Ölçümü olmayan akarsu havzalarında akım tahminlerinin iyileştirilmesi
Ölçümü olmayan akarsu havzalarında akım tahminlerinin iyileştirilmesi
Dosyalar
Tarih
2020
Yazarlar
Yılmaz, Mustafa Utku
Süreli Yayın başlığı
Süreli Yayın ISSN
Cilt Başlığı
Yayınevi
Özet
Su, tüm canlılar için yaşamsal öneme sahip doğal bir kaynaktır. Artan nüfus ve buna bağlı olarak gelişen ihtiyaçlar su kaynaklarının geliştirilmesi konusunda haklı bir baskı oluşturmaktadır. Mevcut su varlığının bilinmesi, su kaynaklarının geliştirilmesi kapsamında en önemli unsurlardan biridir. Bu nedenle, akarsu havzasındaki suyun hidrolojik çevrim içerisinde hareketinin belirlenmesi konusu oldukça önem kazanmıştır. Hidrolojik çevrimin önemli bir bileşeni akarsu akımıdır. Akarsudaki akımın miktarı, akarsuyun belirli noktalarında kurulan akım gözlem istasyonları ile ölçülmektedir. Su kaynaklarının verimli bir şekilde kullanılması ve geliştirilmesi için bu ölçümlerin eksiksiz, uzun süreli ve güvenilir olması gerekmektedir. Ancak, bazı akarsularda mevcut akım ölçümlerinin yetersiz ve eksik olması su kaynaklarının geliştirilmesi çalışmalarında karşılaşılan en önemli sorundur. Dolayısıyla coğrafyanın her yerinde tesis edilemeyen akım gözlem istasyonları yüzünden, hidrolojik çalışmalar bilimsellikten ve ekonomiklikten uzak olma tehlikesiyle karşı karşıya kalabilmektedir. Gelecekte daha küçük su kaynaklarının değerlendirileceği düşünüldüğünde, akım tahmini sorununun artacağı açıktır. Bu sorunu gidermek için akımların doğru ve güvenilir tahminlerinin yapılması önem taşımaktadır. Eksik veriyi tamamlayabilmek ya da ölçümü olmayan akarsu havzalarında akım tahmini yapabilmek için literatürde geliştirilmiş birçok yöntem vardır. Özellikle son on yılda araştırmacılar, ölçümü olmayan akarsu havzalarında akım tahmini için ölçümü olan kaynak (donör) havzadan, ölçümü olmayan (hedef) havzaya hidrolojik bilgi transferi gerektiren çeşitli istatistiksel yöntemler benimsemişlerdir. Bu yöntemler genellikle bölgesel yöntemler olarak adlandırılır. Bu çalışmada, günlük akımları tahmin etmek için, regresyon analizi (REG) yöntemi, drenaj alanı oranı (DAR) yöntemi, çoklu kaynak istasyona dayalı DAR (MDAR) yöntemi, ters mesafe ağırlıklı (IDW) yöntemi, ters benzerlik ağırlıklı (ISW) yöntemi, ortalama akım ile akımların standartlaştırılması (SM) yöntemi, ortalama ve standart sapma ile akımların standartlaştırılması (SMS) yöntemi ve bu tekli yöntemlerin çeşitli varyasyonları çalışma alanlarına uygulanmıştır. Tekli yöntemlerin ağırlıklı tahminlerinin uygulanabilirliğini araştırmak için çeşitli topluluk (ensemble) yöntemleri denenmiştir. Akım gözlemlerinin seyrek olduğu Porsuk Çayı Havzası'nda ve Türkiye'nin yüzey suyu açısından en zengin havzası olan Fırat-Dicle Havzası'nda iki ayrı uygulama çalışması yapılmıştır. Yöntemlerin performansının değerlendirilmesinde, Nash-Sutcliffe Etkinliği (NSE), kök ortalama kare hata (RMSE), RMSE-gözlem standart sapma oranı (RSR), belirleme (determinasyon) katsayısı (R2), yüzde eğilim (PBIAS) ve bağıl hata (RE) ölçütleri kullanılmıştır. Porsuk Çayı Havzası uygulamasında, ilk olarak, seçilen akım gözlem istasyonlarında çeşitli nedenlerle çoğu zaman ölçülememiş ve eksik kalan günlük akım verilerini tamamlamak için REG, DAR, SM ve SMS yöntemleri kullanılmıştır. Bu yöntemler karşılaştırılarak en uygun yöntem ve verileri mevcut olan kaynak istasyonla eksik veriler tamamlanmıştır. İkinci olarak, her bir istasyon sırayla ölçümü olmadığı varsayılarak DAR, MDAR, IDW, SM ve SMS yöntemleri günlük akımı tahmin etmek için kullanılmıştır. SM ve SMS yöntemlerinde kullanılan ölçümü olmadığı varsayılan istasyonların uzun dönem istatistiksel parametrelerini (akımların ortalaması ve standart sapması) elde etmek için regresyon denklemleri önerilmiştir. Bu regresyon denklemleri istatistiksel parametreler ve drenaj alanı arasındaki logaritmik ilişkilere dayalı olarak hesaplanmıştır. Daha anlamlı tahminler elde etmek ve belirsizlikleri azaltmak için tekli yöntemler, NSE performansına göre ağırlıklandırılmış ve daha sonra topluluk tahminleri elde etmek için birleştirilmiştir. Her bir istasyon için iki ve üç yöntemi birleştiren topluluk yöntemlerinin tahmin performansı, tekli yöntemlerin tahmin performansı ile karşılaştırılmıştır. Çeşitli topluluk yöntemlerin test edilmesiyle akım tahminlerinin iyileştirilmesinde umut verici sonuçlar elde edilmiştir. Ayrıca, gözlemlenen ve tahmin edilen verilerin debi süreklilik eğrilerinin farklı hidrolojik durumlar için seçilen aşılma olasılıklarına karşılık gelen akım değerleri karşılaştırılmıştır. Sonuç olarak, ölçümü yetersiz böyle bir havzada elde edilen başarılı sonuçların, akım tahmin literatürüne katkıda bulunması beklenmektedir. Fırat-Dicle Havzası uygulamasında, günlük akımları tahmin etmek için, DAR, MDAR, IDW, ISW, SM ve SMS yöntemleri kullanılmıştır. Yöntemlerin uygulaması için, eksiksiz ve uzun yıllara dayanan akım verilerine sahip Orta Fırat Havzası'ndan 8 ve Yukarı Fırat Havzası'ndan 7 akım gözlem istasyonu seçilmiştir. Her bir havza kendi içinde ayrı ayrı değerlendirilmiştir. IDW ve ISW yöntemlerinin üç farklı güç parametresi (1, 2 ve 3), günlük akım değerlerini tahmin etmek için doğruluk ve uygunluklarını belirlemek amacıyla karşılaştırılmıştır. SM ve SMS yöntemlerinde kullanılacak uzun dönem akım istatistiklerini tahmin etmek için bölgesel çok değişkenli aşamalı regresyon yöntemi kullanılmıştır. Akımların yıllık ve aylık bazda ortalama ve standart sapma değerleri çeşitli hidrometeorolojik ve hidromorfolojik değişkenlere bağlı olarak hesaplanmıştır. Kaynak istasyonlar, her bir hedef istasyon için coğrafi yakınlığa, fiziksel benzerliğe ve korelasyona bağlı olarak belirlenmiştir. Kaynak ve hedef istasyonlar arasındaki fiziksel benzerliği belirlemek için coğrafi, topografik ve iklim değişkenleri gibi temel özellikler göz önünde bulundurulmuştur. Performans ağırlıklı topluluk yöntemleri için mutlak hata, NSE, RSR ve PBIAS değerlerine dayalı tekli yöntem ağırlıklandırma sistemi geliştirilmiştir. 2'li ve 3'lü birleşim topluluk yöntemlerinin tahmin performansı, tekli yöntemlerin tahmin performansı ile karşılaştırılmıştır. Ek olarak, günlük akım verileri gürültüyü azaltmak için ön işleme tabi tutulmuştur. Simetrik iki taraflı hareketli ortalama (MA), günlük akım verilerinin yumuşatılması (smoothing) için kullanılmıştır. İstatistiksel yöntemlerin tahmin performansı, gözlemlenen ve yumuşatılmış günlük akım verileri kullanılarak test edilmiş ve karşılaştırılmıştır. MA ile yumuşatılan günlük akım verilerini kullanan, DAR-MA, MDAR-MA, IDW-MA, ISW-MA, SM-MA, SMS-MA olarak adlandırılan istatistiksel yöntemler önerilmiştir. Yöntemlerin güvenirliliğini test etmek amacıyla blok bootstrap simülasyonu yöntemi kullanılmıştır. Her bir istasyon için elde edilen 1000 adet blok bootstrap verileri kullanılarak debi süreklilik eğrilerinin farklı hidrolojik durumlar için seçilen aşılma olasılıklarına karşılık gelen akımları hesaplanmıştır ve %95 güven düzeyinde güven aralıkları belirlenmiştir. DAR, MDAR, IDW, ISW, SM, SMS, 2'li ve 3'lü birleşim topluluk yöntemler ile elde edilen tahminlerin debi süreklilik eğrilerinin seçilen aşılma olasılıklarına karşılık gelen akım değerlerinin bu aralıklar içinde kalıp kalmadığı test edilmiştir. Sonuç olarak, çalışmada kullanılan yöntemlerin, veri temininde güçlük çekilen su kaynakları projelerinde karar verme ve tasarım için kolaylıkla uygulanabilirliği gösterilmiştir.
Water is a natural source of vital importance for all living things. The growing population and the resulting needs put pressure on the development of water resources. Knowing the amount of water available is one of the most important elements in the development of water resources. Therefore, the determination of the water movement in the hydrological cycle has gained importance. An important component of the hydrological cycle is the streamflow. Streamflow is measured by the gauging stations which are established at particular points of the river. For efficient use and development of water resources, these measurements must be complete, long-term and reliable. However, the lack of measurements in some rivers is the most important problem encountered in the development of water resources. Therefore, hydrological studies may in the danger of being unscientific and uneconomic due to gauging stations that cannot be placed everywhere. Considering that smaller water resources will be utilized in the future, it is clear that streamflow estimation problem will increase. In order to solve this problem, it is important to make accurate and reliable streamflow estimates. In the literature, there are many methods advanced for completing missing data or for estimating streamflow in ungauged basins. Especially in the last decade, researchers have adopted a variety of statistical methods that require the transfer of hydrological information from a gauged source (donor) basin to an ungauged (target) basin for streamflow estimation in ungauged basins. These methods are usually referred to as regional methods. In order to estimate daily streamflows, regression analysis (REG) method, drainage area ratio (DAR) method, multiple source stations based DAR (MDAR) method, inverse distance weighted (IDW) method, inverse similarity weighted (ISW) method, standardization with mean (SM) method, standardization with mean and standard deviation (SMS) method and various variations of these individual methods were applied to the study basins. Various ensemble methods were tried to investigate the applicability of weighted estimates of individual methods. Two separate studies were conducted, one in the Porsuk River Basin, which has sparse streamflow observations, and another in the Euphrates-Tigris Basin which is the richest basin of Turkey in terms of surface water. Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), RMSE-observations standard deviation ratio (RSR), determination of coefficient (R2), percent bias (PBIAS) and relative error (RE) were used to evaluate the performance of each method. Drainage area ratio (DAR) method is one of the oldest information transfer methods for obtaining streamflow values at the target station from the source station. This method is straightforward to apply and is in widespread use by hydrologists because it requires no additional information other than the streamflow values at the target station and the drainage areas of the source and target stations. In the traditional application of this method, area normalized streamflow values are transferred from only single source station to the target station. In addition to the drainage area, there are some other factors that have a significant influence on unique streamflow characteristics of a station. Because the DAR method is used with only single source station, systematic errors can be encountered in the estimation of a target station. When more streamflow gauging stations are used to estimate streamflow for the target station, this method is referred to as the multiple source stations based drainage area ratio (MDAR) method. The MDAR method assumes that the streamflow estimates at the target station can be computed as the weighted average of the estimates of the multiple source stations selected. The inverse distance weighted (IDW) method is one of the most widely used interpolation methods based on the geographical distance between the source and the target stations. This method can be considered as a variant of the DAR method. In the IDW method used in this study, area normalized streamflow values are directly transferred to a target station from multiple source stations. The IDW method estimates the streamflow value for the target station by taking the geographical distance between the source station and the target station as the weight. The closer the geographical distance between the source station and the target station is, the larger the influence on the target station will be. That is, when the distance decreases, the weight coefficient increases. The IDW method, also called an inverse distance to a power, is a weighted average interpolator and the main factor affecting the accuracy of the IDW method is the value of the power parameter. As the power parameter increases, more influence is given to the source stations close to the target station. In the literature, the value of the power parameter is commonly chosen as 2, which is known as the inverse distance square weighted. Alternatively, the inverse similarity weighted (ISW) method, which is similar to the IDW method, can be applied on the basis of multiple source stations. Unlike the IDW method, the ISW method uses the physical similarity distance instead of the geographical distance between the target and the source station. Standardization with mean (SM) and standardization with mean and standard deviation (SMS) are common transfer methods for streamflows. SM method takes into account the ratio of streamflow to the mean streamflow. In this study, the SM method applied with annual (SM1) and monthly (SM12) variations. SM1 standardizes the daily time series with the annual mean streamflow, while SM12 standardizes the daily time series with monthly mean streamflow. Whereas, the SMS method is based on the assumption that the standardized streamflows at both a target and a source station are approximately equal. In this study, the SMS method applied with annual (SMS1) and monthly (SMS12) variations. The distinction between these variations of the SMS method is similar to the distinction between SM1 and SM12. In the application of the Porsuk River Basin, firstly, REG, DAR, SM and SMS methods were used to complete the missing data at the target station. the most appropriate completing method was selected for each station. Missing data at each target station were completed using the source station whose data was available. Secondly, assuming that each station in turn is an ungauged basin, DAR, MDAR, IDW, SM and SMS methods were used to estimate daily streamflow. Statistical parameters (mean and standard deviation of the streamflow) used in the SM and SMS methods were calculated by suggested regression equations based on logarithmic relationships between statistical parameters and drainage area. In order to get more consistent estimation and reduce the uncertainties in the individual methods, the estimates from two or three of the individual methods were weighted according to their relative performance and then combined to obtain the recommended ensemble estimates for each station. The performance of these ensemble methods was compared with that of the individual methods. Promising estimation results from ensemble methods were obtained for each station. In addition, selected percentiles for different hydrological conditions of the flow duration curves of the observed and the estimated data were compared. As a result, obtained successful results in such a poorly gauged basin are expected to contribute to the streamflow estimation literature. In the application of the Euphrates-Tigris Basin, DAR, MDAR, IDW, ISW, SM and SMS methods were used to estimate daily streamflows. For the application of the methods, 8 streamflow gauging stations from the Middle Euphrates Basin and 7 streamflow gauging stations from the Upper Euphrates Basin, which have complete and long-term data were selected. Each basin has been evaluated separately. Three different power parameters (1, 2 and 3) of the IDW and ISW methods were compared to determine their accuracy and suitability for estimating daily streamflow values. The Regional multivariate stepwise regression method was used to estimate long-term streamflow statistics for use in SM and SMS methods. The mean and standard deviation values of the streamflows on an annual and monthly basis were calculated based on the various hydrometeorological and hydromorphological variables. The source stations were identified for each target station based on their geographical proximity, physical similarity, and correlation. Basin characteristics such as geographical, topographical, and climate variables were considered for determining the physical similarity between the source and target stations. The individual method weighting system based on absolute error, NSE, RSR and PBIAS values has been developed for performance-weighted ensemble methods. The estimation performance of various pairwise and triple combinations of the individual methods (ensemble methods) was compared with that of individual methods. In addition, the daily streamflow data were smoothed with the symmetric two-sided moving average (MA) filtering in order to reduce noise. The estimation performance of the statistical methods was tested and compared by using daily streamflow data with preprocessing and without preprocessing. The statistical methods using smoothed daily streamflow data by the MA, which are referred to as DAR-MA, MDAR-MA, IDW-MA, ISW-MA, SM-MA, SMS-MA were proposed. Block Bootstrap simulation method was used to test the reliability of the methods. By using 1000 block bootstrap data obtained for each station, the percentiles of the flow duration curves (values having exceedance probability) were calculated for different hydrological conditions and the 95% confidence interval was determined. It was tested whether the percentiles of the flow duration curves of the estimations obtained by DAR, MDAR, IDW, ISW, SM, SMS, and ensemble methods remain within these intervals. As a result, the methods used in the study have been shown to be easily applicable for decision making and design in water resources projects that have difficulty in obtaining data.
Water is a natural source of vital importance for all living things. The growing population and the resulting needs put pressure on the development of water resources. Knowing the amount of water available is one of the most important elements in the development of water resources. Therefore, the determination of the water movement in the hydrological cycle has gained importance. An important component of the hydrological cycle is the streamflow. Streamflow is measured by the gauging stations which are established at particular points of the river. For efficient use and development of water resources, these measurements must be complete, long-term and reliable. However, the lack of measurements in some rivers is the most important problem encountered in the development of water resources. Therefore, hydrological studies may in the danger of being unscientific and uneconomic due to gauging stations that cannot be placed everywhere. Considering that smaller water resources will be utilized in the future, it is clear that streamflow estimation problem will increase. In order to solve this problem, it is important to make accurate and reliable streamflow estimates. In the literature, there are many methods advanced for completing missing data or for estimating streamflow in ungauged basins. Especially in the last decade, researchers have adopted a variety of statistical methods that require the transfer of hydrological information from a gauged source (donor) basin to an ungauged (target) basin for streamflow estimation in ungauged basins. These methods are usually referred to as regional methods. In order to estimate daily streamflows, regression analysis (REG) method, drainage area ratio (DAR) method, multiple source stations based DAR (MDAR) method, inverse distance weighted (IDW) method, inverse similarity weighted (ISW) method, standardization with mean (SM) method, standardization with mean and standard deviation (SMS) method and various variations of these individual methods were applied to the study basins. Various ensemble methods were tried to investigate the applicability of weighted estimates of individual methods. Two separate studies were conducted, one in the Porsuk River Basin, which has sparse streamflow observations, and another in the Euphrates-Tigris Basin which is the richest basin of Turkey in terms of surface water. Nash-Sutcliffe efficiency (NSE), root mean square error (RMSE), RMSE-observations standard deviation ratio (RSR), determination of coefficient (R2), percent bias (PBIAS) and relative error (RE) were used to evaluate the performance of each method. Drainage area ratio (DAR) method is one of the oldest information transfer methods for obtaining streamflow values at the target station from the source station. This method is straightforward to apply and is in widespread use by hydrologists because it requires no additional information other than the streamflow values at the target station and the drainage areas of the source and target stations. In the traditional application of this method, area normalized streamflow values are transferred from only single source station to the target station. In addition to the drainage area, there are some other factors that have a significant influence on unique streamflow characteristics of a station. Because the DAR method is used with only single source station, systematic errors can be encountered in the estimation of a target station. When more streamflow gauging stations are used to estimate streamflow for the target station, this method is referred to as the multiple source stations based drainage area ratio (MDAR) method. The MDAR method assumes that the streamflow estimates at the target station can be computed as the weighted average of the estimates of the multiple source stations selected. The inverse distance weighted (IDW) method is one of the most widely used interpolation methods based on the geographical distance between the source and the target stations. This method can be considered as a variant of the DAR method. In the IDW method used in this study, area normalized streamflow values are directly transferred to a target station from multiple source stations. The IDW method estimates the streamflow value for the target station by taking the geographical distance between the source station and the target station as the weight. The closer the geographical distance between the source station and the target station is, the larger the influence on the target station will be. That is, when the distance decreases, the weight coefficient increases. The IDW method, also called an inverse distance to a power, is a weighted average interpolator and the main factor affecting the accuracy of the IDW method is the value of the power parameter. As the power parameter increases, more influence is given to the source stations close to the target station. In the literature, the value of the power parameter is commonly chosen as 2, which is known as the inverse distance square weighted. Alternatively, the inverse similarity weighted (ISW) method, which is similar to the IDW method, can be applied on the basis of multiple source stations. Unlike the IDW method, the ISW method uses the physical similarity distance instead of the geographical distance between the target and the source station. Standardization with mean (SM) and standardization with mean and standard deviation (SMS) are common transfer methods for streamflows. SM method takes into account the ratio of streamflow to the mean streamflow. In this study, the SM method applied with annual (SM1) and monthly (SM12) variations. SM1 standardizes the daily time series with the annual mean streamflow, while SM12 standardizes the daily time series with monthly mean streamflow. Whereas, the SMS method is based on the assumption that the standardized streamflows at both a target and a source station are approximately equal. In this study, the SMS method applied with annual (SMS1) and monthly (SMS12) variations. The distinction between these variations of the SMS method is similar to the distinction between SM1 and SM12. In the application of the Porsuk River Basin, firstly, REG, DAR, SM and SMS methods were used to complete the missing data at the target station. the most appropriate completing method was selected for each station. Missing data at each target station were completed using the source station whose data was available. Secondly, assuming that each station in turn is an ungauged basin, DAR, MDAR, IDW, SM and SMS methods were used to estimate daily streamflow. Statistical parameters (mean and standard deviation of the streamflow) used in the SM and SMS methods were calculated by suggested regression equations based on logarithmic relationships between statistical parameters and drainage area. In order to get more consistent estimation and reduce the uncertainties in the individual methods, the estimates from two or three of the individual methods were weighted according to their relative performance and then combined to obtain the recommended ensemble estimates for each station. The performance of these ensemble methods was compared with that of the individual methods. Promising estimation results from ensemble methods were obtained for each station. In addition, selected percentiles for different hydrological conditions of the flow duration curves of the observed and the estimated data were compared. As a result, obtained successful results in such a poorly gauged basin are expected to contribute to the streamflow estimation literature. In the application of the Euphrates-Tigris Basin, DAR, MDAR, IDW, ISW, SM and SMS methods were used to estimate daily streamflows. For the application of the methods, 8 streamflow gauging stations from the Middle Euphrates Basin and 7 streamflow gauging stations from the Upper Euphrates Basin, which have complete and long-term data were selected. Each basin has been evaluated separately. Three different power parameters (1, 2 and 3) of the IDW and ISW methods were compared to determine their accuracy and suitability for estimating daily streamflow values. The Regional multivariate stepwise regression method was used to estimate long-term streamflow statistics for use in SM and SMS methods. The mean and standard deviation values of the streamflows on an annual and monthly basis were calculated based on the various hydrometeorological and hydromorphological variables. The source stations were identified for each target station based on their geographical proximity, physical similarity, and correlation. Basin characteristics such as geographical, topographical, and climate variables were considered for determining the physical similarity between the source and target stations. The individual method weighting system based on absolute error, NSE, RSR and PBIAS values has been developed for performance-weighted ensemble methods. The estimation performance of various pairwise and triple combinations of the individual methods (ensemble methods) was compared with that of individual methods. In addition, the daily streamflow data were smoothed with the symmetric two-sided moving average (MA) filtering in order to reduce noise. The estimation performance of the statistical methods was tested and compared by using daily streamflow data with preprocessing and without preprocessing. The statistical methods using smoothed daily streamflow data by the MA, which are referred to as DAR-MA, MDAR-MA, IDW-MA, ISW-MA, SM-MA, SMS-MA were proposed. Block Bootstrap simulation method was used to test the reliability of the methods. By using 1000 block bootstrap data obtained for each station, the percentiles of the flow duration curves (values having exceedance probability) were calculated for different hydrological conditions and the 95% confidence interval was determined. It was tested whether the percentiles of the flow duration curves of the estimations obtained by DAR, MDAR, IDW, ISW, SM, SMS, and ensemble methods remain within these intervals. As a result, the methods used in the study have been shown to be easily applicable for decision making and design in water resources projects that have difficulty in obtaining data.
Açıklama
Tez (Doktora) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2020
Anahtar kelimeler
Debi tahmin,
Discharge estimation,
Yüzey hidrolojisi,
Surface hydrology