Geostatistics on water resources investigation

Before talking about the different researches that have had as main focus water resources, I think it is necessary to explain first what geostatistics is.

Geostatistics is a type of statistics that is used to analyze and interpret geographically referenced data. It is not restricted to work only with point data, it also works with GIS layers to explore spatial variation, improve generation of digital elevation models (DEM) and their respective simulations, optimize spatial sampling, etc. [1]

A lot of professions can take advantage of the tool geostatistics; among impacted application fields, the ones that have benefited the most are geosciences, water resources, environmental sciences, agriculture, soil sciences, mathematics and statistics, ecology, civil engineering, petroleum engineering, and limnology. [1]

Before geostatistics, conventional mapping was the standard. The main difference between the two is that geostatistical mapping relies on real measurements and semiautomated algorithms, while conventional mapping uses empirical knowledge. Also, it’s important to make clear that geostatistical mapping is an expert based system due to the fact that there has to be a person in charge of making decisions regarding whether to use linear or non-linear models, spatial position or not, to transform or use the original data, etc. This remark is needed because of the wrong existing notion that spatial prediction is completely done by a computer program. [1]

Constant changes occur in the environment and, therefore, in the values that are used in geostatistics; this is why, there has to be a continuous remaking of the maps. Therefore, the phrase geostatistical monitoring seems more appropriate than the more used geostatistical mapping. [1]

The following are the steps required for geostatistical monitoring: [1]

1.      Sampling, designing and processing data.

2.      Field data collection and laboratory analysis.

3.      Point data analysis and model estimation.

4.      Model implementation and performance evaluation.

5.      Production and distribution of the output geoinformation.

 

Examples of water resources investigation using geostatistics

 

Application of geostatistical analysis for evaluating variation in groundwater characteristics: [2]

Agriculture needs standard quality water, but sometimes this fact doesn’t stop people from excessive use of good-quality water resources, therefore low-quality water resources have to be used. Irrigation that doesn’t contemplate the principles of water consumption sums up to this problem. This is how we end up with soluble salts and sodium in the root zone that originates damages to crops, soil and environment.

This is why it is important to know the quantity and quality of groundwater.

In this case of study, the goal was to predict the temporal and spatial variations of groundwater quality parameters. There were two phases, one was to sample 76 wells and measure some of their chemical characteristics; the other phase was to insert the measured properties along with the wells location as a point layer in a GIS environment to draw the maps using a geostatistical method called kriging method which is a sophisticated version of the inverse distance interpolation that is used to determine how much weight should be given to any neighbour. See Fig.1 for an example of a generated map of the area of study using geostatistics.

Fig.1: Map of groundwater salinity [2]

 

Geostatistical modeling of sediment abundance in a heterogeneous basalt aquifer: [3]

This aquifer has intercalated beds of fine-grained sediments, which previous calibrations of the groundwater flow models showed that the hydraulic conductivity is affected by the proportion of the intercalated sediments.

This case of study was conducted in order to make a geostatistical model of sediment abundance in the aquifer so that it can improve future groundwater flow models of the site in study.

For the spatial model of sediment abundance, borehole data was used, and was created using a GIS format that can interface with the groundwater flow model. In order to analyze the data to choose an adequate estimation method and quantifying the uncertainty of the estimates, geostatistical methods were employed. See Fig. 2 for examples of generated maps of the area of study using geostatistics.

Fig. 2: Figure “A” is a map that shows areas with more than 11 % of sediment content and with less than 11 % of sediment content. Figure “B” is a map that shows the median sediment content. Both maps use the uppermost 300 feet of the aquifer. [3]

 

Use of geostatistics in hazardous, toxic and radioactive waste-site investigations: [4]

This study had the goal of making a document that would work as a guide on how to use geostatistics at hazardous, toxic and radioactive-waste (HTRW) site investigations.

This kind of investigations have the goal to determine the extent and spatial distribution of contamination. Due to lack of a uniform distribution of measurements in the region, the uncertainty at the moment of interpolating in order to estimate values, and the need to establish a single representative value for the area, geostatistics is used to solve these problems.

 

Geostatistical investigations into the effects of a hydropower plant on the groundwater resources: [5]

This study focused on the influence that a hydropower plant has on the groundwater table and groundwater dynamics of the area. Geostatistical methods were employed in order to determine the changes of diverse groundwater characteristics.

To measure the groundwater level, 532 observation wells were used. For the interpolation, geostatistical methods were applied to produce the spatial distribution of the groundwater level. See Fig. 3 for an example of a generated map of the area of study using geostatistics.

Fig. 3: Map of the mean groundwater levels for the 1987-1989 three year period [5]

 

Bibliography

  • [1] Hengl, T. A practical guide to geostatistical mapping of environmental variables. JRC Scientific and Technical Reports. 2007. JRC European Commission.
  • [2] Sahebjalal, E. Application of geostatistical analysis for evaluating variation in groundwater characteristics. World Applied Sciences Journal. 2012. IDOSI Publications.
  • [3] Welhan, J.; Farabaugh, R.; Merrick, M; Anderson, S. Geostatistical modeling of sediment abundance in a heterogeneous basalt aquifer at the Idaho National Laboratory, Idaho. Scientific Investigations Report. 2007. USGS.
  • [4] Bossong, C.R.; Karlinger, M.R.; Troutman, B.M.; Vecchia, A.V. Overview and technical and practical aspects for use of geostatistics in hazardous-, toxic-, and radioactive-waste-site investigations. Water-Resources Investigations Report. 1999. USGS.
  • [5] Bárdossy, A.; Molnár, Z. Statistical and geostatistical investigations into the effects of the Gabcikovo hydropower plant on the groundwater resources of northwest Hungary. Hydrological Sciences Journal. 2004.

Saul Montoya

Saul Montoya es Ingeniero Civil graduado de la Pontificia Universidad Católica del Perú en Lima con estudios de postgrado en Manejo e Ingeniería de Recursos Hídricos (Programa WAREM) de la Universidad de Stuttgart con mención en Ingeniería de Aguas Subterráneas y Hidroinformática.

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