Characterisation of Groundwater Drought Using Distributed Modelling, Standardised Indices, and Principal Component Analysis

被引:1
|
作者
Christelis, V. [1 ]
Mansour, M. M. [1 ]
Jackson, C. R. [1 ]
机构
[1] British Geol Survey, Nottingham NG12 5GG, England
基金
英国自然环境研究理事会;
关键词
Groundwater drought; Groundwater modelling; Standardised groundwater level index; Standardised precipitation index; Principal component analysis; PRECIPITATION INDEX; VARIABILITY; PROJECTIONS; RECHARGE; FLOWS; SPI;
D O I
10.1007/s11269-024-03997-4
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
A modelling framework was developed to characterise groundwater drought at a catchment scale in the absence of adequate observational records. The framework was used to characterise historical groundwater drought events for a Chalk aquifer in southern England over the period 1971-2004 during which three major drought events occurred. A numerical groundwater model was used to simulate the groundwater level fluctuations driven by historical time-variable and spatially non-uniform recharge inputs. The standardised groundwater level index (SGI) was applied to the simulated groundwater levels to evaluate the spatial pattern of groundwater drought and of their severity and duration. A dimensionality reduction method, namely principal component analysis (PCA), was applied to the SGI dataset and to the standardised precipitation index (SPI) to further explore the spatio-temporal drought characteristics. The analysis showed inconsistency in the spatial distribution of the duration and severity among the three studied events. PCA indicated that the SPI was not a good predictor of groundwater drought during the extreme European heatwave of 2003 whereas the proposed modelling framework correctly identified the resilience of the groundwater system to that event and in line with observations. Furthermore, significant differences were observed between the spatial patterns obtained from SPI and SGI datasets highlighting the important role that hydrological and hydrogeological features of a catchment have in groundwater drought development.
引用
收藏
页数:15
相关论文
共 50 条
  • [1] Monitoring groundwater quality using principal component analysis
    Patnaik, Manaswinee
    Tudu, Chhabirani
    Bagal, Dilip Kumar
    APPLIED GEOMATICS, 2024, 16 (01) : 281 - 291
  • [2] Monitoring groundwater quality using principal component analysis
    Manaswinee Patnaik
    Chhabirani Tudu
    Dilip Kumar Bagal
    Applied Geomatics, 2024, 16 : 281 - 291
  • [3] Distributed Clustering Using Collective Principal Component Analysis
    Hillol Kargupta
    Weiyun Huang
    Krishnamoorthy Sivakumar
    Erik Johnson
    Knowledge and Information Systems, 2001, 3 (4) : 422 - 448
  • [4] Construction of hospital management indices using principal component analysis
    Almenara-Barrios, J
    García-Ortega, C
    González-Caballero, JL
    Abellán-Hervás, MJ
    SALUD PUBLICA DE MEXICO, 2002, 44 (06): : 533 - 540
  • [5] Modelling of Earphone Design Using Principal Component Analysis
    Lui, Lucas Kwai Hong
    Lee, C. K. M.
    APPLIED SCIENCES-BASEL, 2023, 13 (17):
  • [6] Spatial control of groundwater contamination, using principal component analysis
    Rao, N. Subba
    JOURNAL OF EARTH SYSTEM SCIENCE, 2014, 123 (04) : 715 - 728
  • [7] Spatial control of groundwater contamination, using principal component analysis
    N Subba Rao
    Journal of Earth System Science, 2014, 123 : 715 - 728
  • [8] Analysis of groundwater drought building on the standardised precipitation index approach
    Bloomfield, J. P.
    Marchant, B. P.
    HYDROLOGY AND EARTH SYSTEM SCIENCES, 2013, 17 (12) : 4769 - 4787
  • [9] Distributed Composite Drought Index Based on Principal Component Analysis and Temporal Dependence Assessment
    Santos, Joao F.
    Carrico, Nelson
    Miri, Morteza
    Raziei, Tayeb
    WATER, 2025, 17 (01)
  • [10] Asynchronous Distributed Principal Component Analysis Using Stochastic Approximation
    Morral, Gemma
    Bianchi, Pascal
    Jakubowicz, Jeremie
    2012 IEEE 51ST ANNUAL CONFERENCE ON DECISION AND CONTROL (CDC), 2012, : 1398 - 1403