Groundwater Level Analysis Using Regional Kendall Test for Trend with Spatial Autocorrelation

Ground Water ◽  
2018 ◽  
Vol 57 (2) ◽  
pp. 320-328 ◽  
Author(s):  
Chuanglin Fang ◽  
Siao Sun ◽  
Shaofeng Jia ◽  
Yuanyuan Li
Keyword(s):  
Spatial Autocorrelation ◽  
Groundwater Level ◽  
Kendall Test ◽  
Level Analysis

scholarly journals Assessing the long-term sustainability of the groundwater resources in the Bacchiglione basin (Veneto, Italy) with the Mann–Kendall test: suggestions for higher reliability

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Mara Meggiorin ◽  
Giulia Passadore ◽  
Silvia Bertoldo ◽  
Andrea Sottani ◽  
Andrea Rinaldo
Keyword(s):  
Groundwater Level ◽  
Water Cycle ◽  
Groundwater Resources ◽  
Sustainable Use ◽  
Kendall Test ◽  
Groundwater System ◽  
Aquifer System ◽  
Mann Kendall Test ◽  
Status Assessment

The social, economic, and ecological importance of the aquifer system within the Bacchiglione basin (Veneto, IT) is noteworthy, and there is considerable disagreement among previous studies over its sustainable use. Investigating the long-term quantitative sustainability of the groundwater system, this study presents a statistical methodology that can be applied to similar cases. Using a combination of robust and widely used techniques, we apply the seasonal Mann–Kendall test and the Sen’s slope estimator to the recorded groundwater level timeseries. The analysis is carried out on a large and heterogeneous proprietary dataset gathering hourly groundwater level timeseries at 79 control points, acquired during the period 2005–2019. The test identifies significant decreasing trends for most of the available records, unlike previous studies on the quantitative status of the same resource which covered the domain investigated here for a slightly different period: 2000–2014. The present study questions the reason for such diverging results by focusing on the method’s accuracy. After carrying out a Fourier analysis on the longest available timeseries, for studies of groundwater status assessment this work suggests applying the Mann–Kendall test to timeseries longer than 20 years (because otherwise the analysis would be affected by interannual periodicities of the water cycle). A further analysis of two 60-year-long monthly timeseries between 1960 and 2020 supports the actual sustainable use of the groundwater resource, the past deployment of the groundwater resources notwithstanding. Results thus prove more reliable, and meaningful inferences on the longterm sustainability of the groundwater system are possible.

scholarly journals Variability of spatial patterns of autocorrelation and heterogeneity embedded in precipitation

2018 ◽  
Vol 50 (1) ◽  
pp. 215-230
Author(s):  
Dedi Liu ◽  
Qin Zhao ◽  
Shenglian Guo ◽  
Pan Liu ◽  
Lihua Xiong ◽  
...  
Keyword(s):  
Spatial Heterogeneity ◽  
Spatial Autocorrelation ◽  
Spatial Patterns ◽  
Spatial Interpolation ◽  
Kendall Test ◽  
Test Methods ◽  
Distributed Hydrological Model ◽  
Interpolation Methods ◽  
Increasing Trend ◽  
Spatial Interpolation Methods

Abstract Spatial interpolation of precipitation data is an essential input for hydrological modelling. At present, the most frequently used spatial interpolation methods for precipitation are based on the assumption of stationary in spatial autocorrelation and spatial heterogeneity. As climate change is altering the precipitation, stationary in spatial autocorrelation and spatial heterogeneity should be first analysed before spatial interpolation methods are applied. This study aims to propose a framework to understand the spatial patterns of autocorrelation and heterogeneity embedded in precipitation using Moran's I, Getis–Ord test, and semivariogram. Variations in autocorrelation and heterogeneity are analysed by the Mann–Kendall test. The indexes and test methods are applied to the 7-day precipitation series which are corresponding to the annual maximum 7-day flood volume (P-AM7FV) upstream of the Changjiang river basin. The spatial autocorrelation of the P-AM7FV showed a statistically significant increasing trend over the whole study area. Spatial interpolation schemes for precipitation may lead to better estimation and lower error for the spatial distribution of the areal precipitation. However, owing to the changing summer monsoons, random variation in the spatial heterogeneity analysis shows a significant increasing trend, which reduces the reliability of the distributed hydrological model with the input of local or microscales.

scholarly journals Characteristics and causes of groundwater dynamic changes in Naoli River Plain, Northeast China

2020 ◽  
Vol 20 (7) ◽  
pp. 2603-2615
Author(s):  
Du Xinqiang ◽  
Chang Kaiyang ◽  
Lu Xiangqin
Keyword(s):  
Groundwater Level ◽  
Human Activities ◽  
Dynamic Change ◽  
Kendall Test ◽  
Hydrodynamic Characteristics ◽  
Groundwater Exploitation ◽  
River Plain ◽  
Observation Wells ◽  
Year 2000 ◽  
Groundwater Dynamic

Abstract Identification of groundwater dynamic behavior and its mechanism is the basis of groundwater protection and management. In Naoli River Plain (NRP), an important agricultural cultivation base and wetland in China, the trend of groundwater dynamic change is complicated under natural climate and human activities. Based on the methods of the Mann–Kendall test, Sen's slope estimation and correlation analysis, groundwater hydrodynamic characteristics and causes were identified. Within 68 observation wells from year 2000 to 2015, there are 28, 30 and 10 wells, accounting for 41.2%, 44.1% and 14.7%, that belong to rising, declining and relatively stable change trends, respectively. The average groundwater rising and declining rates are 0.19 m/year and 0.26 m/year respectively. The groundwater level was increasing or stable in the areas where there was no intensive groundwater exploitation, such as wetland, mountain foregrounds, residential lands and dry farmland. The groundwater level was declining obviously in the paddy fields with groundwater as the source of irrigation water. Thus, the groundwater dynamics in NRP were affected both by human activities of groundwater irrigation and climate change. The carrying capacity of groundwater for agricultural cultivation has been overloaded in some areas, and a conjunctive utilization of surface water and groundwater is needed urgently in NRP.

scholarly journals Assessing and Forecasting of Groundwater Level Fluctuation in Joypurhat District, Northwest Bangladesh Using Wavelet Analysis and ARIMA Modeling

2021 ◽  
Author(s):  
Almamunur Rashid ◽  
Mahiuddin Alamgir ◽  
Mohamad Tofayal Ahmed ◽  
Roquia Salam ◽  
Abu Reza Md. Towfiqul I ◽  
...  
Keyword(s):  
Groundwater Level ◽  
Crop Production ◽  
Time Series Data ◽  
Average Rate ◽  
Moving Average ◽  
Arima Model ◽  
Kendall Test ◽  
Series Data ◽  
Agricultural Crop

Abstract Groundwater resource plays a crucial role for agricultural crop production and socio-economic development in some parts of the world including Bangladesh. Joypurhat district, the northwest part of Bangladesh, a crop production hub, is entirely dependent on groundwater irrigation. A precise assessment and prediction of groundwater level (GWL) can assist long-term GWR management, especially in drought-prone agricultural regions. Therefore, this study was carried out to identify trends and magnitude of GWL fluctuation (1980-2019) using the Modified Mann- Kendall test, Pettitt’s Test, and Sen Slope estimators in the drought-prone Joypurhat district, northwest Bangladesh. Time-series data analysis was performed to forecast GWL from 2020 to 2050 using the Auto-Regressive Integrated Moving Average (ARIMA) model. The findings of the MMK test revealed a significant declining trend of GWL, and the trend turning points were identified in the years 1991, 1993, 1997, and 2004, respectively. Results also indicate that the declining rate of GWL varied from 0.104 m/yr to 0.159 m/yr and the average rate of GWL declination was 0.136 m/yr during 1980-2019. The outcomes of wavelet spectrum analysis depicted two significant periods of the declining trend in Khetlal and Akkelpur Upazilas. The results obtained from the optimal identified model ARIMA (2,1,0), indicating that GWL will decline at a depth of 13.76 m in 2050, and the average declination rate of GWL will be 0.143 m/yr in the study area. The predicted results showed a similar declining tendency of GWL from 2020 to 2050, suggesting a disquieting condition, particularly for Khetlal Upazila. This research would provide a practical approach for GWL assessment and prediction that could help decision-makers implement long-term GWR management in the study area.

Application of vector autoregressive model for rainfall and groundwater level analysis

2017 ◽  
Author(s):  
Chai Yoke Keng ◽  
Fam Pei Shan ◽  
Kunio Shimizu ◽  
Tomoaki Imoto ◽  
Habibah Lateh ◽  
...  
Keyword(s):  
Groundwater Level ◽  
Autoregressive Model ◽  
Vector Autoregressive Model ◽  
Vector Autoregressive ◽  
Level Analysis

scholarly journals LONG-TERM GROUNDWATER REGIME TRENDS IN THE AGRICULTURAL AREAS

2018 ◽  
Author(s):  
Aurelija RUDZIANSKAITĖ
Keyword(s):  
Groundwater Level ◽  
Land Surface ◽  
Sandy Loam ◽  
Peat Soil ◽  
Mineral Soil ◽  
Hydrological Regime ◽  
Kendall Test ◽  
Groundwater Level Fluctuations ◽  
Mineral Soils

Long-term data on hydrological regime change of the groundwater situated in moraine sandy loam and peat in Lithuanian karst zone presented in the article. The aim of the paper was on the basis of long-term groundwater studies to determine the water level trends. Groundwater level fluctuations mainly dependent on the ground type. The nearest land surface groundwater level (61-174 cm) was measured in peat soil (well 1), in mineral soil (well 2) was deeper (309-584 cm). Correlation between data of the annual precipitation and groundwater level in mineral soils (r2 = 0.416, tact .= 3.48>t95%=1.74) was more significant than in peat soils (r2 = 0.185, tact.=1.96 >t95%=1.74). The highest fluctuations of groundwater level was determined in mineral soil (well 2). According to Mann-Kendall test, the groundwater level significantly increased in February, April and December. Due to warmer winters decreased the duration and depth of the frost, frequent thaw, this cause increased feeding of aquifer in winter.

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