The Amsterdam area, a highly manipulated delta area formed by
polders and reclaimed lakes, struggles with high nutrient levels in its
surface water system. The polders receive spatially and temporally variable
amounts of water and nutrients via surface runoff, groundwater seepage, sewer
leakage, and via water inlets from upstream polders. Diffuse anthropogenic
sources, such as manure and fertiliser use and atmospheric deposition, add to
the water quality problems in the polders. The major nutrient sources and
pathways have not yet been clarified due to the complex hydrological system
in lowland catchments with both urban and agricultural areas. In this
study, the spatial variability of the groundwater seepage impact was
identified by exploiting the dense groundwater and surface water monitoring
networks in Amsterdam and its surrounding polders. A total of 25 variables
(concentrations of total nitrogen (TN), total phosphorus (TP), NH
The hydrology of many lowland delta areas is highly manipulated by human activities such as ditching, draining, and embanking, to enable agriculture and habitation. Lowland deltas account for 2 % of the world's land, but accommodated around 600 million people in 2000, and will accommodate about 1400 million by 2060, as was estimated by Neumann et al. (2015). The reclamation of swamps and lakes and the drainage of peat areas to enable urbanisation and agriculture severely changed the hydrological, chemical, and ecological environment of these areas (Ellis et al., 2005; Yan et al., 2017). Lowland delta areas are vulnerable for water quality deterioration by processes like salinisation and eutrophication, which can be amplified by climate change (Wu et al., 2015) and land subsidence (Minderhoud et al., 2017).
The Netherlands is a densely populated country where surface water
salinisation and eutrophication are common problems. It is a typical highly
urbanised country, with two-thirds of its land lying below mean sea level. In the Netherlands, small regulated catchments called polders have been developed
over centuries by diking in and draining lakes and swamps (Huisman, 1998).
Over 10 million people are living in the coastal area, mainly in the western
part where a Holocene layer of peat and clay covers Pleistocene fluvioglacial
sands. The deepest polders, in particular, receive large amounts of groundwater
seepage. The surface water levels within the polder catchments are
artificially controlled by pumping water out into the regional water
systems (called
Influences of groundwater on surface water quality have recently gained more
attention from hydrologists (e.g. Rozemeijer and Broers, 2007; De Louw et al.,
2010; Garrett et al., 2012; Delsman et al., 2015). Rozemeijer et al. (2010)
found that groundwater seepage has large impacts on surface water quality in
a lowland agricultural catchment. A study by Holman et al. (2008) in the
United Kingdom and the Republic of Ireland also suggested that the
groundwater contribution to surface water nutrient concentrations is more
important than previously thought. Furthermore, Meinikmann et al. (2015)
found that lacustrine groundwater discharge contributed for more than
50 % of the overall external P load in their study lake. Vermonden et
al. (2009) concluded that upward seepage from the Meuse–Waal canal delivered
NO
Previous water quality research in polder area has mainly focused on the impact of land use types and topography. The impact of groundwater and flow routes on spatial water quality patterns in polders has not been systematically studied. Such insight is highly needed, as a cost-effective protection and regulation of water resources requires an integrated assessment of water and contaminant flow routes in the water system as a whole. In general, however, water and contaminant flow routes in urban settings are more complex than in rural areas, due to the highly variable surface permeability and human emissions of pollutants.
This study aimed at identifying the impact of groundwater on surface water quality in the polder catchments of the greater Amsterdam city area, which is the management area of Waternet, the organisation which manages dikes, regulates water levels and pumping regimes, and is responsible for the clean surface water, drinking water supply, and waste water treatment. To achieve this, we analysed regional surface water and groundwater quality monitoring data in combination with 10 landscape characteristic variables for 144 polders: nitrogen (N) and phosphorus (P) agricultural inputs, surface elevation, paved area percentage, surface water percentage, seepage rate, and soil type represented by calcite, humus, and clay percentages. Our statistical analyses yielded insight into the impact of groundwater on the surface water chemistry of the urban and rural polders of Amsterdam. The presented approach contributes to realistic and effective water quality regulation in the Waternet management area and can also be applied to other deltas in the world with adequate groundwater and surface water monitoring data.
Location of the research area (red) projected on the elevation map of the Netherlands (elevations in metres above mean sea level).
This study focuses on the polder catchment landscape around the city of
Amsterdam in the Netherlands. The whole study area spans 700 km
Our study area is located in the western part of the Netherlands, where large rivers and the sea have intensively interacted for millions of years. The main topographic feature is a Pleistocene sandy ice-pushed ridge with elevations ranging from 0 to 30 m, which is located in the eastern part of the study area (Figs. 1, S1 in the Supplement). To the west, the ridge is bordered by the broad periglacial Pleistocene river plains of the Rhine delta. During the Holocene, these sandy river plains were covered with peat and clay, which are currently found at the surface throughout the western part of the Netherlands, on top of Pleistocene sands. The average thickness of the Holocene peat and clay cover is 20 m, although it increases to over 50 m in former tidal inlet channels (Hijma, 2009).
In 1000 AD, about 5000 years after first settlers appeared in these lowlands, the inhabitants started mining peat, digging ditches, constructing
dikes, reclaiming former swamps and lakes, and pumping water out into a large-scale drainage system (called
The long history of marine influence stopped after closing off the estuaries
and the inland sea in the 20th century (Huisman et al., 1998). In 1932, the
construction of the Closure Dike (
The construction of the Amsterdam–Rhine Canal separated the study area into two parts (Fig. S1): central Holland in the west and the Vecht lakes area in the east. In the central Holland polders, relatively thick peat layers and pyrite-rich clays are still present in the shallow subsoil, as described by Van Wallenburg (1975). The Vecht lakes area is characterized by large open-water areas and a number of wetland nature reserves. The rest of the Vecht lakes area is mainly grassland used for dairy farming. Soils in this area are generally wet and rich in organic matter and clay (Schot and van der Wal, 1992).
Mainly during the 20th century, the urban areas have been growing from the historic city centres on river and tidal channel levees into the surrounding low-lying polders. To facilitate the construction of buildings, a 1–5 m thick layer of sand was often supplied on top of the original sediments. The thickness of this suppletion sand layer is extremely variable even on a small scale. The sand suppletions are either calcite-poor without shell fragments or calcite-rich with shell fragments that indicate their (peri-) marine origin. The spatial distribution and sources of the sand suppletions probably influence groundwater and surface water chemistry, but are poorly registered.
Conceptual model of water fluxes in a polder system in times of
water deficiency
Within the polders, the water levels are artificially maintained between
fixed boundary levels to optimise conditions for their urban or agricultural
land use.
Flow directions of surface water in water surplus and water deficiency period. “Rijnland” refers to the management area of the Rijnland Authority.
The regional flow directions in wet and dry periods in the study area are depicted in Fig. 3. The Amsterdam–Rhine Canal, the Amstel River, and the Vecht River are the main water courses discharging surface water from the south to the north in periods of water surplus (Fig. 3). In periods of water deficiency, however, the flow directions are reversed in some parts of the system.
There are six main sources of inlet water to compensate for water shortage in
dry periods (Fig. 3): (1) Amsterdam–Rhine Canal – water of the ARC
originates from the Rhine and is supplied as inlet water for the southeast
polders and polders in the southeast of Amsterdam city; (2) Amstel River – the
historic canals of the city of Amsterdam are mainly flushed by water from the
Amstel River (via the canals, this water discharges to the downstream part of
the ARC and further into the North Sea); (3) Groot Mijdrecht and Horstermeer
– the brackish surplus of seepage water from the deep polder, Groot
Mijdrecht (
Regions of the study area: (1) Zuider Zee margin, (2) upconing area (deep brackish seepage polders, Groot Mijdrecht and Horstermeer), (3) central Holland, (4) Vecht lakes and (5) ice-pushed ridge. The Amsterdam city area is circled by the blue line.
Based on the geology and paleo-hydrological history as introduced in Sect. 2.1.1, five regions were identified (see Fig. 4). The five regions are: (1) the Zuider Zee margin region, with shallow brackish groundwater, lies directly adjacent to the former saltwater Zuider Zee, which was dammed in the 1930s and transformed into the freshwater Lake IJssel (connected to Lake IJ), which is now the biggest freshwater reservoir of the Netherlands; (2) the deep polders Groot Mijdrecht and Horstermeer, which are reclaimed lakes with clayey lake sediments at the surface. These polders are characterized by upconing of salt groundwater from deeper layers (Oude Essink et al., 2005; Delsman et al., 2014) and intensive arable farming; (3) the central Holland region, where the polders are characterized by a relatively thick sequence of marine clays and intercalated peats; (4) the Vecht lakes region at the western margin of the ice-pushed ridge, characterized by shallow peat soils over a sandy subsoil and large shallow lakes and wetlands resulting from peat excavations (van Loon, 2010), mostly used for dairy farming; and (5) the ice-pushed ridge in the eastern part of the study area, which is characterized by permeable sandy soils, recharge of freshly infiltrated water, and the near absence of draining water courses.
Our a priori expectation was that the groundwater quality of these five regions is significantly different, because of their specific paleo-hydrological situations and present-day groundwater flow patterns. We therefore used the regions to evaluate the groundwater quality patterns and to give structure to our comparisons between groundwater and surface water concentrations and loads.
The database that was compiled and used for this study covers 144 individual
polders and includes monthly surface water quality data, spatiotemporally
averaged groundwater quality data (TN, NO
A total of 802 observation wells of groundwater quality are available from the period 1910–2013 (mostly after 1980), largely drawn from the National Groundwater Database DINO (TNO, DINOloket, 2016). We selected analyses from the upper 50 m of the subsurface, which corresponds with the thickness of the first main Pleistocene aquifer in the area and the Holocene cover layer. For our analyses, in order to use as much of the available groundwater data as possible to cover the entire region and all the polders, we averaged concentrations at individual monitoring screens of each monitoring well for all sampling dates available. The large majority of the groundwater quality data we used is from the last 30 years (for example, 85 % of the chloride and 93 % of the P measurements are from after 1980). In this study area, we do not expect that using some data from before 1980 would create a significant bias to the results of the study, because hydrogeochemical processes in the reactive subsurface such as sulfate reduction and methanogenesis have a stabilising effect on the water composition in this area. Moreover, the overall flow patterns have not changed much in the past 30 to 100 years, because the flow systems are completely determined by the water levels maintained in the polder systems which have not changed much over the past 100 years. However, the interface between freshwater and saltwater is known to slowly move into the direction of a new equilibrium (Oude Essink et al., 2010), but the process is known to be very slow and to continue over the next 200 years.
To analyse the spatial pattern of groundwater quality, we averaged
concentrations of all the monitoring wells located in the same polder (for
more details, see Table S2). For 24 polders out of the polders without
groundwater quality data, the concentrations were estimated by inverse
distance-weighted interpolation, however, using absolute elevation difference
instead of distance. The greater the absolute elevation difference, the less
influence the polder has on the output value. The equations
are as follows:
Because our dataset contains both freshwater and brackish to saline water, we used
the mass SO
Average concentrations in groundwater for each polder were mapped to be
compared with average annual surface water concentrations (see Sect. 2.2.2).
The potential relationship between the solute concentrations in
groundwater (TN, NO
To further explore the statistical relations in our dataset, box and scatter plots
were made to evaluate HCO
Loads represent the contribution of polders to surface water quality of the
regional water system in weight per time unit. To eliminate the impact of the
size of polders, we calculated daily load per area in
kilograms per hectare per day (kg ha
The pumping discharge is regulated to respond to water surplus or deficiency
conditions in the polder catchments. Using the pumping frequency data, we
proved that solute concentrations in pumped water are usually higher at the
beginning of each pumping activity (van der Grift et al., 2016). The pumping
rates may also influence water quality in the polder. To eliminate
differences caused by pumping rates, we used the normalised concentration
calculated using Eq. (6).
Based on a national assessment on ecosystem vulnerability, environmental
quality standards (EQSs) were set by the Water Boards (Heinis and Evers,
2007). For most ditches and channels in the clay and peat regions, EQSs of TN
and TP are 2.4 and 0.15 mg L
We statistically analysed the groundwater and surface water quality data and
landscape characteristic variables by (1) calculating the correlation
coefficients between averaged groundwater solute concentrations and
normalised concentrations of surface water using the Spearman method,
and (2) by selecting variables (based on the correlation matrix above) to be
integrated into multiple linear regression models for predicting surface
water solute concentrations. Again, the Spearman method was applied and
linear regression was based on ranks in order to avoid outliers to determine
the outcomes. The explaining variables for surface water concentrations
include groundwater solute concentrations, N and P agricultural inputs,
landscape characteristics, and the SO
Loads were used to assess the impact of different polders as sources of
solutes for the
Two models were applied for simple solute concentration calculations based on inlet water quality. Model 1 calculates the accumulation of solutes in the water body, with evaporation as the only output for water (leaving the solutes behind). Model 2 models the complete mixing and outlet of both water and solutes via other routes like the outlet weir, infiltration, and leakage. In reality, water leaves the Botshol polder partly via evaporation (Model 1) and partly via other routes (Model 2):
Model 1 (evaporation),
Spatial variation of groundwater quality. (1) Zuider Zee margin,
(2) upconing area (Groot Mijdrecht and Horstermeer), (3) central Holland, (4) Vecht
lakes, (5) ice-pushed ridge (see Fig. 4). The amount of available data of
each group is denoted by
Average groundwater concentrations (mg L
Coefficients of determination between groundwater quality and
surface water quality.
Figures 5 and 6 show the groundwater quality for the upper main aquifer under
the 144 polders for Cl, Ca, HCO
Calculated concentration of sulfate-reacted vs. groundwater chloride concentration. The black line, a, indicates the freshwater–seawater mixing line where sulfate reduction is complete.
Groundwater nutrient (TP and NH
In Fig. 5, the Zuider Zee margin, where brackish groundwater is dominant, P25
and P75 of concentrations are between 290 and 2100 mg L
The Zuider Zee margin and the upconing area showed large ranges of SO
The higher groundwater NH
Groundwater quality varied from fresh, low mineralised in the eastern
parts (Vecht lakes and ice-pushed ridge, Fig. 4) towards brackish, highly
mineralised and nutrient-rich groundwater in the northwest (Zuider Zee margin
and central Holland, Fig. 4). This relationship was further indicated by the
strong correlations between Ca and Cl (Spearman
In the more mineralised groundwater systems, sulfate reduction is a potential
cause of the significant relationship between HCO
Spatial variation of surface water quality. (1) Zuider Zee margin,
(2) upconing area, (3) central Holland, (4) Vecht lakes (5, ice-pushed ridge, not
shown due to insufficient data). The observation number of each group is denoted by
Discharge-normalised average concentrations (mg L
Figures 9 and 10 show the solute concentrations in the four regions: Zuider Zee margin, upconing area, central Holland, and Vecht lakes. Due to insufficient surface water quality data, no results are shown for several polders in the Amsterdam city area (see Fig. 4) and the ice-pushed ridge region. The first is related to the monitoring priorities of the Waternet water board, and the latter is related to the near absence of surface water in this region.
The highest chloride levels (> 300 mg L
The highest SO
According to Figs. 9 and 10, surface water EQSs of TN (2.4 mg N L
Similar to the results of groundwater, higher nutrient levels also exist in
higher mineralised surface waters, which is also indicated by the correlation
results (Table 1): In surface water components Ca and HCO
For the soil variables (lutum, humus, and calcite), only humus showed
correlations with TN, NH
Surface water TN correlated more closely with NH
A common spatial pattern in surface and groundwater chemistry is that polders
in the Zuider Zee margin area, the two upconing polders, and the central
Holland area suffer from a worse water quality situation than the polders in
the Vecht lakes and ice-pushed ridge areas. However, compared with the
underlying groundwater quality, surface water in the whole area has much
lower chloride, bicarbonate, and nutrient levels, but higher SO
Linear regression results of each surface water solute (Spearman).
Table 1 shows that TP, NH
The regression models were significantly improved by including groundwater
concentrations of NH
The results above strongly suggest that the groundwater composition puts limitations on the compliance of the receiving surface water towards the EQSs defined for N and P.
Surface water solute loads (average of 2010 to 2013) distribution
maps (kg ha
Figure 11 shows that the solute loads of polders to the
The influence of the redistribution of the large water volumes and loads from
deep polders was also observed in Figs. 3 and 11. Polders that receive
inlet water from Groot Mijdrecht and Horstermeer (see Sect. 2.1.1, Fig. 3)
showed relatively high solute loads, independent of their own seepage or
infiltration fluxes. This especially holds for polders downstream of Groot
Mijdrecht and Horstermeer, like polder no. 73 (Holendrechter- en Bullewijker
Polder (zuid en west),
Summary of the water and chloride balance for the Botshol polder; the graph shows (1) the initial Cl before the water inlet season (light blue), (2) the resulting Cl peak in Botshol after some months of inlet (dark blue), and (3) the results of the two models (model 1 is dark orange, model 2 is light orange).
The impact of this redistributed water on polder water chemistry is
demonstrated by a simple water and solute mass balance calculation for the
receiving Botshol polder (see Sect. 2.2.4). Figure 12 gives the chloride
concentration results of both the “evaporation” and the “infiltration/outlet”
models. Figure 12 shows that a very simple model can easily explain the peak
Cl concentrations in the Botshol polder to be the result of the inlet of
water from the
This study aimed at identifying the impact of groundwater on surface water quality in the polder catchments of the greater Amsterdam city area. According to the statistical analysis of data over five regions in the study area, a clear influence was identified. Solute concentrations in groundwater and surface water correlated well, although groundwater solute concentrations were generally much higher than normalised concentrations in surface water. The latter seems logical given the dilution of surface water by the precipitation surplus on an annual basis, with the annually discharged surface water being a mixture of seeping groundwater and precipitation. Moreover, similar spatial patterns in solute concentrations were found in groundwater and surface water. The findings on the dominance of groundwater inputs is also supported by the poor correlation with agricultural nutrients inputs, which are usually assumed to be a large source of N and P in surface water. Polders that are influenced by groundwater seepage or by redistributed seepage water from nearby deep polders are at risk of non-compliance, as groundwater concentrations exceeded the TN and TP EQSs for surface water in more than 90 % of the polders. Consequently, the groundwater nutrients input hinders the achievement of water quality targets in the surface water in those lowland landscapes.
In general, the groundwater chemistry corresponds with the geological history of the study area. In the peatland polder catchments within the Dutch delta system of marine, peri-marine, and fluvial unconsolidated deposits, abundant organic matter is present in the subsurface (e.g. Hijma, 2009). The presence of reactive organic matter in the shallow subsurface depletes the infiltrating groundwater from oxygen and nitrate, leading to an overall low redox potential in groundwater, which enables the further decomposition of organic matter downstream.
Main hydrogeochemical reactions in the study area.
Our data strongly suggest that sulfate reduction, sometimes in combination
with methanogenesis, is the main process releasing nutrients (N, P) and
HCO
The seepage of the alkalised groundwater increases the alkalinity of the surface
water, which is indicated by the high correlation between groundwater and
surface water HCO
In the urban area of Amsterdam, sand suppletion, which varies greatly in thickness and chemical composition, is another source of alkalinity. Some of the sands contain shell fragments because of their marine origin. However, little is known about the distribution of these calcite-rich sands. The poorly registered spatial distribution and sources of the supplied calcite-rich sands might complicate the assessment of their impact on urban polder water quality.
Sulfate concentrations are higher in the receiving surface water than in the
groundwater. We ascribe the sulfate surpluses (Fig. 7) to additional sources
affecting the surface water, including atmospheric deposition, agricultural
inputs, sewer leakage (Ellis, et al., 2005), storm runoff, and/or the
oxidation of pyrite (FeS
The groundwater in the upper 50 m of the subsurface of the study area is an important source of nutrients in the study area's surface waters (Delsman, 2015). Brackish groundwater, especially, seeps up into the polders of the Zuider Zee margin region and into the upconing area. The seepage of paleo-marine, brackish groundwater is driven by the low surface water levels after the lake reclamation and the drainage via pumping stations. De Louw et al. (2010) reported that this groundwater seepage predominantly takes place via concentrated boiling through the clay and peat cover layer.
The excess water in the upconing area is re-used as inlet water for several downstream polder catchments, which extends the impact of the brackish, alkaline, and nutrient-rich groundwater to a larger scale. The water redistribution disturbs the “natural” surface water quality patterns and local groundwater impact in the receiving polders, such as the Botshol polder. The redistributed water largely infiltrates and returns with variable travel times via the groundwater system, back towards the deep upconing polders.
Groundwater seepage in our study area leads to eutrophication, and redistributing the discharge from some deep polders further spreads the nutrients into the whole water system. Similar patterns are expected to exist in other lowland areas, which are highly manipulated by human activities. Typical delta areas where subsurface processes are expected to release nutrients from reactive organic matter and peat in the subsurface are the Mekong delta (Minderhoud et al., 2017), the Mississippi delta (Törnqvist et al., 2008), and the Sacramento–San Joaquin delta (Drexler et al., 2009). In many of these areas the water management shows resemblance to the Dutch situation. However, the large amount of groundwater quality and surface water quality data that were available in our study area is unique. Still, signals of groundwater influence on nutrient concentrations were reported from eastern England (M. E. Stuart, British Geological Survey, personal communication, 2016) and from the lowland parts of Denmark (Kronvang et al., 2013).
Besides the contribution from nutrient-rich groundwater seepage, this study
indicated that there are other possible sources of nutrients in the study
area. In agricultural lands, a portion of the applied nutrients is typically
lost to the surface water via drainage and runoff. The high groundwater
NO
In the urban polders within the Amsterdam city that have no significant
seepage (average seepage
In the study area, the most intensively urbanised polders are mainly
infiltrating and are more affected by inlet water containing high Cl and
HCO
The Vecht lakes polders with high surface water area percentages, representing lakes that are mainly used for recreation purposes, showed relatively low solute concentrations and loads in surface water (Figs. 10 and 11). In our study area, many lakes and polders with large surface water areas show large infiltration rates due to their elevation relative to other polders (Vermaat et al., 2010). Moreover, some of these lakes are replenished by inlet water that has passed a phosphate purification unit. In addition, the large open-water area retains nutrient transport due to long residence times and ample opportunities for chemical and biological transformation processes like denitrification, adsorption, and plant uptake.
Due to the disturbance of urban constructions, combined with redistribution of water through artificial drainage corridors, water flow in lowland urban areas is more complex than in rural or non-low-lying and freely draining catchments. Natural patterns of water chemistry might be significantly disturbed and hydrochemical processes are masked. The understanding of urban water quality patterns might improve if the monitoring program would be extended with tracers that are typical for specific sources, such as sewage leakage or urban runoff. Most solutes that are currently measured can originate from various anthropogenic and natural sources.
In the statistical analysis, for each pair of variables, only polders with complete data were taken into account, which could result in a loss of information. Seepage data were simulated by a group of models of which the results may deviate from the hard to measure actual seepage. We used averages of groundwater concentrations and soil properties, which caused a loss of information on the spatial variation within the polders. The interpolation of groundwater quality data also added uncertainty: for example hidden correlations for groundwater parameters. The calculation of the agricultural N and P inputs may also differ from the actual inputs due to errors in the nutrient bookkeeping and model uncertainties. In addition, differences in sampling methods and analytical procedures between groundwater and surface water quality monitoring programs may add uncertainties. These uncertainties may all have influenced the data characteristics apart from the uncertainties in the concentration measurements caused by the sampling, transport, and analytical procedures.
In future studies, urban lowland catchments with and without seepage could be studied separately, and more detailed land use or paved area categories could be included. The drainage and/or leakage from sewage systems and the drainage via tube drains should be taken into consideration. Drainage systems can provide a shortcut for solute transport towards surface water (Rozemeijer and Broers, 2007), leading to higher solute concentrations in surface water. High groundwater levels may induce groundwater discharge via the sewage or drainage systems (Ellis et al., 2005). In addition, studying the temporal variation of surface water quality will give more insights into how the groundwater impact on surface water quality functions, as well as on solute transport and pathways in urban hydrological systems. A detailed monitoring network in several urban polder catchments, which is anticipated as further work, could yield a more complete insight into water and contaminant flow routes and their effects on surface water solute concentrations and loads.
With respect to the water management scenarios, as our study showed that the groundwater nutrient loading towards surface water dominates, reducing the amounts of agricultural nutrient inputs might not contribute enough in improving the water quality. This certainly holds for urban areas where agricultural inputs are absent (see Fig. S3). Given the large loads of N and P that originate from one large polder with upconing brackish groundwater – the Groot Mijdrecht polder – one of the solutions proposed in the Netherlands was to turn this area back into a freshwater lake. By doing so, the seepage of nutrient-rich groundwater would stop as the higher water levels would lead to neutral or even infiltrating conditions. However, this proposal led to a lot of protest among the municipalities and farming communities in the polder and was not considered feasible given the economic values that were involved. This example shows that the reclamation of swamps and lakes for urbanisation or agriculture can lead to increased nutrient loads to surface waters in the surroundings, which are hard to mitigate. This scenario has wider implications for water management in other urbanising lowland areas around the world.
In this paper, a clear groundwater impact on surface water quality was
identified for the greater Amsterdam area. It was concluded that this
groundwater seepage significantly impacts surface water quality in the polder
catchments by introducing brackish, alkaline, and nutrient-rich water. In
general, nutrient concentrations in groundwater were much higher than in
surface water and often exceeded surface water environmental quality
standards (in 93 % of the polders with available data for TP and
in 91 % for TN), which indicates that groundwater is a large potential
source of nutrients in surface water. Our results strongly suggest that
organic matter mineralisation is a major source of nutrients in lowland
deltas where water levels are lowered to enable urbanisation and agricultural
land use. High correlations (
The data statistically processed in this paper are available in the Supplement.
The authors declare that they have no conflict of interest.
This work was funded through a CSC scholarship (no. 201309110088) and supported by the Strategic Research Funding of TNO and Deltares. We would like to thank the Waternet organization for making available their regional data on surface water quality, and we appreciate the contributions by Jos Beemster, Jan Willem Voort, and Jasper Stroom. Edited by: Nandita Basu Reviewed by: two anonymous referees