Simulation Study on the Effect of Sponge Transformation in Old Neighborhoods Based on XP Drainage Model Construction

To address the practical application of runoff reduction and control effects of sponge measures at the building plot scale, XP Drainage was applied to construct a hydrological-hydraulic model and systematically analyze the runoff reduction and control effects of three typical sponge measures, such as storage pond, recessed green space and permeable pavement, by setting up and simulating sponge modification scenarios [1]. The results show that the effect of flood peak reduction and control is recessed green area > storage pond > permeable pavement, the effect of runoff reduction and control is storage pond > recessed green area > permeable pavement, and the effect of various sponge measures on rainfall runoff reduction and delay is good for the recurrence period below 1 in 10 years, and when the rainfall recurrence period reaches 1 in 10 years and above, the proportion of runoff and flood peak reduction decreases to different degrees, and the effect of rainfall storage for high recurrence period is not The results of the study can provide important reference values for the transformation of sponge measures in Xi’an urban districts.

Analysis of Small and Medium–Scale River Flood Risk in Case of Exceeding Control Standard Floods Using Hydraulic Model

Exceeding control standard floods pose threats to the management of small and medium–scale rivers. Taking Fuzhouhe river as an example, this paper analyzes the submerged depth, submerged area and arrival time of river flood risk in the case of exceeding control standard floods (with return period of 20, 50, 100 and 200 years) through a coupled one– and two–dimensional hydrodynamic model, draws the flood risk maps and proposes emergency plans. The simulation results of the one–dimensional model reveal that the dikes would be at risk of overflowing for different frequencies of floods, with a higher level of risk on the left bank. The results of the coupled model demonstrate that under all scenarios, the inundation area gradually increases with time until the flood peak subsides, and the larger the flood peak, the faster the inundation area increases. The maximum submerged areas are 42.73 km2, 65.95 km2, 74.86 km2 and 82.71 km2 for four frequencies of flood, respectively. The change of submerged depth under different frequency floods shows a downward–upward–downward trend and the average submerged depth of each frequency floods is about 1.4 m. The flood risk maps of different flood frequencies are created by GIS to analyze flood arrival time, submerged area and submerged depth to plan escape routes and resettlement units. The migration distances are limited within 4 km, the average migration distance is about 2 km, the vehicle evacuation time is less than 20 min, and the walking evacuation time is set to about 70 min. It is concluded that the flood risk of small and medium–scale rivers is a dynamic change process, and dynamic flood assessment, flood warning and embankment modification scheme should be further explored.

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.

Simulation of karst floods with a hydrological model improved by meteorological model coupling

Karst basins are prone to rapid flooding because of their geomorphic complexity and exposed karst landforms with low infiltration rates. Accordingly, simulating and forecasting floods in karst regions can provide important technical support for local flood control. The study area, the Liujiang karst river basin, is the most well-developed karst area in South China, and its many mountainous areas lack rainfall gauges, limiting the availability of precipitation information. Quantitative precipitation forecast (QPF) from the Weather Research and Forecasting model (WRF) and quantitative precipitation estimation (QPE) from remote sensing information by an artificial neural network cloud classification system (PERSIANN-CCS) can offer reliable precipitation estimates. Here, the distributed Karst-Liuxihe (KL) model was successfully developed from the terrestrial Liuxihe model, as reflected in improvements to its underground structure and confluence algorithm. Compared with other karst distributed models, the KL model has a relatively simple structure and small modeling data requirements, which are advantageous for flood prediction in karst areas lacking hydrogeological data. Our flood process simulation results suggested that the KL model agrees well with observations and outperforms the Liuxihe model. The average Nash coefficient, correlation coefficient, and water balance coefficient increased by 0.24, 0.19, and 0.20, respectively, and the average flood process error, flood peak error, and peak time error decreased by 13%, 11%, and 2 hours, respectively. Coupling the WRF model and PERSIANN-CCS with the KL model yielded a good performance in karst flood simulation and prediction. Notably, coupling the WRF and KL models effectively predicted the karst flood processes and provided flood prediction results with a lead time of 96 hours, which is important for flood warning and control.

Characteristics of the disastrous debris flow of Chediguan gully in Yinxing town, Sichuan Province, on August 20, 2019

On August 20, 2019, at 2 a.m., a disastrous debris flow occurred in Chediguan gully in Yinxing town, China. The debris flow destroyed the drainage groove and the bridge at the exit of the gully. In addition, the debris flow temporarily blocked the Minjiang River during the flood peak, flooding the Taipingyi hydropower station 200 m upstream and leaving two plant workers missing. To further understand the activity of the debris flow after the Wenchuan earthquake, the characteristics of this debris flow event were studied. Eleven years after the Wenchuan earthquake, a disastrous debris flow still occurred in the Chediguan catchment, causing more severe losses than those of earlier debris flows. In this paper, the formation mechanism and dynamic characteristics of this debris flow event are analysed based on a drone survey, high-definition remote sensing interpretations and other means. The catastrophic debris flow event indicates that debris flows in the Wenchuan earthquake area are still active. A large amount of dredging work in the main gully could effectively reduce the debris flow risk in the gully. In addition, it is also important to repair or rebuild damaged mitigation measures and to establish a real-time monitoring and early warning system for the high-risk gully.

The effectiveness of SuDS measures in reducing the rainwater runoff from urbanized areas

Over the last few years, climate change is one of the most important phenomena in the 21st century. It is bringing significant changes and negatively affecting the environment. This unwanted phenom causes substantial changes in climatic and hydrological characteristics that are manifested mainly in urban agglomerations. It affects extreme weather changes, the occurrence of natural disasters, water shortages, and other phenomena threatening the quality of the environment. On the other hand, there are measures close to nature based on the sustainable development of urbanized areas. Their main goal is to reduce the volume and rate of runoff and the concentration of undesirable substances in rain runoff from urban areas. Therefore, in the research study, we focus on evaluating published studies that have adopted the SuDS practices. We will compare the effectiveness of SuDS measures in capturing flood peak from surface runoff, pollution loads, and their impact on water quality. The result of this study could help select SuDS measures depending on the need to address the problem in the river basin.

An Impacts-Based Flood Decision Support System for a Tropical Pacific Island Catchment with Short Warnings Lead Time

Early warnings decision support systems are recognized as effective soft adaptation tools to prepare for the impacts of imminent flooding and minimize potential injuries and/or loss of life in flood-prone regions. This paper presents a case study of a pilot project that aimed to establish an impacts-based flood monitoring, early warnings, and decision support system for the Vaisigano River which flows through Apia, the capital of Samoa. This river is located in a characteristic short and steep catchment with rapid critical flood peak durations following periods of intense rainfall. The developed system integrates numerical weather prediction rainfall forecasts, real-time rainfall, river level and flow monitoring data, precomputed rainfall-runoff simulations, and flood inundation estimates of exposure levels and threat to human safety at buildings and on roads for different return period events. Information is ingested into a centralized real-time, web-based, flood decision support system portal that enables hydrometeorological officers to monitor, forecast and alert relevant emergency or humanitarian responders of imminent flooding with adequate lead time. This includes nowcasts and forecasts of estimated flood peak time, magnitude and likely impacts of inundation. The occurrence of three distinct extreme rainfall and flood events over the 2020/2021 tropical cyclone season provided a means to operationally test the system. In each case, the system proved adequate in alerting duty officers of imminent flooding in the Vaisigano catchment with up to 24 h warnings and response lead time. Gaps for improvement of system capabilities and performance are discussed, with recommendations for future work suggested.

Integrating Remote and In-Situ Data to Assess the Hydrological Response of a Post-Fire Watershed

Forest fire is a common concern in Mediterranean watersheds. Fire-induced canopy mortality may cause the degradation of chemical–physical properties in the soil and influence hydrological processes within and across watersheds. However, the prediction of the pedological and hydrological effect of forest fires with heterogenous severities across entire watersheds remains a difficult task. A large forest fire occurred in 2017 in northern Italy providing the opportunity to test an integrated approach that exploits remote and in-situ data for assessing the impact of forest fires on the hydrological response of semi-natural watersheds. The approach is based on a combination of remotely-sensed information on burned areas and in-situ measurements of soil infiltration in burned areas. Such collected data were used to adapt a rainfall–runoff model over an experimental watershed to produce a comparative evaluation of flood peak and volume of runoff in pre- and post-fire conditions. The model is based on a semi-distributed approach that exploits the Soil Conservation Service Curve Number (SCS-CN) and lag-time methods for the estimation of hydrological losses and runoff propagation, respectively, across the watershed. The effects of fire on hydrological losses were modeled by adjusting the CN values for different fire severities. Direct infiltration measurements were carried out to better understand the effect of fire on soil infiltration capacity. We simulated the hydrological response of the burned watershed following one of the most severe storm events that had hit the area in the last few years. Fire had serious repercussions in regard to the hydrological response, increasing the flood peak and the runoff volume up to 125% and 75%, respectively. Soil infiltration capacity was seriously compromised by fire as well, reducing unsaturated hydraulic conductivity up to 75% compared with pre-fire conditions. These findings can provide insights into the impact of forest fires on the hydrological response of a whole watershed and improve the assessment of surface runoff alterations suffered by a watershed in post-fire conditions.

Tropical cyclone flooding in the Carolinas

The climatology of tropical cyclone flooding in the Carolinas is analyzed through annual flood peak observations from 411 U.S. Geological Survey (USGS) stream gaging stations. Tropical cyclones (TCs) account for 28% of the top ten annual flood peaks, 55% of record floods, and 91% of floods with peak magnitudes at least five times greater than the 10-year floods, highlighting the prominent role of TCs for flood extremes in the Carolinas. Of all TC-related flood events, the top ten storms account for nearly 1/3 of annual flood peaks and more than 2/3 of record floods, reflecting the dominant role of a small number of storms in determining the upper tail of flood peak distributions. Analyses of the ten storms highlight both common elements and diversity in storm properties that are responsible for flood peaks. Extratropical transition and orographic enhancement are important elements of extreme TC flooding in the Carolinas. Analyses of the Great Flood of 1916 highlight the flood peak of 3115 m3 s−1 in French Broad River at Asheville, 2.6 times greater than the second-largest peak from a record of 124 years. We also examine the hydroclimatology, hydrometeorology and hydrology of flooding from Hurricanes Matthew (2016) and Florence (2018). Results point to contrasting storm properties for the two events, including tracks as well as rainfall distribution and associated physical mechanisms. Climatological analyses of vertically integrated water vapor transport (IVT) highlight the critical role of anomalous moisture transport from the Atlantic Ocean in producing extreme rainfall and flooding over the Carolinas.