Historical Flood Research Articles

A Procedure for Combining Improved Correlated Sampling Methods and a Resampling Strategy to Generate a Multi-Site Conditioned Streamflow Process

In this study, a new method is developed to generate multi-site streamflow series. First, a correlated sampling method based on spectral decomposition is employed to simulate a large number of individual years of multi-site streamflow series. Then, combined with historical design flood data, flood characteristic series considering historical floods are generated. Finally, a subset of the streamflow series corresponding to these flood characteristics is selected from the pool of multi-site simulated streamflow series. The proposed model is applied to multi-site streamflow simulations in the upper Yangtze River basin. Experimental results show that the simulated data not only ensure the fundamental statistical characteristics of the observed data, but also provide good preservation of high order self-dependent, cross-dependent at finer and coarser time scales with any marginal distributions and any correlation structures. In addition, the simulated extreme situations are more reliable for risk and vulnerability analysis of multi-reservoir joint operation systems due to the consideration of the historical design flood data.

Forecasting and Seismic Detection of Proglacial Debris Flows at Mount Rainier National Park, Washington, USA

ABSTRACT The glaciated Mount Rainier volcano in southwestern Washington State (United States) has a rich history of outburst floods and debris flows that have adversely impacted infrastructure at Mount Rainier National Park in the 20th and 21st centuries. Retreating glaciers leave behind vast amounts of unconsolidated till that is easily mobilized during high-precipitation-intensity storms in the fall months, and during outburst floods during warm summer months. Over 60 debris flows and outburst floods have been documented between 1926 and 2019 at Mount Rainier. Debris-flow activity has led to the closure of campgrounds and visitor destinations, which has limited visitor access to large swaths of the park. This paper documents efforts to characterize and seismically monitor debris flows, map hazards, and develop forecasting approaches for wet and dry weather debris flows. Using the day-of and historic antecedent weather conditions on past debris-flow days, we developed a debris-flow hazard model to help predict those days with a higher relative hazard for debris-flow activity park-wide based on prevailing and forecasted weather conditions. Debris flows are detected in near-real-time using the U.S. Geological Survey Real-time Seismic Amplitude Measurement (RSAM) tool. If an event is detected, we can then provide evacuation alerts to employees and visitors working and recreating in the areas downstream. Our goal is to accurately forecast the debris-flow hazards up to 7 days ahead of time and then use RSAM to detect debris flows within minutes of their genesis.

Stalagmite flooding frequency record since the middle Little Ice Age from Central China

Comparison of the climate, especially extreme climate changes between the Little Ice Age (LIA) and the present, could provide important information for the predication of extreme climate change in the future. Based on a laminated stalagmite from the middle reaches of the Yangtze River, Central China, an annually resolved stalagmite record of growth rate has been produced dating from 1640 AD. An 11-year running variance sequence of the growth rate shows a positive correlation with a local historical flooding frequency record from 1640 to 1920 AD, suggesting that the stalagmite growth rate variance could be used as a local flooding frequency indicator. In the middle Yangtze catchment, the flooding frequency during the late LIA (1750–1900 AD) is much higher than during the middle LIA (1640–1750 AD) and the early twentieth century (1900–1920 AD). The discrepancy between the stalagmite growth rate variance and the flooding frequency after 1920s AD suggests that the scale of modern flooding is possibly larger than during the earlier periods. Spectral power analysis on growth rate variance of the stalagmite suggests that the flooding cycles around the middle Yangtze River catchment may relate to El Nino/Southern Oscillation (ENSO). The comparison between the stalagmite growth rate variance and reconstructed ENSO records further suggests a link between strong ENSO and high flooding frequency in the middle Yangtze catchment.

Concurrent functional regression to reconstruct river stage data during flood events

On October 4, 2015, the Cedar Creek gage at Congaree National Park stopped reporting stages, and the readings did not resume until approximately 2 weeks later because of record-breaking rainfall that led to some of the worst floodings in South Carolina history. Our goal is to reconstruct the Cedar Creek stage during this missing 2-week window. Our analysis uses a sample of ten historical flood events from the last 25 years. The Congaree River gage in Congaree National Park remained functioning throughout the October 2015 flood, when the stage reached its maximum recorded crest. The stages from the two gages are directly related during floods. We introduce a new method to objectively determine the start and end points of each flood event in the sample and then use these events to predict the missing Cedar Creek stage. We treat the stage as functional data and use a concurrent model to establish the relationship between the two locations during each timepoint of prior flood events. Once this relationship is found, the known Congaree stage is used to predict the missing Cedar Creek stage during the 2015 flood. The results show that there is a strong functional relationship between the two locations, and that the crest of Cedar Creek is a historic high, reaching stages above 17 feet, with a previous high of just over 16 feet.

A GIS-Based Artificial Neural Network Model for Flood Susceptibility Assessment

This article presents a geographic information system (GIS)-based artificial neural network (GANN) model for flood susceptibility assessment of Keelung City, Taiwan. Various factors, including elevation, slope angle, slope aspect, flow accumulation, flow direction, topographic wetness index (TWI), drainage density, rainfall, and normalized difference vegetation index, were generated using a digital elevation model and LANDSAT 8 imagery. Historical flood data from 2015 to 2019, including 307 flood events, were adopted for a comparison of flood susceptibility. Using these factors, the GANN model, based on the back-propagation neural network (BPNN), was employed to provide flood susceptibility. The validation results indicate that a satisfactory result, with a correlation coefficient of 0.814, was obtained. A comparison of the GANN model with those from the SOBEK model was conducted. The comparative results demonstrated that the proposed method can provide good accuracy in predicting flood susceptibility. The results of flood susceptibility are categorized into five classes: Very low, low, moderate, high, and very high, with coverage areas of 60.5%, 27.4%, 8.6%, 2.5%, and 1%, respectively. The results demonstrate that nearly 3.5% of the study area, including the core district of the city and an exceedingly populated area including the financial center of the city, can be categorized as high to very high flood susceptibility zones.

Soil erosion fluxes on the central Chinese Loess Plateau during CE 1811 to 1996 and the roles of monsoon storms and human activities

Evaluating the effects of soil and water conservation on the Chinese Loess Plateau (CLP) during the past 60 years depends mainly on understanding the historical processes of soil erosion fluxes and their mechanism. However, little was known about the historical variation in soil erosion and its driving factors due to the lack of few ideal geological carriers on the CLP. A representative Heshui (HS) landslide-dammed reservoir that formed 200 years ago was drilled with a 31.39 m length sediment sequence. The HS sequence was composed of 165 deposition couplets with 56 annual freeze–thaw layers based on the elemental distributions by X-ray fluorescence core scanners. Mean couplet and annual specific sediment yields (CSSY and ASSY) were 1.44 × 104 t/km2 and 1.28 × 104 t/km2/yr, respectively. The HS sequence was deposited over CE 1811–1996, which was dated by multi-methods crossing among 137Cs activities, annual freeze–thaw layers, CSSY, recent rainfall records, and historical flood index grades. Besides, the threshold value of hydrological events that generated sediments in the HS reservoir was greater than 40 mm. As a result, there were eight periods of high ASSY between CE 1811 and 1996, although the total tendency of the ASSY was decreased, especially under the management of soil and water since the 1960s on the CLP. Interannual change of monsoon storms under El Niño-Southern Oscillation events was the primary factor affecting the variations in ASSY and storms in the HS region. Besides, human activities, such as policies and wars, also had significant influences on the historical soil erosion processes in this region. These results not only shed light on the historical changes in soil erosion fluxes and corresponding hydrological events during the past 200 years in the plateau-gully area of the CLP, but the active mechanisms under the different driving factors were also better understood.

Soil Moisture Responses Associated with Significant Tropical Cyclone Rainfall Events

Several historic rainfall and flooding events associated with Atlantic Basin tropical cyclones have occurred in recent years within the conterminous United States: Hurricane Joaquin (2015) in early October over South Carolina; Hurricane Harvey (2017) in late August over southeastern Texas; Hurricane Florence (2018) in September over North Carolina; and Tropical Storm Imelda (2019) in September, again over southeastern Texas. A common attribute of these events includes a dramatic transition from dry soils to exceptional flooding in a very short time. We use an observations-driven land surface model to measure the response of modeled soil moisture to these tropical cyclone rainfall events and quantify the soil moisture anomalies relative to a daily, county-based model climatology spanning 1981 to 2013. Modeled soil moisture evolution is highlighted, including a comparison of the total column (0-2 m) soil moisture percentiles (derived from analysis values) to the 1981-2013 climatological database. The South Carolina event associated with Hurricane Joaquin resulted in a sudden transition from severe drought to significant flooding in the span of a few days, due to locally 700+ mm of rainfall. The prolonged heavy rainfall associated with Hurricane Harvey resulted in record soil moisture values well in excess of the tail of the climatological distribution. The soil moisture west of the Houston, Texas, metropolitan area was anomalously dry prior to Harvey, but quickly transitioned to near saturation in the top 1 m, while east of the Houston area antecedent soil moisture values were more moist prior to the local 1200+ mm of rainfall and catastrophic flooding in the Beaumont/Port Arthur area. Hurricane Florence led to widespread 500-700+ mm of rainfall in North Carolina, and another dramatic transition from anomalously dry conditions to record wetness. Once again, with Tropical Storm Imelda, portions of southeastern Texas experienced extreme rainfall amounts up to 1000+ mm, resulting in another sharp transition from drought conditions to extreme flooding in <3 days. An experimental forecast soil moisture percentile is presented for the Imelda event, showing the potential to increase situational awareness for upcoming flooding episodes, along with a discussion of how an ensemble-based approach could be explored to address forecast model error and uncertainty.

Soil Moisture Responses Associated with Significant Tropical Cyclone Rainfall Events

Several historic rainfall and flooding events associated with Atlantic Basin tropical cyclones have occurred in recent years within the conterminous United States: Hurricane Joaquin (2015) in early October over South Carolina; Hurricane Harvey (2017) in late August over southeastern Texas; Hurricane Florence (2018) in September over North Carolina; and Tropical Storm Imelda (2019) in September, again over southeastern Texas. A common attribute of these events includes a dramatic transition from dry soils to exceptional flooding in a very short time. We use an observations-driven land surface model to measure the response of modeled soil moisture to these tropical cyclone rainfall events and quantify the soil moisture anomalies relative to a daily, county-based model climatology spanning 1981 to 2013. Modeled soil moisture evolution is highlighted, including a comparison of the total column (0-2 m) soil moisture percentiles (derived from analysis values) to the 1981-2013 climatological database. The South Carolina event associated with Hurricane Joaquin resulted in a sudden transition from severe drought to significant flooding in the span of a few days, due to locally 700+ mm of rainfall. The prolonged heavy rainfall associated with Hurricane Harvey resulted in record soil moisture values well in excess of the tail of the climatological distribution. The soil moisture west of the Houston, Texas, metropolitan area was anomalously dry prior to Harvey, but quickly transitioned to near saturation in the top 1 m, while east of the Houston area antecedent soil moisture values were more moist prior to the local 1200+ mm of rainfall and catastrophic flooding in the Beaumont/Port Arthur area. Hurricane Florence led to widespread 500-700+ mm of rainfall in North Carolina, and another dramatic transition from anomalously dry conditions to record wetness. Once again, with Tropical Storm Imelda, portions of southeastern Texas experienced extreme rainfall amounts up to 1000+ mm, resulting in another sharp transition from drought conditions to extreme flooding in <3 days. An experimental forecast soil moisture percentile is presented for the Imelda event, showing the potential to increase situational awareness for upcoming flooding episodes, along with a discussion of how an ensemble-based approach could be explored to address forecast model error and uncertainty.

Flood spatial prediction modeling using a hybrid of meta-optimization and support vector regression modeling

Flood spatial susceptibility prediction is the first essential step in developing flood mitigation strategies and reducing flood damage. Flood occurrence is a complex process that is not easily predicted through simple methods. This study describes optimization of support vector regression (SVR) using meta-optimization algorithms including the grasshopper optimization algorithm (GOA) and particle swarm optimization (PSO) for flood modeling at Qazvin Plain, Iran. Geospatial data including nine readily available geo-environmental flood conditioning factors (i.e., ground slope, aspect, elevation, planform curvature, profile curvature, proximity to a river, land use, lithology and rainfall) were derived. The information gain ratio (IGR) method was used to determine the relative importance of input variables. A historical flood inventory map for 43 locations was created from existing reports. The geospatial data and historical flood levels were used to construct the training and testing datasets. Then, the training dataset was used to generate flood-susceptibility maps using the optimized SVR model with the GOA and PSO algorithms. Finally, the predictive accuracy of the models was quantified using the statistical measures of root mean square error (RMSE), mean absolute error (MAE), and area under the receiver operating characteristic (ROC) curve (AUC). Although both the GOA and PSO algorithms improved SVR performance, the SVR-GOA model performed best (AUC = 0.959, RMSE = 0.31 and MSE = 0.098), followed by the SVR-PSO model (AUC = 0.959, RMSE = 0.33 and MSE = 0.11) and standalone SVR model (AUC = 0.87, RMSE = 0.35 and MSE = 0.12). Elevation, lithology and aspect had the highest IGR values and were identified as the most effective predictors of flood susceptibility.

Extreme floods of the Changjiang River over the past two millennia: Contributions of climate change and human activity

Climate change and human activity have exerted significant influences on the sediment load and channel morphology of the Changjiang River system, China. However, our knowledge of their influence on flood regime on the centennial to millennial timescales remains limited, and this is mainly because of the difficulty in directly determining the long-term hydrological variability of the Changjiang River over the period before hydrological gauges were established. Based on multiproxy analysis that combines chronological, sedimentological, and geochemical analysis of a 4.8-m-long sediment core retrieved from the subaqueous delta of the Changjiang River, this study establishes a flood history for the Changjiang River during the late Holocene. Our palaeoflood reconstruction revealed 14 multi-decadal periods of extreme floods (19–66 BCE, 25–80, 255–350, 415–475, 550–710, 740–835, 970–990, 1080–1130, 1170–1235, 1275–1390, 1440–1500, 1560–1730, 1810–1830, and 1950–2011 CE). These flood units match well with the observed large floods, documentary records of floods, and sedimentary flood deposits, confirming that the coarse units in the sequence are flood-derived and are regionally representative. Comparing with regional and global palaeoclimate records indicates that major flood events of the Changjiang are strongly modulated by the Asian summer monsoon and the El Niño–Southern Oscillation (ENSO), but that anthropogenic impacts (e.g. artificial channelization and land clearance) have also greatly amplified the flooding frequency over the past 600 yr.

Flood susceptibility mapping using a geomorphometric approach in South Australian basins

Watershed characteristics and their hydrological responses can have severe effects on the occurrence and extent of floods. Therefore, this study focuses on the integration of geospatial techniques and remote sensing data to identify watershed terrain characteristics and evaluate the influence of these characteristics on flood susceptibility in South Australia. Data from the Shuttle Radar Topography Mission (SRTM) and geologic and topographic maps and a geographic information system (GIS) were used to delineate drainage basins, measure morphometric parameters and link different parameters to evaluate the degree of flood vulnerability. Depending on their relations to the flood hazards, the morphometric parameters were categorized into two groups; then, a rank score was assigned to each group. Finally, the flood susceptibility of the basins was visualized, and the basins were classified into low, intermediate and high flood hazard areas. The results show that approximately 45.7, 44.7 and 9.7% of the study area is at risk of high, medium and low degrees of flooding, respectively. The results were validated through secondary data relating to historic floods. The causes of flooding were analysed using rainfall and road density data, while the consequences of flooding were verified by the population distribution across the study area. The findings of this study can be used to support decision-makers in planning and investing in mitigation measures, especially in highly susceptible areas of South Australian basins.

The use of unmanned aerial vehicles for forecasting and preventing floods

The paper considers possible aspects of unmanned aerial vehicles (UAVs) to predict and prevent dangerous situations associated with floods, waterlogging, and stream rise in the territories of settlements in modern conditions. Besides, a historical analysis of such cataclysms was carried out for the period from 2019 to 2020, which deserves the special attention of scientists. The relevance of the paper is undoubted, since the symbiosis of nature and man gives rise to destructive phenomena against the background of an incorrect interaction of these two units. The paper is divided into 5 main sections, which include: introduction, history of floods, possible use of UAVs in water accidents, and further actions after the work of UAVs is done and the conclusions.

Lowcountry at High Tide: A History of Flooding, Drainage, and Reclamation in Charleston, South Carolina by Christina Rae Butler (review)

Lowcountry at High Tide: A History of Flooding, Drainage, and Reclamation in Charleston, South Carolina by Christina Rae Butler (review)

Potential flood frequency analysis and susceptibility mapping using CMIP5 of MIROC5 and HEC-RAS model: a case study of lower Dwarkeswar River, Eastern India

Floods are one of the major concerns in the world today. The lower reaches of the river coming from the western side of West Bengal are often affected by floods. Thereby estimation and prediction of flood susceptibility in the light of climate change have become an urgent need for flood mitigation and is also the objective of this study. The historical floods (1978–2018) of the monsoon-dominated lower Dwarkeswar River, as well as the possibility of future floods (2020–2075), were investigated applying peak flow daily data. The possibilities of future flow and floods were estimated using rainfall data from MIROC5 of CMIP5 Global Circulation Model (GCM). Besides, four extreme value distribution functions like log-normal (LN), Log-Pearson Type III (LPT-3), Gumbel’s extreme value distribution (EV-I) and extreme value distribution-III (EV-III) were applied with different recurrence interval periods to estimate its probability of occurrences. The flood susceptibility maps were analyzed in HEC-RAS Rain-on-grid model and validated with Receiver Operating Characteristic (ROC) curve. The result shows that Log-Pearson-Type-III can be very helpful to deal with flood frequency analysis with minimum value in Kolmogorov–Smirnov (K–S = 0.11676), Anderson–Darling (A–D = 0.55361) and Chi-squared test (0.909) and highest peak discharge 101.9, 844.9, 1322.5, 1946.2, 2387.9 and 2684.3 cubic metres can be observed for 1.5, 5, 10, 25, 50 and 75 years of return period. Weibull’s method of flood susceptibility mapping is more helpful for assessing the vulnerable areas with the highest area under curve value of 0.885. All the applied models of flood susceptibility, as well as the GCM model, are showing an increasing tendency of annual peak discharge and flood vulnerability. Therefore, this study can assist the planners to take the necessary preventive measures to combat floods.

Increased prevalence of indoor Aspergillus and Penicillium species is associated with indoor flooding and coastal proximity: a case study of 28 moldy buildings.

Indoor flooding is a leading contributor to indoor dampness and the associated mold infestations in the coastal United States. Whether the prevalent mold genera that infest the coastal flood-prone buildings are different from those not flood-prone is unknown. In the current case study of 28 mold-infested buildings across the U.S. east coast, we surprisingly noted a trend of higher prevalence of indoor Aspergillus and Penicillium genera (denoted here as Asp-Pen) in buildings with previous flooding history. Hence, we sought to determine the possibility of a potential statistically significant association between indoor Asp-Pen prevalence and three building-related variables: (i) indoor flooding history, (ii) geographical location, and (iii) the building's use (residential versus non-residential). Culturable spores and hyphal fragments in indoor air were collected using the settle-plate method, and corresponding genera were confirmed using phylogenetic analysis of their ITS sequence (the fungal barcode). Analysis of variance (ANOVA) using Generalized linear model procedure (GLM) showed that Asp-Pen prevalence is significantly associated with indoor flooding as well as coastal proximity. To address the small sample size, a multivariate decision tree analysis was conducted, which ranked indoor flooding history as the strongest determinant of Asp-Pen prevalence, followed by geographical location and the building's use.

Weather systems and extreme rainfall generation in the 2019 north Queensland floods compared with historical north Queensland record floods

Earlier papers have addressed floods from warm-air advection (WAA) in southeast Australia and around the globe, and extreme rainfall in US hurricanes and Australian tropical cyclones (TCs). This is the first paper to address the WAA phenomena in causing monsoon and TC floods and in TC-like systems which develop over the interior of northern Australia. The inland events help explain Australia’s worst tropical flooding disaster in 1916. A disastrous series of floods during late January and early February 2019 caused widespread damage in tropical north Queensland both in inland regions and along the coast. This occurred when some large-scale climate influences, including the sea surface temperatures suggested conditions would not lead to major flooding. Therefore, it is important to focus on the weather systems to understand the processes that resulted in the extreme rainfall responsible for the flooding. The structure of weather systems in most areas involved a pattern in which the winds turned in an anticyclonic sense as they ascended from the low to middle levels of the atmosphere (often referred to as WAA) which was maintained over large areas for 11 days. HYSPLIT air parcel trajectory observations were employed to confirm these ascent analyses. Examination of a period during which the heaviest rain was reported and compared with climatology showed a much stronger monsoon circulation, widespread WAA through tropical Queensland where normally its descending equivalent of cold-air advection is found, and higher mean sea level pressures along the south Queensland coast. The monsoon low was located between strong deep monsoon westerlies to the north and strong deep easterlies to the south which ensured its slow movement. This non-TC event produced heavy inland rainfall. Extreme inland rainfall is rare in this region. Dare et al. (2012), using data from 1969/70 to 2009/10, showed that over north Queensland non-TC events produced a large percentage of the total rainfall. The vertical structure associated with one of the earlier events that occurred in 2008 had sufficient data to detect strong and widespread WAA overlying an onshore moist tropical airstream. This appears to have played a crucial role in such extreme rainfall extending well inland and perhaps gives insight to the cause of a 1916 flooding disaster at Clermont which claimed around 70 lives. Several other events over the inland Tropics with strong WAA also help explain the 1916 disaster.

GIS-based multi-criteria analysis for flood prone areas mapping in the trans-boundary Shatt Al-Arab basin, Iraq-Iran

Severe flood events in the trans-boundary Shatt Al-Arab basin (Iraq-Iran) claim hundreds of human lives and cause damage to the economy and environment. Therefore, developing a flood hazard model to recognize the basin’s susceptible areas to flooding is important for decision makers for comprehensive flood risk management. The flood hazard map was prepared using geographical information systems (GIS) and multi-criteria decision analysis (MCDA) along with the application of analytical hierarchy process (AHP) method to identify the optimal selection of weights for the factors that contribute to flood risk. The flooding causative factors used in this study were rainfall, distance to the river, digital elevation model (DEM), slope, land use/land cover (LULC), drainage density, soils, and lithology. The derived flood hazard map consisted of four distinct categories (zones). These zones that depict high, intermediate, low, and very low flood hazard cover around 20%, 40%, 39%, and 2% of the basin area, respectively. The produced flood hazard map was further verified using a historical flood event in the study area. The results were found to be consistent with the historical data of flood events, revealing the model’s effectiveness in the realistic representation of flood hazard mapping.

Preliminary investigation on historical flood events using the HEC-HMS hydrological modelling for Kelantan River catchment

Preliminary investigation on historical flood events using the HEC-HMS hydrological modelling for Kelantan River catchment

A COMPARATIVE ANALYSIS OF HISTORICAL FLOOD EVENTS (POST-1990) IN THE TREBEŞ-NEGEL REPRESENTATIVE BASIN FOR EASTERN CARPATHIANS AND SUBCARPATHIANS TRANSITION ZONE

The European Network of Experimental and Representative Basins (ENERB) is the results of several experimental projects concerning the hydrological forecasting and flood mitigation effort which have been implemented within states member of European Union. In Romania, the hydrometric activity for ENERB it is currently composed of 14 representative basins (RB) of which the Trebeş-Negel (184 km2) was selected as RB for Eastern Carpathian and Subcarpathian transition zone. Located in one of the most affected territories by hydrological hazards, the Trebeş-Negel RB reacted as a small-scale flood sensor for the entire region. Using the well-documented discharge and pluviometric database collected at five gauge stations within the study area, we develop the first comparative analysis of historical flood events that occurred in the Trebeş-Negel RB post-1990. Five exceptional floods were selected: flood events from July 2 to July 8, 1991; flood events from June 16 to June 22, 1992; flood events from July 11 to July 14, 2005; flood events from July 26 to July 31, 2010; and flood events from June 28 to July 1, 2018. All flood events envisaged were caused by heavy rains, when significant amounts of precipitations were recorded which sometimes exceeded 100 mm/day.

Evaluation and validation of flood hazard zoning using Analytical Hierarchy Process and GIS: A case study of Lam River basin (Vietnam)

In recent years, the Lam river basin had suffered various forms of natural disasters such as floods, inundations, windstorms, tornadoes, etc. Among all these, the flood has proved to be the greatest threat to the people and the socio-economic development in the basin. Moreover, it is very frequent as compared to other natural disasters. In view of the fact that such disastrous floods are still occurring in the basin, it becomes a necessity to determine the causes and analyze the components affecting flood. This is important in order to develop an early flood warning system and thus minimize the negative impact of flood in the Lam river basin on the people and the facilities. In this paper, the Analytical Hierarchy Process (AHP) analysis method integrated with GIS technology is used to map flood risk zones in the Lam river basin. The parameters used for the analysis are the main causes affecting the floods. In addition to the 5 most commonly used factors such as slope, rainfall, land cover, soil, and drainage density, this study also includes a new factor - relative slope length to compute a more rigorous and reliable model. The results were compared with the two more methods of flood hazard zoning in the same study area: the method of the main flood caused factor analysis and the method of inheriting, data analyzing, and processing. The results were also validated by the historical flood data of three years 2010, 2013, and 2016.