On identifie simultanément les coefficients d'emmagasinement et de transmissivité hydraulique dans un écoulement souterrain gouvernent par une équation parabolique linéaire. Ces deux paramètres sont supposés être des fonctions constantes par morceaux en espace. Les inconnues du problème sont non seulement les valeurs de ces coefficients mais aussi la géométrie des zones dans lesquelles ces coefficients sont constants. Le problème est formule comme la minimisation d'une fonction de moindres carres calculant la différence entre les mesures et les quantités correspondantes évaluées avec la valeur courante des paramètres. L'objectif principal de ce travail est la construction d'une technique de paramétrisation adaptative guidée par des indicateurs de raffinement. L'utilisation d'indicateurs de raffinement, nous permet de construisons la paramétrisation de façon itérative, on allant d'une paramétrisation à une seule zone à une paramétrisation avec m zones où m est une valeur optimale à identifier. Nous distinguons les cas ou les deux paramètres ont la même paramétrisation et le cas où les deux paramètres ont des paramétrisations différentes. Pour améliorer la résolution du problème inverse d'estimation de paramètres, nous incorporons des estimateurs d'erreurs a posteriori. / We identify simultaneously storage and hydraulic transmissivity coefficients in groundwater flow governed by a linear parabolic equation. Both parameters are assumed to be functions piecewise constant in space. The unknowns are the coefficient values as well as the geometry of the zones where these coefficients are constant. This problem is formulated as minimizing a least-square function calculating the difference between measurements and the corresponding quantities computed with the current parameters values. The main point of this work is to construct an adaptative parameterization technique guided by refinement indicators. Using refinement indicators, we build the parameterization iteratively, going from a one zone parametrization to a parametrization with $m$ zones where $m$ is an optimal value to identify. We distinguish the cases where the two parameters have the same parameterization and different parameterizations.\\ To improve the resolution of the inverse problem, we incorporate a posteriori error estimations.

The overall goal of this dissertation is to determine and develop optimal strategies for inversely calibrating transmissivities (T), elastic and inelastic skeletal storage coefficients (Ske and Skv) of the developed-zone aquifer and conductance (CR) of the basin-fill faults for the entire Las Vegas basin, and to investigate future trends of land subsidence in Las Vegas Valley. This dissertation consists of three separate stand-alone chapters. Chapter 2 presents a discrete adjoint parameter estimation (APE) algorithm for automatically identifying suitable hydraulic parameter zonations from hydraulic head and subsidence measurements. Chapter 3 compares three different inversion strategies to determine the most accurate and computationally efficient method for estimating T and Ske and Skv at the basin scale: the zonation method (ZM), the adaptive multi-scale method and the Differential Evolution Adaptive Metropolis Markov chain Monte Carlo scheme (DREAM MCMC). Chapter 4 outlines a fine-scale numerical model capable of capturing far more hydrologic detail than any previously developed model of Las Vegas Valley The new model is calibrated using high-resolution InSAR data and hydraulic head data from 1912 to 2010. The calibrated model is used to investigate the influence of faults and their potential role on influencing clay thicknesses and land subsidence distributions, and to investigate future trends of land subsidence in Las Vegas Valley. / Ph. D.

From the Proceedings of the 1971 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 22-23, 1971, Tempe, Arizona / Much future computer modeling of the responses of groundwater to water development stresses may be poorly done if the errors and limitations of digital models are not fully appreciated by groundwater hydrologists. Two digital models were constructed of the Tucson basin, one with 1,890 nodes of 1/4 square mile area each and one with 509 nodes of 1 square mile each. The starting point for the digital model was the 2-dimensional, linear, parabolic, time-and space-invariant differential equation of incompressible flow through porous media. An explicit finite-difference equivalent was determined, and a set of 1,890 equations were put in implicit form and solved on a computer in less than 20 seconds at a cost of 2.00 dollars. The errors associated with the model are discussed. In deciding what new data collected in the Tucson basin would give the most improvement in the digital model, a statistical decision theory approach was utilized in which expected opportunity loss and expected worth of sample were calculated for 5 variables. The data was computed using about 110 seconds of computer time, costing about 13.00 dollars. This technique has the advantage of including basin dynamics in estimating worth of additional data by means of using the digital model to compute all values of predicted and 'true' water levels included in the loss function.

This interdisciplinary doctoral dissertation addresses land subsidence in different and diverse study cases in the world, employing advanced techniques and methodologies to measure their magnitude and comprehensively explore its causes, and implications. Investigating areas such as the San Luis Potosi metropolitan area, Alaşehir-Sarıgöl sub-basin (ASSB) in Türkiye, and the Alto Guadalentín Valley in Spain, the research unveils critical insights into the complex dynamics of subsidence phenomena. Utilizing advanced remote sensing techniques like Persistent Scatterer Interferometry (PSI) and Coherent Pixels Technique (CPT), the study assesses subsidence rates and correlates them with factors such as trace faults, groundwater extraction, and soft soil thickness. Validation methodologies were developed and proposed to the scientific community on the first stage, integrating Global Navigation Satellite System (GNSS) benchmarks, enhance the reliability of Differential Synthetic Aperture Radar Interferometry (DInSAR) measurements, ensuring a robust foundation for subsequent analyses. The research aims to contribute to the understanding of land subsidence and contribute to create a decision-support framework to mitigate the phenomenon while addressing specific research objectives within each identified topic of inquiry. The research topic 1 includes the “DInSAR for monitoring land subsidence in overexploited aquifers”. In the San Luis Potosi metropolitan area (Mexico), the application of CPT technique reveals intriguing correlations between trace faults, land subsidence, and groundwater extraction. Specifically, areas in the municipality of Soledad de Graciano Sánchez exhibit subsidence values ranging between -1.5 and -3.5 cm/year, while in San Luis Potosi, values range from -1.8 to -4.2 cm/year. The validation of CPT results against five Global Navigation Satellite System (GNSS) benchmarks establishes a robust correlation of 0.986, underlining the reliability of InSAR-derived deformations. Additionally, in regions like the Alaşehir-Sarıgöl sub-basin (Türkiye), where water stress is heightened due to intensive agricultural irrigation, the study explores the roles of tectonic activity and groundwater withdrawal in land subsidence. Utilizing the P-SBAS algorithm, 98 Sentinel-1 SAR images in ascending orbits and 123 in descending orbits were analysed, covering the period from 2016 to 2020. Independent Component Analysis was applied to distinguish long-term displacements from seasonal variations in the DInSAR time series data. Displacement rates of up to -6.40 cm/year were identified, thus, the proposed P-SBAS algorithm facilitates the monitoring of displacement, revealing direct correlations between DInSAR displacement and critical factors like aquitard layer compaction. These findings contribute valuable insights into the dynamic interactions shaping overexploited aquifers. The research topic 2, developing parallelly to topic 1, consists of the “Validation of DInSAR data applied to land subsidence areas”. Addressing the imperative for validation methodologies in subsidence assessments, a systematic approach introduces statistical analyses and classification schemes. This methodology is designed to validate and refine DInSAR data, enhancing the reliability of subsidence assessments. By normalizing Root Mean Square Error (RMSE) parameters with the range and average of in-situ deformation values and employing the squared Pearson correlation coefficient (R²), a classification scheme is established. This scheme facilitates the acceptance/rejection of DInSAR data for further analyses through the application of automatic analysis supported by a Matlab © code, ensuring a more accurate representation of land subsidence phenomena. The research topic 3 covers the exploitation of DInSAR data for assessing flooding potential and determining characteristic parameters of aquifer systems. The first one is “Impact of land subsidence on flood patterns”. The study in the Alto Guadalentín Valley, a region experiencing extreme flash floods jointly with high-magnitude land subsidence, integrates flood event models, Differential interferometric SAR (DInSAR) techniques, and 2D hydraulic flow models. Through Synthetic Aperture Radar (SAR) satellite images and DInSAR, land subsidence's magnitude and spatial distribution are quantified. The results demonstrate significant changes in water surface elevation between the two 1992 and 2016 temporal scenarios, leading to a 2.04 km² increase in areas with water depths exceeding 0.7 m. These outcomes, incorporated into a flood risk map and economic flood risk assessment, underscore the pivotal role of land subsidence in determining inundation risk and its socio-economical implications. The research offers a valuable framework for enhancing flood modelling by considering the intricate dynamics of land subsidence. The second application of DInSAR data is about the “Automatic calculation of skeletal storage coefficients in aquifer systems”. In response to the need for automating data analysis for specific storage coefficients in aquifer systems, a MATLAB© application is introduced. This application streamlines the correlation between piezometric levels and ground deformation, significantly reducing analysis time and mitigating potential human interpretation errors. The developed application integrates temporal groundwater level series from observation wells and ground deformation data measured by in-situ or remote sensing techniques (e.g., DInSAR). Through the automatic construction of stress-strain curves, the application contributes to the estimation of skeletal storage coefficients, offering a valuable tool for evaluating aquifer system behaviours. This comprehensive research, guided by the complexities of these three distinct research topics, yields detailed insights and methodological advancements. By integrating diverse datasets and employing advanced techniques, this dissertation offers a multidimensional understanding of land subsidence dynamics and provides a robust foundation for sustainable groundwater management globally. / This research is funded by the PRIMA Programme supported by the European Union (Grant agreement 1924), project RESERVOIR.

From the Proceedings of the 1974 Meetings of the Arizona Section - American Water Resources Assn. and the Hydrology Section - Arizona Academy of Science - April 19-20, 1974, Flagstaff, Arizona / The inner basin is a collapse and erosional feature in San Francisco Mountain, an extinct volcano of late Cenozoic age, which lies approximately eight miles north of flagstaff, Arizona. The main aquifer's coefficient of transmissibility is approximately 14,000 gallons per day per foot and the storage coefficient was 0.08. Aquifer boundaries increased rates of drawdown of water levels in the inner basin well field. Inner basin springs which issue from perched reservoirs are not affected by pumpage of inner basin wells. Recharge is greater than the average yield from springs and wells in the basin which has an average of 8,000 acre-feet of water in storage in the principal aquifer. A large amount of water is lost from the inner basin aquifer system via leakage into underlying fractured volcanic rocks. It is believed that a part of this water could be intercepted by pumpage from a well constructed in the interior valley.