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Water Resour Bull 25(6):1163–1168\nBrouziyne Y, Belaqziz S, Benaabidate L, Aboubdillah A, Bilali AE, Elbeltagi A, Tzoraki O, Chehbouni A (2022) Modeling long term response of environmental flow attributes to future climate change in a North African watershed (Bouregreg water shed, Morocco). Ecohydrol Hydrobiol 22:155–167. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecohyd.2021.08.005\nBrisbane Declaration (2007) The Brisbane Declaration: environmental flows are essential for freshwater ecosystem health and human well-being. In: 10th International River Symposium, Brisbane\nHenriksen HJ, Jakobsen A, Pasten-Zapata E, Troldborg L, Sonnenborg TO (2021) Assessing the impacts of climate change om hydrological regimes and fish EQR in two Danish catchments. J Hydrol Reg Stud 34:100798\nHiggs G, Petts G (1988) Hydrological changes and river regulation in the UK. River Res Appl 2:349–368\nHuang W, Duan W, Chen Y (2021) Rapidly declining surface and terrestrial water resources in Central Asia driven by socio-economic and climatic changes. Sci Total Environ 784:147193\nJha R, Sharma KD, Singh VP (2008) Critical appraisal of methods for the assessment of environmental flows and their application in two river systems of India. KSCE J Civ Eng 12(3):213–219\nJian J, Ryu D, Wang QJ (2021) A water-level based calibration of rainfall-runoff models constrained by regionalized discharge indices. J Hydrol 603:126937\nJoshi KD, Jha DN, Alam A, Srivastava SK, Kumar V, Sharma AP (2014) Environmental flow requirements of river Sone: impacts of low discharge on fisheries. Curr Sci 107(3):478–488\nKubiak-Wójcicka K, Zelenáková M, Blištan P, Simonovác D, Pilarska A (2021) Influence of climate change on low flow conditions. Case study Laborec River, Eastern Slovakia. Ecohydrol Hydrobiol 21(4):570–583. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ecohyd.2021.04.001\nKumar S, Roshni T (2019) NDVI-rainfall correlation and irrigation water requirement of different crops in the Sone river-command. Bihar MAUSAM 70(2):339–346\nKumar S, Roshni T, Kahya E, Ghorbani MA (2020) Climate change projections of rainfall and its impact on the cropland suitability for rice and wheat crops in the Sone river command. Bihar Theor Appl Climatol 142:433–451. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs00704-020-03319-9\nLu W, Lei H, Yang D, Tang L, Miao Q (2018) Quantifying the impacts of small dam construction on hydrological alterations in the Jiulong River basin of Southeast China. J Hydrol 567:382–392\nMaharana C, Tripathi JK (2018) The Indian Rivers. J Hydrogeol. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-981-10-2984-4_15\nMonico V, Solera A, Bergillos RJ, Paredes-Arquiola J, Andreu J (2022) Effects of environmental flows on hydrological alteration and reliability of water demands. Sci Total Environ 810:151630. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.scitotenv.2021.151630\nNruthya K, Srinivas VV (2015) Evaluating methods to predict streamflow at ungauged sites using regional flow duration curves: a case study. Aquat Procedia 4:641–648. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.aqpro.2015.02.083\nPetts GE (1996) Water allocation to protect river ecosystems. River Res Appl 12:353–365\nPoff NL, Richter BD, Arthington AH, Bunn SE, Naiman RJ, Kendy E, Acreman M, Apse C, Bledsoe BP, Freeman MC, Henriksen J, Jacobson RB, Kennen JG, Merritt DM, O’Keeffe JH, Olden JD, Rogers K, Tharme RE, Warner A (2010) The ecological limits of hydrological alteration (ELOHA): a new framework for developing regional environmental flow standards. Freshw Biol 55:147–170. https:\u002F\u002Fdoi.org\u002F10.1111\u002Fj.1365-2427.2009.02204.x\nReiser DW, Wesche TA, Estes C (1989) Status of instream flow legislation and practices in North America. Fisheries 14:22–28\nRichter BD, Baumgartner JV, Powell J, Braun DP (1996) A method for assessing hydrologic alteration within ecosystems. Conserv Biol 10(4):1163–1174\nRichter BD, Baumgartner JV, Wigington R, Braun DP (1997) How much water does a river need? Freshw Biol 37(1):231–249\nRichter BD, Baumgartner JV, Braun DP, Powell J (1998) A spatial assessment of hydrologic alteration within a river network. River Res Appl 14:329–340\nSmakhtin VU (2001) Low flow hydrology: a review. J Hydrol 240:147–186\nSmakhtin VU, Toulouse M (1998) Relationships between low flow characteristics of South African streams. Water SA 24:107–112\nStewardson MJ, Gippel CJ (2003) Incorporating flow variability into environmental flow regimes using the flow events method. River Res Appl 19:459–472\nSugiyama H, Vudhivanich V, Whitaker AC, Lorsirirat K (2003) Stochastic flow duration curves for evaluation of flow regimes of rivers. J Am Water Resour Assoc 39(1):47–58\nTharme RE (2003) A global perspective on environmental flow assessment: emerging trends in the development and application of environmental flow methodologies for rivers. River Res Appl 19:397–441. https:\u002F\u002Fdoi.org\u002F10.1002\u002Frra.736\nThe Nature Conservancy (2009) Indicators of hydrologic alteration version 7.1 user's manual\nVerma RK, Murthy S, Verma S, Mishra SK (2017) Design flow duration curves for environmental flows estimation in Damodar River basin. India Appl Water Sci 7:1283–1293",{"EN":184},"Environmental flow is an important indicator of river health as it maintains the natural flow pattern of riverine ecosystem. Although numerous researches for analyzing the hydrological alterations are there, still insightful investigation of site specific knowledge should be required for riverine ecosystem protection. In this study, the objective is to analyze the hydrological status of the Sone river basin in Bihar region, India. This study also focuses to develop a flow duration curve (FDC) to show the time duration–frequency of low-flow events. The hydrological status of the basin was analyzed using indicators of hydrologic alteration (IHA). Low flows were estimated using period of record flow duration curve (POR FDC), and design environmental flow was assessed for 10-year and 100-year return period using stochastic flow duration curve (stochastic FDC). Daily discharge data collected from Koelwar station of Sone river for 1990–2020 period were used for the hydrological analysis. Depending on the quantitative and qualitative assessment of the hydrological alterations, it was found that the hydrological status of the river basin is in a \"very altered\" state. The POR FDC analyzed 7-day mean discharge values (7dQ) appropriate for determining low flows, and discharge values corresponding to 95% probability of exceedance (Q95) were considered as low flow for 7dQ. Stochastic FDCs generated 7-day mean flow duration curves for 10-year (7Q10) and 100-year (7Q100) recurrence intervals. Discharge values corresponding to 95% probability of exceedance for 7Q10 range from 120 to 125 cumec and those for 7Q100 range from 135 to 140 cumec. 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Annu Rev Ecol Evol Syst 35:257–284",{"doi":350},"10.1146\u002Fannurev.ecolsys.35.120202.110122",{"id":20,"text":352,"url":20,"identifiers":353},"Banasik K, Hejduk L (2012) Long-term changes in runoff from a small agricultural catchment. Soil Water Res 7:64–72",{"doi":354},"10.17221\u002F40\u002F2011-SWR",{"id":20,"text":356,"url":20,"identifiers":357},"Bates BC, Kundzewicz ZW, Wu S, Palutikof JP (2008) (eds) Climate change and water, Technical Paper of the Intergovernmental Panel on Climate Change, IPCC Secretariat, Geneva, 3–4",{},{"id":20,"text":359,"url":20,"identifiers":360},"Berezowski T, Szcześniak M, Kardel I, Michałowski R, Okruszko T, Mezghani A, Piniewski M (2016) CPLFD-GDPT5: high-resolution gridded daily precipitation and temperature data set for two largest Polish river basins. 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Turk J Earth Sci 23:462–474. https:\u002F\u002Fdoi.org\u002F10.3906\u002Fyer-1302-6\nRoad, Housing and Urban Development Research Center (2012) Iran strong motion network. http:\u002F\u002Fwww.bhrc.ac.ir\u002F\nSadigh K, Chang CY, Egan JA, Makdisi F, Youngs RR (1997) Attenuation relationships for shallow crustal earthquakes based on California strong motion data. Seismol Res Lett 68(1):180–189\nShoushtari AV, Adnan AB, Zare M (2016) On the selection of ground–motion attenuation relations for seismic hazard assessment of the Peninsular Malaysia region due to distant Sumatran subduction intraslab earthquakes. Soil Dyn Earthq Eng 82:123–137. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.soildyn.2015.11.012\nSugeno M (1985) Industrial applications of fuzzy control. Elsevier Science Pub. Co, New York\nSun SS, Sung DC, Yong RK (2002) Empirical evaluation of a fuzzy logic-based software quality prediction model. http:\u002F\u002Fdl.acm.org\u002Fcitation.cfm?id=765833. Retrieved on 15\u002F05\u002F2016\nThomas S, Pillai GN, Pal K, Jagtap P (2016) Prediction of ground motion parameters using randomized ANFIS (RANFIS). Appl Soft Comput 40:624–634. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asoc.2015.12.013\nTsiftzis I, Andreadis I, Elenas A (2006) Fuzzy system for seismic signal classification. IEE Proc Vis Image Signal Process 153(2):109–114. https:\u002F\u002Fdoi.org\u002F10.1049\u002Fip-vis:20050068\nWadia-fascetti S, Gunes B (2000) Earthquake response spectra models incorporating fuzzy logic with statistics. Comput Aided Civ Infrastruct Eng 15(2):134–146. https:\u002F\u002Fdoi.org\u002F10.1111\u002F0885-9507.00178\nZadeh LA (1965) Fuzzy sets. Inf Control 8:338–353\nZare M, Sabzali S (2006) Spectral attenuation of strong motions in Iran. In: Third international symposium on the effects of surface geology on seismic motion grenoble, France",{"EN":547},"In this study, fuzzy logic modeling is applied to a complex and nonlinear set of data to predict both horizontal and vertical peak ground accelerations in Iranian plateau. The data used for the model include an up-to-date seismic catalogue from earthquakes in Iran for prediction of both horizontal and vertical acceleration of a probable earthquake. Fuzzy logic toolbox on MATLAB program was used for modeling. Earthquake magnitude ranging from 4 to 7.4, source-to-site distance from 7 to 80 km and three different site conditions were considered: rock, stiff soil and soft soil. Results are compared with those from worldwide and regional attenuation relationships, which show the higher capability of the model in comparison with the other models. After training the model, testing of the fuzzy model with the remaining data set was performed to confirm the accuracy of the model. Changes in the peak ground accelerations in connection with changes in input parameters are studied which are in agreement with basic characteristics of earthquake input motions.",{"EN":549},"Peak ground acceleration prediction by fuzzy logic modeling for Iranian plateau",{"VOID":551},"10.1007\u002Fs11600-019-00394-z","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11600-019-00394-z",[554,569],{"id":555,"sortIndex":196,"researcher":20,"roles":556,"affiliations":557,"properties":566},"b985587a-7365-40e7-abfb-d83ea3f8b6c6",[198],[558],{"id":20,"sortIndex":21,"affiliation":559,"properties":20},{"id":560,"createTime":561,"updateTime":561,"relativeEntities":562,"slug":20,"properties":563,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"785b5584-f3da-406f-8c15-c139d5506862","2024-01-09T05:37:59.489+00:00",[],{"title":564},{"VI":565},"CSU Engineering, Faculty of Business, Justice and Behavioral Sciences, Charles Sturt University, Bathurst, Australia",{"title":567},{"VI":568},"Reza Mahinroosta",{"id":570,"sortIndex":21,"researcher":20,"roles":571,"affiliations":572,"properties":581},"f5a2864a-10cb-47e4-8c93-f58cb4c26bc9",[198],[573],{"id":20,"sortIndex":21,"affiliation":574,"properties":20},{"id":575,"createTime":576,"updateTime":576,"relativeEntities":577,"slug":20,"properties":578,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"9dd5a407-ceeb-416b-9938-dd821541dddc","2024-01-09T05:37:59.477+00:00",[],{"title":579},{"VI":580},"Civil Engineering Department, Erzurum Technical University, Erzurum, Turkey",{"title":582},{"VI":583},"Babak Karimi Ghalehjough",{"url":552,"publisher":585,"properties":613},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":586,"slug":10,"properties":587,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":591,"manageAffiliations":592,"indexDatabases":593,"url":95,"thumbnailPath":20,"statistic":608,"gsStatistic":20,"type":169,"analyzePriority":20},[],{"issn":588,"eissn":589,"title":590},{"VOID":13},{"VOID":15},{"EN":17},[],[],[594,601],{"id":77,"indexDatabase":595,"url":90,"indexYears":91,"academicFieldIds":600,"indexDatabaseRanking":94},{"id":79,"createTime":80,"updateTime":81,"relativeEntities":596,"label":597,"description":598,"key":87,"publicationTags":599,"standard":20},[],{"EN":84,"VI":84},{"EN":84,"VI":86},[89],[93],{"id":58,"indexDatabase":602,"url":73,"indexYears":20,"academicFieldIds":607,"indexDatabaseRanking":20},{"id":60,"createTime":61,"updateTime":62,"relativeEntities":603,"label":604,"description":605,"key":69,"publicationTags":606,"standard":20},[],{"EN":65,"VI":65},{"VI":67,"EN":68},[71,72],[75],{"impactFactor":21,"impactFactorByYear":609,"i10Index":109,"i10IndexLast5Year":110,"totalPublication":111,"totalPublicationByYear":610,"totalCitation":132,"totalCitationByYear":611,"totalCitationPerPublication":148,"totalCitationPerPublicationByYear":612,"hindexLast5Year":168,"hindex":168},{"2012":98,"2013":99,"2014":100,"2015":101,"2016":102,"2017":103,"2018":104,"2019":101,"2020":105,"2021":106,"2022":107,"2023":108},{"2006":113,"2007":114,"2008":115,"2009":116,"2010":117,"2011":118,"2012":119,"2013":120,"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":130,"2024":131},{"2006":134,"2007":135,"2008":136,"2009":136,"2010":120,"2011":137,"2012":138,"2013":139,"2014":115,"2015":140,"2016":141,"2017":136,"2018":142,"2019":143,"2020":144,"2021":145,"2022":146,"2023":147},{"2006":150,"2007":151,"2008":152,"2009":153,"2010":154,"2011":155,"2012":156,"2013":157,"2014":158,"2015":159,"2016":160,"2017":161,"2018":162,"2019":163,"2020":164,"2021":165,"2022":166,"2023":167},{"volume":614,"pages":616},{"VOID":615},"68",{"VOID":617},"75-89","2019-12-16",2019,{"id":621,"createTime":622,"updateTime":623,"relativeEntities":624,"slug":625,"properties":626,"entityType":189,"verifyStatus":190,"verifyTime":635,"verifyNote":191,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":636,"fullTextUrl":20,"authors":637,"publicationType":225,"publisherRelationship":743,"citationCount":20,"citationInfo":20,"publishDate":777,"publishYear":261,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":262},"9cf61ce6-3860-4de1-b545-8d00ba8f7980","2023-12-31T12:06:24.499+00:00","2025-02-26T23:55:33.937+00:00",[],"Group-method-of-data-handling-to-forecast-the-daily-water-flow-at-the-Cahora-Bassa-Dam",{"references":627,"abstract":629,"title":631,"doi":633},{"VOID":628},"Abdullah S, Ismail M, Fong SY (2017) Multiple linear regression (MLR) models for long term pm10 concentration forecasting during different monsoon seasons. J Sustain Sci Manag 12(1):60–69\nAlmeida L, Serra JCV (2017) Modelos hidrológicos, tipos e aplicações mais utilizadas. Revista da FAE 20(1):129–137\nBox GE, Jenkins GM, Reinsel GC et al (2015) Time series analysis: forecasting and control. John Wiley & Sons, New Jersey\nChong XY, Vericat D, Batalla RJ et al (2021) A review of the impacts of dams on the hydromorphology of tropical rivers. Sci Total Environ 794:148686\nEbtehaj I, Sammen SS, Sidek LM et al (2021) Prediction of daily water level using new hybridized GS-GMDH and ANFIS-FCM models. Eng Appl Comput Fluid Mech 15(1):1343–1361\nEivani Z, Ahmadi MM, Qaderi K (2016) Estimation of suspended sediment load concentration in river system using Group Method of Data Handling (GMDH). J Watershed Manag Res 7(13):218–229\nEkandjo M, Makurira H, Mwelwa E et al (2018) Impacts of hydropower dam operations in the Mana Pools national park floodplains. Phys Chem Earth Parts A B C 106:11–16\nElkurdy M, Binns AD, Bonakdari H et al (2021) Early detection of riverine flooding events using the group method of data handling for the Bow river, Alberta, Canada. Int J River Basin Manag 29:1–12\nFarlow SJ (1981) The GMDH algorithm of Ivakhnenko. Am Stat 35(4):210–215\nGarzanti E, Bayon G, Dinis P et al (2022) The segmented Zambezi sedimentary system from source to sink: 2. Geochemistry, clay minerals, and detrital geochronology. J Geol 130:171–208\nGilvear DJ, Spray CJ, Casas-Mulet R (2013) River rehabilitation for the delivery of multiple ecosystem services at the river network scale. J Environ Manag 126:30–43\nGoliatt L, Sulaiman SO, Khedher KM et al (2021) Estimation of natural streams longitudinal dispersion coefficient using hybrid evolutionary machine learning model. Eng Appl Comput Fluid Mech 15(1):1298–1320\nHughes D, Mantel S, Farinosi F (2020) Assessing development and climate variability impacts on water resources in the Zambezi river basin: initial model calibration, uncertainty issues and performance. J Hydrol Reg Stud 32(100):765\nHulsman P, Savenije HH, Hrachowitz M (2021) Satellite-based drought analysis in the Zambezi river basin: was the 2019 drought the most extreme in several decades as locally perceived? J Hydrol Reg Stud 34(100):789\nHussain D, Khan AA (2020) Machine learning techniques for monthly river flow forecasting of Hunza river, Pakistan. Earth Sci Inform 13(3):939–949\nIkeda S, Ochiai M, Sawaragi Y (1976) Sequential GMDH algorithm and its application to river flow prediction. IEEE Trans Syst Man Cybern 7:473–479\nIsaacman A (2021) Cahora Bassa dam & the delusion of development. Dædalus 150(4):103–123\nIvakhnenko AG (1971) Polynomial theory of complex systems. IEEE Trans Syst Man Cybern 4:364–378\nJensen KM, Lange RB (2013) The Zambezi. https:\u002F\u002Fwww.jstor.org\u002Fstable\u002Fresrep13303.10?seq=2. Accessed 12 Apr 2021\nKling H, Stanzel P, Preishuber M (2014) Impact modelling of water resources development and climate scenarios on Zambezi river discharge. J Hydrol Reg Stud 1:17–43\nKondo T (1998) The learning algorithms of the GMDH neural network and their application to the medical image recognition. In: Proceedings of the 37th SICE Annual Conference. International Session Papers, IEEE, pp 1109–1114\nKunz MJ (2011) Effect of large dams in the Zambezi river basin: changes in sediment, carbon and nutrient fluxes. PhD thesis, ETH Zurich\nLi RYM, Fong S, Chong KWS (2017) Forecasting the reits and stock indices: group method of data handling neural network approach. Pac Rim Prop Res J 23(2):123–160\nLiu Z, Zhou P, Chen X et al (2015) A multivariate conditional model for streamflow prediction and spatial precipitation refinement. J Geophys Res Atmos 120(19):10–116\nLundberg SM, Lee SI (2017) A unified approach to interpreting model predictions. In: Proceedings of the 31st international conference on neural information processing systems, pp. 4768–4777\nManjoro A, Ferreira PA (2016) Desafios de Moçambique após os ciclones IDAI e Kenneth. Estratégia 465\nManyari WV (2007) Impactos ambientais a jusante de hidrelétricas: o caso da usina de Tucuruí-PA. Master’s thesis, Universidade Federal do Rio de Janeiro, Rio de Janeiro\nMartinho AD, Ribeiro CB, Gorodetskaya Y et al (2020) Extreme learning machine with evolutionary parameter tuning applied to forecast the daily natural flow at Cahora Bassa dam, Mozambique. In: International Conference on Bioinspired Methods and Their Applications. Springer, pp 255–267\nMoosavi V, Talebi A, Hadian MR (2017) Development of a hybrid wavelet packet-group method of data handling (WPGMDH) model for runoff forecasting. Water Resour Manag 31(1):43–59\nMuzzammil M, Alam J, Zakwan M (2015) An optimization technique for estimation of rating curve parameters. In: National Symposium on Hydrology\nNishikawa T, Shimizu S (1982) Identification and forecasting in management systems using the GMDH method. Appl Math Model 6(1):7–15\nOnwubolu GC (2016) GMDH-methodology and implementation in MATLAB. World Scientific\nParsaie A, Azamathulla HM, Haghiabi AH (2020) Physical and numerical modeling of performance of detention dams. J Hydrol 581(121):757\nRajaee T, Jafari H (2020) Two decades on the artificial intelligence models advancement for modeling river sediment concentration: state-of-the-art. J Hydrol 588(125):011\nRibeiro LS, Wilhelm VE, Faria ÉF et al (2019) A comparative analysis of long-term concrete deformation models of a buttress dam. Eng Struct 193:301–307\nRonco P, Fasolato G, Nones M et al (2010) Morphological effects of damming on lower Zambezi river. Geomorphology 115(1–2):43–55\nRonco P, Fasolato D, Di-Silvio G (2006) The case of the Zambezi river in Mozambique: Some investigations on solid transport phenomena downstream Cahora Bassa dam. Proceedings of the International Conference on Fluvial Hydraulogy: Lisbon, Portugal (Taylor & Francis)\nShaofu M, Al-Juboori AM, Alwan AH, et al (2021) On the investigation of monthly river flow generation complexity using the applicability of machine learning models. Complexity 2021\nTeutschbein C, Grabs T, Laudon H et al (2018) Simulating streamflow in ungauged basins under a changing climate: the importance of landscape characteristics. J Hydrol 561:160–178\nTikhamarine Y, Souag-Gamane D, Ahmed AN et al (2020) Improving artificial intelligence models accuracy for monthly streamflow forecasting using grey wolf optimization (GWO) algorithm. J Hydrol 582(124):435\nVörösmarty CJ, Meybeck M, Fekete B et al (2003) Anthropogenic sediment retention: major global impact from registered river impoundments. Global and planetary change 39(1–2):169–190\nWang WC, Chau KW, Cheng CT et al (2009) A comparison of performance of several artificial intelligence methods for forecasting monthly discharge time series. J hydrol 374(3–4):294–306\nWilk P (2022) Expanding the sediment transport tracking possibilities in a river basin through the development of a digital Platform-DNS\u002FSWAT. Appl Sci 12(8):3848\nYonesi HA, Parsaie A, Arshia A et al (2022) Discharge modeling in compound channels with non-prismatic floodplains using GMDH and MARS models. Water Supply 22:4400–21\nZhang XY, Trame MN, Lesko LJ et al (2015) Sobol sensitivity analysis: a tool to guide the development and evaluation of systems pharmacology models. CPT Pharmacomet Syst Pharmacol 4(2):69–79",{"EN":630},"The Zambezi watershed is essential for water supply, irrigation, fishing activities, and river transport of the populations of Southern Africa. The importance and variability of these water resources make it necessary to develop studies that may help understand and manage them. Despite this need, water resources studies for this region are still scarce. Therefore, the present work aims to present a strategy for forecasting the daily water flow of the Zambezi River in the Cahora Bassa dam, located in Mozambique, an important energy producer in the country and the fourth largest dam in Africa. Historical rainfall, evaporation, and humidity records collected from 2003 to 2011 are used for training and testing a model that forecasts water flow using the Group Method of Data Handling algorithm. The results achieved were compared, through error metrics, with those of other models to prove the effectiveness of the assembled model. They revealed that the proposed model achieves a satisfactory performance for the forecast horizon and could become a helpful tool in monitoring hydrographic basins and forecasting their daily streamflow values.",{"EN":632},"Group method of data handling to forecast the daily water flow at the Cahora Bassa Dam",{"VOID":634},"10.1007\u002Fs11600-022-00834-3","2025-02-26T23:55:33.936+00:00","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11600-022-00834-3",[638,653,683,702,724],{"id":639,"sortIndex":343,"researcher":20,"roles":640,"affiliations":641,"properties":650},"5dfdaa0a-c322-40a7-af95-e3b1fd2a606e",[198],[642],{"id":20,"sortIndex":21,"affiliation":643,"properties":20},{"id":644,"createTime":645,"updateTime":645,"relativeEntities":646,"slug":20,"properties":647,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"c23e7e6d-784e-4e99-bdcf-339b2807b24c","2023-12-31T12:06:24.563+00:00",[],{"title":648},{"VI":649},"Department of Production Engineering, Fluminense Federal University, Volta Redonda, Rio de Janeiro, Brazil",{"title":651},{"VI":652},"Eliane da S. 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Acta Geophys 63:1150–1180. https:\u002F\u002Fdoi.org\u002F10.1515\u002Facgeo-2015-0020\nAframovich EL, Astafieva EI, Gokhberg MB, Lapshin VM, Permyakova VE, Steblov GM, Shalimov SL (2004) Variations of the total electron content in the ionosphere from GPS data recorded during the hector mine earthquake of October 16, 1999. Calif Rus J Earth Sci 6(5):339–354. https:\u002F\u002Fdoi.org\u002F10.2205\u002F2004ES000155\nAnonymous: https:\u002F\u002Fwww.volcanodiscovery.com\u002Fhome.html\nAnonymous: https:\u002F\u002Fearthquake.usgs.gov\u002Fearthquakes\u002Feventpage\u002Fusp000cdb4\u002Fshakemap\u002Fintensity\nAnsari K, Corumluoglu O, Panda SK (2017) Analysis of ionospheric TEC from GNSS observables over the Turkish region and predictability of IRI and SPIM models. Astrophys Space Sci 362:65. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10509-017-3043-x\nAnsari K, Corumluoglu O, Verma P (2018) The triangulated affine transformation parameters and barycentric coordinates of Turkish permanent GPS network. Surv Rev 50(362):412–415. https:\u002F\u002Fdoi.org\u002F10.1080\u002F00396265.2017.1297016\nBagiya MS, Joshi HP, Iyer KN, Aggarwal M, Ravindran S, Pathan BM (2009) TEC variations during low solar activity period (2005–2007) near the equatorial ionospheric anomaly crest region in India. Ann Geophys 27:1047–1057. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fangeo-27-1047-2009\nBasciftci F (2021) An analysis of the latest super geomagnetic storm of the 23RD solar cycle (May 15, 2005, Dst: –247 nT). Geomagn Aeron 61:S156–S166. https:\u002F\u002Fdoi.org\u002F10.1134\u002FS0016793222010029\nBasciftci F (2022) Investigating and comparing the two superstorms in the 23rd solar cycle. Indian J Phys 96(10):2707–2716. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12648-022-02396-y\nBasciftci F, Inal C, Yildirim O, Bulbul S (2018) Comparison of regional and global TEC values: Turkey model. Int J Eng Geosci 3(2):61–72. https:\u002F\u002Fdoi.org\u002F10.26833\u002Fijeg.382604\nBasciftci F, Bulbul S (2022) Investigation of ionospheric TEC changes potentially related to Seferihisar–Izmir earthquake (30 October 2020, MW 6.6). Bull Geophys Oceanogr 63(3):403–426. https:\u002F\u002Fdoi.org\u002F10.4430\u002Fbgo00394\nBasu S, Basu Su, Rich FJ, Groves KM, MacKenzie E, Coker C, Sahai Y, Fagundes PR, Becker-Guedes F (2007) Response of the equatorial ionosphere at dusk to penetration electric fields during intense magnetic storms. J Geophys Res 112:A08308. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2006JA012192\nBilitza D (2001) International reference ionosphere 2000. Radio Sci 36(2):261–275. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2000RS002432\nBulbul S, Basciftci F (2021) TEC anomalies observed before and after Sivrice-Elaziğ earthquake (24 January 2020, Mw: 6.8). Arab J Geosci 14:1077. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs12517-021-07426-3\nChukwuma VU, Adekoya BJ, Thomas JE et al (2021) On the significance of requisite criteria in detecting pre-earthquake ionospheric precursors: a case study of the Tohoku earthquake of March 11, 2011. Acta Geophys 69:1545–1566. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11600-021-00627-0\nDautermann T, Calais E, Lognonné P, Mattioli GS (2009) Lithosphere-atmosphere-ionosphere coupling after the 2003 explosive eruption of the soufriere hills volcano, montserrat. Geophys J Int 179:1537–1546\nDavies K, Baker DM (1965) Ionospheric effects observed around time of Alaskan earthquake of March 28 1964. J Geophys Res 70:2251–2253\nDebnath L, Bahatta D (2007) Integral transforms and their applications, 2nd edn, Taylor and Francis LLC\nEroglu E (2018) Mathematical modeling of the moderate storm on 28 February 2008. New Astron 60:33–41. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.newast.2017.10.002\nEroglu E (2022) Discussing total electron content over the solar wind parameters. Math Probl Eng. https:\u002F\u002Fdoi.org\u002F10.1155\u002F2022\u002F9592008\nFreund FT (2011) Pre-earthquake signals: underlying physical processes. J Asian Earth Sci 41:383–400\nFreund FT, Takeuchi A, Lau BW (2006) Electric currents streaming out of stressed igneous rocks–a step towards understanding pre-earthquake low frequency EM emissions. Phys Chem Earth 31:389–396\nFreund FT, Kulahci IG, Cyr G, Ling J, Winnick M, Tregloan-Reed J, Freund MM (2009) Air ionization at rock surfaces and pre-earthquake signals. J Atmos Sol Terr Phy 71:1824–1834\nFuying Z, Yun W, Ningbo F (2011) Application of kalman filter in detecting pre-earthquake ionospheric TEC anomaly. Geodesy Geodyn 2:43–47\nGonzales CA, Kelley MC, Behnke RA, Vickrey JF, Wand R, Holt J (1983) On the latitudinal variations of the ionospheric electric field during magnetospheric disturbances. J Geophys Res Space Phys 88(A11):9135–9144. https:\u002F\u002Fdoi.org\u002F10.1029\u002FJA088iA11p09135\nHabarulema JB, McKinnell LA, Opperman BDL (2009) A recurrent neural network approach to quantitatively studying solar wind effects on TEC derived from GPS; preliminary results. Ann Geophys 27:2111–2125\nInyurt S, Razin MRG (2021) Regional application of ANFIS in ionosphere time series prediction at severe solar activity period. Acta Astronaut 179:450–461. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.actaastro.2020.11.027\nInyurt S, Yildirim O, Mekik C (2017) Comparison between IRI-2012 and GPS-TEC observations over the western black sea. Ann Geophys 35(4):817–824\nKe F, Wang J, Tu M, Wang X, Wang X, Zhao X, Deng J (2018) Enhancing reliability of seismo-ionospheric anomaly detection with the linear correlation between total electron content and the solar activity index F10.7: Nepal earthquake 2015. J Geodyn 121:88–95\nKim VP, Liu JY, Hegal VV (2012) Modeling the pre-earthquake electrostatic effect on the F region ionosphere. Adv Space Res 50:1524–1533. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2012.07.023\nKlotz S, Johnson NL (1983) Encyclopedia of statistical sciences. Wiley, New York\nKoklu K (2021) Mathematical analysis of the 08 May 2014 weak storm. Math Probl Eng. https:\u002F\u002Fdoi.org\u002F10.1155\u002F2021\u002F9948745\nKoklu K (2022) Using artificial neural networks for comparison of the 09 March 2012 intense and 08 May 2014 weak storms. Adv Space Res. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2022.07.067\nLeonard RS, Barnes RA (1965) Observation of ionospheric disturbances following Alaska earthquake. J Geophys Res 70:1250–1253\nLin CC, Shen MH, Chou MY, Chen CH, Yue J, Chen PC, Matsumura M (2017) Concentric traveling ionospheric disturbances triggered by the launch of a spacex falcon 9 rocket. Geophys Res Lett 44:7578–7586\nLiperovsky VA, Pokhotelov OA, Liperovskaya EV, Parrot M, Meister CV, Alimov OA (2000) Modification of sporadic E-layers caused by seismic activity. Surv Geophys 21:449–486. https:\u002F\u002Fdoi.org\u002F10.1023\u002FA:1006711603561\nLiu JY, Chuo YJ, Shan SJ, Tsaı YB, Chen YI, Pulınets SA, Yu SB (2004) Pre-earthquake ionospheric anomalies registered by continuous GPS TEC measurements. Ann Geophys 22(5):1585–1593. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fangeo-22-1585-2004\nLiu JY, Chen YI, Chen CH, Hattori K (2010) Temporal and spatial precursors in the ionospheric global positioning system (GPS) total electron content observed before the 26 december 2004 M9.3 Sumatra-Andaman earthquake. J Geophys Res 115:A09312. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2010JA015313\nLu G, Goncharenko L, Nicolls MJ, Maute A, Coster A, Paxton LJ (2012) Ionospheric and thermospheric variations associated with prompt penetration electric fields. J Geophys Res 117:A08312. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2012JA017769\nMannucci AJ, Tsurutani BT, Kelley MC, Iijima BA, Komjathy A (2009) Local time dependence of the prompt ionospheric response for the 7, 9, and 10 November 2004 superstorms. J Geophys Res 114:A10308. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2009JA014043\nManoj C, Maus S (2012) A real-time forecast service for the ionospheric equatorial zonal electric field. Space Weather 10:1–9\nManoj C, Maus S, Lühr H, Alken P (2008) Penetration characteristics of the interplanetary electric field to the daytime equatorial ionosphere. J Geophys Res 113:A12310. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2008JA013381\nMelgarejo-Morales A, Vazquez-Becerra GE, Millan-Almaraz JR et al (2020) Examination of seismo-ionospheric anomalies before earthquakes of Mw ≥ 5.1 for the period 2008–2015 in Oaxaca, Mexico Using GPS-TEC. Acta Geophys 68:1229–1244. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11600-020-00470-9\nPulinets SA, Ouzounov D, Karelin AV, Boyarchuk KA, Pokhmelnykh LA (2006) The physical nature of thermal anomalies observed before strong earthquakes. Phys Chem Earth 31:43–153\nSaqib M, Şentürk E, Sahu SA et al (2021) Ionospheric anomalies detection using autoregressive integrated moving average (ARIMA) model as an earthquake precursor. Acta Geophys 69:1493–1507. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11600-021-00616-3\nSchaer S, Gurtner W, Feltens J (1998) IONEX: The ionosphere map exchange format version 1. In: Proceedings of the 1998 IGS analysis centers workshop, ESOC. Darmstadt, Germany. pp 233–247\nSchaer S (1999) Mapping and predicting the earth’s ionosphere using the global positioning system, Ph.D Thesis, Universitat Bern, Switzerland\nSenturk E, Cepni MSA (2018) Statistical analysis of seismo-ionospheric TEC anomalies before 63 Mw ≥ 5.0 earthquakes in Turkey during 2003–2016. Acta Geophys 66:1495–1507. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11600-018-0214-2\nSenturk E, Livaoglu H, Cepni MS (2019) A comprehensive analysis of ionospheric anomalies before the Mw7.1 van earthquake on 23 October 2011. J Navigation 72:702–720\nSenturk E, Inyurt S, Sertcelik I (2020) Ionospheric anomalies associated with the Mw 7.3 Iran-Iraq border earthquake and a moderate magnetic storm. Ann Geophys 38:1031–1043. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fangeo-38-1031-2020\nTariq MA, Shah M, Hernández-Pajares M, Iqbal T (2019) Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015–2017. Adv Space Res 63(7):2088–2099. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.asr.2018.12.028\nThemens DR, Jayachandran PT (2016) Solar activity variability in the IRI at high latitudes: comparisons with GPS total electron content. J Geophys Res Space Phys 121(4):793–3807\nToutain JP, Baubron JC (1998) Gas geochemistry and seismotectonics: a review. Tectonophysics 304:1–27\nTsurutani BT, Verkhoglyadova OP, Mannucci AJ, Saito A, Araki T, Yumoto K, Tsuda T, Abdu MA, Sobral JHA, Gonzalez WD, McCreadie H, Lakhina GS, Vasyliūnas VM (2008) Prompt penetration electric fields (PPEFs) and their ionospheric effects during the great magnetic storm of 30–31 October 2003. J Geophys Res 113:A05311. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2007JA012879\nUlukavak M (2021) Deep learning for ionospheric TEC forecasting at mid-latitude stations in Turkey. Acta Geophys 69:589–606. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11600-021-00568-8\nUlukavak M, Yalcinkaya M (2017) Precursor analysis of ionospheric GPS-TEC variations before the 2010 M7.2 Baja California earthquake. Geomat Nat Haz Risk 8(2):295–308. https:\u002F\u002Fdoi.org\u002F10.1080\u002F19475705.2016.1208684\nVaishnav R, Jacobi C, Berdermann J (2019) Long-term trends in the ionospheric response to solar extreme-ultraviolet variations. Ann Geophys 37:1141–1159. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fangeo-37-1141-2019\nYildirim O, Inyurt S, Mekik C (2016) Review of variations in Mw\u003C7 earthquake motions on position and TEC (Mw=6.5 Aegean Sea earthquake sample). Nat Hazards Earth Syst Sci 16:543–557. https:\u002F\u002Fdoi.org\u002F10.5194\u002Fnhess-16-543-2016",{"EN":788},"Models belonging to the ionosphere that is directly affected by factors such as solar activity, geomagnetic storm, earthquake, seasonal changes, and geographical location need to be considered altogether. In this sense, the cause of the ionospheric anomalies should be meticulously distinguished from each other. Ionospheric anomalies that occur before or (and) after an earthquake have a serious place in earthquake prediction studies. Total electron content (TEC) is one of the significant parameters to be able to discuss the anomalies of the ionosphere. This essay investigates ionospheric anomalies before and after the Mw 6.5 Samar, Philippines (12.025° N, 125.416° E and November 18, 2003, at 17:14 UT) earthquake. The paper analyzes anomalies with the aid of the TEC (TECU) map. In the paper, the time-domain TEC variables are transferred to the frequency-domain for observing some clues-peaks by short-term Fourier transformation spectral analysis. The discussion handles the effect of the solar activity with the F10.7 (sfu) index and the effect of geomagnetic storms with Bz (nT), v (km\u002Fs), P (nPa), E (mV\u002Fm), Kp (nT), and Dst (nT) parameters (index). The lower and upper boundaries of the TEC map obtained from the International Reference Ionosphere (IRI-2016) are calculated with the help of median and standard deviation. The boundary-setting process is named statistical analysis. TEC data exceeding the boundaries are marked as anomaly data. According to the paper, 11-day anomalies (9-day of which belong to pre-earthquake) are detected. Probably, the anomalies observed on November 6, 7, and 12 belong to the Samar earthquake.",{"EN":790},"Ionospheric anomalies related to the Mw 6.5 Samar, Philippines earthquake",{"VOID":792},"10.1007\u002Fs11600-022-00980-8","https:\u002F\u002Flink.springer.com\u002F10.1007\u002Fs11600-022-00980-8",[795],{"id":796,"sortIndex":21,"researcher":20,"roles":797,"affiliations":798,"properties":807},"06f0bcc7-6b1f-40ce-9781-56f3cde9c0f5",[198],[799],{"id":20,"sortIndex":21,"affiliation":800,"properties":20},{"id":801,"createTime":802,"updateTime":802,"relativeEntities":803,"slug":20,"properties":804,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"61207294-3619-49fc-9be4-fdfc709c92b4","2023-12-17T18:04:00.856+00:00",[],{"title":805},{"VI":806},"Department of Mathematics, Kirklareli University, Kirklareli, Turkey",{"title":808},{"VI":809},"Emre Eroglu",{"url":793,"publisher":811,"properties":839},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":812,"slug":10,"properties":813,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":817,"manageAffiliations":818,"indexDatabases":819,"url":95,"thumbnailPath":20,"statistic":834,"gsStatistic":20,"type":169,"analyzePriority":20},[],{"issn":814,"eissn":815,"title":816},{"VOID":13},{"VOID":15},{"EN":17},[],[],[820,827],{"id":77,"indexDatabase":821,"url":90,"indexYears":91,"academicFieldIds":826,"indexDatabaseRanking":94},{"id":79,"createTime":80,"updateTime":81,"relativeEntities":822,"label":823,"description":824,"key":87,"publicationTags":825,"standard":20},[],{"EN":84,"VI":84},{"EN":84,"VI":86},[89],[93],{"id":58,"indexDatabase":828,"url":73,"indexYears":20,"academicFieldIds":833,"indexDatabaseRanking":20},{"id":60,"createTime":61,"updateTime":62,"relativeEntities":829,"label":830,"description":831,"key":69,"publicationTags":832,"standard":20},[],{"EN":65,"VI":65},{"VI":67,"EN":68},[71,72],[75],{"impactFactor":21,"impactFactorByYear":835,"i10Index":109,"i10IndexLast5Year":110,"totalPublication":111,"totalPublicationByYear":836,"totalCitation":132,"totalCitationByYear":837,"totalCitationPerPublication":148,"totalCitationPerPublicationByYear":838,"hindexLast5Year":168,"hindex":168},{"2012":98,"2013":99,"2014":100,"2015":101,"2016":102,"2017":103,"2018":104,"2019":101,"2020":105,"2021":106,"2022":107,"2023":108},{"2006":113,"2007":114,"2008":115,"2009":116,"2010":117,"2011":118,"2012":119,"2013":120,"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":130,"2024":131},{"2006":134,"2007":135,"2008":136,"2009":136,"2010":120,"2011":137,"2012":138,"2013":139,"2014":115,"2015":140,"2016":141,"2017":136,"2018":142,"2019":143,"2020":144,"2021":145,"2022":146,"2023":147},{"2006":150,"2007":151,"2008":152,"2009":153,"2010":154,"2011":155,"2012":156,"2013":157,"2014":158,"2015":159,"2016":160,"2017":161,"2018":162,"2019":163,"2020":164,"2021":165,"2022":166,"2023":167},{"volume":840,"pages":841},{"VOID":257},{"VOID":842},"601-611","2022-12-13",{"id":845,"createTime":846,"updateTime":847,"relativeEntities":848,"slug":849,"properties":850,"entityType":189,"verifyStatus":190,"verifyTime":847,"verifyNote":191,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":861,"fullTextUrl":20,"authors":862,"publicationType":225,"publisherRelationship":903,"citationCount":20,"citationInfo":20,"publishDate":932,"publishYear":619,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":262},"37dc980e-03e6-4912-9c1b-6f18a39c3120","2024-04-06T02:19:45.605+00:00","2025-01-15T23:53:52.809+00:00",[],"Relative-amplitude-preservation-in-high-resolution-shallow-reflection-seismic-a-case-study-from-Fore-Sudetic-Monocline-Poland",{"references":851,"keywords":853,"abstract":855,"title":857,"doi":859},{"VOID":852},"Aki K, Richards PG (2002) Quantitative seismology. W.H. Freeman and Company, New York\nAtanackov J, Gosar A (2013) Field comparison of seismic sources for high resolution shallow seismic reflection profiling on the Ljubljana moor (central Slovenia). Acta Geodyn et Geomater 10(1):19–40\nBaumgart-Kotarba M, Dec J, Ślusarczyk R (2001) Quaternary tectonic grabens of Wróblówka and Piniążkowice and their relation to Neogene strata of the Orava Basin and Pliocene sediments of Domański Wierch series in Podhale, Polish West Carpathians. Studia Geomorfolo Carpatho-Balcanica XXXV:101–119\nBaumgart-Kotarba M, Dec J, Kotarba A, Ślusarczyk R (2008) Glacial trough and sediments infill of the Biała Woda Valley (the High Tatra mountains) using geophysical and geomorphological methods. Studia Geomorphol Carpatho-Balcanica XLII:75–108\nBenjumea B, Teixido T (2001) Seismic reflection constraints on the glacial dynamics of Johnsons Glacier. Antarct J Appl Geophys 46:31–44\nBerkhout AJ (1985) Seismic resolution: a key to detailed geologic information. World Oil 201:47–51\nButler P (2012) White noise suppression in the time domain. CSEG Rec 37(9):39–44\nCambois G (2001) AVO processing: myths and reality. CSEG Rec 26:30–33\nCary PW, Lorentz GA (1993) Four-component surface-consistent deconvolution. Geophysics 58:383–392\nChopra S, Castagna JP (2014) AVO. Investigations in geophysics. Society of Exploration Geophysics, Tulsa\nDec J (2012) High-resolution seismic survey for recognition of the Osiek sulphur deposits and determination of dynamic changes resulting from exploitation. Wydawnictwa AGH, Kraków [in Polish with English abstract]\nDec J, Cichostępski K (2017a) Evaluation of sulphur deposit properties on the basis of geomechanical parameters. Zeszyty Naukowe Instytutu Gospodarki Surowcami Mineralnymi i Energią PAN 101:203–216 [in Polish with English abstract]\nDec J, Cichostępski K (2017b) Estimation of sulphur deposit resources on the basis of seismic data. Zeszyty Naukowe Instytutu Gospodarki Surowcami Mineralnymi i Energią PAN 101:217–227 [in Polish with English abstract]\nFrancese RG, Hajnal Z, Schmitt D, Zaja A (2007) High resolution seismic reflection imaging of complex stratigraphic features in shallow aquifers. Memorie Descriptive della Carta Geologica d’Italia LXXVI:175–192\nGisco (2018) Documentation of Gisco vertical geophones. http:\u002F\u002Fwww.giscogeo.com\u002Fproducts-equipment\u002Fgeophones. Accessed 31 July 2018\nKłapciński J, Peryt TM (2007) Budowa geologiczna monokliny przedsudeckiej. Monografia KGHM Polska Miedź SA 69–77\nKłapciński J, Konstantynowicz E, Salski W, Kenig E, Preidl M, Dubińsdki K, Drozdowski S (1984) Atlas obszaru miedzionośnego (monoklina przedsudecka). Wydawnictwo Śląsk, Katowice\nKnapp RW, Steeples DW (1986a) High-resolution common-depth-point seismic reflection profiling: instrumentation. Geophysics 51(2):276–282\nKnapp RW, Steeples DW (1986b) High-resolution common-depth-point reflection profiling: field acquisition parameter design. Geophysics 51(2):283–294\nKwietniak A, Cichostępski K, Pietsch K (2018) Resolution enhancement with relative amplitude preservation for unconventional targets. Interpretation 6(3):SH59–SH71\nMiller RD, Pullan SE, Waldner JS, Haeni FP (1986) Field comparison of shallow seismic sources. Geophysics 51(2):2067–2092\nMiller RD, Steeples DW, Brannan M (1989) Mapping a bedrock surface under dry alluvium with shallow seismic reflections. Geophysics 27:1528–1534\nMiller RD, Steeples DW, Myers PB (1990) Shallow seismic reflection survey across the Meers fault, Oklahoma. Bull Geol Soc Am 102:18–25\nMiller RD, Pullan SE, Steeples DW, Hunter JA (1992) Field comparison of shallow seismic sources near Chino, California. Geophysics 57(5):693–709\nMiller RD, Pullan SE, Steeples DW, Hunter JA (1994) Field comparison of shallow P-wave seismic sources near Houston, Texas. Geophysics 59(11):1713–1728\nMyers PB, Miller RD, Steeples DW (1987) Shallow seismic reflection profile of the Meers fault, Comanche County, Oklahoma. Geophys Res Lett 15:749–752\nPalmer D (1987) High resolution seismic reflection surveys for coal. Geoexploration 24:397–408\nPożaryski W (1979) Mapa geologiczna Polski I krajów ościennych 1:1000000. Wyd. Geologiczne, Warszawa\nResnick JR (1993) Seismic data processing for AVO and AVA analysis. In: Castagna JP, Backus MM (eds) Offset-dependent reflectivity—theory and practice of AVO analysis. Society of Exploration Geophysics, Tulsa, pp 175–189\nRonen J, Claerbout JF (1985) Surface consistent residual statics estimation by stack power maximization. Geophysics 50(12):2759–2767\nSheriff RE (1985) Aspects of seismic resolution. In: Berg OR, Woolvetron DG (eds) Seismic stratigraphy II: an integrated approach to hydrocarbon exploration. AAPG Memoir 39\nSheriff RE (1991) Encyclopedic dictionary of exploration geophysics. Society of Exploration Geophysics, Tulsa, p 240\nSheriff RE (1997) Seismic resolution: a key element. AAPG Explor Geophys Corner 18:44–51\nShuey RT (1985) A simplification of the Zoeppritz equations. Geophysics 50(4):609–614\nSingh S (1984) High-frequency shallow reflection mapping in tin mining. Geophys Prospect 32:1033–1044\nSteeples DW, Miller RD (1990) Seismic reflection methods applied to engineering, environmental, and groundwater problems. In: Ward S (ed) Review and tutorial: investigations in geophysics, vol 5. Society of Exploration Geophysicists, Tulsa, pp 1–30\nSteeples DW, Miller RD (1998) Avoiding pitfalls in shallow seismic reflection surveys. Geophysics 63(4):1213–1224\nTaner MT, Koehler F (1981) Surface consistent corrections. Geophysics 46:17–22\nTreadway JA, Steeples DW, Miller RD (1988) Shallow seismic study of a fault scarp near Borah Peak, Idaho. J Geophys Res 93:6325–6337\nUrsin B (1990) Offset-dependent geometrical spreading in a layered medium. Geophysics 55(4):492–496\nWidess MB (1973) How thin is a thin bed? Geophysics 38(6):1176–1180\nYilmaz O (1987) Seismic data processing. Society of Exploration Geophysics, Tulsa\nYilmaz O (2001) Seismic data analysis. Society of Exploration Geophysics, Tulsa",{"EN":854},"",{"EN":856},"The acquisition parameters and methodology of seismic data processing for high-resolution seismic imaging viewed through relative amplitude preservation are presented. An example of the obtaining of high-quality, shallow seismic data with a variable end-on spread is shown. The source used for the project is an accelerated weight drop. The study area lies within the mine waste disposal area, near Rudna village (Fore-Sudetic Monocline, WS Poland), and results are given for a 2D experimental profile. The aim of the project was to design optimal acquisition and processing parameters for the detailed recognition of Tertiary deposits. The proposed acquisition parameters are a compromise between time, cost and results. 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HD, Trustrum NA, De Rose RC (2003) Geomorphic changes in a complex gully system measured from sequential digital elevation models, and implications for management. Earth Surf Process Landf 28:1043–1058. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fesp.500\nBowman D, Svoray T, Devora S, Shapira I, Laronne JB (2010) Extreme rates of channel incision and shape evolution in response to a continuous, rapid base-level fall, the Dead See, Israel. Geomorphology 114:227–237. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2009.07.004\nBravard JP, Amoros C, Pautou G, Bornette G, Bournaud M, des Châtelliers MC, Gibert J, Peiry JL, Perrin JF, Tachet H (1997) River incision in south-east France: morphological phenomena and ecological effects. Regul Rivers Res Manag 13:1–16\nBrookes A (1987) River channel adjustment downstream from channelization works in England and Wales. Earth Surf Process Landf 12:337–351\nCollins B, Dunne T (1989) Gravel transport, gravel harvesting and channel-bed degradation in rivers draining the southern Olympic Mountains, Washington, USA. Environ Geol Water Sci 13:213–224\nCzech W, Radecki-Pawlik A, Wyżga B, Hajdukiewicz H (2016) Modelling the flooding capacity of a Polish Carpathian river: a comparison of constrained and free channel conditions. Geomorphology 272:32–42. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2015.09.025\nDerose RC, Gomez B, Marden M, Trustrum NA (1998) Gully erosion in Mangatu Forest, New Zealand, estimated from digital elevation models. Earth Surf Process Landf 23:1045–1053\nDewitte O, Jasselette JC, Cornet Y, Van Den Eeckhaut M, Collignon A, Poesen J, Demoulin A (2008) Tracking landslide displacements by multi-temporal DTMs: a combined aerial stereophotogrammetric and LIDAR approach in western Belgium. Eng Geol 99:11–22. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.enggeo.2008.02.006\nDudziak J (1965) Dzika eksploatacja kamienia w powiecie nowotarskim (Uncontrolled exploitation of rocks in the district of Nowy Targ). Ochrona Przyrody 31:161–187 (in Polish, with English summary)\nFlorsheim JL, Chin A, Gaffney K, Slota D (2013) Thresholds of stability in incised “Anthropocene” landscapes. Anthropocene 2:27–41. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.ancene.2013.10.006\nFroehlich W (1980) Hydrologiczne aspekty pogłębiania koryt rzek beskidzkich (Deepening of stream channels in the Beskidy Mts—a hydrological aspect). Zesz Probl Postępów Nauk Roln 235:257–268 (in Polish, with English summary)\nGUGiK (1999) Wytyczne techniczne K-2.7. Zasady wykonywania prac fotolotniczych. GUGiK, Warszawa, p 150\nGUGiK (2001) Wytyczne techniczne K-2.8. Zasady wykonywania ortofotomap w skali 1:10000. GUGiK, Warszawa, p 74\nHajdukiewicz M (2015) The potential accuracy of the survey of landform changes using archival aerial orthophotos: case study of the Białka River valley. In: Jasiewicz J, Zwoliński Z, Mitasova H, Hengl T (eds) Geomorphometry for geosciences. Adam Mickiewicz University, Poznań, pp 243–246\nHajdukiewicz M, Romanyshyn I (2017) An accuracy assessment of spot heights on digital elevation model (DEM) derived from ALS survey: case study of Łysica massif. Struct Environ 31:125–132\nHajdukiewicz H, Wyżga B (2019) Aerial photo-based analysis of the hydromorphological changes of a mountain river over the last six decades: the Czarny Dunajec, Polish Carpathians. Sci Total Environ 648:1598–1613. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.scitotenv.2018.08.234\nHajdukiewicz H, Wyżga B, Zawiejska J (2019) Twentieth-century degradation of Polish Carpathian rivers. Quat Int 504:181–194. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.quaint.2017.12.011\nKeesstra SD, van Huissteden J, Vanderberghe J, Van Dam O, de Gier J, Pleizer ID (2005) Evolution of the morphology of the river Dragonja (SW Slovenia) due to land-use changes. Geomorphology 69:191–207. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2005.01.004\nKlimek K (1983) Erozja wgłębna dopływów Wisły na przedpolu Karpat (Vertical erosion of Vistula tributaries on the Carpathian foreland). In: Kajak Z (ed) Ekologiczne podstawy zagospodarowania Wisły i jej dorzecza. PWN, Warszawa-Łódź, pp 97–108 (in Polish, with English summary)\nKondolf GM, Piégay H, Landon N (2002) Channel response to increased and decreased bedload supply from land use change: contrasts between two catchments. Geomorphology 45:35–51. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0169-555X(01)00188-X\nKorpak J (2007) The influence of river training on mountain channel changes (Polish Carpathian Mountains). Geomorphology 92:166–181. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2006.07.037\nKrzemień K (1981) Zmienność subsystemu korytowego Czarnego Dunajca (The changeability of the Czarny Dunajec channel subsystem). Zesz Nauk Uniw Jagiellońskiego Pr Geogr 53:123–137 (in Polish, with English summary)\nKrzemień K (2003) The Czarny Dunajec River, Poland, as an example of human-induced development tendencies in a mountain river channel. Landf Anal 4:57–64\nKurczyński Z, Bakuła K (2013) Generowanie referencyjnego numerycznego modelu terenu o zasięgu krajowym w oparciu o lotnicze skanowanie laserowe w projekcie ISOK (Generation of countrywide reference digital terrain model from airborne laser scanning in ISOK Project). In: Kurczyński Z (ed) Geodezyjne Technologie Pomiarowe. PTFiT, Warszawa, pp 59–68 (in Polish, with English summary)\nLach J, Wyżga B (2002) Channel incision and flow increase of the upper Wisłoka River, southern Poland, subsequent to the reafforestation of its catchment. Earth Surf Process Landf 27:445–462. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fesp.329\nLandon N, Piégay H, Bravard JP (1998) The Drome River incision (France): from assessment to management. Landsc Urban Plan 43:119–131\nLiébault F, Piégay H (2001) Assessment of channel changes due to long-term bedload supply decrease, Roubion River, France. Geomorphology 36:167–186. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0169-555X(00)00044-1\nMichalowska K, Glowienka E (2008) Multi-temporal data integration for the changeability detection of the unique Słowiński National Park landscape. Int Arch Phot Rem Sens Spat Inf Sci 37:1017–1020\nPeiry JL (1987) Channel degradation in the middle Arve river, France. Regul Rivers Res Manag 1:183–188\nPiégay H, Peiry JL (1997) Long profile evolution of a mountain stream in relation to gravel load management: example of the middle Giffre River (French Alps). Environ Manag 21:909–919\nProkešová R, Kardoš M, Medved’ová A (2010) Landslide dynamics from high-resolution aerial photographs: a case study from the Western Carpathians, Slovakia. Geomorphology 115:90–101. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2009.09.033\nRadecki-Pawlik A, Wyżga B, Czech W, Mikuś P, Zawiejska J, Ruiz-Villanueva V (2016) Modelling hydraulic parameters of flood flows for a Polish Carpathian river subjected to variable human impacts. In: Kundzewicz ZW, Stoffel M, Niedźwiedź T, Wyżga B (eds) Flood risk in the upper Vistula river. Springer, Cham, pp 127–151. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-41923-7_7\nRinaldi M (2003) Recent channel adjustments in alluvial rivers of Tuscany, central Italy. Earth Surf Process Landf 28:587–608. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fesp.464\nRinaldi M, Wyżga B, Surian N (2005) Sediment mining in alluvial channels: physical effects and management perspectives. River Res Appl 21:805–828. https:\u002F\u002Fdoi.org\u002F10.1002\u002Frra.884\nRuiz-Villanueva V, Stoffel M, Wyżga B, Kundzewicz ZW, Czajka B, Niedźwiedź T (2016) Decadal variability of floods in the northern foreland of the Tatra Mountains. Reg Environ Change 16:603–615. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs10113-014-0694-9\nSchiefer E, Gilbert R (2007) Reconstructing morphometric change in a proglacial landscape using historical aerial photography and automated DEM generation. Geomorphology 88:167–178. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2006.11.003\nSimon A (1989) A model of channel response in disturbed alluvial channels. Earth Surf Process Landf 14:11–26\nŠkarpich V, Hradecký J, Dušek R (2013) Complex transformation of the geomorphic regime of channels in the forefield of the Moravskoslezské Beskydy Mts.: case study of the Morávka River (Czech Republic). CATENA 111:25–40. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.catena.2013.06.028\nSurian N, Rinaldi M (2003) Morphological response to river engineering and management in alluvial channels in Italy. Geomorphology 50:307–326. https:\u002F\u002Fdoi.org\u002F10.1016\u002FS0169-555X(02)00219-2\nWheeler DA (1979) The overall shape of longitudinal profiles of streams. In: Pitty AF (ed) Geographical approaches to fluvial processes. Geoabstracts, Norwich, pp 241–260\nWilliams GP, Wolman MG (1984) Downstream effects of dams on alluvial rivers. US Geol Surv Prof Pap 1286:1–83\nWohl E (2004) Disconnected rivers: linking rivers to landscapes. Yale Univ. Press, New Haven, p 320\nWyżga B (1993) River response to channel regulation: case study of the Raba River, Carpathians, Poland. Earth Surf Process Landf 18:541–556\nWyżga B (1997) Methods for studying the response of flood flows to channel change. J Hydrol 198:271–288\nWyżga B (1999) Estimating mean flow velocity in channel and floodplain areas and its use for explaining the pattern of overbank deposition and floodplain retention. Geomorphology 28:281–297\nWyżga B (2001a) A geomorphologist’s criticism of the engineering approach to channelization of gravel-bed rivers: case study of the Raba River, Polish Carpathians. Environ Manag 28:341–358. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs002670010228\nWyżga B (2001b) Impact of the channelization-induced incision of the Skawa and Wisłoka Rivers, southern Poland, on the conditions of overbank deposition. Regul Rivers Res Manag 17:85–100\nWyżga B (2008) A review on channel incision in the Polish Carpathian rivers during the 20th century. In: Habersack H, Piégay H, Rinaldi M (eds) Gravel-bed rivers VI: from process understanding to river restoration. Elsevier, Amsterdam, pp 525–555. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fs0928-2025(07)11142-1\nWyżga B, Hajdukiewicz H, Radecki-Pawlik A, Zawiejska J (2010) Eksploatacja osadów z koryt rzek górskich—skutki środowiskowe i procedury oceny (Exploitation of sediments from mountain river beds—environmental impact and evaluation procedures). Gosp Wodna 6:243–249 (in Polish, with English summary)\nWyżga B, Zawiejska J, Radecki-Pawlik A, Hajdukiewicz H (2012) Environmental change, hydromorphological reference conditions and the restoration of Polish Carpathian rivers. Earth Surf Process Landf 37:1213–1226. https:\u002F\u002Fdoi.org\u002F10.1002\u002Fesp.3273\nWyżga B, Radecki-Pawlik A, Zawiejska J (2016a) Flood risk management in the Upper Vistula basin in perspective: Traditional versus alternative measures. In: Kundzewicz ZW, Stoffel M, Niedźwiedź T, Wyżga B (eds) Flood risk in the upper Vistula basin. Springer, Cham, pp 361–380. https:\u002F\u002Fdoi.org\u002F10.1007\u002F978-3-319-41923-7_18\nWyżga B, Zawiejska J, Hajdukiewicz H (2016b) Multi-thread rivers in the Polish Carpathians: occurrence, decline and possibilities for restoration. Quat Int 415:344–356. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.quaint.2015.05.015\nWyżga B, Zawiejska J, Radecki-Pawlik A (2016c) Impact of channel incision on the hydraulics of flood flows: examples from Polish Carpathian rivers. Geomorphology 272:10–20. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2015.05.017\nZawiejska J, Krzemień K (2004) Human impact on the dynamics of the upper Dunajec River channel: a case study. Geogr Čas 56:111–124\nZawiejska J, Wyżga B (2010) Twentieth-century channel change on the Dunajec River, southern Poland: patterns, causes and controls. Geomorphology 117:234–246. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2009.01.014\nZawiejska J, Wyżga B, Radecki-Pawlik A (2015) Variation in surface bed material along a mountain river modified by gravel extraction and channelization, the Czarny Dunajec, Polish Carpathians. Geomorphology 231:353–366. https:\u002F\u002Fdoi.org\u002F10.1016\u002Fj.geomorph.2014.12.026",{"EN":1023},"Rivers of the Polish Carpathians incised deeply during the twentieth century, but detailed information about the timing and amount of incision of their channels exists only for water-gauge cross sections. Applicability of photogrammetric extraction of digital elevation models (DEMs) from archival aerial photos for reconstructing changes in vertical river position was verified in the study of a 3-km reach of the Czarny Dunajec River. DEMs extracted from a few sets of archival aerial photos from the years 1964–1994 together with recent orthophotos and DEMs were used in the analysis. Measurements taken in river cross sections spaced at 100-m intervals indicated that on average the lowest point of the channel bed lowered between 1964 and 2009 by 1.74 ± 0.17 m, low-flow water surface by 1.57 ± 0.07 m, active river channel by 1.54 ± 0.12 m and the belt of river migration by 1.03 ± 0.15 m. However, the change in vertical river position during the years 1964–2009 varied greatly along the reach, with the elevation of low-flow water surface lowered by up to 3.61 ± 0.07 m in the upper part of the reach and increased by up to 1.34 ± 0.07 m in its lower part. Combining the information about changes in vertical river position and the width of river migration belt yielded data about the change in sediment volume in the reach, with an average annual loss of sediment amounting to 256 ± 37 m3 per 100-m channel segment. The study indicated that DEMs generated from archival aerial photos can be a useful tool in analysing recent vertical channel changes outside water-gauge stations.",{"EN":1025},"Photogrammetric reconstruction of changes in vertical river position using archival aerial photos: case study of the Czarny Dunajec River, Polish 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J., and B. Espildora (1973), Entropy in the assessment of uncertainty in hydrologic systems and models, Water Resour. Res. 9, 6, 1511–1522, DOI: 10.1029\u002FWR009i006p01511.",{"doi":1204},"10.1029\u002FWR009i006p01511",{"id":20,"text":1206,"url":20,"identifiers":1207},"Barberis, C., P. Molnar, P. Claps, and P. Burlando (2003), Hydrologic similarity of river basins through regime stability, Dipartimento Di Idraulica, Trasporti ed Infrastrutture Civili, Politecnico Di Torino.",{},{"id":20,"text":1209,"url":20,"identifiers":1210},"Chapman, T.G. (1986), Entropy as a measure of hydrologic data uncertainty and model performance, J. Hydrol. 85, 1–2, 111–126, DOI: 10.1016\u002F0022-1694(86)90079-X.",{"doi":1211},"10.1016\u002F0022-1694(86)90079-X",{"id":20,"text":1213,"url":20,"identifiers":1214},"Dalezios, N.R., and P.A. Tyraskis (1989), Maximum entropy spectra for regional precipitation analysis and forecasting, J. Hydrol. 109, 1–2, 25–42, DOI: 10.1016\u002F0022-1694(89)90004-8.",{"doi":1215},"10.1016\u002F0022-1694(89)90004-8",{"id":20,"text":1217,"url":20,"identifiers":1218},"Dynowska, I., and J. Pociask-Karteczka (1999), Water circulation. In: L. Starkel (ed.), Geography of Poland. Natural Environment, Warszawa, 343–373 (in Polish).",{},{"id":20,"text":1220,"url":20,"identifiers":1221},"Hattermann, F.F., Z.W. Kundzewicz, S. Huang, T. Vetter, F.-W. Gerstengarbe, and P. Werner (2013), Climatological drivers of changes in flood hazard in Germany, Acta Geophys. 61, 2, 463–477, DOI: 10.2478\u002Fs11600-012-0070-4.",{"doi":1222},"10.2478\u002Fs11600-012-0070-4",{"id":20,"text":1224,"url":20,"identifiers":1225},"Kawachi, T., T. Maruyama, and V.P. Singh (2001), Rainfall entropy for delineation of water resources zones in Japan, J. Hydrol. 246, 1–4, 36–44, DOI: 10.1016\u002FS0022-1694(01)00355-9.",{"doi":1226},"10.1016\u002FS0022-1694(01)00355-9",{"id":20,"text":1228,"url":20,"identifiers":1229},"Koutsoyiannis, D. (2005), Uncertainty, entropy, scaling and hydrological stochastics, 1, Marginal distributional properties of hydrological processes and state scaling, Hydrol. Sci. J. 50, 3, 381–404, DOI: 10.1623\u002Fhysj.50.3.381.65031.",{},{"id":20,"text":1231,"url":20,"identifiers":1232},"Krasovskaia, I. (1995), Quantification of the stability of river flow regimes, Hydrol. Sci. J. 40, 5, 587–598, DOI: 10.1080\u002F02626669509491446.",{"doi":1233},"10.1080\u002F02626669509491446",{"id":20,"text":1235,"url":20,"identifiers":1236},"Krasovskaia, I. (1997), Entropy-based grouping of river flow regimes, J. Hydrol. 202, 1–4, 173–191, DOI: 10.1016\u002FS0022-1694(97)00065-6.",{"doi":1237},"10.1016\u002FS0022-1694(97)00065-6",{"id":20,"text":1239,"url":20,"identifiers":1240},"Krstanovic, P.F., and V.P. Singh (1992), Transfer of information in monthly rainfall series of San Jose, California. In: V.P. Singh and M. Fiorentino (eds.), Entropy and Energy Dissipation in Water Resources, Kluwer Academic Publishers, 155–173, DOI: 10.1007\u002F978-94-011-2430-0_8.",{"doi":1241},"10.1007\u002F978-94-011-2430-0_8",{"id":20,"text":1243,"url":20,"identifiers":1244},"Kundzewicz, Z.W., and S. Huang (2010), Seasonal temperature extremes in Potsdam, Acta Geophys. 58, 6, 1115–1133, DOI: 10.2478\u002Fs11600-010-0026-5.",{"doi":1245},"10.2478\u002Fs11600-010-0026-5",{"id":20,"text":1247,"url":20,"identifiers":1248},"Maruyama, T., and T. Kawachi (1998), Evaluation of rainfall characteristics using entropy, J. Rainwater Catchment Syst. 4, 1, 7–10.",{"doi":1249},"10.7132\u002Fjrcsa.KJ00003257785",{"id":20,"text":1251,"url":20,"identifiers":1252},"Maruyama, T., T. Kawachi, and V.P. Singh (2005), Entropy-based assessment and clustering of potential water resources availability, J. Hydrol. 309, 1–4, 104–113, DOI: 10.1016\u002Fj.jhydrol.2004.11.020.",{"doi":1253},"10.1016\u002Fj.jhydrol.2004.11.020",{"id":20,"text":1255,"url":20,"identifiers":1256},"Shannon, C.E. (1948), A mathematical theory of communication, Bell. Labs. Tech. J. 27, 3, 379–423, DOI: 10.1002\u002Fj.1538-7305.1948.tb01338.x.",{"doi":1257},"10.1002\u002Fj.1538-7305.1948.tb01338.x",{"id":20,"text":1259,"url":20,"identifiers":1260},"Singh, V.P. (1997), The use of entropy in hydrology and water resources, Hydrol. Process. 11, 6, 587–626, DOI: 10.1002\u002F(SICI)1099-1085(199705)11:6>587::AID-HYP479\u003C3.0.CO;2-P.",{"doi":1261},"10.1002\u002F(SICI)1099-1085(199705)11:6\u003C587::AID-HYP479>3.0.CO;2-P",{"id":20,"text":1263,"url":20,"identifiers":1264},"Sonuga, J.O. (1972), Principle of maximum entropy in hydrologic frequency analysis, J. Hydrol. 17, 3, 177–191, DOI: 10.1016\u002F0022-1694(72)90003-0.",{"doi":1265},"10.1016\u002F0022-1694(72)90003-0",{"id":20,"text":1267,"url":20,"identifiers":1268},"Sonuga, J.O. (1976), Entropy principle applied to the rainfall-runoff process, J. Hydrol. 30, 1–2, 81–94, DOI: 10.1016\u002F0022-1694(76)90090-1.",{"doi":1269},"10.1016\u002F0022-1694(76)90090-1",{"id":20,"text":1271,"url":20,"identifiers":1272},"Strupczewski, W.G., K. Kochanek, E. Bogdanowicz, I. Markiewicz, and W. Feluch (2016), Comparison of two nonstationary flood frequency analysis methods within the context of the variable regime in the representative polish rivers, Acta Geophys. 64, 1, 206–236, DOI: 10.1515\u002Facgeo-2015-0070.",{"doi":1273},"10.1515\u002Facgeo-2015-0070",{"id":20,"text":1275,"url":20,"identifiers":1276},"Woś, A. (2010), Climate of Poland in the Second Half of the 20th Century, Wyd. Naukowe UAM, Poznań (in Polish).",{},{"id":20,"text":1278,"url":20,"identifiers":1279},"Wrzesiński, D. (2010), Spatial Differentiation of the Stability of the Flow Regime of European Rivers, Bogucki Wydawnictwo Naukowe, Poznań (in Polish).",{},{"id":20,"text":1281,"url":20,"identifiers":1282},"Wrzesiński, D. (2013a), Entropy of River Flows in Poland, Studia i Prace z Geografii i Geologii 33, Bogucki Wydawnictwo Naukowe, Poznań, 204 pp. (in Polish).",{},{"id":20,"text":1284,"url":20,"identifiers":1285},"Wrzesiński, D. (2013b), Uncertainty of flow regime characteristics of rivers in Europe, Quaest. Geograph. 32, 1, 49–59, DOI: 10.2478\u002Fquageo-2013-0006.",{"doi":1286},"10.2478\u002Fquageo-2013-0006",{"id":20,"text":1288,"url":20,"identifiers":1289},"Wrzesiński, D. (2014), Uncertainty of the flow regime of rivers in Poland, Monografie Komitetu Gospodarki Wodnej PAN 20, 2, 189–201 (in Polish).",{},{"id":1291,"createTime":1292,"updateTime":1292,"relativeEntities":1293,"slug":20,"properties":1294,"entityType":189,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"primaryUrl":1303,"fullTextUrl":20,"authors":1304,"publicationType":225,"publisherRelationship":1337,"citationCount":20,"citationInfo":20,"publishDate":1371,"publishYear":345,"citationAnalyzeStatus":19,"lastCitationAnalyze":20,"indexDatabases":20,"openAccess":20,"references":20,"isForceReanalyzing":262},"2ade9fa7-6973-4a53-b598-f9c98b2ac410","2024-01-15T23:46:26.010+00:00",[],{"references":1295,"abstract":1297,"title":1299,"doi":1301},{"VOID":1296},"Astafyeva E, Afraimovich EL (2004) Long-distance traveling ionospheric disturbances caused by the great Sumatra-Andaman earthquake on 26 December 2004, Institute of Solar-Terrestrial Physics SD RAS, P. 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Sci China Earth Sci 58:151–158. https:\u002F\u002Fdoi.org\u002F10.1007\u002Fs11430-014-5000-7\nSouriau A, Poupinet G (1991) The velocity profile at the base of the liquid core from PKP(BC + Cdiff) data: an argument in favor of radial inhomogeneity. Geophys Res Lett 18:2023–2026\nSouriau A, Roudil P (1995) Attenuation in the uppermost inner core from broad-band GEOSCOPE PKP data. Geophys J Int 123:572–587\nYu W-C, Wen L, Niu F (2005) Seismic velocity structure in the earth’s outer core. J Geophys Res 110:B02302. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2003jb002928\nZou Z, Koper KD, Cormier VF (2008) The structure of the base of the outer core inferred from seismic waves diffracted around the inner core. J Geophys Res 113:B05314. https:\u002F\u002Fdoi.org\u002F10.1029\u002F2007jb005316",{"EN":1298},"Earthquakes are among the most dangerous events that occur on earth and many scientists have been investigating the underlying processes that take place before earthquakes occur. These investigations are fueling efforts towards developing both single and multiple parameter earthquake forecasting methods based on earthquake precursors. One potential earthquake precursor parameter that has received significant attention within the last few years is the ionospheric total electron content (TEC). Despite its growing popularity as an earthquake precursor, TEC has been under great scrutiny because of the underlying biases associated with the process of acquiring and processing TEC data. Future work in the field will need to demonstrate our ability to acquire TEC data with the least amount of biases possible thereby preserving the integrity of the data. This paper describes a process for removing biases using raw TEC data from the standard Rinex files obtained from any global positioning satellites system. The process is based on developing an unbiased TEC (UTEC) data and model that can be more adaptable to serving as a precursor signal for earthquake forecasting. The model was used during the days and hours leading to the earthquake off the coast of Tohoku, Japan on March 11, 2011 with interesting results. The model takes advantage of the large amount of data available from the GPS Earth Observation Network of Japan to display near real-time UTEC data as the earthquake approaches and for a period of time after the earthquake occurred.",{"EN":1300},"Unbiased total electron content (UTEC), their fluctuations, and correlation with seismic activity over Japan",{"VOID":1302},"10.1007\u002Fs11600-017-0105-y","https:\u002F\u002Flink.springer.com\u002Farticle\u002F10.1007\u002Fs11600-017-0105-y",[1305,1320],{"id":1306,"sortIndex":21,"researcher":20,"roles":1307,"affiliations":1308,"properties":1317},"ffe55672-38c9-464e-b7dc-6ee0bb38a852",[198],[1309],{"id":20,"sortIndex":21,"affiliation":1310,"properties":20},{"id":1311,"createTime":1312,"updateTime":1312,"relativeEntities":1313,"slug":20,"properties":1314,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"9de84410-979b-4753-a2f2-953f05529df6","2024-01-15T23:46:26.034+00:00",[],{"title":1315},{"VI":1316},"Science and Tecnology Division Chair, Eastern Nazarene College, Quincy, USA",{"title":1318},{"VI":1319},"Pierre-Richard Cornely",{"id":1321,"sortIndex":196,"researcher":20,"roles":1322,"affiliations":1323,"properties":1334},"ff5fab74-23d1-42cc-9cff-62f2d53fe466",[198],[1324],{"id":20,"sortIndex":21,"affiliation":1325,"properties":20},{"id":1326,"createTime":1327,"updateTime":1328,"relativeEntities":1329,"slug":1330,"properties":1331,"entityType":41,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21},"0a92e475-25dc-4ccb-9c9b-4bfa422f84f9","2024-01-15T23:46:26.046+00:00","2025-06-11T23:28:40.604+00:00",[],"Department-of-Physics-and-Engineering-Chair-Eastern-Nazarene-College-Quincy-USA",{"title":1332},{"VI":1333},"Department of Physics and Engineering, Chair, Eastern Nazarene College, Quincy, USA",{"title":1335},{"VI":1336},"John Hughes",{"url":1303,"publisher":1338,"properties":1366},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1339,"slug":10,"properties":1340,"entityType":18,"verifyStatus":19,"verifyTime":20,"verifyNote":20,"syncStatus":19,"languages":20,"translateLanguages":20,"viewCount":21,"subjectFields":1344,"manageAffiliations":1345,"indexDatabases":1346,"url":95,"thumbnailPath":20,"statistic":1361,"gsStatistic":20,"type":169,"analyzePriority":20},[],{"issn":1341,"eissn":1342,"title":1343},{"VOID":13},{"VOID":15},{"EN":17},[],[],[1347,1354],{"id":77,"indexDatabase":1348,"url":90,"indexYears":91,"academicFieldIds":1353,"indexDatabaseRanking":94},{"id":79,"createTime":80,"updateTime":81,"relativeEntities":1349,"label":1350,"description":1351,"key":87,"publicationTags":1352,"standard":20},[],{"EN":84,"VI":84},{"EN":84,"VI":86},[89],[93],{"id":58,"indexDatabase":1355,"url":73,"indexYears":20,"academicFieldIds":1360,"indexDatabaseRanking":20},{"id":60,"createTime":61,"updateTime":62,"relativeEntities":1356,"label":1357,"description":1358,"key":69,"publicationTags":1359,"standard":20},[],{"EN":65,"VI":65},{"VI":67,"EN":68},[71,72],[75],{"impactFactor":21,"impactFactorByYear":1362,"i10Index":109,"i10IndexLast5Year":110,"totalPublication":111,"totalPublicationByYear":1363,"totalCitation":132,"totalCitationByYear":1364,"totalCitationPerPublication":148,"totalCitationPerPublicationByYear":1365,"hindexLast5Year":168,"hindex":168},{"2012":98,"2013":99,"2014":100,"2015":101,"2016":102,"2017":103,"2018":104,"2019":101,"2020":105,"2021":106,"2022":107,"2023":108},{"2006":113,"2007":114,"2008":115,"2009":116,"2010":117,"2011":118,"2012":119,"2013":120,"2014":121,"2015":122,"2016":123,"2017":124,"2018":125,"2019":126,"2020":127,"2021":128,"2022":129,"2023":130,"2024":131},{"2006":134,"2007":135,"2008":136,"2009":136,"2010":120,"2011":137,"2012":138,"2013":139,"2014":115,"2015":140,"2016":141,"2017":136,"2018":142,"2019":143,"2020":144,"2021":145,"2022":146,"2023":147},{"2006":150,"2007":151,"2008":152,"2009":153,"2010":154,"2011":155,"2012":156,"2013":157,"2014":158,"2015":159,"2016":160,"2017":161,"2018":162,"2019":163,"2020":164,"2021":165,"2022":166,"2023":167},{"volume":1367,"pages":1369},{"VOID":1368},"66",{"VOID":1370},"51-70","2017-12-16"]