Temporal and Periodic Variations of Sunspot Counts in Flaring and Non-Flaring Active Regions

We analyzed temporal and periodic variations of sunspot counts (SSCs) in flaring (C-, M-, or X-class flares), and non-flaring active regions (ARs) for nearly three solar cycles (1986 through 2016). Our main findings are as follows: i) temporal variations of monthly means of the daily total SSCs in flaring and non-flaring ARs behave differently during a solar cycle and the behavior varies from one cycle to another; during Solar Cycle 23 temporal SSC profiles of non-flaring ARs are wider than those of flaring ARs, while they are almost the same during Solar Cycle 22 and the current Cycle 24. The SSC profiles show a multi-peak structure and the second peak of flaring ARs dominates the current Cycle 24, while the difference between peaks is less pronounced during Solar Cycles 22 and 23. The first and second SSC peaks of non-flaring ARs have comparable magnitude in the current solar cycle, while the first peak is nearly absent in the case of the flaring ARs of the same cycle. ii) Periodic variations observed in the SSCs profiles of flaring and non-flaring ARs derived from the multi-taper method (MTM) spectrum and wavelet scalograms are quite different as well, and they vary from one solar cycle to another. The largest detected period in flaring ARs is \(113\pm 1.6~\mbox{days}\) while we detected much longer periodicities (\(327\pm 13\), \(312 \pm 11\), and \(256\pm 8~\mbox{days}\)) in the non-flaring AR profiles. No meaningful periodicities were detected in the MTM spectrum of flaring ARs exceeding \(55\pm 0.7~\mbox{days}\) during Solar Cycles 22 and 24, while a \(113\pm 1.3~\mbox{days}\) period was detected in flaring ARs of Solar Cycle 23. For the non-flaring ARs the largest detected period was only \(31\pm 0.2~\mbox{days}\) for Cycle 22 and \(72\pm 1.3~\mbox{days}\) for the current Cycle 24, while the largest measured period was \(327\pm 13~\mbox{days}\) during Solar Cycle 23.     

Performance Estimation of Aster Global DEM Depending upon the Terrain Inclination

A digital elevation model (DEM) is a source of immense three dimensional data revealing topographic characteristics of any region. The performance of a DEM can be described by accuracy and the morphologic conformity. Both depend upon the quality of data set, the used production technique and the roughness of the terrain. The global DEM of ASTER (Advanced Space-borne Thermal Emission and Reflection Radiometer) was released to public utilization as free of charge on June 2009. It covers virtually overall the globe using 1 arc-second posting interval. Especially easy availability renders ASTER Global DEM (GDEM) one of the most popular and considerable global topographic data for scientific applications. From this point of view, the performance of ASTER GDEM has to be estimated for different kinds of topographies. Accordingly, six test fields from Spain (Barcelona) and Turkey (Istanbul and Zonguldak) have been preferred depending upon the terrain inclination. Thus, the advantages and disadvantages of the DEM product have been proved by means of a group of advanced performance analysis. The analyses indicate that the performance of ASTER GDEM is quite satisfying at urban areas because of flat topography. On the other hand, terrain slope has negative effect on the results. Especially steep, mountainous, forestry topographic formations and the regions which have sudden changes at the altitude have lower accuracy.     

Source Based Characterization and Pollution Profile of a Baker's Yeast Industry

Baker's yeast industry has significant effects on environment due to significant water consumption and high strength wastewater production. Effluents from baker's yeast industry are characterized by high concentrations of biological oxygen demand (BOD₅), chemical oxygen demand (COD), total Kjeldahl nitrogen (TKN), total dissolved solids (TDS), sulfate, and dark brown color. The aim of this study is to provide a detailed quantitative and qualitative identification and characterization of the wastewater sources from different processes of a baker's yeast industry. It is identified that the most polluted wastewater components of the facility are coming from rotary drum filter and evaporation process. However, the highest pollution loads is identified as tank and equipment cleaning effluent due to very high flow rate from this source. The efforts should be on the way to minimize the water usage for the tank and equipment cleaning process, and to recycle less polluted waste streams back to the process.     

A comparative assessment of catchment runoff generation and forest productivity in a semi-arid environment

Understanding the dynamic interactions between forest ecosystems and water in the Mediterranean region is essential for increasing ecosystem services. Even if many studies were implemented to analyse the variations of water and net primary productivity (NPP) in the last decade, this is still an important research question especially for the Eastern Mediterranean, where the research attempts are limited. The main objective of this study was to carry out a comparative analysis of catchment runoff generation and forest NPP and to reveal their temporal dynamics at basin scale in a semi-arid Mediterranean environment. The methodology consisted three steps: (i) estimating catchment runoff generation by implementing process-based J2000 modelling suite, (ii) modelling NPP of the land cover/use types by adapting an ecosystem-process model (BIOME-Biogeochemical cycles) and (iii) assessing the spatio-temporal variability of NPP and runoff dynamics by incorporating the modelling results with multiple regression analysis. Model simulations showed that temperature highly contributed to NPP variations of needle-leaf forests and grasslands. The multiple regression analysis also indicated that runoff was influenced by elevation, precipitation and forest cover. This relationship showed that the inter-annual variability in forest NPP would relate to the variations in runoff distribution across a small Mediterranean subcatchment.     

Basin-wide hydrological system assessment under climate change scenarios through conceptual modelling

ABSTRACT

Mediterranean region is identified as a primary hot-spot for climate change due to the expected temperature and rainfall changes. Understanding the potential impacts of climate change on the hydrology in these regions is an important task to develop long-term water management strategies. The aim of this study was to quantify the potential impacts of the climate changes on local hydrological quantities at the Goksu Watershed at the Eastern Mediterranean, Turkey as a case study. A set of Representative Concentration Pathways (RCP) scenarios were used as drivers for the conceptual hydrological model J2000 to investigate how the hydrological system and the underlying processes would respond to projected future climate conditions. The model was implemented to simulate daily hydrological quantities including runoff generation, Actual Evapotranspiration (AET) and soil-water balance for present (2005–2015) and future (up to 2100). The results indicated an increase of both precipitation and runoff throughout the region from January to March. The region showed a strong seasonally dependent runoff regime with higher flows during winter and spring and lower flows in summer and fall. The study provides a comparative methodology to include meteorological-hydrological modelling integration that can be feasible to assess the climate change impacts in mountainous regions.     

Conditioning Fractal (fBm/fGn) Porosity and Permeability Fields to Multiwell Pressure Data

Stochastic fractal (fGn and fBm) porosity and permeability fields are conditioned to given variogram, static (or hard), and multiwell pressure data within a Bayesian estimation framework. Because fGn distributions are normal/second-order stationary, it is shown that the Bayesian estimation methods based on the assumption of normal/second-order stationary distributions can be directly used to generate fGn porosity/permeability fields conditional to pressure data. However, because fBm is not second-order stationary, it is shown that such Bayesian estimation methods can be used with implementation of a pseudocovariance approach to generate fBm porosity/permeability fields conditional to multiwell pressure data. In addition, we provide methods to generate unconditional realizations of fBm/fGn fields honoring all variogram parameters. These unconditional realizations can then be conditioned to hard and pressure data observed at wells by using the randomized maximum likelihood method. Synthetic examples generated from one-, two-, and three-dimensional single-phase flow simulators are used to show the applicability of our methodology for generating realizations of fBm/fGn porosity and permeability fields conditioned to well-test pressure data and evaluating the uncertainty in reservoir performance predictions appropriately using these history-matched realizations.     

Modelling the current and future spatial distribution of NPP in a Mediterranean watershed

The aim of this study is to use full spatial resolution Envisat MERIS data to drive an ecosystem productivity model for pine forests along the Mediterranean coast of Turkey. The Carnegie, Ames, Stanford Approach (CASA) terrestrial biogeochemical model, designed to simulate the terrestrial carbon cycle using satellite sensor and meteorological data, was used to estimate annual regional fluxes in terrestrial net primary productivity (NPP). At its core this model is based on light-use efficiency, influenced by temperature, rainfall and solar radiation. Present climate data was generated from 50 climate stations within the watershed using co-kriging. Regional scale pseudo-warming data for year 2070 were derived using a Regional Climate Model (RCM) these data were used to downscale the GCM General Circulation Model for the research area as part of an international research project called Impact of Climate Changes on Agricultural Production Systems in Arid Areas (ICCAP). Outputs of climate data can be moderated using the four variables of percent tree cover, land cover, soil texture and NDVI. This study employed 47 MERIS images recorded between March 2003 and September 2005 to derive percent tree cover, land cover and NDVI. Envisat MERIS data hold great potential for estimating NPP with the CASA model because of the appropriateness of both its spatial and its spectral resolution.     

DEM Extraction in Urban Areas Using High-Resolution TerraSAR-X Imagery

Three-dimensional (3D) spatial information is crucial for improving the quality of human life through urban planning and management, and it is widely utilized due to its rapid, periodic and inexpensive acquisition. In this context, extraction of digital surface and elevation models (DSM and DEM) is a significant research topic for space-borne optical and synthetic aperture radar (SAR) remote sensing. The DSMs include visible features on the earth’s surface such as vegetation, forest and elevated man-made objects, while DEMs contain only the bare ground. In this paper, using TerraSAR-X (TSX) high resolution Spotlight (HS) images, high-resolution interferometric DEM generation in a part of Istanbul urban area is aimed. This is not an easy task because of SAR imaging problems in complex geometry of urban settlements. The interferometric processing steps for DSM generation were discussed including critical parameters and thresholds to improve the quality of the final product and a 3 m gridded DSM was generated. The DSM-DEM conversion was performed by filtering and the quality of generated DEM was verified against a reference DEM from stereo photogrammetry with 3 m original grid spacing. The achieved root mean square error of height differences (RMSZ) varies from 7.09 to 8.11 m, depending on the terrain slope. The differential DEM, illustrates the height differences between generated DEM and the reference DEM, was generated to show the correlation between height differences and the coherence map. Finally, a perspective view of test area was created draping extracted DEM and a high-resolution IKONOS panchromatic image.     

Spatio‐temporal trend analysis of drought in the GAP Region,Turkey

Natural Hazards - Drought is considered to be one of the most devastating natural disasters. In recent years, determination of historical droughts has gained more importance. This can be attributed...