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Hydrol., 347, 116, 10.1016\u002Fj.jhydrol.2007.09.040",{"doi":336},"10.1016\u002Fj.jhydrol.2007.09.040",{"id":18,"text":338,"url":18,"identifiers":339},"Krvavica, N., and Rubinić, J. (2020). Evaluation of design storms and critical rainfall durations for flood prediction in partially urbanized catchments. Water, 12.",{"doi":340},"10.3390\u002Fw12072044",{"id":18,"text":342,"url":18,"identifiers":343},"Yang, 2013, Urbanization and climate change: An examination of nonstationarities in urban flooding, J. Hydrometeorol., 14, 1791, 10.1175\u002FJHM-D-12-095.1",{"doi":344},"10.1175\u002FJHM-D-12-095.1",{"id":18,"text":346,"url":18,"identifiers":347},"Arnaud, 2002, Influence of rainfall spatial variability on flood prediction, J. 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Water, 9.",{"doi":372},"10.3390\u002Fw9050342",{"id":18,"text":374,"url":18,"identifiers":375},"Lin, 1988, Application of the step-duration orographic intensification factors method to estimation of PMP for mountainous regions, J. Hohai Univ., 3, 40",{},{"id":18,"text":377,"url":18,"identifiers":378},"Zhou, 2020, The study of urban design storm based on stochastic storm transposition, Adv. Water Sci., 31, 583",{},{"id":18,"text":380,"url":18,"identifiers":381},"Kong, 2016, Spatiotemporal patterns of global-continental-regional scale heavy rainfall, J. Beijing Norm. Univ., 2, 228",{},{"id":18,"text":383,"url":18,"identifiers":384},"Cristiano, 2017, Spatial and temporal variability of rainfall and their effects on hydrological response in urban areas - A review, Hydrol. Earth Sys. Sci., 21, 3859, 10.5194\u002Fhess-21-3859-2017",{"doi":385},"10.5194\u002Fhess-21-3859-2017",{"id":18,"text":387,"url":18,"identifiers":388},"Donat, 2016, More extreme precipitation in the world’s dry and wet regions, Nat. Clim. Chang., 6, 508, 10.1038\u002Fnclimate2941",{"doi":389},"10.1038\u002Fnclimate2941",{"id":18,"text":391,"url":18,"identifiers":392},"Patel, A., Goswami, A., Dharpure, J.K., and Thamban, M. (2020). Rainfall variability over the Indus, Ganga, and Brahmaputra river basins: A spatio-temporal characterisation. Quat. Int.",{"doi":393},"10.1016\u002Fj.quaint.2020.06.010",{"id":18,"text":395,"url":18,"identifiers":396},"Smith, 2005, Extraordinary flood response of a small urban watershed to short duration convective rainfall, J. Hydrometeorol., 6, 599, 10.1175\u002FJHM426.1",{"doi":397},"10.1175\u002FJHM426.1",{"id":18,"text":399,"url":18,"identifiers":400},"Guo, 2006, Mesoscale convective precipitation system modified by urbanization in Beijing City, Atmos. 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Res., 50, 1592, 10.1002\u002F2013WR014224",{"doi":527},"10.1002\u002F2013WR014224",false,{"id":530,"createTime":531,"updateTime":532,"relativeEntities":533,"slug":534,"properties":535,"entityType":141,"verifyStatus":142,"verifyTime":548,"verifyNote":144,"languages":549,"translateLanguages":18,"viewCount":19,"primaryUrl":550,"fullTextUrl":18,"authors":551,"publicationType":214,"publisherRelationship":603,"citationCount":19,"citationInfo":663,"publishDate":18,"publishYear":18,"citationAnalyzeStatus":17,"lastCitationAnalyze":532,"indexDatabases":665,"openAccess":18,"references":666,"isForceReanalyzing":528},"ddf48d5c-f682-4279-8005-498a11150273","2024-10-11T18:54:28.792+00:00","2026-03-31T11:55:48.166+00:00",[],"Developing-an-Effective-Model-for-Predicting-Spatially-and-Temporally-Continuous-Stream-Temperatures-from-Remotely-Sensed-Land-Surface-Temperatures",{"openalex":536,"mag":538,"abstract":540,"title":542,"gsPaper":544,"doi":546},{"VOID":537},"W2185746548",{"VOID":539},"2185746548",{"EN":541},"\u003Cjats:p>Although water temperature is important to stream biota, it is difficult to collect in a spatially and temporally continuous fashion. We used remotely-sensed Land Surface Temperature (LST) data to estimate mean daily stream temperature for every confluence-to-confluence reach in the John Day River, OR, USA for a ten year period. Models were built at three spatial scales: site-specific, subwatershed, and basin-wide. Model quality was assessed using jackknife and cross-validation. Model metrics for linear regressions of the predicted vs. observed data across all sites and years: site-specific r2 = 0.95, Root Mean Squared Error (RMSE) = 1.25 °C; subwatershed r2 = 0.88, RMSE = 2.02 °C; and basin-wide r2 = 0.87, RMSE = 2.12 °C. Similar analyses were conducted using 2012 eight-day composite LST and eight-day mean stream temperature in five watersheds in the interior Columbia River basin. Mean model metrics across all basins: r2 = 0.91, RMSE = 1.29 °C. Sensitivity analyses indicated accurate basin-wide models can be parameterized using data from as few as four temperature logger sites. This approach generates robust estimates of stream temperature through time for broad spatial regions for which there is only spatially and temporally patchy observational data, and may be useful for managers and researchers interested in stream biota.\u003C\u002Fjats:p>",{"EN":543},"Developing an Effective Model for Predicting Spatially and Temporally Continuous Stream Temperatures from Remotely Sensed Land Surface Temperatures",{"VOID":545},"[\"9967814910259238529\"]",{"VOID":547},"10.3390\u002Fw7126660","2024-10-11T18:54:28.791+00:00",[146],"https:\u002F\u002Fwww.mdpi.com\u002F2073-4441\u002F7\u002F12\u002F6660",[552,569,584],{"id":553,"sortIndex":19,"researcher":18,"roles":554,"affiliations":555,"properties":564},"c935845a-7065-4c74-9e28-869fb754ad83",[],[556],{"id":557,"sortIndex":19,"affiliation":558,"properties":18},"a95ee262-17fc-45b2-9cec-1bf1c014d726",{"id":557,"createTime":18,"updateTime":18,"relativeEntities":559,"slug":18,"properties":560,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":563,"statistic":18},[],{"title":561},{"VI":562},"South Fork Research, Inc., 44842 SE 145th St., North Bend, WA, 98045, USA",[],{"title":565,"openalex":567},{"EN":566},"Kristina M. 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A comparison of spatial interpolators, Weed Sci., 51, 44, 10.1614\u002F0043-1745(2002)051[0044:HGIYWM]2.0.CO;2",{"doi":844},"10.1614\u002F0043-1745(2002)051[0044:HGIYWM]2.0.CO;2",{"id":18,"text":846,"url":18,"identifiers":847},"Hwang, 2012, Spatial interpolation schemes of daily precipitation for hydrologic modeling, Stoch. Environ. Res. Risk Assess., 26, 295, 10.1007\u002Fs00477-011-0509-1",{"doi":848},"10.1007\u002Fs00477-011-0509-1",{"id":18,"text":850,"url":18,"identifiers":851},"Integrated Status & Effectiveness Monitoring Program. 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Using Growing Degree Days to Predict Plant Stages, Montana State University-Bozeman.",{},{"id":900,"createTime":901,"updateTime":902,"relativeEntities":903,"slug":904,"properties":905,"entityType":141,"verifyStatus":142,"verifyTime":901,"verifyNote":144,"languages":922,"translateLanguages":923,"viewCount":19,"primaryUrl":925,"fullTextUrl":18,"authors":926,"publicationType":214,"publisherRelationship":948,"citationCount":1009,"citationInfo":1010,"publishDate":18,"publishYear":18,"citationAnalyzeStatus":17,"lastCitationAnalyze":902,"indexDatabases":1014,"openAccess":18,"references":1015,"isForceReanalyzing":528},"39082932-0989-4581-800d-590997e36a99","2024-10-16T14:05:13.517+00:00","2026-03-24T14:34:28.013+00:00",[],"Transport-and-Retention-of-Nitrogen-Phosphorus-and-Carbon-in-North-America-s-Largest-River-Swamp-Basin-the-Atchafalaya-River-Basin",{"mag":906,"gsPaper":908,"keywords":910,"openalex":912,"abstract":914,"title":917,"doi":920},{"VOID":907},"2130466004",{"VOID":909},"[\"16044395923949993708\"]",{"VI":911},"",{"VOID":913},"W2130466004",{"VI":915,"EN":916},"\u003Cjats:p>Các vùng ngập lũ và đất ngập nước ven sông có thể được quản lý hiệu quả để giảm thiểu dinh dưỡng và carbon. Tuy nhiên, hiểu biết của chúng ta về tiềm năng giảm thiểu của các hệ thống sông tự nhiên này còn hạn chế. Nghiên cứu này sử dụng dữ liệu dòng chảy và chất lượng nước lâu dài (1978–2004) từ một vị trí ở thượng nguồn và một vị trí ở hạ nguồn sông Atchafalaya để định lượng lượng nước nhập vào, nước thoát ra và cân bằng khối lượng hóa chất nước lưu thông của nitơ tổng Kjeldahl (TKN = nitơ hữu cơ + nitơ amoni), nitrat + nitrit (NO3 + NO2), phốt pho tổng (TP) và carbon hữu cơ tổng (TOC) qua lưu vực đầm lầy sông lớn nhất Bắc Mỹ. Nghiên cứu đã phát hiện rằng, trong suốt 27 năm qua, Lưu vực Sông Atchafalaya (ARB) đã đóng vai trò như một bể chứa đáng kể cho TKN (tỷ lệ giữ lại hàng năm: 24%), TP (41%), và TOC (12%), nhưng là nguồn phát thải cho nitơ NO3 + NO2 (6%). Về cơ bản hàng năm, ARB đã giữ lại 48,500 t TKN, 16,900 t TP và 167,100 t TOC từ nước sông. Tỷ lệ giữ lại có mối quan hệ chặt chẽ và tích cực với dòng chảy sông, với mức cao trong mùa đông và mùa xuân và mức thấp vào cuối hè. Lượng nước thải NO3 + NO2 cao hơn xảy ra trong suốt mùa xuân và mùa hè, cho thấy vai trò tích cực của các quá trình sinh học đối với nitơ khi nhiệt độ nước và không khí trong lưu vực tăng lên.\u003C\u002Fjats:p>","\u003Cjats:p>Floodplains and river corridor wetlands may be effectively managed for reducing nutrients and carbon. However, our understanding is limited to the reduction potential of these natural riverine systems. This study utilized the long-term (1978–2004) river discharge and water quality records from an upriver and a downriver location of  the Atchafalaya River to quantify the inflow, outflow, and inflow–outflow mass balance of total Kjeldahl nitrogen (TKN = organic nitrogen + ammonia nitrogen), nitrate + nitrite nitrogen (NO3 + NO2), total phosphorous (TP), and total organic carbon (TOC) through the largest river swamp basin in North America. The study found that, over the past 27 years, the Atchafalaya River Basin (ARB) acted as a significant sink for TKN (annual retention: 24%), TP (41%), and TOC (12%), but a source for NO3 + NO2 nitrogen (6%). On an annual basis, ARB retained 48,500 t TKN, 16,900 t TP, and 167,100 t TOC from the river water. The retention rates were closely and positively related to the river discharge with highs during the winter and spring and lows in the late summer. The higher NO3 + NO2 mass outflow occurred throughout spring and summer, indicating an active role of biological processes on nitrogen as water and air temperatures in the basin rise.\u003C\u002Fjats:p>",{"EN":918,"VI":919},"Transport and Retention of Nitrogen, Phosphorus and Carbon in North America’s Largest River Swamp Basin, the Atchafalaya River Basin","Vận chuyển và Giữ lại Nitơ, Phốt pho và Carbon trong Đầm lầy Sông Lớn nhất Bắc Mỹ, Lưu vực Sông Atchafalaya",{"VOID":921},"10.3390\u002Fw5020379",[146],[924],"VI","https:\u002F\u002Fwww.mdpi.com\u002F2073-4441\u002F5\u002F2\u002F379",[927],{"id":928,"sortIndex":19,"researcher":18,"roles":929,"affiliations":930,"properties":939},"95f2634d-ea49-40c9-bd2a-cedf0db37cb5",[],[931],{"id":932,"sortIndex":19,"affiliation":933,"properties":18},"180fd9ce-bc3e-42ac-8748-da89d5357993",{"id":932,"createTime":18,"updateTime":18,"relativeEntities":934,"slug":18,"properties":935,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":938,"statistic":18},[],{"title":936},{"VI":937},"School of Renewable Natural Resources, Louisiana State University Agricultural Center, Baton Rouge, LA 70803, USA",[],{"orcid":940,"title":942,"gsAuthor":944,"openalex":946},{"VOID":941},"https:\u002F\u002Forcid.org\u002F0000-0003-3646-626X",{"EN":943},"Y. 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Quality, 30, 329, 10.2134\u002Fjeq2001.302329x",{"doi":1026},"10.2134\u002Fjeq2001.302329x",{"id":18,"text":1028,"url":18,"identifiers":1029},"Rabalais, 2010, Dynamics and distribution of natural and human-caused coastal hypoxia, Biogeosciences, 7, 585, 10.5194\u002Fbg-7-585-2010",{"doi":1030},"10.5194\u002Fbg-7-585-2010",{"id":18,"text":1032,"url":18,"identifiers":1033},"Turner, 1991, Changes in Mississippi River water quality this century, Bioscience, 41, 140, 10.2307\u002F1311453",{"doi":1034},"10.2307\u002F1311453",{"id":18,"text":1036,"url":18,"identifiers":1037},"Rabalais, 1996, Nutrient changes in the Mississippi River, and system responses on the adjacent continental shelf, Estuaries, 19, 386, 10.2307\u002F1352458",{"doi":1038},"10.2307\u002F1352458",{"id":18,"text":1040,"url":18,"identifiers":1041},"Rabalais, 1998, Consequences of the 1993 Mississippi River flood in the gulf of Mexico, Regul. Rivers Res. Manag., 14, 161, 10.1002\u002F(SICI)1099-1646(199803\u002F04)14:2\u003C161::AID-RRR495>3.0.CO;2-J",{"doi":1042},"10.1002\u002F(SICI)1099-1646(199803\u002F04)14:2\u003C161::AID-RRR495>3.0.CO;2-J",{"id":18,"text":1044,"url":18,"identifiers":1045},"Rabalais, 2002, Beyond science into policy: Gulf of Mexico hypoxia and the Mississippi river, BioScience, 52, 129, 10.1641\u002F0006-3568(2002)052[0129:BSIPGO]2.0.CO;2",{"doi":1046},"10.1641\u002F0006-3568(2002)052[0129:BSIPGO]2.0.CO;2",{"id":18,"text":1048,"url":18,"identifiers":1049},"Mississippi River\u002FGulf of Mexico Watershed Nutrient Task Force, 2008. Gulf of Mexico Action Plan 2008. Available online:http:\u002F\u002Fwater.epa.gov\u002Ftype\u002Fwatersheds\u002Fnamed\u002Fmsbasin\u002Factionplan.cfm.",{},{"id":18,"text":1051,"url":18,"identifiers":1052},"Xu, 2006, Total nitrogen inflow and outflow from a large river swamp basin to the Gulf of Mexico, Hydrol. Sci. J., 51, 531, 10.1623\u002Fhysj.51.3.531",{"doi":1053},"10.1623\u002Fhysj.51.3.531",{"id":18,"text":1055,"url":18,"identifiers":1056},"Xu, Y.J., and Singh, V.P. (2006). Coastal Environment and Water Quality, Water Resources Publications.",{},{"id":18,"text":1058,"url":18,"identifiers":1059},"Murphy, K.E., Touchet, B.A., White, A.G., Daigle, J.J., and Clark, H.L. (1977). Soil survey of St Martin Parish, Louisiana, U.S., Department of Agriculture Soil Conservation Service.",{},{"id":18,"text":1061,"url":18,"identifiers":1062},"(1996). SAS\u002FSTAT User’s Guide, Version 6.12, SAS Institute Inc.. [4th].",{},{"id":18,"text":1064,"url":18,"identifiers":1065},"Lambou, 1983, Transport of organic-carbon in the Atchafalaya Basin, Louisiana, Hydrobiologia, 98, 25, 10.1007\u002FBF00019248",{"doi":1066},"10.1007\u002FBF00019248",{"id":18,"text":1068,"url":18,"identifiers":1069},"Malcolm, R.L., and Durum, W.H. (1976). Organic Carbon and Nitrogen Concentration and Annual Carbon Load of Six Selected Rivers in United States, U.S. Government Printing Office.",{},{"id":18,"text":1071,"url":18,"identifiers":1072},"Dittmar, 2003, Recalcitrant dissolved organic matter in the ocean: Major contribution of small amphiphilics, Mar. Chem., 82, 115, 10.1016\u002FS0304-4203(03)00068-9",{"doi":1073},"10.1016\u002FS0304-4203(03)00068-9",{"id":18,"text":1075,"url":18,"identifiers":1076},"Hedges, 1997, What happens to terrestrial organic matter in the ocean?, Org. Geochem., 27, 195, 10.1016\u002FS0146-6380(97)00066-1",{"doi":1077},"10.1016\u002FS0146-6380(97)00066-1",{"id":18,"text":1079,"url":18,"identifiers":1080},"Benner, 1995, Bacterial carbon metabolism in the Amazon River system, Limnol. Oceanogr., 40, 1262, 10.4319\u002Flo.1995.40.7.1262",{"doi":1081},"10.4319\u002Flo.1995.40.7.1262",{"id":18,"text":1083,"url":18,"identifiers":1084},"Miller, 1997, Interaction of photochemical and microbial processes in the degradation of refractory dissolved organic matter from a coastal marine environment, Limnol. Oceanogr., 42, 1317, 10.4319\u002Flo.1997.42.6.1317",{"doi":1085},"10.4319\u002Flo.1997.42.6.1317",{"id":18,"text":1087,"url":18,"identifiers":1088},"Opsahl, 1997, Distribution and cycling of terrigenous dissolved organic matter in the ocean, Nature, 386, 480, 10.1038\u002F386480a0",{"doi":1089},"10.1038\u002F386480a0",{"id":18,"text":1091,"url":18,"identifiers":1092},"Coffin, 1999, Stable isotope analysis of carbon cycling in the Perdido Estuary, Florida, Estuaries, 22, 917, 10.2307\u002F1353071",{"doi":1093},"10.2307\u002F1353071",{"id":18,"text":1095,"url":18,"identifiers":1096},"Raymond, 2001, DOC cycling in a temperate estuary: A mass balance approach using natural 14C and 13C isotopes, Limnol. Oceanogr., 46, 655, 10.4319\u002Flo.2001.46.3.0655",{"doi":1097},"10.4319\u002Flo.2001.46.3.0655",{"id":18,"text":1099,"url":18,"identifiers":1100},"Hammer, D.A. (1989). Constructed Wetlands for Wastewater Treatment, Lewis Publishers.",{},{"id":18,"text":1102,"url":18,"identifiers":1103},"Benner, 2001, Molecular indicators of the sources and transformations of dissolved organic matter in the Mississippi river plume, Org. Geochem., 32, 597, 10.1016\u002FS0146-6380(00)00197-2",{"doi":1104},"10.1016\u002FS0146-6380(00)00197-2",{"id":18,"text":1106,"url":18,"identifiers":1107},"(1987). Farm Drainage in the United States: History, Status, and Prospects; Economic Research Service, Miscellaneous Publ. No. 1455.",{},{"id":18,"text":1109,"url":18,"identifiers":1110},"Goolsby, D.A., Battaglin, W.A., Lawrence, G.B., Artz, R.S., Aulenbach, B.T., and Hooper, R.P. (1999). Flux and Sources of Nutrients in the Mississippi-Atchafalaya Basin; Topic 3 Report for the Integrated Assessment on Hypoxia in the Gulf of Mexico. Silver Spring (MD), NOAA Coastal Ocean Office.",{},{"id":18,"text":1112,"url":18,"identifiers":1113},"Donner, S.D., Kucharik, C.J., and Foley, J.A. (2004). Impact of changing land use practices on nitrate export by the Mississippi River. Glob. Biogeochem. Cycles, 18, Article No. GB1028.",{"doi":1114},"10.1029\u002F2003GB002093",{"id":18,"text":1116,"url":18,"identifiers":1117},"Kadlec, R.H., and Knight, R.L. (1996). Treatment Wetlands, Lewis Publishers.",{},{"id":18,"text":1119,"url":18,"identifiers":1120},"Donner, S.D., Kucharik, C.J., and Oppenheimer, M. (2004). The influence of climate on in-stream removal of nitrogen. Geophys. Res. Lett., 31, Article No. L20509.",{"doi":1121},"10.1029\u002F2004GL020477",{"id":18,"text":1123,"url":18,"identifiers":1124},"Banasik, K., Horowitz, A., Owens, P.N., Stone, M., and Walling, D.E. (2010). Sediment Dynamics for a Changing Future.",{},{"id":18,"text":1126,"url":18,"identifiers":1127},"Schepers, J.S., and Raun, W.R. (2008). Nitrogen in Agricultural Systems. Agronomy Monograph 49, American Society of Agronomy, Crop Science Society of America, Soil Science Society of America.",{"doi":1128},"10.2134\u002Fagronmonogr49",{"id":18,"text":1130,"url":18,"identifiers":1131},"Seitzinger, 1988, Denitrification in fresh-water and coastal marine ecosystems—Ecological and geochemical significance, Limnol. Oceanogr., 33, 702, 10.4319\u002Flo.1988.33.4_part_2.0702",{"doi":1132},"10.4319\u002Flo.1988.33.4_part_2.0702",{"id":18,"text":1134,"url":18,"identifiers":1135},"Knight, 1999, The use of treatment wetlands for petroleum industry effluents, Environ. Sci. Technol., 33, 973, 10.1021\u002Fes980740w",{"doi":1136},"10.1021\u002Fes980740w",{"id":18,"text":1138,"url":18,"identifiers":1139},"BryantMason, 2013, Limited capacity of river corridor wetlands to remove nitrate: A case study on the Atchafalaya River Basin during the 2011 Mississippi River Flooding, Water Resour. Res., 49, 283, 10.1029\u002F2012WR012185",{"doi":1140},"10.1029\u002F2012WR012185",{"id":18,"text":1142,"url":18,"identifiers":1143},"Sprague, 2011, Nitrate in the Mississippi River and its tributaries, 1980 to 2008: Are we making progress?, Environ. Sci. Technol., 45, 7209, 10.1021\u002Fes201221s",{"doi":1144},"10.1021\u002Fes201221s",{"id":18,"text":1146,"url":18,"identifiers":1147},"Alexander, 2000, Effect of stream channel size on the delivery of nitrogen to the Gulf of Mexico, Nature, 403, 758, 10.1038\u002F35001562",{"doi":1148},"10.1038\u002F35001562",{"id":1150,"createTime":1151,"updateTime":1152,"relativeEntities":1153,"slug":1154,"properties":1155,"entityType":141,"verifyStatus":17,"verifyTime":1152,"verifyNote":1162,"languages":18,"translateLanguages":18,"viewCount":19,"primaryUrl":1163,"fullTextUrl":1164,"authors":1165,"publicationType":214,"publisherRelationship":1225,"citationCount":18,"citationInfo":18,"publishDate":1286,"publishYear":1287,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":1288,"openAccess":18,"references":18,"isForceReanalyzing":528},"7bf094ef-972f-4cd7-b429-faa67f8d9007","2023-12-26T01:15:26.783+00:00","2025-02-25T02:08:50.865+00:00",[],"Flood-Susceptibility-Mapping-Using-GIS-Based-Analytic-Network-Process-A-Case-Study-of-Perlis-Malaysia",{"title":1156,"doi":1158,"abstract":1160},{"EN":1157},"Flood Susceptibility Mapping Using GIS-Based Analytic Network Process: A Case Study of Perlis, Malaysia",{"VOID":1159},"10.3390\u002Fw11030615",{"EN":1161},"Understanding factors associated with flood incidence could facilitate flood disaster control and management. This paper assesses flood susceptibility of Perlis, Malaysia for reducing and managing their impacts on people and the environment. The study used an integrated approach that combines geographic information system (GIS), analytic network process (ANP), and remote sensing (RS) derived variables for flood susceptibility assessment and mapping. Based on experts’ opinion solicited via ANP survey questionnaire, the ANP mathematical model was used to calculate the relative weights of the various flood influencing factors. The ArcGIS spatial analyst tools were used in generating flood susceptible zones. The study found zones that are very highly susceptible to flood (VHSF) and those highly susceptible to flood (HSF) covering 38.4% (30,924.6 ha) and 19.0% (15,341.1 ha) of the study area, respectively. The results were subjected to one-at-a-time (OAT) sensitivity analysis to verify their stability, where 6 out of the 22 flood scenarios correlated with the simulated spatial assessment of flood susceptibility. The findings were further validated using real-life flood incidences in the study area obtained from satellite images, which confirmed that most of the flooded areas were distributed over the VHSF and HSF zones. This integrated approach enables network model structuring, and reflects the interdependences among real-life flood influencing factors. This accurate identification of flood prone areas could serve as an early warning mechanism. The approach can be replicated in cities facing flood incidences in identifying areas susceptible to flooding for more effective flood disaster control.","Author affiliation is blank","https:\u002F\u002Fwww.mdpi.com\u002F2073-4441\u002F11\u002F3\u002F615","https:\u002F\u002Fwww.mdpi.com\u002F2073-4441\u002F11\u002F3\u002F615\u002Fpdf?version=1553511738",[1166,1174,1181,1188,1195,1202,1209,1217],{"id":1167,"sortIndex":19,"researcher":18,"roles":1168,"affiliations":1170,"properties":1171},"ada8e7ce-6e19-47f5-94d1-94fbe79fb9be",[1169],"AUTHOR",[],{"title":1172},{"VI":1173},"Dano, Umar Lawal",{"id":1175,"sortIndex":107,"researcher":18,"roles":1176,"affiliations":1177,"properties":1178},"b6c90a4a-49a8-46b3-9bc2-6cc44c6f39f1",[1169],[],{"title":1179},{"VI":1180},"Balogun, Abdul-Lateef",{"id":1182,"sortIndex":104,"researcher":18,"roles":1183,"affiliations":1184,"properties":1185},"9d7bcf69-bdf4-40da-9eb1-a492b95f6829",[1169],[],{"title":1186},{"VI":1187},"Matori, Abdul-Nasir",{"id":1189,"sortIndex":108,"researcher":18,"roles":1190,"affiliations":1191,"properties":1192},"7a0b6b0b-a5b4-4872-8ef7-993f39ddd347",[1169],[],{"title":1193},{"VI":1194},"Wan Yusouf, Khmaruzzaman",{"id":1196,"sortIndex":1013,"researcher":18,"roles":1197,"affiliations":1198,"properties":1199},"0fcec66d-cce0-4be1-96ac-b1da28ab6c8f",[1169],[],{"title":1200},{"VI":1201},"Abubakar, Ismaila Rimi",{"id":1203,"sortIndex":1012,"researcher":18,"roles":1204,"affiliations":1205,"properties":1206},"13f56386-8b12-47e3-b8a8-b23ae37db538",[1169],[],{"title":1207},{"VI":1208},"Said Mohamed, Mohamed Ahmed",{"id":1210,"sortIndex":1211,"researcher":18,"roles":1212,"affiliations":1213,"properties":1214},"1ecafa8f-8fc9-4dcd-ba76-a8b8eb00ef3d",6,[1169],[],{"title":1215},{"VI":1216},"Aina, Yusuf Adedoyin",{"id":1218,"sortIndex":1219,"researcher":18,"roles":1220,"affiliations":1221,"properties":1222},"44cdd280-89f5-4ec9-b084-fa478b31ebdc",7,[1169],[],{"title":1223},{"VI":1224},"Pradhan, Biswajeet",{"url":1163,"publisher":1226,"properties":1279},{"id":6,"createTime":7,"updateTime":8,"relativeEntities":1227,"slug":10,"properties":1228,"entityType":16,"verifyStatus":17,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":19,"subjectFields":1231,"manageAffiliations":1248,"indexDatabases":1259,"url":18,"thumbnailPath":18,"statistic":1274,"gsStatistic":18,"type":18,"analyzePriority":18},[],{"title":1229,"eissn":1230},{"EN":13},{"VOID":15},[1232,1236,1240,1244],{"id":22,"createTime":18,"updateTime":18,"relativeEntities":1233,"label":1234,"description":1235,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":25},{},{"id":28,"createTime":18,"updateTime":18,"relativeEntities":1237,"label":1238,"description":1239,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":31},{},{"id":34,"createTime":18,"updateTime":18,"relativeEntities":1241,"label":1242,"description":1243,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":37},{},{"id":40,"createTime":18,"updateTime":18,"relativeEntities":1245,"label":1246,"description":1247,"parentId":18,"standard":18,"scholarHubFieldId":18},[],{"EN":43},{},[1249,1254],{"id":47,"createTime":18,"updateTime":18,"relativeEntities":1250,"slug":18,"properties":1251,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1253,"statistic":18},[],{"title":1252},{"EN":51},[],{"id":54,"createTime":18,"updateTime":18,"relativeEntities":1255,"slug":18,"properties":1256,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":1258,"statistic":18},[],{"title":1257},{"EN":58},[],[1260,1267],{"id":62,"indexDatabase":1261,"url":75,"indexYears":18,"academicFieldIds":1266,"indexDatabaseRanking":18},{"id":64,"createTime":18,"updateTime":18,"relativeEntities":1262,"label":1263,"description":1264,"key":71,"publicationTags":1265,"standard":18},[],{"EN":67,"VI":67},{"EN":69,"VI":70},[73,74],[77,78],{"id":80,"indexDatabase":1268,"url":91,"indexYears":92,"academicFieldIds":1273,"indexDatabaseRanking":98},{"id":82,"createTime":18,"updateTime":18,"relativeEntities":1269,"label":1270,"description":1271,"key":88,"publicationTags":1272,"standard":18},[],{"EN":85,"VI":85},{"EN":85,"VI":87},[90],[94,95,96,97],{"impactFactor":19,"impactFactorByYear":1275,"i10Index":103,"i10IndexLast5Year":104,"totalPublication":105,"totalPublicationByYear":1276,"totalCitation":109,"totalCitationByYear":1277,"totalCitationPerPublication":114,"totalCitationPerPublicationByYear":1278,"hindexLast5Year":117,"hindex":117},{"2021":101,"2022":102},{"2017":107,"2019":108,"2020":107},{"2017":111,"2019":112,"2020":113},{"2017":111,"2019":116,"2020":113},{"issue":1280,"pages":1282,"volume":1284},{"VOID":1281},"3",{"VOID":1283},"615",{"VOID":1285},"11","2019-03-01",2019,[73,98],{"id":1290,"createTime":1291,"updateTime":1292,"relativeEntities":1293,"slug":1294,"properties":1295,"entityType":141,"verifyStatus":17,"verifyTime":1292,"verifyNote":1162,"languages":18,"translateLanguages":1308,"viewCount":19,"primaryUrl":1309,"fullTextUrl":1310,"authors":1311,"publicationType":214,"publisherRelationship":1337,"citationCount":1398,"citationInfo":1399,"publishDate":1402,"publishYear":1400,"citationAnalyzeStatus":1403,"lastCitationAnalyze":1404,"indexDatabases":1405,"openAccess":18,"references":18,"isForceReanalyzing":528},"95aeae24-067c-4667-b263-636b8845f5d5","2024-02-20T22:17:19.493+00:00","2025-02-22T02:37:17.565+00:00",[],"Surface-Water-Monitoring-within-Cambodia-and-the-Vietnamese-Mekong-Delta-over-a-Year-with-Sentinel-1-SAR-Observations",{"abstract":1296,"title":1299,"gsPaper":1302,"keywords":1304,"doi":1306},{"EN":1297,"VI":1298},"This study presents a methodology to detect and monitor surface water with Sentinel-1 Synthetic Aperture Radar (SAR) data within Cambodia and the Vietnamese Mekong Delta. It is based on a neural network classification trained on Landsat-8 optical data. Sensitivity tests are carried out to optimize the performance of the classification and assess the retrieval accuracy. Predicted SAR surface water maps are compared to reference Landsat-8 surface water maps, showing a true positive water detection of ∼90% at 30 m spatial resolution. Predicted SAR surface water maps are also compared to floodability maps derived from high spatial resolution topography data. Results show high consistency between the two independent maps with 98% of SAR-derived surface water located in areas with a high probability of inundation. Finally, all available Sentinel-1 SAR observations over the Mekong Delta in 2015 are processed and the derived surface water maps are compared to corresponding MODIS\u002FTerra-derived surface water maps at 500 m spatial resolution. Temporal correlation between these two products is very high (99%) with very close water surface extents during the dry season when cloud contamination is low. This study highlights the applicability of the Sentinel-1 SAR data for surface water monitoring, especially in a tropical region where cloud cover can be very high during the rainy seasons.","Nghiên cứu này trình bày một phương pháp để phát hiện và giám sát nước mặt bằng dữ liệu Radar Khẩu độ Tổng hợp (SAR) của Sentinel-1 tại Campuchia và Đồng bằng sông Cửu Long ở Việt Nam. Phương pháp này dựa trên phân loại mạng nơ-ron được huấn luyện với dữ liệu quang học Landsat-8. Các thử nghiệm độ nhạy được thực hiện để tối ưu hóa hiệu suất phân loại và đánh giá độ chính xác truy xuất. Các bản đồ nước mặt dự đoán từ SAR được so sánh với bản đồ nước mặt tham chiếu từ Landsat-8, cho thấy tỷ lệ phát hiện nước đúng khẳng định khoảng 90% ở độ phân giải không gian 30 m. Bản đồ nước mặt dự đoán từ SAR cũng được so sánh với bản đồ nguy cơ ngập lụt được suy diễn từ dữ liệu địa hình có độ phân giải không gian cao. Kết quả cho thấy sự đồng nhất cao giữa hai bản đồ độc lập với 98% diện tích nước mặt từ SAR được tìm thấy tại những khu vực có khả năng ngập lụt cao. Cuối cùng, tất cả các quan sát Sentinel-1 SAR có tại Đồng bằng sông Cửu Long trong năm 2015 được xử lý và các bản đồ nước mặt được suy ra được so sánh với các bản đồ nước mặt tương ứng được suy ra từ MODIS\u002FTerra ở độ phân giải không gian 500 m. Mối tương quan thời gian giữa hai sản phẩm này rất cao (99%) với diện tích bề mặt nước rất gần nhau trong mùa khô khi ô nhiễm mây thấp. Nghiên cứu này nhấn mạnh khả năng ứng dụng của dữ liệu Sentinel-1 SAR trong giám sát nước mặt, đặc biệt là ở những vùng nhiệt đới nơi mà độ bao phủ mây có thể rất cao trong các mùa mưa.",{"EN":1300,"VI":1301},"Surface Water Monitoring within Cambodia and the Vietnamese Mekong Delta over a Year, with Sentinel-1 SAR Observations","Giám sát nước mặt tại Campuchia và Đồng bằng sông Cửu Long ở Việt Nam trong vòng một năm, với quan sát Sentinel-1 SAR",{"VOID":1303},"4248434711180304940",{"VI":1305},"giám sát nước mặt, Sentinel-1, SAR, Đồng bằng sông Cửu Long, Campuchia, Landsat-8, độ phân giải không gian, ngập lụt, nhiệt đới, 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Coat., 133, 27, 10.1016\u002Fj.porgcoat.2019.03.049",{"doi":1751},"10.1016\u002Fj.porgcoat.2019.03.049",{"id":18,"text":1753,"url":18,"identifiers":1754},"Padaki, 2011, Conversion of Microfiltration Membrane into Nanofiltration Membrane by Vapour Phase Deposition of Aluminium for Desalination Application, Desalination, 274, 177, 10.1016\u002Fj.desal.2011.02.007",{"doi":1755},"10.1016\u002Fj.desal.2011.02.007",{"id":18,"text":1757,"url":18,"identifiers":1758},"Liravi, 2020, A Comprehensive Review on Recent Advances in Superhydrophobic Surfaces and Their Applications for Drag Reduction, Prog. Org. 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The study employs six indices defined by the Expert Team on Climate Change Detection Indices to evaluate extreme precipitation. Observed datasets and Coupled Model Intercomparison Project Phase six (CMIP6) simulations are employed to assess the changes during the two main rainfall seasons: March to May (MAM) and October to December (OND). The results show an increase in consecutive dry days (CDD) and decrease in consecutive wet days (CWD) towards the end of the 21st century (2081–2100) relative to the baseline period (1995–2014) in both seasons. Moreover, simple daily intensity (SDII), very wet days (R95 p), very heavy precipitation >20 mm (R20 mm), and total wet-day precipitation (PRCPTOT) demonstrate significant changes during OND compared to the MAM season. The spatial variation for extreme incidences shows likely intensification over Uganda and most parts of Kenya, while a reduction is observed over the Tanzania region. The increase in projected extremes may pose a serious threat to the sustainability of societal infrastructure and ecosystem wellbeing. The results from these analyses present an opportunity to understand the emergence of extreme events and the capability of model outputs from CMIP6 in estimating the projected changes. 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Clim., 27, 7185, 10.1175\u002FJCLI-D-13-00447.1",{"doi":2274},"10.1175\u002FJCLI-D-13-00447.1",{"id":18,"text":2276,"url":18,"identifiers":2277},"Lyon, 2012, A recent and abrupt decline in the East African long rains, Geophys. Res. Lett., 39, 02702, 10.1029\u002F2011GL050337",{"doi":2278},"10.1029\u002F2011GL050337",{"id":18,"text":2280,"url":18,"identifiers":2281},"Nicholson, 2017, Climate and climatic variability of rainfall over eastern Africa, Rev. Geophys., 55, 590, 10.1002\u002F2016RG000544",{"doi":2282},"10.1002\u002F2016RG000544",{"id":18,"text":2284,"url":18,"identifiers":2285},"Camberlin, P. (2018). Climate of Eastern Africa. Oxford Research Encyclopedia of Climate Science, Oxford University Press (OUP).",{"doi":2286},"10.1093\u002Facrefore\u002F9780190228620.013.512",{"id":18,"text":2288,"url":18,"identifiers":2289},"Adhikari, 2015, Climate change and eastern Africa: A review of impact on major crops, Food Energy Secur., 4, 110, 10.1002\u002Ffes3.61",{"doi":2290},"10.1002\u002Ffes3.61",{"id":18,"text":2292,"url":18,"identifiers":2293},"Mumo, 2018, Assessing Impacts of Seasonal Climate Variability on Maize Yield in Kenya, Int. J. Plant Prod., 12, 297, 10.1007\u002Fs42106-018-0027-x",{"doi":2294},"10.1007\u002Fs42106-018-0027-x",{"id":18,"text":2296,"url":18,"identifiers":2297},"Dike, V., Lin, Z.-H., and Ibe, C. (2020). Intensification of Summer Rainfall Extremes over Nigeria during Recent Decades. Atmosphere, 11.",{"doi":2298},"10.3390\u002Fatmos11101084",{"id":18,"text":2300,"url":18,"identifiers":2301},"Dosio, A., Jury, M.W., Almazroui, M., Ashfaq, M., Diallo, I., Engelbrecht, F.A., Klutse, N.A.B., Lennard, C., Pinto, I., and Sylla, M.B. (2021). Projected future daily characteristics of African precipitation based on global (CMIP5, CMIP6) and regional (CORDEX, CORDEX-CORE) climate models. Clim. Dyn., 1–24.",{"doi":2302},"10.1007\u002Fs00382-021-05859-w",{"id":18,"text":2304,"url":18,"identifiers":2305},"Mafuru, 2020, The influence of ENSO on the upper warm temperature anomaly formation associated with the March–May heavy rainfall events in Tanzania, Int. J. Clim., 40, 2745, 10.1002\u002Fjoc.6364",{"doi":2306},"10.1002\u002Fjoc.6364",{"id":18,"text":2308,"url":18,"identifiers":2309},"Maidment, 2015, Recent observed and simulated changes in precipitation over Africa, Geophys. Res. Lett., 42, 8155, 10.1002\u002F2015GL065765",{"doi":2310},"10.1002\u002F2015GL065765",{"id":18,"text":2312,"url":18,"identifiers":2313},"Xu, H., Chen, H., and Wang, H. (2021). Future changes in precipitation extremes across China based on CMIP6 models. Int. J. Clim.",{"doi":2314},"10.1002\u002Fjoc.7264",{"id":18,"text":2316,"url":18,"identifiers":2317},"Gu, 2013, Interdecadal variability\u002Flong-term changes in global precipitation patterns during the past three decades: Global warming and\u002For pacific decadal variability?, Clim. Dyn., 40, 3009, 10.1007\u002Fs00382-012-1443-8",{"doi":2318},"10.1007\u002Fs00382-012-1443-8",{"id":18,"text":2320,"url":18,"identifiers":2321},"Dai, 2016, Future Warming Patterns Linked to Today’s Climate Variability, Sci. Rep., 6, 6",{},{"id":18,"text":2323,"url":18,"identifiers":2324},"Hua, 2016, Possible causes of the Central Equatorial Af-rican long-term drought, Environ. Res. Lett., 11, 124002, 10.1088\u002F1748-9326\u002F11\u002F12\u002F124002",{"doi":2325},"10.1088\u002F1748-9326\u002F11\u002F12\u002F124002",{"id":18,"text":2327,"url":18,"identifiers":2328},"Ongoma, 2019, Evaluation of CMIP5 twentieth century rainfall simulation over the equatorial East Africa, Theor. Appl. Clim., 135, 893, 10.1007\u002Fs00704-018-2392-x",{"doi":2329},"10.1007\u002Fs00704-018-2392-x",{"id":18,"text":2331,"url":18,"identifiers":2332},"Onyutha, C., Asiimwe, A., Ayugi, B., Ngoma, H., Ongoma, V., and Tabari, H. (2021). Observed and Future Precipitation and Evapotranspiration in Water Management Zones of Uganda: CMIP6 Projections. Atmosphere, 12.",{"doi":2333},"10.3390\u002Fatmos12070887",{"id":18,"text":2335,"url":18,"identifiers":2336},"Cattani, E., Merino, A., Guijarro, J.A., and Levizzani, V. (2018). East Africa Rainfall Trends and Variability 1983–2015 Using Three Long-Term Satellite Products. Remote Sens., 10.",{"doi":2337},"10.3390\u002Frs10060931",{"id":18,"text":2339,"url":18,"identifiers":2340},"Endris, 2018, Future changes in rainfall associated with ENSO, IOD and changes in the mean state over Eastern Africa, Clim. Dyn., 52, 2029, 10.1007\u002Fs00382-018-4239-7",{"doi":2341},"10.1007\u002Fs00382-018-4239-7",{"id":18,"text":2343,"url":18,"identifiers":2344},"Ayugi, B., Tan, G., Niu, R., Babaousmail, H., Ojara, M., Wido, H., Mumo, L., Nooni, I., and Ongoma, V. (2020). Quantile Mapping Bias Correction on Rossby Centre Regional Climate Models for Precipitation Analysis over Kenya, East Africa. Water, 12.",{"doi":2345},"10.20944\u002Fpreprints202001.0119.v1",{"id":18,"text":2347,"url":18,"identifiers":2348},"Karim, R., Tan, G., Ayugi, B., Babaousmail, H., and Liu, F. (2020). Evaluation of Historical CMIP6 Model Simulations of Seasonal Mean temperature over Pakistan during 1970–2014. Atmosphere, 11.",{"doi":2349},"10.3390\u002Fatmos11091005",{"id":18,"text":2351,"url":18,"identifiers":2352},"Sian, K.L.K., Wang, J., Ayugi, B., Nooni, I., and Ongoma, V. (2021). Multi-Decadal Variability and Future Changes in Precipitation over Southern Africa. Atmosphere, 12.",{"doi":2353},"10.3390\u002Fatmos12060742",{"id":18,"text":2355,"url":18,"identifiers":2356},"Ngoma, H., Wen, W., Ayugi, B., Babaousmail, H., Karim, R., and Ongoma, V. (2021). Evaluation of precipitation simulations in CMIP6 models over Uganda. Int. J. Clim.",{"doi":2357},"10.1002\u002Fjoc.7098",{"id":18,"text":2359,"url":18,"identifiers":2360},"Babaousmail, H., Hou, R., Ayugi, B., Ojara, M., Ngoma, H., Karim, R., Rajasekar, A., and Ongoma, V. (2021). Evaluation of the Performance of CMIP6 Models in Reproducing Rainfall Patterns over North Africa. Atmosphere, 12.",{"doi":2361},"10.3390\u002Fatmos12040475",{"id":18,"text":2363,"url":18,"identifiers":2364},"Knutti, 2013, Robustness and uncertainties in the new CMIP5 climate model projections, Nat. Clim. Chang., 3, 369, 10.1038\u002Fnclimate1716",{"doi":2365},"10.1038\u002Fnclimate1716",{"id":2367,"createTime":2368,"updateTime":2368,"relativeEntities":2369,"slug":2370,"properties":2371,"entityType":141,"verifyStatus":142,"verifyTime":2368,"verifyNote":144,"languages":2380,"translateLanguages":18,"viewCount":19,"primaryUrl":2381,"fullTextUrl":18,"authors":2382,"publicationType":214,"publisherRelationship":2435,"citationCount":1211,"citationInfo":2495,"publishDate":18,"publishYear":18,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":2497,"openAccess":18,"references":2498,"isForceReanalyzing":528},"72c481f6-b807-4b51-bbac-e07d848eae6a","2025-02-10T16:42:39.823+00:00",[],"Future-Changes-in-the-Surface-Water-Balance-over-Western-Canada-Using-the-CanESM5-CMIP6-Ensemble-for-the-Shared-Socioeconomic-Pathways-5-Scenario",{"openalex":2372,"abstract":2374,"title":2376,"doi":2378},{"VOID":2373},"W4214675834",{"EN":2375},"\u003Cjats:p>The Prairie provinces of Canada have about 80% of Canada’s agricultural land and contribute to more than 90% of the nation’s wheat and canola production. A future change in the surface water balance over this region could seriously affect Canada’s agro-economy. In this study, we examined 25 ensemble members of historical (1975 to 2005), near future (2021–2050), far future (2050–2080), and end of the century (2080–2100) simulations of the Canadian Earth System Model version 5 (CanESM5) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). A comprehensive analysis of a new Net Water Balance Index (NWBI) indicates an increased growing season dryness despite increased total precipitation over the Prairie provinces. Evapotranspiration increases by 100–300 mm with a 10–20% increase in moisture loss due to transpiration. Total evaporation decreases by 15–20% as the fractional contribution of evaporation from soil decreases by 20–25%. Total evaporation from vegetation increases by 10–15%. These changes in the surface water balance suggest enhanced plant productivity when soil moisture is sufficient, but evaporative water loss that exceeds precipitation in most years.\u003C\u002Fjats:p>",{"EN":2377},"Future Changes in the Surface Water Balance over Western Canada Using the CanESM5 (CMIP6) Ensemble for the Shared Socioeconomic Pathways 5 Scenario",{"VOID":2379},"10.3390\u002Fw14050691",[146],"https:\u002F\u002Fwww.mdpi.com\u002F2073-4441\u002F14\u002F5\u002F691",[2383,2410],{"id":2384,"sortIndex":19,"researcher":18,"roles":2385,"affiliations":2386,"properties":2403},"e25f9e27-0b7b-4e1b-9f22-1f16bc7fb6f3",[],[2387,2395],{"id":2388,"sortIndex":19,"affiliation":2389,"properties":18},"4074942f-eb4e-4fc9-90ff-e071e1bb3b0b",{"id":2388,"createTime":18,"updateTime":18,"relativeEntities":2390,"slug":18,"properties":2391,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2394,"statistic":18},[],{"title":2392},{"EN":2393},"International Arctic Research Center, Fairbanks, AK 99775, USA",[],{"id":2396,"sortIndex":107,"affiliation":2397,"properties":18},"c5413bf3-7293-4daa-b2fd-12e1013559fe",{"id":2396,"createTime":18,"updateTime":18,"relativeEntities":2398,"slug":18,"properties":2399,"entityType":18,"verifyStatus":18,"verifyTime":18,"verifyNote":18,"languages":18,"translateLanguages":18,"viewCount":18,"url":18,"parentIds":2402,"statistic":18},[],{"title":2400},{"EN":2401},"Prairie Adaptation Research Collaborative, University of Regina, Regina, SK S4S 0A2, Canada",[],{"orcid":2404,"title":2406,"openalex":2408},{"VOID":2405},"https:\u002F\u002Forcid.org\u002F0000-0001-9351-8092",{"EN":2407},"S. 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Available online: https:\u002F\u002Fwww.fcc-fac.ca\u002Ffcc\u002Fresources\u002Ftrade-rankings-report-2019-e.pdf.",{},{"id":18,"text":2503,"url":18,"identifiers":2504},"Sauchyn, D., Davidson, D., and Johnston, M. (2017). Prairie Provinces, Chapter 4 in Canada in a Changing Climate: Regional Perspectives Report.",{},{"id":18,"text":2506,"url":18,"identifiers":2507},"Zhang, X., Flato, G., Kirchmeier-Young, M., Vincent, L.A., Wan, H., Wang, X., Rong, R., Fyfe, J.C., Li, G., and Kharin, V.V. (2022, January 11). Changes in temperature and precipitation across Canada, Canada’s Changing Climate Report, Available online: https:\u002F\u002Fwww.nrcan.gc.ca\u002Fsites\u002Fwww.nrcan.gc.ca\u002Ffiles\u002Fenergy\u002FClimate-change\u002Fpdf\u002FCCCR_Chapter4-Temperature%20and%20Precipitation%20Across%20Canada.pdf.",{},{"id":18,"text":2509,"url":18,"identifiers":2510},"Gillet, N., Flato, G., Zhang, X., Derksen, C., Bonsal, B., Greenan, B., Bush, E., Shepherd, M., Peters, D., and Gilbert, D. (2019). Canada’s Changing Climate Report.",{},{"id":18,"text":2512,"url":18,"identifiers":2513},"Vincent, 2018, Changes in Canada’s Climate: Trends in Indices Based on Daily Temperature and Precipitation Data, Atmos. Ocean, 56, 332, 10.1080\u002F07055900.2018.1514579",{"doi":2514},"10.1080\u002F07055900.2018.1514579",{"id":18,"text":2516,"url":18,"identifiers":2517},"Kerr, S., Andreichuk, Y., and Sauchyn, D. (2019). Re-Evaluating the Climate Factor in Agricultural Land Assessment in a Changing Climate—Saskatchewan, Canada. Land, 8.",{"doi":2518},"10.3390\u002Fland8030049",{"id":18,"text":2520,"url":18,"identifiers":2521},"Qian, 2019, Climate change impacts on Canadian yields of spring wheat, canola and maize for global warming levels of 1.5 °C, 2.0 °C, 2.5 °C and 3.0 °C, Environ. Res. Lett., 14, 074005, 10.1088\u002F1748-9326\u002Fab17fb",{"doi":2522},"10.1088\u002F1748-9326\u002Fab17fb",{"id":18,"text":2524,"url":18,"identifiers":2525},"Qian, 2018, Simulated canola yield responses to climate change and adaptation in Canada, Agron. J., 110, 133, 10.2134\u002Fagronj2017.02.0076",{"doi":2526},"10.2134\u002Fagronj2017.02.0076",{"id":18,"text":2528,"url":18,"identifiers":2529},"Qian, 2016, Projecting yield changes of spring wheat under future climate scenarios on the Canadian Prairies, Theor. Appl. Climatol., 123, 651, 10.1007\u002Fs00704-015-1378-1",{"doi":2530},"10.1007\u002Fs00704-015-1378-1",{"id":18,"text":2532,"url":18,"identifiers":2533},"Kurkute, 2020, Assessment and projection of the water budget over western Canada using convection-permitting weather research and forecasting simulations, Hydrol. Earth Syst. Sci., 24, 3677, 10.5194\u002Fhess-24-3677-2020",{"doi":2534},"10.5194\u002Fhess-24-3677-2020",{"id":18,"text":2536,"url":18,"identifiers":2537},"Newton, B.W., Farjad, B., and Orwin, J.F. (2021). Spatial and temporal shifts in historic and future temperature and precipitation patterns related to snow accumulation and melt regimes in Alberta, Canada. Water, 13.",{"doi":2538},"10.3390\u002Fw13081013",{"id":18,"text":2245,"url":18,"identifiers":2540},{"doi":2247},{"id":18,"text":2542,"url":18,"identifiers":2543},"Swart, 2019, The Canadian Earth System Model version 5 (CanESM5.0.3), Geosci. Model Dev., 12, 4823, 10.5194\u002Fgmd-12-4823-2019",{"doi":2544},"10.5194\u002Fgmd-12-4823-2019",{"id":18,"text":2546,"url":18,"identifiers":2547},"Tebaldi, 2016, The Scenario Model Intercomparison Project (ScenarioMIP) for CMIP6, Geosci. Model Dev., 9, 3461, 10.5194\u002Fgmd-9-3461-2016",{"doi":2548},"10.5194\u002Fgmd-9-3461-2016",{"id":18,"text":2550,"url":18,"identifiers":2551},"Riahi, 2017, The Shared Socioeconomic Pathways and their energy, land use, and greenhouse gas emissions implications: An overview, Glob. Environ. Chang., 42, 153, 10.1016\u002Fj.gloenvcha.2016.05.009",{"doi":2552},"10.1016\u002Fj.gloenvcha.2016.05.009",{"id":18,"text":2554,"url":18,"identifiers":2555},"Woodcock, 2018, Canadian boreal forest greening and browning trends: An analysis of biogeographic patterns and the relative roles of disturbance versus climate drivers, Environ. Res. Lett., 13, 014007, 10.1088\u002F1748-9326\u002Faa9b88",{"doi":2556},"10.1088\u002F1748-9326\u002Faa9b88",{"id":18,"text":2558,"url":18,"identifiers":2559},"Espinoza, 2018, Global Analysis of Climate Change Projection Effects on Atmospheric Rivers, Geophys. Res. Lett., 45, 4299, 10.1029\u002F2017GL076968",{"doi":2560},"10.1029\u002F2017GL076968",{"id":18,"text":2562,"url":18,"identifiers":2563},"Anis, M.R., and Sauchyn, D.J. (2021). Ensemble Projection of Future Climate and Surface Water Supplies in the North Saskatchewan River Basin above Edmonton, Alberta, Canada. Water, 13.",{"doi":2564},"10.3390\u002Fw13172425",{"id":18,"text":2566,"url":18,"identifiers":2567},"Warner, 2017, Changes in the climatology, structure, and seasonality of northeast pacific atmospheric rivers in CMIP5 climate simulations, J. Hydrometeorol., 18, 2131, 10.1175\u002FJHM-D-16-0200.1",{"doi":2568},"10.1175\u002FJHM-D-16-0200.1",{"id":18,"text":2570,"url":18,"identifiers":2571},"Gameda, 2007, Climatic trends associated with summerfallow in the Canadian Prairies, Agric. For. Meteorol., 142, 170, 10.1016\u002Fj.agrformet.2006.03.026",{"doi":2572},"10.1016\u002Fj.agrformet.2006.03.026",{"id":18,"text":2574,"url":18,"identifiers":2575},"Betts, 2013, Impact of land use change on the diurnal cycle climate of the Canadian Prairies, J. Geophys. Res. Atmos., 118, 11996",{},{"id":18,"text":2577,"url":18,"identifiers":2578},"Li, 2018, Indices of Canada’s future climate for general and agricultural adaptation applications, Clim. Chang., 148, 249, 10.1007\u002Fs10584-018-2199-x",{"doi":2579},"10.1007\u002Fs10584-018-2199-x",{"id":2581,"createTime":2582,"updateTime":2582,"relativeEntities":2583,"slug":2584,"properties":2585,"entityType":141,"verifyStatus":142,"verifyTime":2596,"verifyNote":144,"languages":2597,"translateLanguages":18,"viewCount":19,"primaryUrl":2598,"fullTextUrl":18,"authors":2599,"publicationType":214,"publisherRelationship":2666,"citationCount":112,"citationInfo":2726,"publishDate":18,"publishYear":18,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":2729,"openAccess":18,"references":2730,"isForceReanalyzing":528},"f5eb8ba5-23f7-43b4-bc75-2d08142372cc","2025-02-04T01:05:25.672+00:00",[],"Filtering-Capability-of-Porous-Asphalt-Pavements",{"openalex":2586,"mag":2588,"abstract":2590,"title":2592,"doi":2594},{"VOID":2587},"W2793369560",{"VOID":2589},"2793369560",{"EN":2591},"\u003Cjats:p>The objective of this study is to assess the filtering capability of porous asphalt pavement models and the quality of rainwater filtered by such models. Three slabs of porous asphalt mixtures and two models composed of porous layers that resulted in porous pavement structures were produced. Data were collected in two phases: using rainwater directly from the sky and then using stormwater runoff collected from a street. Parameters such as pH, dissolved oxygen, ammonia, phosphorus, nitrite, aluminium, chromium, copper, zinc, and iron were measured. For both rainwater and stormwater runoff quality analyses, there was an increase in the concentration of the following parameters: phosphorus, iron, aluminium, zinc, nitrite, chromium, copper, and pH; there was no significant variation in the concentration of dissolved oxygen; and there was a decrease in ammonia in one of the models. However, the concentrations of only phosphorus and aluminium exceeded the limits established by the Brazilian National Environmental Council and National Water Agency for the use of non-potable water. The models were capable of filtering rainwater and stormwater runoff, and reducing the concentration of ammonia. It can be concluded that it is possible to collect stormwater runoff from porous asphalt surfaces and porous asphalt pavements. Porous asphalt pavements are able to filter out certain pollutants from stormwater runoff and rainwater, and were shown to be an alternative to supply rainwater for non-potable uses and to recharge the water table.\u003C\u002Fjats:p>",{"EN":2593},"Filtering Capability of Porous Asphalt 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2012, Quantifying the behavior of porous asphalt overlays with respect to drainage hydraulics and runoff water quality, Environ. Eng. Geosci., 18, 99, 10.2113\u002Fgseegeosci.18.1.99",{"doi":2734},"10.2113\u002Fgseegeosci.18.1.99",{"id":18,"text":2736,"url":18,"identifiers":2737},"Tilley, J.S., and Slonecker, T.E. (2017, May 23). Quantifying the Components of Impervious Surfaces, Available online: https:\u002F\u002Fpubs.usgs.gov\u002Fof\u002F2007\u002F1008\u002Fofr2007-1008.pdf.",{},{"id":18,"text":2739,"url":18,"identifiers":2740},"Green, 2012, Identification and induction of human, social, and cultural capitals through an experimental approach to stormwater management, Sustainability, 4, 1669, 10.3390\u002Fsu4081669",{"doi":2741},"10.3390\u002Fsu4081669",{"id":18,"text":2743,"url":18,"identifiers":2744},"2013, Sustainable drainage practices in Spain, specially focused on pervious Pavements, Water, 5, 67, 10.3390\u002Fw5010067",{"doi":2745},"10.3390\u002Fw5010067",{"id":18,"text":2747,"url":18,"identifiers":2748},"Schaus, L.K. (2007). Porous Asphalt Pavement Designs: Proactive Design for Cold Climate Use. [Master’s Thesis, University of Waterloo].",{},{"id":18,"text":2750,"url":18,"identifiers":2751},"Suzuki, C.Y., Azevedo, A.M., and Kabbach Júnior, F.I. (2013). Drenagem Subsuperficial de Pavimentos—Conceitos e Dimensionamento [Subsurface Drainage Pavements—Concepts and Design], Oficina de Textos. (In Portuguese).",{},{"id":18,"text":2753,"url":18,"identifiers":2754},"Boogaard, 2014, Evaluating the infiltration performance of eight Dutch permeable pavements using a new full-scale infiltration testing method, Water, 6, 2070, 10.3390\u002Fw6072070",{"doi":2755},"10.3390\u002Fw6072070",{"id":18,"text":2757,"url":18,"identifiers":2758},"Lucke, T., Beecham, S., Boogaard, F., and Baden, M. (2013, January 23–27). Are infiltration capacities of clogged permeable pavements still acceptable?. Proceedings of the NOVATECH 2013 International Conference on Planning and Technologies for Sustainable Management of Water in the City, Lyon, France.",{},{"id":18,"text":2760,"url":18,"identifiers":2761},"National Asphalt Pavement Association (NAPA) (2003). Porous Asphalt Pavement, National Asphalt Pavement Association.",{},{"id":18,"text":2763,"url":18,"identifiers":2764},"Huber, G. (2000). Performance Survey on Open-Graded Friction Course Mixes.",{},{"id":18,"text":2766,"url":18,"identifiers":2767},"Kiran, 2015, Sustainable approaches for stormwater quality improvements with experimental geothermal paving systems, Sustainability, 7, 1388, 10.3390\u002Fsu7021388",{"doi":2768},"10.3390\u002Fsu7021388",{"id":18,"text":2770,"url":18,"identifiers":2771},"Pratt, 1995, UK research into the performance of permeable pavement, reservoir structures in controlling stormwater discharge quantity and quality, Water Sci. Technol., 32, 63, 10.2166\u002Fwst.1995.0016",{"doi":2772},"10.2166\u002Fwst.1995.0016",{"id":18,"text":2774,"url":18,"identifiers":2775},"Kumar, 2016, In-situ infiltration performance of different permeable pavements in an employee used parking lot—A four-year study, J. Environ. Manag., 167, 8, 10.1016\u002Fj.jenvman.2015.11.019",{"doi":2776},"10.1016\u002Fj.jenvman.2015.11.019",{"id":18,"text":2778,"url":18,"identifiers":2779},"Siriwardene, 2007, Modelling of sediment transport through stormwater gravel filters over their lifespan, Environ. Sci. Technol., 41, 8099, 10.1021\u002Fes062821v",{"doi":2780},"10.1021\u002Fes062821v",{"id":18,"text":2782,"url":18,"identifiers":2783},"Collins, 2008, Hydrologic comparison of four types of permeable pavement and standard asphalt in eastern North Carolina, J. Hydrol. Eng., 13, 1146, 10.1061\u002F(ASCE)1084-0699(2008)13:12(1146)",{"doi":2784},"10.1061\u002F(ASCE)1084-0699(2008)13:12(1146)",{"id":18,"text":2786,"url":18,"identifiers":2787},"American Society of Civil Engineers (ASCE) (2013). Permeable Pavements: Recommended Design Guidelines, Permeable Pavement Technical Committee of the Water Resources Institute of the American Society of Civil Engineers.",{},{"id":18,"text":2789,"url":18,"identifiers":2790},"Drake, 2014, Stormwater quality of spring–summer–fall effluent from three partial-infiltration permeable pavement systems and conventional asphalt pavement, J. Environ. Manag., 139, 69, 10.1016\u002Fj.jenvman.2013.11.056",{"doi":2791},"10.1016\u002Fj.jenvman.2013.11.056",{"id":18,"text":2793,"url":18,"identifiers":2794},"McDaniel, R.S., Thornton, W.D., and Dominguez, J.G. (2004). Field Evaluation of Porous Asphalt Pavement, Purdue University, Schools of Civil and Mechanical Engineering. Final Report.",{},{"id":18,"text":2796,"url":18,"identifiers":2797},"Putman, B.J. (2012). Evaluation of Open-Graded Friction Courses: Construction, Maintenance, and Performance, Clemson University, Glenn Department of Civil Engineering. Report No. FHWA-SC-12-04.",{},{"id":18,"text":2799,"url":18,"identifiers":2800},"Transit New Zeland (TNZ) (2007). Specification for Porous Asphalt, Transit New Zeland. Transit New Zeland SP\u002FSP11 070704.",{},{"id":18,"text":2802,"url":18,"identifiers":2803},"National Asphalt Pavement Association (NAPA) (2008). Porous Asphalt Pavements for Stormwater Management. Design, Construction and Maintenance Guide, National Asphalt Pavement Association.",{},{"id":18,"text":2805,"url":18,"identifiers":2806},"Dierkes, C., Kuhlman, L., Kandasamy, J., and Angelis, G. (2002, January 8–13). Pollution retention capability and maintenance of permeable pavements. Proceedings of the 9th International Conference on Urban Drainage, Portland, OR, USA.",{"doi":2807},"10.1061\u002F40644(2002)40",{"id":18,"text":2809,"url":18,"identifiers":2810},"Agarwal, S.K. (2009). Heavy Metal Pollution, A.P.H. Publishing.",{},{"id":18,"text":2812,"url":18,"identifiers":2813},"Llopart-Mascaró, A., Ruiz, R., Martínez, M., Malgrat, P., and Rubio, P. (July, January 27). Analysis of Rainwater quality: Towards sustainable Rainwater management in urban environments. Proceedings of the NOVATECH 2010 7th International Conference on Sustainable Techniques and Strategies for Urban Water Management, Lyon, France.",{},{"id":18,"text":2815,"url":18,"identifiers":2816},"Washington State Department of Transportation (WSDOT) (2007). Untreated Highway Runoff in Western Washington.",{},{"id":18,"text":2818,"url":18,"identifiers":2819},"Barrett, M.E., Malina, J.F., Charbeneau, R.J., and Ward, G.H. (1995). Characterization of Highway Runoff in the Austin Texas Area, Bureau of Engineering Research.",{},{"id":18,"text":2821,"url":18,"identifiers":2822},"Yuen, 2012, Accumulation of potentially toxic elements in road deposited sediments in residential and light industrial neighborhoods of Singapore, J. Environ. Manag., 101, 151, 10.1016\u002Fj.jenvman.2011.11.017",{"doi":2823},"10.1016\u002Fj.jenvman.2011.11.017",{"id":18,"text":2825,"url":18,"identifiers":2826},"National Ready-Mixed Concrete Association (NRMCA) (2004). Freeze-Thaw Resistance of Pervious Concrete, National Ready-Mixed Concrete Association.",{},{"id":18,"text":2828,"url":18,"identifiers":2829},"Balades, 1995, Permeable pavements: Pollution management tools, Water Sci. Technol., 32, 49, 10.2166\u002Fwst.1995.0012",{"doi":2830},"10.2166\u002Fwst.1995.0012",{"id":18,"text":2832,"url":18,"identifiers":2833},"Pagotto, 2000, Comparison of the hydraulic behaviour and the quality of highway runoff water according to the type of pavement, Water Res., 34, 4446, 10.1016\u002FS0043-1354(00)00221-9",{"doi":2834},"10.1016\u002FS0043-1354(00)00221-9",{"id":18,"text":2836,"url":18,"identifiers":2837},"Agência Nacional das Águas (ANA) (2005). Conservação e Reúso da Água em Edificações, Agência Prol Editora Gráfica. (In Portuguese).",{},{"id":18,"text":2839,"url":18,"identifiers":2840},"Conselho Nacional do Meio Ambiente (CONAMA) (2011). Conselho Nacional do Meio Ambiente Resolução No 430, de 13 de Maio de 2011. Condições e Padrões de Lançamento de Efluentes, (In Portuguese).",{},{"id":18,"text":2842,"url":18,"identifiers":2843},"Conselho Nacional do Meio Ambiente (CONAMA) (2005). Conselho Nacional do Meio Ambiente Resolução No 357, de 18 de Março de 2005. Classificação dos Corpos de Água e Diretrizes Ambientais Para Seu Enquadramento, (In Portuguese).",{},{"id":18,"text":2845,"url":18,"identifiers":2846},"Laboratório Central de Saúde Pública (LACEN) (2000). Manual de Orientação Para Coleta de Água e Amostras Ambientais, (In Portuguese).",{},{"id":18,"text":2848,"url":18,"identifiers":2849},"Brazil (2017, May 10). Departamento Nacional de Infraestrutura de Transportes\u002FInstituto de Pesquisas Rodoviárias. Coletânea de Normas, (In Portuguese).",{},{"id":18,"text":2851,"url":18,"identifiers":2852},"American Society for Testing and Materials (ASTM) (2002). Annual Book of ASTM Standards, American Society for Testing and Materials. Available online: https:\u002F\u002Fwww.astm.org.",{},{"id":18,"text":2854,"url":18,"identifiers":2855},"The California Department of Transportation (CALTRANS) (2006). California Department of Transportation Open Graded Friction Course Usage Guide, Division of Engineering Services.",{},{"id":18,"text":2857,"url":18,"identifiers":2858},"Departamento de Estradas de Rodagem de São Paulo (DER\u002FSP) (2006). Especificação Técnica: Pré-Misturado a Quente, (In Portuguese).",{},{"id":18,"text":2860,"url":18,"identifiers":2861},"University of New Hampshire Stormwater Center (UNHSC) (2009). Design Specifications for Porous Asphalt Pavement and Infiltrations Beds, University of New Hampshire Stormwater Center (UNHSC).",{},{"id":18,"text":2863,"url":18,"identifiers":2864},"Scholz, 2010, Efficiency of permeable pavement systems for the removal of urban runoff pollutants under varying environmental conditions, Environ. Prog. Sustain. Energy, 29, 358, 10.1002\u002Fep.10418",{"doi":2865},"10.1002\u002Fep.10418",{"id":18,"text":2867,"url":18,"identifiers":2868},"Bean, 2007, Evaluation of four permeable pavement sites in eastern North Carolina for runoff reduction and water quality impacts, J. Irrig. Drain. Eng., 133, 583, 10.1061\u002F(ASCE)0733-9437(2007)133:6(583)",{"doi":2869},"10.1061\u002F(ASCE)0733-9437(2007)133:6(583)",{"id":18,"text":2871,"url":18,"identifiers":2872},"Companhia Ambiental do Estado de São Paulo (CETESB) (2014). Norma técnica L5.202 Coliformes totais e fecais—determinação pela técnica de tubos múltiplos: método de ensaio, Publicações e Relatórios; Companhia Ambiental do Estado de São Paulo. (In Portuguese).",{},{"id":18,"text":2874,"url":18,"identifiers":2875},"Quevedo, C.M.G. (2015). Avaliação da Presença de Fósforo nos Esgotos Sanitários e da Atual Contribuição dos Detergentes. [Ph.D. Thesis, Universidade de São Paulo (USP), Faculdade de Saúde Pública]. (In Portuguese).",{},{"id":18,"text":2877,"url":18,"identifiers":2878},"Brow, 2015, Nutrient infiltration concentration from three permeable pavement types, J. Environ. Manag., 164, 74, 10.1016\u002Fj.jenvman.2015.08.038",{"doi":2879},"10.1016\u002Fj.jenvman.2015.08.038",{"id":18,"text":2881,"url":18,"identifiers":2882},"Chughtai, 2014, Study of physicochemical parameters of rainwater: A case study of Karachi, Pakistan, Am. J. Anal. Chem., 5, 235, 10.4236\u002Fajac.2014.54029",{"doi":2883},"10.4236\u002Fajac.2014.54029",{"id":18,"text":2885,"url":18,"identifiers":2886},"Cederkvist, 2017, Method for assessment of stormwater treatment facilities—Synhetic road runoff addition including micro-pollutants and tracer, J. Environ. Manag., 198, 107, 10.1016\u002Fj.jenvman.2017.04.097",{"doi":2887},"10.1016\u002Fj.jenvman.2017.04.097",{"id":2889,"createTime":2890,"updateTime":2891,"relativeEntities":2892,"slug":2893,"properties":2894,"entityType":141,"verifyStatus":142,"verifyTime":2890,"verifyNote":144,"languages":2908,"translateLanguages":2909,"viewCount":19,"primaryUrl":2910,"fullTextUrl":18,"authors":2911,"publicationType":214,"publisherRelationship":3060,"citationCount":3120,"citationInfo":3121,"publishDate":18,"publishYear":18,"citationAnalyzeStatus":17,"lastCitationAnalyze":18,"indexDatabases":3126,"openAccess":18,"references":3127,"isForceReanalyzing":528},"7025213e-11b9-4c8b-9c10-166cda31aa85","2024-10-13T15:46:33.810+00:00","2025-02-03T08:19:37.848+00:00",[],"Comparison-of-Long-Short-Term-Memory-Networks-and-the-Hydrological-Model-in-Runoff-Simulation",{"openalex":2895,"mag":2897,"abstract":2899,"title":2902,"keywords":2905,"doi":2906},{"VOID":2896},"W2999092792",{"VOID":2898},"2999092792",{"VI":2900,"EN":2901},"\u003Cjats:p>Mô hình hóa dòng chảy là một trong những thách thức quan trọng trong lĩnh vực thủy văn học. Có nhiều phương pháp khác nhau, từ mô hình dựa trên lý thuyết vật lý cho đến mô hình hoàn toàn dựa trên dữ liệu. Trong bài báo này, chúng tôi đề xuất một phương pháp dựa trên dữ liệu sử dụng mạng Nơ-ron Dài Ngắn (LSTM) tiên tiến nhất. Mô hình được đề xuất đã được áp dụng tại lưu vực Hồ Poyang (PYLB) và hiệu suất của nó được so sánh với Mạng Nơ-ron Nhân tạo (ANN) và Công cụ Đánh giá Nước & Đất (SWAT). Chúng tôi trước tiên kiểm tra tác động của số bước thời gian trước đó (kích thước cửa sổ) trong độ chính xác mô phỏng. Kết quả cho thấy kích thước cửa sổ không thích hợp lớn sẽ làm giảm hiệu suất mô hình một cách đáng kể. Đối với PYLB, kích thước cửa sổ 15 ngày có thể là phù hợp cho cả độ chính xác và hiệu quả tính toán. Chúng tôi sau đó đã đào tạo mô hình với 2 tập dữ liệu đầu vào khác nhau, bao gồm tập dữ liệu chỉ có lượng mưa và tập dữ liệu tất cả các biến khí tượng sẵn có. Kết quả cho thấy mặc dù LSTM với dữ liệu lượng mưa là đầu vào duy nhất có thể đạt được kết quả mong muốn (với NSE dao động từ 0.60 đến 0.92 trong giai đoạn thử nghiệm), nhưng hiệu suất có thể được cải thiện đơn giản bằng cách cung cấp cho mô hình nhiều biến khí tượng hơn (với NSE dao động từ 0.74 đến 0.94 trong giai đoạn thử nghiệm). Hơn nữa, kết quả so sánh với ANN và SWAT cho thấy ANN có thể đạt hiệu suất tương đương với SWAT trong hầu hết các trường hợp, trong khi hiệu suất của LSTM thì tốt hơn nhiều. Kết quả của nghiên cứu này nhấn mạnh tiềm năng của LSTM trong mô hình hóa dòng chảy, đặc biệt là cho các khu vực mà dữ liệu địa hình chi tiết không có sẵn.\u003C\u002Fjats:p>","\u003Cjats:p>Runoff modeling is one of the key challenges in the field of hydrology. Various approaches exist, ranging from physically based over conceptual to fully data driven models. In this paper, we propose a data driven approach using the state-of-the-art Long-Short-Term-Memory (LSTM) network. The proposed model was applied in the Poyang Lake Basin (PYLB) and its performance was compared with an Artificial Neural Network (ANN) and the Soil & Water Assessment Tool (SWAT). We first tested the impacts of the number of previous time step (window size) in simulation accuracy. Results showed that a window in improper large size will dramatically deteriorate the model performance. In terms of PYLB, a window size of 15 days might be appropriate for both accuracy and computational efficiency. We then trained the model with 2 different input datasets, namely, dataset with precipitation only and dataset with all available meteorological variables. Results demonstrate that although LSTM with precipitation data as the only input can achieve desirable results (where the NSE ranged from 0.60 to 0.92 for the test period), the performance can be improved simply by feeding the model with more meteorological variables (where NSE ranged from 0.74 to 0.94 for the test period). Moreover, the comparison results with the ANN and the SWAT showed that the ANN can get comparable performance with the SWAT in most cases whereas the performance of LSTM is much better. The results of this study underline the potential of the LSTM for runoff modeling especially for areas where detailed topographical data are not available.\u003C\u002Fjats:p>",{"EN":2903,"VI":2904},"Comparison of Long Short Term Memory Networks and the Hydrological Model in Runoff Simulation","So sánh mạng Nơ-ron Dài Ngắn Trong Mô Hình Thủy văn trong Mô phỏng Chảy 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H.B., and Yang, D.W. 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