This paper explores the vulnerability of two estuaries, the Clyde in Glasgow, Scotland, in the developed world with an established infrastructure, and where finance can be made available for adaption and mitigation. The other is in Gambia, West Africa, where poverty is endemic, the infrastructure undeveloped and where the finances for adaption and mitigation are severely limited. The paper employs a numerical modeling approach, first for the Clyde Estuary in Glasgow with a rich data-set modeled with commercial 1-d and 2-d models, and then the Gambia estuary in West Africa with a very sparse data-set, modeled with a 1-d model and an idealized 3-d CFD model. The paper demonstrates different modeling techniques appropriate to each case and the very different scale of threats, vulnerability and different responses required to ensure greater sustainability in each estuary.
Evapotranspiration (ET) is the most significant water balance component and is also a very complex component to evaluate in spatio-temporal scales. Remotely-sensed data greatly increases the accuracy of basin wide ET estimation but only in periods with available satellite images. This paper describes an attempt to estimate daily ET regardless of the availability of the satellite images. The method is based on application of the interpolated evaporative fraction (Λ) from "historical" satellite images to periods with no satellite data available. Basin wide daily ET is obtained by combining interpolated Λ and standard PET methods on meteorological stations. The reliability of such approach was evaluated by comparing the obtained daily ET to the SEBAL ET estimates through the analysis of residuals (∆), standard deviations of residuals (σ) and the Nash-Sutcliffe coefficient (NSE) over the basin. The SEBAL ET estimates were validated with the data from two lysimeters. The discrepancy of obtained ET versus the SEBAL ET estimates (∆ = 0.13 mm day −1 , σ = 0.64 mm day −1 , NSE = 0.07) indicated that the proposed concept has relatively high accuracy, which is notably higher than the Penman-Monteith interpolated ET estimates (∆ = 1.94 mm day −1 , σ = 1.03 mm day −1 , NSE = −4.71). It was shown that a total of five images can provide a reliable estimate of interpolated Λ and thus represent specific characteristics of a basin. As the presented concept requires minimum remote sensing data and ground based inputs, it could be applied to estimate basin wide daily ET in data scarce regions and in periods with no satellite images available.
This paper shows the results of the hydraulic-hydrologic calculations of karst spring discharges and the groundwater level in the aquifer of spring catchment. The calculations were performed for the Golubinka spring in Zadar area for the 4-year period. The chosen approach was a model using relatively scarce data set, including limnigraphic data on the difference between the sea water level and the freshwater level on the spring itself and the precipitation data from the meteorological station Zadar. The determination of discharge hydrographs, based on inherent assumptions and available data, yields the proportionality coefficients between the discharge and the limnigraphic data on the Golubinka spring itself. Further, based on the discharge hydrograph, groundwater level oscillation was determined. The resulting spring discharge hydrograph and groundwater levels, along with the assumption of Golubinka spring as the only spring on the catchment, were used in creating turbulent seepage model of the fractured system within the aquifer, which evidently extends along the axis of the Golubinka spring catchment. The model yielded suitable turbulent seepage coefficients of the fracture system. By using the numerical model KarstMod it was estimated that, on average, concentrated fracture flow drains around 85% of infiltrated volumes and the remaining 15% accounts for diffuse matrix flow. Finally, the Modflow model was used in order to get insight into the flow field and the distribution of equipotentials in the aquifer of the Golubinka catchment.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.