Examining alterations in environmental flow conditions through different methods and assessing managerial requirements for wetland ecosystems

The sustainability of wetland ecosystems largely depends on the quantity and quality of environmental flows that feed wetlands. Therefore, it is of great importance to evaluate river flows to wetlands in terms of flow potentials and to analyze the effects of periodically observed hydrological differences on environmental flow potentials and to enable the development of environmental management strategies based on hydrological criteria according to these changes. The basis for these studies is hydrological data compiled from observation stations on rivers. However, due to some different priorities, current observation stations are not adequately positioned for wetland ecosystems, which negatively affects the representation of flows from wetlands. From this point of view, it is aimed to derive synthetic data from available data stations related that can represent wetland flows, but where there is no measurement data location, and to evaluate the environmental flows of wetlands in this way. In the study, the derivation of flow time series over monthly mean flows was performed using the MA SYE (Sustainable Yield Estimator) approach. However, statistical methods have been used to estimate monthly average time series for surface flow and subsequent environmental flow for a review period of 20 years. First, surface flow quantities were calculated by subjecting to regression with surface flows corresponding to measurable climate and physical basin characteristics; At the next stage, current estimates were made over current continuity curves, taking into account the probabilities of additional transients. In the continuation of the study, the environmental flow values are calculated comparatively under different environmental management strategy predictions for different periods using GEFC (Global Environmental Flow Calculator) through and the results are displayed through graphical representations and statistical measures.