20:
empowering them to take appropriate actions to mitigate the potential consequences of flooding on human lives, property, and the environment. By accounting for the various dimensions of a flood event, such as occurrence, magnitude, duration, and spatial extent, flood forecasting models can offer a more holistic and detailed representation of the impending risks and facilitate more effective response strategies.
47:
in comparison to data-driven models, especially in the absence of inputs like rainfall. However, physically-based models are state-dependent and require accurate initial conditions for optimal performance. During the so-called "warming period" of the model, the performance might be lower due to the reliance on initial conditions.
31:
On the other hand, more comprehensive flood forecasting methods involve predicting the flood extent by utilizing hydrodynamic information from models. These approaches not only consider the exceedance of a threshold but also aim to estimate the spatial distribution, timing and extent of the flooding.
27:
When flood forecasting is limited to estimating the moment a threshold is exceeded, researchers often concentrate on predicting water levels or river discharge in a particular location. This approach provides valuable information about the potential onset of a flood event, enabling decision-makers to
23:
Flood forecasting is a multifaceted discipline that aims to predict various aspects of flood events, including their occurrence, magnitude, timing, duration, and spatial extent. However, the scope and definition of flood forecasting can differ across scientific publications and methodologies. In some
46:
simulate the underlying physical processes involved in flood generation and propagation, such as precipitation, infiltration, runoff, and routing. These models are typically more stable and reliable due to their inherent representation of the physics, making them less susceptible to forecast errors
35:
Incorporating hydrodynamic information into flood forecasting models allows for a more complete understanding of the potential impacts of flood events, accounting for factors such as the inundation of infrastructure, agricultural lands, and residential areas. By considering the spatial distribution
60:
combine the strengths of physically-based and data-driven models to enhance flood forecasting accuracy and reliability. Hybrid models can utilize the physical understanding from physically-based models while benefiting from the adaptive learning capabilities of data-driven models. An example of a
53:
focus on discovering patterns and relationships within historical data without explicitly representing the physical processes. They can learn complex, non-linear relationships and adapt to changing conditions, making them useful in situations where data is abundant and accurate representation of
19:
is the process of predicting the occurrence, magnitude, timing, and duration of floods in a specific area, often by analysing various hydrological, meteorological, and environmental factors. The primary goal of flood forecasting is to deliver timely and accurate information to decision-makers,
39:
Flood forecasting can be done using various methodologies, which can be broadly categorized into physically-based models, data-driven models, or a combination of both. The choice of the most suitable approach depends on factors such as data availability, catchment characteristics, and desired
437:, where the distinction between the two is that the outcome of flood forecasting is a set of forecast time-profiles of channel flows or river levels at various locations, while "flood warning" is the task of making use of these forecasts to tell decisions on warnings of floods.
32:
Hydrodynamic models, such as the
Hydrologic Engineering Center's River Analysis System (HEC-RAS) or the MIKE suite of models, simulate water flow and its interaction with the surrounding environment, providing detailed predictions of flood extent, depth, and velocity.
479:
Nearing, Grey; Cohen, Deborah; Dube, Vusumuzi; Gauch, Martin; Gilon, Oren; Harrigan, Shaun; Hassidim, Avinatan; Klotz, Daniel; Kratzert, Frederik; Metzger, Asher; Nevo, Sella; Pappenberger, Florian; Prudhomme, Christel; Shalev, Guy; Shenzis, Shlomo (March 2024).
28:
initiate preventive measures and minimize potential damages. In this context, flood forecasting models are designed to predict when the water level or discharge will surpass a predefined threshold, usually based on historical data and established risk levels.
575:
Nevo, Sella; Morin, Efrat; Gerzi
Rosenthal, Adi; Metzger, Asher; Barshai, Chen; Weitzner, Dana; Voloshin, Dafi; Kratzert, Frederik; Elidan, Gal; Dror, Gideon; Begelman, Gregory; Nearing, Grey; Shalev, Guy; Noga, Hila; Shavitt, Ira (2022-08-05).
24:
cases, flood forecasting is focused on estimating the moment when a specific threshold in a river system is exceeded, while in other cases, it involves predicting the flood extent and employing hydrodynamic information from models.
440:
Real-time flood forecasting at regional area can be done within seconds by using the technology of artificial neural network. Effective real-time flood forecasting models could be useful for early warning and disaster prevention.
61:
hybrid model is coupling a hydrological model with a machine learning algorithm to improve flood prediction accuracy. Hybrid models may also incorporate physical processes into the structure of the machine learning models.
54:
physical processes is challenging. Examples of data-driven models include regression techniques, Artificial Neural
Networks (ANN), Support Vector Machines (SVM), and tree-based algorithms like Random Forest or XGBoost.
676:
Application of self-organising maps and multi-layer perceptron-artificial neural networks for streamflow and water level forecasting in data-poor catchments: the case of the Lower Shire floodplain, Malawi
156:
36:
of flooding, these models enable more effective flood management and response strategies, ensuring that resources are allocated appropriately and that vulnerable populations are adequately protected.
681:
Delft-FEWS, state of the art system for flood forecasting and operational water management (most advanced system available, used on national scale in Europe and the USA)
386:
337:
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239:
190:
408:
357:
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210:
719:
423:
635:
Chang, Li-Chiu; Shen, Hung-Yu; Chang, Fi-John (2014-11-27). "Regional flood inundation nowcast using hybrid SOM and dynamic neural networks".
410:
is the flood forecasting model, which can be a physically-based model, a data-driven model or a hybrid model depending on the approach chosen.
426:
models to forecast flow rates and water levels for periods ranging from a few hours to days ahead, depending on the size of the watershed or
545:
712:
950:
69:
1318:
705:
430:. Flood forecasting can also make use of forecasts of precipitation in an attempt to extend the lead-time available.
1944:
1475:
1939:
1500:
1641:
1591:
1485:
1919:
415:
1145:
694:, an informal yet highly active group of researchers in the field of predictive hydrologic uncertainty.
1929:
1881:
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1924:
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1381:
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1275:
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1656:
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481:
290:
denotes a vector of proxy variables (e.g., soil moisture, land use, topography) at time
1965:
1856:
1769:
1734:
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1102:
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427:
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612:
1959:
1896:
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1805:
1571:
1536:
1490:
1450:
1445:
1205:
1077:
1037:
783:
763:
621:
513:
434:
578:"Flood forecasting with machine learning models in an operational framework"
1886:
1636:
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1082:
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419:
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1423:
1386:
1333:
1057:
1042:
1017:
891:
455:
685:
1901:
1581:
1465:
1405:
1363:
1235:
1072:
940:
881:
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1759:
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1358:
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1230:
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1117:
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935:
925:
823:
1541:
1508:
1185:
1027:
994:
594:
1851:
1800:
1328:
1323:
1285:
1190:
1062:
999:
688:, a conceptual rainfall-runoff model using a nonlinear reservoir
388:
represents the initial conditions and catchment characteristics,
1646:
1518:
1343:
1338:
1290:
1280:
1250:
1175:
930:
861:
833:
732:
574:
1744:
1729:
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1428:
1401:
1348:
1215:
1210:
1180:
1165:
974:
744:
728:
151:{\displaystyle \displaystyle F(t)=f(P_{t},X_{t},H_{t},C_{t})}
40:
prediction accuracy. Here is an overview of each approach:
680:
482:"Global prediction of extreme floods in ungauged watersheds"
1774:
1739:
1295:
1255:
1220:
1694:
1135:
64:
Flood forecasting can be mathematically represented as:
692:
hepex.org the
Hydrologic Ensemble Prediction EXperiment
691:
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367:
345:
318:
296:
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169:
73:
72:
402:
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233:
204:
184:
150:
1957:
727:
433:Flood forecasting is an important component of
634:
713:
666:Abhishek Tripathi Manju Devi Offcial Pradhan
241:represents the precipitation input at time
720:
706:
611:
593:
521:
1319:International scale of river difficulty
414:In many operational systems forecasted
1958:
701:
582:Hydrology and Earth System Sciences
13:
339:is the historical data up to time
14:
1977:
669:
1476:Flooded grasslands and savannas
628:
568:
538:
472:
192:is the flood forecast at time
179:
173:
144:
92:
83:
77:
1:
657:10.1016/j.jhydrol.2014.07.036
466:
1642:Universal Soil Loss Equation
1592:Hydrological transport model
1486:Storm Water Management Model
7:
444:
10:
1982:
1146:Antecedent drainage stream
506:10.1038/s41586-024-07145-1
1910:
1882:River valley civilization
1844:
1783:
1765:Riparian-zone restoration
1665:
1527:
1499:
1400:
1372:
1304:
1126:
993:
910:
832:
743:
613:10.5194/hess-26-4013-2022
1945:Countries without rivers
1920:Rivers by discharge rate
1632:Runoff model (reservoir)
1597:Infiltration (hydrology)
451:Runoff model (reservoir)
1617:River Continuum Concept
1382:Agricultural wastewater
44:Physically-based models
1940:River name etymologies
1867:Hydraulic civilization
1725:Floodplain restoration
1501:Point source pollution
1276:Sedimentary structures
404:
382:
353:
333:
304:
284:
255:
235:
206:
186:
152:
1552:Discharge (hydrology)
1514:Industrial wastewater
995:Sedimentary processes
405:
383:
381:{\displaystyle C_{t}}
354:
334:
332:{\displaystyle H_{t}}
305:
285:
283:{\displaystyle X_{t}}
256:
236:
234:{\displaystyle P_{t}}
207:
187:
153:
1657:Volumetric flow rate
1241:Riffle-pool sequence
637:Journal of Hydrology
394:
365:
343:
316:
294:
267:
245:
218:
196:
185:{\displaystyle F(t)}
167:
70:
1831:Whitewater kayaking
1826:Whitewater canoeing
1627:Runoff curve number
1471:Flood pulse concept
649:2014JHyd..519..476C
643:(Part A): 476–489.
604:2022HESS...26.4013N
498:2024Natur.627..559N
1857:Aquatic toxicology
1770:Stream restoration
1735:Infiltration basin
1587:Hydrological model
1103:Sediment transport
926:Estavelle/Inversac
804:Subterranean river
461:Flood Modeller Pro
424:streamflow routing
400:
378:
349:
329:
300:
280:
251:
231:
202:
182:
148:
147:
51:Data-driven models
1953:
1952:
1930:Whitewater rivers
1836:Whitewater slalom
1667:River engineering
1567:Groundwater model
1528:River measurement
1456:Flood forecasting
1271:Sedimentary basin
1128:Fluvial landforms
1033:Bed material load
809:River bifurcation
588:(15): 4013–4032.
492:(8004): 559–563.
403:{\displaystyle f}
352:{\displaystyle t}
303:{\displaystyle t}
254:{\displaystyle t}
205:{\displaystyle t}
17:Flood forecasting
1973:
1915:Rivers by length
1750:River morphology
1652:Wetted perimeter
1557:Drainage density
1068:Headward erosion
897:Perennial stream
769:Blackwater river
722:
715:
708:
699:
698:
661:
660:
632:
626:
625:
615:
597:
572:
566:
565:
563:
561:
552:. Archived from
542:
536:
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476:
409:
407:
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401:
387:
385:
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376:
358:
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157:
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130:
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117:
116:
104:
103:
1981:
1980:
1976:
1975:
1974:
1972:
1971:
1970:
1956:
1955:
1954:
1949:
1925:Drainage basins
1906:
1840:
1779:
1755:Retention basin
1715:Erosion control
1710:Detention basin
1661:
1577:Hjulström curve
1529:
1523:
1495:
1439:Non-water flood
1396:
1368:
1314:Helicoidal flow
1300:
1201:Fluvial terrace
1196:Floating island
1122:
997:
989:
980:Rhythmic spring
914:
906:
887:Stream gradient
828:
814:River ecosystem
779:Channel pattern
747:
739:
726:
672:
664:
633:
629:
573:
569:
559:
557:
556:on 16 July 2012
544:
543:
539:
477:
473:
469:
447:
420:rainfall-runoff
395:
392:
391:
372:
368:
366:
363:
362:
344:
341:
340:
323:
319:
317:
314:
313:
295:
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274:
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264:
246:
243:
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225:
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216:
215:
197:
194:
193:
168:
165:
164:
138:
134:
125:
121:
112:
108:
99:
95:
71:
68:
67:
12:
11:
5:
1979:
1969:
1968:
1951:
1950:
1948:
1947:
1942:
1937:
1932:
1927:
1922:
1917:
1911:
1908:
1907:
1905:
1904:
1899:
1894:
1889:
1884:
1879:
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1869:
1864:
1859:
1854:
1848:
1846:
1842:
1841:
1839:
1838:
1833:
1828:
1823:
1818:
1816:Stone skipping
1813:
1808:
1803:
1798:
1793:
1787:
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1778:
1777:
1772:
1767:
1762:
1757:
1752:
1747:
1742:
1737:
1732:
1727:
1722:
1717:
1712:
1707:
1702:
1700:Drop structure
1697:
1692:
1687:
1682:
1680:Balancing lake
1677:
1671:
1669:
1663:
1662:
1660:
1659:
1654:
1649:
1644:
1639:
1634:
1629:
1624:
1619:
1614:
1609:
1607:Playfair's law
1604:
1599:
1594:
1589:
1584:
1579:
1574:
1569:
1564:
1562:Exner equation
1559:
1554:
1549:
1547:Bradshaw model
1544:
1539:
1533:
1531:
1525:
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1478:
1473:
1468:
1463:
1458:
1453:
1448:
1443:
1442:
1441:
1436:
1434:Urban flooding
1426:
1421:
1419:Crevasse splay
1416:
1414:100-year flood
1410:
1408:
1398:
1397:
1395:
1394:
1389:
1384:
1378:
1376:
1374:Surface runoff
1370:
1369:
1367:
1366:
1361:
1356:
1354:Stream capture
1351:
1346:
1341:
1336:
1331:
1326:
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1308:
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1299:
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1268:
1266:Rock-cut basin
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1148:
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1138:
1132:
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1124:
1123:
1121:
1120:
1115:
1110:
1108:Suspended load
1105:
1100:
1098:Secondary flow
1095:
1090:
1088:Retrogradation
1085:
1080:
1075:
1070:
1065:
1060:
1055:
1053:Dissolved load
1050:
1045:
1040:
1035:
1030:
1025:
1020:
1015:
1010:
1004:
1002:
991:
990:
988:
987:
985:Spring horizon
982:
977:
972:
970:Mineral spring
967:
966:
965:
955:
954:
953:
951:list in the US
948:
938:
933:
928:
922:
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877:Stream channel
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799:Drainage basin
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781:
776:
771:
766:
761:
759:Alluvial river
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696:
695:
689:
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678:
671:
670:External links
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567:
550:allenpress.com
546:"AMS Glossary"
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79:
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9:
6:
4:
3:
2:
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1928:
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1923:
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1916:
1913:
1912:
1909:
1903:
1900:
1898:
1897:Surface water
1895:
1893:
1892:Sacred waters
1890:
1888:
1885:
1883:
1880:
1878:
1877:Riparian zone
1875:
1873:
1870:
1868:
1865:
1863:
1862:Body of water
1860:
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1837:
1834:
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1827:
1824:
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1811:Riverboarding
1809:
1807:
1806:River surfing
1804:
1802:
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1555:
1553:
1550:
1548:
1545:
1543:
1540:
1538:
1535:
1534:
1532:
1530:and modelling
1526:
1520:
1517:
1515:
1512:
1510:
1507:
1506:
1504:
1502:
1498:
1492:
1491:Return period
1489:
1487:
1484:
1482:
1479:
1477:
1474:
1472:
1469:
1467:
1464:
1462:
1459:
1457:
1454:
1452:
1451:Flood control
1449:
1447:
1446:Flood barrier
1444:
1440:
1437:
1435:
1432:
1431:
1430:
1427:
1425:
1422:
1420:
1417:
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1078:Palaeochannel
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58:Hybrid models
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25:
21:
18:
1935:Flash floods
1887:River cruise
1784:River sports
1637:Stream gauge
1622:Rouse number
1612:Relief ratio
1461:Flood-meadow
1455:
1392:Urban runoff
1306:Fluvial flow
1291:River valley
1261:River island
1226:Meander scar
1141:Alluvial fan
1083:Progradation
958:Karst spring
902:Winterbourne
857:Chalk stream
819:River source
794:Distributary
665:
640:
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558:. Retrieved
554:the original
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1796:Fly fishing
1720:Fish ladder
1705:Daylighting
1424:Flash flood
1387:First flush
1334:Plunge pool
1058:Downcutting
1043:Debris flow
1018:Aggradation
892:Stream pool
456:Flood alert
428:river basin
1902:Wild river
1582:Hydrograph
1572:Hack's law
1537:Baer's law
1481:Inundation
1466:Floodplain
1406:stormwater
1364:Whitewater
1236:Oxbow lake
1073:Knickpoint
1048:Deposition
941:Hot spring
882:Streamflow
872:Stream bed
789:Confluence
595:2111.02780
467:References
1966:Hydrology
1872:Limnology
1821:Triathlon
1791:Canyoning
1760:Revetment
1690:Check dam
1602:Main stem
1359:Waterfall
1246:Point bar
1231:Mouth bar
1171:Billabong
1118:Water gap
1113:Wash load
1093:Saltation
1013:Anabranch
936:Holy well
824:Tributary
622:1027-5606
514:1476-4687
1960:Category
1675:Aqueduct
1542:Baseflow
1509:Effluent
1186:Cut bank
1151:Avulsion
1028:Bed load
1008:Abrasion
532:38509278
523:10954541
445:See also
1852:Aquifer
1845:Related
1801:Rafting
1329:Meander
1324:Log jam
1286:Thalweg
1191:Estuary
1063:Erosion
1000:erosion
912:Springs
867:Current
834:Streams
774:Channel
737:springs
733:streams
686:RainOff
645:Bibcode
600:Bibcode
494:Bibcode
160:where:
1647:WAFLEX
1519:Sewage
1402:Floods
1344:Riffle
1339:Rapids
1281:Strath
1251:Ravine
1176:Canyon
931:Geyser
862:Coulee
847:Bourne
842:Arroyo
745:Rivers
729:Rivers
620:
560:9 July
530:
520:
512:
486:Nature
1745:Levee
1730:Flume
1685:Canal
1429:Flood
1349:Shoal
1216:Gully
1211:Gulch
1181:Chine
1166:Bayou
1023:Armor
975:Ponor
750:lists
590:arXiv
1775:Weir
1740:Leat
1404:and
1296:Wadi
1256:Rill
1221:Glen
1206:Gill
1156:Bank
998:and
963:list
946:list
917:list
852:Burn
735:and
618:ISSN
562:2015
528:PMID
510:ISSN
422:and
1695:Dam
1161:Bar
1136:Ait
653:doi
641:519
608:doi
518:PMC
502:doi
490:627
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