China
Africa
Explore chapters and articles related to this topic
Drought and water supply
Published in Stephen A. Thompson, Hydrology for Water Management, 2017
There are many ways to quantitatively define and analyze the phenomena of drought. First is by using a runs approach. A runs approach defines and describes drought using properties of a stochastic time series. Drought indices are a second way to define and describe drought. Some indices are extremely simple; some quite complex. An example of a simple index is to define a threshold value for a hydrologic variable and some duration of time when water availability is below that threshold. An example would be, say, less than 80% of normal precipitation in a 2-month period. The Palmer Drought Severity Index (PDSI) is a more complex index based on a water balance. The runs approach and the PDSI are discussed at length below. A third way to study drought is by frequency analysis similar to that used for floods in Chapter 11. Frequency analysis does not define droughts, it only assigns recurrence intervals to drought events that are defined by some other method. Drought frequency analysis can be applied to low streamflows exactly as was done for high streamflows. The annual minimum streamflow series is composed of the lowest streamflows for each year. The flows can be ranked and plotted on probability paper. The Gumbel Type III probability distribution (also called the Weibull distribution) fits annual minimum series data fairly well. In some cases the planner may need to know the probability of discharge periods of various lengths, such as the driest 5-day period. Discharges for different intervals can be defined and subjected to the same type of frequency analysis.
Agricultural Drought Indices: Combining Crop, Climate, and Soil Factors
Published in Saeid Eslamian, Faezeh Eslamian, Handbook of Drought and Water Scarcity, 2017
Nicolas R. Dalezios, Anne Gobin, Ana M. Tarquis Alfonso, Saeid Eslamian
Indices for the quantification of agricultural drought should be based on soil moisture measurements; however, these are often assessed indirectly by water balance calculations. A typical example is the Palmer drought severity index (PDSI) [42], which is considered an index of meteorological drought, although it can be used as an index of agricultural drought as well. The PDSI is a complex method, widely applied internationally, which is based on a soil moisture budget that considers precipitation and temperature for a given area over a period of months or years. In this method, drought is defined in terms of a reduction of available moisture below the level normally available and allows the degree of dryness to be rated based on expected climatic conditions. The severity of drought is considered to be a function of the length of period as well as the magnitude of abnormal moisture deficiency.
Environmental Evaluation: Lessons Learned from Case Studies
Published in Saeid Eslamian, Faezeh Eslamian, Handbook of Drought and Water Scarcity, 2017
The PDSI, known operationally as the Palmer drought index (PDI), attempts to measure the duration and intensity of the long-term drought-inducing circulation patterns. Long-term drought is cumulative, so the intensity of drought during the current month is dependent on the current weather patterns plus the cumulative patterns of previous months. Since weather patterns can change almost literally—overnight from a long-term drought pattern to a long-term wet pattern—the PDSI (PDI) can respond fairly rapidly. However, the PDI has been observed to have some pitfalls, which include failure to detect drought rapidly enough, and in some cases, only limited success was recorded as an operational drought monitoring tool. The PDSI is calculated using precipitation and temperature data, as well as the local available water content of the soil, from the inputs; all the basic terms of the water balance equation can be determined, including ET, soil recharge and runoff, and moisture loss from the surface layer. However, human impacts on the water balance such as irrigation are not considered [4,23].
A comprehensive assessment of remote sensing and traditional based drought monitoring indices at global and regional scale
Published in Geomatics, Natural Hazards and Risk, 2022
Niranga Alahacoon, Mahesh Edirisinghe
Drought indicators and indices are usually used by a large number of researchers to study in detail of spatial distribution, duration, and severity of a drought (Steinemann et al. 2005). In the early days of drought monitoring, absolute rainfall or rainfall deficit was used, which was expressed as a percentage of rainfall outflow (Heim 2002). However, with a greater focus on assessing the severity of drought and the complexity of drought studies in different climatic as well as environmental regions, researchers are increasingly inclined to develop new drought indices (Steinmann et al. 2005). The Palmer Drought Intensity Index (PDSI) has been cited by various researchers as one of the earliest drought index developed to assess the severity of relative drought nationwide (Plamer 1965; Hayes et al. 2012). Due to various limitations in the use of the PDSI, other indices such as the Surface Water Supply Index (SWSI; Schaefer and Desmond 1982) and the Standardized Precipitation Index (SPI; McKee et al. 1993), Rainfall Anomaly Index (RAI; Van Rooy 1965) was developed.
Drought monitoring in Ceyhan Basin, Turkey
Published in Journal of Applied Water Engineering and Research, 2021
Palmer Drought Severity Index (PDSI) is the first used index quantifying drought impacts under various climates (Palmer 1965). However, it has some limitations, calibrations and spatial comparability issues (Dai 2013; Mo and Chelliah 2006; Vicente-Serrano et al. 2009). The Standardized Precipitation Index (SPI) is widely applied under different climate regions for describing and comparing drought events (McKee et al. 1993). However, several studies have noted that the rise of global temperature leads to increase in water demand and evapotranspiration (Heim, 2017; Koch and Vögele 2009; Kirshen et al. 2008; García-Ruiz et al. 2011). Hence, the Standardized Precipitation Evaporation Index (SPEI) is developed considering both precipitation and potential evapotranspiration (PET) (Vicente-Serrano et al. 2010). PET is calculated by applying the classic Thornthwaite (TH) method (Ahmadi and Fooladmand, 2008; Thornthwaite, 1948), which is vulnerable in arid and semiarid regions (Tabari et al., 2013). The Penman–Monteith (PM) method is another method that needs more parameters including wind speed, relative humidity and solar radiation (Trenberth et al., 2014).
Performance evaluation of the CHIRPS precipitation dataset and its utility in drought monitoring over Yunnan Province, China
Published in Geomatics, Natural Hazards and Risk, 2019
Wenqi Wu, Yungang Li, Xian Luo, Yueyuan Zhang, Xuan Ji, Xue Li
Drought can be classified using drought indices (Chen et al. 2016), allowing researchers to evaluate such climate anomalies quantitatively in terms of duration, intensity, and spatial extent (Mishra and Singh 2010). The Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index (SPI) are the two indices used most widely (Mishra and Nagarajan 2011; Zhong et al. 2018). Calculation of the PDSI requires many parameters such as precipitation, air pressure, air temperature, and soil moisture. Moreover, because the timescale of the PDSI is fixed, the index cannot reveal the variability of regional drought events on multiple timescales. The SPI, which was developed by McKee et al. (1993), considers only rainfall when defining drought periods and therefore this index is often used to overcome these problems. It can be used to track drought over multiple timescales, and it is flexible with respect to the selected period space. The salient advantages of the SPI are that it can be computed for different timescales and it can provide early warning of drought and help assess drought severity (WMO 2012). The SPI has been applied to the study of different aspects of drought, e.g. frequency analysis (Guo et al. 2017), forecasting (Mishra et al. 2007), spatiotemporal analysis, and climate impact studies (Ashraf and Routray 2015). In addition, the SPI has been used widely to investigate the occurrence of meteorological drought in many countries and regions, e.g. Ethiopia (Edossa et al. 2010), Romania (Ionita et al. 2016), India (Mahajan and Dodamani 2016), Singapore (Tan et al. 2017), and China (Chen et al. 2017).