Predicting of the Climate-induced Depletion in Groundwater Level and Storage: A case in Akarçay Basin

This study was to evaluate the groundwater-level behavior in Geum River Basin (9645.5 km2) of South Korea with HadGEM3-RA RCP 4.5 and 8.5 climate change scenarios and future groundwater use data using the soil and water assessment tool (SWAT). Before evaluating future groundwater behavior, the SWAT model was calibrated and validated using the daily inflows and storage of two dams (DCD and YDD) in the basin for 11 years (2005–2015), the daily groundwater-level observation data at five locations (JSJS, OCCS, BEMR, CASS, and BYBY), and the daily inflow and storage of three weir locations (SJW, GJW, and BJW) for three years and five months (August 2012 to December 2015). The Nash–Sutcliffe efficiency (NSE) and the coefficient of determination (R2) of two dam inflows was 0.55–0.70 and 0.67–0.75. For the inflows of the three weirs, NSE was 0.57–0.77 and R2 was 0.62–0.81. The average R2 value for the groundwater levels of the five locations ranged from 0.53 to 0.61. After verifying the SWAT for hydrologic components, we evaluated the behavior of future groundwater levels by future climate change scenarios and estimated future ground water use by Korean water vision 2020 based on ground water use monitoring data. The future groundwater-level decreased by −13.0, −5.0, and −9.0 cm at three upstream locations (JSJS, OCCS, and BEMR) among the five groundwater-level observation locations and increased by +3.0 and +1.0 cm at two downstream locations (CASS and BYBY). The future groundwater level was directly affected by the groundwater recharge, which was dependent on the seasonal and spatial precipitations in the basin.

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Analysis of groundwater drought building on the standardised precipitation index approach

Hydrology and Earth System Sciences ◽

10.5194/hess-17-4769-2013 ◽

2013 ◽

Vol 17 (12) ◽

pp. 4769-4787 ◽

Cited By ~ 128

Author(s):

J. P. Bloomfield ◽

B. P. Marchant

Keyword(s):

Time Series ◽

Groundwater Level ◽

Precipitation Index ◽

Monitoring Networks ◽

Level Data ◽

Index Approach ◽

Groundwater Drought ◽

Standardised Precipitation Index ◽

Positive Linear Correlation ◽

And Storage

Abstract. A new index for standardising groundwater level time series and characterising groundwater droughts, the Standardised Groundwater level Index (SGI), is described. The SGI builds on the Standardised Precipitation Index (SPI) to account for differences in the form and characteristics of groundwater level and precipitation time series. The SGI is estimated using a non-parametric normal scores transform of groundwater level data for each calendar month. These monthly estimates are then merged to form a continuous index. The SGI has been calculated for 14 relatively long, up to 103 yr, groundwater level hydrographs from a variety of aquifers and compared with SPI for the same sites. The relationship between SGI and SPI is site specific and the SPI accumulation period which leads to the strongest correlation between SGI and SPI, qmax, varies between sites. However, there is a consistent positive linear correlation between a measure of the range of significant autocorrelation in the SGI series, mmax, and qmax across all sites. Given this correlation between SGI mmax and SPI qmax, and given that periods of low values of SGI can be shown to coincide with previously independently documented droughts, SGI is taken to be a robust and meaningful index of groundwater drought. The maximum length of groundwater droughts defined by SGI is an increasing function of mmax, meaning that relatively long groundwater droughts are generally more prevalent at sites where SGI has a relatively long autocorrelation range. Based on correlations between mmax, average unsaturated zone thickness and aquifer hydraulic diffusivity, the source of autocorrelation in SGI is inferred to be dependent on dominant aquifer flow and storage characteristics. For fractured aquifers, such as the Cretaceous Chalk, autocorrelation in SGI is inferred to be primarily related to autocorrelation in the recharge time series, while in granular aquifers, such as the Permo–Triassic sandstones, autocorrelation in SGI is inferred to be primarily a function of intrinsic saturated flow and storage properties of aquifer. These results highlight the need to take into account the hydrogeological context of groundwater monitoring sites when designing and interpreting data from groundwater drought monitoring networks.

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Groundwater-level and storage-volume changes in the Equus Beds aquifer near Wichita, Kansas, predevelopment through January 2015

Scientific Investigations Report ◽

10.3133/sir20155121 ◽

2015 ◽

Cited By ~ 1

Author(s):

Joshua A. Whisnant ◽

Cristi V. Hansen ◽

Patrick J. Eslick

Keyword(s):

Groundwater Level ◽

Volume Changes ◽

Storage Volume ◽

And Storage

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An Overview of Digital Image Processing and Recognition (Invited Paper)

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100055837 ◽

1982 ◽

Vol 40 ◽

pp. 700-702

Author(s):

R. C. Gonzalez

Keyword(s):

Image Processing ◽

New York ◽

Digital Image Processing ◽

Digital Image ◽

Practical Implementation ◽

Submarine Cable ◽

Vigorous Growth ◽

Digitized Pictures ◽

Processing Techniques ◽

And Storage

Interest in digital image processing techniques dates back to the early 1920's, when digitized pictures of world news events were first transmitted by submarine cable between New York and London. Applications of digital image processing concepts, however, did not become widespread until the middle 1960's, when third-generation digital computers began to offer the speed and storage capabilities required for practical implementation of image processing algorithms. Since then, this area has experienced vigorous growth, having been a subject of interdisciplinary research in fields ranging from engineering and computer science to biology, chemistry, and medicine.

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Control of Secretory Production in the Isopod Hepatopancreas

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100094085 ◽

1972 ◽

Vol 30 ◽

pp. 166-167

Author(s):

John W. Roberts ◽

E. R. Witkus

Keyword(s):

B Cells ◽

Morphological Data ◽

Secretory Product ◽

Secretory Function ◽

Secretory Material ◽

Blind Ending ◽

Secretory Production ◽

Regenerative Cells ◽

Immature Cells ◽

And Storage

The isopod hepatopancreas, as exemplified by Oniscus ascellus. is comprised of four blind-ending diverticula. The regenerative cells at the tip of each diverticula differentiate into either club-shaped B-cells, which serve a secretory function, or into conoid S-cells, which serve in the absorption and storage of nutrients.The glandular B-cells begin producing secretory material with the development of rough endoplasmic reticulum during their process of maturation from the undifferentiated regenerative cells. Cytochemical and morphological data indicate that the hepatopancreas sequentially produces two types of secretory material within the large club-shaped cells. The production of the carbohydrate-like secretory product in immature cells seems to be phased out as the production of the osmiophilic secretion was phased in as the cell matured.

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Quantitative Analysis Of X-Ray Images From Geological Materials

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s042482010013482x ◽

1990 ◽

Vol 48 (2) ◽

pp. 244-245

Author(s):

J. M. Paque ◽

R. Browning ◽

P. L. King ◽

P. Pianetta

Keyword(s):

Quantitative Analysis ◽

Bulk Composition ◽

Principal Component ◽

Analytical Description ◽

Bulk Sample ◽

Geological Samples ◽

X Ray ◽

Software And Hardware ◽

And Storage ◽

Insight Into

Geological samples typically contain many minerals (phases) with multiple element compositions. A complete analytical description should give the number of phases present, the volume occupied by each phase in the bulk sample, the average and range of composition of each phase, and the bulk composition of the sample. A practical approach to providing such a complete description is from quantitative analysis of multi-elemental x-ray images.With the advances in recent years in the speed and storage capabilities of laboratory computers, large quantities of data can be efficiently manipulated. Commercial software and hardware presently available allow simultaneous collection of multiple x-ray images from a sample (up to 16 for the Kevex Delta system). Thus, high resolution x-ray images of the majority of the detectable elements in a sample can be collected. The use of statistical techniques, including principal component analysis (PCA), can provide insight into mineral phase composition and the distribution of minerals within a sample.

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