Article
Engineering, Civil
Muhammad S. Ashraf, Ijaz Ahmad, Noor M. Khan, Fan Zhang, Ahmed Bilal, Jiali Guo
Summary: This study investigates variations in streamflow at 20 stations in the upper Indus river basin using different methods, finding that extremely low flows are increasing more significantly than extremely high flows. This may lead to constant pressure on water resources availability in the lower Indus plains where agricultural activities are dependent.
WATER RESOURCES MANAGEMENT
(2021)
Article
Green & Sustainable Science & Technology
Muhammad Shehzad Ashraf, Muhammad Shahid, Muhammad Waseem, Muhammad Azam, Khalil Ur Rahman
Summary: The use of hydro-climatological time series to identify patterns is crucial for understanding climate change and drought. In this study, hydrological drought variability based on the standard drought index (SDI) was investigated in the Upper Indus River Basin (UIRB) of Pakistan. The findings showed a significant decreasing trend in hydrological drought from October to March and a significant increasing trend from April to September. The IITA method was found to be reliable and effective in analyzing these trends.
Article
Environmental Sciences
Fatma Akcay, Bilal Bingolbali, Adem Akpinar, Murat Kankal
Summary: This study analyzed wind speed and significant wave height in coastal areas of the Black Sea using innovative trend analysis methods and compared them with traditional methods. The results showed that the innovative method was better at capturing trend changes. In most months, there was a decreasing trend in average significant wave height, and average wind speed showed a decreasing trend in the inner continental shelf of the southwestern and southeastern Black Sea.
FRONTIERS IN MARINE SCIENCE
(2022)
Article
Water Resources
Musa Esit
Summary: In this study, innovative polygon trend analysis (IPTA) along with Mann-Kendall and innovative trend analysis (ITA) with significance tests were used to analyze the hydrometeorological trends in Ankara province, Turkey. The results showed that ITA and IPTA were more sensitive in capturing precipitation, temperature, relative humidity, and evapotranspiration trends compared to the MK test. The SQ-MK, CUSUM, and SNHT tests successfully detected a change in annual evapotranspiration in 2005.
JOURNAL OF WATER AND CLIMATE CHANGE
(2023)
Article
Environmental Sciences
Mohammad Arab Amiri, Milan Gocic
Summary: The analysis using the ITA method and the Mann-Kendall test on the historical precipitation changes in Serbia from 1946-2019 showed that the southwestern part of the country has the greatest increasing trend, with a noticeable gradient in precipitation trend from east to west. The ITA method was found to be more sensitive in detecting hidden trends compared to the MK trend test.
ENVIRONMENTAL EARTH SCIENCES
(2021)
Article
Water Resources
Arus Edo Harka, Nura Boru Jilo, Fiseha Behulu
Summary: The study investigated the spatio-temporal patterns and variability of rainfall in the Upper Wabe Shebelle River Basin in Ethiopia and found that high rainfall amount occurred in the wet season and high variability in the dry season. The ITA method was shown to be more robust than the MK test in detecting trends, providing valuable insights for water resource planning and management in the region.
JOURNAL OF HYDROLOGY-REGIONAL STUDIES
(2021)
Article
Environmental Sciences
Yilinuer Alifujiang, Jilili Abuduwaili, Yongxiao Ge
Summary: This study investigated the temporal patterns of river runoff data in the Lake Issyk-Kul basin in Central Asia and found various significant increasing and decreasing trends in different time series. The innovative trend analysis (ITA) method was effective in identifying these trends, compared to the Mann-Kendall (MK) trend test. The study revealed the seasonal variations in river runoff data and highlighted the importance of evaluating different values in analyzing trends.
Article
Meteorology & Atmospheric Sciences
Zekai Sen
Summary: In this paper, a new trend methodology is proposed based on the characteristics of crossings along any given straight line within the given time series. It does not require any restrictive assumptions and provides a series of trends at different levels within the variation range of the time series. The methodology is compared with a classical trend determination method and applied to data from the Danube River and Turkey.
THEORETICAL AND APPLIED CLIMATOLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
Zulfaqar Saadi, Zaher Mundher Yaseen, Aitazaz Ahsan Farooque, Nur Athirah Mohamad, Mohd Khairul Idlan Muhammad, Zafar Iqbal
Summary: This study aims to reveal the spatio-temporal trend in extreme rainfall and temperature in Sarawak peatland due to climate change. The Modified Mann-Kendall test was used to analyze trend and confirm the impact of large scale climate events. The study provides essential insights into the behavior of different extreme climate variables and their potential impact on the peatland area susceptible to flood and fire.
WEATHER AND CLIMATE EXTREMES
(2023)
Article
Environmental Sciences
A. Bharath, Ramesh Maddamsetty, M. Manjunatha, T. Reshma
Summary: The study aims to determine the variability and trend in rainfall in Karnataka state, India. The findings reveal increased annual and seasonal rainfall in the study area, except for a significant decline during the post-monsoon season.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Geosciences, Multidisciplinary
Ali Emre Koruk, Murat Kankal, Mehmet Berkant Yildiz, Fatma Akcay, Murat San, Sinan Nacar
Summary: This study investigates the effects of climate change on precipitation in the Susurluk Basin in northwestern Turkey using innovative trend analysis methods. The results show that the innovative methods are more effective in identifying trends compared to traditional methods, with higher visual inspection and interpretation capabilities.
PHYSICS AND CHEMISTRY OF THE EARTH
(2023)
Article
Meteorology & Atmospheric Sciences
Veysel Gumus, Oguz Simsek, Yavuz Avsaroglu
Summary: This study examines the monthly mean streamflow trends in Turkey's Mediterranean basins using different methods and finds that the innovative ITST and IPTA methods are more sensitive in determining significant trends. The results show a more significant decrease in streamflow in the eastern part of the basin, which is important for water resource planning in the region.
THEORETICAL AND APPLIED CLIMATOLOGY
(2023)
Article
Meteorology & Atmospheric Sciences
Ali Danandeh Mehr, Bahrudin Hrnjica, Ognjen Bonacci, Ali Torabi Haghighi
Summary: This study examined the trends in temperature and precipitation in Osijek from 1900 to 2018. The results showed varying trends in temperature across different seasons and temperature ranges, while precipitation exhibited a decreasing trend in spring and an increasing trend in summer. Overall, there was no significant trend in annual precipitation over the past century.
THEORETICAL AND APPLIED CLIMATOLOGY
(2021)
Article
Environmental Sciences
Tommaso Caloiero, Roberto Coscarelli, Gaetano Pellicone
Summary: This study analyzed rainfall data in the southern Italy's Calabria region and found decreasing trends in annual and winter-autumn rainfall, as well as an increasing trend in summer rainfall.
Article
Environmental Sciences
Hai Minh Nguyen, Sylvain Ouillon, Vinh Duy Vu
Summary: In this study, the sea surface height at the Hon Dau tidal gauge station in Vietnam was analyzed between 1961 and 2020. The results showed that the annual sea level varied within a range of 165.23 cm to 206.06 cm, with an average water level of 190.87 cm over the 60-year period. The sea level has been rising in recent years, particularly from 2016 to the present. The Mann-Kendall test and Sen's innovative trend analysis were used to estimate the sea level rise, and both methods showed a significant increasing trend of about 3.08 to 3.38 mm/year for the entire period.
Article
Water Resources
Salah Difi, Yamina Elmeddahi, Aziz Hebal, Vijay P. Singh, Salim Heddam, Sungwon Kim, Ozgur Kisi
Summary: In this paper, a new approach for monthly streamflow prediction based on the extreme learning machine (ELM) and metaheuristic bat algorithm (Bat-ELM) is proposed. The Bat-ELM outperformed other models in terms of prediction performance and can be used for predicting high and extreme streamflow.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Engineering, Civil
Nguyen Van Thieu, Surajit Deb Barma, To Van Lam, Ozgur Kisi, Amai Mahesha
Summary: This study proposes an improved AI model, Augmented Artificial Ecosystem Optimization-based Multi-Layer Perceptron (AAEO-MLP), to build a monthly groundwater level (GWL) forecasting model. The AAEO-MLP model utilizes Levy flight trajectory and Gaussian random to improve the optimizing ability. The results show that the AAEO-MLP is superior to other models in terms of prediction accuracy, convergence, and stability.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Mahdi Majedi-Asl, Mehdi Fuladipanah, Hedi Mahmoudpour, Ebrahim Ebrahimpour, Ozgur Kisi
Summary: In this study, a vulnerability map and genetic algorithm were used to design an optimal monitoring network for the Urmia coastal aquifer. The optimization process considered the correlation between electrical conductivity and vulnerability index, as well as the number and spatial distribution of monitoring wells. The results showed that the chosen weighting coefficient had a significant effect on the optimal solution, resulting in a reduction of 18 wells from the existing network.
GEOCARTO INTERNATIONAL
(2023)
Article
Environmental Sciences
Rana Muhammad Adnan, Hong-Liang Dai, Reham R. Mostafa, Abu Reza Md. Towfiqul Islam, Ozgur Kisi, Salim Heddam, Mohammad Zounemat-Kermani
Summary: The accurate assessment of groundwater levels is critical, especially in arid and semi-arid areas. This study compares the performance of new extreme learning machines (ELM) methods tuned with metaheuristic algorithms in groundwater level estimation.
GEOCARTO INTERNATIONAL
(2023)
Article
Environmental Sciences
Reham R. Mostafa, Ozgur Kisi, Rana Muhammad Adnan, Tayeb Sadeghifar, Alban Kuriqi
Summary: This study investigates the efficiency of two machine-learning methods, random vector functional link (RVFL) and relevance vector machine (RVM), improved with new metaheuristic algorithms, quantum-based avian navigation optimizer algorithm (QANA), and artificial hummingbird algorithm (AHA) in modeling potential evapotranspiration (ET0) using limited climatic data. The results showed that AHA and QANA significantly improved the efficiency of RVFL and RVM in modeling ET0.
Article
Green & Sustainable Science & Technology
Muhammed A. Hassan, Hindawi Salem, Nadjem Bailek, Ozgur Kisi
Summary: This study introduces random forest models to predict fuel consumption and emission rates of passenger cars in Greater Cairo, Egypt. The results demonstrate the reliability of the models in predicting fuel consumption and CO2, CO, and NOx emissions.
Article
Green & Sustainable Science & Technology
Meysam Nouri, Parveen Sihag, Ozgur Kisi, Mohammad Hemmati, Shamsuddin Shahid, Rana Muhammad Adnan
Summary: This study evaluated the discharge coefficient of a combined compound rectangular broad-crested-weir (BCW) gate using the computational fluid dynamics (CFD) modeling approach and soft computing models. Six data-driven procedures were used to estimate the coefficient of discharge (C-dt) of the weir gates, and the SVM model showed the highest accuracy in prediction. The multimode ANN model was found to be the most suitable for predicting the C-dt of a BCW gate, with minimum root mean square error (RMSE) and maximum correlation.
Article
Agronomy
Rana Muhammad Adnan Ikram, Reham R. Mostafa, Zhihuan Chen, Abu Reza Md. Towfiqul Islam, Ozgur Kisi, Alban Kuriqi, Mohammad Zounemat-Kermani
Summary: Hybrid metaheuristic algorithm is a powerful tool in AI that provides accurate ETo prediction, which is crucial for water resource availability and hydrological studies. However, its use in predicting ETo is limited. In this study, the prediction abilities of two SVR models combined with three MAs were compared. The results showed that the SVR-PSOGWO model outperformed other models and could significantly reduce RMSE in ETo prediction. This hybrid machine learning model is recommended for monthly ETo prediction in humid regions and similar climates worldwide.
Editorial Material
Engineering, Civil
Ozgur Kisi, Kai Liepelt, Christoph Kulls
JOURNAL OF HYDROLOGIC ENGINEERING
(2023)
Article
Environmental Sciences
Behrooz Keshtegar, Jamshid Piri, Waqas Ul Hussan, Kamran Ikram, Muhammad Yaseen, Ozgur Kisi, Rana Muhammad Adnan, Muhammad Adnan, Muhammad Waseem
Summary: Accurate estimation of sediment yields is crucial for studying river morphology and water resources management. The radial M5 tree (RM5Tree) model was found to be applicable in accurately estimating sediment yields using various parameters in the Gilgit River, Upper Indus Basin (UIB) tributary, Pakistan. The RM5Tree model outperformed other models like support vector regression (SVR), artificial neural network (ANN), multivariate adaptive regression spline (MARS), M5Tree, sediment rating curve (SRC), and response surface method (RSM) in terms of prediction accuracy and peak sediment prediction.
Article
Environmental Sciences
Payam Khosravinia, Mohammad Reza Nikpour, Ozgur Kisi, Rana Muhammad Adnan
Summary: The study aims to accurately estimate the discharge coefficient for flow through triangular side orifices using data-driven models such as SVM, LSSVM, and LSSVM-GSA. Experimental data was used to estimate the discharge coefficient using five dimensionless variables. The models were evaluated using statistical indices and charts. The results showed that LSSVM-GSA performed the best, with the highest coefficients of determination (R-2) and Nash-Sutcliffe efficiency (NSE), and the least RMSE and MAE. The ratio of orifice crest height to orifice height (W/H) was identified as having the highest influence on the discharge coefficient.
Article
Engineering, Marine
Rana Muhammad Adnan Ikram, Xinyi Cao, Tayeb Sadeghifar, Alban Kuriqi, Ozgur Kisi, Shamsuddin Shahid
Summary: This study examines the performance of a new hybrid neuro-fuzzy model, which combines the neuro-fuzzy (ANFIS) approach with the marine predators' algorithm (MPA), in predicting short-term significant wave heights. The ANFIS-MPA model is compared with two other hybrid methods, ANFIS-GA and ANFIS-PSO, and shows better accuracy in predicting significant wave height for multiple lead times ranging from 1 h to 1 day. The investigation of the best input for the prediction models using multivariate adaptive regression spline further enhances the accuracy of the ANFIS-MPA model.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Water Resources
Rana Muhammad Adnan, Hong-Liang Dai, Reham R. Mostafa, Abu Reza Md. Towfiqul Islam, Ozgur Kisi, Ahmed Elbeltagi, Mohammad Zounemat-Kermani
Summary: Accurate measurement of water resources is crucial for achieving a sustainable environment. This study presents the development and verification of hybrid extreme learning machine (ELM) models coupled with metaheuristic methods for monthly streamflow prediction. The results showed that the ELM-SAMOA and ELM-PSOGWO models offered the best accuracy compared to other models. These models can be successfully applied in modeling monthly streamflow prediction with local or external hydro-meteorological datasets.
APPLIED WATER SCIENCE
(2023)
Article
Water Resources
Pouria Nakhaei, Ozgur Kisi
Summary: The rapid decline of Lake Urmia in northwest Iran, caused by both human and natural factors, prompted the use of the Soil and Water Assessment Tool (SWAT) model. The study aimed to determine the most effective reservoir outflow simulation scheme and assess the impact of land use changes in the Zarrineh River basin on Lake Urmia. The target release approach for controlled reservoirs and the measured outflow schemes were compared, with the former showing superior performance during validation. Three land use scenarios were considered, and the gradually updating land use scenario exhibited significant improvements in validation results.
HYDROLOGICAL SCIENCES JOURNAL
(2023)
Article
Mathematics
Rana Muhammad Adnan Ikram, Xinyi Cao, Kulwinder Singh Parmar, Ozgur Kisi, Shamsuddin Shahid, Mohammad Zounemat-Kermani
Summary: This study examines the suitability of six metaheuristic regression techniques for predicting short-term significant wave heights. Hourly data and historical values from two stations in Australia were used as inputs for the predictions. The Gaussian process regression (GPR) showed the highest accuracy in predicting single-time-step and multi-time-step significant wave heights.
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)