Abstract:Groundwater and surface water are often closely coupled and are both under the influence of multiple stressors. Stressed groundwater systems may lead to a poor ecological status of surface waters but to date no conceptual framework to analyse linked multi-stressed groundwater - surface water systems has been developed. In this paper, a framework is proposed showing the effect of groundwater on surface waters in multiple stressed systems. This framework will be illustrated by applying it to four European catchm… Show more
“…The dynamic TTDs for the Springendalse Beek catchment were calculated using forward particle tracking on a high-resolution spatially distributed groundwater flow model following the method described by Kaandorp et al (2018a). A concise description 105 of the method is given here and more details are found in Kaandorp et al (2018a).…”
Section: Groundwater Model and Ttdsmentioning
confidence: 99%
“…The dynamic TTDs for the Springendalse Beek catchment were calculated using forward particle tracking on a high-resolution spatially distributed groundwater flow model following the method described by Kaandorp et al (2018a). A concise description 105 of the method is given here and more details are found in Kaandorp et al (2018a). Groundwater flow was calculated using an existing finite-difference groundwater flow model (MODFLOW, Harbaugh, 2005) created and calibrated on groundwater heads and validated with both groundwater heads and river discharge in earlier studies (Hendriks et al, 2014;Kuijper et al, 2012).…”
Abstract. Surface waters are under pressure of diffuse pollution from agricultural activities and groundwater is known to be a connection between the agricultural fields and streams. We calculated in-stream concentrations by coupling input curves for tritium, chloride and nitrate with dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient 3D groundwater flow model using forward particle tracking. We tested our approach in a lowland stream and found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. A sensitivity analysis was done to study the breakthrough of agricultural nitrate and it was found that an unsaturated zone, increased mean travel time and a longer distance between agricultural fields and stream cause a lag in the breakthrough of agricultural solutes. Similarly, the recovery of concentrations after measures that aim to reduce the solute inputs is determined by these parameters, with combinations of slow reduction rates and long MTT tending to result in considerable lag times after start of the reductions. We labelled the part of the catchment area where the seepage water infiltrated that contributes to stream discharge at a certain moment in time the groundwater contributing area. This groundwater contributing area was shown to increase and shrink based on wetness conditions within the catchment. Especially the location of agricultural fields in the groundwater contributing area in relation to the catchments’ drainage network was found to be an important factor that largely governs the travel times of the agricultural pollutants. We conclude that groundwater functions as a buffer on the effect of agricultural pollution, by distributing water in time and space and making it possible for different waters to mix.
“…The dynamic TTDs for the Springendalse Beek catchment were calculated using forward particle tracking on a high-resolution spatially distributed groundwater flow model following the method described by Kaandorp et al (2018a). A concise description 105 of the method is given here and more details are found in Kaandorp et al (2018a).…”
Section: Groundwater Model and Ttdsmentioning
confidence: 99%
“…The dynamic TTDs for the Springendalse Beek catchment were calculated using forward particle tracking on a high-resolution spatially distributed groundwater flow model following the method described by Kaandorp et al (2018a). A concise description 105 of the method is given here and more details are found in Kaandorp et al (2018a). Groundwater flow was calculated using an existing finite-difference groundwater flow model (MODFLOW, Harbaugh, 2005) created and calibrated on groundwater heads and validated with both groundwater heads and river discharge in earlier studies (Hendriks et al, 2014;Kuijper et al, 2012).…”
Abstract. Surface waters are under pressure of diffuse pollution from agricultural activities and groundwater is known to be a connection between the agricultural fields and streams. We calculated in-stream concentrations by coupling input curves for tritium, chloride and nitrate with dynamic groundwater travel time distributions (TTDs) derived from a distributed, transient 3D groundwater flow model using forward particle tracking. We tested our approach in a lowland stream and found that the variable contribution of different groundwater flow paths to stream water quality reasonably explained the majority of long-term and seasonal variation in the measured stream nitrate concentrations. A sensitivity analysis was done to study the breakthrough of agricultural nitrate and it was found that an unsaturated zone, increased mean travel time and a longer distance between agricultural fields and stream cause a lag in the breakthrough of agricultural solutes. Similarly, the recovery of concentrations after measures that aim to reduce the solute inputs is determined by these parameters, with combinations of slow reduction rates and long MTT tending to result in considerable lag times after start of the reductions. We labelled the part of the catchment area where the seepage water infiltrated that contributes to stream discharge at a certain moment in time the groundwater contributing area. This groundwater contributing area was shown to increase and shrink based on wetness conditions within the catchment. Especially the location of agricultural fields in the groundwater contributing area in relation to the catchments’ drainage network was found to be an important factor that largely governs the travel times of the agricultural pollutants. We conclude that groundwater functions as a buffer on the effect of agricultural pollution, by distributing water in time and space and making it possible for different waters to mix.
“…Surface water bodies such as rivers, lakes, and wetlands are connected to their underlying groundwater in most types of landscapes (Winter, ). Natural exchanges between surface water and groundwater can strongly affect physical hydrological processes (Karan, Sebok, & Engesgaard, ; Winter, Harvey, Franke, & Alley, ), properties (Hayashi & Rosenberry, ; Jin et al, ), and the ecological behaviour of both water bodies (Hanrock, Boulton, & Humphreys, ; Kaandorp et al, ). The potential impacts of climate change and human activities on surface and groundwater resources increase the urgency for reliable assessment of surface water–groundwater interactions (Hutchins et al, ; Smerdon, ).…”
Floodplain systems are most often hydrologically complex settings characterized by highly variable surface water–groundwater interactions that are subjected to wide‐ranging wetting and drying over seasonal timeframes. This study used field methods, statistical analysis, and the Darcy's law approach to explore surface water–groundwater dynamics, interactions, and fluxes in a geographically complex river‐floodplain wetland‐isolated lake system (Poyang Lake, China). The floodplain system of Poyang Lake is affected by strongly seasonal shifts between dry and wet processes that cause marked changes in surface water and groundwater flow regimes. Results indicate that wetland groundwater is more sensitive to variations in river levels than the seasonal isolated lakes. In general, groundwater levels are lower than those of the isolated lakes but slightly higher than river levels. Statistical analysis indicates that the river hydrology plays a more significant role than the isolated lakes in controlling floodplain groundwater dynamics. Overall, the river shows gaining conditions and occasionally losing conditions with highly variable Darcy fluxes of up to +0.4 and −0.2 m/day, respectively, whereas the isolated lakes are more likely to show slightly losing conditions (less than −0.1 m/day). Although seasonal flux rates range from 7.5 to 48.2 m/day for surface water–groundwater interactions in the floodplain, the flux rates for river–groundwater interactions were around four to seven times higher than that of the isolated lake–groundwater interactions. The outcomes of this study have important implications for improving the understanding of the water resources, water quality, and ecosystem functioning for both the river and the lake.
“…Studies conducted globally continue to indicate the combined use of multiple methods for assessing GW-SW interactions is most plausible due to the compensation of the spatial and temporal shortfalls of other methods (Binley et al 2013;Cao et al 2012;Cey et al 1998;Fleckenstein et al 2010;Kaandorp et al 2018;Kakuchi et al 2012;Kalbus et al 2006;Petelet-Giraud et al 2007;Yang et al 2014).This study applied a multiple methods to assess GW-SW interaction by estimating groundwater fluxes using the automated base flow separation, while GW-SW quality characterization was done using hydro-chemical analysis.…”
Madlala, T. et al. (2018). Application of multi-method approach to assess groundwater-surface water interaction, for catchment management.
AbstractGlobally, the dependence of river systems to delayed discharge of subsurface water to augment flows during dry seasons is well documented. Discharge of fresh subsurface water can dilute concentrated river flow quality during reduced flow. Observed and reported results on the Berg River's declining water quantity and quality are a concern to the regions socio-economic growth and environmental integrity. Understanding the role of subsurface water discharges on the quantity and quality of receiving surface water courses can improve their management during dry periods. A case study was designed and implemented in the upper Berg River catchment in the Western Cape Province of South Africa to assess the influence of groundwater-surface water interaction on water quantity and quality. This study aimed to quantify and characterize the quality of subsurface water available in the upper catchment to improve observed declining water quality downstream. Hydrograph separation provided estimates of water fluxes during 2012-2014 low and high flow periods, while hydrochemical analysis provided insights on impacts of major land use activity in this catchment on water resources. Hydrograph separation analysis indicated that the Berg River is 37.9% dependent on subsurface water discharges annually. Dominant Na-Cl-type water indicates the quality of water from the upper Berg River is largely affected by natural processes including short residence times of aquifer water, rock-water interactions and atmospheric deposition of NaCl ions. These results provide insights for suggesting management options to be implemented to protect subsurface water for continued dilution and water resources management in the lower catchments.
Materials and methods Study site descriptionThe Berg River catchment in the Western Cape of South Africa is an important source of water to the greater city of Cape Town, its surrounding towns and dependent ecosystems.
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