Influence of Headwater Reservoirs on Climate Change Impacts and Flood Frequency in the Kabul River Basin

While climate change impacts vary globally, for the Kabul River Basin (KRB), concerns are primarily associated with frequent flooding. This research describes the influence of headwater reservoirs on projections of climate change impacts and flood frequency, and how the riparian countries can benefit from storing of floodwaters for use during dry seasons. Six climate change scenarios and two Representative Concentration Pathways (RCPs) are used in three periods of a quarter-century each. The Soil and Water Assessment Tool (SWAT) is used to assess how the proposed reservoirs will reduce flooding by ~38% during the wet season, reduce the flood frequency from five to 25 years return period, and increase low flows by ~110% during the dry season, which reflect an ~17.5% reduction in the glacier-covered area by the end of the century. The risks and benefits of reservoirs are highlighted in light of the developmental goals of Afghanistan and Pakistan.

Multivariate Dam-Site Flood Frequency Analysis of the Three Gorges Reservoir Considering Future Reservoir Regulation and Precipitation

Under a changing environment, the current hydrological design values derived from historical flood data for the Three Gorges Reservoir (TGR) might be no longer applicable due to the newly-built reservoirs upstream from the TGR and the changes in climatic conditions. In this study, we perform a multivariate dam-site flood frequency analysis for the TGR considering future reservoir regulation and summer precipitation. The Xinanjiang model and Muskingum routing method are used to reconstruct the dam-site flood variables during the operation period of the TGR. Then the distributions of the dam-site flood peak and flood volumes with durations of 3, 7, 15, and 30 days are built by Pearson type III (PIII) distribution with time-varying parameters, which are expressed as functions of both reservoir index and summer precipitation anomaly (SPA). The multivariate joint distribution of the dam-site flood variables is constructed by a 5-D C-vine copula. Finally, by using the criteria of annual average reliability (AAR) associated with the exceedance probabilities of OR, AND and Kendall, we derive the multivariate dam-site design floods for the TGR from the predicted flood distributions during the future operation period of the reservoir. The results indicate that the mean values of all flood variables are positively linked to SPA and negatively linked to RI. In the future, the flood mean values are predicted to present a dramatic decrease due to the regulation of the reservoirs upstream from the TGR. As the result, the design dam-site floods in the future will be smaller than those derived from historical flood distributions. This finding indicates that the TGR would have smaller flood risk in the future.

Spatiotemporal variation in global floods with different affected areas and the contribution of influencing factors to flood-induced mortality (1985–2019)

Floods are great threats to human life and property. Extensive research has investigated the spatiotemporal variation in flood occurrence, while few have studied the heterogeneity in global flood events of different sizes, which may require different coping strategies and risk reduction policies. In this study, we analysed the spatiotemporal patterns of global flood events with different affected areas (classified in three levels) during 1985–2019 and examined the contribution of different influencing factors to flood-induced mortality using Geodetector. The results show that (1) the increase in global flood frequency was mainly caused by Level II and Level III floods, and the average area affected by flood events has been increasing yearly since 1985. (2) In America and Africa, the frequency of Level III floods has increased monotonically. At the same time, the frequency of Level I floods in Europe and Level II floods in Asia has increased significantly. (3) For Europe and Asia, most of the deaths occurred with Level II floods; while for America and Africa, Level III floods caused the most mortality. (4) The top three factors contributing to the spatial heterogeneity in flood-induced mortality were the affected population, GDP per capita and flood duration. The contribution of each factor varied among the different types of floods. Topographic factors (percentage of mountainous area) magnified flood-induced mortality during extreme events with heavy rainfall, especially for Level III floods. The heterogeneity in flood frequency and flood-induced mortality indicates that flood protection measures should be more targeted. In addition, the increase in large-scale floods (Level III) highlights the need for transregional cooperation in flood risk management.

Land Subsidence in the Texas Coastal Bend: Locations, Rates, Triggers, and Consequences

Land subsidence and sea level rise are well-known, ongoing problems that are negatively impacting the entire Texas coast. Although ground-based monitoring techniques using long-term global navigation satellite systems (GNSS) records provide accurate subsidence rates, they are labor intensive, expensive, time-consuming, and spatially limited. In this study, interferometric synthetic aperture radar (InSAR) data and techniques were used to map the locations and quantify rates of land subsidence in the Texas Coastal Bend region during the period from October 2016 to July 2019. InSAR-derived land subsidence rates were then validated and calibrated against GNSS-derived rates. The factors controlling the observed land subsidence rates and locations were investigated. The consequences of spatial variability in land subsidence rates in Coastal Bend were also examined. The results indicated that: (1) land subsidence rates in the Texas Coastal Bend exhibited spatial variability, (2) InSAR-derived land subsidence rates were consistent with GNSS-derived deformation rates, (3) land subsidence in the Texas Coastal Bend could be attributed mainly to hydrocarbon and groundwater extraction as well as vertical movements along growth faults, and (4) land subsidence increased both flood frequency and severity in the Texas Coastal Bend. Our results provide valuable information regarding not only land deformation rates in the Texas Coastal Bend region, but also the effectiveness of interferometric techniques for other coastal rural areas around the globe.

Hydroclimatic variability of opposing Late Pleistocene climates in the Levant revealed by deep Dead Sea sediments

Annual and decadal-scale hydroclimatic variability describes key characteristics that are embedded into climate in situ and is of prime importance in subtropical regions. The study of hydroclimatic variability is therefore crucial to understand its manifestation and implications for climate derivatives such as hydrological phenomena and water availability. However, the study of this variability from modern records is limited due to their relatively short span, whereas model simulations relying on modern dynamics could misrepresent some of its aspects. Here we study annual to decadal hydroclimatic variability in the Levant using two sedimentary sections covering ∼ 700 years each, from the depocenter of the Dead Sea, which has been continuously recording environmental conditions since the Pleistocene. We focus on two series of annually deposited laminated intervals (i.e., varves) that represent two episodes of opposing mean climates, deposited during MIS2 lake-level rise and fall at ∼ 27 and 18 ka, respectively. These two series comprise alternations of authigenic aragonite that precipitated during summer and flood-borne detrital laminae deposited by winter floods. Within this record, aragonite laminae form a proxy of annual inflow and the extent of epilimnion dilution, whereas detrital laminae are comprised of sub-laminae deposited by individual flooding events. The two series depict distinct characteristics with increased mean and variance of annual inflow and flood frequency during “wetter”, with respect to the relatively “dryer”, conditions, reflected by opposite lake-level changes. In addition, decades of intense flood frequency (clusters) are identified, reflecting the in situ impact of shifting centennial-scale climate regimes, which are particularly pronounced during wetter conditions. The combined application of multiple time series analyses suggests that the studied episodes are characterized by weak and non-significant cyclical components of sub-decadal frequencies. The interpretation of these observations using modern synoptic-scale hydroclimatology suggests that Pleistocene climate changes resulted in shifts in the dominance of the key synoptic systems that govern rainfall, annual inflow and flood frequency in the eastern Mediterranean Sea over centennial timescales.

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

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 425 million EUR. 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 program. This HPE was characterized by successive, well-organized convective structures that impacted a spatial extent of 7500 km2, with rainfall amounts equal 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, simple scaling theory between flood magnitude and total rainfall amount is explored.

Projecting Hydrological Responses to Climate Change Using CMIP6 Climate Scenarios for the Upper Huai River Basin, China

The influence of climate change on the regional hydrological cycle has been an international scientific issue that has attracted more attention in recent decades due to its huge effects on drought and flood. It is essential to investigate the change of regional hydrological characteristics in the context of global warming for developing flood mitigation and water utilization strategies in the future. The purpose of this study is to carry out a comprehensive analysis of changes in future runoff and flood for the upper Huai River basin by combining future climate scenarios, hydrological model, and flood frequency analysis. The daily bias correction (DBC) statistical downscaling method is used to downscale the global climate model (GCM) outputs from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) and to generate future daily temperature and precipitation series. The Xinanjiang (XAJ) hydrological model is driven to project changes in future seasonal runoff under SSP245 and SSP585 scenarios for two future periods: 2050s (2031–2060) and 2080s (2071–2100) based on model calibration and validation. Finally, the peaks over threshold (POT) method and generalized Pareto (GP) distribution are combined to evaluate the changes of flood frequency for the upper Huai River basin. The results show that 1) GCMs project that there has been an insignificant increasing trend in future precipitation series, while an obvious increasing trend is detected in future temperature series; 2) average monthly runoffs in low-flow season have seen decreasing trends under SSP245 and SSP585 scenarios during the 2050s, while there has been an obvious increasing trend of average monthly runoff in high-flow season during the 2080s; 3) there is a decreasing trend in design floods below the 50-year return period under two future scenarios during the 2050s, while there has been an significant increasing trend in design flood during the 2080s in most cases and the amplitude of increase becomes larger for a larger return period. The study suggests that future flood will probably occur more frequently and an urgent need to develop appropriate adaptation measures to increase social resilience to warming climate over the upper Huai River basin.

Probabilistic interval estimation of design floods under non-stationary conditions by an integrated approach

Quantifying the uncertainty of non-stationary flood frequency analysis is very crucial and beneficial for planning and design of water engineering projects, which is fundamentally challenging especially in the presence of high climate variability and reservoir regulation. This study proposed an integrated approach that combined the Generalized Additive Model for Location, Scale and Shape parameters (GAMLSS) method, the Copula function and the Bayesian Uncertainty Processor (BUP) technique to make reliable probabilistic interval estimations of design floods. The reliability and applicability of the proposed approach were assessed by flood datasets collected from two hydrological monitoring stations located in the Hanjiang River of China. The precipitation and the reservoir index were selected as the explanatory variables for modeling the time-varying parameters of marginal and joint distributions using long-term (1954–2018) observed datasets. First, the GAMLSS method was employed to model and fit the time-varying characteristics of parameters in marginal and joint distributions. Second, the Copula function was employed to execute the point estimations of non-stationary design floods. Finally, the BUP technique was employed to perform the interval estimations of design floods based on the point estimations obtained from the Copula function. The results demonstrated that the proposed approach can provide reliable probabilistic interval estimations of design floods meanwhile reducing the uncertainty of non-stationary flood frequency analysis. Consequently, the integrated approach is a promising way to offer an indication on how design values can be estimated in a high-dimensional problem.