Estimation of aquifers hydraulic parameters by three different tecniques: geostatistics, correlation and modeling

Characterization of aquifers hydraulic parameters is a difficult task that requires field information. Most of the time the hydrogeologist relies on a group of values coming from different test to interpret the hydrogeological setting and possibly, generate a model. However, getting the best from this information can be challenging. In this thesis, three cases are explored. First, hydraulic conductivities associated with measurement scale of the order of 10−1 m and collected during an extensive field campaign near Tübingen, Germany, are analyzed. Estimates are provided at coinciding locations in the system using: the empirical Kozeny-Carman formulation, providing conductivity values, based on particle size distribution, and borehole impeller-type flowmeter tests, which infer conductivity from measurements of vertical flows within a borehole. Correlation between the two sets of estimates is virtually absent. However, statistics of the natural logarithm of both sets at the site are similar in terms of mean values and differ in terms of variogram ranges and sample variances. This is consistent with the fact that the two types of estimates can be associated with different (albeit comparable) measurement (support) scales. It also matches published results on interpretations of variability of geostatistical descriptors of hydraulic parameters on multiple observation scales. The analysis strengthens the idea that hydraulic conductivity values and associated key geostatistical descriptors inferred from different methodologies and at similar observation scales (of the order of tens of cm) are not readily comparable and should not be embedded blindly into a flow (and eventually transport) prediction model. Second, a data-adapted kernel regression method, originally developed for image processing and reconstruction is modified and used for the delineation of facies. This non-parametric methodology uses both the spatial and the sample value distribution, to produce for each data point a locally adaptive steering kernel function, self-adjusting the kernel to the direction of highest local spatial correlation. The method is shown to outperform the nearest-neighbor classification (NNC) in a number of synthetic aquifers whenever the available number of data is small and randomly distributed. Still, in the limiting case, when the domain is profusely sampled, both the steering kernel method and the NNC method converge to the true solution. Simulations are finally used to explore which parameters of the locally adaptive kernel function yield optimal reconstruction results in typical field settings. It is shown that, in practice, a rule of thumb can be used to get suboptimal results, which are best when key prior information such as facies proportions is used. Third, the effect of water temperature fluctuation on the hydraulic conductivity profile of coarse sediments beneath an artificial recharge facility is model and compared with field data. Due to the high permeability, water travels at a high rate, and therefore also water with different temperature is also present on the sediment under the pond at different moments, this translates into different hydraulic conductivity values within the same layer, even though all the other parameters are the same for this layer. Differences of almost 79% in hydraulic conductivity were observed for the model temperatures (2 °C – 25 °C). This variation of hydraulic conductivity in the sediment below the infiltration pond when water with varying temperature enters the sediment, causes the infiltration velocity to change with time and produces the observed fluctuation on the field measurements.La caracterización de los parámetros hidráulicos de los acuíferos es una tarea difícil que requiere información de campo. La mayoría de las veces el hidrogeólogo se basa en un grupo de valores procedentes de diferentes pruebas para interpretar la configuración hidrogeológica y posiblemente , generar un modelo . Sin embargo, obtener lo mejor de esta información puede ser un reto. En esta tesis se analizan tres casos. Primero, se analizan las conductividades hidráulicas asociadas a una escala de medición del orden de 10 m− 1 y obtenidas durante una extensa campaña de campo cerca de Tübingen, Alemania. Las estimaciones se obtuvieron en puntos coincidentes en el sitio, mediante: la formulación empírica de Kozeny - Carman, proporcionando valores de conductividad, con base en la distribución de tamaño de partículas y las pruebas del medidor de caudal de tipo impulsor en el pozo, el cual infiere las medidas de conductividad a partir de los flujos verticales dentro de un pozo. La correlación entre los dos conjuntos de estimaciones es prácticamente ausente. Sin embargo, las estadísticas del logaritmo natural de ambos conjuntos en el lugar son similares en términos de valores medios y difieren en términos de rangos del variograma y varianzas de muestra. Esto es consecuente con el hecho de que los dos tipos de estimaciones pueden estar asociados con escalas de apoyo de medición diferentes (aunque comparables). También coincide con los resultados publicados sobre la interpretación de la variabilidad de los descriptores geoestadísticos de parámetros hidráulicos en múltiples escalas de observación . El análisis refuerza la idea de que los valores de conductividad hidráulica y descriptores geoestadísticos clave asociados al inferirse de diferentes metodologías y en las escalas de observación similares (en el caso del orden de decenas de cm) no son fácilmente comparables y debe ser utilizados con cuidado en la modelación de flujo (y eventualmente, el transporte) del agua subterránea. En segundo lugar, un método de regresión kernel adaptado a datos, originalmente desarrollado para el procesamiento y la reconstrucción de imágenes se modificó y se utiliza para la delimitación de las facies. Esta metodología no paramétrica utiliza tanto la distribución espacial como el valor de la muestra, para producir en cada punto de datos una función kernel de dirección localmente adaptativo, con ajuste automático del kernel a la dirección de mayor correlación espacial local. Se demuestra que este método supera el NNC (por su acrónimo en inglés nearest-neighbor classification) en varios casos de acuíferos sintéticos donde el número de datos disponibles es pequeño y la distribución es aleatoria. Sin embargo, en el caso límite, cuando hay un gran número de muestras, tanto en el método kernel adaptado a la dirección local como el método de NNC convergen a la solución verdadera. Las simulaciones son finalmente utilizadas para explorar cuáles parámetros de la función kernel localmente adaptado dan resultados óptimos en la reconstrucción de resultados en escenarios típicos de campo. Se demuestra que, en la práctica, una regla general puede ser utilizada para obtener resultados casi óptimos, los cuales mejoran cuando se utiliza información clave como la proporción de facies. En tercer lugar, se modela el efecto de la fluctuación de la temperatura del agua sobre la conductividad hidráulica de sedimentos gruesos debajo de una instalación de recarga artificial y se compara con datos de campo. Debido a la alta permeabilidad, el agua se desplaza a alta velocidad alta, y por lo tanto, agua con temperatura diferente también está presente en el sedimento bajo el estanque en diferentes momentos, esto se traduce en diferentes valores de conductividad hidráulica dentro de la misma capa, a pesar de que todos los demás parámetros son los mismos para esta capa. Se observaron diferencias de casi 79 % en la conductividad hidráulica en el modelo, para las temperaturas utilizadas (2 º C - 25 º C ). Esta variación de la conductividad hidráulica en el sedimento por debajo de la balsa de infiltración cuando el agua de temperatura variable entra en el sedimento, causa un cambio en la velocidad de infiltración con el tiempo y produce las fluctuacciones observadas en las mediciones de campo

Infilitration tests at the Sant Vicenç dels Horts artificial recharge experimental site

Infiltration capacity is the key parameter in an artificial recharge operation site. Infiltration capacity is spatially variable, and during operation it is also temporally variable due to surface clogging processes. Double-ring infiltrometer tests were performed at an experimental site close to Barcelona city (Spain). The site is located on alluvial deposits from the Llobregat River and comprises two half hectare ponds. River water collected upstream traveled through a two km pipe before entering the settling pond. Once the pond is filled water flows to the infiltration pond. Tests were performed only in the latter, prior to and after recharging the ponds. Prior to recharge, six points were selected to estimate infiltration capacity Points were evenly distributed and chosen considering apparent soil texture at the site (coarse, medium and fine grains). All tests were performed allowing water to infiltrate for two hours and data was interpreted using the modified Kostiakov equation. Ponds were then flooded for about two months. The average infiltration rate values for the full infiltration pond before and after the flooding campaign were 5.8 m/day and 2.2 m/day, respectively. The double ring tests were then repeated at the same points, showing a reduction of the infiltration rate that varied between 7 and 90%. Control points with the initial highest infiltration rates presented the highest reduction in infiltration. Physical clogging due to particles settling appears to be the most likely cause of the diminished infiltration rates. This result is confirmed by other independent measurements during the flooding test. There is a clear tendency towards a lower infiltration rates when observing the relation through time of flow entering per volume of water on the infiltration pond at a given time.Peer ReviewedPostprint (published version

A locally adaptive kernel regression method for facies delineation

Facies delineation is defined as the separation of geological units with distinct intrinsic characteristics (grain size, hydraulic conductivity, mineralogical composition). A major challenge in this area stems from the fact that only a few scattered pieces of hydrogeological information are available to delineate geological facies. Several methods to delineate facies are available in the literature, ranging from those based only on existing hard data, to those including secondary data or external knowledge about sedimentological patterns. This paper describes a methodology to use kernel regression methods as an effective tool for facies delineation. The method uses both the spatial and the actual sampled values to produce, for each individual hard data point, a locally adaptive steering kernel function, self-adjusting the principal directions of the local anisotropic kernels to the direction of highest local spatial correlation. The method is shown to outperform the nearest neighbor classification method in a number of synthetic aquifers whenever the available number of hard data is small and randomly distributed in space. In the case of exhaustive sampling, the steering kernel regression method converges to the true solution. Simulations ran in a suite of synthetic examples are used to explore the selection of kernel parameters in typical field settings. It is shown that, in practice, a rule of thumb can be used to obtain suboptimal results. The performance of the method is demonstrated to significantly improve when external information regarding facies proportions is incorporated. Remarkably, the method allows for a reasonable reconstruction of the facies connectivity patterns, shown in terms of breakthrough curves performance

A quick and inexpensive method to quantify spatially variable infiltration capacity for artificial recharge ponds using photographic images

The efficiency of artificial surface ponds (SPs) for managed aquifer recharge (MAR) is mostly controlled by the topmost portion of the soil. The most significant soil property controlling recharge is the infiltration capacity (Ic), which is highly variable in space. Assessing its spatial distribution in detail is prohibitive in practice due to high costs, time effort, and limited site accessibility. We present an alternative method for a quick and low-cost quantitative estimation of the spatial distribution of Ic based on satellite images. The fact that hydraulic properties of topsoils and color intensities of digital images depend on some common factors such as moisture content, nature and organization of grains, proportion of iron, and organic and clay content among others, allow us to infer infiltration capacities from color intensities. The relationship between these two variables is site specific and requires calibration. A pilot SP site in Catalonia (Spain) is used as an application example. Two high-resolution digital images of the site are provided at no cost by the local cartographic institute as well as from a popular Internet-based map server. An initial set of local infiltration experiments, randomly located, were found to correlate to color intensities of the digital images. This relationship was then validated against additional independent measurements. The resulting maps of infiltration were then used to estimate the total maximum infiltration of the artificial pond area, the results being consistent with an independent flooding test performed at the site

Quantitative comparison of impeller-flowmeter and particle-size-distribution techniques for the characterization of hydraulic conductivity variability

Hydraulic conductivities associated with measurement scale of the order of 10–1 m and collected during an extensive field campaign near Tübingen, Germany, are analyzed. Estimates are provided at coinciding locations in the system using: (1) the empirical Kozeny-Carman formulation, providing conductivity values, K GS, based on particle-size distribution, and (2) borehole impeller-type flowmeter tests, which infer conductivity, K FM, from measurements of vertical flows within a borehole. Correlation between the two sets of estimates is virtually absent. However, statistics of the natural logarithm of K GS and K FM at the site are similar in terms of mean values (averages of ln K GS being slightly smaller) and differ in terms of variogram ranges and sample variances. This is consistent with the fact that the two types of estimates can be associated with different (albeit comparable) measurement (support) scales. It also matches published results on interpretations of variability of geostatistical descriptors of hydraulic parameters on multiple observation scales. The analysis strengthens the idea that hydraulic conductivity values and associated key geostatistical descriptors inferred from different methodologies and at similar observation scales (of the order of tens of cm) are not readily comparable and should not be embedded blindly into a flow (and eventually transport) prediction model

Combining physical-based models and satellite images for the spatio-temporal assessment of soil infiltration capacity

The performance of managed artificial recharge (MAR) facilities by means of surface ponds (SP) is controlled by the temporal evolution of the global infiltration capacity Ic of topsoils. Cost-effective maintenance operations that aim to maintain controlled infiltration values during the activity of the SP require the full knowledge of the spatio-temporal variability of Ic. This task is deemed uncertain. The natural reduction in time of Ic depends on complex physical, biological and chemical reactions that clog the soil pores and has been observed to decay exponentially to an asymptotic non-zero value. Moreover, the relative influence of single clogging processes depend on some initial parameters of the soil, such as the initial infiltration capacity (Ic,0). This property is also uncertain, as aquifers are typically heterogeneous and scarcely characterized in practical situations. We suggest a method to obtain maps of Ic using a geostatistical approach, which is suitable to be extended to engineering risk assessment concerning management of SP facilities. We propose to combine geostatistical inference and a temporally-lumped physical model to reproduce non-uniform clogging in topsoils of a SP, using field campaigns of local and large scale tests and additionally by means of satellite images as secondary information. We then postulate a power-law relationship between the parameter of the exponential law, k, and Ic,0. It is found that calibrating the two parameters of the power law model it is possible to fit the temporal evolution of total infiltration rate at the pond scale in a MAR test facility. The results can be used to design appropriate measures to selectively limit clogging during operation, extending the life of the infiltration pond. The performance of managed artificial recharge (MAR) facilities by means of surface ponds (SP) is controlled by the temporal evolution of the global infiltration capacity Ic of topsoils. Cost-effective maintenance operations that aim to maintain controlled infiltration values during the activity of the SP require the full knowledge of the spatio-temporal variability of Ic. This task is deemed uncertain. The natural reduction in time of Ic depends on complex physical, biological and chemical reactions that clog the soil pores and has been observed to decay exponentially to an asymptotic non-zero value. Moreover, the relative influence of single clogging processes depend on some initial parameters of the soil, such as the initial infiltration capacity (Ic,0). This property is also uncertain, as aquifers are typically heterogeneous and scarcely characterized in practical situations. We suggest a method to obtain maps of Ic using a geostatistical approach, which is suitable to be extended to engineering risk assessment concerning management of SP facilities. We propose to combine geostatistical inference and a temporally-lumped physical model to reproduce non-uniform clogging in topsoils of a SP, using field campaigns of local and large scale tests and additionally by means of satellite images as secondary information. We then postulate a power-law relationship between the parameter of the exponential law, ¿, and Ic,0. It is found that calibrating the two parameters of the power law model it is possible to fit the temporal evolution of total infiltration rate at the pond scale in a MAR test facility. The results can be used to design appropriate measures to selectively limit clogging during operation, extending the life of the infiltration pon

Quantitative comparison of impeller flowmeter and particle-size dsitribution techniques for the characterization of hydraulic conductivity variability

Basic univariate statistics and key geostatistical parameters of estimates of hydraulic conductivity obtained at the decimeter scale by two different methods are presented and compared. The two estimates are based on (1) the empirical Kozeny-Carman formulation, and (2) impeller flowmeter tests. The former provides values of conductivity, KGS, based on particle size distributions. Impeller flowmeter techniques allow inferring conductivities, KFM, from measurements of vertical flows within a borehole. Data obtained during an extensive monitoring campaign at an experimental site located near the city of Tübingen, Germany, are considered. Statistics of the natural logarithm of KGS and KFM at the site are similar in terms of mean values (with averages of ln KGS being slightly smaller than those of ln KFM) and differ in terms of variogram ranges and sample variances. The correlation between the two sets of estimates is virtually absent. Additional data from two different sites already presented in the literature allow comparing conductivity estimates from flowmeter and grain-size distributions (or permeameter measurements) taken at adjacent wells and support the finding that KGS and KFM lack correlation. The analysis highlights the difficulty in obtaining meaningful quantitatively comparable hydraulic conductivity data at the decimetric scale.Peer ReviewedPostprint (published version

Probabilistic analysis of maintenance and operation of artificial recharge ponds

      Aquifer artificial recharge from surface infiltration ponds is often conducted to replenish depleted aquifers in arid and semi-arid zones. Physical and bio-geochemical clogging decreases the host soil’s infiltration capacity, which has to be restored with periodic maintenance activities. We develop a probabilistic modeling framework that quantifies the risk of a pond’s infiltration capacity falling below its target value due to soil heterogeneity and clogging. This framework can act as a tool to aid managers in optimally selecting and designing maintenance strategies. Our model enables one to account for a variety of maintenance strategies that target different clogging mechanisms. The framework is applied to an existing pond in Barcelona, Spain as well as to several synthetic infiltration ponds with varying statistical distributions of initial infiltration capacity. We find that physical clogging mechanisms induce the greatest uncertainty and that maintenance targeted at these can yield optimal results. However, considering the fundamental role of the spatial variability in the initial properties, we conclude that an adequate initial characterization of the surface infiltration ponds is crucial to determining the degree of uncertainty of different maintenance solutions and thus to making cost-effective and reliable decisions. &nbsp

Cantonal location of the articles on hydrogeology in the Central American Journal of Geology

Desde 1984, cuando la Revista Geológica de América Central se empezó a publicar, se han presentado 36 artículos en el campo de la hidrogeología, de estos, 24 corresponden con trabajos que presentan un área de estudio dentro de Costa Rica. En este trabajo se presentan los cantones que han formado parte de las zonas de estudio de estos artículos. Además se comenta sobre la frecuencia con que se publican artículos sobre este tópico. Finalmente, se comenta sobre las posibles razones por las que algunos cantones concentran más investigaciones hidrogeológicas que otrosSince 1984, when The Central American Journal of Geology was first published, 36 papers have been presented within the field of hydrogeology, of which 24 have a study zone within Costa Rica. In this paper are presented the cantons that have been part of the study areas in these articles, along with the frequency with which articles on this topic are published. Finally, the possible reasons behind the concentration of hydrogeological research in some areas are explore

Hydrochemistry of the surface waters at the Rincon River Basin, Osa Peninsula, Costa Rica

The Rincon River Basin is characterized by steep and rugged topography with outcrops of recent sediments as well as igneous and sedimentary rocks. The area is mostly covered by forest (Tropical Wet Forest) and agricultural land, with some scattered towns. The basin collects water from a total area of 209,8km2. Water samples were taken along the dry, transition and rainy seasons of 2004 and 2005, through six sampling campaigns and 11 selected sites in the study area. The waters are characterized by an average temperature of 26,8°C, and an average dissolved oxygen concentration of 7,7mg O2/L. The average electrical conductivity (EC) was 161,8μS/cm. They are moderately soft with a range of pH values between 6,62 and 8,17 and a maximum change of 0,5pH units. The bicarbonate concentration ranged from 54,3mg HCO3/L up to 160,8mg HCO3/L. They meet the criteria for calcium bicarbonate waters.La cuenca del río Rincón tiene una densidad poblacional de alrededor de 30 habitantes por km2, un área total de 209,8 km2 y el río una longitud de 29 km, posee varios tributarios entre ellos el río Riyito, el río Pavón y una gran cantidad de pequeñas quebradas entre las cuales están Agua buena y Banegas. En ella afloran unidades de roca ígnea y sedimentaria, además de sedimentos recientes. En general, se caracteriza por su topografía abrupta y quebrada. En esta zona se halla un gran número de hábitats tropicales, predominantemente bosque muy húmedo Tropical hasta el bosque muy húmedo-Premontano transición a basal. El objetivo principal planteado para este estudio consistió en conocer la calidad química de las aguas superficiales de la cuenca del río Rincón en la Península de Osa. Para ello se seleccionaron 11 sitios de muestreo distribuidos en el área del estudio y en cada uno de ellos se tomaron seis muestras a lo largo de la época seca, la de transición y la lluviosa del año 2004–2005. Las aguas superficiales de la cuenca del río Rincón se caracterizaron por presentar una temperatura promedio de 26,8°C y una concentración promedio de oxígeno disuelto de 7,7mg O2/L. Las aguas de la cuenca se clasifican como aguas moderadamente suaves. El ámbito de valores de pH medidos en la cuenca estuvo entre 6,62 y 8,17, con una variación promedio de 0,5 unidades. La conductividad promedio en la cuenca fue 161,8μS/cm. El ámbito de concentraciones de bicarbonato fue de 54,3mg HCO3/L a 160,8mg HCO3/L. Según la clasificación de Piper las aguas superficiales de la cuenca del río Rincón son bicarbonatadas cálcicas. La calidad del agua superficial de la cuenca del río Rincón es apta para la preservación y la conservación de la vida acuática.Universidad de Costa Rica/[802-A6-104]/UCR/Costa RicaUCR::Vicerrectoría de Investigación::Unidades de Investigación::Ciencias Básicas::Centro en Investigación en Contaminación Ambiental (CICA)UCR::Vicerrectoría de Docencia::Ciencias Básicas::Facultad de Ciencias::Escuela Centroamericana de Geologí