Distributed modeling of soil erosion and sediment transport

A mathematical model is used for the estimation of the annual sediment yield resulting from rainfall and runoff at the outlet of Nestos River basin (Toxotes, Thrace, Greece), where the ecologically interesting Nestos delta exists. The model is applied to that part of Nestos River basin (838 km2) which lies downstream of three dams. Two dams (Thissavros and Platanovryssi) have been already constructed, while the third one (Temenos) is under construction. The model consists of three sub-models: a rainfall-runoff sub-model, a surface erosion sub-model and a sediment transport sub-model for streams. This model is also capable of computing the annual erosion amount and sediment yield in the individual sub-basin

Χρήση του δείκτη QBR για την εκτίμηση των επιπτώσεων της κατασκευής φραγμάτων κατά μήκος της κοίτης ενός μεσογειακού χειμάρρου στην παρόχθια βλάστηση

Ο χείμαρρος «Γεραμπίνη» Ζαγοράς Πηλίου, ο οποίος αποτελεί την περιοχή μελέτης, είναι ένα υδατικό οικοσύστημα με έντονες διακυμάνσεις στο υδρολογικό του ισοζύγιο. Με κύριο στόχο την αποτροπή των πλημυρρικών φαινομένων, κατασκευάστηκαν κατά μήκος του, είκοσι ένα (21) φράγματα στερέωσης. Στην παρούσα εργασία προσδιορίζεται και αναλύεται ο δείκτης QBR «Qualitat del Bosc de Ribera», ο οποίος αποτελεί έναν αξιόπιστο ποιοτικό δείκτη της παρόχθιας βλάστησης για τα μεσογειακά υδατικά οικοσυστήματα. Από την συλλογή, επεξεργασία και ανάλυση των δεδομένων προκύπτει ότι η τεχνητή διευθέτηση του μεσογειακού χειμάρρου δεν αποτέλεσε τροχοπέδη στη διατήρηση και στην αναβάθμιση της δυναμικής των στοιχείων που συντελούν στη φυσική εξέλιξη της παρόχθιας βλάστησής του

Simulation and trend analysis of the water quality monitoring daily data in Nestos River delta. Contribution to the sustainable management and results for the years 2000-2002

The transboundary River Nestos in the Balkan Peninsula is a surface water resource shared by Hellas and Bulgaria. The Public Power Corporation of Hellas (DEH) proceeded to the dams' construction of Thesaurus in 1997 and Platanovrissi in 2000, to satisfy the increased needs for power production and irrigation in the Regions of Eastern Macedonia and Thrace in the Hellenic Territory. DEH following the Ministerial Agreement of the Hellenic Parliament "KYA 18492/19-09-1996'' funded a series of Research Projects concerned on the monitoring of the water quantity and quality data of Nestos from the Hellenic-Bulgarian borders to its estuaries in the Thracian sea. "PERSEAS'' Research Group from Aristotle University of Thessaloniki, carried out the research, design, construction, installation, operation and maintenance of the "R.E.MO.S.'' (Remote Environmental MOnitoring System) networks. Three REMOS networks have been installed in the areas of (a) the River Nestos deltaic channel, (b) Thesaurus dam-lake in the intramountainous valley and (c) Potamoi (Despat) and Pagoneri (Nestos) villages close to the borders between Hellas and Bulgaria. They record water level (H), water and air temperature (T), water conductivity (ECw), Redox potential (RP) and dissolved oxygen (DO) on a 24h basis, since the beginning of the year 2000. The research carried out in this paper, is focused on the REMOS station in the final course of Nestos in the deltaic area. The continuous monitoring and the data analysis yield useful results for the quality and quantity of the hydrologic regime of Nestos after the dams' construction, as well as for the trends detected of the quality parameters (ECw, RP and DO) and the water level, using the nonparametric Spearman's criterion. The best fitted model of time trend, for each variable, was chosen. The statistical sample of each one of the quality variables consisted of about 1000 values based on daily measures on a three years monitoring program (1/1/2000-31/12/2002). Further research and analysis for the other network stations of REMOS should provide useful results for the sustainable management of the transboundary River Nestos

Comparison of the performance of stochastic models in forecasting daily dissolved oxygen data in dam-Lake Thesaurus

This study presents the development and validation of three different stochastic models on the basis of (a) their efficiency to forecast and (b) their ability to utilize auxiliary environmental information. The three models are ARIMA models, transfer function (TF) models, and artificial neural networks. Four-year (2004–2007) daily measurements of dissolved oxygen at four different depths (1, 20, 40 and 70 m) of Thesaurus dam-lake in River Nestos, Eastern Macedonia, Greece, were used to obtain the best models for these time series. For the final selected models, four statistical criteria (mean square error (MSE), roοt-mean-square error (RMSE), MAPE, and NSC) were used to evaluate the accuracy of the forecast and to compare the forecasting ability for one step ahead of each approach. For 1- and 20-m depth, the best forecast is obtained by ARIMA models, while for the 40-m depth, TF models gives the best forecast. Finally for the 70-m depth, according to the MSE, RMSE, and NSC statistical criteria, ARIMA models are the best, while for the MAPE, TF models are the best. Further research could be carried out concerning on (a) the comparison of these models with other forecasting ones, (b) the application of forecasting for more than one step ahead (m = 2, 3, …), and (c) the implementation of such models in other deep lakes and the assessment of the comparison between them. © 2016 Balaban Desalination Publications. All rights reserved

Sustainable management of Agiasma Lagoon-River Nestos delta-Using REMOS daily monitoring data of water quality and quantity parameters Trends, assessments, and natural hazards for the years 2000-2002

Three R.E.MO.S. (Remote Environmental MOnitoring System) telemetric networks have been installed in the catchment area of River Nestos, by research team PERSEAS. The first network has been installed in Nestos Delta. This network consists of two Remote Stations (R.S.): The first one is called R.S. "Nestos" and is settled in Nestos Delta in Chrysoupoli and the second one is called R.S "Agiasma" and is settled in the homonymous Lagoon. This paper deals with R.S. "Agiasma", which operates in Agiasma Lagoon, an area of great environmental importance in the west part of River Nestos Delta. The gradients of the water quality and quantity monitored parameters are very important for the ecological preservation of the lagoon. Moreover, this case can be an excellent example of how the real-time monitoring data can work as an alarm system to prevent environmental hazards. The scientific issues this paper is focused on are: 1. The three years systematic daily electronic monitoring data (1/1/2000-31/12/2002). The monitored parameters are Water level-H (cm), Salinity-Sal (parts per thousand), Redox Potential-RP (mV), Dissolved Oxygen-DO (mg/l), Water Temperature-T(w) (degrees C) and Air Temperature-T(a) (degrees C). 2. The assessment of water quality and quantity parameters and the aquatic environment of Agiasma lagoon. 3. The detection of trends. using the non-parametric Spearman's criterion. This trend analysis proved the existence of trends for the parameters H, Sal and RP. 4. The necessity of real-time monitoring, which can prevent and confront possible natural hazards and disasters and work as an alarm system for the local authorities. (C) 2009 Elsevier B.V. All rights reserved

An empirical model of sediment deposition processes in Lake Kerkini, Central Macedonia Greece

The deposition processes in Kerkini Reservoir, since 1933, are examined in this paper. Built on the course of River Strymonas at the plain of Serres for anti-flooding control, it was gradually developed as a multipurpose reservoir for irrigation and a very important international wetland protected by the Ramsar Treaty. The deposition into Lake Kerkini is caused by the high rates of sediment transport by River Strymonas from the Bulgarian, Serbian and Former Yugoslav Republic of Macedonia territory drainage basin of Kerkini of 11,600 km(2). The life expectancy of the original reservoir was approximately 40 years. The sediment transport and the deposition volumes and rates were high during the first stages of Kerkini operation due to deforestations and stockbreeding activities against forested and agricultural areas in southwestern Bulgaria before World War II, which intensify erosion and deposition phenomena in Kerkini's catchment. They were gradually reduced due to the anti-erosion hydraulic works, extended reforestations mainly in the period 1962-1977, and the natural processes of Strymonas-Kerkini hydrosystem to attain its equilibrium. Based on six systematic bottom surveys of the reservoir from 1933 to 1991, two empirical formulas of the total deposition volume (I V pound (s)) and the deposition rates (Delta I V pound (s)/Delta I t) pound through time (I t) pound were developed. The results have been compared with other catchments of the broader Balkan area concerning the erosion, sediment yield, sediment deposition volumes, and rates, and it was found in accordance with the measured data. The obtained empirical model was used to estimate the life expectancy of the new rebuilt reservoir of Kerkini in 1984; in the case of natural processes, these do not change dramatically in the transboundary Lake Kerkini catchment. The deposition processes of Kerkini were the major causes of its development into an internationally important wetland and biotope. Kerkini offers development opportunities for scientific research, environmental education, ecotourism, and recreation activities

Comparison and assessment of the monitoring data of two REMOS stations in Nestos and Pagoneri for the year 2004. The base for an integrated water management

The monitoring results of two "REMOS" telemetric stations, in River Nestos, are compared. The first one is situated at the Nestos Delta, near Hrisoupoli (Remote Station - RS "Nestos"), and the second one is situated at the course of Nestos, near the Greek-Bulgarian borders (Remote Station - RS "Pagoneri"). The fluctuations of the qualitative and quantitative water parameters have been normalized in the Nestos Delta, following its new anthropogenic regime, whereas at the course of the river, above the power plants, important peaks are noted in the qualitative and quantitative parameters. During the statistical process of these parameters, their trend is examined and their goodness-of-fit assessment of the normal and log-normal distribution is checked, for a significance level of 5%. From the parameters that were examined for RS "Nestos", the water level (H) and the water electrical conductivity (EC(w)) presented a trend, while for RS "Pagoneri", the same parameters did, including dissolved oxygen (DO). A linear regression model was best fitted at all of these parameters. During the goodness-of-fit test, for RS "Nestos" it was reported that water level (H) and water temperature (T(w)) follow the normal distribution (the first marginally), while air temperature (T(a)) follows the log-normal distribution. On the other hand, in RS "Pagoneri", none of the parameters follow a distribution

Morphometric analysis of the drainage network of Samos Island (northern Aegean Sea): Insights into tectonic control and flood hazards

The morphometric analysis of alluvial drainage provides insights into its dynamics, erosion capacity, susceptibility to floods and possible genetic relations to tectonic faulting. In this study, we analysed the drainage system of Samos Island, located in the northern Aegean Sea. The results indicate a vulnerability to erosion and flooding events, and these intense phenomena concentrate mostly on third-order catchments. Two dissimilar drainage network systems are shown: an older drainage network system with a main NW–SE direction, which includes fourth- and fifth-order branches, and a recent drainage network system, which includes new, smaller order branches with a main NE–SW direction. The major tectonic fault orientations are NNW–SSE. The branches of the hydrographic network and faults present different directions, which indicates that the hydrographic pattern is not affected by tectonics. © 201

Hydrologic processes simulation using the conceptual model Zygos: the example of Xynias drained Lake catchment (central Greece)

In the catchment of Xynias drained Lake, hydrologic processes simulation took place using a lumped approach with the conceptual model Zygos. The model implements a conceptual soil moisture accounting scheme extended with a groundwater tank and the input data were the monthly time series of rainfall and the potential evapotranspiration. The automatic optimization procedure of the model was implemented using the evolutionary annealing-simplex algorithm for maximum 11,000 iterations, inserting an 18-month observed runoff time series. It showed that hydrologic balance factors had non-physical significance for the study area. The model’s manual calibration for a Nash coefficient of 0.85 revealed that actual evapotranspiration constitutes 62.5 % (389.7 mm), runoff 22.7 % (141.8 mm) and infiltration 14.8 % (92.2 mm) of precipitation, showing optimal adaptation of simulated to observed runoff. The model estimated the initial reserve of soil moisture related to the presence of organic matter which increases water retention, a residue of the former lake. It confirmed zero runoff values during the summer months and connected the occurrence of springs and the outflows to other catchments (59.8 mm) with the karstification degree of the study area. The error on the annual rainfall is 4.9 % and is considered acceptable. © 2016, Springer-Verlag Berlin Heidelberg

Deep learning in water resources management: The case study of Kastoria lake in Greece

The effects of climate change on water resources management have drawn worldwide attention. Water quality predictions that are both reliable and precise are critical for an effective water resources management. Although nonlinear biological and chemical processes occurring in a lake make prediction complex, advanced techniques are needed to develop reliable models and effective management systems. Artificial intelligence (AI) is one of the most recent methods for modeling complex structures. The applications of machine learning (ML), as a part of AI, in hydrology and water resources management have been increasing in recent years. In this paper, the ability of deep neural networks (DNNs) to predict the quality parameter of dissolved oxygen (DO), in Lake Kastoria, Greece, is tested. The available dataset from 11 November 2015, to 15 March 2018, on an hourly basis, from four telemetric stations located in the study area consists of (1) Chl-a (µg/L), (2) pH, (3) temperature—Tw (◦C), (4) conductivity (µS/cm), (5) turbidity (NTU), (6) ammonia (NH4, mg/L), (7) nitrate nitrogen (N–NO3, mg/L), and (8) dissolved oxygen (DO) (mg/L). Feed-forward deep neural networks (FF-DNNs) of DO, with different structures, are tested for all stations. All the well-trained DNNs give satisfactory results. The optimal selected FF-DNNs of DO for each station with a high efficiency (NSE > 0.89 for optimal selected structures/station) constitute a good choice for modeling dissolved oxygen. Moreover, they provide information in real time and comprise a powerful decision support system (DSS) for preventing accidental and emergency conditions that may arise from both natural and anthropogenic hazards. © 2021 by the authors. Licensee MDPI, Basel, Switzerland