Detecting Flood Variations in Shanghai over 1949–2009 with Mann-Kendall Tests and a Newspaper-Based Database

Abstract

Abstract:A valuable aid to assessing and managing flood risk lies in a reliable database of historical floods. In this study, a newspaper-based flood database for Shanghai (NFDS) for the period 1949-2009 was developed through a systematic scanning of newspapers. After calibration and validation of the database, Mann-Kendall tests and correlation analysis were applied to detect possible changes in flood frequencies. The analysis was carried out for three different flood types: overbank flood, agricultural waterlogging, and urban waterlogging. The compiled NFDS registered 146 floods and 92% of them occurred in the flood-prone season from June to September. The statistical analyses showed that both the annual flood and the floods in June-August increased significantly. Urban waterlogging showed a very strong increasing trend, probably because of insufficient capacity of urban drainage system and impacts of rapid urbanization. By contrast, the decrease in overbank flooding and the slight increase in agricultural waterlogging were likely because of the construction of river levees and seawalls and the upgrade of agricultural drainage systems, respectively. This OPEN ACCESSWater 2015, 7 1809 study demonstrated the usefulness of local newspapers in building a historical flood database and in assessing flood characterization.

Analyzing explanatory factors of urban pluvial floods in Shanghai using geographically weighted regression

“…For example, a survey of 351 cities across mainland China found that 62 % experienced at least one pluvial flood per year, and that 74.6 % of the cities had been inundated to a depth of more than 50 mm during (Xie 2013. In Shanghai in particular, urban pluvial floods were found to have increased significantly between 1949 and 2009 (Du et al 2015a).…”

“…Although disaster databases have been established on global (Guha-Sapir et al 2015), national (Shi et al 2000;Rashid 2011), and regional scales (Llasat et al 2009), only a few databases have detailed urban pluvial floods with high spatial resolution (GRIP 2015). Fine-scale databases have been recently established on the basis of telephone questionnaires (Merz et al 2013), citizen complaints (Gaitan and ten Veldhuis 2015), insurance claims (Spekkers et al 2013), and newspaper reports (Du et al 2015a).…”

“…The GWR model can analyze spatially explicit relationships between explanatory factors and a dependent variable (Osborne et al 2007;Harris et al 2014), and so it is expected to better reflect the non-stationarity and heterogeneity of urban pluvial flood systems. In this study, Shanghai is used as a case study for the model, as the frequent pluvial floods in this global metropolis have attracted widespread attention (Shi et al 2010;Du et al 2015a). …”

Simulation and Prediction of Climate Variability and Assessment of the Response of Water Resources in a Typical Watershed in China

“…The Mann-Kendall test (M-K test) assessed the trends and abrupt changes in a time series [59], and linear trend analyses were used for temperature analyses [60]; and Ens indicates how well the plot of observed versus simulated data fits the 1:1 line. A value of 0.75 < Ens ≤ 1.00 is very good, 0.65 < Ens ≤ 0.75 is good, 0.5 < Ens ≤ 0.65 is satisfactory, and Ens ≤ 0.5 is unsatisfactory [56].…”

“…The Mann-Kendall test (M-K test) assessed the trends and abrupt changes in a time series [59], and linear trend analyses were used for temperature analyses [60]; and the five-year moving average and accumulating anomalies were applied to the precipitation analysis.…”