and water resources problems and it may replace the classical regression model hitherto used most especially for non-linear system. Two different types of ANN namely, feed-forward back-propagation neural network (FBNN) and radial basis function neural network (RBFNN) were used in this study to simulate the inter-relationships between elevation, surface area and storage capacity at Langat reservoir system, Malaysia. In addition, classical auto regression (AR) model was developed for comparative analysis over the proposed ANN model. The main finding of this study showed that proposed ANN model could significantly improve the simulation accuracy over the classical AR mode. On the other hand, the results obtained for RBFNN were found to be more accurate than the simulation of AR and FBNN. This study thus concludes that the ANN method is more suitable to simulate the reservoir behavior than the classical regression model. Key words: Artificial neural network, elevation-storage, elevation-surface area, reservoir simulation.

Effects of model resolution on optimal design of subsurface flow and transport problems

Mathematical modeling of water resources problems is regularly undertaken to aid the management or design of a system. These optimal design problems can require a large number of model simulations with different sets of design variables. In an effort to reduce the computational expense of such design problems, various sources of error are typically introduced into the numerical model simulations, often without explicit consideration of subsequent effects on solution quality. We investigate several sources of such errors, including model formulation, grid resolution, and solver error for a set of community test problems, which have received attention in the literature as a vehicle to evaluate and evolve optimization methods. Results show that common shortcuts used to reduce computational effort can lead to inaccurate solutions that differ quantitatively and qualitatively from optimal solutions found using highly resolved methods. In addition to highlighting what we believe is a common issue, we present improved solutions to the problems considered, identify alternative model and optimization formulations that give equivalent accuracy with reduced computational effort, and provide guidance for improving generally the reliability of optimal design solutions to water resources problems.

The Design of Domestic Sewage Reuse System in Urban Residence and Analysis its Energy Conservation Utility

Faced with the increasingly serious problems of water resources, "China's economic and social development Twelfth Five-Year Plan" proposed to promote energy saving and emission reduction, the technical transformation of domestic water, and the utilization of recycled water. According to this, the paper mainly studies the city residential sewage reuse. First it analyzes the situation of China's urban water resources and feasibility of urban residence sewage reuse. Then through investigation and study, it divides the domestic sewage into three categories: namely, high-quality sewage, medium-quality sewage, and low-quality sewage, and for different types of sewage are treated in different ways. Key part of this paper is the domestic sewage reuse system design, this design reflects the characteristics of effective use of sewage resources and reduce energy consumption, possesses the environmental utility of saving water, reducing pollution and wastewater emissions. The purpose of this paper is effective use of domestic sewage, so as to achieve the environmental and social usefulness of energy saving and emission reduction.

Karst and artificial recharge: Theoretical and practical problems: A preliminary approach to artificial recharge assessment

Summary Managed Aquifer Recharge (MAR) is an emerging sustainable technique that has already generated successful results and is expected to solve many water resource problems, especially in semi-arid and arid zones. It is of great interest for karst aquifers that currently supply 20–25% of the world’s potable water, particularly in Mediterranean countries. However, the high heterogeneity in karst aquifers is too complex to be able to locate and describe them simply via field observations. Hence, as compared to projects in porous media, MAR is still marginal in karst aquifers. Accordingly, the present work presents a conceptual methodology for Aquifer Rechargeability Assessment in Karst – referred to as ARAK. The methodology was developed noting that artificial recharge in karst aquifers is considered an improbable challenge to solve since karst conduits may drain off recharge water without any significant storage, or recharge water may not be able to infiltrate. The aim of the ARAK method is to determine the ability of a given karst aquifer to be artificially recharged and managed, and the best sites for implementing artificial recharge from the surface. ARAK is based on multi-criteria indexation analysis modeled on karst vulnerability assessment methods. ARAK depends on four independent criteria, i.e. Epikarst, Rock, Infiltration and Karst. After dividing the karst domain into grids, these criteria are indexed using geological and topographic maps refined by field observations. ARAK applies a linear formula that computes the intrinsic rechargeability index based on the indexed map for every criterion, coupled with its attributed weighting rate. This index indicates the aptitude for recharging a given karst aquifer, as determined by studying its probability first on a regional scale for the whole karst aquifer, and then by characterizing the most favorable sites. Subsequently, for the selected sites, a technical and economic feasibility factor is applied, weighted by the difficulties that could occur when trying to undertake a recharge operation at a selected site from the surface. Each site is finally rated by its rechargeability index – the product of two factors, the intrinsic rechargeability and the feasibility index. ARAK was applied to the region of Damour, Lebanon, on the Mediterranean coast where uncontrolled exploitation of public and private wells led to its partial salinization by seawater. A MAR system in Damour region represents an interesting solution to cope with salinization and the insufficiency of the resource.

Group decision making on water resources based on analysis of individual rankings

In problems to do with managing water resources multiple decision makers are involved, each acting in their own right and using different value systems. In the literature on management science, several procedures are proposed in order to establish a collective preference based on the aggregation of different individual preferences. However, the well-known methods that focus on a single winner have some inconveniences that should be addressed. This paper is focused on a group decision making procedure based on the analysis of individual rankings with the aim of choosing an appropriate alternative for a water resources problem. This alternative is found to be the best compromise from the points of view of all actors involved in the decision problem. The structure of the method is set out as is its application to the water resources problem. A comparison with other methods is presented and discussed.

Treatment processes for contaminated aqueous media

Following the 2005 INCEED Conference held in Charlotte, North Carolina, USA, a number of candidate papers were submitted by authors for review and consideration for publication in this important Special Edition. Papers in both the technical note (short but important contributions) and full paper formats were considered. This special edition of The Environmentalist Journal focuses on the Treatment Processes for Contaminated Media as it relates to industrial and environmental applications. The contamination of aquifer has been a subject of great importance due to increased mining activities, improper discharge of spent fossil fuels, and the use of chemical fertilizers and pesticides in various agricultural activities. The different articles published in this special edition reflect the advancements that have been made to curb the deleterious effects of these aquatic contaminants. The proposed method of removing NOx through catalytic reduction plays a significant role in reducing acid rain. In agricultural practices, acid rain is a serious problem encountered in developing countries with no catalytic converters installed in exhausts of automobiles. The persistence of NOx in the atmosphere also impacts the air quality, which is important especially for people with respiratory problems. The mechanisms proposed in this study for NOx oxidation are vital in addressing these problems. The investigation involving the effect of white rot fungi on the remediation of anthracene-contaminated soil promises to prevent the eventual contamination of groundwater by this contaminant. The carcinogenic and teratogenic effects of anthracene have been well documented. It is found from this study that the fluctuating concentrations of anthracene in soil continues to decrease with the time and can be correlated with the secretion of ligninolytic enzymes by white rot fungi. Another investigation covered in this edition includes the application of membrane technology in groundwater purification. As shown in this study, the removal of excess fluoride from underground water can be successfully completed at a low cost. The proposed method of membrane technology can be applied to address the global problem of limited fresh water resources and the demand of improved water quality. In an associated study, the de-fluoridation of groundwater using magnesium oxide was investigated and indicated that this process can be applied in the removal of various contaminants from groundwater through combined precipitation. In the experimental investigation of electrokinetic extraction of lead from kaolinites, the results from the proposed models indicate that electrokinetic extraction can be applied in removing organic and inorganic contaminants from sediments and can be applied to real-time studies as well. In conclusion, I would like to thank the many reviewers that took out their time to help us with careful and detailed critical reviews of the papers submitted in this edition. I thank them also for all their comments and recommendations, which helped to improve the quality of the articles in this edition.

Invited perspective: Why I am an optimist

I address a range of topics that provide the sociopolitical‐technological setting for my professional life. I discuss some influential features of post–World War II world geopolitics, landmark technological developments of that era, and the resulting follow‐up technologies that have made it possible to approach various problems in hydrology and water resources. I next address societal needs that have driven developments in hydrology and water resources engineering and follow with a discussion of the modern foundations of our science and what I think are the principal issues in hydrology. I pose three community challenges that when accomplished should advance hydrologic science: data network needs for improving the water budgets at all scales, characterizing subsurface water flow paths, and the information archiving and mining needs from instruments that will generate substantially richer data detail than have been used for most hydrologic work to the present. I then discuss several hydrologic and water resource risk‐based decision issues that matter to society to illustrate how such risks have been addressed successfully in the past. I conclude with a long‐term community “grand challenge,” the coupled modeling of the ocean‐atmosphere‐landform hydrologic cycle for the purpose of long–lead time hydrologic prediction.

An improved Markov chain model based on autocorrelation and entropy techniques and its application to state prediction of water resources

According to the relationships among state transition probability matrixes with different step lengths, an improved Markov chain model based on autocorrelation and entropy techniques was introduced. In the improved Markov chain model, the state transition probability matrixes can be adjusted. The steps of the historical state of the event, which was significantly related to the future state of the event, were determined by the autocorrelation technique, and the impact weights of the event historical state on the event future state were determined by the entropy technique. The presented model was applied to predicting annual precipitation and annual runoff states, showing that the improved model is of higher precision than those existing Markov chain models, and the determination of the state transition probability matrixes and the weights is more reasonable. The physical concepts of the improved model are distinct, and its computation process is simple and direct, thus, the presented model is sufficiently general to be applicable to the prediction problems in hydrology and water resources.

Research on the Water Quality Monitoring System for Inland Lakes based on Remote Sensing

Abstract At present, the problem of water resources and environment especially on inland lakes has attracted increasingly attention of researchers. Remote Sensing technology have been widely used to monitor the water resources and environment with high-frequency, large-scale, multi-spectral characteristics. This paper presented a vision of the Water Quality Monitoring System for Inland Lakes (WQMSIL). The WQMSIL aims to reflect the trend of inland lakes environment quality by making full use of advantages of remote sensing data, combined with ground-based observation data. The WQMSIL provided a variety of information to reflect the problems of water quality of inland lakes and to make it convenient for the experts to make a further decision-making and the public to participation. In the paper, the design of the WQMSIL is presented including system requirements, system framework, system structure and system features. The WQMSIL will be tested contains three significant components. The improvement of the system in the future is also presented in the paper.

Dealing with many-objective problems in water resources planning and management

AbstractAmong the different difficulties plaguing the optimal planning and management of water resources, the presence of several and conflicting interests is one of the most intriguing, as this imposes to formulate multi-objective optimization problems, whose resolution yields to a set of Pareto efficient solutions. Both classical and evolutionary multi-objective optimization algorithms can efficiently deal with a reduced number of objectives (usually not more than three), while the majority of the real-world applications requires the designer to handle a much larger number of interests, leading to the so-called many-objective optimization problems. It is then common practice to simply reduce the dimensionality of the objective vector by removing the objectives considered to be redundant. To improve such approach, this study proposes to aggregate, rather than remove, the objectives in few variables, with respect to which the optimization problem is then solved. In particular, the aggregation is obtained via Non-negative Sparse Principal Component Analysis (NSPCA), a feature extraction technique that provides linear combinations of the objectives, while explaining the variance in the data with few combinations and imposing a non-negative constraint on the obtained coefficients. This novel method is demonstrated on a regional environmental planning problem, characterized by four conflicting objectives.

Experimental and simulation study of an air gap membrane distillation module with solar absorption function for desalination

Being capable of directly utilizing solar thermal energy, the solar driven membrane distillation desalination system has evolved as a promising technology for alleviating the energy and water resource problems. An innovative device for desalination, which is a hybrid of a solar collector and a membrane distillation, called SAF–AGMD (air gap membrane distillation with solar absorption function) is proposed. The experimental and simulation results are reported. The experimental results validate the feasibility of the design and the water production rate is enhanced by 2–8% compared to the simple AGMD module. The mathematic model takes into account the heat and mass transfers via correlations from the literature. The model is verified by the experimental data under different conditions, including the temperature and flow rate of inlet fluids, the air gap thickness and the solar radiation. The differences between the model predication and the experimental results are within 10%. The model is further incorpora...

Treatments of Precipitation Inputs to Hydrologic Models

Hydrologic models are used to assess many water resource problems, from agricultural use and water quality to engineering issues. This study shows how the combination of rain gauges (accurate at a point) and NEXRAD precipitation data (covering a wide area) can provide accurate, timely rainfall data that can drive the Soil and Water Assessment Tool (SWAT) model, which provides a more reliable tool for producers and policy-makers alike. The treatment of rainfall data was tested in the South Fork of the Iowa River, which covers about 788 km2 (194,720 ac) and is one of 15 benchmark watersheds of the USDA Conservation Effects Assessment Project (CEAP). The results show significant improvement in model predictions in which rainfall data were correctly modified. Gauge records with values for trace events performed better as data sources than records in which trace events were given zero value, even though the mean annual rainfall differed by <25 mm. The combination of rain gauge and NEXRAD data provided superior results even when the watershed included a sufficient spatial distribution of rain gauges. Of the six methods used to adjust gauge and NEXRAD data, inverse distance weighting or kriging with external drift predicted streamflow among the four gauges was the best among those tested. In the absence of rain gauge data, the simple adjustment of the NEXRAD estimates to match total rainfall amounts in the region resulted in adequate streamflow estimates. This finding is important because uncorrected NEXRAD precipitation values, although only 15% below annual precipitation values, resulted in a greater than 50% difference in streamflow estimates. The choice of rainfall treatment should be considered carefully to provide accurate model predictions.