Groundwater Elevation Research Articles

Groundwater dependence of riparian woodlands and the disrupting effect of anthropogenically altered streamflow.

Riparian ecosystems fundamentally depend on groundwater, especially in dryland regions, yet their water requirements and sources are rarely considered in water resource management decisions. Until recently, technological limitations and data gaps have hindered assessment of groundwater influences on riparian ecosystem health at the spatial and temporal scales relevant to policy and management. Here, we analyze Sentinel-2-derived normalized difference vegetation index (NDVI; n = 5,335,472 observations), field-based groundwater elevation (n = 32,051 observations), and streamflow alteration data for riparian woodland communities (n = 22,153 polygons) over a 5-y period (2015 to 2020) across California. We find that riparian woodlands exhibit a stress response to deeper groundwater, as evidenced by concurrent declines in greenness represented by NDVI. Furthermore, we find greater seasonal coupling of canopy greenness to groundwater for vegetation along streams with natural flow regimes in comparison with anthropogenically altered streams, particularly in the most water-limited regions. These patterns suggest that many riparian woodlands in California are subsidized by water management practices. Riparian woodland communities rely on naturally variable groundwater and streamflow components to sustain key ecological processes, such as recruitment and succession. Altered flow regimes, which stabilize streamflow throughout the year and artificially enhance water supplies to riparian vegetation in the dry season, disrupt the seasonal cycles of abiotic drivers to which these Mediterranean forests are adapted. Consequently, our analysis suggests that many riparian ecosystems have become reliant on anthropogenically altered flow regimes, making them more vulnerable and less resilient to rapid hydrologic change, potentially leading to future riparian forest loss across increasingly stressed dryland regions.

Using isotopes and hydrogeochemistry to characterize groundwater flow systems within intensively pumped aquifers in an arid inland basin, Northwest China

The impacts of long-term pumping on groundwater flow patterns and groundwater chemistry are unclear in the Manas River Basin, an arid inland basin in Northwest China. In this study, hydraulic heads, hydrochemistry and environmental isotopic tracers were analyzed to reveal groundwater flow patterns, recharge sources and deduce hydrogeochemical processes in this highly exploited aquifer system. Spatial trends in the isotopic ratios δ18O and δ2H indicate that groundwater originates from glacial melting and precipitation in the mountainous area. In the piedmont plains, dissolution of calcite, gypsum and dolomite yields a groundwater type dominated by Ca-HCO3-SO4 with TDS of 300 mg/L. In this area, high 3H concentrations demarcate local flow systems and imply modern precipitation recharge. Downgradient in the lowlands, irrigation return flow recharges shallow groundwater through local flow paths. Groundwater pumping has intensified vertical hydraulic gradients causing vertical mixing between aquifers. Generally, across the basin, regional flow systems contain groundwater with 14C ages ranging from modern to 33,000 years, with the oldest waters found in wells with depths greater than 200 m. From high to low elevation groundwater chemistry transitions from Ca-HCO3-SO4 to Na-Cl-SO4 type as concentrations of Cl− and overall TDS increase. The replacement of Ca2+ with Na+ as the dominant cation suggests reverse ion exchange and carbonate precipitation occur along the intermediate and regional flow paths. Anthropogenic activities (i.e. pumping, irrigation return flow, application of fertilizers) impact shallow groundwater chemistry (<60 m). This research reveals the impacts of natural and human-induced hydrogeochemical processes impacting groundwater chemistry in this basin with implications for similar semi-arid to arid, inter-montane basins around the world.

The Shear Strength Parameters as a Function of the Volumetric Water Content of Baghdad City Soils at Tigris River Bank

The capital of Iraq, Baghdad city, is considered one of the regions with a diverse soil composition besides the various characteristics of these soils. The subbase layers can be divided into three zones that are fully saturated, partially saturated, and dry state. This research accomplishes the investigation and assessment of the geotechnical attributes of soil layers of the city, where these characteristics are associated with the ground water elevation. The water level disparity of the Tigris River was correlated with variation of the ground water level and with geotechnical results of more than 260 boreholes. The analysis of the output data revealed that undrained shear strength parameters of soil layers near the Tigris river bank is controlled by the flocculation of the water in the river. New relationships were developed associating the volumetric water content (VWC) with shear strength parameters of these soils (cu and ϕ). These empirical equations show that predicting strength compounds of partially saturated soils as a linear relation for the angle of internal friction and nonlinear for soil cohesive function with (VWC). Where is an increase of the amount of saturation in the (VWC) results a decrease in strength properties for the soil (cu and ϕ).

Analysis of spatio-temporal trend in groundwater elevation data from arsenic affected alluvial aquifers – Case study from Murshidabad district, West Bengal, Eastern India

Fluctuation in groundwater level is a time-dependent stochastic process. It is also a function of various inflow and outflow components to and from the hydrologic system concerned. Depth to water level data are measured through a network of observation wells or hydrograph stations to ascertain the degree of fluctuation in groundwater level at the desired scale, on a long-term basis. Basically, these depths to water level data are point measurements, which can be regarded as random variables furnishing changes in groundwater storage over time. The intrinsic in-homogeneity in aquifer materials introduces variations like jumps, trends, and periodicities in such hydrologic time series data. Thus, trending results from certain gradual, natural and/or anthropogenic interventions in the hydrologic environment and analyses of their trends are imperative for assessment of groundwater level scenario in the area of interest. This in turn, is essential for strategic planning and management for exploitation of the precious groundwater resource in the same area. The area of interest in this article, i.e., Murshidabad is one of the nine arsenic affected districts of West Bengal. Here, contamination persist within, shallow, arseniferous, alluvial aquifers, which are otherwise widely exploited for irrigation purposes. According to many researchers working in this area, over-exploitation of groundwater is the root cause for the plummeting water level and the widespread arsenic contamination as well. The present study intends to detect and analyze the trends persisting in the depth to water level data measured over a period from 1996 to 2016, in Murshidabad district of West Bengal, India, amidst its complex and contrasting hydrogeologic set-up and interpret the results in terms of the hydrologic attributes of the Bengal basin as a whole. The non-parametric Mann–Kendall test and the Sen’s slope estimator have been used to identify the linear trend persisting in the time series pre- and post-monsoon groundwater elevation values. The analysis indicates statistically significant decline in water level across the study area especially during the post-monsoon season. This can be attributed to the recharge–discharge disparity within the hydrologic regime; brought through intense pumping over the study area. Its ill effect being particularly observed in the western part of river Bhagirathi. Findings of such study are crucial for assessment of dynamic groundwater resources of the district and subsequently can be utilized as a decision support tool for groundwater management at micro-level.

Result-based management approach for aquifer restoration problems using a combined numerical simulation – parallel evolutionary optimization model

Result-based management (RBM) has been used as a new management approach for groundwater resources planning. Based on this approach, three levels of results including outputs (aquifer stability), outcomes (positive balance), and impacts (aquifer restoration) have been considered in this study. To monitor these levels, three indicators based on sustainability, filling, and restoration definitions are given to describe the associated RBM aquifer restoration problems. In this study, a combined simulation–optimization model has been developed using a MODFLOW-based numerical simulation model and a parallel evolutionary algorithm of continuous ant colony optimization. The model has been applied to a real case study of Namdan aquifer located in Fars province, Iran, over a planning horizon of 10 years. Three levels of outputs, outcomes, and impacts have been achieved and the effectiveness of RBM approach in groundwater resources management has been assessed. The important observations are: (1) The planning based on the management problems of sustainability, filling, and restoration indicators leads to an increase in the groundwater elevation by 3, 9.47, and 10.61 m at the end of management period in comparison with the beginning of the period; (2) The planning based on the restoration indicator causes the highest level of rise in groundwater elevation and reaches the restoration target as highlighting the significance of a proper management setup to achieve the proposed target; (3) The investigations based on reliability, utility, and vulnerability indicators show the improvement of aquifer restoration status over the results chain. The methodology given in this study can be a novel approach to the realistic management of groundwater resources considering the proposed targets while it can be improved by the involvement of stakeholders and beneficiaries in RBM implementation.

Multi-objective optimization of groundwater monitoring network using a probability Pareto genetic algorithm and entropy method (case study: Silakhor plain)

Abstract Optimal groundwater monitoring networks have an important role in water resources management. For this purpose, two scenarios were presented. The first scenario designs a monitoring network and the second scenario chooses optimal wells from the existing ones in the study area of the monitoring network. At the first step, a database including groundwater elevation in potential wells was produced using the Kriging method. The optimal monitoring network in the first scenario was determined by preset conventions and found by the non-dominated sorting genetic algorithm (NSGA-II). In the second scenario, the optimal monitoring network was determined by entropy theory through calculating entropy for each of the 29 observation wells. Finally, the first scenario obtained a network with 12 observation stations showing root mean square error (RMSE) value given as 0.61 m. Comparison between entropy of rainfall and groundwater level time series in the first scenario had the same variation. The optimal monitoring network in the first scenario has been able to reduce the number of monitoring stations by 60% in comparison with the existing observation network. The second scenario used entropy theory and calculated the energy of each of the 29 observation wells which obtained a monitoring network with 11 stations.

Evaluation of recharge areas of Arusha Aquifer, Northern Tanzania: application of water isotope tracers

Abstract In Arusha urban, northern Tanzania, groundwater contributes about 80% of the water supply. However, elevated fluoride levels and evidence of anthropogenic pollution have been reported in the groundwater around Mount Meru which is a water source for Arusha urban. This study aims at understanding the recharge areas and flow pathways of groundwater in what has been a poorly monitored area. The study uses the isotopic ratio of oxygen and hydrogen to estimate the groundwater recharge area and flow pathway. The results show the recharge elevation of groundwater is between 1,800 and 3,500 m above mean sea level on the slopes of Mount Meru. The average fluoride contents in the study area are 5.3 ± 0.4 mg/L greater than the limits of 1.5 mg/L set by the World Health Organization (WHO) and Tanzania. The nitrate concentration of 83.9 mg/L at the lower elevation areas (&amp;lt;1,400 m above mean sea level) exceeds the 50 mg/L WHO limit. The relationship of F− with δ18O and NO3− suggests the leaching of fluoride in high altitudes and dilution in lower altitudes.

Hydrogeochemical modeling for groundwater management in arid and semiarid regions using MODFLOW and MT3DMS: A case study of the Jeffara of Medenine coastal aquifer, South‐Eastern Tunisia

AbstractThe study of water quality and the quantification of reserves and their variations according to natural and anthropogenic forcing is necessary to establish an adequate management plan for groundwater resources. For this purpose, a modeling approach is a useful tool that allows, after calibration phase and verification of simulation, and under different scenarios of forcing and operational changes, to estimate and control the groundwater quantity and quality. The main objective of this study is to collect all available data in a model that simulates the Jeffara of Medenine coastal aquifer system functioning. To achieve this goal, a conceptual model was constructed based on previous studies and hydrogeological investigations. The regional groundwater numerical flow model for the Jeffara aquifer was developed using MODFLOW working under steady‐state and transient conditions. Groundwater elevations measured from the piezometric wells distributed throughout the study area in 1973 were selected as the target water levels for steady state (head) model calibration. A transient simulation was undertaken for the 42 years from 1973 to 2015. The historical transient model calibration was satisfactory, consistent with the continuous piezometric decline in response to the increase in groundwater abstraction. The developed numerical model was used to study the system's behavior over the next 35 years under various constraints. Two scenarios for potential groundwater extraction for the period 2015–2050 are presented. The predictive simulations show the effect of the increase of the exploitation on the piezometric levels. To study the phenomenon of salinization, which is one of the most severe and widespread groundwater contamination problems, especially in coastal regions, a solute transport model has been constructed by using MT3DMS software coupled with the groundwater flow model. The best calibration results are obtained when the connection with the overlying superficial aquifer is considered suggesting that groundwater contamination originates from this aquifer.Recommendations for water resource managers The results of this study show that Groundwater resources of Jeffara of Medenine coastal aquifer in Tunisia are under immense pressure from multiple stresses. The water resources manager must consider the impact of economic and demographic development in groundwater management to avoid the intrusion of saline water. The results obtained presented some reference information that can serve as a basis for water resources planning. The model runs to provide information that managers can use to regulate and adequately control the Jeffara of Medenine water resources.

Relationship betweem vegatation and relative elevation of groundwater after cutting down a ground in Hororo area, Kushiro Wetland

Relationship betweem vegatation and relative elevation of groundwater after cutting down a ground in Hororo area, Kushiro Wetland

Seepage Velocity: Large Scale Mapping and the Evaluation of Two Different Aquifer Conditions (Silty Clayey and Sandy)

Seepage velocity is a very important criterion in infrastructure construction. The planning of numerous large infrastructure projects requires the mapping of seepage velocity at a large scale. To date, however, no reliable approach exists to determine seepage velocity at such a scale. This paper presents a tool within ArcMap/Geographic Information System (GIS) software that can be used to map the seepage velocity at a large scale. The resultant maps include both direction and magnitude mapping of the seepage velocity. To verify the GIS tool, this study considered two types of aquifer conditions in two regions in Iraq: silty clayey (Babylon province) and sandy (Dibdibba in Karbala province). The results indicate that, for Babylon province, the groundwater flows from the northwest to southeast with a seepage velocity no more than 0.19 m/d; for the Dibdibba region, the groundwater flows from the west to the east with a seepage velocity not exceeding 0.27 m/d. The effectiveness of the presented tool in depicting the seepage velocity was thus demonstrated. The accuracy of the resultant maps depends on the resolution of the four essential maps (groundwater elevation head, effective porosity, saturated thickness, and transmissivity) and locations of wells that are used to collect the data.

Exploiting Earth Observation Data to Impute Groundwater Level Measurements with an Extreme Learning Machine

Groundwater resources are expensive to develop and use; they are difficult to monitor and data collected from monitoring wells are often sporadic, often only available at irregular, infrequent, or brief intervals. Groundwater managers require an accurate understanding of historic groundwater storage trends to effectively manage groundwater resources, however, most if not all well records contain periods of missing data. To understand long-term trends, these missing data need to be imputed before trend analysis. We present a method to impute missing data at single wells, by exploiting data generated from Earth observations that are available globally. We use two soil moisture models, the Global Land Data Assimilation System (GLDAS) model and National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) soil moisture model to impute the missing data. Our imputation method uses a machine learning technique called Extreme Learning Machine (ELM). Our implementation uses 11 input data-streams, all based on Earth observation data. We train and apply the model one well at a time. We selected ELM because it is a single hidden layer feedforward model that can be trained quickly on minimal data. We tested the ELM method using data from monitoring wells in the Cedar Valley and Beryl-Enterprise areas in southwest Utah, USA. We compute error estimates for the imputed data and show that ELM-computed estimates were more accurate than Kriging estimates. This ELM-based data imputation method can be used to impute missing data at wells. These complete time series can be used improve the accuracy of aquifer groundwater elevation maps in areas where in-situ well measurements are sparse, resulting in more accurate spatial estimates of the groundwater surface. The data we use are available globally from 1950 to the present, so this method can be used anywhere in the world.

Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency

Historical wetland hydrology data are instrumental to support the design of wetland management and restoration strategies but are rarely available. In this study, we tested the capabilities and limitations of a simple methodological framework based on publicly available MODIS Land Reflectance Products to estimate wetland soil surface saturation and inundation spatiotemporal dynamics. Using supervised learning and high-resolution groundwater and surface water elevation data, the framework searches for spectral algorithms, referred to as the wet/dry wetland status classifier (WSC) and the continuous wetland dynamics identifier (WDI), that best predict upper soil layer wetness status in the study wetland. We used Google Earth Engine (GEE) for fast access and processing of the full range of MODIS data. The capabilities of GEE also enabled us to readily conduct a comparative assessment of the MODIS 8-day composite and daily collections and test various pixel-level quality filters to select reliable data at the highest possible temporal resolution. We tested the framework on the internationally-recognized Ramsar site Palo Verde National Park wetland in Costa Rica, and we obtained good results (overall prediction accuracy of 86.6% and kappa coefficient of 0.7 for the WSC; r2 of 0.71 for the WDI). High-resolution water level data allowed us to assess the challenges, promises and limitations of using MODIS products for wetland hydrology applications. We then applied the WSC and WDI to map the 2000-2016 sub-weekly wetland hydroperiod at 500m resolution, achieving a temporal resolution rarely matched in remote sensing for wetland studies. The analysis of the end-products, combined with the field water elevation data, provided new insights into the drivers controlling the spatiotemporal dynamics of hydroperiod within the Palo Verde wetland and did not reveal any significant temporal trends. The WSC and WDI framework developed here can be useful for reconstructing long-term hydroperiod variability and uncovering its drivers for other wetland systems globally.

Prediction of Wetland Hydrogeomorphic Type Using Morphometrics and Landscape Characteristics

Accurate spatial maps of wetlands are critical for regional conservation and rehabilitation assessments, yet this often remains an elusive target. Such maps ideally provide information on wetland occurrence and extent; hydrogeomorphic (HGM) type; and condition/ level of degradation. All three elements are needed to provide ancillary layers to support mapping from remote imagery and ground-truthing. Knowledge of HGM types is particularly important, because different types show differential levels of sensitivity to degradation, and modeling accuracy for occurrence. Here, we develop and test a simple approach for predicting the most likely HGM type for mapped yet unattributed wetland polygons. We used a dataset of some 11,500 wetland polygons attributed by HGM types (floodplain, depression, seep, channeled and un-channeled valley-bottom) from the Western Cape Province in South Africa. Polygons were attributed and described in terms of nine landscape metrics, at a sub-catchment scale. Using a combination of box-and-whisker plots and PCA, we identified four variables (groundwater depth, relief ratio, slope and elevation) as being the most important variables in differentiating HGM types. We divided the data into equal parts for training and testing of a simple Bayesian network model. Model validation included field assessments. HGM types were most sensitive to elevation. Model predication was good, with error rates of only 32%. We conclude that this is a useful technique that can be widely applied using readily available data, for rapid classification of HGM types at a regional scale.

Combined use of stable isotopes and hydrochemical characteristics to determine streamflow sources in the Jonkershoek catchment, South Africa

ABSTRACT The stable isotopes of water (18O, 2H) and other hydrochemical properties were used to assess seasonal changes between sources of stream water and flow pathways in baseflow conditions for two headwater sub-catchments (∼3 km2) of the Jonkershoek, a mountainous catchment in the Western Cape of South Africa. The sub-catchments differ in land cover, one is dominated by indigenous fynbos vegetation and the other by pine plantation. Stream water, higher elevation springs, and lower elevation groundwater samples were collected monthly from January 2018 to January 2019, and were analysed for stable isotopes, electrical conductivity (EC) and pH. The stream water isotopic values resembled those of groundwater during the dry and wet seasons. Results indicated a steady contribution of spring discharge to streams during the dry season, with rainfall contribution less evident. Wet season flows were attributed to interflow including perennial and ephemeral springs. Spatial variations in EC between the sub-catchments were indicative of a greater proportional input from subsurface water, more evaporation and/or more mineral dissolution in the pine-dominated sub-catchment. The spatiotemporal variability in EC was significantly larger than for the stable isotopes. These findings enabled conceptualization of streamflow generation processes that can support strategic water resource management practices in this region.

Effect of excess soil water on the development of Bermuda grass (Cynodon spp.)

ABSTRACT Soil drainage is an important technique in the construction of a sports lawn and information about the sensitivity of the crop to excess water influences the design of the project. Assuming that excess water affects the development of the grass and that the indices SEW30 (Sum of Excess Water above 0.30 m depth) and SDI (Stress-Day Index) are sensitive to the variables of development of the crop, the objective was to identify the sensitivity of Bermuda grass to the excess of water. The experimental design was completely randomized with five treatments and four repetitions. The treatments consisted of groundwater elevations: 0 cm d (at the level of the drains - control); 180 cm d (at 0.20 m from the soil surface); 270 cm d (at 0.15 m from the soil surface); 360 cm d (at 0.10 m from the soil surface); and 450 cm d (at 0.05 m from the soil surface), carried out fortnightly, lasting three days. The variables used to test the treatment were root length, photosynthesis rate, dry mass of roots, stolons, rhizomes, culms and leaves and dry mass of grass clippings. Stress caused by excess water near the soil surface reduced root length, dry mass of culms and leaves, and photosynthesis rate; Bermuda grass was more sensitive to excess water in its initial vegetative stage, which occurs until 42 days after planting; and the photosynthesis rate in the treatment with highest stress level decreased by approximately by 2/3 when compared to the condition of no water table.

Study of Leachate Penetration in Shallow Groundwater Around Jabon Landfill Sidoarjo

This study was conducted at Jabon Landfill located in Jabon District, Sidoarjo. Jabon Landfill has been operating since 2003 with the Controlled Landfill system. Laboratory test results of samples taken at 18 sampling points in the east, south and west zones of the landfill for Total Dissolved Solid (TDS), Turbidity, Manganese (Mn) and Chloride (Cl−) parameters showed that they were higher than the quality standards except Iron (Fe). According to the groundwater elevation, contaminants were dispersed towards the east and south of the Landfill. Leachate pollutant index was 7.70 which means it was moderately polluted. A well was used as a source of clean water but the well water has a quality status of moderately polluted and lightly polluted. The distance and depth of initial groundwater have a significant effect on the status of water quality.

Importance of Spatial Resolution in Global Groundwater Modeling.

Global-scale gradient-based groundwater models are a new endeavor for hydrologists who wish to improve global hydrological models (GHMs). In particular, the integration of such groundwater models into GHMs improves the simulation of water flows between surface water and groundwater and of capillary rise and thus evapotranspiration. Currently, these models are not able to simulate water table depth adequately over the entire globe. Unsatisfactory model performance compared to well observations suggests that a higher spatial resolution is required to better represent the high spatial variability of land surface and groundwater elevations. In this study, we use New Zealand as a testbed and analyze the impacts of spatial resolution on the results of global groundwater models. Steady-state hydraulic heads simulated by two versions of the global groundwater model G3 M, at spatial resolutions of 5 arc-minutes (9 km) and 30 arc-seconds (900 m), are compared with observations from the Canterbury region. The output of three other groundwater models with different spatial resolutions is analyzed as well. Considering the spatial distribution of residuals, general patterns of unsatisfactory model performance remain at the higher resolutions, suggesting that an increase in model resolution alone does not fix problems such as the systematic overestimation of hydraulic head. We conclude that (1) a new understanding of how low-resolution global groundwater models can be evaluated is required, and (2) merely increasing the spatial resolution of global-scale groundwater models will not improve the simulation of the global freshwater system.

Sensitivity Analysis of a Groundwater Infiltration Model and Sea-Level Rise Applications for Coastal Sewers

Groundwater elevations in coastal cities will be affected by climate-change-induced sea level rise (SLR) and wastewater collection systems will experience increased groundwater infiltration (GWI) due to greater submergence of sewer pipes. Commercial sewer hydraulics models consider GWI to be a constant quantity estimated via a low-flow monitoring campaign and are incapable of predicting future flows due to changes in GW elevations. A global sensitivity analyses conducted for a two-dimensional GWI pipe flow model found the most important input parameters are groundwater head and surrounding soil hydraulic conductivity. Two case studies were conducted considering a range of pipe defect severity to estimate increases in GWI associated with predictions of future SLR. The findings are that SLR will begin to have noticeable impacts in terms of increased average dry weather flow (ADWF) as soon as 2030 (3–10%) and will increase dramatically in the future (10–29% by 2050, and 50% or more by 2100). Daily and seasonal tide ranges affect the normal diurnal flow variations by between 3% and 10%. The estimation methodology and case studies described here illustrate the coming future importance of SLR effects on GWI in coastal collection systems that should be included in facilities planning and design.

Domestic well vulnerability to drought duration and unsustainable groundwater management in California’s Central Valley

Millions of Californians access drinking water via domestic wells, which are vulnerable to drought and unsustainable groundwater management. Groundwater overdraft and the possibility of longer drought duration under climate change threatens domestic well reliability, yet we lack tools to assess the impact of such events. Here, we leverage 943 469 well completion reports and 20 years of groundwater elevation data to develop a spatially-explicit domestic well failure model covering California’s Central Valley. Our model successfully reproduces the spatial distribution of observed domestic well failures during the severe 2012–2016 drought (n = 2027). Next, the impact of longer drought duration (5–8 years) on domestic well failure is evaluated, indicating that if the 2012–2016 drought would have continued into a 6 to 8 year long drought, a total of 4037–5460 to 6538–8056 wells would fail. The same drought duration scenarios with an intervening wet winter in 2017 lead to an average of 498 and 738 fewer well failures. Additionally, we map vulnerable wells at high failure risk and find that they align with clusters of predicted well failures. Lastly, we evaluate how the timing and implementation of different projected groundwater management regimes impact groundwater levels and thus domestic well failure. When historic overdraft persists until 2040, domestic well failures range from 5966 to 10 466 (depending on the historic period considered). When sustainability is achieved progressively between 2020 and 2040, well failures range from 3677 to 6943, and from 1516 to 2513 when groundwater is not allowed to decline after 2020.

Seasonal drivers of chemical and hydrological patterns in roadside infiltration-based green infrastructure

Infiltration-based green infrastructure has become a popular means of reducing stormwater hazards in urban areas. However, the long-term effects of green infrastructure on the geochemistry of roadside environments are poorly defined, particularly given the considerable roadside legacy metal contamination from historic industrial activity and vehicle emissions (e.g., Pb). Most current research on green infrastructure geochemistry is restricted to time periods of less than a year or limited sets of chemical species. This further limits our understanding of systems that evolve over time and are subject to seasonal variability. Between 2016 and 2018, two infiltration trenches in Pittsburgh, PA, were monitored to determine infiltration rates and dissolved nutrient and metal content. The trench water was analyzed to characterize seasonal patterns in both trench function and chemistry. Shifting patterns in infiltration rate and geochemical activity show trends corresponding with seasonal changes. Trench function is dependent on the local water table, with the highest infiltration rates occurring when evapotranspiration is active and groundwater elevation is low. Two seasonal chemical patterns were identified. The first is driven by road salt application in the winter and interaction of the salt pulse increase Pb and Cu concentrations. The second is driven by the formation of summer reducing environments that increase dissolved Fe and Mn. These findings suggest that chemical and hydrological activity in infiltration-based green infrastructure varies seasonally and may remobilize legacy contamination.