Karstic spring wetlands of the Persepolis Basin, southwest Iran: unique sediment archives of Holocene environmental change and human impacts

Palustrine carbonates are frequently found with active and dried karstic springs in the foothills of the mountains bordering the Persepolis Basin, southwest Iran. A combination of geological conditions favours their formation, including (i) the presence of karstic limestone aquifers in the limbs of anticlines cut through by fault systems; (ii) very gentle slopes from the spring resurgence point towards the centre of the alluvial plain, creating a flat waterlogged area; and (iii) a semiarid climate with marked precipitation seasonality or significant fluctuations in water discharge and wetland water table. We suggest the term “anastomosing wetlands” or “anastomosing palustrine environments” to denote the studied karstic spring–fed carbonate wetlands, because of similarities with anastomosing river systems in aerial view. The common presence of extended anastomosing wetland carbonates in the Persepolis Basin and adjacent basins in the central and southern Zagros suggests that they can play an important role in the geological records of collision-related basin-and-range settings dominated by karstic limestones. Karstic spring wetlands are a main source of fresh water hosting a rich biodiversity, which attracts human communities, whose impact is visible in the archaeological material imbedded in the wetland stratigraphy. Fresh water availability, through these spring wetlands, partly explains why the semiarid Persepolis region was selected by successive civilizations, from Elamites to Persians until early Islamic entities, to establish regional centres throughout the period from the third millennium B.C. to the first millennium A.D. Only a few of these ecosystems have survived the intensive human activities of recent decades.

SEASONAL STOCHASTIC SIMULATION AND TIMESERIES MODELLING - ANALYSIS OF A KARSTIC SPRING IN CENTRAL MACEDONIA, GREECE

The objective of this paper is to find an appropriate Seasonal Auto-Regressive Integrated Moving Average (SARIMA) model for fitting the monthly discharge of a karstic spring located at the North of the city of Serres (Agios Ioannis, Mount Menikio) by considering the minimum of Akaike Information Criterion (AIC). Box- Jenkins methodology applies models to find the best fit of a timeseries to past values of this timeseries, in order to make forecasting and consists of a four-step iterative procedure: identification, estimation, diagnostic check and forecasting. Timeseries analysis and forecasting of hydrological parameters such as spring discharge may be useful in decision making and optimum water resources usage. In this study, monthly discharge measurements are analysed. Initial data are firstly transformed to normal and stationary using differencing methods. Autocorrelation and Partial Autocorrelation functions are calculated to determine the order of Autoregressive and Moving Average parameters and residuals are then checked to show the “white noise”. The spring discharge data are forecasted based on the selected model up to 2008 and are then compared with measured values. The timeseries model SARIMA (2,1,1)(1,0,1)12 could be used in monthly discharge forecasting at a short time (upcoming one year) with a simple and explicit model structure in order to help decision m akers to establish priorities in terms of water demand management. Finally, the corr elation coefficient between the observed and fitted data is essentially high, while the absolute and relative errors are significantly low.