Application of a short-term hydrological forecast system

Bu çalışmanın amacı kar erimesinin etkili olduğu dağlık memba havzaları için kısa dönemli akım tahmin sisteminin geliştirilmesidir. Çalışma alanları olarak seçilen dağlık Fırat ve Seyhan Havzaları, yüksek su potansiyeli, bu potansiyeli besleyen kar erimeleri, mansapta büyük ve önemli su yapılarının bulunması ile ön plana çıkmaktadırlar. Yağış-akış ilişkisinin simülasyonu için dağlık bölge uygulamalarında literatürde yaygın olarak kullanılan HBV modeli seçilmiştir. Sayısal Hava Tahmin (SHT) verisi olarak Mesoscale Model 5 (MM5) ve Weather Research and Forecast (WRF) model sonuçları kullanılmıştır. Hidrolojik model parametrelerinin gözlenen yağış, sıcaklık ve akım verileriyle kalibrasyon/doğrulama işleminin yapılmasının ardından, analizleri yapılan SHT verilerinin girdi olarak kullanılması ile 1 ve 2 günlük akım tahminleri elde edilmiştir. İleriye dönük akım tahminleri Delft-FEWS platformunda kapalı döngü şeklinde çalıştırılarak, geçmiş dönem tahmin simülasyonları gerçekleştirilmiş ve akım gözlemleri ile kıyaslanarak performans değerlendirmesi yapılmıştır. Elde edilen sonuçlar havzaların akış aşağısında bulunan su yapılarının daha verimli işletilmesine ve böylece ülke ekonomisine katkı sağlayabilecektir.This study aims to deploy a short term hydrological forecast system in snow dominated mountainous basins. The headwaters of Euphrates and Seyhan Basins, selected as study areas, stand out with their high water potential, snow melt feeding this potential and the presence of large and important water structures in the downstream. For the simulation of precipitation-runoff relationship, HBV model, a widely used model in the literature especially for mountainous regions, is utilized. Mesoscale Model 5 (MM5) and Weather Research and Forecast (WRF) model results are preferred as Numerical Weather Prediction (NWP) data. After calibration/validation of hydrological model parameters with observed precipitation, temperature and flow data, 1- and 2-day flow estimates are obtained using the analyzed NWP data as input. Hindcast simulations for the past period are implemented with a closed-loop structure on the Delft-FEWS platform, and performance evaluation is conducted by comparing them with streamflow observations. The results obtained may contribute to the more efficient operation of water structures located downstream of the basins and thus to the national economy

Evaluation Of Reservoir Model Integration With Deterministic And Probabilistic Streamflow Forecasts

Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems

Product- and Hydro-Validation of Satellite-Based Precipitation Data Sets for a Poorly Gauged Snow-Fed Basin in Turkey

Satellite-based Precipitation (SBP) products are receiving growing attention, and their utilization in hydrological applications is essential for better water resource management. However, their assessment is still lacking for data-sparse mountainous regions. This study reveals the performances of four available PERSIANN family products of low resolution near real-time (PERSIANN), low resolution bias-corrected (PERSIANN-CDR), and high resolution real-time (PERSIANN-CCS and PERSIANN-PDIR-Now). The study aims to apply Product-Validation Experiments (PVEs) and Hydro-Validation Experiments (HVEs) in a mountainous test catchment of the upper Euphrates Basin. The PVEs are conducted on different temporal scales (annual, monthly, and daily) within four seasonal time periods from 2003 to 2015. HVEs are accomplished via a multi-layer perceptron (MLP)-based rainfall-runoff model. The Gauge-based Precipitation (GBP) and SBP are trained and tested to simulate daily streamflows for the periods of 2003–2008 and 2009–2011 water years, respectively. PVEs indicate that PERSIANN-PDIR-Now comprises the least mean annual bias, and PERSIANN-CDR gives the highest monthly correlation with the GBP data. According to daily HVEs, MLP provides a compromising alternative for biased data sets; all SBP models show reasonably high Nash–Sutcliffe Efficiency for the training (above 0.80) and testing (0.62) periods, while the PERSIANN-CDR-based MLP (0.88 and 0.79) gives the highest performance

Bazı polimerlerin laboratuvar koşullarında yüzey akış, toprak kaybı ve kaymak tabakası direnci üzerine etkileri

Two soil samles with sandy clay loam and sandy loam textures were used and it was carried out in laboratory conditions with 3 replicated at this study. After artificial rainfall were applied on erosion plots which were sprayed polyacrylamide (PAM) and polyvinylalcohol (PVA) at different intensities (0, 6.70 ve 33.50 kg ha-1), it was investigated the effects of these polymers on runoff, soil loss and crust strengths. End of this study, it was found that these values were decreased for both of soils. According to statistical analyses, it was determined that PAM and PVA applications reduced runoff and crust strengths significantly (P ;lt; 0.05) in sandy loam textures soil sample.Bu araştırmada kumlu killi tın ve kumlu tın bünyede iki toprak örneği kullanılmış ve araştırma laboratuvar koşullarında 3 tekrarlı olarak yürütülmüştür. Farklı yoğunluklardaki poliakrilamid (PAM) ve polivinilalkol (PVA) (6.70 ve 33.50 kg ha-1) püskürtülmüş erozyon parsellerine yapay yağış uyguladıktan sonra, bu polimerlerin yüzey akış, toprak kaybı ve kaymak tabakası direnci üzerine etkileri incelenmiştir. Araştırma sonucunda, her iki toprak örneğinde de bu değerlerin düştüğü saptanmıştır. İstatistiksel analizlere göre, kumlu tın toprak örneğinde PAM ve PVA uygulamalarının yüzey akış ve kaymak tabakası direncini önemli düzeyde azalttığı belirlenmiştir (P 0.05)

Probabilistic Snow Cover and Ensemble Streamflow Estimations in the Upper Euphrates Basin

Predicting snow cover dynamics and relevant streamflow due to snowmelt is a challenging issue in mountainous basins. Spatio-temporal variations of snow extent can be analyzed using probabilistic snow cover maps derived from satellite images within a relatively long period. In this study, Probabilistic Snow Depletion Curves (P-SDCs) and Probabilistic Snow Lines (P-SLs) are acquired from Moderate Resolution Imaging Spectroradiometer (MODIS) cloud-filtered daily snow cover images. Analyses of P-SDCs show a strong correlation with average daily runoff (R2 = 0.90) and temperature (R2 = 0.96). On the other hand, the challenge lies in developing noteworthy methods to use P-SDCs in streamflow estimations. Therefore, the main objective is to explore the feasibility of producing probabilistic runoff forecasts with P-SDC forcing in a snow dominated basin. Upper Euphrates Basin in Turkey has large snow extent and high snowmelt contribution during spring and summer periods. The melting characteristics are defined by P-SDCs using MODIS imagery for 2001-2012. The value of snow probability maps on ensemble runoff predictions is shown with Snowmelt Runoff Model (SRM) during 2013-2015 where the estimated runoff values indicate good consistency (NSE: 0.47-0.93) with forecasts based on the derived P-SDCs. Therefore, the probabilistic approach distinguishes the snow cover characteristics for a region and promotes a useful methodology on the application of probabilistic runoff predictions especially for snow dominated areas

Comparison of Elongation and Calcification Patterns of Styloid Process on Panoramic and Cone Beam Computed Tomography Images

Purpose: The styloid process (SP) is part of the temporal bone that is a cylindric bony projection located immediately in front of the stylomastoid foramen. The normal reported length of the SP ranges from 20 to 32 mm and longer than 30 mm was considered to be elongated SP. The aim of this study was to compare the SP findings (length, type, and calcification pattern) on panoramic and cone beam computed tomography (CBCT) images. Materials and Methods: 163 patients who had panoramic and CBCT images in the same year were included to the study. On panoramic images calcifications beyond the mandibular foramen were classified as elongated SP while on CBCT images SP which had measured more than 30mm were accepted as elongated. Varying SP calcification classifications were reported by different researchers and in this study Langlais classification (Type 1 Elongated, Type 2 Pseudoarticulated, and Type 3 Segmented), the most accepted classification, was used. Calcification pattern were classified as calcified outlined, partially calcified, nodular, and completely calcified. Results: This study included 35 (21.5%) men, 128 (78.5%) women, 163 patients with mean age 46.13 ± 0.91 (21-65) years. On panoramic images 101 (62%) normal, 45 (27.6%) bilateral and 17 (10.4) unilateral elongated SP were detected. On CBCT images 85 (52.1%) normal, 56 (34.4%) bilateral and 22 (13.4%) unilateral elongated SP were detected. The agreement of the two imaging modalities was calculated as moderate (58.4%). Type 1 SP and partially calcified were the most common features of SP in both imaging modalities. Conclusion: Some SP cases, which are evaluated as not elongated in panoramic images, can be detected as elongated in CBCT images. Therefore, it is recommended to evaluate SP with CBCT in prevalence studies and cases where length is critical