Analysis of nonintrinsic spatial variability by residual kriging with application to regional groundwater levels

Neuman, Shlomo P.; Jacobson, E.A.

doi:10.1007/bf01886329

Cited by 155 publications

(80 citation statements)

References 9 publications

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“…Kriging of various forms has been used to interpolate maps of potentiometric surfaces from water table data (Delhomme, 1978;Neuman and Jacobsen, 1984;ASCE, 1990). The goal of most research of this nature is how to best interpolate discrete spatial observations into full coverage.…”

Section: Introductionmentioning

confidence: 99%

Geostatistical investigation into the temporal evolution of spatial structure in a shallow water table

Lyon

Seibert

Lembo

et al. 2006

Hydrol. Earth Syst. Sci.

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Abstract. Shallow water tables near-streams often lead to saturated, overland flow generating areas in catchments in humid climates. While these saturated areas are assumed to be principal biogeochemical hot-spots and important for issues such as non-point pollution sources, the spatial and temporal behavior of shallow water tables, and associated saturated areas, is not completely understood. This study demonstrates how geostatistical methods can be used to characterize the spatial and temporal variation of the shallow water table for the near-stream region. Event-based and seasonal changes in the spatial structure of the shallow water table, which influences the spatial pattern of surface saturation and related runoff generation, can be identified and used in conjunction to characterize the hydrology of an area. This is accomplished through semivariogram analysis and indicator kriging to produce maps combining soft data (i.e., proxy information to the variable of interest) representing general shallow water table patterns with hard data (i.e., actual measurements) that represent variation in the spatial structure of the shallow water table per rainfall event. The area used was a hillslope in the Catskill Mountains region of New York State. The shallow water table was monitored for a 120 m×180 m near-stream region at 44 sampling locations on 15-min intervals. Outflow of the area was measured at the same time interval. These data were analyzed at a short time interval (15 min) and at a long time interval (months) to characterize the changes in the hydrologic behavior of the hillslope. Indicator semivariograms based on binary-transformed ground water table data (i.e., 1 if exceeding the time-variable median depth to water table and 0 if not) were created for both short and long time intervals. For the short time interval, the indicator semivariograms showed a high degree of spatial structure in the shallow water table for the spring, with increased range during many rain events.Correspondence to: T. S. Steenhuis (tss1@cornell.edu) During the summer, when evaporation exceeds precipitation, the ranges of the indicator semivariograms decreased during rainfall events due to isolated responses in the water table. For the longer, monthly time interval, semivariograms exhibited higher sills and shorter ranges during spring and lower sills and longer ranges during the summer. For this long time interval, there was a good correlation between probability of exceeding the time-variable median water table and the soil topographical wetness index during the spring. Indicator kriging incorporating both the short and long time interval structure of the shallow water table (hard and soft data, respectively) provided more realistic maps that agreed better with actual observations than the hard data alone. This technique to represent both event-based and seasonal trends incorporates the hillslope-scale hydrological processes to capture significant patterns in the shallow water table. Geostatistical analysis of the spatial and temp...

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Section: Introductionmentioning

confidence: 99%

Geostatistical investigation into the temporal evolution of spatial structure in a shallow water table

Lyon

Seibert

Lembo

et al. 2006

Hydrol. Earth Syst. Sci.

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“…In this study, a hybrid computational model is proposed by combining the ANN and kriging for estimating the evaporation at ungauged sites. Kriging has been recognized as a geostatistical tool for interpolating the value at a random location based on nearby information and has been applied to problems in hydrological fields (Schuurmans et al, 2007;Neuman and Jacobson, 1984;Legleiter, 2008). A number of studies have investigated the applicability of neural networks with geostatistics to environment, such as fallout (Kanevsky et al, 1996), temperature (Koike et al, 2001), etc.…”

Section: Figmentioning

confidence: 99%

A spatial neural fuzzy network for estimating pan evaporation at ungauged sites

Chung

Chiang

Chang

2012

Hydrol. Earth Syst. Sci.

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Abstract. Evaporation is an essential reference to the management of water resources. In this study, a hybrid model that integrates a spatial neural fuzzy network with the kringing method is developed to estimate pan evaporation at ungauged sites. The adaptive network-based fuzzy inference system (ANFIS) can extract the nonlinear relationship of observations, while kriging is an excellent geostatistical interpolator. Three-year daily data collected from nineteen meteorological stations covering the whole of Taiwan are used to train and test the constructed model. The pan evaporation (E pan ) at ungauged sites can be obtained through summing up the outputs of the spatially weighted ANFIS and the residuals adjusted by kriging. Results indicate that the proposed AK model (hybriding ANFIS and kriging) can effectively improve the accuracy of E pan estimation as compared with that of empirical formula. This hybrid model demonstrates its reliability in estimating the spatial distribution of E pan and consequently provides precise E pan estimation by taking geographical features into consideration.

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“…Neuman [3] (1984) and Sun [4] (1999) put forward the Residual Kriging (RK) method to presume regional groundwater levels. The basic idea is to filter trend components out of groundwater levels to get residual measured water levels, then use Ordinary Kriging(OK) method to presume space distribution of the residual water levels.…”

Section: )mentioning

confidence: 99%

Ordovician Limestone Aquifer Seepage Field Simulation Based on Modflow

Wei¹,

Yin²,

Wang³

et al. 2012

Proceedings of 2012 National Conference on Information Technology and Computer Science

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Abstract-According to the data of draining test, we simulated the Ordovician limestone aquifer seepage field by MODFLOW module of GMS (Groundwater Modeling System). After numerical simulation model building, we successfully simulated the seepage field formed by draining test and dynamic changes in the water level by model recognition and inspection. The results reflect that lateral connectivity and hydraulic connection of fissure and crevasse is weak in Ordovician limestone aquifer. The study provides theoretical base and practical references for safe mining of No.11 coal seam which is threatened by Ordovician limestone aquifer confined water.

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Analysis of nonintrinsic spatial variability by residual kriging with application to regional groundwater levels

Cited by 155 publications

References 9 publications

Geostatistical investigation into the temporal evolution of spatial structure in a shallow water table

Geostatistical investigation into the temporal evolution of spatial structure in a shallow water table

A spatial neural fuzzy network for estimating pan evaporation at ungauged sites

Ordovician Limestone Aquifer Seepage Field Simulation Based on Modflow

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