RISK OF EXTREME EVENTS IN A MULTIOBJECTIVE FRAMEWORK1

ABSTRACT: This paper summarizes advances made in risk-based decisionmaking in water resources through use of the partitioned multiobjective risk method (PMRM). (Risk is a measure of the probability and severity of adverse effects.) In the PMRM, the risk of extreme events is differentiated from risk involving less extreme damage severity and is evaluated within a multiobjective framework. Study of the extreme-event risk function f₄(*) has addressed the following issues: methods for calculating f₄(*); the sensitivity of f₄(*) to various parameters, particularly to the partitioning point of the extreme-event range and the selection of probability density functions; insight provided by the statistics of extremes; and the impact of f₄(*) on risk management, for example, in the application of the PMRM to water resources problems. In particular, this paper shares with the reader recent research results on the PMRM, the relationship between the statistics of extremes and the conditional expected value, derived formulas for f₄(*), distribution-free estimates of f₄(*), documented case studies in dam safety, and future research directions.     

The Euler Number as an Index of Spatial Integrity of Landscapes: Evaluation and Proposed Improvement

The spatial integrity of a habitat or landscape is determined by the occurrence of habitat fragments and of perforations inside them. A landscape is said to have less spatial integrity with increasing numbers of fragments and perforations. The Euler number (ε) is a numerical measure of spatial integrity, based upon the difference |n _f −n _p | between the number of fragments (n _f ) and the number of perforations (n _p ). In this contribution, ε is evaluated, and an improvement is presented as a new index ε*, which is a combination of two metrics (ε _i , ε _d ) based on n _f and n _p . The term ε _i quantifies the intensity of perforation and/or fragmentation. The term ε _d measures the extent to which fragmentation predominates perforation, and vice versa. The intensity and dominance measures are combined into an Euclidean distance measure, generating the new ensemble value ε*, calculated as ε*= (n _f +n _p )⁻¹√[1 +n _f ²]. Use, sensitivity, and application of ε*, ε _i , and ε _d are illustrated using percolation maps. Application of the new metrics by environmental scientists is encouraged because (1) no negative values can be generated with ε*, ε _i , and ε _d ; (2) the range of ε*, ε _i , and ε _d is fixed; (3) process dominance and intensity are both assessed; (4) ε*, ε _i , and ε _d are easy to calculate and to interpret; and (5) ε* is not only based upon |n _f −n _p |, as ε is. Guidelines for practical use by means of a biplot of ε _i and ε _d are given.     

Improved SWAT Model Performance With Time-Dynamic Voronoi Tessellation of Climatic Input Data in Southern Africa1

Andersson, Jafet C.M., Alexander J.B. Zehnder, Bernhard Wehrli, and Hong Yang, 2012. Improved SWAT Model Performance with Time-Dynamic Voronoi Tessellation of Climatic Input Data in Southern Africa. Journal of the American Water Resources Association (JAWRA) 48(3): 480-493. DOI: 10.1111/j.1752-1688.2011.00627.x Abstract: In this study, we compared two approaches to obtain climatic time series for the Soil and Water Assessment Tool (SWAT), namely the conventional centroid method and time-dynamic Voronoi tessellation, and assessed the performance of SWAT in simulating discharge and smallholder maize yields in Southern Africa. Climatic time series were estimated with each method. The Voronoi method utilized all available precipitation and temperature data, but the centroid method used only 14.5 and 82.5%, respectively. After centroid processing, sub-basin time series were on average 42 and 63% incomplete, respectively. After Voronoi processing, all time series were complete. SWAT was fed with each climate dataset. Each model setup was independently calibrated and validated against discharge and maize yield. Similar model performance was obtained with both methods for yield. The root mean squared error during calibration was 0.26 and 0.27 t ha⁻¹ for the centroid and Voronoi methods, respectively (p-value: 0.80). However, daily discharge simulations improved significantly with the Voronoi method. The coefficient of determination increased from 0.24 to 0.39 in the calibration period (p-value: 9.6 × 10⁻¹³) and from 0.41 to 0.48 in the validation period (p-value: 3.1 × 10⁻³). The Voronoi method improved the simulation of the river flow regime. The largest improvements were obtained in data scarce situations, at high spatial and temporal resolution, and where the centroid method performed the worst.     

MULTICRITERION DECISION MAKING FOR FLOOD CONTROL OPERATIONS: THEORY AND APPLICATIONS1

ABSTRACT: Flood control operations are generally complex in nature, as they are often associated with a large quantity of uncertain factors in combination of noncommensurable criteria. It has been found that the use of fuzzy set theory coupled with multicriterion decision making (MCDM) methods is very promising. In this paper, a multicriterion fuzzy recognition model is established for flood control operations. A subjective preference and iterative weights method is proposed for weight assessment. First, an initial solution of criteria weights, which is directly analyzed from the selected alternatives, is obtained by using the proposed fuzzy recognition model. Then, according to their knowledge related to real time flood operations, operators may modify the initial weights if necessary. When the relative membership grades of alternatives belonging to all rankings are fixed, a defuzzification equation is used to calculate the rank feature value vector. Based on the rank feature value vector, one can evaluate the alternative set. Two flood operation cases are provided to illustrate the application of the proposed model. With the incorporation of the operator's knowledge related to flood operations, the proposed model is flexible in giving weights and realizes more practical flood control operations.     

Index of Alien Impact: A Method for Evaluating Potential Ecological Impact of Alien Plant Species

Alien plant species are stressors to ecosystems and indicators of reduced ecosystem integrity. The magnitude of the stress reflects not only the quantity of aliens present, but also the quality of their interactions with native ecosystems. We develop an Index of Alien Impact (IAI) to estimate the collective ecological impact of in situ alien species. IAI summarizes the frequency of occurrence and potential ecological impact (Invasiveness-Impact Score (I _i )) of individual alien species for all aliens present in a particular location or community type. A component metric, I _i , is based on ecological species traits (life history, ecological amplitude, and ability to alter ecosystem processes) that reflect mechanisms, which can increase impact to ecosystem structure and function. While I _i is less complex than some other multi-metric rankings of alien impact, it compares well to these metrics and to qualitative judgments. IAI can be adapted for different ecological settings by modifying the set of species traits incorporated in I _i to reflect properties likely to breach biotic and abiotic barriers or alter ecosystem function in a particular region or community type of interest. To demonstrate our approach, we created versions of IAI and I _i , applicable to the diverse streamside vegetation of a river basin (19,631 km²) spanning low-elevation arid to mesic montane habitats in eastern Oregon, USA. In this demonstration effort, we (1) evaluate relationships of IAI to metrics describing invasion level, and (2) illustrate the potential utility of IAI for prioritizing alien species management activities and informing restoration goals.     

The comparison of a revised Leopold matrix and fuzzy methods in environmental impact assessment,a case study: The construction of Al‐A'amiriya residential complex,Baghdad, Iraq

Environmental impact assessment (EIA) is an efficient method to recognize and alleviate the unfavorable and inevitable impacts of human activity on the environment. The EIA is dependent on expert opinions, which can be influenced by personal experience and knowledge. To evaluate this influence, we carried out EIA of 6,000 residential apartment units of Al‐A'amiriya, Baghdad, Iraq, using a revised Leopold matrix and fuzzy methods. The matrix results reflected the direct opinions of experts. The fuzzy method was developed according to the principles of expert comments. In the matrix method, the environmental impacts of each activity were evaluated by scores between −5 (very bad) to 5 (very good). The inputs to the fuzzy method were intensity and weather stability. The fuzzy estimation of the environmental impact was composed of a group of three values; P1 as the intensity, P2 as the extent, and P3 as the persistence. We gathered the expert opinions and used the Analytical Hierarchical Process to determine the weighting coefficient of each fuzzy anticipation. The matrix method was dependent on the expert opinions. The mean values of the matrix and P‐values in each column and row scores depict the impacts of a project on the environmental aspects and each element of construction on the environment. The comparison of the results indicated an average difference of 30% between the Leopold matrix and fuzzy methods. In regard to the availability and sufficiency of data, the difference was around 10%.     

Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection

The location selection for landfill municipal solid waste is an important issue in waste management. Selection of the optimal location requires consideration of multiple alternative solutions and evaluation factors because of system complexity. Further, ranking of the alternative locations and selection of the most optimal and efficient locations for landfill waste are an important multi-criteria decision-making problem. In this study, the candidate locations for landfill are determined based on Political, Economical, Environmental and Social factors are assessed through decision-makers’ opinion and by the methodology that incorporates fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). Specifically, the fuzzy AHP technique is applied to determine the weights of selected criteria impacting the location selection process, and the fuzzy AHP is adapted to model the linguistic vagueness and ambiguity, which can also be expressed as triangular fuzzy numbers. Furthermore, fuzzy TOPSIS technique is employed to rank the alternative locations. The applicability of this methodology is demonstrated by a case study of landfill waste location selection in the region of Casablanca, Morocco, and the results are compared with other techniques. Finally, to complete the treatment, a sensitivity analysis is performed to examine the impact of the preferences given by decision-makers to choose the best location.     

ANALYSIS OF A KARSTIC AQUIFER MANAGEMENT PROBLEM BY FUZZY COMPOSITE PROGRAMMING1

ABSTRACT: A multiple objective framework for water resources problems possessing uncertain or imprecise elements is provided using distance-based concepts, fuzzy set theory, and fuzzy arithmetic. The case of regional management of a karstic aquifer in Hungary in which six conflicting objectives and six alternatives have been identified illustrates the methodology The objectives are classified into three groups of two objectives each, namely: (1) environmental (aesthetics, thermal springs temperature), (2) economic (mining, tourism), and (3) water quality (nitrates, phosphates). Both environmental objectives are formulated under fuzziness, and all objectives are scaled using the extension principle. Fuzzy compromise programming (FCP-I) is then applied; here, all six objectives are entered in a single l_p norm measuring the distance between each alternative and an ideal point. Next, fuzzy composite programming (FCP-II) is developed; here, a trade off is first made within each group of objectives, and then an upper level trade-off takes place between the three groups. The fuzzy numbers describing each alternative as a result from applying these techniques are ranked to yield an ordering of the alternatives. The results of applying FCP.I, FCP-II, and two different ordering techniques are compared. The FCP-II technique appears to provide a relatively simple approach at hierarchical or multilevel multiple objective decision-making, where uncertainty is described by fuzziness. (KEY TERMS: compromise programming; fuzzy arithmetic; fuzzy sets; hierarchical criteria; karstic aquifer; l_p, norms; mining; multiple objectives; thermal springs.)     

Quality and sustainability in the production process: A study of bakeries using an integrated multi-criteria method based on fuzzy AHP and fuzzy TOPSIS

The objective of the present study is to evaluate, determine, and apply alternatives for improving the quality of the process and the product, with an emphasis on sustainable practices, using an integrated multi-criteria method. For this purpose, an analysis was conducted at a chain of bakeries, aiming to highlight bottlenecks in the production process and in the product. With the support of a literature review, four criteria and seven alternatives were defined to overcome these bottlenecks and, at the same time, contribute to the sustainability of the organization. For data analysis, six decision makers were interviewed and, following their evaluations, an integrated method based on fuzzy AHP and fuzzy TOPSIS was created. The fuzzy AHP was adopted to establish the importance of the criteria, while the fuzzy TOPSIS was used to evaluate and classify the alternatives developed to bypass the bottlenecks. The results revealed that of the criteria, Criterion “Cr1 – Quality” was prioritized. On the other hand, the alternative with the best performance was “A3 – Physical Layout Reorganization”. Applying this alternative, the study demonstrates the results achieved such as reduction of errors and accident risks, as well as greater fluidity in the productive space. the present study also makes theoretical and managerial contributions to the field, bringing the theory closer to the reality of companies that operate in the food sector.     

A multi-criteria decision analysis of solid waste treatment options in Pakistan: Lahore City—a case in point

Population of the world is increasing day by day, resulting in enormous amount of waste production. In the modern age of great technological advancements, there needs to be a systematic method to keep the environment clean. The waste management activities, i.e., collection, transport and disposal, pose a great challenge to the waste managers as they have to factor in various eclectic factors such as land availability, facilities available, budget, time required and the impact it would have on the environment, while tackling this problem. Lahore, despite being the most developed city of Pakistan, does not have a suitable solid waste management system. An increasing population leads to more waste generation, and in Lahore the situation is no different. Several waste management companies are working in the city, but as of yet they have not been able to make significant inroads to completely eradicate the problem. The aim of this paper is to suggest a suitable way for dealing with the waste. To accomplish this aim, a hierarchy-based model is used, considering six criteria and five alternatives. We used multi-criteria decision analysis to decide among different waste management alternatives. Forecasting has been used to find the population and waste produced over the years. Analytical hierarchy process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) are used to rank the feasible alternative. The results show that the population and waste were increasing drastically. Aerobic digestion was ranked as the best alternative for waste management according to AHP and TOPSIS, but there is great variation among the rank of other alternatives.     

Calibration and Validation of ADAPT and SWAT for Field‐Scale Runoff Prediction1

Abstract: The pollutant reduction possible with a given agricultural best‐management practice (BMP) is complex and site‐specific. Water‐quality models can evaluate BMPs, but model results are often limited by the lack of calibrated parameters for a given BMP. This study calibrated runoff prediction of two models (ADAPT and SWAT) for individual field plots having one till and two no‐till management practices. The factors used for runoff calibration were curve number II (CN_II) and saturated hydraulic conductivity (Ksat) for ADAPT, and CN_II, Ksat, and available water capacity for SWAT. Results were evaluated using coefficient of determination (R²), Nash‐Sutcliffe efficiency (E_f), root‐mean square error, median‐based E_f, and sign tests. Results indicated that for ADAPT, the best‐fit CN_II was 66 for the NT/SB (no‐till plot with surface‐broadcast fertilizer) treatment, 68 for the NT/DB (no‐till with deep‐banded fertilizer) treatment, and 70 for the tilled plot, whereas for SWAT the best‐fit CN_II was much higher, 86, for all treatments. Neither agreed with the textbook CN_II, 78, for sorghum in silty clay loam soil. The best‐fit model parameters for both runoff calibration phases had excellent correlation to monthly totals and moderate correlation to individual events.     

NONLINEAR PROGRAMMING IN RIVER BASIN MODELING1

ABSTRACT: This paper explores the use of nonlinear programming in river basin water quality modelling. Applications recently reported in the literature, along with the author's experience with nonlinear programming, are reviewed. Results obtained using nonlinear programming are compared with the results obtained by other researchers using linear and dynamic programming to solve river basin water quality optimization problems. These water quality models have objective functions with continuous first partial derivatives, several inequality and variable bound constraints, and are of the form: minizie Σ^j=n_j=1Y_j(X_j) subject to Σ^j=n_j=1a_ijX_jb_i, i=1,2, …, m c_jX_jd_j, j= 1,2, …, n The variable X_i is the maximum allowable ratio of the BOD (biochemical oxygen demand) of the effluent outflow to the BOD of the wastewater inflow for treatment plant j, in the range c_j to d_j. The a_ijd and b_i are constants in the DO (dissolved oxygen) and BOD constraints. The resuks show, given certain assumptions about the data, that nonlinear programming is a better solution method for these problems than is either linear programming or dynamic programming.     

A Hydrologic Drying Bias in Water‐Resource Impact Analyses of Anthropogenic Climate Change

For water‐resource planning, sensitivity of freshwater availability to anthropogenic climate change (ACC) often is analyzed with “offline” hydrologic models that use precipitation and potential evapotranspiration (E_p) as inputs. Because E_p is not a climate‐model output, an intermediary model of E_p must be introduced to connect the climate model to the hydrologic model. Several E_p methods are used. The suitability of each can be assessed by noting a credible E_p method for offline analyses should be able to reproduce climate models’ ACC‐driven changes in actual evapotranspiration in regions and seasons of negligible water stress (E_w). We quantified this ability for seven commonly used E_p methods and for a simple proportionality with available energy (“energy‐only” method). With the exception of the energy‐only method, all methods tend to overestimate substantially the increase in E_p associated with ACC. In an offline hydrologic model, the E_p‐change biases produce excessive increases in actual evapotranspiration (E), whether the system experiences water stress or not, and thence strong negative biases in runoff change, as compared to hydrologic fluxes in the driving climate models. The runoff biases are comparable in magnitude to the ACC‐induced runoff changes themselves. These results suggest future hydrologic drying (wetting) trends likely are being systematically and substantially overestimated (underestimated) in many water‐resource impact analyses.     

Possible Utilization of Silica Gel Sludge for the Removal of Phenol from Aqueous Solutions: Laboratory Studies

This paper discusses the adsorption capacity of silica gel sludge for phenol removal from aqueous solution. Kinetic experiments showed that phenol adsorption was completed after 2 h. Adsorption isotherms were measured for phenol from aqueous solution onto silica gel sludge under various pHs and temperatures. Results showed that the adsorption capacities for phenol was increased as pH decreased from 6.5 to 2. Temperature also was found to affect the adsorption isotherm. As temperature increases from 30 to 50°C, the adsorption capacity increases. The adsorption equilibrium of phenol on silica gel sludge was described by the linear Freundlich and Langmuir models. Furthermore, results showed that the isotherm parameters fit both linearized Langmuir and Freundlich adsorption isotherms. The Freundlich and Langmuir parameters at optimum pH was found as K _f=2.89, 1/n=0.23 and K _d=22.0, q _m=7.98, respectively. Whereas, for those at optimum temperature it was observed as K _f=2.87, 1/n=0.16 and K _d=20.93, q _m=7.91, respectively.     

Life cycle modelling of fossil fuel power generation with post-combustion CO2 capture

Due to its compatibility with the current energy infrastructures and the potential to reduce CO₂ emissions significantly, CO₂ capture and geological storage is recognised as one of the main options in the portfolio of greenhouse gas mitigation technologies being developed worldwide. The CO₂ capture technologies offer a number of alternatives, which involve different energy consumption rates and subsequent environmental impacts. While the main objective of this technology is to minimise the atmospheric greenhouse gas emissions, it is also important to ensure that CO₂ capture and storage does not aggravate other environmental concerns. This requires a holistic and system-wide environmental assessment rather than focusing on the greenhouse gases only. Life Cycle Assessment meets this criteria as it not only tracks energy and non-energy-related greenhouse gas releases but also tracks various other environmental releases, such as solid wastes, toxic substances and common air pollutants, as well as the consumption of other resources, such as water, minerals and land use. This paper presents the principles of the CO₂ capture and storage LCA model developed at Imperial College and uses the pulverised coal post-combustion capture example to demonstrate the methodology in detail. At first, the LCA models developed for the coal combustion system and the chemical absorption CO₂ capture system are presented together with examples of relevant model applications. Next, the two models are applied to a plant with post-combustion CO₂ capture, in order to compare the life cycle environmental performance of systems with and without CO₂ capture. The LCA results for the alternative post-combustion CO₂ capture methods (including MEA, K⁺/PZ, and KS-1) have shown that, compared to plants without capture, the alternative CO₂ capture methods can achieve approximately 80% reduction in global warming potential without a significant increase in other life cycle impact categories. The results have also shown that, of all the solvent options modelled, KS-1 performed the best in most impact categories.     

Woodlot scale: A method for rapid assessment of woodlot values

A method is described for the rapid survey and determination of the ecological value of woodlots. The three dominant tree species in a stand are given a visual ranking that is converted to awoodlot index through the use of species adaptation values. The woodlot index is scaled by presettlement vegetation type to yield awoodlot scale. The ecologically most valuable woodlots in a region are identified by using the woodlot scale and data on woodlot area, human disturbance, and tree density. The woodlot index corresponds closely to results from conventional methods of woodlot surveys. This method should be valuable to land-use planners for environmental impact assessment and regional planning.     

Determination of dissolved oxygen limitation in aerobic biofilm reactors

The concentration of dissolved oxygen (DO) strongly influences the performance of aerobic biofilm reactors because organic oxidation is limited by the availability of oxygen. However, it is not necessary to maintain a high DO level in the reactors in order to overcome this limitation. Excessive aeration wastes energy. Therefore, the determination of the onset of DO limitation against organic substrate removal in aerobic biofilm reactors is important for their effective operation. This study is aimed at developing an expression to determine the onset of DO limitation and hence to control the aeration system. The expression developed is as follows: , where S_b and C_b are the bulk concentrations of organic substrate and DO, respectively; D_ws and D_wc are the diffusion coefficients of organic substrate and oxygen in the reactors respectively; and R_b is an overall ratio of oxygen consumption to organic substrate removal in the reactors. The latter is the key parameter in the equation, and is determined by the characteristics of the substrate, biofilm, and reactor. In order to measure the value of R_b, the authors have developed a micro-biofilm reactor. The value of R_b was determined to be 0.13 (mg O₂ mg⁻¹ COD_cr) for glucose removal with this reactor. The equation has, subsequently, been verified with data from batch and continuous experiments.     

A quantitative method for accounting human opinion,preferences and perceptions in ecosystem management

Ecosystem management (EM) is a holistic approach, in which public participation in decision-making, and incorporation of human preferences, needs and perceptions in management plans is a main element. The decision-making from human opinion method (DeMHO), presented here, can be used in EM in selecting the more suitable and socially acceptable management plan, in order to protect or restore an ecosystem. The method focuses on the quantification of the human opinion, preferences and perceptions, which are investigated after research on the local population of the ecosystem. The results of this research are the inputs of the method; multi-criteria decision-making procedures, such as the analytic hierarchy process (AHP), the expected utility method (EUM) and compromise programming (CP) are used to assign the appropriate weights and rank according to their importance the interest groups, the issues to be studied, and the alternative management plans. The alternatives are also evaluated by assessing their sustainable character. The paper presents DeMHO and its application in the National Park of Eastern Macedonia and Thrace in Greece, after a research through a questionnaire on the local population.     

Using nighttime light data to estimate water evaporation inside buildings in China's urban areas

Urbanization has a great impact on urban evapotranspiration. Water evaporation inside buildings is an important part of urban water vapor resources and a crucial core of urban hydrological processes. The systematic studies on building water evaporation (BWE) are mostly the method of experimental monitoring. This study proposed a new method to simulate and estimate water evaporation flux inside buildings in urban areas. Based on the nighttime light data and urban per capita gross domestic product (GDP), a new modeling system was built to simulate the total BWE. Building area was calculated using the nighttime light data. And the BWE coefficient D_f was estimated according to the important indicator of economic development per capita GDP value. Then the water evaporation inside urban buildings and the spatial distribution of water evaporation inside buildings in typical cities could be obtained. The results showed that the total amount of water evaporation inside buildings in China's urban areas was 24.5 billion m³. Among the 31 provincial capitals in China, Shanghai had the largest BWE of 1.08 billion m³. The minimum water evaporation of buildings in Lhasa was 20.0 million m³. Studies of BWE can assess urban water budgets, support on-demand allocation of water resources, and provide a fundamental understanding of the relationship between water resources and energy heat island effects in urban areas.     

周至国家级自然保护区综合评价体系研究

根据周至国家级自然保护区的实际情况，从3个准则、24个基层指标因子出发，运用定性和定量相结合的德尔菲法、模糊数学法以及层次分析相结合的综合方法进行评价。其中，运用对称贴近度进行各个指标因子排序比较；运用非对称贴近度评价出生态质量、有效管理质量、社会经济价值分别处于较好、较差、较好水平，同时得出周至自然保护区综合水平较好。