Spatiotemporal & Geostatistical Modelling of Groundwater Level Depth Over Haryana-Punjab, India
Issue: 2023 - Volume 27 [Issue 11]
Seemab Akhtar *
PECPL, Kolkata, India.
Department of Environmental Science, Integral University, Lucknow, India.
*Author to whom correspondence should be addressed.
The present study focuses on the Haryana and Punjab regions of the Indus basin, India. The study aims to analyze the long-term spatial-temporal changes in the groundwater level from 1996 to 2019. The modelling study involves a twofold objective. First, the ordinary kriging method estimates and evaluates spatial and temporal variations in groundwater level depth (surface-to-water level). Second, the study applies a pixel-based Mann-Kendall trend analysis. The point kriging cross-validation (PKCV) results are optimum, acceptable, and supports the unbiasedness hypothesis of kriging. The trend, significant or not, is determined by the Mann-Kendall test, while Sen's slope estimator determines the slope magnitude of the trend. Results revealed a significantly (at 99% and 95% confidence interval) high-rate depletion zone of groundwater level from 1996–2019 in the southwestern-central region to the western-northern area for all four seasons. The average rate of groundwater level in these zones declined from 40.36 cm/yr. to 37.42 cm/yr. It was observed from trend modelling in the monsoon season for 2014-2019 (Six-year window) that the net per cent area of groundwater level for the study area in the high- and low-rate depletion zone was hiked by 0.90% and 2.17%, respectively.
Keywords: Ordinary kriging, significant trend, mann-kendall, sen's slope
How to Cite
Nourani V, Mogaddam AA, Nadiri AO. An ANN-based model for spatiotemporal groundwater level forecasting. Hydrological Processes. 2008;22(26): 5054–5066. DOI:https://doi.org/10.1002/hyp.7129
Rajmohan N, Elango L. Hydrogeochemistry and its relation to groundwater level fluctuation in the Palar and Cheyyar river basins, southern India. Hydrological Processes. 2006;20(11): 2415–2427. DOI:https://doi.org/10.1002/hyp.6052
Akhtar S. Spatial-temporal Trends Mapping and Geostatistical Modelling of Groundwater Level Depth Over Northern Parts of Indo-Gangetic Basin, India. Journal of Geography, Environment and Earth Science International. 2023; 27(10):96–112. DOI:https://doi.org/10.9734/jgeesi/2023/v27i10719
Neeti N, Eastman JR. A Contextual Mann-Kendall Approach for the Assessment of Trend Significance in Image Time Series. Transactions in GIS, 2011;15(5):599–611. DOI:https://doi.org/10.1111/j.1467-9671. 2011.01280.x
Uyan M, Cay T. Spatial analyses of groundwater level differences using geostatistical modeling. Environmental and Ecological Statistics. 2013;20(4):633–646. DOI:https://doi.org/10.1007/s10651-013-0238-3
Varouchakis EA, Theodoridou PG, Karatzas GP. Spatiotemporal geostatistical modeling of groundwater levels under a Bayesian framework using means of physical background. Journal of Hydrology. 2019;575487–498 DOI:https://doi.org/10.1016/j.jhydrol.2019.05.055
Vousoughi FD, Dinpashoh Y, Aalami MT, Jhajharia D. Trend analysis of groundwater using non- parametric methods (case study: Ardabil plain). Stochastic Environmental Research and Risk Assessment. 2013;27(2):547–559 DOI:https://doi.org/10.1007/s00477-012-0599-4
Srivastava GS, Singh IB, Kulshrestha AK. Geomorphic and tectonic features of Punjab-Haryana plain as identified from digital elevation model and surface profiles. Himalayan Geology. 2014;35(2): 97–109.
Shekhar S, Kumar S, Densmore AL, van Dijk WM, Sinha R, Kumar M, Joshi SK, Rai SP, Kumar D. Modelling water levels of northwestern India in response to improved irrigation use efficiency. Scientific Reports. 2020;10(1);1–16. DOI:https://doi.org/10.1038/s41598-020-70416-0
Srivastava GS, Singh IB, Kulshrestha AK. Late quaternary geomorphic evolution of yamuna-sutlej interfluve: Significance of terminal fan. In Journal of the Indian Society of Remote Sensing. 2006;34:(2).
Chowdary VM, Chandran RV, Neeti N, Bothale RV, Srivastava YK, Ingle P, Ramakrishnan D, Dutta D, Jeyaram A, Sharma JR, Singh R. Assessment of surface and sub-surface waterlogged areas in irrigation command areas of Bihar state using remote sensing and GIS. Agricultural Water Management. 2008; 95(7):754–766. DOI:https://doi.org/10.1016/j.agwat.2008.02.009
Liu T, Mickley LJ, Gautam R, Singh MK, DeFries RS, Marlier ME. Detection of delay in post-monsoon agricultural burning across Punjab, India: Potential drivers and consequences for air quality. Environmental Research Letters. 2021; 16(1). DOI:https://doi.org/10.1088/1748-9326/ abcc28
Giraldo R, Delicado P, Mateu J. Ordinary kriging for function-valued spatial data. Environmental and Ecological Statistics. 2011;18(3):411–426. . DOI:https://doi.org/10.1007/s10651-010-0143-y
Fensholt R, Rasmussen K, Nielsen TT, Mbow C. Evaluation of earth observation based long term vegetation trends - Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data. Remote Sensing of Environment, 2009a;113(9):1886–1898. DOI:https://doi.org/10.1016/j.rse.2009.04.004
Fensholt R, Rasmussen K, Nielsen TT, Mbow C. Evaluation of earth observation based long term vegetation trends - Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data. Remote Sensing of Environment. 2009b;113(9):1886–1898.
Sobrino JA, Julien Y. Trend analysis of global MODIS-terra vegetation indices and land surface temperature between 2000 and 2011. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 2013;6(5):2139–2145. DOI:https://doi.org/10.1109/JSTARS.2013.2239607
Jaagus J. Climatic changes in Estonia during the second half of the 20th century in relationship with changes in large-scale atmospheric circulation. Theoretical and Applied Climatology. 2006;83(1–4):77–88. DOI:https://doi.org/10.1007/s00704-005-0161-0
da Silva RM, Santos CAG, Moreira M, Corte-Real J, Silva VCL, Medeiros IC. Rainfall and river flow trends using Mann–Kendall and Sen's slope estimator statistical tests in the Cobres River basin. Natural Hazards. 2015;77(2):1205–1221. DOI:https://doi.org/10.1007/s11069-015-1644-7