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Map of Connecticut River Basin (CRB) and the location of USGS streamflow gauges with their coverage area.
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This paper evaluates the feasibility of using satellite precipitation datasets in flood frequency analysis based on the accuracy of different return period flows derived using a hydrologic model driven with satellite and ground-based reference rainfall fields over the Connecticut River Basin. Four quasi-global satellite products (TRMM-3B42V7, TRMM-...
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... study area is the CRB located in the northeast United States, with a domain ranging from 41 N to 45 N latitude and 71 W to 74 W longitude (Figure 1). CRB is a major river basin in New England and discharges to the Connecti- cut River. ...
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Flood is considered as the most widespread and disastrous natural calamity in the world which adversely affects the socioeconomic condition and lives of the people living within the floodplain areas of the world. The Jiadhal River basin of Dhemaji district, Assam experiences a high magnitude of flood almost every year, leaving the people of that ar...
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... The reanalysis products assimilate remote sensing and in situ observations as numerical models of the global atmosphere and land surface (Dee et al. 2011;Saha et al. 2010). Estimations provided by these datasets are used for many research and applied cases, such as trend analysis (Balling et al. 2016;Toride et al. 2018), drought monitoring (Ahmadebrahimpour et al. 2019;Golian et al. 2019;Liu et al. 2020), flood modeling (Dis et al. 2016;Nhi et al. 2018;Yuan et al. 2019), and stream-flow simulation (Try et al. 2020;Yuan et al. 2017). ...
The objective of this study was to model a new drought index called the Fusion-based Hydrological Meteorological Drought Index (FHMDI) to simultaneously monitor hydrological and meteorological drought. Aiming to estimate drought more accurately, local measurements were classified into various clusters using the AGNES clustering algorithm. Four single artificial intelligence (SAI) models—namely, Gaussian Process Regression (GPR), Ensemble, Feedforward Neural Networks (FNN), and Support Vector Regression (SVR)—were developed for each cluster. To promote the results of single of products and models, four fusion-based approaches, namely, Wavelet-Based (WB), Weighted Majority Voting (WMV), Extended Kalman Filter (EKF), and Entropy Weight (EW) methods, were used to estimate FHMDI in different time scales, precipitation, and runoff. The performance of single and combined products and models was assessed through statistical error metrics, such as Kling–Gupta efficiency (KGE), Mean Bias Error (MBE), and Normalized Root Mean Square Error (NRMSE). The performance of the proposed methodology was tested over 24 main river basins in Iran. The validation results of the FHMDI (the compliance of the index with the pre-existing drought index) revealed that it accurately identified drought conditions. The results indicated that individual products performed well in some river basins, while fusion-based models improved dataset accuracy more compared to local measurements. The WMV with the highest accuracy (lowest NRMSE) had a good performance in 60% of the cases compared to all other products and fusion-based models. WMV also showed higher efficiency in 100% of the cases than all other fusion-based and SAI models for simultaneous hydrological and meteorological drought estimation. In light of these findings, we recommend the use of fusion-based approach to improve drought modeling.
... Statistical metrics are widely used to assess model performance in hydrological analyses and applications [62][63][64][65]. BC, BC M , HM, HM M , HS, KH, PM 0.5 , and SC-driven ET performances were evaluated using CRMSE, PCC, DET, MAE, MRE, MSE, NSCE, NNSCE, Bias, and RMSD statistical indices at a daily temporal resolution. ...
... It can be calculated using Equation (36), and its values vary from 0 to +∞. A lower CRMSE indicates better consistency, whereas a value of zero signifies no random error between the time series [65,66]. PCC is the covariance of the two variables divided by the product of their standard deviations and can be calculated using Equation (37). ...
The hydrological cycle should be scrutinized and investigated under recent climate change scenarios to ensure global water management and to increase its utilization. Although the FAO proposed the use of the Penman-Monteith (PM) equation worldwide to predict evapotranspiration (ET), which is one of the most crucial components of the hydrological cycle, its complexity and time-consuming nature, have led researchers to examine alternative methods. In this study, the performances of numerous temperature-driven ET methods were examined relative to the PM using daily climatic parameters from central stations in 11 districts of the Kahramanmaras province. Owing to its geographical location and other influencing factors, the city has a degraded Mediterranean climate with varying elevation gradients, while its meteorological patterns (i.e., temperature and precipitation) deviate from those of the main Mediterranean climate. A separate evaluation was performed via ten different statistical metrics, and spatiotemporal ET variability was reported for the districts. This study revealed that factors such as altitude, terrain features, slope, aspect geography, solar radiation, and climatic conditions significantly impact capturing reference values, in addition to temperature. Moreover, an assessment was conducted in the region to evaluate the effect of modified ET formulae on simulations. It can be drawn as a general conclusion that the Hargreaves-Samani and modified Blaney-Criddle techniques can be utilized as alternatives to PM in estimating ET, while the Schendel method exhibited the lowest performance throughout Kahramanmaras.
... According to Kamal et al. (2017a), Log Pearson III (LP3) distribution method is known for maintaining data originality and giving a better fit over other probability distributions for longer return periods. The LP3 is currently the preferred and standard probability distribution model used by the U.S. and Australia because of its appropriate capacity to estimate extreme flood events (Dis et al., 2018). The distribution has been found to be yielding good results in many applications, particularly for flood peak data (Bhat et al., 2019). ...
The objective of this study was to analyse Manafwa River flood frequency in Eastern Uganda. Analysis of Manafwa River maximum annual flows from 1949-2015 was undertaken using Log Pearson 3 distribution in comparison with Gumbel, Normal and Log Normal distributions to determine frequency of occurrence and magnitude of extreme floods. Statistical analysis including goodness of fit tests of chi-square, Kolmogorov-Smirnov and Anderson-Darling tests were used to generate the most suitable probability distribution model. The results show quantile magnitudes lowest for Log Normal distribution at 43.59 m3/s and highest for Log Pearson 3 distribution at 51.67 m3/s. The 5-year quantile estimates are highest for Normal and Log Pearson at 70.37 m3/s and 63.99 m3/s respectively. The 10-year quantile estimates are highest for Log Normal and lowest for Log Pearson 3 distributions at 87.57 m3/s and 75.13 m3/s respectively. The 100-year quantile estimates are lowest for Normal and highest for Log Normal distributions at 108.57 m3/s and 154.66 m3/s respectively. The 200-year quantile estimates are lowest for Normal and highest for Log Normal distributions respectively at 114.980 m3/s and 177.16 m3/s respectively. Log Pearson 3 distribution emerged as best fit for data. From the statistical analysis, LP 3 probability distribution presents the most accurate regression coefficient at 0.8486 and the most suitable distribution of goodness of best fit using A-D, K-S and Chi square tests followed by the Gumbel distribution. The tests yield 0.15666, 0.04855 and 0.88502 for A-D, K-S and Chi square tests respectively for the LP 3 distribution. There is an increasing upward trend of the discharges at Manafwa River floodplains at higher probabilities of exceedance across all the probability distributions due to varrying climatic changes and rapid landuse changes in the Manafwa catchment. Manafwa river floodplains have the capacity to accommodate and boost crop production and productivity. Any nutrients lost to leaching could be gained from subsequent fallowing and sustainable soil fertility management including; proper drainage, crop rotation, adding organic manure, cover cropping and among others
... The CREST hydrologic model was jointly developed by the University of Oklahoma and the NASA SERVIR project team [58]. It has been publicly available for a decade and widely used in a number of research projects from basin to global scales [10,[59][60][61][62][63]. We used the common version CREST v2.1 to assess the hydrologic availability and capabilities of multi-source precipitation estimates [64]. ...
Satellite and reanalysis precipitation estimates of high quality are widely used for hydrological modeling, especially in ungauged or data-scarce regions. To improve flood simulations by merging different precipitation inputs or directly merging streamflow outputs, this study comprehensively evaluates the accuracy and hydrological utility of nine corrected and uncorrected precipitation products (TMPA-3B42V7, TMPA-3B42RT, IMERG-cal, IMERG-uncal, ERA5, ERA-Interim, GSMaP, GSMaP-RNL, and PERSIANN-CCS) from 2006 to 2018 on a daily timescale using the Coupled Routing and Excess Storage (CREST) hydrological model in two flood-prone tributaries, the Beijiang and Dongjiang Rivers, of the Pearl River Basin, China. The results indicate that (1) all the corrected precipitation products had better performance (higher CC, CSI, KGE’, and NSCE values) than the uncorrected ones, particularly in the Beijiang River, which has a larger drainage area; (2) after re-calibration under Scenario II, the two daily merged precipitation products (NSCE values: 0.73–0.87 and 0.69–0.82 over the Beijiang and Dongjiang Rivers, respectively) outperformed their original members for hydrological modeling in terms of BIAS and RMSE values; (3) in Scenario III, four evaluation metrics illustrated that merging multi-source streamflow simulations achieved better performance in streamflow simulation than merging multi-source precipitation products; and (4) under increasing flood levels, almost all the performances of streamflow simulations were reduced, and the two merging schemes had a similar performance. These findings will provide valuable information for improving flood simulations and will also be useful for further hydrometeorological applications of remote sensing data.
... Evaporation (EP) is the phenomenon of water transfer from the earth and water surfaces to the atmosphere and is an important element in water budget analysis, the management of water resources, and the design of hydrometeorological models [1,2]. Additionally, this phenomenon can greatly affect the capacities of reservoirs in terms of both natural lakes and dams, the efficiency of basins, irrigation programming, and the size of hydromechanics structures like pump stations in the catchments [3][4][5]. EP estimations from lake surfaces, however, are a challenge given the multitude of parameters used in these processes, varying spatiotemporally, and the measurements required to validate these estimates [6]. ...
... The following statistical indices were used in this study for the evaluation of the model performance. The Nash-Sutcliffe Coefficient of Efficiency (NSCE) gives an indication of the predictive skill of the model and can be calculated with Equation (4). In comparison to the NSCE alone, the Normalized Nash-Sutcliffe Coefficient of Efficiency (NNSE) gives a more accurate indicator of the model performance by accounting for the variability in the measurements (Equation (5)). ...
The most crucial losses in the hydrological cycle occur due to evaporation (EP). As a result, the accurate attainment of this complex phenomenon is critical in studies on irrigation, efficiency in the basins, dams, continuous hydrometeorological simulations, flood frequency, and water budget analysis. However, EP data sets are expensive, difficult to sustainably measure, and scarce, also, predictions are challenging tasks due to the wide range of parameters involved in these processes. In this study, the data gaps are filled with Class A evaporation pan observations through building a new meteorological station during seasons with no gauge measurements available for a three-year time period. These observations demonstrate high correlations with the readings from the Meteorology Airport Station, with a PCC of 0.75. After the continuous EP time series was completed over Kahramanmaras, these values were retrieved non-linearly via an artificial intelligence model using multi-meteorological parameters. In the study, the simulation performance is evaluated with the help of eight different statistical metrics in addition to graphical representations. The evaluation reveals that, when compared to the other EP functions, using both temperature and wind-driven simulations has the highest correlation (PCC = 0.94) and NSCE (0.87), as well as the lowest bias (P Bias = −1.65%, MAE = 1.27 mm d −1 , RMSD = 1.6 mm d −1 , CRMSE = 24%) relative to the gauge measurements, while they give the opposite results in the solely precipitation-based models (PCC = 0.42, NSCE = 0.17, P Bias = −6.44%, MAE = 3.58 mm d −1 , RMSD = 4.2 mm d −1 , CRMSE = 62%). It has been clearly seen that the temperature parameter is the most essential factor, while precipitation alone may be insufficient in EP predictions; additionally, wind speed and relative humidity would improve the prediction performance in artificial intelligence techniques.
... Predictions in ungauged watersheds have become a challenge for the hydrological community worldwide (e.g., Emmerik, Mulder, Eilander, Piet, & Savenije, 2015;Ibrahim, Wisser, Barry, & Fowe, 2015;Sivapalan et al., 2003). To achieve better predictions of water resources over sparsely gauged or ungauged watersheds, lacking sufficient in-situ measurements, hydrologists, and water resource managers need to develop and use models or techniques which do not require long time series of meteorological and hydrological measurements (Gao et al., 2017;Khan et al., 2012;Loukas & Vasiliades, 2014;Mei & Anagnostou, 2016). ...
Satellite rainfall products (SRPs) have the potential to overcome the limitations of ground-based rainfall observations and provide an alternative to inadequately or ungauged watersheds. However, due to the relatively poor accuracy and associated uncertainties to SRPs, it is necessary to evaluate their quality and applicability for each investigated watershed. This paper evaluates the usefulness of SRPs as forcing data for hydrological modeling under different scenarios and assesses their applicability for the Kedougou, Mako and Simenti sub-basins of the Gambia River. To achieve this, the “Génie Rural à 4 paramètres Journalier model” (GR4J) hydrological model was employed to simulate the streamflow considering four different scenarios: i) non-calibrated GR4J model run with uncorrected SRPs (Scenario 1); ii) non-calibrated model run with corrected SRPs (Scenario 2); GR4J model was calibrated and validated using uncorrected SRPs, and then they were utilized to drive the model (Scenario 3); GR4J model was calibrated and validated and then run using forcing inputs from corrected SRPs (Scenario 4). Results revealed that under Scenario 1 the SRPs performed poorly over the three sub-basins, while under scenario 2, the simulated daily streamflows showed relative improvement when run using corrected SRPs with 6 or 10 rainfall stations. Under the scenarios 3 and 4, the calibrated model provides significant improvement of the simulated streamflow with both the corrected and non-corrected SRPs. Finally, the SRPs demonstrate potential for use in watersheds where there are no rain gauges. The performance loss from scenario 4 (considered as the reference) to scenario 3 does not exceed 20%. Similarly, the performance loss from scenario 4 to scenario 2 does not exceed 50% when the SRPs are corrected using 3 and 6 rainfall stations (e.g., in the Kedougou sub-basin). Thus, they can be considered acceptable for hydrological simulations when the hydrological model is calibrated with measured streamflow.
... If reliable, this can be used as input data in different types of models for different applications. The GPM product has been recognized for its good performance in various hydrological applications, such as rainfall frequency analysis [44], extreme precipitation [45], flood analysis [46], and drought monitoring [47]. Chile is a country affected by several types of hydrometeorological events [45,48]. ...
Accurate rainfall measurement is a challenge, especially in regions with diverse climates and complex topography. Thus, knowledge of precipitation patterns requires observational networks with a very high spatial and temporal resolution, which is very difficult to construct in remote areas with complex geological features such as desert areas and mountains, particularly in countries with high topographical variability such as Chile. This study evaluated the performance of the near-real-time Integrated Multi-satellite Retrievals for GPM (IMERG) Early product throughout Chile, a country located in South America between 16° S-66° S latitude. The accuracy of the IMERG Early was assessed at different special and temporal scales from 2015 to 2020. Relative Bias (PBIAS), Mean Absolute Error (MAE), and Root-Mean-Squared Error (RMSE) were used to quantify the errors in the satellite estimates, while the Probability of Detection (POD), False Alarm Ratio (FAR), and Critical Success Index (CSI) were used to evaluate product detection accuracy. In addition, the consistency between the satellite estimates and the ground observations was assessed using the Correlation Coefficient (CC). The spatial results show that the IMERG Early had the best performance over the central zone, while the best temporal performance was detected for the yearly precipitation dataset. In addition, as latitude increases, so do errors. Also, the satellite product tends to slightly overestimate the precipitation throughout the country. The results of this study could contribute towards the improvement of the IMERG algorithms and open research opportunities in areas with high latitudes, such as Chile.
... Rastgele hatayı ölçen MKOH ölçütü 0 ile +∞ arasında değişen değerler almaktadır. Burada tahminler sıfıra ne kadar yakınsa yöntem o kadar başarılıdır [22][23][24][25][26]. Bu çalışma ile gelecek 50 yıllık nüfus tahminlerinin il genelinde ve merkez ilçelerde artış göstereceğinden su kaynakları ihtiyaçlarının özellikle bu yerlerde artacağı öngörülmekte; diğer taraftan, kontrolsüz kentleşme doğal havza yapısını bozacağından meteorolojik afetlerin başında gelen feyezan ve ani taşkın riskini artırmaktadır. ...
Nüfus artış hızı; kültürel, bilimsel ve teknolojik gelişmelere eş güdümlü olarak değişmektedir. Hızlı nüfus artışı ve göç, kontrolsüz kentleşmeye ve klimatolojik değişikliklere neden olabilmektedir. 1960’tan günümüze kentleşme hızının artmasıyla birlikte Kahramanmaraş’da 50’den fazla taşkın meydana gelmiş, yerleşim yerleri ve tarım arazileri zarar görmüştür. Bu nedenle, geleceğe yönelik kalkınma planları yapılırken nüfusun doğru tahmin edilmesi, planlamanın uygulanabilmesi ve verimliliği açısından önemlidir. Nüfus, çeşitli parametrelere dayanan nüfus projeksiyonlarıyla hesaplanmaktadır. Bu çalışmada, bölgenin 2070 yılına kadarki nüfusu 10 yıllık aralıklarla matematiksel yöntemler kullanılarak tahmin edilmiştir. Yöntemlerin tahmin performansı çeşitli indisler yardımıyla belirlenmiş olup matematiksel metotların genel olarak başarılı olduğu gözlemlenmiştir. Merkez ve merkeze yakın ilçelerde gelecek nüfusların artacağı yönde bir trendin olduğu ve tahminlerin sayımlara yakınsadığı ancak merkezden uzaklaştıkça bu oranın düştüğü belirlenmiştir.
... İstatistiksel indisler, tahminlerin referanslara yakınlığının değerlendirilmesini sağlamak amacıyla hidrologlar tarafından sıklıkla kullanılır [35][36][37]. Bu çalışmada ise farklı metotlara göre hesaplanan ET değerlerinin performanslarını değerlendirmek amacıyla Ortalama Bağıl Hata (OBH) ve Pearson Korelasyon Katsayısı (PCC) kullanılmıştır. OBH indisi tahmin değerlerinin referanslara yakınlığını ifade eder ve Eşitlik 12 ile hesap edilir. ...
Suyun öneminin tartışılmaz olduğu gerçeğini göz önüne alarak, hidrolojik çevrimin ve onun en karmaşık bileşenlerinden biri olan evapotranspirasyon (ET) kaybının iyi belirlenmesi gerekmektedir. Topraktan ve açık su yüzeylerinden buharlaşma ve bitkilerden terleme yoluyla kaybedilen suyun birleşimi olarak tanımlanan ET değerini belirlemek amacıyla birçok ampirik yöntem geliştirilmiş ve bu yöntemler üzerinde modifiye çalışmaları yapılmıştır. Dünyada yaygın olarak bilinen FAO-Penman-Monteith (FAO- PM) denklemi referans alınarak Hargreaves-Samani (HS) ve Blaney-Criddle (BC) denklemleri ile bu iki denklemin modifiye çalışmaları kullanılarak Van ilinde 11 istasyona ait 6 yıllık (2015-2020) günlük meteorolojik veriler ile ET hesabı yapılmış ve modifiye çalışmaların etkileri araştırılmıştır. Pearson Korelasyon Katsayısı (PCC) ve Ortalama Bağıl Hata (OBH) performans değerlendirme indislerinin kullanıldığı çalışmada, tüm sonuçlar incelendiğinde HS ve Modifiye HS (MHS) denklemlerinin iyi sonuçlar verdiği izlenmiştir. HS denklemi içerisindeki sabit değerler üzerinden yapılan modifiye çalışmaları ile oluşan MHS denkleminin, bazı istasyonlarda HS denkleminden daha iyi sonuçlar verdiği gözlemlenmiştir. Yükseklik ile ET arasındaki ilişki dikkate alınarak HS ve BC denklemlerinin yükseklik verisini kullanan modifiye çalışmaları da araştırmaya dâhil edilmiştir. Rakım bazlı modifiye edilen HS denklemi 6 denklem arasında ortalama 0,88 korelasyon değeri ile en kötü sonuçlara sahip denklem olmuştur. BC denklemi üzerinde yapılan modifiye çalışmalar BC denklemine kıyasla daha iyi sonuçlar vermiştir.
... As the r-value approaches one, the agreement between the observed data and the simulated data increases. The correlation coefficient for the statistical study is calculated according to Equation 12 (Dis, Anagnostou, & Mei, 2018 CRMSE ranges from 0 to ∞. As the CRMSE value approaches 0, CRMSE indicates that the generated equation performance is successful. ...
... If the CRMSE value is less than 100, it means that the equation performance is acceptable. The CRMSE is calculated according to Equation 14 (Dis et al., 2018). ...
... ranges from -∞ to ∞. The success of the equation increases as the MRE value approaches 0. The MRE coefficient is calculated according to Equation 15(Dis et al., 2018). ...
Engineers prefer reduced beam section (RBS) connections in steel moment frames built in earthquake zones due to their many benefits. The RBS shape design significantly affects joint behavior. This paper examines the effect of RBS geometry on joint behavior and seismic performance using ANSYS finite element analysis software. RBS connections are investigated using European profiles and steel grades due to the limited number of studies using European profiles in the literature. The simulation study is carried out in three stages. In the first stage, an experimental study in the literature is simulated, and the reliability of the created finite element model is checked. In the second stage, geometric changes are made to the verified numerical model, and the obtained new models are examined under monotonic loading to observe the effect of RBS geometry on moment-rotation behavior. In the third stage, the effect of the change in the RBS geometry on the seismic performance is investigated under cyclic loading. As a result of the study, the effects of various changes made in the RBS geometry on the joint behavior and seismic performance are presented graphically. By using the results of the analysis under monotonic loading, the regression analysis is carried out, and the formulas giving the elastic-plastic stiffness, elastic moment capacity, and elastic rotation angle of the support are derived. Besides, simulation models show that the RBS joints' seismic performance met the minimum criteria specified in the earthquake code (AISC/ANSI 341-16) when European steel profiles and quality are applied.
