Flood Magnitude Research Articles

Flood Frequency Analysis of Araniar Medium Irrigation Project in Chittoor District by using Gumbel's Distribution

Flood frequency analysis is one of the most important statistical technique to understand the nature and magnitude of high discharge of floods in the river. The objective of flood frequency analysis was to relate the magnitude of floods and their frequency of occurrence through probability distribution. Flood frequency analysis is essential to reduce the impact of flood damage by predicting the floods by adopting the suitable flood prediction model. The Araniar reservoir was constructed across the Araniar river in the Chittoor district of Andhra Pradesh. The flood frequency analysis was conducted on the Araniar reservoir using Gumbel’s extreme value distribution method in the year 2019-2020. Daily maximum inflow data from the Department of Water Resources, Andhra Pradesh, were collected for the period 1990-2019 and used for flood frequency analysis of Araniar Reservoir using Gumbel's extreme value distribution method. From the observations of Gumbel’s distribution, the R2 value acquired from the trend line equation was 0.9803, indicating that Gumbel's extreme value distribution was suitable for estimating predicted reservoir flood flow. The estimated flood flow for upcoming years of 2 years, 10 years, 50 years, 100 years,150 years, 200 years, 300 years and 400 years were found to be 38.29 Mm3/year, 66.96 Mm3/year, 92.08 Mm3/year, 102.71 Mm3/year, 108.90 Mm3/year, 113.29 Mm3/year, 119.47 Mm3/year and 123.85 Mm3/year respectively. The mean instantaneous flow in the reservoir was 40.88149 Mm3/year which was nearly equal to a return period of about 2 years. The estimated flood flows of the Araniar reservoir was useful for constructing important dam hydraulic structures, advising agricultural patterns in the command area, and protecting lives and property downstream of the catchment region.

Lake sediments from southern Norway capture Holocene variations in flood seasonality

Owing to the combined impact of human encroachment and global climate change, river flood hazards have increased around the world. Over the past decades, rapid warming has augmented atmospheric moisture fluxes. The resulting intensification of the hydrological cycle, as evident from instrumental records, is linked to more frequent and severe flooding. However, this observational baseline is too short to adequately assess long-term flood variability under different climate conditions. Geological archives can fill this critical knowledge gap by providing long-term (millennia) empirical constraints on the magnitude and frequency of floods. To reconstruct the frequency of flood events over the last >8000 years, this study investigated the Holocene lacustrine sediments from Lake Lygne in southwestern Norway. The precipitation in this area is sourced from the North Atlantic Ocean and transported by the prevalent westerly winds. As such, reconstructions of flood frequency variability may shed light on past moisture flux and flood generating weather systems in this part of northwestern Europe. We applied a multiproxy approach to robustly fingerprint the flood sediment signatures using multiple independent lines of evidence. This approach included analysing the sediments using X-ray fluorescence (XRF), computed tomography (CT scanning), and magnetic susceptibility (MS). We identified two types of event beds that differed significantly from background sedimentation throughout the sedimentary archive, which we interpreted as river flood deposits: one type is minerogenic and coarse silt-dominated; the other is a composite of minerogenic sediments and macrofossils. By comparing the sediment record with instrumental water discharge data from the last 100 years, we argue that these differing flood signals represent two flood regimes: rainfall-triggered floods during autumn and snowmelt-triggered floods during spring. Conducting a rate of change (RoC) analysis, we found significant millennial- and centennial-scale variability in the frequency of flood events. Moreover, comparing our findings with palaeoclimate reconstructions in the North Atlantic region, we found that the warmer than present early-mid-Holocene was dominated by extreme precipitation-triggered floods, shifting towards more snowmelt-triggered floods in the late Holocene.

How Do Vulnerable People in Bangladesh Experience Environmental Stress From Sedimentation in the Haor Wetlands? An Exploratory Study

AbstractThe haor landscape is a wetland ecosystem in northeast Bangladesh, comprising shallow depressions that undergo large changes in water inundation between the monsoon and dry seasons. Sediment is supplied to the haor from rivers originating in the adjacent Shillong Plateau, and can adversely affect these largely arable agricultural lands. The critical adverse effects of changing hydrology and enhanced sedimentation due to anthropogenic change include the reduction of natural water storage capacity, changes in the timing and magnitude of floods, and increasing loss and damage to crops, which consequently affect the livelihoods of wetland dwellers. This study employs a mixed‐methods approach to investigate how sedimentation has affected the livelihoods of the residents and the pressures they experience. Cross‐sectional surveys and interviews were conducted with 180 respondents in Lubar and Pochashul Haors (LPH), Sunamganj District, and allied with an analysis of satellite images that reveals the nature of landscape change over the past 56 years. Our findings confirm that sedimentation has been promoted through both natural processes of alluvial fan progradation and anthropogenic forcings. Enhanced sedimentation threatens the agriculture of the region and affects the livelihood of local inhabitants, leading to other societal issues related to income, education, employment, health, displacement, and sexual harassment. The mixed methods employed herein are essential tools to reveal these effects. In order to reduce the vulnerability of the local population, a transboundary dialog between India and Bangladesh is needed to realize measures to protect wetland resources and achieve progress towards environmental sustainability.

A Bayesian copula-based nonstationary framework for compound flood risk assessment along US coastlines

• Trends in and dependence between sea level and precipitation increase the probability of compound flooding along US coastlines, most notably along the Southeast coast. • A Bayesian copula-based framework captures the uncertainty in the quantification of compound flood frequency. • Precipitation trends play a major role in increasing the uncertainty in compound flood frequency. • To account for non-stationarity, a long historical record is required. When elevated coastal water levels and heavy precipitation occur simultaneously or in succession, their joint impact may be exacerbated compared to their individual occurrence. Sea-level rise, shifts in precipitation patterns, and the presence of correlation between flooding drivers can increase the frequency of these compound events. In this study, a copula-based Bayesian framework that incorporates the impact of dependence between flooding drivers (i.e., sea level and precipitation) and accounts for the nonstationarity in these hydrologic variables is developed. The framework is used to assess how the individual and combined effects of dependence and nonstationarity influence the frequency and magnitude of compound coastal-pluvial flooding. Furthermore, the Bayesian framework allows for the incorporation of uncertainty, which may arise from shortage of data, model selection, and parameter estimation, into flood frequency analysis. The proposed framework is applied to 32 station pairs across the US coastlines to identify locations that experience the highest risk of compound flooding and to assess the major contributors to uncertainty in the bivariate return period. The results show that the Southeast Atlantic coast experiences the highest increase in the risk of compound flooding, followed by the Gulf and Northeast Atlantic coasts. Sea-level rise and dependence between flooding drivers have a larger influence on bivariate return periods than changes in precipitation patterns. Under a nonstationary framework, precipitation is the major contributor to uncertainty compared to sea level and dependence. In addition, results demonstrate that uncertainty is highly dependent on the length of joint data. This study highlights the importance of incorporating hydrological dependence and trends and associated uncertainty into the quantification of return periods to permit reliable estimation of flood hazards.

Multiday Precipitation Is a Prominent Driver of Floods in Indian River Basins

AbstractIndia witness floods during the summer monsoon (June–September) that disproportionately affect the socioeconomic well‐being of millions of people. Nonstructural measures such as flood early warning systems play a crucial role in mitigating the impacts; however, these require a proper understanding of flood drivers. The drivers of floods in the Indian river basins have not been examined for the observed and projected future climate. Here using a novel framework, we examine antecedent moisture conditions and precipitation characteristics before high flow events. We estimate the probability of occurrence of flood drivers and their association with peak flood magnitude under the observed and projected future climate in Indian river basins. Multiday precipitation, a proxy to heavy precipitation on wet soil conditions, was found as the predominant flood driver in the observed and projected future climate. We show that multiday precipitation is more prominent driver than extreme soil moisture conditions in larger rivers basins while extreme precipitation drives floods in smaller river basins. The frequency of major drivers of floods is projected to rise in the future, which may pose a greater risk to agriculture and infrastructure under the warming climate.

UAV rapidly-deployable stage sensor with electro-permanent magnet docking mechanism for flood monitoring in undersampled watersheds

The availability of historical flood data is vital in recognizing weather-related trends and outlining necessary precautions for at-risk communities. Flood frequency, magnitude, endurance, and volume are traditionally recorded using established streamgages; however, the material and installation costs allow only a few streamgages in a region, which yield a narrow data selection. In particular, stage, the vertical water height in a water body, is an important parameter in determining flood trends. This work investigates a low-cost, compact, rapidly-deployable alternative to traditional stage sensors that will allow for denser sampling within a watershed and a more detailed record of flood events. The package uses a HC-SR04 ultrasonic sensor to measure stage, onboard memory for recording flood events, and an electropermanet magnet (EPM) to enable Unmanned Aerial Vehicle (UAV) deployments. Optional modules for solar panels and wireless communication can also be added to extend package longevity or allow wireless control of the EPM. The stage sensor package was found to have a range of 0.02 to 4 m with a 6.9 mm accuracy and capable of a 6.4 day long deployment. With the total cost of production at 271.37 USD, it is a cheaper and more flexible alternative to traditional stage sensors that will enable dense sensor networks and rapid response to flooding events.

Impacts of Global Climate Change on Temperature and Precipitation in Basra City, Iraq

Climate change affects countries’ economies and households through a variety of channels. Rising temperatures and changes in rainfall patterns affect agricultural yields of both rain fed and irrigated crops, and will change hydropower production, increased frequencies and magnitudes of floods and droughts can significantly increase the need for public investment in physical infrastructure. An investigation was carried out to identify trends in temperature and precipitation time series covering a period from (1970-2019) in the province of Basra south of Iraq, northwest of Arabian Gulf. The two variables were considered for analysis on both monthly and annual basis. The percentages of significant trends obtained for each parameter for 12 months and annually were presented. Temperature anomalies were plotted, the relationship between annual mean temperature and precipitation have been determined by Pearson’s Correlation coefficients, and were statistically measured. It was observed that the monthly and annually mean temperatures have increased, while precipitation trends have decreased; moreover, there is a negative weak relationship between temperature and precipitation, while a strong negative relationship was observed between the monthly average for the whole period of minimum and maximum temperature and rainfall

Flood risk mapping and urban infrastructural susceptibility assessment using a GIS and analytic hierarchical raster fusion approach in the Ona River Basin, Nigeria

The topical climate change effect, along with several uncontrolled anthropogenic activities, has resulted in a global flood disaster that continues to wreak havoc on human ecology. The hydraulic and integrated modelling approaches appear to stand out in the sequence of flood risk models that have been presented because of their predictive accuracy. The former has a high probability of under predicting and the latter has a high tendency to over-predict. This study proposed a modelling approach that combines the hydraulic and integrated models using analytical hierarchical raster fusion techniques to strengthen the weaknesses of the individual models. This study seeks to undertake a flood inundation model, a runoff model, and raster fusion models using GIS and HEC-RAS rain-on-grid methods to map flood risk and perform a flood infrastructural susceptibility assessment in the Ona river basin of Ibadan city. The flood risk model's main findings revealed that 48.2% of the Ona river basin is exposed from moderate to very high flood risk. It was revealed that rainfall introduces excess stormwater into the basin, but the stream channels associated with physical features are the major influencing factors. Also vulnerable to very high flood magnitudes include places with high building, road and rail network density, and locations with a high density of damaged bridges and culverts. This study shows that the robust modelling approach presented here yielded insightful results that can be used by relevant authorities to implement flood management models and define priorities for flood catastrophe risk planning, early warning, and preparedness.

Alluvial ichnofacies from Upper Triassic red beds in India: Implications for palaeoenvironment and palaeoclimate

Trace fossils are highly sensitive to the hydrodynamic conditions of depositional systems, substrate, and climate and hence yield information about spatio-temporal changes in palaeoenvironment and palaeoclimate. In this paper, we report alluvial trace fossil assemblages from the Upper Triassic Tiki Formation of the Rewa Basin, central India. Based on detailed facies analysis and architecture, two depositional environments are identified in this formation: (1) perennial braided channel belts and (2) extensive and complex floodplains containing ephemeral small fluvial channels, lakes, and crevasse splay deposits. Upper flow regime primary structures in laterally extensive sandstones encased in the floodplain deposits indicate short-lived high magnitude flood discharge, suggestive of seasonal climates. Trace fossils are sporadically distributed through these facies, generally in suites of low abundance, although in places the bioturbation index is higher. Three major ichnofacies, namely Skolithos, Scoyenia and Mermia are recognized, based on the association of different trace fossils preserved in the channel, crevasse splay of proximal floodplain and pond/lake of distal floodplain deposits, respectively. Vertical Beaconites in palaeosols and an abrupt change from Skolithos to Scoyenia ichnofacies indicate a highly variable water table, controlled by seasonal precipitation. The transitions between the Skolithos, Scoyenia and Mermia ichnofacies reveal that trace fossil preservation was variously controlled by channel abandonment, floodplain dewatering, substrate desiccation or periodic waterlogging of overbank areas. Specifically, increased water discharge over the floodplain during high precipitation, followed by post-flood recovery of hot, dry, low-water table conditions may have been a key controlling factor in shaping the ichnological characteristics of these Upper Triassic red beds.

Event and Catchment Controls of Heavy Tail Behavior of Floods

AbstractIn some catchments, the distribution of annual maximum streamflow shows heavy tail behavior, meaning the occurrence probability of extreme events is higher than if the upper tail decayed exponentially. Neglecting heavy tail behavior can lead to an underestimation of the likelihood of extreme floods and the associated risk. Partly contradictory results regarding the controls of heavy tail behavior exist in the literature and the knowledge is still very dispersed and limited. To better understand the drivers, we analyze the upper tail behavior and its controls for 480 catchments in Germany and Austria over a period of more than 50 years. The catchments span from quickly reacting mountain catchments to large lowland catchments, allowing for general conclusions. We compile a wide range of event and catchment characteristics and investigate their association with an indicator of the tail heaviness of flood distributions, namely the shape parameter of the GEV distribution. Following univariate analyses of these characteristics, along with an evaluation of different aggregations of event characteristics, multiple linear regression models, as well as random forests, are constructed. A novel slope indicator, which represents the relation between the return period of flood peaks and event characteristics, captures the controls of heavy tails best. Variables describing the catchment response are found to dominate the heavy tail behavior, followed by event precipitation, flood seasonality, and catchment size. The pre‐event moisture state in a catchment has no relevant impact on the tail heaviness even though it does influence flood magnitudes.

A Vine Copula‐Based Polynomial Chaos Framework for Improving Multi‐Model Hydroclimatic Projections at a Multi‐Decadal Convection‐Permitting Scale

AbstractPhysically based hydrologic models have been extensively used for hydroclimatic projections, but key challenges remain owing to the heavy computational burden and structural variability of physically based models. In this study, we develop a vine copula‐based polynomial chaos framework for improving multi‐model projections of hydroclimatic regimes at a convection‐permitting scale over the Dongjiang River Basin located in South China. Specifically, a deep neural network (DNN)‐based polynomial chaos expansion (PCE) is developed to significantly improve the efficiency of probabilistic hydrologic predictions. A vine copula multi‐model ensemble approach is also proposed to robustly combine hydrologic predictions generated from multiple DNN‐based PCEs to improve reliability and accuracy. To assess regional hydrologic responses to changing climate, multi‐decadal nested‐grid climate projections over the Guangdong‐Hong Kong‐Macao Greater Bay Area (GBA) are developed using the convection‐permitting Weather Research and Forecasting (WRF) model with 4‐km horizontal grid spacing. Our findings reveal that the DNN‐based PCEs achieve comparable performance to the physically based hydrologic predictions with an extremely low computational cost. The vine copula multi‐model ensemble approach outperforms the Bayesian model averaging (BMA) by generating more accurate and reliable hydrologic predictions. The developed framework and physical models also lead to consistent projections of future changes in streamflow regimes. Our findings reveal that the projected increases in the frequency and intensity of extreme precipitation can lead to substantial increases in flood magnitudes, but the increases may not be obvious for river basins affected by multiple reservoirs.

Broad valleys and barrier dams in upstream Brahmaputra efficiently retain Tibetan-sourced sediments: Evidence from palaeoflood records

Recent studies confirm that more than 50% of the sediment load of the Brahmaputra River originates from the Namche Barwa massif, whose area is just 2–3% of the total drainage area. This sediment flux anomaly cannot be attributed to only rapid erosion caused by extreme outburst floods because the young cooling age population of the Namche Barwa source sediment is disproportionally high even in the modern sediment transported by normal river flows. We propose a new mechanism for this anomaly by integrating new findings of palaeoflood sedimentary records with previous field surveys around Yigong Lake, a residual dammed lake in the lower Yigong River which is a major tributary of the Brahmaputra River, in the southeastern margin of Tibet. The magnitude of the palaeoflood event upstream of the lake, with a peak discharge of 64,500 m3/s estimated by using hydraulic reconstruction approaches, is far smaller than that of downstream flood events. Tibetan source sediment transport is truncated by the juxtaposition of broad valleys and barrier dams on the edge of the highly exhumated region with cooling ages of <2 Ma. This juxtaposition has three effects: trapping large amounts of the upstream sediment load, flattening the hydrograph of upstream extreme floods, and enlarging the magnitude of downstream outburst floods. Hence, the spatial consistency of the broad valley-dammed lake systems in the Rivers in the young cooling region probably shed light on understanding the sediment source conundrum for the Brahmaputra River.

Expected annual probability of infection: A flood-risk approach to waterborne infectious diseases

This study introduces a new approach for the investigation of infections after an accidental ingestion of contaminated floodwater. The concept of Expected Annual Probability of Infection (EAPI) is introduced and implemented in an infection risk-model approach, by combining a Quantitative Microbial Risk Assessment (QMRA) with the four steps in flood risk assessment. Two groups and exposure paths are considered: adults wading in floodwater and small children swimming/playing in floodwater. The study area is located in Ghana, West Africa. Even though Ghana is one of the most urbanized countries in Africa it has significant problems with water resources management and public health. While cholera is classified as endemic in Accra, the natural and human-made characteristics of the capital makes it prone to flooding. The results of the EAPI approach show that on one hand the concentration of pathogens in floodwater, and thus the risk of infection, decreases with the increase of the flood magnitude. On the other hand, larger floods can spread the pathogens further from the point source, threatening populations previously not identified as at risk by small-scale floods. The concept of EAPI is demonstrated for cholera but it can be extended to other waterborne diseases and also different pathways of exposure, requiring minimal adaptations. For future applications, better estimation of EAPI key components and improvement points are discussed and recommendations given for all the assessment steps.

Detection of trends in observed river floods in Poland

Study Region Poland (representative sample of 146 flow gauges free of major human modifications, located in 12 major river basins) Study Focus The objective was to present trends in selected river flood indicators (magnitude, frequency and timing) in Poland, using the annual maximum daily flow and peak-overthreshold approaches. Two periods (1956–2019 and 1981–2019) were analyzed. The first period maximized the temporal coverage and featured 58 gauges, while the second period maximized spatial coverage and featured 146 gauges. Trends were computed using the non-parametric Mann-Kendall test (MK) and Sen slope for changes in magnitude and timing, while flood frequency trend was detected by chisquare test on parametric Poisson regression. New Hydrological Insights for the Region We found a general decreasing trend in flood magnitude, with frequently occurring statistical significance, for the majority of river basins (particularly in north-eastern Poland). The strongest of these trends exceeded 15% per decade. A positive trend was detected in the southern part, particularly in the Upper Vistula Basin. No substantial and significant trends were detected in flood frequency, where identified changes mostly did not exceed values of ± 0.2 events per decade. Trend in flood timing showed a strong pattern of earlier flood occurrences in the southern half of the country for both periods, and an opposite behaviour in the north-eastern and northwestern regions.

Hydrometeorological analysis of the 12 and 13 September 2019 widespread flash flooding in eastern Spain

Abstract. On 12 and 13 September 2019, a long-lasting heavy precipitation episode (HPE) affected the València, Murcia and Almería regions in eastern Spain. Observed rainfall amounts were close to 500 mm in 48 h, being the highest cumulative precipitation registered in some rain gauges for the last century. Subsequent widespread flash flooding caused seven fatalities and estimated economical losses above EUR 425 million. High-resolution precipitation estimates from weather radar observations and flood response from stream gauges are used in combination with a fully distributed hydrological model to examine the main hydrometeorological processes within the HyMeX programme. This HPE was characterized by successive, well-organized convective structures that impacted a spatial extent of 7500 km2, with rainfall amounts equal to or larger than 200 mm. The main factors driving the flood response were quasi-stationarity of heavy precipitation, very dry initial soil moisture conditions and large storage capacities. Most of the examined catchments exhibited a dampened and delayed hydrological response to cumulative precipitation: until runoff thresholds were exceeded, infiltration-excess runoff generation did not start. This threshold-based hydrological behaviour may impact the shape of flood peak distributions, hindering strict flood frequency statistical analysis due to the generally limited lengths of data records in arid and semi-arid catchments. As an alternative, a power-law relationship is analytically derived to specifically link flood magnitude to rainfall amount, with the parameters depending on basin and precipitation features. This power law could aid in developing empirical envelope curves so as to assess hydrologic risk in arid and semi-arid catchments with a threshold-based hydrological behaviour.

Hydrological effects of large dams in Chilean rivers

Study regionEight rivers regulated by large dams located in three hydro-climatic zones along the Chilean latitudinal gradient. Study focusWe performed a multi-temporal scale analysis of flow records and we used data from official gauging stations to characterise the non-altered and the altered river regimes to determine the magnitude and persistence of the hydrological alteration downstream from large dams in Chile. These analyses provide relevant information to improve the understanding of such alterations, and a conceptual basis for assessing future impacts as the country plans to build a series of large dams in the coming years. New hydrological insights for the regionThe mean annual runoff was reduced in all the study rivers. The monthly flows of the rivers from the northern arid zone were the most affected by the dams. The magnitude and frequency of floods decreased in all the study rivers. Moreover, northern drier river systems did not recover their hydrological conditions in the distance downstream of the dams, probably due to transmission losses and water extractions and diversions; in contrast, southern rivers partially recovered their flow regimes with distance downstream, mainly due to the inflows from permanent non-regulated tributaries. So far, this is the first study in Chile that comprehensively analyses the hydrological effects of large dams.

Investigating the Linkage between Extreme Rainstorms and Concurrent Synoptic Features: A Case Study in Henan, Central China

Extraordinary floods are linked with heavy rainstorm systems. Among various systems, their synoptic features can be quite different. The understanding of extreme rainstorms by their causative processes may assist in flood frequency analysis and support the evaluation of any changes in flood occurrence and magnitudes. This paper aims to identify the most dominant meteorological factors for extreme rainstorms, using the ERA5 hourly reanalysis dataset in Henan, central China as a case study. Past 72 h extreme precipitation events are investigated, and six potential factors are considered in this study, including precipitable water (PW), the average temperature (Tavg) of and the temperature difference (Tdiff) between the value at 850 hPa and 500 hPa, relative humidity (RH), convective available potential energy (CAPE), and vertical wind velocity (Wind). The drivers of each event and the dominant factor at a given location are identified using the proposed metrics based on the cumulative distribution function (CDF). In Henan, central China, Wind and PW are dominant factors in summer, while CAPE and Wind are highly related factors in winter. For Zhengzhou city particularly, Wind is the key driver for summer extreme rainstorms, while CAPE plays a key role in winter extreme precipitation events. It indicates that the strong transport of water vapor in summer and atmospheric instability in winter should receive more attention from the managers and planners of water resources. On the contrary, temperature-related factors have the least contribution to the occurrence of extreme events in the study area. The analysis of dominant factors can provide insights for further flood estimations and forecasts.

Hydrological behaviour of an unregulated eastern slope river under changing historical climate

The Elbow River is an eastern slope river with headwaters in the Rocky Mountains in Alberta whose major end-use is a critical source of municipal water for Calgary. Overwinter precipitation in its watershed falls primarily as snow and accumulates as snowpack until spring melt. Precipitation falls mainly as rain from May until October. The river is unregulated above Calgary’s water supply reservoir, and its relatively undeveloped watershed makes it ideal for examining potential climate change impacts on river hydrology. Available historical hydrometeorological data (1967 to 2015) from the basin were assessed to study its hydrological behaviour under a changing climate. The analysis showed significant upward trends in both flow and precipitation variables, especially from 1979 to 2015. Significant increases in both annual flow volume and annual maximum daily flow (AM-flow), and later seasonal occurrence of AM-flow, were not observed in other eastern slope rivers. Although these changes could attenuate predicted water supply shortages, they could also potentially increase flood magnitudes. The analysis also revealed that three sub-watersheds, which are approximately equal in geographic area, contributed differing flow volumes during the high-flow season (May to October). The upper watershed contributed most (∼68%), followed by the middle (∼26%) and lower (∼6%) watersheds, on average. Extreme high-flow events (ie >90th percentile AM-flow) were strongly related to high rainfall events, but not significantly related to snowpack loss (or melt). Moderate AM-flows were positively related to both the cumulative snowpack loss before the high-flow season and the cumulative antecedent precipitation prior to the AM-flow, suggesting that the antecedent soil moisture conditions could play a role. Predictions of climate change impacts on this eastern slope river’s hydrology should thus consider the effects of meteorological variables and the moisture conditions of the watershed.

Potential impacts of failure of the Grand Ethiopian Renaissance Dam on downstream countries

AbstractThis study assesses the potential downstream impacts in the event of a flood due to failure, either structural or operational, of the Grand Ethiopian renaissance dam (GERD). The following two failure scenarios were modeled as part of this study: Dam Break (DB) and MisGuided Dam Operation (MGDO) as a result of a false flood signature. The DB scenario shows that 40% of the intensively cultivated Gezira Plain would be inundated with average water depths of more than 10 m, resulting in catastrophic loss of highly productive farmlands, livestock, inhabitants, and infrastructure. This scenario did not model damage further downstream since for this magnitude flood it will require another flood routing model given the more complex geometry downstream of the Gezira Plain. In the MGDO scenario flood flows are lower and would have no impact on the Gezira Plain but would reach the High Aswan Dam (HAD) and fill it to its maximum allowable capacity for two and a half months and it would require emergency releases for more than 5 months. The required emergency releases from the HAD are expected to create significant flooding downstream. To accommodate the potential of extra releases from the GERD during flood events the operational rules for the HAD should be modified. However, providing more flood buffer at the HAD will limit the live capacity that is currently used for securing downstream flow requirements during drought periods. One of the expected impacts of increasing the flood buffer would be a reduction of the HAD's contribution to Egypt's GDP. Based on the results of this study the operational rules for the GERD and the HAD should be evaluated and possibly modified.

Numerical Simulation of Alpine Flash Flood Flow and Sedimentation in Gullies With Large Gradient Variations

Compared with floods occurring over plains, alpine flash floods are formed over scattered locations with complex terrain and data is often lacking regarding the land topography, flow and sedimentation, causing difficulties when developing mathematical models to predict flash floods. The existing flash flood models mainly focus on the influence of water flow, such as the sharp increase in flow discharge caused by convergence at steep slopes, disregarding the sediment load carried by the water flow. However, under the effect of high-intensity sediment transport, the sedimentation in gullies may lead to surges in water level, causing the phenomenon of “great disasters resulting from minor flooding”. In this study, an efficient and accurate water-sediment coupling model was established with a Godunov-type finite volume method based 2D flow model, and a sediment module and OPENMP parallel computing module were added as well. Firstly, a common gully in mountainous area with large gradient variations was used as a generalized model to explore the impact of sedimentation on the flow field of the gully and compared with the physical model. Then, the alpine flash flood incident in Gengdi Village was simulated with the computer model. The calculation results show that the high-intensity sedimentation significantly increased the magnitude of alpine flash floods. Calculated by this mathematical model, the research results verified that this mathematic model can efficiently, accurately and concisely predict the occurrence of flash floods in gullies with large gradient variations. The model also provides a flow and sediment modeling method that incorporates the effect of high-intensity sediment transport into the traditional flash flood flow model. Thus, this model can be a powerful tool for detecting flash floods.