Uncertainty estimation of end-member mixing using generalized likelihood uncertainty estimation (GLUE), applied in a lowland catchment

End-member mixing models have been widely used to separate the different components of a hydrograph, but their effectiveness suffers from uncertainty in both the identification of end-members and spatiotemporal variation in end-member concentrations. In this paper, we outline a procedure, based on the generalized likelihood uncertainty estimation (GLUE) framework, to more inclusively evaluate uncertainty in mixing models than existing approaches. We apply this procedure, referred to as G-EMMA, to a yearlong chemical data set from the heavily impacted agricultural Lissertocht catchment, Netherlands, and compare its results to the traditional end-member mixing analysis (EMMA). While the traditional approach appears unable to adequately deal with the large spatial variation in one of the end-members, the G-EMMA procedure successfully identified, with varying uncertainty, contributions of five different end-members to the stream. Our results suggest that the concentration distribution of effective end-members, that is, the flux-weighted input of an end-member to the stream, can differ markedly from that inferred from sampling of water stored in the catchment. Results also show that the uncertainty arising from identifying the correct end-members may alter calculated end-member contributions by up to 30%, stressing the importance of including the identification of end-members in the uncertainty assessment

Nonlinear model predictive control of salinity and water level in polder networks: Case study of Lissertocht catchment

A significant increase in surface water salinization in low-lying deltas is expected globally due to saline groundwater exfiltration driven by rising sea levels and decreasing freshwater availability. Sustaining fresh water-dependent agriculture in such areas will entail an increased demand for fresh water flushing. Unfortunately, the flushing of surface water is not operationally optimised and results in excessive use of scarce freshwater. To meet the increased demand for flushing, while minimizing the need for diverted freshwater, new operational designs are required. This paper presents a novel network model based approach that uses De Saint Venant (SV) and Advection Dispersion (AD) equations to optimize multiple objectives on water level and salinity control using a Nonlinear Model Predictive Control (NMPC). The resulting NMPC problem is solved with a receding horizon implementation, where the nonlinear program (NLP) at each iteration is solved using state-of-the-art large scale interior point solver (IPOPT). We evaluate the performance of the proposed approach and compare it to the traditional fixed flushing for a representative Dutch polder. Firstly, the approach is shown to be capable of controlling the water level and salinity level in the polder. Secondly, the results highlight that the network of canals, which were originally made for drainage, could not be made sufficiently fresh with current intake capacity. A simple design approach was used to identify appropriate new capacities for two of the gates that allow optimal flushing to guarantee the required water level and salinity constraints

Factors Determining the Natural Fresh-Salt Groundwater Distribution in Deltas

Most river deltas are densely populated areas with intensive agriculture. The increased shortage of fresh surface water that results from rising demands are expected to lead to increased groundwater pumping, which leads to sea water intrusion. To correctly project the future of fresh groundwater resources in deltas, knowing the current fresh-salt groundwater distribution is a prerequisite. However, uncertainties about these distributions and their drivers are large. To understand these uncertainties, we conducted a global sensitivity analysis of a complex three-dimensional variable- density groundwater model of a synthetic delta, simulating the effect of the last glacial low stand and the subsequent marine transgression. The analysis is unique in its wide range of geometries, hydrogeological parameterizations, and boundary conditions analyzed, making it representative for a large number of deltas worldwide. We find that the aquifer hydraulic conductivity is the most uncertain input and has a strong nonmonotonous effect on the total salt mass onshore. The calculated fresh-salt groundwater distributions were classified into five classes and compared to real-world case studies. We find that salinity inversions occur in deltaic systems with high representative system anisotropies as a remnant of a marine transgression. These salinity inversions were observed in half of the real-world cases, indicating that their fresh-salt groundwater distributions are not in a dynamic equilibrium. We conclude that it is very likely that past marine transgressions are still reflected in the current fresh-salt groundwater distributions in deltas. This makes paleo-groundwater modeling a prerequisite for effective simulation of present-day groundwater salinity distributions in these systems

Fast calculation of groundwater exfiltration salinity in a lowland catchment using a lumped celerity/velocity approach

To support operational water management of freshwater resources in coastal lowlands, a need exists for a rapid, well-identifiable model to simulate salinity dynamics of exfiltrating groundwater. This paper presents the lumped Rapid Saline Groundwater Exfiltration Model (RSGEM). RSGEM simulates groundwater exfiltration salinity dynamics as governed by the interplay between water velocity, gradually adjusting the subsurface salinity distribution, and pressure wave celerity, resulting in a fast flow path response to groundwater level changes. RSGEM was applied to a field site in the coastal region of the Netherlands, parameter estimation and uncertainty analysis were performed using generalized likelihood uncertainty estimation. The model showed good correspondence to measured groundwater levels, exfiltration rates and salinity response. Moreover, RSGEM results were very similar to a detailed, complex groundwater flow and transport model previously applied to this field site

Factors Determining the Natural Fresh-Salt Groundwater Distribution in Deltas

Most river deltas are densely populated areas with intensive agriculture. The increased shortage of fresh surface water that results from rising demands are expected to lead to increased groundwater pumping, which leads to sea water intrusion. To correctly project the future of fresh groundwater resources in deltas, knowing the current fresh-salt groundwater distribution is a prerequisite. However, uncertainties about these distributions and their drivers are large. To understand these uncertainties, we conducted a global sensitivity analysis of a complex three-dimensional variable- density groundwater model of a synthetic delta, simulating the effect of the last glacial low stand and the subsequent marine transgression. The analysis is unique in its wide range of geometries, hydrogeological parameterizations, and boundary conditions analyzed, making it representative for a large number of deltas worldwide. We find that the aquifer hydraulic conductivity is the most uncertain input and has a strong nonmonotonous effect on the total salt mass onshore. The calculated fresh-salt groundwater distributions were classified into five classes and compared to real-world case studies. We find that salinity inversions occur in deltaic systems with high representative system anisotropies as a remnant of a marine transgression. These salinity inversions were observed in half of the real-world cases, indicating that their fresh-salt groundwater distributions are not in a dynamic equilibrium. We conclude that it is very likely that past marine transgressions are still reflected in the current fresh-salt groundwater distributions in deltas. This makes paleo-groundwater modeling a prerequisite for effective simulation of present-day groundwater salinity distributions in these systems

A Greedy Algorithm for Optimal Sensor Placement to Estimate Salinity in Polder Networks

We present a systematic approach for salinity sensor placement in a polder network, where the objective is to estimate the unmeasured salinity levels in the main polder channels. We formulate this problem as optimization of the estimated salinity levels using root mean square error (RMSE) as the “goodness of fit” measure. Starting from a hydrodynamic and salt transport model of the Lissertocht catchment (a low-lying polder in the Netherlands), we use principal component analysis (PCA) to produce a low-order PCA model of the salinity distribution in the catchment. This model captures most of the relevant salinity dynamics and is capable of reconstructing the spatial and temporal salinity variation of the catchment. Just using three principal components (explaining 93% of the variance of the dataset) for the low-order PCA model, three optimally placed sensors with a greedy algorithm make the placement robust for modeling and measurement errors. The performance of the sensor placement for salinity reconstruction is evaluated against the detailed hydrodynamic and salt transport model and is shown to be close to the global optimum found by an exhaustive search with a RMSE of 82.2 mg/L

Nonlinear model predictive control of salinity and water level in polder networks: Case study of Lissertocht catchment

A significant increase in surface water salinization in low-lying deltas is expected globally due to saline groundwater exfiltration driven by rising sea levels and decreasing freshwater availability. Sustaining fresh water-dependent agriculture in such areas will entail an increased demand for fresh water flushing. Unfortunately, the flushing of surface water is not operationally optimised and results in excessive use of scarce freshwater. To meet the increased demand for flushing, while minimizing the need for diverted freshwater, new operational designs are required. This paper presents a novel network model based approach that uses De Saint Venant (SV) and Advection Dispersion (AD) equations to optimize multiple objectives on water level and salinity control using a Nonlinear Model Predictive Control (NMPC). The resulting NMPC problem is solved with a receding horizon implementation, where the nonlinear program (NLP) at each iteration is solved using state-of-the-art large scale interior point solver (IPOPT). We evaluate the performance of the proposed approach and compare it to the traditional fixed flushing for a representative Dutch polder. Firstly, the approach is shown to be capable of controlling the water level and salinity level in the polder. Secondly, the results highlight that the network of canals, which were originally made for drainage, could not be made sufficiently fresh with current intake capacity. A simple design approach was used to identify appropriate new capacities for two of the gates that allow optimal flushing to guarantee the required water level and salinity constraints.Water ManagementWater Resource

Nonlinear model predictive control of salinity and water level in polder networks: Case study of Lissertocht catchment

A significant increase in surface water salinization in low-lying deltas is expected globally due to saline groundwater exfiltration driven by rising sea levels and decreasing freshwater availability. Sustaining fresh water-dependent agriculture in such areas will entail an increased demand for fresh water flushing. Unfortunately, the flushing of surface water is not operationally optimised and results in excessive use of scarce freshwater. To meet the increased demand for flushing, while minimizing the need for diverted freshwater, new operational designs are required. This paper presents a novel network model based approach that uses De Saint Venant (SV) and Advection Dispersion (AD) equations to optimize multiple objectives on water level and salinity control using a Nonlinear Model Predictive Control (NMPC). The resulting NMPC problem is solved with a receding horizon implementation, where the nonlinear program (NLP) at each iteration is solved using state-of-the-art large scale interior point solver (IPOPT). We evaluate the performance of the proposed approach and compare it to the traditional fixed flushing for a representative Dutch polder. Firstly, the approach is shown to be capable of controlling the water level and salinity level in the polder. Secondly, the results highlight that the network of canals, which were originally made for drainage, could not be made sufficiently fresh with current intake capacity. A simple design approach was used to identify appropriate new capacities for two of the gates that allow optimal flushing to guarantee the required water level and salinity constraints

A greedy algorithm for optimal sensor placement to estimate salinity in polder networks

We present a systematic approach for salinity sensor placement in a polder network, where the objective is to estimate the unmeasured salinity levels in the main polder channels. We formulate this problem as optimization of the estimated salinity levels using root mean square error (RMSE) as the "goodness of fit" measure. Starting from a hydrodynamic and salt transport model of the Lissertocht catchment (a low-lying polder in the Netherlands), we use principal component analysis (PCA) to produce a low-order PCA model of the salinity distribution in the catchment. This model captures most of the relevant salinity dynamics and is capable of reconstructing the spatial and temporal salinity variation of the catchment. Just using three principal components (explaining 93% of the variance of the dataset) for the low-order PCA model, three optimally placed sensors with a greedy algorithm make the placement robust for modeling and measurement errors. The performance of the sensor placement for salinity reconstruction is evaluated against the detailed hydrodynamic and salt transport model and is shown to be close to the global optimum found by an exhaustive search with a RMSE of 82.2 mg/L.Water Resource

Dunne regenwaterlenzen in zoute kwelgebieden

In zoute kwelgebieden zijn dunne regenwaterlenzen van groot belang voor de landbouw omdat ze vaak de enige zoetwaterbron zijn en voorkomen dat (te) zout kwelwater de wortelzone bereikt. Veldonderzoek in Zeeland heeft voor het eerst in beeld gebracht hoe deze lenzen er precies uitzien, hoe ze veranderen in de tijd en welke processen daarbij een rol spelen. De lenzen blijken erg kwetsbaar voor klimaatverandering. De opgedane systeemkennis maakt het mogelijk hiervoor mitigerende maatregelen te formuleren