Groundwater Observation Wells Research Articles

Spatial and temporal groundwater dynamics in extreme arid basins

AbstractTo accurately obtain the spatial distribution characteristics of groundwater level in an extremely arid zone and its dynamic change patterns under the influence of human activities, based on the data of 55 groundwater observation wells in the middle and lower reaches of the Kriya River, spatial interpolation of regional groundwater level data were performed using the inverse distance weight, spline function, trend surface, and the ordinary kriging methods. The optimal interpolation method was selected by its accuracy to spatially interpolate the groundwater level data in the study area from 2019 to 2021. The results show that: (1) the ordinary kriging method has the highest interpolation accuracy (MAE = 7.1393, MRE = 0.0058, RMSE = 9.4314) and reflects the spatial and temporal variability and distribution characteristics of groundwater levels with great accuracy. (2)The relationship between surface water–groundwater recharge and discharge in different areas of the river channel in the desert section varies depending on geological structure, surface water seepage, and other elements. (3) Groundwater in the Taklamakan Desert has little effect on groundwater recharge in the Dariyabui Oasis, and changes in groundwater dynamics in the oasis are predominantly influenced by surface runoff. (4) Monthly changes in groundwater levels in the Yutian Oasis are continuous, with ‘V’ shaped fluctuations, a declining trend in the southern part, no significant change in the central part, and a slight increase in the northern part. These results contribute to the sustainable management of water resources in the Kriya River Basin, provide a basis for groundwater prediction, and offer a reference for studies of other, similar extreme desert area basins.

A parsimonious approach to predict regions affected by sewer-borne contaminants in urban aquifers

Leaky urban drainage networks (UDNs) exfiltrating wastewater can contaminate aquifers. Detailed knowledge on spatiotemporal distributions of water-dissolved, sewer-borne contaminants in groundwater is essential to protect urban aquifers and to optimize monitoring systems. We evaluated the effect of UDN layouts on the spreading of sewer-borne contaminants in groundwater using a parsimonious approach. Due to the UDN’s long-term leakage behavior and the existence of non-degradable sewer-borne contaminants (equivalent to a conservative and constant contaminant source), we employed a concept of horizontal line sources to mimic the UDN layout. This does not require the consideration of bio-degradation processes or temporal delay and effectively bypasses the vadose zone, thus reducing computational requirements associated with a full simulation of leakages. We used a set of synthetic leakage scenarios which were generated using fractals and are based on a real-world UDN layout. We investigated the effects of typical leakage rates, varying groundwater flow directions, and UDN’s layouts on the shape of the contaminant plume, disregarding the resulted concentration. Leakage rates showed minimal effects on the total covered plume area, whereas 89% of the variance of the plume’s geometry is explained by both the UDN’s layout (e.g., length and level of complexity) and groundwater flow direction. We demonstrated the potential of applying this approach to identify possible locations of groundwater observation wells using a real UDN layout. This straightforward and parsimonious method can serve as an initial step to strategically identify optimal monitoring systems locations within urban aquifers, and to improve sewer asset management at city scale.

The Association between Meteorological Drought and the State of the Groundwater Level in Bursa, Turkey

This study addressed the intricate interplay between meteorological droughts and groundwater level fluctuations in the vicinity of Mount Uludag in Bursa, Turkey. To achieve this, an exhaustive analysis encompassing monthly precipitation records and groundwater level data sourced from three meteorological stations and eight groundwater observation points spanning the period from 2007 to 2018 was performed. Subsequently, this study employed the Standard Precipitation Index (SPI) and Standard Groundwater Level (SGL) metrics, meticulously calculating the temporal extents of drought events for each respective time series. Following this, a judicious application of both the Thiessen and Support Vector Machine (SVM) methodologies was undertaken to ascertain the optimal groundwater observation wells and their corresponding SGL durations, aligning them with SPI durations tied to the selected meteorological stations. The SVM technique, in particular, excelled in the identification of the most pertinent observation wells. Additionally, the Elman Neural Network (ENN) and its optimized version through the Firefly Algorithm (ENN-FA), demonstrated their prowess in accurately predicting SPI durations based on SGL durations. The results were favorable, as evidenced by the commendable performance metrics of the Normalized Root Mean Square Error (NRMSE), the Nash–Sutcliffe Efficiency (NSE), the product of the coefficient of determination and the slope of the regression line (bR2), and the Kling–Gupta Efficiency (KGE). Consequently, the favorable simulation results were construed as evidence supporting the presence of a discernible association between SGL and the duration of the SPI. As we substantiate the concordance between the temporal extent of meteorological droughts and the perturbations in groundwater levels, this unmistakably underscores the fact that the historical fluctuations in groundwater levels within the region were predominantly attributable to climatic influences, rather than being instigated by anthropogenic activities. Nevertheless, it is imperative to underscore that this revelation should not be misconstrued as an endorsement of future heedless exploitation of groundwater resources.

Determination and analysis of groundwater ecological level in Changling County

In order to determine and analyze the groundwater ecological level in Changling County, a total of Landsat 8 series remote sensing images from 2017 to 2021, buried depth data of 51 groundwater observation Wells and 47 phreatic salinity detection data in 2021 were collected. Based on the field investigation and laboratory experiment, the spatial and temporal changes of groundwater level and vegetation coverage in the study area from 2013 to 2017 were determined by using remote sensing technology (the Environment for Visualizing Images) and geographic information system. Through the analysis of the vegetation coverage ratio and the relationship between the groundwater depth and diving salinity, we determine the appropriate growth of vegetation in the study area of diving level and diving salinity water. The results showed that from 2017 to 2021 in the average groundwater level and vegetation cover degree decline year by year, the study area northwest shallow depth of groundwater, vegetation cover degree better, however, in the central and eastern regions, the groundwater depth is larger and the vegetation coverage degree is poor. When the depth of local groundwater is 3.3–4.5 m and the phreatic salinity is less than 0.85 g/L, the ecological water level and phreatic salinity are suitable for vegetation growth in the study area. When the depth of local water is less than 3 m, soil salinization occurs in the surface soil near the lake marsh. When the depth of local water was greater than 8.4 m, the phenomenon of soil desertification appeared in some areas of central China.

Three years of soil moisture observations by a dense cosmic-ray neutron sensing cluster at an agricultural research site in north-east Germany

Abstract. Cosmic-ray neutron sensing (CRNS) allows for the estimation of root-zone soil water content (SWC) at the scale of several hectares. In this paper, we present the data recorded by a dense CRNS network operated from 2019 to 2022 at an agricultural research site in Marquardt, Germany – the first multi-year CRNS cluster. Consisting, at its core, of eight permanently installed CRNS sensors, the cluster was supplemented by a wealth of complementary measurements: data from seven additional temporary CRNS sensors, partly co-located with the permanent ones; 27 SWC profiles (mostly permanent); two groundwater observation wells; meteorological records; and Global Navigation Satellite System reflectometry (GNSS-R). Complementary to these continuous measurements, numerous campaign-based activities provided data by mobile CRNS roving, hyperspectral imagery via UASs, intensive manual sampling of soil properties (SWC, bulk density, organic matter, texture, soil hydraulic properties), and observations of biomass and snow (cover, depth, and density). The unique temporal coverage of 3 years entails a broad spectrum of hydro-meteorological conditions, including exceptional drought periods and extreme rainfall but also episodes of snow coverage, as well as a dedicated irrigation experiment. Apart from serving to advance CRNS-related retrieval methods, this data set is expected to be useful for various disciplines, for example, soil and groundwater hydrology, agriculture, or remote sensing. Hence, we show exemplary features of the data set in order to highlight the potential for such subsequent studies. The data are available at doi.org/10.23728/b2share.551095325d74431881185fba1eb09c95 (Heistermann et al., 2022b).

Groundwater monitoring and specific yield estimation using time-lapse electrical resistivity imaging and machine learning

This paper presents an alternative method for monitoring groundwater levels and estimating specific yields of an unconfined aquifer under different seasonal conditions. The approach employs the Time-Lapse Electrical Resistivity Imaging (TL-ERI) method and machine learning-based time series clustering. A TL-ERI survey was conducted at ten sites (WS01-WS10 sites) throughout the dry and wet seasons, with five-time measurements collected for each site, in the Taichung-Nantou Basin along the Wu River, Central Taiwan. The obtained resistivity raw data was inverted and converted into normalized water content values using Archie’s law, followed by applying the Van Genuchten (VG) model for the Soil Water Characteristic Curve to estimate the Groundwater Level (GWL), and estimated the theoretical specific yield (Sy) by computing the difference between the saturated and residual water contents of the fitted VG model. In addition, the specific yield capacity (Sc), representing the nature of the storage capacity in the aquifer, was also calculated. The results showed that this approach was able to estimate those hydrogeological parameters. The spatial distribution of the GWL reveals that during the dry-wet seasons from February to July, there was a high GWL that extended from southeast to northwest. Conversely, during the wet-dry seasons from July to October, the high GWL shrank, which can be attributed to recharge variations from rainfall events. The determined spatial distribution of Sy and Sc fall within the range of 0.03–0.24 and 0.14–0.25, respectively. To quantitatively establish areas of similar groundwater level changes along with the VG model parameter variations during the study period, a Time series Clustering analysis (TSC) was performed by utilizing Hierarchical Agglomerative Clustering (HAC). The findings suggest that the WS03 site is a promising area for further investigation due to its highest Sc value with a slight change in groundwater levels during the dry and wet seasons. This study brings an advanced development of the geoelectrical method to estimate regional hydrogeological parameters in an area with limited available groundwater observation wells, in different seasonal conditions for groundwater management purposes.

Reconstruction of GRACE terrestrial water storage anomalies using Multi-Layer Perceptrons for South Indian River basins.

The Gravity Recovery and Climate Experiment (GRACE) satellite mission began in 2002 and ended in June 2017. GRACE applications are limited in their ability to study long-term water cycle behavior because the data is limited to a short period, i.e., from 2002 to 2017. In this study, we aim to reconstruct (1960-2002) GRACE total water storage anomalies (TWSA) to obtain a continuous TWS time series from 1960 to 2016 over four river basins of South India, namely the Godavari, Krishna, Cauvery and Pennar River basins, using Multilayer Perceptrons (MLP). The Seasonal Trend Decomposition using Loess procedure (STL) method is used to decompose GRACE TWSA and forcing datasets into linear trend, interannual, seasonal, and residual parts. Only the de-seasoned (i.e., interannual and residual) components are reconstructed using the MLP method after the linear trend and seasonal components are removed. Seasonal component is added back after reconstruction of de-seasoned GRACE TWSA to obtain complete TWSA series from 1960 to 2016. The reconstructed GRACE TWSA are converted to groundwater storage anomalies (GWSA) and compared with nearly 2000 groundwater observation well networks. The results conclude that the MLP model performed well in reconstructing GRACE TWSA at basin scale across four river basins. Godavari (GRB) experienced the highest correlation (r = 0.96) between the modelled TWSA and GRACE TWSA, followed by Krishna (KRB) with r = 0.93, Cauvery (CRB) with r = 0.91, and Pennar (PCRB) with r = 0.92. The seasonal GWSA from GRACE (GWSAGRACE) correlated well with the GWSA from groundwater observation wells (GWSAOBS) from 2003 to 2016. KRB exhibited the highest correlation (r=0.85) followed by GRB (r=0.81), PCRB (r=0.81) and CRB (r=0.78). The established MPL technique could be used to reconstruct long-term TWSA. The reconstructed TWSA data could be useful for understanding long-term trends, as well as monitoring and forecasting droughts and floods over the study regions.

Groundwater flow patterns in a coastal fen exposed to drainage, rewetting and interaction with the Baltic Sea

Low-lying coastal peatlands are unique ecosystems where water levels and salt input with seawater determine vegetation and greenhouse gas emissions, while the export of nutrients and carbon via submarine groundwater discharge influences biogeochemical processes in shallow coastal sediments. Anthropogenic interferences like drainage and diking strongly impact the water flow. This study aimed at understanding the hydrological system in a rewetted coastal fen typical for the southern Baltic Sea. Groundwater observation wells were installed both in the peat layer and underlying sands, and continuous readings of water levels and specific conductivities were combined with groundwater dating and major ion composition analyses. Apparent tritium–helium groundwater ages between 7 and more than 60 years in the shallow aquifer below the peat revealed a long memory of the system. Recharge through the peat layer was identified as a major source of groundwater from neon and helium isotopes in combination with water levels. Chloride concentrations showed a homogeneous fraction of 30 % sea water throughout the aquifer despite differing groundwater ages. Drainage ditches still affect groundwater flow today depending on the peat and aquifer thickness. Both nutrient-enriched, brackish, deeper groundwater and freshwater from the precipitation-fed dune dike discharge to the sea. We conclude that rewetting of coastal peatlands mainly affects the groundwater in the upper peat, with little impact on the underlying aquifer, and might revive submarine groundwater discharge and associated nutrient fluxes despite low hydraulic gradients.

An integrated study of the spatiotemporal character, pollution assessment, and migration mechanism of heavy metals in the groundwater of a subtropical mangrove wetland

Mangrove wetlands connecting the land and sea are critical and dynamic ecosystems which act as biogeochemical reactors that influence the concentrations and distributions of heavy metals in the groundwater and adjacent seawater. In this paper, a subtropical mangrove wetland in China was selected to investigate the spatiotemporal patterns of groundwater heavy metals and the driving mechanism along an intertidal transect with distinct undulated topography and vegetation zonation. Along the transect, five groundwater observation wells (W1-5) were set to collect groundwater samples at three different sediment depths (0.5, 1.2, and 2.0 m) and the advective flux between groundwater and surface water were calculated during four seasonal sampling campaigns from 2019 to 2020. The results showed that the seaward W1-3 acted as the groundwater discharge area while the landward W4-5 served as the surface water recharge area. The results of single-factor contamination index showed that a potential pollution risk of Hg existed at the study sites. The distribution of other heavy metals in the mangrove groundwater exhibited a seasonal variability along the transect during the sampling campaigns. For example, the relative high concentrations of Fe, Pb, Cu, Cr, and Zn focused in the landward zones in the dry seasons (autumn and winter 2019), whereas they changed to the seaward zones in the wet seasons (summer and autumn 2020). Moreover, the intertidal aquifer can act as a sink to enrich heavy metals in winter 2019 and autumn 2020 but become a source to discharge heavy metals to the sea in summer 2020. The above migration patterns of heavy metals were ascribed to the multiple complex factors including the seawater-groundwater interactions, vegetation zonation, biogeochemical reactions, and anthropogenic activities. This study contributed to the better understanding of heavy metal behaviors in mangrove groundwater so as to improve the sustainable management of mangrove wetlands under the pressure of anthropogenic activities and climate change.

The Effect and Sustainable Management of Simply Overdraft in Two Different Groundwater Observation Wells

The term overdraft has been defined as a situation in which groundwater extraction by pumping exceeds the aquifer charge over an extended period of time. Groundwater is the main source of drinking and utility water in rural areas, especially in arid and semi-arid regions. The aquifer is recharged by precipitation, rivers, and lakes. Causes such as the increase in temperatures due to climate change, decrease in precipitation, pollution of aquifers with wastes negatively affect the recharge of groundwater. When unlicensed wells and unconscious use of water in agriculture are added to all these reasons, which increase overdraft, the future of groundwater is endangered. For this reason, the sustainable management of groundwater is of great importance. In this study, changes in water levels were investigated by using the data of some observation wells within the borders of Uluova micro-basin in Elazig Province, one of the sub-basins of the Fırat basin, one of the important basins of Turkey. The study was carried out by comparing the seasonal water level measurements of two different observation wells drilled at the same ground level in Yurtbaşı and Yazıkonak towns within the borders of the Uluova basin in 2011-2018. Seasonal water level measurements for each year in the relevant observation wells were made in September when the water level is the lowest and in April when the water level is the highest. In both observation wells, it was observed thatgroundwater levels dropped significantly in September, the end of the dry period. Except for 2018, it was observed that the water levels in the Yurtbaşı observation well in September and April decreased much more than the water levels in the Yazıkonak observation well. In the September 2018 measurement, the measurement could not be made because the water in the Yazıkonak observation well was completely exhausted. When the seasonal water changes in the wells are examined, it can be said that the seasonal water level change in the Yurtbaşı observation well is more pronounced, except for 2018. As a result, it was observed that the water level in both wells decreased with each passing year compared to the previous year. This shows that overdraft results should be investigated in more detail by examining different observation wells in the region. In addition, it has been understood that it is very important to create a management model for the sustainability of groundwater resources by using the data of other observation wells in the basin.
 Keywords: Groundwater, Overdraft, Well, Sustainable management*This study has been produced from the PhD research titled “Uluova Mikro Havzası Yeraltı Sularının Sürdürülebilir Yönetimi (Sustainable Management of the Uluova Micro Basin)” which is being prepared in the Graduate School of Sciences Fırat University, Department of Civil Engineering, Hydraulic Doctorate Program

Research on soil physical characteristics and dynamic response of groundwater to irrigation in typical irrigation area of Huangshui River Basin

Under the influence of the natural and human factors, water table of irrigated area Changes frequently, but it is mainly affected by irrigation water infiltration replenishment. Basic physical properties of different soil layer of the typical field were determined and analyzed, and 5 groundwater observation wells were constructed to carry out the experiment of the response of groundwater to irrigation. The results showed that the upper vertical 0-40 cm is loose, the 40-60 cm layer is relatively tight, and the lower part 60-200 cm tend to loose again. Soil saturated water holding capacity, capillary water holding capacity and field capacity showed increased first and then decreased trend with the increase of soil depth. They almost showed the same nearly evenly spaced degressive trend. The groundwater stage dynamic change rule of spring and seedling irrigation stage in the typical plot was fit to the hydrological geology condition of grade-Iterrace of Huangshui river valley. Lateral canal water direction formed a line effect. The rangeability of water table of spring irrigation period was significantly higher than that of seedling irrigation period.

Detection, characterization, and analysis of land subsidence in Nairobi using InSAR

Nairobi, Kenya’s capital city, is one of the fastest-growing cities on the continent. The rapid expansion of human activities has resulted in the overexploitation of natural resources, such as water. In the past, Nairobi had been identified as a vulnerable area to environmental hazards, such as land subsidence. Due to the lack of a functioning deformation-monitoring system in Kenya, the subsidence in Nairobi has yet to be empirically quantified. In this paper, we report the results of the first InSAR-based spatial assessment of land subsidence in Nairobi. Our analysis indicates both localized and regionalized subsidence in several locations in the west and north west of Nairobi. The largest deforming unit in Nairobi’s western part is subsiding at approximately 62 mm/yr. Land subsidence can be attributed to groundwater overexploitation because it coincides with regions with the highest decline in groundwater levels. However, subsidence can also be attributed to consolidation associated with rapid urbanization in other areas such as east of Nairobi. This evaluation corroborates previous hydrogeological investigations which indicated that Nairobi was at risk of subsidence, contributing to flooding in some residential areas. The findings will help guide future decision-making in several agencies as well as provide an effective tool for planning mitigation measures to prevent further subsidence. A few of these include regulating borehole drilling, planning of roads and buildings, and locating groundwater observation wells. In addition, the observed significant land subsidence stresses the need for an updated geodetic reference system. Since Nairobi plays a significant role in the economy of Kenya, the effects of subsidence may be devastating and it is imperative that steps are taken to minimize their impact.

Characterization of Regional Groundwater System Based on Aquifer Response to Recharge–Discharge Phenomenon and Hierarchical Clustering Analysis

The investigations of groundwater hydrograph reasonably reflect the aquifer response to recharge–discharge phenomenon and its characteristics. A better understanding of aquifer characteristics such as regional aquifer classification, recharge and discharge patterns, aquifer geology and flow patterns are the surface indicators that may be more effective and less costly for interpreting basic regional hydrogeological conditions and assessments. This study deals with the application of Hierarchical Clustering Analysis to understand the groundwater spatio-temporal patterns and to visualize/classify the nature of the aquifer in the regional area of Kaohsiung City, Taiwan. Groundwater level fluctuation patterns and slopes of rising and recession limbs are used to identify the pumping effects and classify aquifers. The results of clustering analysis show that the groundwater observation wells in the study area can be divided into five major characteristics along with the upstream to downstream of Kaoping River. The clusters are consistent with basic lithology distribution and age of sedimentary, which represents the characteristics of groundwater level fluctuation. The identified groundwater hydrographs patterns provide newer insights related to aquifer response to recharge–discharge phenomenon, types of aquifers and their behaviors. The knowledge of water level fluctuations in the observation wells provides a piece of prior information about the abstraction of groundwater. The proposed aquifer classification and pumping effect have great potential for applied use in groundwater management e.g., save drilling cost.

Space-Time Evolutions of Land Subsidence in the Choushui River Alluvial Fan (Taiwan) from Multiple-Sensor Observations

Land subsidence is a significant problem around the world that can increase the risk of flooding, damage to infrastructure, and economic loss. Hence, the continual monitoring of subsidence is important for early detection, mechanism understanding, countermeasure implementation, and deformation prediction. In this study, we used multiple-sensor observations from the Continuous Global Positioning System (CGPS), the small baseline subset (SBAS) algorithm, interferometric synthetic-aperture radar (InSAR), precise leveling, multi-layer compaction monitoring wells (MLCWs), and groundwater observation wells (GWs) to show the spatial and temporal details of land subsidence in the Choushui River alluvial fan (CRAF), Taiwan, from 1993 to 2019. The results showed that significant land subsidence has occurred along the coastal areas in the CRAF, and most of the inland subsidence areas have also experienced higher subsidence rates (>30 mm/yr). The analysis of subsidence along the Taiwan High Speed Rail (THSR) revealed a newly formed subsidence center between Tuku and Yuanchang Townships in Yunlin, with high subsidence rates ranging from 30 to 70 mm/yr. We propose a map showing, for the first time, the distribution of deep compactions occurring below 300 m depth in the CRAF.

Seasonal dynamics modifies fate of oxygen, nitrate, and organic micropollutants during bank filtration\xa0\u2014\xa0temperature-dependent reactive transport modeling of field data

Bank filtration is considered to improve water quality through microbially mediated degradation of pollutants and is suitable for waterworks to increase their production. In particular, aquifer temperatures and oxygen supply have a great impact on many microbial processes. To investigate the temporal and spatial behavior of selected organic micropollutants during bank filtration in dependence of relevant biogeochemical conditions, we have set up a 2D reactive transport model using MODFLOW and PHT3D under the user interface ORTI3D. The considered 160-m-long transect ranges from the surface water to a groundwater extraction well of the adjacent waterworks. For this purpose, water levels, temperatures, and chemical parameters were regularly measured in the surface water and groundwater observation wells over one and a half years. To simulate the effect of seasonal temperature variations on microbial mediated degradation, we applied an empirical temperature factor, which yields a strong reduction of the degradation rate at groundwater temperatures below 11 °C. Except for acesulfame, the considered organic micropollutants are substantially degraded along their subsurface flow paths with maximum degradation rates in the range of 10−6 mol L−1 s−1. Preferential biodegradation of phenazone, diclofenac, and valsartan was found under oxic conditions, whereas carbamazepine and sulfamethoxazole were degraded under anoxic conditions. This study highlights the influence of seasonal variations in oxygen supply and temperature on the fate of organic micropollutants in surface water infiltrating into an aquifer.

Combining Groundwater Flow Modeling and Local Estimates of Extreme Groundwater Levels to Predict the Groundwater Surface with a Return Period of 100 Years

Knowledge about extreme groundwater levels is needed to avoid structural or environmental damage by groundwater flooding. Typically, distributions of extreme groundwater levels are generated by interpolation between results derived from local extreme value analysis at groundwater observation wells. As an alternative methodology, we propose to apply the Gumbel distribution to groundwater level time series, which are computed by a groundwater flow model. In the approach, model-based and observation-based extreme groundwater values are compared at every observation well using the model simulation period and the longest available observation period to calculate correction values that are regionalized over the model area. We demonstrate the applicability of the approach at the Südliches Wiener Becken (SWB) aquifer south of Vienna, where a groundwater flow model between 1993 to 2017 is available to compute the distribution of the groundwater levels with a hundred year return period (GLsWHYRP). We could show that the resulting GLsWHYRP are generally increased in regions of groundwater recharge and decreased in regions of groundwater discharge. The developed approach can also be used to assess the impact of changing boundary conditions on groundwater level and extreme highs and lows based on corresponding model scenarios.

Drought characterization using the Combined Terrestrial Evapotranspiration Index over the Indus, Ganga and Brahmaputra river basins

Drought is a recurring natural disaster, which significantly affects the economy and environment of diverse geographical area worldwide. Therefore, it is imperative to develop a new technique that enables comprehensive identification and monitoring of drought over a large spatial extent. In this study, a new drought index called Combined Terrestrial Evapotranspiration Index (CTEI) is developed by using a combination of Gravity Recovery and Climate Experiment (GRACE) data and meteorological parameters, i.e. precipitation (P) and potential evapotranspiration (PET) over the Indus, Ganga, and the Brahmaputra (IGB) river basins. Further, the results of CTEI are compared with pre-existing drought indices, which highlighted good correlation with GRACE Groundwater Drought Index (GGDI) (ρ = 0.88), Water storage deficit index (WSDI) (ρ = 0.96), Combined Climatologic Deviation Index (CCDI) (ρ = 0.97) and Standardized Precipitation-Evapotranspiration Index (SPEI) (ρ = 0.49). It also compared with In-situ Groundwater Drought Index (IGDI) derived by groundwater observation wells. The mean annual CTEI exhibited a strong correlation with IGDI (0.49 to 0.77) and climatic parameters (P, PET, and land surface temperature). Outcomes illustrated a significant potential of CTEI index and extended the utility of GRACE derived Terrestrial Water Storage observations for drought characterization as well as quantification of its severity.

Land subsidence due to groundwater extraction and tectonic activity in Pingtung Plain, Taiwan

Abstract. Pingtung coastal plain, located at the active convergent boundary between Philippine Sea Plate and Eurasian Plate, is one of the most active areas regarding tectonic deformation in Taiwan. Groundwater over-pumping for aquaculture along the coast area of Pingtung plain induced a serious land subsidence problem for decades. How much land subsidence contributed by tectonic activity and groundwater pumping is a crucial issue for tectonic study and groundwater management in this area. This study collected the data in different fields and proposed a conceptual model to calculate the quantities of land subsidence caused by natural (tectonic) and human (pumping) factors. The data from the Global Positioning System (GPS) are used to illustrate the total subsidence concerning vertical displacement. A system called the multi-level compaction monitoring well (MCMW) is able to measure the vertical compaction in different depths from the earth surface to the depth of 200 m. Two GPS stations, named CLON and FALI, close to two MCMWs, named Jiadong and Fangliao, are adopted for analysis The data during 2007 and 2016 taken from MCMWs and groundwater observation wells indicate that the compaction in the shallow depth should be mainly caused by groundwater over-pumping due to their high correlation coefficients (from 0.58–0.95). The difference of the vertical deformation between GPS and MCMW indicates that there is deformation beyond the depth within 200 m. From the data and literature, the further vertical deformation should be due to tectonic activity associated with tectonic escape and extrusion of the Taiwan orogen with average vertical deformation from −3.0 to −4.4 mm. Therefore, the quantities of land subsidence contributed by local groundwater over-pumping and regional tectonic activities are successfully separated. The method and concept proposed in this study can be used in land subsidence quantification due to both tectonic activity and groundwater over-pumping.

Using Satellite‐Based Vegetation Cover as Indicator of Groundwater Storage in Natural Vegetation Areas

AbstractNormalized Difference Vegetation Index (NDVI) is widely used as an efficient indicator of vegetation cover. Here we assess the possibility of using NDVI as an indicator of groundwater storage. We used groundwater level (GWL) obtained from in situ groundwater observation wells (n > 15,000) in India in 2005–2013. Good correlation (r > 0.6) is observed between NDVI and GWL in natural vegetation‐covered areas, that is, forest lands, shrubs, and grasslands. We apply artificial neural network and support vector machine approaches to investigate the relationship between GWL and NDVI using both of the parameters as input. Artificial neural network‐ and support vector machine‐simulated GWL matches very well with observed GWL, particularly in naturally vegetated areas. Thus, we interpret that NDVI may be used as a suitable indicator of groundwater storage conditions in certain areas where the water table is shallow and the vegetation is natural and where in situ groundwater observations are not available.

Temperature-dependent redox zonation, nitrate removal and attenuation of organic micropollutants during bank filtration

River bank filtration (RBF) is considered to efficiently remove nitrate and trace organic micropollutants (OMP) from polluted surface waters. This is essential for maintaining good groundwater quality and providing high quality drinking water. Predicting the fate of OMP during RBF is difficult as the biogeochemical factors controlling the removal efficiency are not fully understood. To determine in-situ removal efficiency and degradation rates of nitrate and OMP indicator substances we conducted a field study in a RBF system during a period of one and a half years incorporating temporally and spatially varying redox conditions and temperature changes typically occurring in temperate climates. RBF was analyzed by means of mixing ratios between infiltrated river water and groundwater as well as average residence times of surface water towards the individual groundwater observation wells. These results were used to calculate temperature dependent first order degradation rates of redox sensitive species and several OMP. Five out of ten investigated OMP were completely removed along RBF pathways. We demonstrate that degradation rates of several OMP during bank filtration were controlled by redox conditions and temperature whereby temperature itself also had a significant influence on the extent of the most reactive oxic zone. The seasonal variations in temperature alone could explain a considerable percentage of the variance in dissolved oxygen (34%), nitrate (81%) as well as the OMPs diclofenac (44%) and sulfamethoxazole (76%). Estimated in-situ degradation rates roughly varied within one order of magnitude for temperature changes between 5 °C and 20 °C. This study highlights that temporal variability in temperature and redox zonation is a significant factor for migration and degradation of nitrate and several OMPs.