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Does Deforestation Trigger Severe Flood Damage at Hoeryeong City in North Korea?

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Does Deforestation Trigger Severe Flood Damage at Hoeryeong City in North Korea? Article Does Deforestation Trigger Severe Flood Damage at Hoeryeong City in North Korea? Joongbin Lim 1 , Kyoung-Min Kim 1 and Kyoo-Seock Lee 2,* 1 Inter-Korean Forest Research Team, Division of Global Forestry, Department of Forest Policy and Economics, National Institute of Forest Science, 57 Hoegi-ro, Dongdaemun-gu, Seoul 02455, Korea 2 Department of Landscape Architecture, Graduate School, Sungkyunkwan University, Suwon 16419, Korea * Correspondence: [email protected]; Tel.: +82-31-290-7845 Received: 4 August 2019; Accepted: 9 September 2019; Published: 11 September 2019 Abstract: North Korea has suffered flood damage every year since 1995. It is assumed that this damage is linked to deforestation. Therefore, the purpose of this study was to investigate the effects of deforestation on the occurrence of floods in North Korea using spatial statistical techniques. The research was conducted at Hoeryeong City, which experienced disastrous flooding in 2016. A land-use change map was produced using two Landsat data sets from 1977 and 2016. The flood- damaged areas map, landform map, and the distance from the nearest stream map were also used in the spatial statistical analysis. In the deforestation zone, area of soil loss over 200 tons/yr increased by 14 km2 (16.6%), while that under 50 tons/yr decreased by 25 km2 (29.3%). In addition, the land-use change, runoff coefficient, and peak time runoff increased from 0.31 to 0.46, 56.3 mm/hr to 60.8 mm/hr, and 128.2 m3/sec to 206.6 m3/sec, respectively. Also, spatial statistical analysis results showed that land-use change was concluded to strongly affect the occurrence of floods. In conclusion, deforestation at Hoeryeong City contributed to severe flooding due to changes in land-use policy. The results of this study will help decision makers to establish the North Korean forest restoration policy and countermeasures against flood damage. Keywords: land-use policy; deforestation; RUSLE; soil loss; runoff change 1. Introduction North Korea has suffered flood damage every year since 1995, with serious damage occurring in 1995, 2007, 2012, and 2016 [1,2]. Hoeryeong City in particular experienced heavy rains brought by Typhoon Lionrock, which overflowed the Tumen River and brought enormous amounts of water into the plains on August 30, 2016. Due to that flood, some 68,900 people lost their homes, 11,600 houses were destroyed, and 29,800 other houses suffered massive damage [3]. This damage has been attributed to deforestation in North Korea [1,2,4–6]. Forests have been changed to newly developed croplands along the gentle hillslope for national economic difficult after 1980 in North Korea [1,2,4,5,7–9]. The developed croplands are named Darakbat (terraced crop field with embankment) and Bitalbat (titled crop field developed on the original hillslope) [9]. Flooding by deforestation has been studied by several research groups [10–12]. Bradshaw et al. [10] showed that deforestation has a negative correlation with flood frequency using generalized linear and mixed-effects models with data collected from 1990 to 2000 from 56 developing countries. The most frugal models estimated that for over 65% of the variation in flood frequency, almost 14% was due to forest cover variables alone. Tan-Soo et al. [11] investigated the effects of deforestation on flood-mitigation services in Peninsular Malaysia using detailed data on both flood events and land-use change for 31 river basins. They found Forests 2019, 10, 789; doi:10.3390/f10090789 www.mdpi.com/journal/forests Forests 2019, 10, 789 2 of 14 that the change of inland tropical forests to oil palm and rubber plantations significantly raised the number of flood days during the wettest months of the year. De la Paix et al. [12] analyzed soil degradation and changed flood risks as a result of deforestation. Their results showed that deforestation caused by the use of fuelwood and competition for agriculture land led to increased soil erosion and floods. Besides, land-use change effects on flooding have been studied by comparing runoff change and flood occurrence [13–16]. Lin et al. [13] investigated runoff responses on daily, annual, and monthly time scales using SWAT (Soil and Water Assessment Tool) at Jinjiang, a coastal catchment of southeast China. They found that, between 1985 and 2006, in land-use scenarios, daily runoff changes were more significant than monthly or annual time scales. Moreover, their simulations showed that deforestation decreased evapotranspiration, percolation loss to depth, and led to high runoff. Ye et al. [14] investigated runoff changes due to development in Mt. Kyeryong National Park in South Korea, finding that increased runoff volume was due to deforestation by development. Guo et al. [15] used the SWAT model to investigate the effects of climate, land-use, and land-cover on hydrology and streamflow in the Xinjiang River basin of the Poyang Lake. A notable finding of this study is that deforestation increases flood potential and also enhances the impact of drought. Nirupama and Simonovic [16] showed a relationship between an impervious area and river flows using remote sensing techniques and the relevant meteorological and hydrological data. A floods risk has been considerably elevated between 1974 and 2000 due to dense urbanization in the watershed of the Upper Thames River in the City of London, Ontario in Canada. However, no statistically valid or numerical approach has been used to test deforestation effects on flooding. Thus, it is necessary to investigate a spatial statistical and numerical approach for this assumption. The K-function [17,18] has been widely used to study the spatial correlation of mapped point data [19]. Okabe and Yamada [20] developed a method to conduct the K-function analysis of point correlation in a network. This technique is used in various fields for investigating the relationship between two spatial groups [19,21,22]. Spooner et al. [19] investigated a spatial analysis of roadside Acacia populations on a road network using the network K-function for univariate analysis and network cross K- function for bivariate analysis. The point location data for roadside populations of three Acacia species in a fragmented agricultural landscape of south-eastern Australia were used in this study. They suggested that the network K-function method will become a useful statistical tool for the analyses of ecological data along roads, field margins, streams, and other networks. Yamada and Thill [21] compared planar and network K-function in traffic accident analysis to illustrate the risk of false-positive detection associated with the use of a statistic designed for a planar space to analyze a network constrained phenomenon. Analyses were implemented based on Monte Carlo simulation and applied to 1997 traffic accident data in the Buffalo, NY area. Their results indicated that the planar K-function analysis is problematic since it entails a significant change of over detection clustered patterns. The network K-function can be regarded as the most reliable method to analyze traffic accident data. Dai et al. [22] investigated the impact of the built environment on pedestrian crashes and the identification of crash clusters on an urban university campus of Georgia State University. They used pedestrian crash data with network kernel density estimation and network K-function. They suggested that the findings can be used to understand the correlation between the built environment and pedestrian safety to prioritize the high-density zones for intervention efforts and to formulate research hypotheses for investigating pedestrian crashes. As we have seen in the literature review, network cross K-function can be used to analyze the correlation between the two spatial data. However, there were no studies to investigate the deforestation effect on Flood-damaged Areas (FDAs) using network cross K-function yet. Therefore, the purpose of this study was to investigate the effects of deforestation on the occurrence of floods at Hoeryeong City in North Korea through spatial statistical techniques. This study was an Forests 2019, 10, x FOR PEER REVIEW 3 of 15 Forests 2019, 10, 789 3 of 14 decision-makers to establish the North Korean forest restoration policy and countermeasures against extensionflood damage. of the previous study [2]. Ultimately this study was implemented to help decision-makers to establish the North Korean forest restoration policy and countermeasures against flood damage. 2. Materials and Methods 2. Materials and Methods 2.1. Study Area 2.1. Study Area The research was conducted at Hoeryeong City (42° 26’ N, 129° 45’ E, 1,754 km2) in northern 2 NorthThe Korea research (Figure was 1), conducted which experienced at Hoeryeong disastro City (42us◦ flood26’ N, damage 129◦ 45’ E,in 1,7542016 kmby Typhoon) in northern Lionrock. North KoreaThe city (Figure has a1 typical), which temperate experienced continental disastrous climate flood damagewith four in distinct 2016 by seasons. Typhoon Temperatures Lionrock. The range city hasfrom a typicallows between temperate −5 and continental −17°C in climate January with to highs four distinct between seasons. 16 and Temperatures25°C in August. range Due from to moist lows betweenair coming5 from and the17 ◦PacificC in January Ocean, to the highs summer between is ho 16t and and humid 25◦C in [23]. August. The yearly Due to average moist air rainfall coming of − − fromapproximately the Pacific 1077 Ocean, mm the occurs summer predominantly is hot and humid during [23]. the The July yearly and average August rainfallmonsoon of approximately season [2,24]. 1077Due mmto air occurs masses predominantly coming from during Siberia, the the July winter and Augustis dry and monsoon cold [25]. season Geographically, [2,24]. Due to airthe masses city is comingmountainous from Siberia, with high the peaks winter and is dry hills and of coldMt. Obong [25]. Geographically, and Mt.
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