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Deep learning algorithms and their fuzzy extensions for streamflow prediction in climate change framework J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Rishith Kumar Vogeti, Rahul Jauhari, Bhavesh Rahul Mishra, K. Srinivasa Raju, D. Nagesh Kumar
View largeDownload slide View largeDownload slide Close modal The present study analyzes the capability of convolutional neural network (CNN), long short-term memory (LSTM), CNN-LSTM, fuzzy CNN, fuzzy LSTM, and fuzzy CNN-LSTM to mimic streamflow for Lower Godavari Basin, India. Kling–Gupta efficiency (KGE) was used to evaluate these algorithms. Fuzzy-based deep learning algorithms have shown significant
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Decadal mapping of flood inundation and damage assessment in the confluence region of Rivers Niger and Benue using multi-sensor data and Google Earth Engine J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Caleb Odiji, Godstime James, Ademuyiwa Oyewumi, Shomboro Karau, Belinda Odia, Halima Idris, Olaide Aderoju, Abubakar Taminu
View largeDownload slide View largeDownload slide Close modal Climate change has made weather patterns more extreme, causing floods in Nigeria. Flooding is the most frequent and serious natural hazard in the confluence region of Rivers Niger and Benue, impacting lives, agriculture, and socio-economic activities significantly. Advancements in satellite technology and computational capabilities have
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Energy-based hydro-economic modeling of climate change effects on the Upper Euphrates Basin J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Ayca Aytac, Mustafa Sahin Dogan, M. Cihat Tuna
Climate change and global warming are expected to affect water resources management and planning, requiring adaptations to changing conditions. Therefore, it is very important, especially for decision-makers, to identify demand deficits due to less water availability with climate change that may occur in the existing water supply system in advance. FEHEM, a hydroeconomic optimization model of the integrated
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Ecological health assessment of the Qinghe River Basin: analysis and recommendations J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Jingcheng Lei, Jinfeng Zhang, Peiying Li, Hongliang Zhang, Chengbin Xu
View largeDownload slide View largeDownload slide Close modal The assessment of ecosystem health at the scale of a large river basin is currently an important direction in environmental science and landscape ecology research. This study focuses on the ecological health assessment of the Qinghe River Basin. Following the Guidelines for Eco-health Assessment of Basin (Trial), a framework was designed
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Selection of representative general circulation models under climatic uncertainty for Western North America J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Seyed Kourosh Mahjour, Giovanni Liguori, Salah A. Faroughi
Climate change research uses an ensemble of general circulation model runs (GCMs-runs) to predict future climate under uncertainties. To reduce computational costs, this study selects representative GCM-runs (RGCM-runs) for Western North America (WNA) based on their performance in replicating historical climate conditions from 1981 to 2005 and projecting future changes from 1981–2010 to 2071–2100.
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Deriving location-specific synthetic seasonal hyetographs using GPM records and comparing with SCS curves J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Bhavin Ram, Murari Lal Gaur, Gautam R. Patel, M. K. Tiwari
The hyetograph represents the temporal spread of rainfall intensity occurring at a point or over a watershed during a storm. The importance of regionally derived/developed hyetographs and the pooled sets of categorical seasonal curves on intensity-duration, intensity-depth, and depth-duration are of multifarious conveniences and importance. Twenty-one years of daily and sub-daily rainfall records (2000–2020)
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Artificial neural networks for monthly precipitation prediction in north-west Algeria: a case study in the Oranie-Chott-Chergui basin J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Ahcene Bouach
The north-west region of Algeria, pivotal for the nation's water resources and agriculture, faces challenges from changing precipitation patterns due to climate change. In response, our study introduces a robust forecasting tool utilizing artificial neural networks (ANNs) to predict monthly precipitation over a 12-month horizon. We meticulously evaluated two normalization methods, ANN-SS and ANN-MM
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Hydrological assessment of the Gundlakamma sub-basin through SWAT modeling: integration of land use land cover (LULC) and climate changes J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 K. V. Sivakumar Babu, Aravindan Achuthan, Shamshaad Ahmad
Gundlakamma sub-basin faces challenges with increasing water demand and climate change impacts, requiring innovative solutions for sustainable water management. The study was conducted to improve the long-term utilization of water resources in Andhra Pradesh. To accomplish this, the study attempts to estimate LULC change detection and its impact on water resources by analyzing the performance of the
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Investigating the vulnerability of the northern coasts of Iran due to changes in the water level of the Caspian Sea by considering the effects of climate change J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Sina Ghassabian, Omid Tayari, Mehdi Momeni Roghabadi, Mohsen Irandoost
Coastal aquifers are one of the most important sources of water supply, and it is expected that the effects of climate change will be one of their threatening factors in the short or long term. The present study was conducted in the northern coasts of Iran (Amirabad, Babolsar) and the main goal was to investigate the behavior of saltwater advance in coastal aquifers considering the changes in the coastline
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Catchment response to climate change under CMIP6 scenarios: a case study of the Krishna River Basin J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Suram Anil, Anand Raj P, Vamsi Krishna Vema
View largeDownload slide View largeDownload slide Close modal This study assessed the impacts of climate change on the water balance of the Krishna River Basin (KRB) in India. A frequency-based metric, known as symmetric uncertainty, was used to select the top 50% of global climate models (GCMs) from a pool of 18 Coupled Model Intercomparison Project Phase 6 (CMIP6) GCMs for hydrological modelling
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Identifying yield and growing season precipitation gaps for maize and millet in Cameroon J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Terence Epule Epule, Vincent Poirier, Daniel Etongo, Jessica Andriamasinoro
View largeDownload slide View largeDownload slide Close modal Climate change drives huge differences between the actual and projected yield and growing season precipitation. Therefore, this work identifies yield and precipitation gaps for maize and millet at the national and subnational scales as well as policy considerations for agricultural policy experts that can mitigate these gaps. Yield data
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Characteristics and distribution model of wind and wave in Shengsi mussel culture area under the impacts of tropical cyclones J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Zuli Wu, Minsi Xiong, Yongchuang Shi, Yunpeng Song, Yang Dai, Shengmao Zhang
View largeDownload slide View largeDownload slide View largeDownload slide View largeDownload slide View largeDownload slide View largeDownload slide View largeDownload slide View largeDownload slideClose modal The primary industry in Shengsi County, Zhejiang Province, China, is the raft-based cultivation of Mytilus coruscus, which is highly sensitive to wind and wave disturbances. This study aims
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Analysis of the temporal variations in glaciers’ surface area in Alaknanda River Basin, Uttarakhand J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 V. Nunchhani, Sujit Hazarika, Rimum Murtem, Arnab Bandyopadhyay, Aditi Bhadra
View largeDownload slide View largeDownload slide Close modal This study presented detailed analysis of glacier surface extent in the Alaknanda river basin, Western Himalaya, using Landsat series data, land surface temperature and digital elevation model (DEM). The clean glaciers were delineated using automatic glacier extraction index (AGEI) and the debris-covered glaciers were extracted by utilizing
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A drought study in the basin of Lake Urmia under climate change scenarios with higher spatial resolution to understand the resilience of the basin J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Pariya Mohammad Pourian Bazzaz, Sina Sadeghfam, Rahman Khatibi, Vahid Nourani
View largeDownload slide View largeDownload slide Close modal The exposure of the basin of Lake Urmia to meteorological droughts under climate change scenarios is investigated in this study. Should the catastrophic disappearance of the lake be explained by climate change, the basin would not be resilient to droughts in the future. This is examined by a climate change modelling involving downscaling:
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Improvement of daily pan-evaporation calculation in arid and semi-arid regions by limited climatic data J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Mehdi Mohammadi, Meysam Salarijazi, Khalil Ghorbani, Amir-Ahmad Dehghani
In this study, 14 equations have been investigated to calculate pan-evaporation in arid and semi-arid regions (based on the De Martonne aridity index). Two indicators i.e. nRMSE and MBE, were used to analyze the results. The Kohler -Nordonson -Fox (K -N -F) (1955) equation, on the one hand, is more precise than other original equations and, on the other hand, is one of the equations that has less impact
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Detecting drought-prone regions through drought indices J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Sangita Pawar, Mahesh Shelke, Nikita Kushare
View largeDownload slide View largeDownload slide Close modal Climate change has led to heightened variability in global rainfall patterns, resulting in greater unpredictability and inconsistency, and it has led to the origin of meteorological drought situation. This has amplified the frequency of droughts or drought-like conditions worldwide. India, being primarily agrarian, faces significant challenges
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Analysis of the effect of rainfall center location on the flash flood process at the small basin scale J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Guangzhao Chen, Jingming Hou, Tian Wang, Xujun Gao, Dangfeng Yang, Tao Li
View largeDownload slide View largeDownload slide Close modal With the increasing frequency of extreme convective weather, the spatial–temporal variability of rainfall becomes more diversified. As a result of the insufficient quality of rainfall monitoring data in mountainous areas, the flash flood simulation usually does not consider the effect of the rainfall center location. In this work, the GPU
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Linking ecological characteristics with fish diversity, assemblage patterns and feeding guilds, and GIS applications along the temporal and spatial gradients in a large subtropical reservoir, India, for sustainable management J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Absar Alam, Jeetendra Kumar, Uttam Kumar Sarkar, Dharm Nath Jha, Sanjeev Kumar Sahu, Shyamal Chandra Sukla Das, Saket Kumar Srivastava, Vijay Kumar, Basanta Kumar Das
The objective of the investigation was to explore the abundance, composition, and diversity patterns of the fish fauna along the temporal and spatial scale and study the influence of environmental parameters on the fish assemblage in the Rihand reservoir, a large sub-tropical Indian reservoir in India. On the temporal scale, the highest abundance was recorded in the summer season and the lowest in
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Modeling surface water potential using the SWAT model combined with principal component analysis in the ungauged Gelana watershed, Ethiopia J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Habtamu Daniel
View largeDownload slide View largeDownload slide Close modal This study aims to model and assess surface water potential in an ungauged watershed using the Soil and Water Assessment Tool (SWAT), principal component analysis (PCA), and regression-based regionalization techniques in the Gelana River, Ethiopia. The SWAT model was calibrated (and validated) for the 1989–2007 (2008–2015) period, and it
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Climate change-induced drought and implications on maize cultivation area in the upper Nan River Basin, Thailand J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Rabin Bastola, Sangam Shrestha, S. Mohanasundaram, Ho Huu Loc
View largeDownload slide View largeDownload slide Close modal The escalating frequency of climate change-induced droughts poses a severe threat to rainfed maize cultivation in Thailand's upper Nan River Basin (NRB). Utilizing the standardized precipitation evapotranspiration index, this study comprehensively examines spatial and temporal drought patterns and their potential agricultural impact. Findings
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Accelerated anti-oxidant enzymes and phytochemical potential of Taxus wallichiana (Himalayan yew) under moist temperate forest of Himalayan, Pakistan J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Sanam Zarif Satti, Samina Siddiqui, Asim Shahzad, Wadood Shah
View largeDownload slide View largeDownload slide Close modal Taxus wallichiana (Himalayan yew) antioxidant potential enhances the release of secondary metabolites and enzymes under stress; over the last few decades owing to changes in climatic regimes, such species are under constant threat in the moist temperate Himalayan forests. The present study aims to evaluate the effect of change in land-use
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Alternative pricing for irrigation water management in the context of climate change J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Houcine Jeder
View largeDownload slide View largeDownload slide Close modal Irrigation water pricing is an economic regulation instrument widely used in agriculture. Constant annual pricing is always criticized by local decision-makers as well as scientific researchers because it does not take into account the seasonal availability of water in the context of climate change. This study proposes a mathematical programming
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Ensemble rainfall–runoff modeling of physically based semi-distributed models using multi-source rainfall data fusion J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Tagesse Gichamo, Vahid Nourani, Hüseyin Gökçekuş, Gebre Gelete
View largeDownload slide View largeDownload slide Close modal This study was aimed at ensemble rainfall–runoff modeling by Soil and Water Analysis Tool (SWAT), the Hydrologic Engineering Center's Hydraulic Modeling System, and Hydrologiska Byråns Vattenbalansavdelning of Gilgel-Abay watershed, Blue Nile basin, Ethiopia. For modeling, daily rainfall datasets of five gauges and three satellites, streamflow
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Analysis of past and projected changes in extreme precipitation indices in some watersheds in Côte d'Ivoire J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 N'da Jocelyne Maryse Christine Amichiatchi, Jean Hounkpè, Gneneyougo Emile Soro, Ojelabi Oluwatoyin Khadijat, Isaac Larbi, Andrew Manoba Limantol, Abdul-Rauf Malimanga Alhassan, Tie Albert Goula Bi, Agnidé Emmanuel Lawin
The purpose of this study is to analyse trends in annual rainfall extremes over five watersheds within Côte d'Ivoire using observed (1976–2017) and projected (2020–2050) rainfall data from the fourth version of the Rossby Centre regional atmospheric model, RCA4, for the representative concentration pathways RCP 4.5 and RCP 8.5. Four rainfall extreme indices, namely, the consecutive dry days (CDD),
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Analyzing the relationship between meteorological changes and evapotranspiration trends in Gia Lai province, Central Highlands of Vietnam J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Phan Thi Ha, Le Minh Hai, Nguyen Duy Liem, Nguyen Le Tan Dat, Nguyen Thi Huyen, Nguyen Ngoc Thuy, Nguyen Kim Loi
View largeDownload slide View largeDownload slide Close modal This study aims to analyze the historical trends of evapotranspiration at annual and seasonal scales and assess the sensitivity to various meteorological factors in Gia Lai province from 1980 to 2019. The modified innovative-Şen trend method and Sobol analysis are employed for trend identification and sensitivity assessment, respectively
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Water quality prediction: a data-driven approach exploiting advanced machine learning algorithms with data augmentation J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Karthick K, S. Krishnan, R. Manikandan
View largeDownload slide View largeDownload slide Close modal Water quality assessment plays a crucial role in various aspects, including human health, environmental impact, agricultural productivity, and industrial processes. Machine learning (ML) algorithms offer the ability to automate water quality evaluation and allow for effective and rapid assessment of parameters associated with water quality
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Analysis of different hypotheses for modeling air–water exchange and temperature evolution in a tropical reservoir J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Juliana-Andrea Alzate-Gómez, Hélène Roux, Ludovic Cassan, Thomas Bonometti, Jorge Alberto Escobar Vargas, Luis-Javier Montoya Jaramillo
The present analysis shows that the most crucial parameter for a correct representation of the observed temperature behavior are the heat exchange coefficient and the wind. The different approaches tested all have limitations, but they can reproduce reservoir temperature trends at different depths with a maximum standard deviation ranging from 3 °C to 8 °C.
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Evaluation of mine water quality based on the PCA–PSO–BP model J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Jiaqi Wang, Yanli Huang
View largeDownload slide View largeDownload slide Close modal To enhance the mining area's overall use of mine water in the arid area of Western China and mitigate the current water scarcity problem, this paper introduces an intelligent optimization algorithm and neural network for mine water quality evaluation and proposes a principal component analysis (PCA)–particle swarm optimization (PSO)–back
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The effect of arbuscular mycorrhizal fungi on carbon dioxide (CO2) emission from turfgrass soil under different irrigation intervals J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Gökhan Boyno, Caner Yerli, Talip Çakmakci, Ustun Sahin, Semra Demir
Increased nutrient and/or water uptake by arbuscular mycorrhizal (AM) symbiosis can affect soil biochemical properties and emission of the greenhouse gas carbon dioxide (CO2). Therefore, an experiment was designed to investigate the effect of AM fungi (AMF) on CO2 emissions from turfgrass. Three different AMF species (Funneliformis mosseae, Claroideoglomus etunicatum, and Rhizophagus irregularis) were
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Hydroclimatic projection: statistical learning and downscaling model for rainfall and runoff forecasting J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Shweta Kodihal, M. P. Akhtar, Satya Prakash Maurya
View largeDownload slide View largeDownload slide Close modal The study is carried out to investigate the surface runoff depth with changing precipitation due to climate change in the study area where sandy loam and loamy soil are dominant. In this study, future rainfall is projected by a statistical downscaling model (SDSM) using a set of predictors derived from a Coupled Model Intercomparison Project
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Predicting the peak flow and assessing the hydrologic hazard of the Kessem Dam, Ethiopia using machine learning and risk management centre-reservoir frequency analysis software J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-02-01 Elias Gebeyehu Ayele, Esayas Tesfaye Ergete, Getachew Bereta Geremew
View largeDownload slide View largeDownload slide View largeDownload slide View largeDownload slideClose modal Flooding due to overtopping during peak flow in embankment dams primarily causes dam failure. The Kessem River watershed of the Awash basin in the Rift Valley of the Afar region in Ethiopia was studied intricately to predict the causes of the Kessem Dam safety using machine learning predictive
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A review on climate change impacts, models, and its consequences on different sectors: a systematic approach J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Amit Rawat, Dilip Kumar, Bhishm Singh Khati
View largeDownload slide View largeDownload slide Close modal Climate change refers to long-term alterations in climate patterns across various regions of the world. As per the data availability and explanations given by different researchers, human exercises, particularly the burning of coal, deforestation, and the use of oil, have increased the temperature of the Earth by significantly improving
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Can an emission trading policy promote green transformation of regional economies?: evidence from China J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Jiali Qian, Yinxiang Zhou
View largeDownload slide View largeDownload slide Close modal To promote the green development of the global economy and solve the global energy and climate problems, the green transformation of the regional economy is the only way to solve development challenges. Carbon emission trading policies, as an important market mechanism for promoting carbon emission reduction, can further promote green economic
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Random forest and support vector machine classifiers for coastal wetland characterization using the combination of features derived from optical data and synthetic aperture radar dataset J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Sandra Maria Cherian, Rajitha K
View largeDownload slide View largeDownload slide Close modal Mapping mangrove forests is crucial for their conservation, but it is challenging due to their complex characteristics. Many studies have explored machine learning techniques that use Synthetic Aperture Radar (SAR) and optical data to improve wetland classification. This research compares the random forest (RF) and support vector machine
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Comparison of multi-source satellite remote sensing observations for monitoring the variations of small lakes: a case study of Dai Lai Lake (Vietnam) J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Binh Pham-Duc
View largeDownload slide View largeDownload slide Close modal This study compares the capability of Sentinel-1, Sentinel-2, and PlanetScope (PS) satellites in monitoring the variations of surface water of Dai Lai Lake, located in North Vietnam, for the 2018–2023 period. The analysis involves the utilization of Google Earth Engine to partially process Sentinel-1 and Sentinel-2 observations, while PS
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Block-level long-term rainfall variability using trend analysis in a state of central India J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Kamlesh Kumar Sahu, Surendra Kumar Chandniha, Manish Kumar Nema, G. K. Das, Haritha Lekshmi V., Pratibha Warware
View largeDownload slide View largeDownload slide Close modal Rainfall is the key weather element which regulates the hydrological cycle, availability of water resources and crop production. In this study, spatial and temporal variability of rainfall has been investigated on seasonal and annual time scales of the 149 blocks of Chhattisgarh State using 120 years (1901–2020) of rainfall data. Non-parametric
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Integration of machine learning and hydrodynamic modeling to solve the extrapolation problem in flood depth estimation J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Huu Duy Nguyen, Dinh Kha Dang, Nhu Y Nguyen, Chien Pham Van, Thi Thao Van Nguyen, Quoc-Huy Nguyen, Xuan Linh Nguyen, Le Tuan Pham, Viet Thanh Pham, Quang-Thanh Bui
Flood prediction is an important task, which helps local decision-makers in taking effective measures to reduce damage to the people and economy. Currently, most studies use machine learning to predict flooding in a given region; however, the extrapolation problem is considered a major challenge when using these techniques and is rarely studied. Therefore, this study will focus on an approach to resolve
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Impacts of climate change on streamflow of Qinglong River, China J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Xingpo Liu, Zixuan Tang
View largeDownload slide View largeDownload slide Close modal Climate change significantly influences water resources and flood hazards in global watersheds. This study focuses on predicting the impact of climate change on the streamflow of the Qinglong River situated in northern China. The streamflow of the Qinglong River (2021-2100) under two climate change scenarios (RCP 4.5 and RCP 8.5) was mainly
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Improving the forecasting accuracy of monthly runoff time series of the Brahmani River in India using a hybrid deep learning model J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Sonali Swagatika, Jagadish Chandra Paul, Bibhuti Bhusan Sahoo, Sushindra Kumar Gupta, P. K. Singh
Accurate prediction of monthly runoff is critical for effective water resource management and flood forecasting in river basins. In this study, we developed a hybrid deep learning (DL) model, Fourier transform long short-term memory (FT-LSTM), to improve the prediction accuracy of monthly discharge time series in the Brahmani river basin at Jenapur station. We compare the performance of FT-LSTM with
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Tree dieback and subsequent changes in water quality accelerated the climate-related warming of a central European forest lake J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Jiří Kopáček, Stanislav Grill, Josef Hejzlar, Petr Porcal, Jan Turek
View largeDownload slide View largeDownload slide Close modal The water temperature of many lakes has recently risen as a result of climate change. We evaluated trends in the cloudiness, solar radiation, wind, air and water temperatures, ice cover, thermocline depth, transparency, and composition of two Bohemian Forest lakes (Czech Republic) from 1998 to 2022. Lake water temperatures increased by 0
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Impacts of hydroclimate change on climate-resilient agriculture at the river basin management J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Chiranjit Singha, Satiprasad Sahoo, Ajit Govind, Biswajeet Pradhan, Shatha Alrawashdeh, Taghreed Hamdi Aljohani, Hussein Almohamad, Abu Reza Md Towfiqul Islam, Hazem Ghassan Abdo
View largeDownload slide View largeDownload slide Close modal This paper focuses on exploring the potential of Climate resilient agriculture (CRA) for river basin-scale management. Our analysis is based on long-term historical and future climate and hydrological datasets within a GIS environment, focusing on the Ajoy River basin in West Bengal, Eastern India. The standardized anomaly index (SAI) and
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Bias correction of ERA5-Land temperature data using standalone and ensemble machine learning models: a case of northern Italy J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Majid Niazkar, Reza Piraei, Andrea Menapace, Pranav Dhawan, Daniele Dalla Torre, Michele Larcher, Maurizio Righetti
View largeDownload slide View largeDownload slide Close modal Using the global climate model outputs without any adjustment may bring errors in water resources and climate change investigations. This study tackles the critical issue of bias correction temperature in ERA5-Land reanalysis for 10 ground stations in northern Italy using nine machine learning (ML) techniques. Among standalone ML models
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Temporal variation in glacier surface area and glacial lakes in glaciated river basins of Arunachal Pradesh J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Rimum Murtem, Sameer Mandal, V. Nunchhani, Megozeno Megozeno, Arnab Bandyopadhyay, Aditi Bhadra
View largeDownload slide View largeDownload slide Close modal Climate change-induced glacier recession has sparked a dynamic transformation of glaciers in high-mountain areas worldwide, resulting in genesis, expansion, and dissipation of glacial lakes that pose a potential threat to downstream communities, underscoring the need for regular monitoring. This study incorporates the automated glacier extraction
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Consequence assessment of the La Giang dike breach in the Ca River system, Vietnam J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Chau Kim Tran, Thai Canh Nguyen
View largeDownload slide View largeDownload slide Close modal Ca River is one of the largest rivers in Vietnam. The river provides water, electricity, and navigation for millions of people living along the banks. Besides these great benefits, the river also poses many potential risks for people. In the case of flooding, this river can cause terrible damage, especially in the case of dike breach. Therefore
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Accounting for climate change in water infrastructure design: evaluating approaches and recommending a hybrid framework J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Kenneth Hunu, S. A. Conrad, M. DePue
View largeDownload slide View largeDownload slide Close modal A traditional hydrologic water infrastructure design assumes that the climate is stationary, and that historic data reflect future conditions. The traditional approach may no longer be applicable since the earth's climate is not stationary. Thus, there is a need for a new way of designing water infrastructure that accounts for the effects
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Climatic characteristics and main weather patterns of extreme precipitation in the middle Yangtze River valley J. Water Clim. Chang. (IF 2.8) Pub Date : 2024-01-01 Hongzhuan Chen, Xinhuai Yin, Xiaoyu Huang, Enrong Zhao, Xiaofeng Ou, Chengzhi Ye
View largeDownload slide View largeDownload slide Close modal Based on the daily precipitation data and ERA5 reanalysis data of 40 years from 1981 to 2018 in the middle Yangtze River Valley (MYRV), the climatic characteristics of extreme precipitation are analyzed using statistical methods. The multivariate empirical orthogonal functions and spectral clustering methods are used to classify and synthesize
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What water supply system research is needed in the face of a conceivable societal collapse? J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Peter van Thienen, Georgios Alexandros Chatzistefanou, Christos Makropoulos, Lydia Vamvakeridou-Lyroudia
View largeDownload slide View largeDownload slide Close modal The world grapples with immediate crises like COVID-19, Russia's invasion of Ukraine, floods, droughts and wildfires. However, a longer-term crisis looms due to humanity's overstepping of planetary boundaries and its disruptive consequences. Growing awareness of the potential collapse of societies due to planetary boundary violations has
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The burden of water insecurity: a review of the challenges to water resource management and connected health risks associated with water stress in small island developing states J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Stephanie Yolan Parker, Kimalie Fabian Parchment, Georgiana Marie Gordon-Strachan
View largeDownload slide View largeDownload slide Close modal Water resources, whether exceeding per capita water abundance thresholds or below water scarcity thresholds, are health determinants within small island developing states (SIDS). Thresholds indicate water stress vulnerability in SIDS, but underestimate the physicality associated with a lack of water. The objectives of this study were to
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Trend in rainfall associated with tropical cyclones in Mexico attributed to climate change and variability J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Sinuhé Alejandro Sánchez Martínez, Fernando J. González Villarreal, Ramón Domínguez Mora, Maritza Liliana Arganis Juárez
View largeDownload slide View largeDownload slide Close modal The aim of this study was to investigate the existence and the magnitude of trend in different areas and durations of rainfall associated with tropical cyclones (TCR). To achieve this objective, a mixed-method approach was employed using depth–area–duration (DAD) and areal reduction factor (ARFs) curves that can be described as a logarithm
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Regional-scale flood impacts on a small mountainous catchment in Thailand under a changing climate J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Sawitree Rojpratak, Seree Supharatid
Extreme rainfall and flooding are common during the summer monsoon season in Thailand. In this study, we utilized Robust Empirical Quantile Mapping (RQUANT) to correct the bias in precipitation, and total runoff data obtained from the latest Couple Model Intercomparison Project phase 6 (CMIP6) for the upper Lam Takong river basin. Five different methods were employed to estimate the river discharge
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Estimation of daily suspended sediment concentration in the Ca River Basin using a sediment rating curve, multiple regression, and long short-term memory model J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Chien Pham Van, Hien Le, Le Van Chin
View largeDownload slide View largeDownload slide Close modal This study presents a sediment rating curve (SRC), multiple regression (MR), and long short-term memory (LSTM) model for estimating daily suspended sediment concentration (SSC). The data of daily SSC at Yen Thuong and daily flow at five locations in the Ca River Basin, Vietnam are used to demonstrate multiple approaches. Using the daily
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Integrated assessment of flood and drought hazards for current and future climate in a tributary of the Mekong river basin J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Jessica Penny, Dibesh Khadka, Mukand Babel, Priscila Alves, Slobodan Djordjević, Albert S. Chen, Ho Huu Loc
Projecting floods and droughts characteristics under climate change is important to formulate an integrative management plan and enhance resiliency of society. However, studies that provide the integration of floods-drought hazards are scarce within literature. This study assessed flood and drought hazards separately and together for future climate in the Mun River basin, a tributary of the Mekong
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Enhancing climate-resilient urban river restoration: predictive modeling of geomorphic changes J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Farzad Jalaeifar, Amin Sarang, Asghar Abdoli, Mohammad Hosein Niksokhan
View largeDownload slide View largeDownload slide Close modal Urbanization and climate change are two potent forces shaping the contemporary environment. Urban rivers, integral to city life, are profoundly affected by these dynamics. While restoration efforts have yielded promising results, a persistent challenge lies in the inadequate consideration of geomorphic processes and climate change impacts
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Modelling and forecasting of urban flood under changing climate and land use land cover J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Sreemanthrarupini Nariangadu Anuthaman, Saravanan Ramasamy, Balamurugan Ramasubbu, Balaji Lakshminarayanan
Chennai is a rapidly urbanizing Indian mega-city and experiences flooding frequently. Literature state that climate change and land use change have a significant impact on the runoff generated every year, making it essential to study the historical trend and forecast changes in land use land cover (LULC) and climate to model runoff. This study considered Adyar watershed for LULC change detection, climate
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Simulation and optimization of Lar Dam reservoir storage under climate change conditions J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Hediyeh Sadeghijou, Amirpouya Sarraf, Hassan Ahmadi
View largeDownload slide View largeDownload slide Close modal In this research, A 15-year impact of climate change in Lar Dam has been investigated. The results showed that in the case of climate change under three scenarios, Tmax and the Tmin have increased by 5, 5.23, 6.2% and 3.5, 5.6, 5.17%, respectively, and the amount of precipitation increased by 8.55, 9.5, 13%, respectively. Also, the highest
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The water–energy–food (WEF) nexus as a tool to develop climate change adaptation strategies: a case study of the Buffalo River catchment, South Africa J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Nosipho Dlamini, A. Senzanje, T. Mabhaudhi
View largeDownload slide View largeDownload slide Close modal The Buffalo River catchment in KwaZulu-Natal, South Africa, has limited water resource infrastructure development, and climate change is predicted to increase its water supply deficits by exacerbating water distribution inequalities. This study evaluates and optimises current climate change policy plans on the Buffalo River catchments water
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Eco-efficiency analysis of rainfed and irrigated maize systems in Bosnia and Herzegovina J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Ivana Mitrović, Mladen Todorović, Mihajlo Marković, Andi Mehmeti
View largeDownload slide View largeDownload slide Close modal This study evaluated the eco-efficiency of rainfed and irrigated maize production in Bosnia and Herzegovina. Environmental impact assessments were performed through energy, carbon footprint, and water scarcity footprint analysis. For economic analysis, gross and net returns and benefit–cost ratios were calculated. Eco-efficiency was measured
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Nexus of land use land cover dynamics and extent of soil loss in the Panjkora River Basin of eastern Hindu Kush J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Haseeb Ur Rahman, Muhammad Shakir
View largeDownload slide View largeDownload slide Close modal The increasing population, deforestation and conversion of agricultural land to the built-up areas are putting pressure on land resources. Moreover, among land degradation, soil loss is one of the common issues that has had adverse consequences for natural ecosystems, thus affecting livelihoods. The Panjkora River Basin is selected as the
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Assessing the vulnerability of flash floods to climate change in arid zones: Amman–Zarqa Basin, Jordan J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Rihan Al Saodi, Mustafa Al Kuisi, Ahmed Al Salaymeh
View largeDownload slide View largeDownload slide Close modal The objective of this study was to evaluate the sensitivity of flash floods to future climate change in the Amman–Zarqa Basin, Jordan. Historical daily rainfall and temperature data from 1970 to 2018 were collected, along with projected daily data derived from general circulation models (GCMs) forecast spanning 2019–2060. The methodology
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Assessing the utility of hybrid hydrological modeling over complex conditions of the Chitral basin, Pakistan J. Water Clim. Chang. (IF 2.8) Pub Date : 2023-12-01 Zain Syed, Prince Mahmood, Sajjad Haider, Shakil Ahmad
Streamflow forecasting holds pivotal importance for planning and decision-making in the domain of water resources management. The Chitral basin in Pakistan is characterized by high altitude and glaciated terrain. Simulating streamflows in this type of region is challenging due to complex orography and uncertain climate data. This complexity persuaded us to explore three frameworks (soil and water assessment