Planning Of Water Resources Systems Research Articles

Evaluation of Carrying Capacity on Water Resources Based on Improved Water Footprint Method

A water footprint based principal component analysis method (WFPCA) has been proposed for evaluation of carrying capacity on water resources. The evaluation indexes can be defined based on the water footprint theory. Then the comprehensive evaluation value of water resources carrying capacity can be generated by the method of principal component analysis. The developed WFPCA method has been applied in the case study in Tongliao City, China. The results show that the indexes defined based on the water footprint theory can reflect the interactions between human being activities and water resources systems. The readjustment of water utilization structure affects the practical water use and the virtual water footprint in Tongliao City. The comparison of comprehensive evaluation values from 2010 to 2019 indicates that the water resources carrying capacity in Tongliao City continues to increase, which is benefited from the reasonable planning of water resources systems and the effective management of environment systems.

Uncertainties and risks in reservoir operations under changing hydroclimatic conditions

Abstract Uncertainties and risks associated with hydroclimatic variations pose a challenge to the management and planning of water resources systems. This study demonstrates the importance of understanding the changing hydrologic regime of the Feather River Basin (FRB) and its impacts on water resources decision variables (i.e., storage requirement and performance of a water supply reservoir). A simple storage–yield–reliability model (S–Y–R) is used to quantify the risk of the stationary-based designed reservoir under the temporal variation and nonstationarity in N-year blocks of the Feather River Inflow into Lake Oroville (FRI). Furthermore, the potential linkages of the long-term variability in the FRI to climate variations are investigated by applying wavelet spectrum and coherence analysis to the FRI and atmospheric–oceanic indices (e.g., ENSO and PDO). The results show substantial variations in the FRB hydrologic regime over different timescales with episodes of abrupt shifts toward significantly higher storage requirements, and decrease in the reservoir performance during historical periods of high FRI variance and lag-1 serial correlation. Although the mean inflows are high, the storage capacity is increased by (a) 38 and 48% due to the 5 and 20% increase in the FRI variance during the periods 1904–1953 and 1960–2009, respectively, and (b) 34% due to the increase in the serial correlation coefficient in the period of 1750–1799. Likewise, reservoir performance significantly decreased for the same reasons in the same critical periods. The reliability and resilience dropped to 74 and 29% (1904–1953) and to 76 and 50% (1960–2009 period) due to the increased variance of FRI, while vulnerability reached 70% during the high lag-1 correlations in 1532–1581 and 1564–1613, and 40% in 1904–1953 due to the high FRI variance. Furthermore, the wavelet coherence analysis observes strong associations between the streamflow and climate teleconnection patterns in specific periodic cycles during the same critical periods which link the variability in FRI and decision variables to the hydroclimatic variations. These linkages give a primary indication for the reservoir storage requirement characterization.

Impact of Scenario Selection on Robustness

AbstractMultiple plausible future scenarios are being used increasingly in preference to a single deterministic or probabilistic prediction of the future in the long‐term planning of water resources systems. These scenarios enable the determination of the robustness of a system—the consideration of performance across a range of plausible futures—and allow an assessment of which possible future system configurations result in a greater level of robustness. There are many approaches to selecting scenarios, and previous studies have observed that the choice of scenarios might affect the estimated robustness of the system. However, these observations have been anecdotal and qualitative. This paper develops a systematic, quantitative methodology for exploring the influence of scenario selection on the robustness and the ranking of decision alternatives. The methodology is illustrated on the Lake Problem. The quantitative results obtained confirm the qualitative observations of previous works, showing that the selection of scenarios is important, as it has a large influence on the robustness value calculated for each decision alternative. However, we show that it has a relatively small influence on how those decision alternatives are ranked. This implies that despite the difference in robustness values, similar decision outcomes will be reached in this case study, regardless of the basis on which the scenarios are obtained. It is also revealed that the impact of the scenarios on the robustness values is due to complex interactions with the system model and robustness metrics.

Analysis of the Spatial Characteristics of the Water Usage Patterns Based on ESDA-GIS: An Example of Hubei Province, China

The spatial characteristics and the high-duty water regions of the Water Usage Patterns (WUP) are very important for the allocation and management of water resources. Taken Hubei province, China as an example, we adopted the exploratory spatial data analysis (ESDA) method to investigate the spatial dependence and local patterns of the WUP from 2003 to 2012. Subsequently, the spatial variation mechanisms were analyzed through the gravity center model. The results indicated that the overall spatial dependence of the agricultural WUP was detected (more significant after 2008). Moreover, the global spatial autocorrelation analysis results on the domestic WUP showed statistical significance (Moran’s I > 0.1, P < 0.05). These indicated that the local patterns were presented. The high values clustering areas of the agricultural and domestic WUP were mainly distributed in the central province and in the western province respectively. However, the approximate random distribution was identified for the industrial WUP because the industrial development had been conducted widely in the whole province during these years. Furthermore, the governmental policies and natural environment contributed to the spatial evolution tendency of the WUP. An increasing trend of the spatial association of the agricultural WUP and a significant decreasing trend of that of the domestic WUP, which suggested that the natural circumstance superiority and the industrial structure adjustment related to water utilization has been utilized and implemented effectively. This study can provide a useful reference and guidance for scientific planning of water resource systems.

Water Resources Optimization Method in the Context of Climate Change

AbstractThis paper describes a method for water resources optimization in the context of climate change. The method takes into account the midterm variability or seasonality of inflows as well as the uncertainty in the climate change and resulting flows. The objective of the optimization algorithm is to find a compromise between the long-term planning of water resources systems and the midterm operations for optimum hydropower production. The proposed algorithm consists of the midterm dynamic programming formulation coupled with the use of the expected value of the cost-to-go function between two consecutive long-term periods. Future climate projections and transition probabilities between projections represent the stochastic nature of inflows and the nonstationarity of climate. The performance of the method was evaluated through the simulation of inflow projections for the Manicouagan River basin in Quebec, Canada. The results showed that the algorithm was able to adapt the operating policy to the climat...

Evaluate the Performance of stochastic models in Generating Monthly Discharges for the Rivers in North of Iraq

The data of monthly discharge which are available for most of the rivers in the north of Iraq have a short recorded period ,which has a great influence in the design and planning of water resources systems , where this short recorded not contain a critical and extreme flows sample of the low flow sequences. Two stochastic models , bivariate "Thomas & Fiering" model and multi-side "matalas" model were used for generating time series for(100) years for the lower Zab and Diyala river at upstream of Dokan Dam and Derbendekhan Dam using the available recorded data for the period (1962-1997) . From application of different statistical tests (Kolmogrov–Smirnov), Chi-Square (X2), Root Mean Square Error (RMSE), Mean Absolute Error (MAE, Z), found that "Matalas" model is more performance than the bivariate model, "Thomas & Fiering" generate time series for both rivers, so it can be concluded that the "Matalas" model can be proposed to be used for generating the flow series for the different rivers in the northern Iraq. Key Words: Time Serious for monthly discharge, Stochastic Models , bivariate "Thomas & Fiering" model, "Matalas" model, Statistical Tests

Drought Analysis Based on a Marked Cluster Poisson Model

Abstract This paper presents an operational definition of drought events based on an “excess over threshold” approach applied on rainfall series and develops a stochastic model for describing droughts defined in that way. The model consists of a Poisson cluster process to represent drought occurrence and a marked process composed of three series of random variables (duration, deficit, and maximum intensity) to describe drought severity; it is theoretically justified, and adequate procedures to check its validity are suggested and applied on five Spanish rainfall series. Useful parameters for the design and planning of water resource systems, together with their confidence intervals, are estimated from the model.

ITOM: an interval-parameter two-stage optimization model for stochastic planning of water resources systems

Planning of water resources systems is often associated with many uncertain parameters and their interrelationships are complicated. Stochastic planning of water resources systems is vital under changing climate and increasing water scarcity. This study proposes an interval-parameter two-stage optimization model (ITOM) for water resources planning in an agricultural system under uncertainty. Compared with other optimization techniques, the proposed modeling approach offers two advantages: first, it provides a linkage to pre-defined water policies, and; second, it reflects uncertainties expressed as probability distributions and discrete intervals. The ITOM is applied to a case study of irrigation planning. Reasonable solutions are obtained, and a variety of decision alternatives are generated under different combinations of water shortages. It provides desired water-allocation patterns with respect to maximum system benefits and highest feasibility. Moreover, the modeling results indicate that an optimistic water policy corresponding to higher agricultural income may be subject to a higher risk of system-failure penalties; while, a too conservative policy may lead to wastage of irrigation supplies.

A stochastic rainfall model for the assessment of regional water resource systems under changed climatic condition

Abstract. A stochastic model is developed for the synthesis of daily precipitation using conditioning by weather types. Daily precipitation statistics at multiple sites within the region of Yorkshire, UK, are linked to objective Lamb weather types (LWTs) and used to split the region into three distinct precipitation sub-regions. Using a variance minimisation criterion, the 27 LWTs are clustered into three physically realistic groups or ‘states'. A semi-Markov chain model is used to synthesise long sequences of weather states, maintaining the observed persistence and transition probabilities. The Neyman-Scott Rectangular Pulses (NSRP) model is then fitted for each weather state, using a defined summer and winter period. The combined model reproduces key aspects of the historic precipitation regime at temporal resolutions down to the hourly level. Long synthetic precipitation series are useful in the sensitivity analysis of water resource systems under current and changed climatic conditions. This methodology enables investigation of the impact of variations in weather type persistence or frequency. In addition, rainfall model statistics can be altered to simulate instances of increased intensity or proportion of dry days for example, for individual weather groups. The input of such data into a water resource model, simulating potential atmospheric circulation changes, will provide a valuable tool for future planning of water resource systems. The ability of the model to operate at an hourly level also allows its use in a wider range of hydrological impact studies, e.g. variations in river flows, flood risk estimation etc. Keywords: water resources; climate change; impacts; stochastic rainfall model; Lamb weather types

Hydrological Forecasting Using Neural Networks

Operational planning of water resources systems like reservoirs and power plants calls for real-time or on-line forecasting of runoff and river stage. Most of the real-time forecasting models used in the past are of the distributed type, where the forecasts are made at several locations within a catchment area. In situations where the information is needed only at specific sites in a river basin, and needs to be more accurate, the time and effort required in developing and implementing such complicated models may not be justified. Simpler neural network (NN) forecasts may therefore seem attractive as an alternative. The present study demonstrates the application of NNs to real-time forecasting of hourly flood runoff and daily river stage, as well as to the prediction of rainfall sufficiency for India. The study showed the capability of NNs in all of these applications. In many situations they performed better than the statistical models.

Potential of Modern Data Types for Future Water Resources Management

Presently a change of paradigm in the field of planning and operation of water management schemes can be observed. The introduction of the principle of sustainable development by the United Nations and the principle of integrated river basin management postulated by the European Union play a major role in this context. Introduction of these new principles requires development of new planning tools, which in turn require a much better data basis than available hitherto. This paper deals with new data types already partly available now, partly to be expected to be developed in the medium-range future. The present data situation is discussed, along with the obvious deficits of conventional data. New data types will not be limited to point measurements, but rather must comprise information covering large areas with a higher resolution in time and space than presently available. Remote sensing data will play a more important role in the future. Furthermore, digital maps, digital elevation models, etc. are also of growing importance and will be processed, together with remote sensing and other data, within Geographical Information Systems of future generations also exposing the potential for working with multi-temporal imagery. In the paper it is shown that in the future more accurate data will be available, not only in terms of data quality, but also resolution in time and space. It is shown how the new types of hydrometeorological data postulate new types of hydrological models. Here, distributed system models are of growing importance. Furthermore, it is shown how the combination of remote sensing with other information leads to new data types that allow integrated planning of water resources systems. The potential of real time data is highlighted, particularly in the context of real time operation of water resources systems, especially for flood control. The potential of large-scale data schemes in the context of regional and continental water management schemes is discussed. Global atmospheric models coupled to hydrological models are discussed, and their potential to consider long-distance effects of certain phenomena (e.g., El Niño) are mentioned. For sustainable development of water resources, the potential of long-term data prediction scenarios is evaluated, and an example of this principle for planning future water supply systems is presented. The paper ends with a vision of future developments in planning water management schemes on the basis of new data types

The Value of Considering Autocorrelation Between Inflows in the Stochastic Planning of Water Resource Systems

Reliability programming formulations offer a family ofexplicit stochastic models for planning the operationof complex water resources systems. These models usecumulative probability distributions of the sum ofinflows to characterize their variability in theplanning period. Applicability of these models for avariety of problems has been limited, mainly due tothe assumption of independence between inflows indifferent time periods that leads to the derivation ofconservative operating policies. This paper presentsthree new approaches to overcome this limitation. Theperformance of the proposed approaches is demonstratedthrough comparison of the operating policies derivedfrom these approaches and the Independent Approach. Operational planning of the Manitoba Hydro energygeneration system, a predominantly hydro-based utilitycompany in Manitoba (Canada), is used as the case study.

An interactive inexact-fuzzy approach for multiobjective planning of water resource systems

In this study, an inexact fuzzy multiobjective programming (IFMOP) method is developed and applied to a case study of water pollution control planning in the Lake Erhai Basin. The IFMOP improves upon the existing multiobjective programming methods with advantages in data availability, solution algorithm, computational requirement and result interpretation. The case study project was supported by the United Nations Environment Programme (UNEP). The results indicate that desired schemes for a number of system activities in different subareas/periods were obtained. Inheriting uncertain natures of the model inputs, the majority of solutions present as inexact values which provide decision-makers with a flexible decision space. Generally, the modeling results would provide scientific bases for the formulation of policies/strategies regarding regional socio-economic development and environmental protection.

An interactive inexact-fuzzy approach for multiobjective planning of water resource systems

In this study, an inexact fuzzy multiobjective programming (IFMOP) method is developed and applied to a case study of water pollution control planning in the Lake Erhai Basin. The IFMOP improves upon the existing multiobjective programming methods with advantages in data availability, solution algorithm, computational requirement and result interpretation. The case study project was supported by the United Nations Environment Programme (UNEP). The results indicate that desired schemes for a number of system activities in different subareas/periods were obtained. Inheriting uncertain natures of the model inputs, the majority of solutions present as inexact values which provide decision-makers with a flexible decision space. Generally, the modeling results would provide scientific bases for the formulation of policies/strategies regarding regional socio-economic development and environmental protection.

Reliability constrained capacity expansion planning of water resource systems

Two questionable features of many existing studies of capacity expansion planning problems in water resources are (1) the modelling of the expansion as a deterministic process, and (2) the lack of control over the incidence of system failure. System failure, in this presentation, is related to the occurrence of shortfalls in water supply. A sequential decision model is used as a general framework for the formulation of stochastic demand capacity expansion problems subject to reliability constraints designed to regulate the incidence of system failure. Various different types of constraint are investigated and each is incorporated into a dynamic programming solution procedure by means of Lagrangian theory. Computational examples illustrate the potential importance of using such reliability constraints in the analysis of capacity expansion problems.

Broad horizons in water resource planning and investment

In spite of vastly expanded knowledge and computational abilities available in the planning of water resource systems, the scope of most planning efforts remains too narrow. It is argued that planning efforts must be broadened in three ways; (1) geographically, to take into account not just hydrologic interdependencies but the wider range of market and financial relationships; (2) between public and private sectors, to assure that public investments yield sufficiently high returns; (3) to encompass all relevant alternatives, both technological and institutional, for attaining the objectives of development. Examples are given from various water resource areas of the costs of failing to use sufficiently broad horizons in planning.

Field level planning of water resource systems

Comprehensive water resource planning formulates optimal programs, largely investment programs, in a systems context through use of principles of production and allocation economics and operations research. The planning problem entails maximization of an objective function, subject to constraints and to the production function. System design consists of derivation of three fundamental relationships—the cost‐input, benefit‐output, and output‐input functions—and their application to the system under study. The process of system design at field level consists of three major elements: preparation for planning; performance of basic physical, economic, and social studies; and formulating system designs, which in turn involves preliminary screening of development alternatives and detailed systems analysis of the alternatives that survive the screening. Major new techniques of analysis, typically computer oriented, include (1) optimal scheduling methods for the planning task, such as the Critical Path Method and its variants; (2) regional input‐output analysis to derive regional economic projections; (3) improved theoretical models and practical methods of data analysis for deriving benefit‐output functions, including those for flood prevention, outdoor recreation, and domestic and industrial water supply; (4) models for generating synthetic streamflow sequences and stochastic storage‐yield functions; (5) linear programming and rough simulation techniques for preliminary screening of development alternatives; and (6) detailed simulation analyses and response‐surface sampling for derivation and study of final system designs. Some of the new techniques can be used feasibly in current planning; others require further development and testing before they can be put to practical use.