Transitions in ancient inland freshwater resource management in Sri Lanka affect biota and human populations in and around coastal lagoons.

The increasing anthropogenic pressure on natural environments results in impacts that affect tropical forest areas and their biodiversity. Adverse impacts on terrestrial and oceanic environments often compound in the intertidal area, where mangrove forest ecosystems thrive. In tropical coastal areas of many developing countries where people depend on wood and other mangrove forest products and services, forest degradation leads to socioeconomic problems. At the same time, increasing freshwater needs in these areas are expected to cause additional problems. On the basis of remote sensing and ground truthing complemented by colonial archival material from the Dutch East India Company (1602-1800), we report that changes to the historic system of inland freshwater management have increased dramatically in recent times. Hydrological changes, such as interbasin transfers, have resulted in a qualitative ecological and socioeconomic degradation in three coastal lagoons in southern Sri Lanka. Variations in river hydrology have caused changes in the areas suitable as mangrove habitat and, thus, have resulted in an altered distribution. However, increases in mangrove area can mask the degradation of the site in terms of floristic composition, significance of the species, and biodiversity (this effect is termed "cryptic ecological degradation"). It is important that such changes be carefully monitored to ensure biological and socioeconomic sustainability.

Physical water scarcity metrics for monitoring progress towards SDG target 6.4: An evaluation of indicator 6.4.2 "Level of water stress".

Target 6.4 of the recently adopted Sustainable Development Goals (SDGs) deals with the reduction of water scarcity. To monitor progress towards this target, two indicators are used: Indicator 6.4.1 measuring water use efficiency and 6.4.2 measuring the level of water stress (WS). This paper aims to identify whether the currently proposed indicator 6.4.2 considers the different elements that need to be accounted for in a WS indicator. WS indicators compare water use with water availability. We identify seven essential elements: 1) both gross and net water abstraction (or withdrawal) provide important information to understand WS; 2) WS indicators need to incorporate environmental flow requirements (EFR); 3) temporal and 4) spatial disaggregation is required in a WS assessment; 5) both renewable surface water and groundwater resources, including their interaction, need to be accounted for as renewable water availability; 6) alternative available water resources need to be accounted for as well, like fossil groundwater and desalinated water; 7) WS indicators need to account for water storage in reservoirs, water recycling and managed aquifer recharge. Indicator 6.4.2 considers many of these elements, but there is need for improvement. It is recommended that WS is measured based on net abstraction as well, in addition to currently only measuring WS based on gross abstraction. It does incorporate EFR. Temporal and spatial disaggregation is indeed defined as a goal in more advanced monitoring levels, in which it is also called for a differentiation between surface and groundwater resources. However, regarding element 6 and 7 there are some shortcomings for which we provide recommendations. In addition, indicator 6.4.2 is only one indicator, which monitors blue WS, but does not give information on green or green-blue water scarcity or on water quality. Within the SDG indicator framework, some of these topics are covered with other indicators.

Simple hydraulic conductivity estimation by the Kalman filtered double constraint method.

This paper presents the Kalman Filtered Double Constraint Method (DCM-KF) as a technique to estimate the hydraulic conductivities in the grid blocks of a groundwater flow model. The DCM is based on two forward runs with the same initial grid block conductivities, but with alternating flux-head conditions specified on parts of the boundary and the wells. These two runs are defined as: (1) the flux run, with specified fluxes (recharge and well abstractions), and (2) the head run, with specified heads (measured in piezometers). Conductivities are then estimated as the initial conductivities multiplied by the fluxes obtained from the flux run and divided by the fluxes obtained from the head run. The DCM is easy to implement in combination with existing models (e.g., MODFLOW). Sufficiently accurate conductivities are obtained after a few iterations. Because of errors in the specified head-flux couples, repeated estimation under varying hydrological conditions results in different conductivities. A time-independent estimate of the conductivities and their inaccuracy can be obtained by a simple linear KF with modest computational requirements. For the Kleine Nete catchment, Belgium, the DCM-KF yields sufficiently accurate calibrated conductivities. The method also results in distinguishing regions where the head-flux observations influence the calibration from areas where it is not able to influence the hydraulic conductivity.

SEEPAGE, a new MODFLOW DRAIN package.

The prediction of the location of ground water discharge areas is a key aspect for the protection and (re)development of ground water-dependent wetlands. Ground water discharge areas can be simulated with MODFLOW using the DRAIN package by setting the drain level equal to the topography, while the conductance is mostly set to an arbitrary high value. However, conceptual and practical problems arise in the calculation of the ground water discharge by the DRAIN package as calculated water tables above the land surface, difficult parameterization of the conductance, and large water balance errors. To overcome these problems, a new SEEPAGE package for MODFLOW is proposed. The basic idea of this package is an adaptable constant head cell. It has a variable head, unless the ground water rises above the seepage level, in which case it has a constant head cell. The estimation of the ground water discharge location along a homogeneous, isotropic, linear sloping profile is used to verify the model and to compare it to the DRAIN solution. In an application to three basins in Belgium, it is shown that the SEEPAGE package can be used in combination with the DRAIN package in situations where an upper boundary for a free water table and additional resistance for drainage is required. It is clearly demonstrated that the identification and delineation of regional ground water discharge areas is more accurate using the SEEPAGE package.

Application of a Bayesian approach to stochastic delineation of capture zones.

This paper presents a Bayesian Monte Carlo method for evaluating the uncertainty in the delineation of well capture zones and its application to a wellfield in a heterogeneous, multiaquifer system. In the method presented, Bayes' rule is used to update prior distributions for the unknown parameters of the stochastic model for the hydraulic conductivity, and to calculate probability-based weights for parameter realizations using head residuals. These weights are then assigned to the corresponding capture zones obtained using forward particle tracking. Statistical analysis of the set of weighted protection zones results in a probability distribution for the capture zones. The suitability of the Bayesian stochastic method for a multilayered system is investigated, using the wellfield Het Rot at Nieuwrode, Belgium, located in a three-layered aquifer system, as an example. The hydraulic conductivity of the production aquifer is modeled as a spatially correlated random function with uncertain parameters. The aquitard and overlying unconfined aquifer are assigned random, homogeneous conductivities. The stochastic results are compared with deterministic capture zones obtained with a calibrated model for the area. The predictions of the stochastic approach are more conservative and indicate that parameter uncertainty should be taken into account in the delineation of well capture zones.

Improving surface-subsurface water budgeting using high resolution satellite imagery applied on a brownfield.

The estimation of surface-subsurface water interactions is complex and highly variable in space and time. It is even more complex when it has to be estimated in urban areas, because of the complex patterns of the land-cover in these areas. In this research a modeling approach with integrated remote sensing analysis has been developed for estimating water fluxes in urban environments. The methodology was developed with the aim to simulate fluxes of contaminants from polluted sites. Groundwater pollution in urban environments is linked to patterns of land use and hence it is essential to characterize the land cover in a detail. An object-oriented classification approach applied on high-resolution satellite data has been adopted. To assign the image objects to one of the land-cover classes a multiple layer perceptron approach was adopted (Kappa of 0.86). Groundwater recharge has been simulated using the spatially distributed WetSpass model and the subsurface water flow using MODFLOW in order to identify and budget water fluxes. The developed methodology is applied to a brownfield case site in Vilvoorde, Brussels (Belgium). The obtained land use map has a strong impact on the groundwater recharge, resulting in a high spatial variability. Simulated groundwater fluxes from brownfield to the receiving River Zenne were independently verified by measurements and simulation of groundwater-surface water interaction based on thermal gradients in the river bed. It is concluded that in order to better quantify total fluxes of contaminants from brownfields in the groundwater, remote sensing imagery can be operationally integrated in a modeling procedure.