This dataset consists of polylines representing simulated groundwater elevation contours developed to visualize groundwater-level trends for each map figure extent (larger work, figure 22) for Eagle, Dayton, and Churchill Valleys, west-central Nevada.

The Utah Groundwater Conditions Web Product is a comprehensive digital tool designed to monitor and report on the groundwater conditions across Utah. Developed by the U.S. Geological Survey (USGS) for the Utah Department of Natural Resources, this web product integrates data from multiple public and private sources to provide an annual update on groundwater levels and usage. The web product gives easy visual access to groundwater pumpage estimates along with other data such as water levels, stream discharge, and precipitation records. The charts allow users to see trends as well as correlations between multiple data sets. This web product will be updated yearly and is available at https://warcapps.usgs.gov/gs-water/uwsc/ugcwa.

The three tabular datasets are the results of an analysis supporting the indicator 'Long-term Trends in Groundwater Levels in B.C.' updated by Environmental Reporting BC in 2024. The analysis used groundwater level monitoring data from the Provincial Groundwater Observation Well Network as well as attribute data for all groundwater wells. The datasets include: 1). Annual results of trend analysis by well: includes attributes (e.g. well name, number, lat/long, depth, aquifer type, region etc) for each well used in the analysis, as well as the results of the analysis (trend and significance) for the all-data, 10-year, and 20-year trend data. 2). Complete trending results of every option provided in the interactive data visualization, including monthly trends. 3). The monthly median groundwater levels (in m below ground) for each month of each year for each well used in the analyses. The dataset includes The R code for reproducing this indicator summary data is available on GitHub.

Groundwater Data Loggers Market Outlook

The global groundwater data loggers market size is projected to grow from USD 425 million in 2023 to USD 656 million by 2032, reflecting a compound annual growth rate (CAGR) of 5.1% during the forecast period. The increasing necessity for precise and continuous monitoring of groundwater levels and quality is a significant growth factor for this market. Government regulations and the rising awareness regarding water conservation are further propelling the market growth.

One of the primary growth factors driving the groundwater data loggers market is the escalating demand for water resource management. As water scarcity becomes a growing issue worldwide, accurate groundwater monitoring becomes crucial for ensuring sustainable water use. Governments and environmental agencies are increasingly investing in advanced technologies to gather precise data on groundwater levels and quality. This demand for efficient water management solutions is expected to drive the market significantly over the next decade.

Furthermore, advancements in data logging technologies are enhancing the capabilities and functionalities of groundwater data loggers. Modern data loggers are now equipped with sophisticated sensors and connectivity features that enable real-time data acquisition and remote monitoring. These technological enhancements not only improve the accuracy of data collected but also reduce the need for manual intervention, making groundwater monitoring more efficient and cost-effective. These innovations are likely to contribute substantially to the market's growth.

Environmental monitoring is another key factor contributing to the market expansion. Increasing awareness regarding the environmental impact of industrial activities and agricultural practices is compelling various stakeholders to adopt groundwater data loggers. These devices help in tracking the effects of pollutants and contaminants on groundwater, thereby aiding in the implementation of corrective measures. As environmental regulations become more stringent, the demand for groundwater data loggers is anticipated to rise, driving market growth.

Regionally, North America is expected to dominate the groundwater data loggers market due to stringent environmental regulations and the presence of numerous water management projects. The region's advanced technological infrastructure also facilitates the adoption of sophisticated data logging systems. In contrast, the Asia Pacific region is projected to exhibit the highest growth rate due to increasing industrial activities and growing concerns over water scarcity. Rapid urbanization and agriculture-driven economies in countries like India and China are expected to fuel the demand for groundwater data loggers in this region.

Product Type Analysis

The groundwater data loggers market is segmented by product type into portable groundwater data loggers and fixed groundwater data loggers. Portable groundwater data loggers are gaining popularity due to their ease of use and flexibility. These loggers can be easily transported to different locations, making them ideal for field studies and temporary monitoring projects. Their compact size and battery-operated nature allow for deployment in remote areas where power supply may be unreliable. As a result, the demand for portable groundwater data loggers is expected to see significant growth during the forecast period.

Fixed groundwater data loggers, on the other hand, are primarily used for long-term monitoring at permanent sites. These loggers are often integrated into larger environmental monitoring systems and provide continuous data over extended periods. They are typically more robust and capable of withstanding harsh environmental conditions. The reliability and durability of fixed groundwater data loggers make them indispensable for ongoing projects that require consistent data collection. As environmental monitoring becomes more critical, the demand for fixed data loggers is expected to remain strong.

The versatility of portable groundwater data loggers also makes them suitable for a wide range of applications, including emergency response situations where quick deployment is essential. Their ability to record data over short intervals and transmit it wirelessly to central databases enhances their utility in dynamic and rapidly changing environments. This adaptability is likely to contribute to the growing market share of portable groundwater data loggers.

In contrast, fixed groundwater data

The U.S. Geological Survey (USGS) Water Resources Mission Area (WMA) is working to address a need to understand where the Nation is experiencing water shortages or surpluses relative to the demand for water need by delivering routine assessments of water supply and demand and an understanding of the natural and human factors affecting the balance between supply and demand. A key part of these national assessments is identifying long-term trends in water availability, including groundwater and surface water quantity, quality, and use. This data release contains Mann-Kendall monotonic trend analyses for 18 observed annual and monthly streamflow metrics at 6,347 U.S. Geological Survey streamgages located in the conterminous United States, Alaska, Hawaii, and Puerto Rico. Streamflow metrics include annual mean flow, maximum 1-day and 7-day flows, minimum 7-day and 30-day flows, and the date of the center of volume (the date on which 50% of the annual flow has passed by a gage), along with the mean flow for each month of the year. Annual streamflow metrics are computed from mean daily discharge records at U.S. Geological Survey streamgages that are publicly available from the National Water Information System (NWIS). Trend analyses are computed using annual streamflow metrics computed through climate year 2022 (April 2022- March 2023) for low-flow metrics and water year 2022 (October 2021 - September 2022) for all other metrics. Trends at each site are available for up to four different periods: (i) the longest possible period that meets completeness criteria at each site, (ii) 1980-2020, (iii) 1990-2020, (iv) 2000-2020. Annual metric time series analyzed for trends must have 80 percent complete records during fixed periods. In addition, each of these time series must have 80 percent complete records during their first and last decades. All longest possible period time series must be at least 10 years long and have annual metric values for at least 80% of the years running from 2013 to 2022. This data release provides the following five CSV output files along with a model archive: (1) streamflow_trend_results.csv - contains test results of all trend analyses with each row representing one unique combination of (i) NWIS streamgage identifiers, (ii) metric (computed using Oct 1 - Sep 30 water years except for low-flow metrics computed using climate years (Apr 1 - Mar 31), (iii) trend periods of interest (longest possible period through 2022, 1980-2020, 1990-2020, 2000-2020) and (iv) records containing either the full trend period or only a portion of the trend period following substantial increases in cumulative upstream reservoir storage capacity. This is an output from the final process step (#5) of the workflow. (2) streamflow_trend_trajectories_with_confidence_bands.csv - contains annual trend trajectories estimated using Theil-Sen regression, which estimates the median of the probability distribution of a metric for a given year, along with 90 percent confidence intervals (5th and 95h percentile values). This is an output from the final process step (#5) of the workflow. (3) streamflow_trend_screening_all_steps.csv - contains the screening results of all 7,873 streamgages initially considered as candidate sites for trend analysis and identifies the screens that prevented some sites from being included in the Mann-Kendall trend analysis. (4) all_site_year_metrics.csv - contains annual time series values of streamflow metrics computed from mean daily discharge data at 7,873 candidate sites. This is an output of Process Step 1 in the workflow. (5) all_site_year_filters.csv - contains information about the completeness and quality of daily mean discharge at each streamgage during each year (water year, climate year, and calendar year). This is also an output of Process Step 1 in the workflow and is combined with all_site_year_metrics.csv in Process Step 2. In addition, a .zip file contains a model archive for reproducing the trend results using R 4.4.1 statistical software. See the README file contained in the model archive for more information. Caution must be exercised when utilizing monotonic trend analyses conducted over periods of up to several decades (and in some places longer ones) due to the potential for confounding deterministic gradual trends with multi-decadal climatic fluctuations. In addition, trend results are available for post-reservoir construction periods within the four trend periods described above to avoid including abrupt changes arising from the construction of larger reservoirs in periods for which gradual monotonic trends are computed. Other abrupt changes, such as changes to water withdrawals and wastewater return flows, or episodic disturbances with multi-year recovery periods, such as wildfires, are not evaluated. Sites with pronounced abrupt changes or other non-monotonic trajectories of change may require more sophisticated trend analyses than those presented in this data release.

Groundwater-quality data were collected from 559 wells as part of the National Water-Quality Assessment Project of the U.S. Geological Survey National Water-Quality Program from January through December 2014. The data were collected from four types of well networks: principal aquifer study networks, which assess the quality of groundwater used for public water supply; land-use study networks, which assess land-use effects on shallow groundwater quality; major aquifer study networks, which assess the quality of groundwater used for domestic supply; and enhanced trends networks, which evaluate the time scales during which groundwater quality changes. Groundwater samples were analyzed for a large number of water-quality indicators and constituents, including major ions, nutrients, trace elements, volatile organic compounds, pesticides, radionuclides, and some special interest constituents (arsenic speciation, chromium (VI) and perchlorate). These groundwater quality data are tabulated in a U.S. Geological Survey Data Series Report DS-1063 which is available at https://dx.doi.org/10.3133/ds1063 and in this data release. Quality-control samples also were collected and select data from 2012-2014 are included in the report DS1063 and this data release. Data from the environmental and QC blank and replicate samples from the 2012-2013 sampling period were presented in Arnold and others (2016). Data from spike QC samples have not previously been published Data from VOC spike QC data from May 2012-December 2014 are published in this report (see larger work citation) and data release along with an analysis of QC data where detections in field blank samples, variability in replicate samples, and recoveries in VOC spike samples are described for the entire sampling period through the date covered in this report (May 2012-December 2014). Pesticide spike samples and analysis of recoveries will be presented in a later report. There are 42 tables that are part of the larger work citation. There are 9 tables in the text of the larger work citation and 33 external tables included in this data release. The 9 tables not included in the data release are summary tables derived from some of the other 33 tables. Tables in the text include table 1, Appendix 1 tables 1-1 and 1-2; Appendix 2 table 2-1, and Appendix 4 tables 4-1 through 4-6. Tables that are external files are tables 1 through 12; Appendix 4 tables 4-7 through 4-27. This compressed file contains 33 files of groundwater-quality data in ASCII text tab-delimited format and 33 corresponding metadata in xml format for wells sampled for the U.S. Geological Survey National Water-Quality Assessment Project.

The Nature Conservancy (TNC) owns ecologically rich properties that include groundwater-dependent ecosystems (GDEs) in Oasis Valley, Nevada. AngloGold Ashanti has acquired the rights to several gold mines in Oasis Valley, including the North Bullfrog Project, where the company conducted two multiday aquifer tests in 2023 and 2024 to assess aquifer hydraulics and evaluate water level drawdown. In partnership with TNC, Desert Research Institute (DRI) monitored groundwater levels at sites within Oasis Valley to identify potential hydrologic impacts that could be attributed to the aquifer tests. Combined water level and water temperature sensors were installed and activated with a five-minute measurement frequency between August 30, 2023, and March 20, 2024, at the NC-GWE-OV-2 well (in Parker Ranch), OVU Lower ET Well (in the Atwood Preserve), and Crystal Spring. DRI also operates systems for monitoring meteorology at Colson Pond (in the Atwood Preserve) and diverted flow from Crystal Sprin..., Transducer water level data were post-processed after each field trip. Quality control is performed through the Trainset program (https://trainset.geocene.com/). This program allows for the visualization and labeling of large sets of data. The data from each well were analyzed and labeled with different indicators, such as data offloads, adjusting periods (time soon after the sensor was first installed, when readings may be less accurate), dry (transducer out of the water), frozen (if sensor temperature drops to freezing), spikes, dips, wide dips (drop > 1.0 inch [2.5 cm], and then return to the original water level multiple hours later), steps (sudden increase or decrease to a new fairly constant water level), and flatlines. These labels help to identify different trends and possible erroneous data., , # Supplemental dataset: Monitoring Groundwater Levels in Oasis Valley, NV, and Evaluating Potential Drawdown During the North Bullfrog Aquifer Test

https://doi.org/10.5061/dryad.0zpc8676t

Description of the data and file structure

This data folder contains offloads from the following sensors:

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The simulated 1970 unconfined depth to watertable across the entire model domain. This represents a pre-development water table surface.

Choosing a year that best represents the climatic circumstances for the simulation objectives is an essential part of the steady-state assessment. This decision was influenced by the availability of appropriate calibration data. This approach generally allows for the selection of a year that was outside the bounds of a longer term shift in annual rainfall distribution. The selected steady-state condition was based on 1970 rainfall and assumed no groundwater extractions. This initial state was selected to represent predevelopment conditions as post-1970 historic groundwater pumping in the region (on and offshore) have not achieved a quasi-equilibrium response as based on available groundwater hydrograph trends.

The transient simulation period was 1970 to 2012. This period captures both pre-mine development and a range of varying climatic conditions, including above average wet and dry sequences. The 1970 starting date enables the incorporation of historic groundwater extraction data into the model and provides sufficient lead time for the groundwater model to minimise the impact of initial conditions on model predictions associated with the period of interest, namely the calibration/validation period of 2000 to 2012.

Copied from the Gippsland Groundwater Model report, 2015.

Purpose

The steady-state calibration model represents the 1970 Latrobe Valley pre-development conditions. On the basis that steady-state predictions reflect long-term equilibrium conditions assuming constant groundwater inputs and stresses throughout time, no groundwater extractions were assigned during the steady-state simulation.

Dataset History

"The simulated 1970 unconfined potentiometric surface (watertable) and depth-to-watertable across the entire model domain is shown in Figure 114 and Figure 115 respectively. (ED. see figures in the Gippsland Groundwater model report)

Visual comparison of the Victorian SAFE depth to watertable map (Figure 116) with the steady-state simulated depth to watertable shows the watertable surface is reasonable within the alluvial systems, however in some upland locations the watertable appears in greater connection with surface features than presented in the Victorian Aquifer Framework (VAF) data. This is not considered a significant issue as these areas are well beyond the zone of interest.

It must be noted that the VAF depth to watertable map was derived using a combination of terrain analysis and interpolated bore data, and in part on proximity to streams within the exposed basement areas. Additionally, the VAF reflects the 1990 conditions whereas the simulated steady-state depth to watertable represents pre-development conditions. As such, it is expected that that the simulated steady-state depth to watertable map would have a greater area of shallow watertable than reported in the VAF spatial layer."

This text copied from the Gippsland Groundwater Model report 2015.

Dataset Citation

Victorian Department of Economic Development, Jobs, Transport and Resources (2015) Depth to water - simulated 1970 steady state raster. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/4f343452-3dae-4184-b5f5-5690a17a82f6.

This e-book is a quick primer on earth observation of water resources and has been developed jointly by the World Bank and NASA. It provides a basic introduction to hydrologic processes and the types of in-situ and earth observation monitoring approaches to gain a global perspective to help address problems in the real world such as floods, droughts, cyclones, and forecasting for agriculture and water-related disease management applications. It provides a primer for accessing useful NASA data, modeling tools, related interactive viewers and useful links in this regard, that showcase interactive maps to visualize precipitation and even groundwater data and trends and near-real time flood potential from space. This e-book provides an illustrative overview of the use of increasingly powerful free data from satellites that can be critical for monitoring and managing watersheds and aquifers around the world.

The Environmental Services Division conducts aquifer groundwater monitoring at approximately 130 selected wells within the Albuquerque city limits. Groundwater monitoring activities consist of groundwater sampling collection and measuring hydrologic parameters. The monitoring program provides consistent and representative data aimed at assessing the chemical water quality of Albuquerque's underground aquifer. It determines spatial and temporal trends in water quality. Approximately 170 samples are collected from Environmental Services Division wells an an annual basis. Water table elevations are also measured to track short and long term hydrologic changes.

The information gathered through the groundwater monitoring program is used to assess the groundwater resource, project future conditions of, address contamination concerns, and provide the information necessary to protect our underground aquifer. It is available and shared with local, state and federal organizations.

This application provides two different ways to explore City of Albuquerque Groundwater Level Measurements. One is a mapping application and the other is a dashboard. Select a tab on the top to switch between the two applications. All data is collected and provided by the City of Albuquerque, Environmental Health Department, Environmental Services Division. The mapping and well data presented on this page is presented for informational purposes and is provisional and has not been reviewed for completeness or accuracy. Please see the disclaimer of liability at: http://www.cabq.gov/abq-apps/abq-data-disclaimer-1

The groundwater monitoring equipment market is experiencing robust growth, projected to reach a value of $1129 million in 2025 and maintain a Compound Annual Growth Rate (CAGR) of 5.5% from 2025 to 2033. This expansion is driven by several key factors. Increasing concerns about water scarcity and contamination are prompting governments and industries to invest heavily in advanced monitoring technologies. The rising adoption of sophisticated sensors, data analytics, and remote monitoring solutions enhances the efficiency and accuracy of groundwater assessments. Furthermore, stringent environmental regulations worldwide are compelling stricter monitoring practices, fueling demand for these specialized equipment. The market encompasses a diverse range of technologies, including sensors for various parameters (level, quality, contaminants), data loggers, and software for data analysis and visualization. Leading players such as AMS, Inc., Xylem Analytics, and Solinst Canada Ltd. are at the forefront of innovation, constantly developing new and improved monitoring solutions. The market segmentation is influenced by the type of equipment (sensors, data loggers, software), application (environmental monitoring, industrial use, agricultural use), and geographical location. While precise regional data is unavailable, we can infer that developed regions with robust environmental regulations and significant industrial activity (North America, Europe) will likely dominate the market. The competitive landscape is characterized by both established players and emerging technology providers, fostering innovation and driving down costs. Future growth will be shaped by advancements in sensor technology (e.g., IoT integration), the development of more sophisticated data analysis tools, and the increasing adoption of cloud-based solutions for remote monitoring and data management. The market's trajectory underscores the critical importance of groundwater management and the continuing need for advanced monitoring solutions to ensure water quality and availability.

Abstract

This dataset was derived by the Bioregional Assessment Programme. The parent datasets are identified in the Lineage field in this metadata statement. The processes undertaken to produce this derived dataset are described in the History field in this metadata statement.

This dataset contains raster representations of Total Dissolved Solid (TDS) measurement trends in groundwater samples for each hydrogeological formation in the Galilee Basin subregion.

The dataset also contains supplementary polygon Feature Classes for each formation, to be used in the visualisation of the rasters. For each formation this includes:

a) A rectangular data extent polygon feature class - created based on the distribution of data points for each formation and used to define the extent of the each raster

b) Data extent mask - further defines the extent of data distribution as well as the spatial extent of the formation, used to visualise the TDS trends for each formation only within the formation boundary and near the spread of point data.

Purpose

Provides a visual representation for use in maps, of TDS measurement trends in groundwater for each hydrogeological formation in the Galilee Basin subregion.

Dataset History

The raster layers within this dataset were created using the 'Topo to Raster' interpolation method in ArcGIS. Topo to Raster uses an iterative finite difference interpolation technique. This method is preferred for map and visualisation purposes, especially in sparse data regions, as surface continuity is not compromised at a global level. This results in raster layers with smooth surfaces and trends for any level of data density, and surface continuity between areas of varying density.

Raster layers and polygon Feature Classes were created from the source point Feature Classes (dataset: GAL Hydrochemistry Formations QC for TDS v02 GIS - GUID: 109a21cd-a167-4320-84be-ab56cfc12cee)

Formation Data Extent polygons: An arbitrary rectangular polygon was created around the extent of points contained in each source point Feature Class

Formation Data Extent Mask: a hole was clipped from the Formation Data Extent polygon. The Eastern boundary of each hole was traced from the equivalent formation polygon found within the Galilee Groundwater Model, Hydrogeological Formation Extents v01 dataset (GUID: 5afbf7f1-1ee0-444b-9f77-dbad8d8de95b), while the western, northern and southern extent was defined by the distribution of point data or the Galilee subregion boundary (Bioregional Assessment areas v03, GUID: 96dbf469-5463-4f4d-8fad-4214c97e5aac).

Topo to Raster parameters

Input feature data = respective point feature class from source dataset

Field = TDS

Type = Point Elevation

Output cell size = 0.001

Output extent = Formation data extent polygon Feature Class

Smallest z value to be used in interpolation = smallest TDS value of input point Feature Class

Largest z value to be used in interpolation = largest TDS value of input point Feature Class

Drainage enforcement = NO_ENFORCE

Primary type of input data = SPOT

All other parameters left as default.

Dataset Citation

Bioregional Assessment Programme (XXXX) GAL Hydrochemistry Formations QC for TDS v02 Surfaces. Bioregional Assessment Derived Dataset. Viewed 11 April 2016, http://data.bioregionalassessments.gov.au/dataset/ff165a41-f7f3-4922-870e-6837fd40f228.

Dataset Ancestors

• Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements 20131204

• Derived From GAL Hydrochemistry Formations QC for TDS v02

• Derived From GAL Aquifer Formation Extents v01

• Derived From GAL Aquifer Formation Extents v02

• Derived From Carmichael Coal Mine and Rail Project Environmental Impact Statement

• Derived From QLD Hydrochemistry QA QC GAL v02

• Derived From Bioregional Assessment areas v03

• Derived From GAL Hydrochemistry Formations QC for TDS v01

• Derived From QLD Dept of Natural Resources and Mines, Groundwater Entitlements linked to bores v3 03122014

• Derived From GEODATA TOPO 250K Series 3, File Geodatabase format (.gdb)

• Derived From RPS Galilee Hydrogeological Investigations - Appendix tables B to F (original)

• Derived From GEODATA TOPO 250K Series 3

• Derived From NSW Catchment Management Authority Boundaries 20130917

• Derived From Geological Provinces - Full Extent

• Derived From Phanerozoic OZ SEEBASE v2 GIS

• Derived From QLD Department of Natural Resources and Mining Groundwater Database Extract 20131111

• Derived From QLD DNRM Hydrochemistry with QA/QC

• Derived From GAL Hydrochemistry Formations QC for TDS v02 GIS

• Derived From Galilee Groundwater Model, Hydrogeological Formation Extents v01

• Derived From Queensland petroleum exploration data - QPED

• Derived From Natural Resource Management (NRM) Regions 2010

• Derived From Three-dimensional visualisation of the Great Artesian Basin - GABWRA

• Derived From QLD Department of Natural Resources and Mining Groundwater Database Extract 20142808

• Derived From Bioregional Assessment areas v01

• Derived From Bioregional Assessment areas v02

• Derived From Queensland Geological Digital Data - Detailed state extent, regional. November 2012

• Derived From Geoscience Australia, 1 second SRTM Digital Elevation Model (DEM)

This resource contains Supplementary Tables and Source Data for the manuscript entitled 'Decadal increase in groundwater inorganic carbon concentrations across Sweden' by Klaus, M., under conditional acceptance in Communications Earth & Environment. The manuscript is based on groundwater chemistry observations from 55 sampling sites distributed across Sweden and sampled quarterly between 1980 and 2020 within the Swedish national groundwater monitoring program run by the Geological Survey of Sweden. The Supplementary Tables contain statistical analyses of linear trends in water chemistry, including among others concentrations of dissolved inorganic carbon, carbon dioxide, alkalinity, pH. The source data contain point observations and linear trends in dissolved inorganic carbon, carbon dioxide, bicarbonate, pH and several acidification proxies. For details, see the variable description and table caption files, as well as the manuscript.

The global groundwater monitoring instruments market is experiencing robust growth, driven by increasing concerns over water scarcity, pollution, and the need for effective water resource management. The market, valued at approximately $2.5 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 7% from 2025 to 2033. This growth is fueled by several factors, including the rising adoption of advanced monitoring technologies like sensors and data loggers, increasing government initiatives promoting sustainable water management practices, and the growing demand for accurate and real-time groundwater data in various sectors such as agriculture, industry, and environmental protection. Furthermore, technological advancements leading to the development of more efficient, reliable, and cost-effective instruments are contributing significantly to market expansion. Several key trends are shaping the market's trajectory. The increasing integration of IoT (Internet of Things) technologies in groundwater monitoring systems is enabling remote data acquisition and analysis, enhancing operational efficiency and reducing costs. The demand for sophisticated data analytics and visualization tools is also on the rise, allowing stakeholders to gain deeper insights from collected data. However, the market faces certain challenges, such as the high initial investment costs associated with deploying advanced monitoring systems and the need for skilled personnel to operate and maintain the equipment. Despite these restraints, the long-term outlook for the groundwater monitoring instruments market remains positive, fueled by the ongoing need for sustainable and efficient groundwater management globally. The market is segmented by instrument type (sensors, data loggers, etc.), application (agriculture, industry, etc.), and region. Major players like AMS, Inc., Besst, Inc., and Xylem Analytics are driving innovation and competition in this growing market.

The groundwater monitoring instruments market, valued at $1298 million in 2025, is projected to experience robust growth, driven by increasing concerns over water scarcity and pollution, stringent environmental regulations, and the rising adoption of advanced monitoring technologies. The 5.1% CAGR from 2019 to 2033 indicates a steady expansion, fueled by factors such as the escalating demand for accurate and real-time data for effective groundwater management. Key market drivers include the need for efficient irrigation management in agriculture, growing industrialization leading to increased groundwater contamination, and the increasing prevalence of waterborne diseases necessitating proactive monitoring. Technological advancements, such as the integration of IoT sensors and sophisticated data analytics, are further enhancing the capabilities of groundwater monitoring systems, leading to improved decision-making and resource allocation. The market segmentation, though not explicitly provided, likely includes various instrument types such as sensors (water level, quality, etc.), data loggers, and software solutions for data analysis and visualization. Geographic segmentation would show varying regional growth rates based on factors like regulatory frameworks, industrial development, and agricultural practices. The competitive landscape is characterized by the presence of both established players and emerging companies, indicating a dynamic market with ongoing technological innovation and market consolidation. The forecast period (2025-2033) will likely witness further market expansion, particularly in regions with high water stress and rapid urbanization. The historical period (2019-2024) provides a baseline understanding of market development which demonstrates a trend of increasing demand and the market's resilience to economic fluctuations.

The Utah Groundwater Conditions Web Product is a comprehensive digital tool designed to monitor and report on the groundwater conditions across Utah. Developed by the U.S. Geological Survey (USGS) for the Utah Department of Natural Resources, this web product integrates data from multiple public and private sources to provide an annual update on groundwater levels and usage. The web product gives easy visual access to groundwater pumpage estimates along with other data such as water levels, stream discharge, and precipitation records. The charts allow users to see trends as well as correlations between multiple data sets. This web product will be updated yearly and is available at https://warcapps.usgs.gov/gs-water/uwsc/ugcwa.

The California Groundwater Ambient Monitoring and Assessment Program Priority Basin Project (GAMA-PBP) analyzed for per-and polyfluoroalkyl substances (PFAS) in groundwater samples collected from domestic and public drinking water supply wells in California. GAMA-PBP is a cooperative program between the U.S. Geological Survey and the California State Water Resources Control Board. This data release contains data for samples collected from May 2019 through December 2022 and includes revisions to earlier data (Kent, 2021) that were either screened or removed after analysis of quality-control data. Please see the quality-control and other descriptions of the data in the processing steps in the xml file. Subsequent updates will include data for samples collected after December 2022. Data are also publicly available for download from Jurgens and others (2018). The dataset consists of 4 tables. Table 1 lists the names and abbreviations of the twenty-eight PFAS constituents analyzed. Table 2 contains information about each site visited, including _location and well depth information. Table 3 contains results for each PFAS constituent analyzed and includes quality-control sample results where applicable. Table 4 contains a list of every sample collected at each site and has a summary of all the PFAS detections for each sample. This data release supercedes previous PFAS data release versions reported by Kent (2021). Version 2.0 of the previous data release (Kent, 2021) contained data for samples collected from May 2019 through June 2021. Data from Kent (2021) is available upon request from the authors of this data release. References: Kent, R.H., 2021, Data sets for: Sampling for Per-and Polyfluoralkly Substances (PFAS) by the GAMA Priority Basin Project (GAMA-PBP)(2019-2021) (ver. 2.0, October 2021): U.S. Geological Survey data release, https://doi.org/10.5066/P92IPRJD. Jurgens, B.C., Jasper, M., Nguyen, D.H., and Bennett, G.L., 2018, USGS CA GAMA-PBP Groundwater Quality Results--Assessment and Trends: U.S. Geological Survey website, available at https://doi.org/10.5066/P91WJ2G1.

Abstract

This dataset and its metadata statement were supplied to the Bioregional Assessment Programme by a third party and are presented here as originally supplied.

The simulated 1970 unconfined potentiometric surface (watertable) across the entire model domain. The potentiometric surface represents the uppermost saturated surface and variability over the region.

Choosing a year that best represents the climatic circumstances for the simulation objectives is an essential part of the steady-state assessment. This decision was influenced by the availability of appropriate calibration data. This approach generally allows for the selection of a year that was outside the bounds of a longer term shift in annual rainfall distribution. The selected steady-state condition was based on 1970 rainfall and assumed no groundwater extractions. This initial state was selected to represent predevelopment conditions as post-1970 historic groundwater pumping in the region (on and offshore) have not achieved a quasi-equilibrium response as based on available groundwater hydrograph trends. The transient simulation period was 1970 to 2012. This period captures both pre-mine development and a range of varying climatic conditions including above average wet and dry sequences. The 1970 starting date enables the incorporation of historic groundwater extraction data into the model and provides sufficient lead time for the groundwater model to minimise the impact of initial conditions on model predictions associated with the period of interest namely the calibration/validation period of 2000 to 2012. Copied from the Gippsland Groundwater Model report 2015.

Purpose

The surface indicates the likely regional groundwater flow direction and gradient in the area illustrating the condition at time point 1970.

Dataset History

The simulated 1970 unconfined potentiometric surface (watertable) and depth-to-watertable across the entire model domain is shown in Figure 114 and Figure 115 respectively. (ED. see figures in the Gippsland Groundwater model report). Visual comparison of the Victorian SAFE depth to watertable map (Figure 116) with the steady-state simulated depth to watertable shows the watertable surface is reasonable within the alluvial systems however in some upland locations the watertable appears in greater connection with surface features than presented in the Victorian Aquifer Framework (VAF) data. This is not considered a significant issue as these areas are well beyond the zone of interest. It must be noted that the VAF depth to watertable map was derived using a combination of terrain analysis and interpolated bore data and in part on proximity to streams within the exposed basement areas. Additionally the VAF reflects the 1990 conditions whereas the simulated steady-state depth to watertable represents pre-development conditions. As such it is expected that that the simulated steady-state depth to watertable map would have a greater area of shallow watertable than reported in the VAF spatial layer.

This text copied from the Gippsland Groundwater Model report 2015. See Beverly et al (2015) for more details.

Dataset Citation

Bioregional Assessment Programme (2015) Potentiometric surface - simulated 1970 raster. Bioregional Assessment Source Dataset. Viewed 05 October 2018, http://data.bioregionalassessments.gov.au/dataset/883f86cd-8d1c-4672-bcde-7b872248ddb2.

The global market for portable sonic water level meters is experiencing steady growth, projected at a Compound Annual Growth Rate (CAGR) of 6.3% from 2025 to 2033. In 2025, the market size is estimated at $241 million. This growth is driven by increasing demand for accurate and efficient water resource management in both municipal and industrial sectors. The rising adoption of smart water management systems and the need for real-time data on groundwater levels are key factors contributing to this market expansion. Furthermore, advancements in sensor technology, leading to improved accuracy and portability of these meters, are fueling market growth. The integrated type segment currently holds a larger market share compared to split type meters due to its ease of use and comprehensive data collection capabilities. Geographically, North America and Europe are currently leading the market, owing to robust infrastructure and well-established water management practices. However, emerging economies in Asia-Pacific are expected to witness significant growth in the coming years, driven by increasing urbanization and industrialization. Competition in the market is moderately high, with key players such as Solinst, Xylem, and Ravensgate constantly innovating and expanding their product offerings to cater to diverse customer needs. The market is also witnessing the emergence of smaller, specialized companies focused on niche applications. Restraints on market growth may include the relatively high initial investment cost of the equipment and the need for skilled personnel for operation and data interpretation. The forecast period of 2025-2033 will see continued expansion of the portable sonic water level meter market. This growth will be underpinned by factors including increasing government investments in water infrastructure projects globally, stricter environmental regulations pushing for better water resource monitoring, and the growing adoption of IoT-enabled solutions for remote water level monitoring. The market will likely see further segmentation based on application-specific features and the integration of advanced analytics capabilities. Companies are likely to focus on developing user-friendly interfaces, enhanced data analysis tools, and cost-effective solutions to broaden the market reach and cater to a wider range of users. The increasing demand for reliable and precise data in various sectors like agriculture and environmental monitoring will also contribute to the growth of this market.

What do you see: the trend in the average nitrate concentration in the upper meter of groundwater in nature reserves for the period 1989-2014. The map shows the decrease (in %) in nitrate concentration per location between 1989 and 2014 (a green/yellow ball: nitrate has fallen; a red/purple ball: nitrate has risen).

The only input of N and S in these areas takes place via air, via atmospheric deposition. As a result of (inter)national measures, N and S emissions and depositions have decreased and this is reflected in the trends in groundwater in nature areas. The map is based on measurements of the TrendMeetnet Acidification. At 150 locations in the Netherlands, especially in forest/heide areas on sand, samples were taken from the upper meters of the groundwater. The sites were sampled 6 times in the period 1989-2014.