Sen / ?en Applied Drought Modeling, Prediction, and Mitigation

1. Auflage 2015
ISBN: 978-0-12-802422-5
Verlag: Elsevier Science & Techn.
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 484 Seiten

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 Istanbul, 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).

Autoren/Hrsg.

Sen, Zekâi

?en, Zekƒi

Leseproben

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...