scholarly journals Comparison of parametric and non-parametric methods for trend identification in groundwater levels in Sirjan plain aquifer, Iran

2020 ◽  
Vol 51 (6) ◽  
pp. 1455-1477
Author(s):  
Rasoul Mirabbasi ◽  
Farshad Ahmadi ◽  
Deepak Jhajharia
Keyword(s):  
Trend Analysis ◽  
Parametric Methods ◽  
Quantitative Index ◽  
Analysis Method ◽  
Statistical Tool ◽  
Identification Methods ◽  
Groundwater Levels ◽  
Level Data ◽  
Trend Identification ◽  
Non Parametric

Abstract In the present study, five parametric and non-parametric methods: linear regression (LR), conventional Mann–Kendall (MK), modified Mann–Kendall (MMK), Spearman's Rho (SR) and Innovative Trend Method (ITM) were used to identify trends in the groundwater levels of 60 piezometers distributed uniformly across Sirjan plain, Iran, from 2005 to 2018. The LR method was found to be affected by the presence of outliers and autocorrelation. The conventional non-parametric tests (MK and SR) were not able to offset the effects of the autocorrelations between the groundwater level data. The ITM method was also found to be a not so comprehensive and precise statistical tool for trend analysis because it does not provide a quantitative index for identifying trend significance. Therefore, the MMK test was found to be the most appropriate trend analysis method among the five trend identification methods used in this study by eliminating the effect of all significant autocorrelation coefficients. The results of the MMK test showed that the groundwater levels in Sirjan plain had witnessed significant decreasing trends during the study period. In only 24 months (out of a total 10,080 studied months), no significant decreasing trends in groundwater levels were observed.

Trend analysis of groundwater using non-parametric methods (case study: Ardabil plain)

2012 ◽  
Vol 27 (2) ◽  
pp. 547-559 ◽  
Author(s):  
Farnaz Daneshvar Vousoughi ◽  
Yagob Dinpashoh ◽  
Mohammad Taghi Aalami ◽  
Deepak Jhajharia
Keyword(s):  
Trend Analysis ◽  
Parametric Methods ◽  
Non Parametric

The Distribution of Health Care Costs and Their Statistical Analysis for Economic Evaluation

1998 ◽  
Vol 3 (4) ◽  
pp. 233-245 ◽  
Author(s):  
Andrew Briggs ◽  
Alastair Gray
Keyword(s):  
Health Care ◽  
Health Care Costs ◽  
Health Care Cost ◽  
Cost Data ◽  
Parametric Methods ◽  
Patient Level Data ◽  
Patient Level ◽  
Level Data ◽  
Care Costs ◽  
Non Parametric

Objective: Where patient level data are available on health care costs, it is natural to use statistical analysis to describe the differences in cost between alternative treatments. Health care costs are, however, commonly considered to be skewed, which could present problems for standard statistical tests. This review examines how authors report the distributional form of health care cost data and how they have analysed their results. Method: A review of cost-effectiveness studies that collected patient-level data on health care costs. To supplement the review, five datasets on health care costs are examined. Consideration is given to the use of parametric methods on the transformed scale and to non-parametric methods of analysing skewed cost data. Results: Since economic analysis requires estimation in monetary units, the usefulness of transformation-based methods is limited by the inability to retransform cost differences to the original scale. Non-parametric rank sum methods were also found to be of limited use for economic analysis, partly due to the focus on hypothesis testing rather than estimation. Overall, the non-parametric approach of bootstrapping was found to offer a useful test of the appropriateness of parametric assumptions and an alternative method of estimation where those assumptions were found not to hold. Conclusions: Guidelines for the analysis of skewed health care cost data are offered.

scholarly journals Detection of Groundwater Levels Trends Using Innovative Trend Analysis Method in Temperate Climatic Conditions

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2129
Author(s):  
Ionuț Minea ◽  
Daniel Boicu ◽  
Oana-Elena Chelariu
Keyword(s):  
Trend Analysis ◽  
Groundwater Level ◽  
Global Climate ◽  
Groundwater Resources ◽  
Winter Season ◽  
Climatic Conditions ◽  
Positive Trend ◽  
Analysis Method ◽  
Groundwater Levels ◽  
Innovative Trend Analysis

The evolution of groundwater levels is difficult to predict over medium and long term in the context of global climate change. Innovative trend analysis method (ITA) was used to identify these trends, and ITA index was calculated to measure their magnitude. The data used are sourced from 71 hydrogeological wells that were dug between 1983 and 2018 and cover an area of over 8000 km2 developed in the temperate continental climate in the north-eastern part of Romania. The results obtained by applying the ITA show a general positive trend for groundwater level over 50% of wells for winter and spring seasons and annual values. The negative trends were observed for more than 43% of wells for the autumn season followed by the summer season (less than 40%). The magnitude of trends across the region shows a significant increase for spring season (0.742) followed by winter season (0.353). Important changes in the trends slopes and magnitudes have been identified for groundwater level depth between 0 and 4 m (for winter and spring seasons) and between 4 and 6 m (for summer and autumn seasons). The results can be implemented in groundwater resources management projects at local and regional level.

scholarly journals Depletion of groundwater resources under rapid urbanisation in Africa: recent and future trends in the Nairobi Aquifer System, Kenya

2020 ◽  
Vol 28 (8) ◽  
pp. 2635-2656
Author(s):  
Samson Oiro ◽  
Jean-Christophe Comte ◽  
Chris Soulsby ◽  
Alan MacDonald ◽  
Canute Mwakamba
Keyword(s):  
Negative Impact ◽  
Groundwater Resources ◽  
Climatic Data ◽  
Groundwater Abstraction ◽  
Management Scenarios ◽  
Aquifer System ◽  
Groundwater Levels ◽  
Future Evolution ◽  
Level Data ◽  
Groundwater Assessment

AbstractThe Nairobi volcano-sedimentary regional aquifer system (NAS) of Kenya hosts >6 M people, including 4.7 M people in the city of Nairobi. This work combines analysis of multi-decadal in-situ water-level data with numerical groundwater modelling to provide an assessment of the past and likely future evolution of Nairobi’s groundwater resources. Since the mid-1970s, groundwater abstraction has increased 10-fold at a rate similar to urban population growth, groundwater levels have declined at a median rate of 6 m/decade underneath Nairobi since 1950, whilst built-up areas have increased by 70% since 2000. Despite the absence of significant trends in climatic data since the 1970s, more recently, drought conditions have resulted in increased applications for borehole licences. Based on a new conceptual understanding of the NAS (including insights from geophysics and stable isotopes), numerical simulations provide further quantitative estimates of the accelerating negative impact of abstraction and capture the historical groundwater levels quite well. Analysis suggests a groundwater-level decline of 4 m on average over the entire aquifer area and up to 46 m below Nairobi, net groundwater storage loss of 1.5 billion m3 and 9% river baseflow reduction since 1950. Given current practices and trajectories, these figures are predicted to increase six-fold by 2120. Modelled future management scenarios suggest that future groundwater abstraction required to meet Nairobi projected water demand is unsustainable and that the regional anthropogenically-driven depletion trend can be partially mitigated through conjunctive water use. The presented approach can inform groundwater assessment for other major African cities undergoing similar rapid groundwater development.

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