An Exploratory Optimal Framework of Low Impact Development Measures Spatial Arrangement based on Source Tracking for Urban Flood Mitigation

Urban areas are vulnerable to flooding as a result of climate change and population growth and thus rainstorm-induced flood losses are becoming increasingly severe. Low impact development (LID) measures are a storm management technique designed for controlling runoff in urban areas, which is critical for solving urban flood hazard. Therefore, this study developed an exploratory simulation-optimization framework for the spatial arrangement of LID measures. The proposed framework begins by applying a numerical model to simulate hydrological and hydrodynamic processes during a storm event, and the urban flood model coupled with the source tracking method was then used to identify the flood source areas. Next, based on source tracking data, the LID investment in each subcatchment was determined using the inundation volume contribution ratio of the flood source area (where most of the investment is required) to the flood hazard area (where most of the flooding occurs). Finally, the resiliency and sustainability of different LID scenarios were evaluated using several different storm events in order to provide suggestions for flooding predictions and the decision-making process. The results of this study emphasized the importance of flood source control. Furthermore, to quantitatively evaluate the impact of inundation volume transport between subcatchments on the effectiveness of LID measures, a regional relevance index (RI) was proposed to analyze the spatial connectivity between different regions. The simulation-optimization framework was applied to Haikou City, China, wherein the results indicated that LID measures in a spatial arrangement based on the source tracking method are a robust and resilient solution to flood mitigation. This study demonstrates the novelty of combining the source tracking method and highlights the spatial connectivity between flood source areas and flood hazard areas. Further, the framework acts as a strategic tool for the effective spatial arrangement design of LID measures.

A review of modelling methodologies for flood source area (FSA) identification

Flooding is an important global hazard that causes an average annual loss of over 40 billion USD and affects a population of over 250 million globally. The complex process of flooding depends on spatial and temporal factors such as weather patterns, topography, and geomorphology. In urban environments where the landscape is ever-changing, spatial factors such as ground cover, green spaces, and drainage systems have a significant impact. Understanding source areas that have a major impact on flooding is, therefore, crucial for strategic flood risk management (FRM). Although flood source area (FSA) identification is not a new concept, its application is only recently being applied in flood modelling research. Continuous improvements in the technology and methodology related to flood models have enabled this research to move beyond traditional methods, such that, in recent years, modelling projects have looked beyond affected areas and recognised the need to address flooding at its source, to study its influence on overall flood risk. These modelling approaches are emerging in the field of FRM and propose innovative methodologies for flood risk mitigation and design implementation; however, they are relatively under-examined. In this paper, we present a review of the modelling approaches currently used to identify FSAs, i.e. unit flood response (UFR) and adaptation-driven approaches (ADA). We highlight their potential for use in adaptive decision making and outline the key challenges for the adoption of such approaches in FRM practises.

A spatial framework to explore needs and opportunities for interoperable urban flood management

Managing current and future urban flood risks must consider the connection (i.e. interoperability) between existing (and new) infrastructure systems to manage stormwater (pluvial flooding). Yet, due to a lack of systematic approaches to identify interoperable flood management interventions, opportunities are missed to combine investments of existing infrastructure (e.g. drainage, roads, land use and buildings) with blue-green infrastructure (e.g. sustainable urban drainage systems, green roofs, green spaces). In this study, a spatial analysis framework is presented combining hydrodynamic modelling with spatial information on infrastructure systems to provide strategic direction for systems-level urban flood management (UFM). The framework is built upon three categories of data: (i) flood hazard areas (i.e. characterize the spatial flood problem); (ii) flood source areas (i.e. areas contributing the most to surface flooding); (iii) the interoperable potential of different systems (i.e. which infrastructure systems can contribute to water management functions). Applied to the urban catchment of Newcastle-Upon-Tyne (UK), the study illustrates the novelty of combining spatial data sources in a systematic way, and highlights the spatial (dis)connectivity in terms of flood source areas (where most of the flood management intervention is required) and the benefit areas (where most of the reduction in flooding occurs). The framework provides a strategic tool for managing stormwater pathways from an interoperable perspective that can help city-scale infrastructure development that considers UFM across multiple systems. This article is part of the theme issue ‘Urban flood resilience’.

Evaluation of coupled ANN-GA model to prioritize flood source areas in ungauged watersheds

An important step in flood control planning is identification of flood source areas (FSAs). This study presents a methodology for identifying FSAs. Unit flood response (UFR) approach has been proposed to quantify FSAs at subwatershed and/or cell scale. In this study, a distributed ModClark model linked with Muskingum flow routing was used for hydrological simulations. Furthermore, a fuzzy hybrid clustering method was adopted to identify hydrological homogenous regions (HHRs) resulting in clusters involving the most effective variables in runoff generation as selected through factor analysis (FA). The selected variables along with 50-year rainfall were entered into an artificial neural network (ANN) model optimized via genetic algorithm (GA) to predict flood index (FI) at cell scale. The case studies were two semi-arid watersheds, Tangrah in northeastern Iran and Walnut Gulch Experimental Watershed in Arizona. The results revealed that the predicted values of FI via ANN-GA were slightly different from those derived via UFR in terms of mean squared error (MSE), mean absolute error (MAE), and relative error (RE). Also, the prioritized FSAs via ANN-GA were almost similar to those of UFR. The proposed methodology may be applicable in prioritization of HHRs with respect to flood generation in ungauged semi-arid watersheds.

Climate Change Impact on Flood Frequency and Source Area in Northern Iran under CMIP5 Scenarios

This study assessed the impact of climate change on flood frequency and flood source area at basin scale considering Coupled Model Intercomparison Project phase 5 General Circulation Models (CMIP5 GCMs) under two Representative Concentration Pathways (RCP) scenarios (2.6 and 8.5). For this purpose, the Soil and Water Assessment Tool (SWAT) hydrological model was calibrated and validated for the Talar River Basin in northern Iran. Four empirical approaches including the Sangal, Fill–Steiner, Fuller, and Slope-based methods were used to estimate the Instantaneous Peak Flow (IPF) on a daily basis. The calibrated SWAT model was run under the two RCP scenarios using a combination of twenty GCMs from CMIP5 for the near future (2020–40). To assess the impact of climate change on flood frequency pattern and to quantify the contribution of each subbasin on the total discharge from the Talar River Basin, Flood Frequency Index (FFI) and Subbasin Flood Source Area Index (SFSAI) were used. Results revealed that the projected climate change will likely lead to an average discharge decrease in January, February, and March for both RCPs and an increase in September and October for RCP 8.5. The maximum and minimum temperature will likely increase for all months in the near future. The annual precipitation could increase by more than 20% in the near future. This is likely to lead to an increase of IPF. The results can help managers and policy makers to better define mitigation and adaptation strategies for basins in similar climates.

Sentinel lymph node scintigraphy in cutaneous melanoma using a planar calibration phantom filled with Tc-99m pertechnetate solution for body contouring

Background and aims. Melanoma is a disease that has an increasing incidence worldwide. Sentinel lymph node scintigraphy is a diagnostic tool that offers important information regarding the localization of the sentinel lymph nodes offering important input data to establish a pertinent and personalized therapeutic strategy. The golden standard in body contouring for sentinel lymph node scintigraphy is to use a planar flood source of Cobalt-57 (Co-57) placed behind the patients, against the gamma camera. The purpose of the study was to determine the performance of the procedure using a flood calibration planar phantom filled with aqueous solution of Technetion-99m (Tc-99m) in comparison with the published data in literature where the gold standard was used.Methods. The study was conducted in the Department of Nuclear Medicine of Oncology Institute “Prof. Dr. Ion Chiricuţă” Cluj-Napoca in 95 patients, 31 males and 64 females. The localization of the lesions was grouped by anatomical regions as follows: 23 on lower limbs, 17 on upper limbs, 45 on thorax and 10 on abdomen. The calibration flood phantom containing aqueous solution of Tc-99m pertechnetate was used as planar source to visualize the body contour of the patients for a proper anatomic localization of detected sentinel lymph nodes. The radiopharmaceutical uptake in sentinel lymph nodes has been recorded in serial images following peritumoral injection of 1 ml solution of Tc-99m albumin nanocolloids with an activity of 1 mCi (37 MBq). The used protocol consisted in early acquired planar images within 15 minutes post-injection and delayed images at 2-3 hours and when necessary, additional images at 6-7 hours. The acquisition matrix used was 128x128 pixels for an acquisition time of 5 - 7 minutes. The skin projection of the sentinel lymph nodes was marked on the skin and surgical removal of detected sentinel lymph nodes was performed the next day using a gamma probe for detection and measurements.Results. The sentinel lymph nodes were detected in 92 cases and confirmed with the gamma probe during the surgical procedure. The localization of the lymph nodes was as follows: for the tumors localized on lower limb 23 lymph nodes were localized in inguinal region, for the tumors localized on upper limb, 17 lymph nodes were localized in axilla, for the tumors localized on the thorax, 40 lymph nodes were localized in axilla and 3 were localized in the inguinal region; for the tumors localized on the abdomen, 1 lymph node was localized in axilla and 8 lymph nodes was localized in inguinal region. Regarding the negative sentinel lymph node cases, 2 cases were registered for primarily lesions localized on thorax and 1 for a lesion localized on abdomen. According to histology, 26 cases revealed lymphatic metastatic invasion. Dose rates measured at 1m from the calibrator phantom had an average value of 3.46 μSv/h (SD 0.19) and at 1.4m, the value was 2.57 μSv/h (SD 0.22). Dose rates measured at the same distances from the Co-57 planar flood source had a average values of 32.5μSv/h (SD 0.11) respectively 24.1 μSv/h (SD 0.14).Conclusion. The planar calibration flood phantom is an effective tool for body contouring in sentinel lymph node scintigraphy and offers accurate anatomical information to efficiently localize the detected sentinel lymph nodes in melanoma, being for the first time used and mentioned as a pertinent alternative in our department.

TREND ANALYSIS OF PRECIPITATION DATA IN FLOOD SOURCE AREAS OF KELANTAN RIVER BASIN

Rainfall is one of the most important climatic elements that influence both the spatial and temporal water availability. Therefore, identification of its trend over years is vital for detection of extreme climatic changes. The purpose of this study is to investigate the variability of precipitation in flood source areas of Kelantan river basin by detecting precipitation flood changes in the temporal structure for the period of 1984-2014. A total of 17 rain gage stations with at least 25 years’ records in the temporal structure for the period 1984-2014 were selected. For the AMF data, 4 gauging stations were selected for the analysis. Mann-Kendall and Sen slope estimator tests were used to detect possible precipitation trend. This resulted in the detection of non-statistically significant trend in the annual maximum series of 24-hr precipitation in 12 of the 17 selected rain gauge locations and statistically significant trend in 5 locations for the period under study. Whereas, the AMF series signaled significance at 5% level in all the stations. This may be as a result of watershed characteristics such as land use changes soil, topography, of the study area which needs to be studied in detail.