Applied Drought Modeling, Prediction, and Mitigation

 
 
Elsevier (Verlag)
  • 1. Auflage
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  • erschienen am 3. August 2015
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  • 484 Seiten
 
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978-0-12-802422-5 (ISBN)
 

Applied Drought Modelling, Prediction, and Mitigation provides a practical guide to new and recent methodologies for drought characterizations, change modeling, down-scaling, and future predictions.

The modeling procedures covered by the book include recent advancements in regional drought extent, coverage, intensity, and water deficit predictions, which are increasingly significant given current climate change impacts on water resources.

Each modeling procedure is explained theoretically prior to the mathematical derivation, and includes book examples, exercises, and case studies that supplement the applied and practical material, thus making the approaches accessible and applicable to the reader.


  • Presents new and recent methodologies for drought characterizations, change modeling, down-scaling, and future predictions
  • Includes online modeling tools to help readers quickly solve drought related problems
  • Presents methodologies, including drought features (duration, intensity, and magnitude) at any desired risk level
  • Include case studies from arid and semi-arid regions


Dr. Zekai Sen obtained his B. Sc. and M. Sc Degrees from the Technical University of ?stanbul, Civil Engineering Faculty, in 1972. His post-graduate studies were carried out at the University of London, Imperial College of Science and Technology. He was granted a Diploma of Imperial College (DIC) in 1972, M. Sc. in Engineering Hydrology in 1973 and his Ph. D. in stochastic hydrology in 1974. He worked in different countries such as England, Norway, Saudi Arabia and Turkey. He worked in different universities such as the King Abdulaziz University, Faculty of Earth Sciences, Hydrogeology Department; Istanbul Technical University, Faculty of Astronautics and Aeronautics, Meteorology Department. His main interests are hydrology, water resources, hydrogeology, atmospheric sciences, hydrometeorology, hydraulics, science philosophy and history. He has published about 230 SCI scientific papers in different international top journals and has seven book publications, including the forthcoming Practical and Applied Hydrogeology (2014).
  • Englisch
  • USA
Elsevier Science
  • 14,19 MB
978-0-12-802422-5 (9780128024225)
0128024224 (0128024224)
weitere Ausgaben werden ermittelt
  • Front Cover
  • Applied Drought Modeling, Prediction, and Mitigation
  • Copyright
  • Table of Contents
  • Dedication
  • Preface
  • Chapter One: Introduction
  • 1.1. General
  • 1.2. Historical View
  • 1.3. Atmospheric Composition and Drought
  • 1.4. Drought Definitions
  • 1.5. Droughts, Aridity, and Desertification
  • 1.6. Drought Impacts
  • 1.7. Drought Regions
  • 1.8. Drought Types and Their Impacts
  • 1.8.1. Meteorological Drought
  • 1.8.2. Hydrological Drought
  • 1.8.3. Agricultural Drought
  • 1.8.4. Socioeconomic Drought
  • 1.8.5. Famine
  • 1.8.6. Water Shortages and Effects
  • 1.9. Significant Drought Mitigation Points
  • References
  • Chapter Two: Basic Drought Indicators
  • 2.1. General
  • 2.2. Simple Drought Indicators
  • 2.3. Palmer Drought Indicators
  • 2.3.1. Palmer Drought Severity Index
  • 2.3.2. Palmer Hydrological Drought Index
  • 2.4. Surface Water Supply Index
  • 2.5. Percent of Normal Indicator
  • 2.6. Decile Indicator
  • 2.7. Crop Moisture Index
  • 2.8. Erinç Drought Indicator
  • 2.9. Water Balance Indicators
  • 2.10. Köppen Drought Indicator and Modifications
  • 2.11. Martonne Drought Indicator
  • 2.12. Budyko-Lettau Drought Ratio Indicator
  • 2.13. Aridity Index (AI)
  • 2.14. Standardized Precipitation Index
  • 2.14.1. Pros and Cons of SPI
  • 2.15. Typical Problems with Indicators and Triggers
  • 2.16. Percentiles for Drought Indicators and Triggers
  • 2.17. Triple Drought Indicator
  • 2.18. Fuzzy Logic Approach
  • 2.19. Continuity Curve
  • References
  • Chapter Three: Temporal Drought Analysis and Modeling
  • General
  • Numerical Definition of Droughts
  • The Threshold Level Method
  • Drought Forecasting
  • Drought Models
  • Drought Features
  • Temporal Drought Modeling Methodologies
  • First Order Markov Process Drought Properties
  • Drought Duration Statistical Properties
  • Critical Drought Duration Statistical Properties
  • Maximum Deficit Summation
  • Dependent Process Maximum Total Deficit
  • Critical Drought Duration
  • Enumeration Model of Independent Bernoulli Trials
  • Dependent Bernoulli Trials
  • Second-Order Markov Process Drought Properties
  • Seasonal Bernoulli Trials
  • Analytical Derivation of Longest Run-Length
  • Crossing Probabilities
  • Identically and Independently Distributed Variables
  • Unidentically and Independently Distributed Variables
  • Annual Flow Totals
  • Independent Processes
  • Normally Distributed Processes
  • Logarithmic Normally Distributed Processes
  • Drought Features Software
  • Independent Bernoulli Trials Software
  • Dependent Bernoulli Trials Software
  • Identically and Independently Distributed Variable Software
  • Un-Identically and Independently Distributed Variable Software
  • References
  • Chapter Four: Regional Drought Analysis and Modeling
  • 4.1. General
  • 4.2. Regional Numerical Definition of Droughts
  • 4.3. Techniques to Predict Regional Droughts
  • 4.3.1. Statistical Regression
  • 4.3.2. Time Series Analysis
  • 4.3.3. Pattern Recognition
  • 4.3.4. Linear Discriminant and Nearest Neighbor Analysis
  • 4.3.5. Stochastic or Probabilistic Analysis
  • 4.4. Regional Drought Features
  • 4.5. Random Drought Coverage Areas
  • 4.5.1. Regional Drought Descriptor Definitions
  • 4.6. Analytical Formulation
  • 4.7. Total Areal Deficit (D)
  • 4.8. Maximum Deficit Intensity (Id)
  • 4.9. Areal Joint Drought PDF
  • 4.10. Rainy and Nonrainy Days
  • 4.10.1. Daily Rainfall Data Statistics
  • 4.10.2. Temporal Variation
  • 4.10.3. Spatial Variation
  • 4.11. Double-Logarithmic Method for Determination of Monthly Wet and Dry Periods
  • 4.12. Power Law in Describing Temporal and Spatial Precipitation Pattern
  • 4.12.1. Description of Data Preparation
  • 4.12.2. Methodology
  • 4.12.3. Graphical Analysis of Numbers of Wet and Dry Months
  • Appendix4.1. Areal Maximum Probability Coverages
  • Appendix4.2. Total Areal Deficit
  • References
  • Chapter Five: Spatiotemporal Drought Analysis and Modeling
  • 5.1. General
  • 5.2. Spatiotemporal Drought Models
  • 5.2.1. Persistent Regional Drought Model
  • 5.2.2. Multiseasonal Regional Drought Model
  • 5.2.3. Drought Parameters
  • 5.3. Drought Spatiotemporal Modeling
  • 5.3.1. Multivariate Runs
  • 5.3.1.1. Distribution of n-Fold Run-Length
  • 5.3.1.1.1. n Series Serially and Mutually lndependent
  • 5.3.1.1.1.1. Run-Sums
  • 5.3.1.1.2. n Series Serially lndependent but Mutually Dependent
  • 5.3.1.1.3. n Series Serially Dependent but Mutually lndependent
  • 5.3.1.1.4. n Series Serially and Mutually Dependent
  • 5.4. Regional Wet and Dry Spell Analysis With Heterogeneous Probability Occurrences
  • 5.4.1. Dry and Wet Spell Features
  • 5.4.2. Regional Models
  • 5.4.3. Regional Persistence Model
  • 5.4.4. Multiseasonal Model
  • 5.5. Areal Precipitation Coverage Probability From a Set of Heterogeneous Point Probability
  • 5.5.1. Definitions of Basic Probabilities
  • 5.5.2. Theoretical Treatment
  • 5.5.3. Numerical Applications
  • Appendix5.1. Heterogeneous Regional Binomial PDF Calculation Software
  • References
  • Chapter Six: Climate Change, Droughts, and Water Resources
  • 6.1. General
  • 6.2. Basic Definitions and Concepts
  • 6.3. Atmospheric Composition and Pollution
  • 6.3.1. Natural Chemical and Hydrological Cycles
  • 6.4. Climate Belt Shifts Simple Model
  • 6.5. Adapting to Climate Change
  • 6.6. Drought Disasters
  • 6.7. Desertification and Climate Change
  • 6.7.1. General Approach to Desertification Problem
  • 6.7.2. Drought and Climate Change
  • 6.7.3. Water Resources, Climate Change, and Drought
  • 6.8. Climate Models
  • 6.8.1. Downscaling Methodology
  • 6.8.2. Application for the AP
  • 6.8.2.1. Quadrangle Downscaling Methodology
  • 6.9. Climate Change and Major Cities
  • 6.9.1. Istanbul Water Consensus
  • 6.9.2. Methodology
  • 6.9.3. Applications
  • 6.10. Climate Change and Water Resources
  • 6.10.1. Climate Impacts on Water Supplies
  • 6.10.2. Climate Impacts on Water Demand
  • 6.11. Global Warming Threat on Water Resources
  • 6.11.1. Effect of Climate Change on Water Availability
  • 6.11.2. Effect of Climate Change on Extremes
  • 6.11.3. Effect of Climate Change on Groundwater Recharge
  • 6.11.3.1. Groundwater Recharge
  • 6.11.4. Climate Change and Engineering Systems
  • 6.12. Some Recommendations
  • References
  • Chapter Seven: Drought Hazard Mitigation and Risk
  • 7.1. General
  • 7.2. Basic Definitions
  • 7.3. Goals and Objectives
  • 7.3.1. Policies, Strategies, and Tools
  • 7.4. Drought Watches Systems and Relief
  • 7.4.1. Early Warning System
  • 7.5. Drought Mitigation Planning History and Objectives
  • 7.5.1. Drought Mitigation
  • 7.6. Vulnerability Management
  • 7.6.1. Water Resources Management
  • 7.6.1.1. Engineering Structures and Management
  • 7.6.2. Water Harvesting and Management
  • 7.6.3. Safe Yield Management
  • 7.7. Risk Analysis Management
  • 7.8. Disaster Management
  • 7.9. Droughts Risk Calculation Methodology
  • 7.9.1. Probabilistic Risk and Safety Calculations
  • 7.9.1.1. Dependent and Independent Processes
  • 7.9.1.2. Return Period and Risk
  • 7.10. Drought Duration-Safety Curves
  • 7.11. Weather Modification
  • 7.11.1. Frequency Double Ratio Method
  • References
  • Index
Chapter Two

Basic Drought Indicators


Abstract


Droughts need to be described not only linguistically but for applications their numerical preliminary quantifications are necessary for classification purposes. In general droughts are classified as incipent, mild, moderate, severe, and extreme according to which the necessary precautions can be taken for the least damage on the social activities. The core of this chapter is concerned with different drought descriptors as indices, including the most widely used alternatives such as Palmer, surface water supply, water balance, aridity, standardized precipitation, triple drought, and fuzzy logic indices. In general, each one of these simply formulated indicators describes the magnitude, duration, severity, or spatial coverage extent of drought. Almost all of them are based on meteorological and hydrological variables, such as precipitation, especially rainfall, temperature, streamflow, soil moisture, reservoir storage, and groundwater level. Several of them can be synthesized into a single indicator on a quantitative scale, often called a drought index. Although drought indices can provide ease of implementation, the scientific and operational meaning of an index value may raise questions, such as how each indicator is combined or weighted for an overall index derivation and how an arbitrary index value relates to hydrometeorological and statistical characteristics of droughts. Such questions are answered through the application of probabilistic and statistical procedures. The benefits and drawbacks of each index are presented comparatively with their convenient applications in drought areas.

Keywords

Aridity

Fuzzy

Index

Palmer

Probability

Standardized precipitation

Statistics

Triple drought

Water balance

Chapter Outline

2.1 General   43

2.2 Simple Drought Indicators   45

2.3 Palmer Drought Indicators   50

2.3.1 Palmer Drought Severity Index   52

2.3.2 Palmer Hydrological Drought Index   59

2.4 Surface Water Supply Index   60

2.5 Percent of Normal Indicator   62

2.6 Decile Indicator   66

2.7 Crop Moisture Index   68

2.8 Erinç Drought Indicator   69

2.9 Water Balance Indicators   69

2.10 Köppen Drought Indicator and Modifications   70

2.11 Martonne Drought Indicator   71

2.12 Budyko-Lettau Drought Ratio Indicator   73

2.13 Aridity Index (AI)   74

2.14 Standardized Precipitation Index   76

2.14.1 Pros and Cons of SPI   82

2.15 Typical Problems with Indicators and Triggers   86

2.16 Percentiles for Drought Indicators and Triggers   88

2.17 Triple Drought Indicator   90

2.18 Fuzzy Logic Approach   96

2.19 Continuity Curve   100

References   102

2.1 General


The causes of major droughts begin with anomalies of less precipitation than normal in the weather or climate conditions that may affect hydropower generation and water demand for agricultural and industrial activities. Such natural phenomena can be assessed effectively if simple and practical formulations are available. Complicated models, procedures, and approaches may lead to finer resolutions of drought problems, but readily available direct verbal guidance or numerical indicators together with their corresponding verbal information are more desirable for practical applications. Droughts, among the most extreme natural events that affect society and the environment at large, can be dealt with initially via simple observations, calculations, and procedures.

In general, practical indicators describe the magnitude, duration, severity, or spatial coverage extent of drought. They are based on meteorological and hydrological variables, such as precipitation, temperature, streamflow, soil moisture, reservoir storage, and groundwater level. Several of them can be synthesized into a single indicator on a quantitative scale, often called a drought index. Although drought indices can provide ease of implementation, the scientific and operational meaning of an index value may raise questions, such as how each indicator is combined or weighted for an overall index derivation and how an arbitrary index value relates to hydrometeorological and statistical characteristics of droughts.

There are two types of drought indicators as described by Mawdsley et al. (1994); one is concerned with the environment and the other with water availability.

1. Environmental indicators: These are related to hydrometeorological and hydrological conditions and they help to measure the direct effect on the hydrological cycle. Among the most significant indicators are the deficits (dry spells) either in precipitation or streamflow or soil moisture or in their composition. They indicate the frequency of drought occurrences and various characteristics such as the drought duration and/or severity. The definition of these characteristics requires a threshold level, which is usually adopted as the arithmetic average or water demand level, but any other convenient level can also be adapted.

2. Water resource indicators: Generally, they measure severity in terms of the drought impact on water resources (surface or groundwater) that supply domestic, agricultural, and industrial uses, especially; and the impact on groundwater recharge, abstractions, and surface water levels behind the reservoirs. Water resources-related drought indicators are dependent not only on natural events, but also on the human interferences such as a steady increase in water demand versus limited supply facilities. Water resources mismanagement for water supply may also affect the drought conditions apart from a lack of rainfall or runoff. Water stresses and shortages are among the social dimensions of droughts due to mismanagement ("see chapter: Introduction").

Another definition of droughts posits two distinctive categories: conceptual droughts, where there are not specific formulations and procedures, and operational droughts that need treatment on a real-time basis including identification of the onset, severity, and termination of drought episodes ("see chapter: Temporal Drought Analysis and Modeling"). In this context, the operational drought category is similar to the water resources indicators (Wilhite and Glantz, 1985).

The indices are useful tools for characterization and comparison of drought events regarding their timing and responses to a threshold level under circumstantial conditions. They provide information for drought management efforts provided that the operational aspects of droughts are known such as drought duration, severity, and frequency in addition to probabilistic, statistical, and stochastic features. Although there are numerous drought definitions in practical application, the most significant one is concerned with the water resources supply and demand balance. For instance, deficiency in demand may trigger a possible drought if the sequence and the intensity (amount) of the deficiencies are longer and greater than the response to general water resources. Because water resources, their exploitation, and consumption patterns differ from place to place, drought definition and calculation procedures take different forms as drought indicators. The most commonly encountered droughts are meteorological, hydrological, and agricultural types, all of which individually or collectively impact on society and economic channels; hence, the combined result appears in the form of a socioeconomic drought ("see chapter: Introduction"). There are various drought indicators (WMO, 1975a,b; Erinç, 1965; Ogallo, 1989; Rao, 1986; Al-Sefry et al., 2004) but each one has its pros and cons.

In many publications, including this book, when droughts are the main subject, quantitative and rather complex numerical methodologies and formulations come to the fore for their description. It is well understood that the models are main tools for predictions including droughts, but they need numerical data only. The models can be run provided a that numerical database is available, but unfortunately a verbal (linguistic) database is not considered in many applications. In fact, without linguistic information and a logical rule base one cannot develop meaningful models for...

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