scholarly journals Fuzzy linear regression analysis for groundwater response to meteorological drought in the aquifer system of Xanthi plain, NE Greece

2021 ◽  
Author(s):  
Christopher Papadopoulos ◽  
Mike Spiliotis ◽  
Ioannis Gkiougkis ◽  
Fotios Pliakas ◽  
Basil Papadopoulos
Keyword(s):  
Linear Regression ◽  
Linear Regression Analysis ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Fuzzy Linear Regression ◽  
Aquifer System ◽  
Irrational Behavior ◽  
Groundwater Response ◽  
Linear Regressions

Abstract This paper studies, through the principles of fuzzy set theory, groundwater response to meteorological drought in the case of an aquifer system located in the plains at the southeast of Xanthi, NE Greece. Meteorological drought is expressed through standardized Reconnaissance Drought Index (RDISt) and Standardized Precipitation Index (SPI), which are calculated for various reference periods. These drought indices are considered as independent variables in multiple fuzzy linear regression based on Tanaka's model, while the observed water table regarding two areas is used as a dependent variable. The fuzzy linear regression of Tanaka is characterized by the inclusion constraints where all the observed data must be included in the produced fuzzy band. Hence, each fuzzy output can get an interval of values where a membership degree corresponds to each of them. A modification of the Tanaka model by adding constraints is proposed in order to avoid irrational behavior. The results show that there was a significant influence of the meteorological drought of the previous hydrological year, while geology plays an important role. Furthermore, the use of RDISt improves the results of fuzzy linear regressions in all cases. Two suitability measures and a measure of comparison between fuzzy numbers are used.

scholarly journals Development of a Multiple Linear Regression Model for Meteorological Drought Index Estimation Based on Landsat Satellite Imagery

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3393
Author(s):  
Seon Woo Kim ◽  
Donghwi Jung ◽  
Yun-Jae Choung
Keyword(s):  
Remote Sensing ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Drought Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Model ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Index Estimation ◽  
Cumulative Precipitation

Climate polarization due to global warming has increased the intensity of drought in some regions, and the need for drought estimation studies to help minimize damage is increasing. In this study, we constructed remote sensing and climate data for Boryeong, Chungcheongnam-do, Korea, and developed a model for drought index estimation by classifying data characteristics and applying multiple linear regression analysis. The drought indices estimated in this study include four types of standardized precipitation indices (SPI1, SPI3, SPI6, and SPI9) used as meteorological drought indices and calculated through cumulative precipitation. We then applied statistical analysis to the developed model and assessed its ability as a drought index estimation tool using remote sensing data. Our results showed that its adj.R2 value, achieved using cumulative precipitation for one month, was very low (approximately 0.003), while for the SPI3, SPI6, and SPI9 models, the adj.R2 values were significantly higher than the other models at 0.67, 0.64, and 0.56, respectively, when the same data were used.

scholarly journals Análisis comparativo de índices de sequía en Andalucía para el periodo 1901-2012

2016 ◽  
Vol 42 (1) ◽  
pp. 67 ◽  
Author(s):  
M. Peña-Gallardo ◽  
S. R. Gámiz-Fortís ◽  
Y. Castro-Diez ◽  
M. J. Esteban-Parra
Keyword(s):  
Time Windows ◽  
Initial Period ◽  
Climatic Variability ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Precipitation Index ◽  
Drought Indices ◽  
Global Evaluation ◽  
Temporal Behaviour ◽  
The Standardized Precipitation Index

The aim of this paper is the analysis of the detection and evolution of droughts occurred in Andalusia for the period 1901-2012, by applying three different drought indices: the Standardized Precipitation Index (SPI), the Standardized Precipitation and Evapotranspiration Index (SPEI) and the Standardized Drought-Precipitation Index (IESP), computed for three time windows from the initial period 1901-2012. This analysis has been carried out after a preliminary study of precipitation trends with the intention of understanding the precipitation behaviour, because this climatic variable is one of the most important in the study of extreme events. The specific objectives of this study are: (1) to investigate and characterize the meteorological drought events, mainly the most important episodes in Andalusia; (2) to provide a global evaluation of the capacities of the three different considered indices in order to characterize the drought in a heterogeneous climatically territory; and (3) to describe the temporal behaviour of precipitation and drought indices series in order to establish the general characteristics of their evolution in Andalusia. The results have shown that not all the indices respond similarly identifying the intensity and duration of dry periods in this kind of region where geographical and climatic variability is one of the main elements to be considered.

scholarly journals Elucidating Diverse Drought Characteristics from Two Meteorological Drought Indices (SPI and SPEI) in China

2020 ◽  
Vol 21 (7) ◽  
pp. 1513-1530 ◽  
Author(s):  
Lingcheng Li ◽  
Dunxian She ◽  
Hui Zheng ◽  
Peirong Lin ◽  
Zong-Liang Yang
Keyword(s):  
Clustering Algorithm ◽  
Potential Evapotranspiration ◽  
Standardized Precipitation Index ◽  
Three Dimensional ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Severity ◽  
Severe Drought ◽  
Small Areas ◽  
Drought Characteristics

AbstractThis study elucidates drought characteristics in China during 1980–2015 using two commonly used meteorological drought indices: standardized precipitation index (SPI) and standardized precipitation–evapotranspiration index (SPEI). The results show that SPEI characterizes an overall increase in drought severity, area, and frequency during 1998–2015 compared with those during 1980–97, mainly due to the increasing potential evapotranspiration. By contrast, SPI does not reveal this phenomenon since precipitation does not exhibit a significant change overall. We further identify individual drought events using the three-dimensional (i.e., longitude, latitude, and time) clustering algorithm and apply the severity–area–duration (SAD) method to examine the drought spatiotemporal dynamics. Compared to SPI, SPEI identifies a lower drought frequency but with larger total drought areas overall. Additionally, SPEI identifies a greater number of severe drought events but a smaller number of slight drought events than the SPI. Approximately 30% of SPI-detected drought grids are not identified as drought by SPEI, and 40% of SPEI-detected drought grids are not recognized as drought by SPI. Both indices can roughly capture the major drought events, but SPEI-detected drought events are overall more severe than SPI. From the SAD analysis, SPI tends to identify drought as more severe over small areas within 1 million km2 and short durations less than 2 months, whereas SPEI tends to delineate drought as more severe across expansive areas larger than 3 million km2 and periods longer than 3 months. Given the fact that potential evapotranspiration increases in a warming climate, this study suggests SPEI may be more suitable than SPI in monitoring droughts under climate change.

scholarly journals Commonly Used Drought Indices as Indicators of Soil Moisture in China

2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Severity Index ◽  
Agricultural Drought ◽  
Weather Data ◽  
Drought Indices ◽  
Drought Severity ◽  
Better Than

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.

Intuitionistic fuzzy linear regression analysis

2012 ◽  
Vol 12 (2) ◽  
pp. 215-229 ◽  
Author(s):  
R. Parvathi ◽  
C. Malathi ◽  
M. Akram ◽  
Krassimir T. Atanassov
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Fuzzy Linear Regression ◽  
Intuitionistic Fuzzy

scholarly journals Finescale Evaluation of Drought in a Tropical Setting: Case Study in Sri Lanka

2009 ◽  
Vol 48 (1) ◽  
pp. 77-88 ◽  
Author(s):  
Bradfield Lyon ◽  
Lareef Zubair ◽  
Vidhura Ralapanawe ◽  
Zeenas Yahiya
Keyword(s):  
Sri Lanka ◽  
Standardized Precipitation Index ◽  
Meteorological Drought ◽  
Drought Indices ◽  
Drought Risk ◽  
Mitigation And Adaptation ◽  
Wide Range ◽  
Drought Relief ◽  
Drought Indicators ◽  
The Standardized Precipitation Index

Abstract In regions of climatic heterogeneity, finescale assessment of drought risk is needed for policy making and drought management, mitigation, and adaptation. The relationship between drought relief payments (a proxy for drought risk) and meteorological drought indicators is examined through a retrospective analysis for Sri Lanka (1960–2000) based on records of district-level drought relief payments and a dense network of 284 rainfall stations. The standardized precipitation index and a percent-of-annual-average index for rainfall accumulated over 3, 6, 9, and 12 months were used, gridded to a spatial resolution of 10 km. An encouraging correspondence was identified between the spatial distribution of meteorological drought occurrence and historical drought relief payments at the district scale. Time series of drought indices averaged roughly over the four main climatic zones of Sri Lanka showed statistically significant (p < 0.01) relationships with the occurrence of drought relief. The 9-month cumulative drought index provided the strongest relationships overall, although 6- and 12-month indicators provided generally similar results. Some cases of appreciable drought without corresponding relief payments could be attributed to fiscal pressures, as during the 1970s. Statistically significant relationships between drought indicators and relief payments point to the potential utility of meteorological drought assessments for disaster risk management. In addition, the study provides an empirical approach to testing which meteorological drought indicators bear a statistically significant relationship to drought relief across a wide range of tropical climates.

Sign in / Sign up

Export Citation Format

Share Document