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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].
Discrete Random Variables
Published in William M. Mendenhall, Terry L. Sincich, Statistics for Engineering and the Sciences, 2016
William M. Mendenhall, Terry L. Sincich
Drought recurrence in Texas. A drought is a period of abnormal dry weather that causes a serious hydrologic imbalance in an area. The Palmer Drought Index (PDI) is designed to quantitatively measure the severity of a drought. A PDI value of −1 or less indicates a dry (drought) period. A PDI value greater than −1 indicates a wet (non-drought) period. Civil engineers at the University of Arizona used paleontology data and historical records to determine PDI values for each of the past 400 years in Texas (Journal of Hydrologic Engineering, Sept./Oct. 2003). The researchers discovered that the number Y of years that need to be sampled until a dry (drought) year is observed follows an approximate geometric distribution. A graph of the distribution is shown at the top of the page. From the graph, estimate E(Y). (Hint: Use the formula in Section 4.3.)Use the result, part a, to estimate the value of p for the geometric distribution.Estimate the probability that 7 years must be sampled in order to observe a drought year.
Water: consumption, usage patterns, and residential infrastructure. A comparative analysis of three regions in the Lima metropolitan area
Published in Water International, 2020
Daniel R. Rondinel-Oviedo, Jaime M. Sarmiento-Pastor
Three aspects should be considered in the context of climate: average rainfall, average temperature, and the Palmer drought index (Rockaway et al., 2011) or relative humidity (Manco Silva et al., 2012) – together referred to as ‘climatology’ (Sánchez García & Blanco Jiménez, 2012). More specific metrics include maximum temperature and the number of rainy days (Barberán & Salvador, 2010). A close association exists among temperature, rainfall, and residential water consumption per capita, with changing patterns and higher consumption in the summer (Fercovic & Melo, 2010). This is more true in low-density houses (probably owing to the presence of gardens) than in mid- or high-density ones, whose consumption tends to be more stable throughout the year (Domene & Saurí, 2006).
Comparison of vegetation regeneration after wildfire between Mediterranean and tundra ecosystems by using Landsat images
Published in Annals of GIS, 2018
Cheuklap Au Yeung, Rongrong Li
Figure 3 illustrates the vegetation regeneration trends in the WCF and ARF areas, along with the logarithmic trend lines. The two wildfires present a similar pattern, i.e. their RI values dropped significantly in 2008 (the year immediately after the fires), and then rebounded rapidly in 2009 before increasing at a steadier pace from 2010. From the sixth to eighth years (2013–2015) after the fires, the vegetation regeneration in the two cases differed little. A minor drop in the RI occurred in 2014, followed by an obvious increase in 2015, which can probably be attributed to other megascale factors. According to the NCDC (2016), the whole of California experienced a period of extreme to exceptional drought in 2014, whereas the Palmer Drought Index for Alaska was normal in that year.
Investigation of trends in extreme events: a case study of Ceyhan Basin, Turkey
Published in Journal of Applied Water Engineering and Research, 2023
Mehmet Ishak Yuce, Musa Esit, Veysel Kalaycioglu
Climate change has impacted water supplies, human life, the environment, agricultural activities, and industrial productivity as a result of global warming (Shi and Xu 2008). The monitoring of changes in meteorological and climate data series is a significant and difficult task that is gaining in popularity as a result of its importance in water management and drought. The MK method has shown that climate change has a positive impact on the maximum and minimum temperatures of Gombe city in northeastern Nigeria (Alhaji et al. 2018). Chen et al. (2009) used the Mann–Whitney–Petit test to explore historical trends of meteorological drought in Taiwan. Tabari et al. (2012) used the Kendall and Spearman non-parametric tests to investigate changes in drought severity and rainfall series in Iran from 1966 to 2005. Wang et al. (2013) investigated the variability and pattern of drought characteristics in China's Huang-Huai-Hai Plain, including Annual Total Drought Severity (ATDS), Annual Total Drought Duration (ATDD), and Annual Drought Frequency (ADF). Asfaw et al. (2018) studied the Woleka basin's precipitation and temperature trends in northern Ethiopia. Using the Palmer Drought Index approach, the number of dry years was found to be increasing. According to the MK method, the mean and minimum temperatures increased, but there was no noticeable trend in maximum temperature data. Researchers have taken into account studies including long records of climatic and hydrologic variables (Yuce et al. 2015; Yuce et al. 2018; Cannarozzo et al. 2006; Yu et al. 2006; Kampata et al. 2008; Sen 1968; Kumar et al. 2010; dos Santos et al. 2011; Zhong and Li 2009).