Frequency and Magnitude Variability of Yalu River Flooding

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Frequency and Magnitude Variability of Yalu River Flooding Hydrol. Earth Syst. Sci., 24, 4743–4761, 2020 https://doi.org/10.5194/hess-24-4743-2020 © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License. Frequency and magnitude variability of Yalu River flooding: numerical analyses for the last 1000 years Hui Sheng1, Xiaomei Xu2, Jian Hua Gao2,3, Albert J. Kettner4, Yong Shi2, Chengfeng Xue1, Ya Ping Wang1, and Shu Gao1 1State Key Laboratory of Estuarine and Coastal Research, School of Marine Sciences East China Normal University, Shanghai, 200062, China 2School of Geography and Ocean Science, Ministry of Education Key Laboratory for Coast and Island Development, Nanjing University, Nanjing, China 3Laboratory for Marine Geology, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266061, China 4CSDMS Integration Facility, INSTAAR, University of Colorado, Boulder, CO 80309-0545, USA Correspondence: Jian Hua Gao ([email protected]) and Ya Ping Wang ([email protected]) Received: 29 October 2019 – Discussion started: 3 February 2020 Revised: 17 May 2020 – Accepted: 21 August 2020 – Published: 5 October 2020 Abstract. Accurate determination of past flooding character- cies of the Yalu River increased during 1000–1940, followed istics is necessary to effectively predict the future flood dis- by a decrease until the present day. Frequency trends were aster risk and dominant controls. However, understanding the strongly modulated by climate variability, particularly by effects of environmental forcing on past flooding frequency the intensity and frequency of rainfall events. The magni- and magnitude is difficult owing to the deficiency of observa- tudes of larger floods, events with a return period of 50 to tions (data available for less than 10 % of the world’s rivers) 100 years, increased by 19.1 % and 13.9 %, respectively, and extremely short measurement time series (< 100 years). due to climate variability over the last millennium. Anthro- In this study, a numerical model, HYDROTREND, which pogenic processes were found to either enhance or reduce generates synthetic time series of daily water discharge at flooding, depending on the type of human activities. Defor- a river outlet, was applied to the Yalu River to (1) reconstruct estation increased the magnitude of larger floods (100- and annual peak discharges over the past 1000 years and estimate 50-year floods) by 19.2 %–20.3 %, but the construction of flood annual exceedance probabilities and (2) identify and cascade reservoirs in 1940 significantly reduced their mag- quantify the impacts of climate change and human activity nitude by 36.7 % to 41.7 %. We conclude that under intensi- (runoff yield induced by deforestation and dam retention) on fied climate change and human activities in the future, effec- the flooding frequency and magnitude. Climate data obtained tive river engineering should be considered, particularly for from meteorological stations and ECHO-G climate model small- and medium-sized mountainous river systems, which output, morphological characteristics (hypsometry, drainage are at a higher risk of flood disasters owing to their relatively area, river length, slope, and lapse rate), and hydrological poor hydrological regulation capacity. properties (groundwater properties, canopy interception ef- fects, cascade reservoir retention effect, and saturated hy- draulic conductivity) form significant reliable model inputs. Monitored for decades, some proxies on ancient floods allow 1 Introduction for accurate calibration and validation of numerical model- ing. Extreme climate events have increased over the last cen- Simulations match well the present-day monitored tury, threatening human life and property (Cai et al., 2014; data (1958–2012) and the literature records of historical UNISDR, 2015; Winsemius et al., 2015). River floods are flood events (1000–1958). They indicate that flood frequen- the most common and damaging of all natural disasters glob- ally, particularly in intensely developed river basins, deltas, Published by Copernicus Publications on behalf of the European Geosciences Union. 4744 H. Sheng et al.: Frequency and magnitude variability of Yalu River flooding and coastal regions (Field et al., 2012; Jian et al., 2014). basis. The model has proven to be capable of capturing the Globally, flood damage has led to an average annual loss of range of magnitude and return intervals of peak discharge USD 104 billion, which is expected to increase in response to events on decadal, centennial, or longer climatic scales for population growth and development of flood-prone regions small- to medium-sized river basins (102–105 km2) (Syvitski (Jongman et al., 2012; UNISDR, 2015). et al., 1998; Syvitski and Morehead, 1999). Predominantly, research has been focused on the phys- The Yalu River is a typical mountainous river that flows ical and statistical characteristics of flood events, estimat- into a macro-tide estuary. Under the impacts of large peak ing flood probability and flooding frequency variability in discharges and tidal jacking, cities of China and North Ko- response to urbanization, climate change, and other factors rea in the lower reaches of the Yalu River severely suffer (Sambrook Smith et al., 2010; Munoz et al., 2015, 2018; Ket- from flood disasters (Zhai et al., 2015). Compared with other tner et al., 2018; Zhang et al., 2018). However, only short- river systems, the potential for flash flooding in mountainous term (< 100-year) fluvial gauge data exist for most rivers rivers is susceptible to both climatic events and human ac- globally, and the existing observational data are largely af- tivities (Yang and Yin, 2018). Over the past 1000 years, the fected by human activities (Milliman and Farnsworth, 2013). Yalu River witnessed a drier and cooler climatic transition These relatively short records lead to large uncertainties in during the Little Ice Age (LIA). In addition, land reclama- the predictions of future flood disasters and are problematic tion, warfare, reservoir construction, and rapid urbanization in discerning whether changes in flood frequency and mag- have influenced the hydrological characteristics of the river nitude are in response to climate change or human activities (Sheng et al., 2019). Frequent flood disasters, drastic changes (Holmes and Dinicola, 2010; Yang and Yin, 2018). Deter- in the catchment environment, and insufficient research into mining the magnitude and frequency of historical floods can flooding make the Yalu River an appropriate study area for help predict future trends in flood disasters. To date, stud- simulating, reconstructing, and identifying how flood mag- ies have used riverine sedimentological records to identify nitude and frequency have responded to climate change and the frequency and magnitude of historical floods (Gomez et human activities over the past 1000 years. al., 1995; Paola, 2003; Munoz et al., 2018). Large floods In this study, HYDROTREND is applied to numerically can leave distinctive imprints in sedimentary deposits un- reconstruct and investigate the impacts of climate change der relatively stable sedimentary environments (Sadler, 1981; and human activities (deforestation and dam retention) on Paola, 2003). However, sedimentary records are influenced the flooding frequency and magnitude for the Yalu River by a range of flooding magnitudes as well as both fre- over the past 1000 years. Present-day (1958–2012) and long- quent and rare flooding events (Magilligan et al., 1998; Sam- term (1000–1990) climate input data of the Yalu basin were brook Smith et al., 2010). Therefore, it is difficult to accu- obtained from meteorological stations (https://data.cma.cn/, rately discriminate between flood events of different scales last access: 20 May 2019) and the ECHO-G climate model. and to quantify the frequency and magnitude of past floods The climate model ECHO-G that coupled the spectral atmo- using the sedimentary record (Sambrook Smith et al., 2010). spheric model ECHAM4 and the Hamburg Ocean Primitive Numerical modeling provides an alternative to observational Equation global model (HOPE-G) generates monthly precip- or sedimentary record studies and can successfully repro- itation and temperature data of the Yalu River over the last duce basin hydrology over the long term with high accu- millennium (Liu et al., 2009, 2011). Monthly climate out- racy (Syvitski and Morehead, 1999). Consequently, to im- puts from the ECHO-G model are downscaled by the degree- prove the understanding of the main controlling factors of day module and rainfall event module in HYDROTREND, the flooding frequency and magnitude under the impact of and these can be applied to create normally distributed ran- climate change and human activities, the forward hydrologi- dom daily temperatures and synthetic daily rainfall distri- cal model HYDROTREND is applied here. butions within the month using the Monte Carlo technique HYDROTREND is a climate-driven hydrological water (Syvitski et al., 1998). Morphological characteristics (hyp- balance and transport model that simulates the daily time sometry, drainage area, slope, and latitude) and hydrologi- series of water and sediment discharge as a function of cli- cal properties (lapse rate, groundwater properties, canopy in- mate trends and drainage basin characteristics (Syvitski et terception effects, and saturated hydraulic conductivity) are al., 1998; Kettner and Syvitski, 2008). The model creates collected and processed based on the guidebook of the HY- daily water discharge at a river mouth based on a classic wa- DROTREND
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