HydroResearchPub Date : 2025-01-01Epub Date: 2024-12-17DOI: 10.1016/j.hydres.2024.12.003
George Bennett
{"title":"A review of the data used to validate groundwater recharge maps created with GIS techniques over the past two decades","authors":"George Bennett","doi":"10.1016/j.hydres.2024.12.003","DOIUrl":"10.1016/j.hydres.2024.12.003","url":null,"abstract":"<div><div>Groundwater recharge maps developed using GIS techniques are important tools that aid the identification of recharge zones. This map must be validated with field data. This study reviewed 63 articles published between 2007 and 2024 to examine the data used to validate these maps and identify the appropriate data for validation. About 50 % of articles reviewed contain non-validated maps, suggesting that many researchers did not do map validation. A total of 12 types of data have been identified to validate groundwater recharge maps, including electrical conductivity, total dissolved solids, stable isotope, and the magnitude of groundwater level fluctuations. Moreover, this review shows that 50 % (<em>n</em> = 6) of the identified data have high uncertainty and are therefore inappropriate for validation, including groundwater level, nitrate concentration, well yield, and aquifer transmissivity. Data reflecting groundwater residence time are more appropriate for validation.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 276-285"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HydroResearchPub Date : 2025-01-01Epub Date: 2025-01-22DOI: 10.1016/j.hydres.2025.01.001
Md. Imran Hosen , Md. Mahmudul Hasan , Md. Talha , Most. Mitu Akter , N.M. Refat Nasher
{"title":"Exploring the cooling benefits of Urban Lakes: A multi-year analysis of Dhaka, Bangladesh","authors":"Md. Imran Hosen , Md. Mahmudul Hasan , Md. Talha , Most. Mitu Akter , N.M. Refat Nasher","doi":"10.1016/j.hydres.2025.01.001","DOIUrl":"10.1016/j.hydres.2025.01.001","url":null,"abstract":"<div><div>The historical and contemporary development of Dhaka city is predominantly unplanned, resulting in significant environmental deterioration. The lack of green and blue spaces and the built areas make it hard for people to stay in comfortable living conditions. The impacts of urban water bodies on the local thermal environment are examined in this study. Landsat 5, 7, and 8 images of 1991, 1996, 2001, 2006, 2011, 2016, and 2021 years were analyzed using ArcGIS (V.10.8) to look at the seasonal changes of normalized difference vegetation index (NDVI) and land surface temperature (LST) of the surrounding lake area. The LST was obtained at a spatial resolution of 30 m using Landsat TM and TIRS imagery, particularly in cloud-free conditions within the study area. The lake water controls the temperature of the adjacent area within 100 to 150 m. The presence of the lake mitigated the disparity between the maximum and minimum temperatures in the hinterland thermal conditions. With time, there was a gradual but consistent rise in temperatures across the board, encompassing the monthly peaks, lows, and averages. Notably, the highest temperatures increased at a faster rate compared to lower and average temperature ranges. It's important to highlight that the rate of temperature rise was more pronounced at 200 m from the lake compared to the increase observed at 100 m. The rise in global temperature due to climate change has made cooling effects less effective for blue bodies in cities. This study's outcomes will help urban planners understand the blue and green space planning in cities to create a comfortable living environment.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 361-373"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154701","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HydroResearchPub Date : 2025-01-01Epub Date: 2024-12-24DOI: 10.1016/j.hydres.2024.12.004
Gaurav Pakhale, Rakesh Khosa, A.K. Gosain
{"title":"Trends and periodicities in Krishna Basin rainfall/extremes found via hierarchical analysis","authors":"Gaurav Pakhale, Rakesh Khosa, A.K. Gosain","doi":"10.1016/j.hydres.2024.12.004","DOIUrl":"10.1016/j.hydres.2024.12.004","url":null,"abstract":"<div><div>Analysing the spatiotemporal changes in long-term rainfall and extreme events at a river basin scale is crucial for optimal water resource management. This study examines trends in long-term rainfall and extreme event indices in the Krishna River Basin (KRB) using Indian Meteorological Department (IMD) 0.25° resolution daily precipitation data from 1951 to 2019. Methods include the Mann–Kendall trend test, Innovative Trend Analysis (ITA), Hurst's Rescaled Range (H<sub>e</sub>) Analysis, and Wavelets.</div><div>The results show variations in rainfall and extreme event patterns across KRB subsystems. Overall, Annual Rainfall (AR) is decreasing, with significant trends in Ghatprabha (K3), Lower Bhima (K6), and Vedavati (K9). Seasonal and monthly rainfall trends are not significant. Extreme event indices (Daily rainfall greater than 10 mm [R10], Daily rainfall greater than 20 mm [R20], and Daily rainfall greater than 40 mm [R40], the annual maximum for 1 to 7 days and starting days of such events showed the non-significant trend in some of the subsystems when analysed with statistical methods; however, graphical analysis using ITA indicates clear trends. H<sub>e</sub> construed a sustainable decreasing trend and predicted a future rainfall reduction. The wavelet power spectra for different indices infer periods between 2 and 16, predominantly concentrated around 2–4 year bands. Decreasing annual rainfall in most headwater catchments, captured by most methods, suggests that KRB will experience less rainfall and fewer rainy days in the future.</div><div>By discerning long-term rainfall trends and periodic patterns in the KRB, future water availability can be predicted, and extreme events can be better analysed. This analysis will be the basis for devising robust flood control measures, mitigating flood risks, and optimizing water resource allocation across sectors, thereby enhancing resilience to climate variability in future.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 316-331"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154689","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HydroResearchPub Date : 2025-01-01Epub Date: 2025-04-17DOI: 10.1016/j.hydres.2025.04.001
Jinyang Zhou , Huihui Yin , Yeling Liu , Baoshan Cui , Qing Wang
{"title":"Relationships between hydrological connectivity and river-lake ecospace in urban-rural areas","authors":"Jinyang Zhou , Huihui Yin , Yeling Liu , Baoshan Cui , Qing Wang","doi":"10.1016/j.hydres.2025.04.001","DOIUrl":"10.1016/j.hydres.2025.04.001","url":null,"abstract":"<div><div>Hydrological connectivity refers to a water-mediated transfer of matter, energy, and organisms in the hydrological cycle and plays a key role in shaping river-lake ecospace and their relevant functions. However, the river-lake ecospace is usually used to indicate static land units such as rivers, lakes, and riparian zones, which lack deep exploration of their relationships and connotations. As a functional space, the river-lake ecospace correlate with variations in hydrological connectivity in terms of structural and functional diversity along the unban-rural gradient. To better understand the relationship between hydrological connectivity and the river-lake ecospace, we first analyzed the characteristics and driving factors of hydrological connectivity in urban-rural areas and then summarized the distribution and functions of the river-lake ecospace. Based on these, we discussed the relationship between the variations in both of them in river-lake system from the aspects of structure, process, and function. Finally, we propose implications for regulating and optimizing the river-lake connectivity to expand the ecospace and enhance its functions.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 374-383"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143869434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HydroResearchPub Date : 2025-01-01Epub Date: 2024-11-20DOI: 10.1016/j.hydres.2024.11.004
Meserecordias Wilfred Lema
{"title":"Contamination of urban waterways: A mini-review of water pollution in the rivers of East Africa's major cities","authors":"Meserecordias Wilfred Lema","doi":"10.1016/j.hydres.2024.11.004","DOIUrl":"10.1016/j.hydres.2024.11.004","url":null,"abstract":"<div><div>This study performs a mini-review, and provides sustainable solutions for water pollution challenges affecting major rivers flowing through urban areas in East Africa. Through a synthesis of 100 peer-reviewed publications between 2010 and 2023, the research examines deteriorating water quality in rivers; Tana, Nakivubo, Kafue, Ruaha, Ruvu and Mara from untreated municipal and industrial wastewater discharges from expanding cities. Results show that BOD, COD, nutrients, heavy metals and bacteria levels exceed national and international standards, degrading riverine environments and posing public health risks. Key constraints to effective pollution management are identified as overlapping governance responsibilities, outdated legal frameworks, lack of clear discharge standards, weak monitoring and compliance, and financing shortfalls. A suite of integrated solutions is proposed, emphasizing upgraded wastewater infrastructure, industrial effluent controls, and enabling policy reforms with strong multi-stakeholder coordination. The study aims to highlight urban river pollution challenges to guide evidence-based mitigation by East African water managers and policymakers.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 307-315"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143154700","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Remote sensing in hydrology: A systematic review of its applications in the Upper Blue Nile Basin, Ethiopia","authors":"Yilkal Gebeyehu Mekonnen , Tena Alamirew , Abebe Demissie Chukalla , Demelash Ademe Malede , Sileshi Getahun Yalew , Aramde Fetene Mengistu","doi":"10.1016/j.hydres.2024.09.002","DOIUrl":"10.1016/j.hydres.2024.09.002","url":null,"abstract":"<div><p>The Upper Blue Nile basin is important for sustaining millions of livelihoods in Ethiopia and downstream nations. However, there are very few hydroclimate observatories in the basin. Remote sensing is an alternative for providing synoptic, repetitive, and timely information. This review investigated how remote sensing data is applied in studying the basin's hydrology. The main application areas include satellite rainfall products evaluation, land use land cover change mapping, evapotranspiration modeling, groundwater recharge estimation, and soil moisture and water storage monitoring. CHIRPS is reported to be the best-performing satellite-based precipitation product. Natural forest, grassland, and shrubland coverage is decreasing, whereas agriculture and urban are increasing. Remote Sensing is used to extract hydrogeological features, identify recharge zones, assess soil moisture, and manage reservoirs. Overall, this review offers insights into how remote sensing can be applied in hydrology, benefiting policymakers, researchers, and practitioners by harnessing the full potential of remote sensing technology.</p></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 1-12"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589757824000246/pdfft?md5=3cad4158aa424985ee8625c67c626def&pid=1-s2.0-S2589757824000246-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142167728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Evaluation of distributed and semi-distributed hydrological models in complex River Basin system, Nepal","authors":"Bhumi Raj Budhathoki , Tirtha Raj Adhikari , Lele Shu , Suraj Shrestha , Ram Prasad Awasthi , Binod Dawadi , Binod Baniya , Yam Prasad Dhital","doi":"10.1016/j.hydres.2024.09.006","DOIUrl":"10.1016/j.hydres.2024.09.006","url":null,"abstract":"<div><div>Hydrological information is essential for planning water resource projects and for simulating hydrological models to calibrate and generate streamflow data. This study evaluates the performance of distributed and semi-distributed hydrological models in the Tamakoshi River Basin (TRB), Nepal. The models assessed include the Spatial Process in Hydrology (SPHY), Hydrologiska Byråns Vattenbalansavdelning (HBV), and Hydrologic Engineering Centre Hydrologic Modeling System (HEC-HMS). The models were evaluated using metrics such as Nash-Sutcliffe Efficiency (NSE) ranging from 0.62 to 0.77, Coefficient of Determination (R<sup>2</sup>) from 0.76 to 0.77, and Percentage Bias (P Bias) from 26.16 % to −3.54 % during daily calibration. All three models were successfully calibrated and validated on a daily and monthly basis using observed discharge data at the Busti station in the TRB. The SPHY model performed better during the calibration period compared to the validation period, while the HBV and HEC-HMS models showed better performance during validation than calibration. Among the statistical indicators, the coefficient of determination closely matched, but NSE and P Bias showed some deviations. This comparative analysis of calibrated and validated models is valuable for filling gaps in hydrological data records and for selecting appropriate hydrological models for planning, managing, and developing water resource projects in the TRB.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 49-57"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2589757824000283/pdfft?md5=247cc2284cd2dfe92c5701d79df14ea2&pid=1-s2.0-S2589757824000283-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142312672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HydroResearchPub Date : 2025-01-01Epub Date: 2024-10-12DOI: 10.1016/j.hydres.2024.10.001
Lokesh P , Madhesh C , Aneesh Mathew , Padala Raja Shekar
{"title":"Machine learning and deep learning-based landslide susceptibility mapping using geospatial techniques in Wayanad, Kerala state, India","authors":"Lokesh P , Madhesh C , Aneesh Mathew , Padala Raja Shekar","doi":"10.1016/j.hydres.2024.10.001","DOIUrl":"10.1016/j.hydres.2024.10.001","url":null,"abstract":"<div><div>Landslide susceptibility mapping is vital for disaster management and sustainable land-use planning. This research was conducted in Wayanad, Kerala, India, to identify landslide susceptible zones. The study used large geospatial datasets, such as elevation, slope, aspect, curvature, stream power index, topographic wetness index, land use and land cover, rainfall, flow accumulation, geology, and geomorphology. It is followed by the application of various machine learning and deep learning models such as the support vector machine, artificial neural networks, logistic regression, random forest, gradient boosting machine, recurrent neural networks long short-term memory, and deep neural network models to map the landslide susceptible zones. The model was trained and validated using the landslide inventory map, which contains 298 sites of landslides. The random forest model, with 97 % accuracy, performed the best. It is possible to effectively mitigate landslides and plan long-term land use by identifying hazardous zones within the study region.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 113-126"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
HydroResearchPub Date : 2025-01-01Epub Date: 2024-11-19DOI: 10.1016/j.hydres.2024.11.005
Sina Sam, Mehmet Özger
{"title":"A multi-method and multi-duration trend analysis of temperature and precipitation in Istanbul, Turkey, by using meteorological records, MERRA-2 reanalysis, and IMERG estimations","authors":"Sina Sam, Mehmet Özger","doi":"10.1016/j.hydres.2024.11.005","DOIUrl":"10.1016/j.hydres.2024.11.005","url":null,"abstract":"<div><div>In this study, temperature and precipitation trends in Istanbul were analyzed using data from a ground-based station for the 1960–2019 interval, Integrated Multi-SatellitE Retrievals for Global Precipitation Measurement (GPM IMERG) for 2000–2019, and Modern-Era Retrospective Analysis for Research and Applications (MERRA-2) temperature reanalysis for 1980–2019. Single-duration analysis revealed significant increasing temperature trends with minor downward and major upward tendencies in precipitation. Multi-duration analysis resulted with dominant decreasing and increasing temperature trends, respectively, in 1980–1999 and 2000–2019, alongside decreasing precipitation trends in 1980–1999 winter and 2000–2019 spring, which were undetected in the single-duration analysis. As a novel attempt, trends based on MERRA-2 and IMERG data were compared with ground-based records in Istanbul and revealed better compatibility in MERRA-2, especially in 2000–2019 compared to IMERG data. By comparing various statistical methods and data sources, this study offers valuable insights into hydrometeorological trend analysis and aids transition from conventional to novel data sources.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 209-222"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142701658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Flood susceptibility analysis to sustainable development using MCDA and support vector machine models by GIS in the selected area of the Teesta River floodplain, Bangladesh","authors":"Shapla Akhter , Md. Mostafizur Rahman , Md. Moniruzzaman Monir","doi":"10.1016/j.hydres.2024.10.004","DOIUrl":"10.1016/j.hydres.2024.10.004","url":null,"abstract":"<div><div>Managing flood risks to ensure sustainable development, this research analyses the flood susceptibility in the selected area of the Teesta River floodplain in Bangladesh using the MCDA model with the SVM model. The different geological and climatic flood vulnerability factors used in this study were collected from USGS, BMD, BARC, BWDB, and BBS. This study reveals that the channel pattern changed, drainage density decreased by 42.28 %, and TWI became high during the study period (2000−2020). This study shows that the very high, high, and medium flood-susceptible zones increased by 5.66 %, 2.7 %, and 7.74 %, and the low-risk zone decreased by 10.79 % during the study period. The drainage system was found to be a significant flood conditioning factor, and the waterbody and river area decreased by 5.31 %. From the flood inventory prediction rate curve analysis 70 % of validation points agreed with field data. According to AUC, the average success rate is 91.51 %.</div></div>","PeriodicalId":100615,"journal":{"name":"HydroResearch","volume":"8 ","pages":"Pages 127-138"},"PeriodicalIF":0.0,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142577847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}