Loss Of Storage Capacity Research Articles

Framework for reservoir sedimentation estimation using the hydrological model and campaign—A case study of A Vuong Reservoir in central Vietnam

Sediment estimation would help practice sustainable watershed management and efficient reservoir operation. Different methods exist to estimate reservoir sedimentation based on the differences in sediment yield flowing in and releasing from the reservoir and successive bathymetric field measurements. This paper investigates the variability in sediment yield from watersheds and sedimentation in the A Vuong reservoir in central Vietnam using the soil and water assessment tool (SWAT) compared with bathymetry mapping. Bathymetry data were collected in 2003, 2015, and 2021 and conducted in 2022. SWAT was calibrated from 1996 to 2008 and validated from 2009 to 2020 using monthly observations. SWAT performs well and can accurately simulate monthly streamflow and sediment yield. The goodness-of-fit analyses suggested that the area list representation of the watershed behavior and satisfactory Sutcliffe efficiency (NSE = 0.86) values for streamflow were obtained during the calibration and validation periods. For sediment simulation, the efficiency is lower than streamflow's, with NSE in the validation values of 0.61. The results showed that the sedimentation estimate from the SWAT model is smaller than that from bathymetry. A Vuong reservoir's annual storage capacity loss due to sedimentation accumulation from the SWAT model and bathymetry was 0.08% and 0.38%, respectively. Based on the bathymetry data, we estimated that the average rate of sedimentation deposition of A Vuong reservoir was 1.3 Mm3/y. The average calculated net deposition value was 4.3 m (0.3 m per year) within fourteen years of operation. The study outcomes demonstrated that the framework approach may transfer to an ungauged catchment and address the complex sedimentation problem in tropical regions.

Development and characterization of mesoporous silica-MgSO4-MgCl2 binary salt composites for low-grade heat storage in fluidized bed systems

Achieving nearly zero-energy buildings requires the efficient utilization and storage of renewable energy. Salt-hydrate-based thermochemical energy storage (TCES) systems are promising due to their high heat storage capacity and minimal seasonal heat loss. However, challenges remain in their commercialization and large-scale application. For instance, TCES systems using magnesium sulphate (MgSO4) provide low temperature lifts due to slow reaction kinetics. Incorporating deliquescent salts like magnesium chloride (MgCl2) can enhance sorption performance but may introduce stability issues such as agglomeration and decomposition. This study presents a novel binary-salt composite combining MgSO4 and MgCl2 within commercial mesoporous silica (CMS) to address these challenges and enhance overall performance. The binary-salt composite powder, with a particle size range of 150–300 μm, is well-suited for use in fluidized-bed reactors, where fast mass and heat transfer promote efficient moisture adsorption, prevent uneven temperature distribution, and reduce agglomeration. Thermogravimetric analysis (TGA) was employed to evaluate the water sorption and desorption behaviour of MgCl2-MgSO4@CMS binary-salt composites with a total salt content of 50 wt% and salt mixing ratios of 3:1, 1:1, and 1:3. The corresponding water sorption capacities were 0.95, 0.68, and 0.57 g/g, respectively. In comparison, the MgSO4@CMS single-salt composite showed a lower water adsorption capacity of 0.47 g/g and required temperatures exceeding 150 °C for complete regeneration. Reactor-scale experiments demonstrated that the MgCl2-MgSO4@CMS composite with a 1:1 salt mixing ratio could be fluidized at low gas velocities on the order of 10−2 m/s, achieving a maximum temperature lift of 24.7 °C and an energy density of 1018 kJ/kg during hydration at 80% relative humidity and 30 °C. Additionally, the binary-salt composite showed good cyclic stability with less particle agglomeration compared to the MgCl2@CMS single-salt composite.

Diminished storage capacity of ponds caused by sedimentation weakens their nitrogen removal efficiency

Though their small size, ponds play a disproportionately crucial role in eliminating nitrogen (N) transporting to downstream freshwaters. As significant water infrastructures, ponds are non-sustainable due to loss of storage capacity resulting from sedimentation. However, the effects of pond sedimentation on N removal is widely neglected in landscape N processing. The NUFER (Nutrient flows in Food chains, Environment and Resources use) model was employed to estimate N runoff from 1960 to 2018. We reconstructed the dynamic of number and storing capacity of about 14 million ponds due to construction and sedimentation from 1960 to 2018, projecting these trends into the year 2060. Our approach incorporated first-order kinetic reactions, including water residence time (HRT), to estimate N removal of ponds, utilizing data 6 monitoring ponds and 81 ponds from literature studies. Our analysis reveals a fourteen-fold increase in N runoff over the past six decades, rising from 0.8 Mt N in 1960 to 11.4 Mt N in 2018. Due to the initial rapid expansion of ponds, N removal by ponds increased from 6.4 % in 1960 to 13.6 % in 1990. Sedimentation is prevalent in ponds, particularly in small ponds with a sedimentation accumulation rate of 2.96 cm yr−1. Pond sedimentation, which reduces HRT, resulted in a decrease in pond N removal percentage to 11.2 % in 2018 and a projected 7.4 % by the year 2060, assuming similar sediment accumulation rates persist in the future. Overall, our findings underscore the non-negligible role of ponds as landscape nodes in N cycling. Urgent mitigation measures are needed to extend the lifetime of existing ponds and sustain their critical role in water quality management.

Study of the impact of sediments on the mechanical behavior of concrete and towards the penetration of carbon dioxide

Dam reservoirs are exposed to a loss of water storage capacity due to the phenomenon of siltation. This particularity can be expressed by the siltation of reservoirs and the entrainment of particles transported by watercourses. Siltation of reservoirs is a critical state which causes a reduction in the storage capacity of dams. Algeria is characterized by a semi-arid climate, which annually loses a considerable volume of water storage. The carbonation of concrete is influenced by a number of parameters which accelerate its kinetics. These parameters are the porosity of the concrete, the quantity of lime contained in the cement, the concentration of CO2 in the atmosphere and the humidity of the environment. It should be noted that, water being the vector for moving aggressive agents, carbon dioxide can only diffuse through the concrete if the latter is not completely saturated and not perfectly dry at the same time. Another factor increasing the permeability of concrete is the amount of limestone added to the cement during its manufacture at the factory. This permeability allows the diffusion of CO2 or other aggressive agents in the concrete. The addition of limestone to cement must therefore be used with caution. The objective is to propose economically competitive and easy-to-implement formulations which allow the valorization of these materials in the making of ordinary concrete by partial substitution of cement (10, 20 and 30%) and its influence on the progress of long-term carbonation after six years of curing in the open air. The sediment is treated by calcination at 750°C to make it active. Natural carbonation tests were carried out on the study concretes in order to evaluate their durability. The results obtained confirmed the possibility of producing concretes incorporating calcined sludge at dosages of up to 30% without compromising the quality of these concretes from the point of view of behavior in the face of attacks by the dissolution of carbon dioxide from the air in the interstitial solution of concrete, meeting economic, ecological and technological objectives.

Bathymetric survey and volumetric analysis of Bakolori dam reservoir North West Nigeria

Many approaches have been devised for measuring water depth in bathymetric surveys, which are used to assess sediment deposited directly in lakes and reservoirs. This technique is mostly used to calculate the reservoir's capacity and the amount of sedimentation that occurs there. The results of the volumetric analysis and bathymetric survey of the Bakolori Dam reservoir, which is situated in Northwestern Nigeria, are presented in this work. During this investigation, the differential Global Positioning System receiver (GPS), automatic level measuring tool, echo-sounder, and engine boat were utilized. ArcGis 10.0 was used to analyze the acquired data. In order to evaluate the reservoir capacity loss during the Bakolori reservoir's operating period as of 1983, the designed computed reservoir capacity was compared with the current bathymetry survey. At a spillway crest elevation of 334 meters above mean sea level (amsl), the reservoir's initial capacity is reported as 430 million cubic meters (MCM). However, the capacity has since been revised to 291 meters at the same level, with a volume change of 139,269,495 m3. As a result, the reservoir's volume changed by approximately 139 MCM during a thirty-five (35) year period of service, representing a loss of storage capacity, while the annual siltation rate was around 3,979,128 m3/a. This indicated that 33% of the reservoir's storage capacity had silted up. This is demonstrated by the aquatic weeds that have grown to a height of 334.21 meters on the lake's surface, rising from the lakebed. Therefore, to prevent total siltation, the dam reservoir needs to be adequately dredged.

The relationship between hydrogen storage capacity and 4d transition metal-carbon surface binding energy

This study explores the correlation between the strength of 4d-transition metal (TM)/surface binding energy (BE) and the hydrogen storage capacity in decorated (TM@CNF) and doped (TM/CNF) carbon nanoflakes. The findings reveal smaller TM-CNF distances and larger BE for doped cases. These TM-CNF bond characteristics impact the storage capacity, with doped cases outperforming in Mo/CNF and Tc/CNF and decorated in Y@CNF and Zr@CNF scenarios. This contrasting performance underscores the difficulty in finding a surface/dopant combination for efficient storage, where the BE cannot be weak due to its stability and also cannot be too strong due to the loss of storage capacity.

Impact of reservoir construction on the sediment budget of a downstream-linked freshwater lake

ABSTRACT We investigated the magnitude of reservoir sedimentation upstream and its sediment-shadow effect on a large downstream-linked lake, Lake Tana (Ethiopia). To better understand the reservoir-induced reductions of fluvial sediment downstream, sediment budgets for two scenarios were developed. The results indicated that reservoir sedimentation is extremely high, with annual storage capacity losses (1–4.2%) exceeding the global average. Consequently, unless mitigation measures are implemented, the reservoirs’ dead storage volume will be filled with sediment in less than 42% of their designed life expectancy. The sediment-trapping conditions created by the reservoirs will also reduce sediment inflow from tributaries into the lake by 15–52%, overbank sedimentation on floodplains by 33–48%, and sediment deposition in Lake Tana by 16–54% annually. Overall, under the current environmental set-up, the ongoing and planned reservoir constructions could extend the expected useful lifetime of Lake Tana from 918 to 2022 years.

Predicting reservoir sedimentation using multilayer perceptron – Artificial neural network model with measured and forecasted hydrometeorological data in Gibe-III reservoir, Omo-Gibe River basin, Ethiopia

The estimation and prediction of the amount of sediment accumulated in reservoirs are imperative for sustainable reservoir sedimentation planning and management and to minimize reservoir storage capacity loss. The main objective of this study was to estimate and predict reservoir sedimentation using multilayer perceptron–artificial neural network (MLP-ANN) and random forest regressor (RFR) models in the Gibe-III reservoir, Omo-Gibe River basin. The hydrological and meteorological parameters considered for the estimation and prediction of reservoir sedimentation include annual rainfall, annual water inflow, minimum reservoir level, and reservoir storage capacity. The MLP-ANN and RFR models were employed to estimate and predict the amount of sediment accumulated in the Gibe-III reservoir using time series data from 2014 to 2022. ANN-architecture N4-100-100-1 with a coefficient of determination (R2) of 0.97 for the (80, 20) train-test approach was chosen because it showed better performance both in training and testing (validation) the model. The MLP-ANN and RFR models' performance evaluation was conducted using MAE, MSE, RMSE, and R2. The models’ evaluation result revealed that the MLP-ANN model outperformed the RFR model. Regarding the train data simulation of MLP-ANN and RFR shown R2 (0.99) and RMSE (0.77); and R2 (0.97) and RMSE (1.80), respectively. On the other hand, the test data simulation of MLP-ANN and RFR demonstrated R2 (0.98) and RMSE (1.32); and R2 (0.96) and RMSE (2.64), respectively. The MLP-ANN model simulation output indicates that the amount of sediment accumulation in the Gibe-III reservoir will increase in the future, reaching 110 MT in 2030–2031, 130 MT in 2050–2051, and above 137 MTin 2071–2072.

Risk Factors for Long-term Body Weight Loss After Proximal Gastrectomy: A Retrospective Analysis.

Proximal gastrectomy (PG) is a therapy for early-stage proximal gastric cancer and offers advantages such as the preservation of food storage capacity and less body weight loss (BWL). Nevertheless, significant BWL following PG may occur, affecting the patient's well-being and survival. In this study, we aimed to identify the relevant factors for BWL following PG by analyzing an institutional database of patients. We enrolled 58 consecutive patients who underwent PG for gastric or esophagogastric junction cancer at our institution between April 2004 and March 2021. Based on BWL at 12 months postoperatively, we retrospectively compared and examined patient characteristics, surgical details, and nutritional markers. The mean BWL of the 58 patients included in this analysis was 14.0±7.2%. When the patients were divided into BWL-moderate (n=29) and BWL-severe (n=29) groups using a cutoff value of 15.7%, the latter experienced early BWL within 1 month postoperatively, primarily due to body fat mass reduction, with no recovery during the 60 months of follow up. In contrast, gradual recovery was observed among patients in the BWL-moderate group after experiencing the lowest body weight 24 months postoperatively. A greater decrease in body fat mass than in muscle mass was observed in both groups. Blood hemoglobin levels did not recover in the BWL-severe group. The BWL-severe group after proximal gastrectomy demonstrated significantly greater early postoperative BWL, primarily attributed to a reduction in body fat mass, with hardly any recovery. Early postoperative nutritional intervention might be proposed to prevent long-term BWL.

Experiment and prediction for dynamic storage capacity of underground gas storage rebuilt from hydrocarbon reservoir

Understanding the variation in dynamic storage capacity is significant and meaningful to design operation strategy of underground gas storage (UGS). However, there is a lack of methods to recognize and predict dynamic storage capacity of UGS. This paper introduces a novel experimental system to directly measure rock porosity under different effective stresses. W gas storage, the biggest UGS in Central China, was taken as a case to discuss trend characteristic of dynamic storage capacity. Then a model for predicting dynamic storage capacity of UGS was further developed based on experimental results. Lastly, the prediction model was used to evaluate dynamic storage capacity after 30 operation cycles in W gas storage. Results show that porosity of reservoir rock, as well as dynamic storage capacity of UGS decreases with cyclic stress, and the loss gradually reduces with alternating stress cycle. In addition, after 30 operation cycles, the loss of dynamic storage capacity is about 1.34 × 108 m3, 1.40 % of total initial storage capacity in Zone Z1 of W gas storage, and about 0.11 × 108 m3, 1.51 % of total initial storage capacity in Zone Z2. Specially, modelling flow in this work is not only suitable for W gas storage, but also can be used to study any UGSs rebuilt from hydrocarbon reservoirs.

Towards a dynamic effective drainage area map for the Canadian Prairie: Sensitivity of contributing area to wetland storage capacity

Wetlands that occupy topographic depressions are a defining feature of the Canadian Prairie. These features control hydrological connectivity as they contain high storage capacity relative to typically available precipitation and runoff. Altering wetland distribution changes the frequency with which areas can become hydrologically connected to the catchment outlet. There are several methods that have proven successful in estimating contributing area response to changes in wetland storage, but none have been applied widely across the Canadian Prairie. The objective of this study was (1) to determine if the rate at which contributing area changes with loss of wetland storage capacity is related to wetland distribution, and if so, (2) to map sensitivity across the region. To do so, a GIS analysis was employed in which iterative measurements were made of contributing area expansion with simulated wetland storage capacity loss. Results show that those catchments with more small wetlands have more sensitive contributing areas to storage capacity loss. Extrapolation of this relationship across the Canadian Prairie shows that areas in western Manitoba and southeastern Saskatchewan are among the most sensitive. These results provide a better understanding of how contributing area may change with loss of wetland storage capacity. This may inform implementation of beneficial management practices, transportation network design, and management of streamflow and nutrient transport to downstream lakes across the region.

Modeling the optimal management of land subsidence due to aquifers overexploitation

The study of land subsidence has recently been expanded due to its increased occurrence and magnitude worldwide. This paper develops and applies an optimal control model of groundwater extractions under conditions of land subsidence. We include, in a traditional groundwater management model, two types of negative externalities associated with land subsidence: damage to infrastructure and to economic activities, and the loss of aquifer storage capacity. Using a two-stage optimal control method, characterized by two sub-problems corresponding to the phase before and after the occurrence of subsidence, we find the economically sustainable paths of groundwater extractions and water table levels under the existence of land subsidence impacts. The theoretical results indicate that the presence of land subsidence dictates the optimal paths of groundwater withdrawals and water table levels. The model has been applied to the Alto Guadalentín over-exploited aquifer system in the Segura River Basin of Spain. The empirical outcomes indicate that by following the optimal paths, groundwater extractions should be curtailing to avoid reaching the critical water level at which subsidence takes place. Results suggest that regional net present value of welfare over the planning period, under the two land subsidence scenarios, is reduced by nearly 1–5%, compared to the no land subsidence scenario. Furthermore, under subsidence, even with relatively small impacts of both types of externalities, groundwater optimal extractions are kept at levels that avoid these externalities. These outcomes clearly call for government intervention in order to reduce groundwater withdrawals in aquifers with propensity to face undesirable subsidence effects.

Pixel-Based Soil Loss Estimation and Prioritization of North-Western Himalayan Catchment Based on Revised Universal Soil Loss Equation (RUSLE)

Land degradation is a noteworthy environmental risk causing water quality issues, reservoir siltation, and loss of valuable arable lands, all of which negate sustainable development. Analysis of the effect of land use changes on erosion rate and sediment yield is particularly useful to identify critical areas and define catchment-area treatment plans. This study utilized remote sensing and geographical information system/science (GIS) techniques combined with the Revised Universal Soil Loss Equation (RUSLE) on a pixel basis to estimate soil loss over space and time and prioritized areas for action. The methodology was applied to the Sutlej catchment from the perspective of sedimentation of the Bhakra reservoir, which is leading to the loss of active storage capacity and performance and of the safety and efficiency of many existing hydroelectric projects in the Sutlej and its tributaries that drain the Himalayas. Soil loss estimation using RUSLE was first calibrated using data from three sites, and the calibrated model was then used to estimate catchment soil loss for 21 years (1995–2015). The number of land use/land cover (LULC) classes as 14 and the C factor as 0.63 for agriculture land were optimized using the observed data for the Sutlej catchment. Further, the linkage between soil erosivity and annual precipitation was also established. It was concluded that extensive control treatment would be necessary from the soil and water conservation point of view. Structures like check dams, terraces, bunds, and diversion drains in the upstream can overcome the issue of fragmentation of soil in the Sutlej catchment.

Global land subsidence mapping reveals widespread loss of aquifer storage capacity

Groundwater overdraft gives rise to multiple adverse impacts including land subsidence and permanent groundwater storage loss. Existing methods are unable to characterize groundwater storage loss at the global scale with sufficient resolution to be relevant for local studies. Here we explore the interrelation between groundwater stress, aquifer depletion, and land subsidence using remote sensing and model-based datasets with a machine learning approach. The developed model predicts global land subsidence magnitude at high spatial resolution (~2 km), provides a first-order estimate of aquifer storage loss due to consolidation of ~17 km3/year globally, and quantifies key drivers of subsidence. Roughly 73% of the mapped subsidence occurs over cropland and urban areas, highlighting the need for sustainable groundwater management practices over these areas. The results of this study aid in assessing the spatial extents of subsidence in known subsiding areas, and in locating unknown groundwater stressed regions.

Partially unzipped carbon nanotubes-CaCu3Ti4O12/ferroelectric polymer nanodielectric composites with high permittivity, high energy storage capacity and low dielectric loss

Partially unzipped carbon nanotubes-CaCu3Ti4O12/ferroelectric polymer nanodielectric composites with high permittivity, high energy storage capacity and low dielectric loss

Estimating Reservoir Sedimentation Rates and Storage Capacity Losses Using High‐Resolution Sentinel‐2 Satellite and Water Level Data

AbstractIn nearly all reservoirs, storage capacity is steadily lost due to trapping and accumulation of sediment. Despite critical importance to freshwater supplies, reservoir sedimentation rates are poorly understood due to sparse bathymetry survey data and challenges in modeling sedimentation sequestration. Here, we proposed a novel approach to estimate reservoir sedimentation rates and storage capacity losses using high‐resolution Sentinel‐2 satellites and daily in situ water levels. Validated on eight reservoirs across the central and western United States, the estimated reservoir bathymetry and sedimentation rates have a mean error of 4.08% and 0.05% yr−1, respectively. Estimated storage capacity losses to sediment vary among reservoirs, which overall agrees with the pattern from survey data. We also demonstrated the potential applications of the proposed approach to ungauged reservoirs by combining Sentinel‐2 with sub‐monthly water levels from recent satellite altimeters.

Simulation of present and future land subsidence in the Rafsanjan plain, Iran, due to groundwater overexploitation using numerical modeling and InSAR data analysis

In the Rafsanjan plain, Iran, the excessive use of groundwater for pistachio irrigation since the 1960s has led to a severe water level decline as well as land subsidence. In this study, the advantages of InSAR analyses and groundwater flow modeling are combined to improve the understanding of the subsurface processes causing groundwater-related land subsidence in several areas of the region. For this purpose, a calibration scheme for the numerical groundwater model was developed, which simultaneously accounts for hydraulic aquifer parameters and sediment mechanical properties of land subsidence and thus considers the impact of water release from aquifer compaction. Simulation results of past subsidence are calibrated with satellite-based InSAR data and further compared with leveling measurements. Modeling results show that land subsidence in this area occurs predominantly in areas with fine-grained sediments and is therefore only partly dependent on groundwater level decline. During the modeling period from 1960 to 2020, subsidence rates of up to 21 cm year−1 are simulated. Due to the almost solely inelastic compaction of the aquifer, this has already led to an irreversible aquifer storage capacity loss of 8.8 km3. Simulation results of future development scenarios indicate that although further land subsidence cannot be avoided, subsidence rates and the associated aquifer storage capacity loss can be reduced by up to 50 and 36%, respectively, by 2050 through the implementation of improved irrigation management for the pistachio orchards.

A Halogen-Bonded Organic Framework (XOF) Emissive Cocrystal for Acid Vapor and Explosive Sensing, and Iodine Capture.

There is a strong and urgent need for efficient materials that can capture radioactive iodine atoms from nuclear waste. This work presents a novel strategy to develop porous materials for iodine capture by employing halogen bonding, mechanochemistry and crystal engineering. 3D halogen-bonded organic frameworks (XOFs) with guest-accessible permanent pores are exciting targets in crystal engineering for developing functional materials, and this work reports the first example of such a structure. The new-found XOF, namely TIEPE-DABCO, exhibits enhanced emission in the solid state and turn-off emission sensing of acid vapors and explosives like picric acid in nanomolar quantity. TIEPE-DABCO captures iodine from the gas phase (3.23 g g-1 at 75 °C and 1.40g g-1 at rt), organic solvents (2.1g g-1 ), and aqueous solutions (1.8g g-1 in the pH range of 3-8); the latter with fast kinetics. The captured iodine can be retained for more than 7 days without any leaching, but readily released using methanol, when required. TIEPE-DABCO can be recycled for iodine capture several times without any loss of storage capacity. The results presented in this work demonstrate the potential of mechanochemical cocrystal engineering with halogen bonding as an approach to develop porous materials for iodine capture and sensing.

Effects of SO2 poisoning and regeneration on spinel containing CH4 oxidation catalysts

Methane oxidation under periodic conditions and the oxygen storage capacity of a bilayer Pt/Pd/Al2O3 over a Mn0.5Fe2.5O4 spinel catalyst were studied before and after SO2 exposure, and after simulated regeneration conditions. Prior to sulfur exposure, improvement in CH4 oxidation conversion under periodic conditions compared to steady-state conditions was observed. After sulfur exposure at 100 °C, there was a loss in CH4 oxidation performance and a loss of oxygen storage capacity of the spinel material. The extent of regeneration from sulfur poisoning depends on the ability to induce the decomposition of sulfate species, and while all regeneration methods tested in this study did improve CH4 conversion, regeneration methods under periodic conditions induced greater sulfur species desorption from the catalyst surface leading to improved CH4 conversion. Key regeneration parameters – temperature, feed composition, modulation amplitude and frequency – were optimized to induce S species decomposition and correlated to CH4 oxidation activity recovery.

InSAR-Based Early Warning Monitoring Framework to Assess Aquifer Deterioration

Aquifer surveillance is key to understanding the dynamics of groundwater reservoirs. Attention should be focused on developing strategies to monitor and mitigate the adverse consequences of overexploitation. In this context, ground surface deformation monitoring allows us to estimate the spatial and temporal distribution of groundwater levels, determine the recharge times of the aquifers, and calibrate the hydrological models. This study proposes a methodology for implementing advanced multitemporal differential interferometry (InSAR) techniques for water withdrawal surveillance and early warning assessment. For this, large open-access images were used, a total of 145 SAR images from the Sentinel 1 C-band satellite provided by the Copernicus mission of the European Space Agency. InSAR processing was carried out with an algorithm based on parallel computing technology implemented in cloud infrastructure, optimizing complex workflows and processing times. The surveillance period records 6-years of satellite observation from September 2016 to December 2021 over the city of Chillan (Chile), an area exposed to urban development and intensive agriculture, where ~80 wells are located. The groundwater flow path spans from the Andes Mountain range to the Pacific Ocean, crossing the Itata river basin in the Chilean central valley. InSAR validation measurements were carried out by comparing the results with the values of continuous GNSS stations available in the area of interest. The performance analysis is based on spatial analysis, time series, meteorological stations data, and static level measurements, as well as hydrogeological structure. The results indicate seasonal variations in winter and summer, which corresponds to the recovery and drawdown periods with velocities > −10 mm/year, and an aquifer deterioration trend of up to 60 mm registered in the satellite SAR observation period. Our results show an efficient tool to monitor aquifer conditions, including irreversible consolidation and storage capacity loss, allowing timely decision making to avoid harmful exploitation.