sustainability

Article Assessing the Habitat Suitability of Dam Reservoirs: A Quantitative Model and Case Study of the Hantan River Dam,

Hyeongsik Kang 1, Myoung-Jin Um 2 and Daeryong Park 3,* 1 Division of Water Environment, Korea Environment Institute, 370 Sicheong-daero, Sejong 30147, Korea; [email protected] 2 Department of Civil and Environmental Engineering, Yonsei University, 50 Yonsei-ro, Seodaemun-gu, Seoul 03722, Korea; [email protected] 3 Department of Civil, Environmental, and Plant Engineering, Konkuk University, 120, Neungdong-ro, Gwangjin-gu, Seoul 05029, Korea * Correspondence: [email protected]; Tel.: +82-2-450-0493; Fax: +82-2-450-3726

Academic Editor: Shelley Burgin Received: 21 August 2016; Accepted: 27 October 2016; Published: 1 November 2016

Abstract: The main objective of this study was to investigate ecologically healthy regions near a dam reservoir. This study developed a model for assessing habitat suitability as a proxy for the ecological value of reservoirs. Three main factors comprising nine assessment variables were selected and classified as having a habitat suitability (HS) between 0 and 1: (1) geomorphic factors of altitude, slope steepness, and slope aspect; (2) vegetation factors of forest physiognomy, vegetation type, and tree age; and (3) ecological factors of land cover, ecological quality index, and environmental conservation value assessment. The spatial distribution of the nine HS indices was determined using geographic information systems and combined into one HS index value to determine ecologically healthy regions. The assessment model was applied to areas surrounding the Hantan River Dam, South Korea. To verify the model, wildlife location data from the national ecosystem survey of the Ministry of Environment were used. Areas with an HS index between 0.73 and 1 were found to contain 72% of observed wildlife locations. Ecologically healthy areas were identified by adding the indices of each variable. The methods shown here will be useful for establishing ecological restoration plans for dam reservoirs in South Korea.

Keywords: dam reservoir; ecological factors; environmental factors; geographic information systems; geomorphic factors; habitat suitability (HS); restoration

1. Introduction The primary influence of dam construction is on the surrounding environment and ecosystem of the river. The river changes completely in form and depth as a reservoir. Dam construction also causes habitat isolation through geomorphic separation of habitats, loss of species diversity, disruption to fish migration, and other changes due to variations in the water flow and hydrological regime, detachment of movement corridors, and species composition changes [1–3]. To understand how dam construction affects the ecosystem, there must be a comprehensive evaluation that considers various factors. The World Commission on Dams [2] analyzed how a dam influences the surrounding environment and ecosystem based on an assessment of wildlife species. Chen et al. [4] suggested a conceptual model that analyzes the environmental impact of dams in terms of the ecological network. Although the evaluation was not applied to an actual dam in that study, it was clear that more data are needed for a full quantitative evaluation. Thus far, in South Korea, there have been only a few river ecosystem evaluations or wetland function assessments [5,6]. These assessment methods

Sustainability 2016, 8, 1117; doi:10.3390/su8111117 www.mdpi.com/journal/sustainability Sustainability 2016, 8, 1117 2 of 16 quantitatively evaluate the current ecosystem, but quantifying the effects of dam construction on the ecosystem remains difficult. Given the negative effects of dams, appropriate planning for ecological restoration and adjustment is required to ameliorate the damage [7,8]. In South Korea, a guide to eco-friendly design was published by the Korea Water Resources Corporation [9], and Koo [10] examined eco-friendly ways to reduce the environmental damage that can occur during dam construction and operation. However, current dam construction and ecological restoration efforts are still insufficient, especially in the creation of restoration plans for individual dams. Therefore, to plan for effective dam reservoir ecological restoration in the future, complementary data should be gathered, including on factors needed for ecological restoration. The type and location of the most severe damage should be predicted quantitatively; standardized restoration plans should not be adjusted to each individual dam. Geographic information systems (GIS) have been applied for spatial analysis studies of ecological restoration. GIS can be used for spatial analysis assessment, and GIS-based habitat suitability models have previously been applied to specific species [11–13]. For example, Pereira and Itami [12] and Vincenzi et al. [13] suggested a GIS-based habitat suitability (HS) model for red squirrels on Mt. Graham (Arizona, USA) and a clam, Tapes philippinarum, in the Mediterranean, respectively. In addition, Kliskey et al. [11] applied pine marten and woodland caribou HS models for scenario testing in the North Columbia Mountains of British Columbia, Canada. Ortigosa et al. [14] developed a model for habitat suitability assessment known as the Valutazione della Vocazionalità Faunistica (VVF). They employed five categories, including morphologic, vegetation, trophic, meteo-climate, and anthrophic variables with GIS and various classification functions, and applied it to Capra ibex in Adamello National Park, Italy, for verification. Hirzel and Arlettaz [15] suggested a new HS model using the distance of environmental aspects and the geometric mean. They used bearded vulture habitat in the Swiss Alps as a target habitat and showed that an HS model incorporating the geometric mean was a good trade-off between the two competing constraints of generality and precision. HS studies of dams or reservoirs often focus on fish [16–18], such as carp in the Yangtze River [16], and particular fish habitats in specific rivers, such as fish habitats in the Lancang River in China [17]. Most HS-related studies deal with specific species over a large area. However, ecologically valuable regions near dam reservoir areas must also be investigated because dam reservoirs in South Korea are mostly located near river headwaters that correspond to mountainous areas, where water is abundant. Animals in these areas probably have very specific habitats located around dam reservoirs. The main objective of this study is to investigate ecologically valuable regions near dam reservoirs, considering a combination of multiple variables using GIS. Specifically, this study aims to (1) develop an HS model to investigate ecologically healthy areas using a selection of significant variables in the main environmental categories; (2) determine wildlife HS indices (HSIs) for species in the Hantan River Dam reservoir; and (3) analyze and assess the spatial characteristics of HSIs. The results of this study will assist with the successful evaluation of ecologically valuable regions near dam reservoir areas and serve as a tool for biodiversity conservation.

2. Materials and Methods

2.1. Study Area The Hantan River Dam is a flood control dam in Northern South Korea (Figure1), designed to minimize flood damage in the basin. The dam is 85 m high and 705 m long, with a total reservoir capacity of 311.3 million m3 (Figure1). The Imjin River Basin is an area that has seen increased loss of life and property damage from flooding as urbanization has rapidly progressed in line with industrial development. The basin area of the Hantan River and the Imjin River is predominantly mountainous, so the river gradient is relatively steep, and many streams pass through the valleys. The uppermost parts of the basin, at the peaks of the mountains, vary in elevation from 1500–1800 m above sea level. Therefore, after rainfall, the inflow of water increases dramatically and is the main cause SustainabilitySustainability2016 2016, ,8 8,, 1117 1117 33 ofof 1615

dramatically and is the main cause of flood damage downstream. The Paju-si and Munsam-eup of flood damage downstream. The Paju-si and Munsam-eup areas, which are at the far downstream areas, which are at the far downstream end of the Hantan River, are spread out on a large plain. The end of the Hantan River, are spread out on a large plain. The tide of the reaches within tide of the Yellow Sea reaches within 30 km of these downstream sites, which have suffered severe 30 km of these downstream sites, which have suffered severe flood damage in the past. The Hantan flood damage in the past. The Hantan River flood control dam was built to minimize flood damage River flood control dam was built to minimize flood damage by controlling the stream stage of the by controlling the stream stage of the Imjin River within the Imjin River basin, where damage most Imjin River within the Imjin River basin, where damage most often occurs during localized torrential often occurs during localized torrential downpours [19]. In this study, we chose a target area downpours [19]. In this study, we chose a target area consisting of all land within 1.0 km of the dam consisting of all land within 1.0 km of the dam reservoir border [20]. reservoir border [20].

FigureFigure 1.1. LocationLocation ofof studystudy sitesite (Hantan(Hantan RiverRiver Dam)Dam) inin thethe ImjinImjin RiverRiver Basin,Basin,South SouthKorea. Korea.

2.2.2.2. EcologicalEcological ValueValue AssessmentAssessment ModelModel ConstructionConstruction WeWe classifiedclassified thethe factorsfactors thatthat affectaffect damdam ecosystemsecosystems intointo threethree mainmain categories:categories: geomorphic,geomorphic, vegetation,vegetation, andand ecological.ecological. WeWe selectedselected threethree variablesvariables forfor eacheach categorycategory fromfrom thethe UnitedUnited StatesStates FishFish andand WildlifeWildlife ServiceService guidelines guidelines [ 21[21]] and and bounded bounded these these nine nine variables variables betweenbetween 00 andand 1,1, asas suggestedsuggested byby OrtigosaOrtigosa etet al.al. [14[14].]. Finally,Finally, wewe spatiallyspatially overlaidoverlaid allall ninenine classificationclassification mapsmaps andand producedproduced anan averageaverage wildlifewildlife HS HS map. map. Figure Figure2 shows 2 shows the the spatially-distributed spatially-distributed evaluation evaluation process process for wildlife for wildlife HSI inHSI the in Hantan the Hantan River River Dam Dam reservoir. reservoir. WeWe assigned assigned an an index index of of 1.0 1.0 to to natural natural habitats habitats or or the the most most suitable suitable conditions conditions for wildlife,for wildlife, and and 0.0 to0.0 artificial to artificial habitats habitats or the or mostthe most inappropriate inappropriate conditions conditions for wildlife. for wildlife. The indexThe index for each for each variable variable was calculatedwas calculated by multiplying by multiplying the value the value of each of variable each variable by its respectiveby its respective area and area summing and summing these values these forvalues the totalfor the area. total To area. identify To theidentify spatial the distribution spatial distribution of areas withof areas the highestwith the ecological highest ecological function, wefunction, calculated we indicescalculated from indices eachecological from each variable ecological for eachvariable map for cell. each Toanalyze map cell. and To evaluate analyze these and indicesevaluate as these a whole, indices we usedas a thewhole, map we overlay used methodthe map of overlay McHarg method [22]. The of mapMcHarg overlay [22]. method The map is aoverlay concept method of land is analysis a concept that createsof land aanalysis map for that each creates evaluation a map variable, for each overlaps evaluation the maps, variable, and createsoverlaps a compositethe maps, mapand showingcreates a total composite evaluation map values. showing It is total a common evaluation application values. ofIt GISis a datacommon [23]. Weapplication used the indicesof GIS betweendata [23]. 0–1 We for used each the of theindice nines variablesbetween 0–1 for individualfor each of maps, the nine so the variables final index for (averageindividual of individualmaps, so the indexes) final index was (average on a scale of of individual 0–1. indexes) was on a scale of 0–1. Sustainability 2016, 8, 1117 4 of 16 Sustainability 2016, 8, 1117 4 of 15

FigureFigure 2. 2. TheThe quantification quantification process process of of habitat habitat suitab suitabilityility (HS) estimation used in this study.

2.3. Application of Model to Study Area Figures 33–5–5 showshow thethe specificspecific variables,variables, conditions,conditions, andand assignedassigned indicesindices used in this study. There areare generalgeneral standards standards for for ideal ideal geomorphic geomorphic conditions, conditions, but theybut dothey not do accurately not accurately reflect specificreflect specificfeatures features of the target of the dam target area. dam area.

2.3.1. Classification Classification of Geomorphic Variables For geomorphic variables, we we used used a a digital elev elevationation model (DEM) map with a scale of 1:25,000 issued by by the the National National Geographic Geographic Information Information Institute, Institute, Korea, Korea, to extract to extract basic basic data on data altitude, on altitude, slope steepness,slope steepness, and slope and slopeaspect. aspect. Figure Figure 3 shows3 shows the the di distributionstribution and and classification classification of of altitude, slopeslope steepness, and slope aspect in the geomorphic catego categoryry for the Hantan River Dam. This study applied the evaluation evaluation method method of of the the Instream Instream Flow Flow and and Aquatic Aquatic System System Group Group [24] [24 to] todetermine determine the the ranges ranges of altitude,of altitude, slope slope steepness, steepness, and and slope slope aspect. aspect. The The ranges ranges of of altitude, altitude, slope slope steepness, steepness, and and slope slope aspect were defined defined as as follows: follows: a adominant dominant region region (contain (containinging over over 50% 50% of ofdata) data) was was assigned assigned to 1, to and 1, and all otherall other regions regions were were assigned assigned to 0.5. to 0.5.As shown As shown in Figure in Figure 3a, when3a, when the altitude the altitude was wasdivided divided into 10 into m 10intervals, m intervals, 51.4% 51.4%of measured of measured altitude altitude values were values distributed were distributed in the 100–170 in the 100–170m range.m Thus, range. a 1.0-point Thus, a 1.0-pointvalue was value assigned was assigned to the 100–170 to the 100–170 m section, m section, as it asis ita isregion a region with with a ahigh high possibility possibility of of wildlife presence, and a 0.5-point value was assigned to the remaining regions. For th thee slope steepness, 59.8% of values were distributed in the 00°–15°◦–15◦ section. Thus, a 1.0-point value was assigned to thethe 00°–15°◦–15◦ section, and and a a 0.5-point 0.5-point value value was was assigned assigned to tothe the sections sections with with other other slope slope steepness steepness (Figure (Figure 3b).3 Forb). theFor distribution the distribution of slope of slope aspect aspect in the in the target target area area,, a 1.0-point a 1.0-point value value was was assigned assigned to to flat flat land land and and to slope steepness that face 22.522.5°–157.5°◦–157.5◦ (58.1%),(58.1%), an andd a a 0.5-point value was assigned to the remainingremaining slope aspects. aspects. Sustainability 2016, 8, 1117 5 of 16

, -1-__; __ 11 """",,1.,,-0 _ .____ -"- 0"'.5'---______1 12 . · 10 -!-- .- -I- - ,- 1----· 1- - ;-

·'" - -

4 ·:- --- . 2 I-H-H..... l t o I. I , . , , , 00000 0 0 0 0 00 00000 00000000000 000 or, r_ C'\ 0 -< ,..., or. 00 0 ..... '" ,..., ..". , ___ 00 0 , , ' ...... ~ ~ " ~ .-00 C'\ 0 ..... '" ..... '" <' , 000 , , " ...... , , '", '", <',, ~, ~ ' ~I ~ ~ ~ ~ ~ ~ ~ 7 '10 '1__ "';' -:tI.OO':lOO 0 • 0 • 0 • 0 • 00• • 00000 00000000000 000 ~ 0 ---~ --or . -'0 r- ooC'\o ..... <'I ..". r_ C'\ 0 ..... '0 r_ C'\ 7 <' , ...., -" ...... '" '" <', '" <'I <', ,..., ,..., ,..., ,..., ,..., ,..., ,..., -t ..". or, ------Altitude (m)

(a) 25 1.0 0.5 2O

Co' 15 0 ' ~ 0 . ~ -0 '" 10 5

o o 0·, 5-1 0 10-1 5 15-10 20-15 25-30 30-35 35-4040-45 45-50 50-55 Slope steepness CO)

(b)

Slope (lspect CO)

(e)

Figure 3. Distribution and classification of geomorphic variables in the Hantan River Dam reservoir area: (a) Altitude; (b) Slope steepness; and (c) Slope aspect.

2.3.2. Classification of Vegetation Variables For the forest physiognomy category, we assigned indices of 1.0 for natural forest, 0.5 for plantation forest, and 0.0 for unforested areas in Figure4a. For the vegetation type category, species compositions that were closest to those of natural vegetation were considered the highest class (mixed stand forest, in this case), followed by broadleaf forest and coniferous forest, while unforested areas had the lowest score; indices are 1.0, 0.7, 0.3, and 0.0, respectively, in Figure4b. Forest age grades were assigned evenly-spaced indices from 1.0 for grade 5 to 0.2 for grade 1, with 0.0 for unforested areas, as shown in Figure4c. Sustainability 2016, 8, 1117 6 of 16 Sustainability 2016, 8, 1117 6 of 15

1 0.9 0.8 0.7 0.6 0.5 0.4 Classification 0.3 0.2 0.1 0 Mixed forest Broadleaf forest Coniferous forest Non-forest Vegetation type

1 0.9 0.8 0.7 0.6 0.5 0.4

Classification 0.3 0.2 0.1 0 Over 40 31~40 21~30 11~20 1~10 Non-forest Tree age

Figure 4. Classification of vegetation variables in the Hantan River Dam reservoir area: (a) Forest Figure 4. Classification of vegetation variables in the Hantan River Dam reservoir area: (a) Forest physiognomy; (b) Vegetation type; and (c) Tree age. physiognomy; (b) Vegetation type; and (c) Tree age.

2.3.3.2.3.3. Classification Classification of of Ecological Ecological Variables Variables TheThe Ministry Ministry of of Environment Environment [[25]25] providesprovides an ec ecologicalological quality quality index index (EQI) (EQI) map map for for terrestrial terrestrial areasareas that that divides divides the the quality quality ofof terrestrialterrestrial ecosystemsecosystems into into three three grades. grades. According According to tothe the EQI EQI map, map, GradeGrade 1 indicates1 indicates areas areas of of natural natural environmentenvironment conservationconservation and and restoration, restoration, grade grade 2 represents 2 represents areasareas that that try try to to promote promote conservationconservation of of the the natu naturalral environment, environment, and and grade grade 3 characterizes 3 characterizes areas areas in inneed need of of development. development. We Wesummed summed the areas the areas(km2) based (km2) on based grades on and grades applied and the applied indices thebased indices on basedthe following on the following classes: classes:1.0 for 1.0grade for 1, grade 0.7 1,for 0.7 grade for grade2, 0.3 2,for 0.3 grade for grade 3, and 3, and0.0 0.0for forno nodata. data. EnvironmentalEnvironmental conservation conservation valuevalue assessmentassessment (ECVA) (ECVA) is is a a process process of of scientifically scientifically assessing assessing the the geomorphicgeomorphic and and environmental environmental featuresfeatures of the land and and grading grading the the conservation conservation suitability suitability [26]. [26 ]. TheThe EVCA EVCA classifies classifies thethe entireentire countrycountry intointo fivefive grades, with with grade grade 1 1indicating indicating the the most most environmentally valuable areas and grade 5 representing those most suitable for development. environmentally valuable areas and grade 5 representing those most suitable for development. Sustainability 2016, 8, 1117 7 of 16 Sustainability 2016, 8, 1117 7 of 15

GradeGrade 4 is4 intendedis intended for environmentallyfor environmentally friendly friend development.ly development. Grade Grade 3 indicates 3 indicates buffer buffer areas betweenareas conservationbetween conservation and development. and development. The ECVA The map ECVA incorporates map incorporates 67 assessment 67 assessment values based values on criteria based of naturalness,on criteria of diversity, naturalness, rarity, diversity, vulnerability, rarity, vulnerability, and stability and [27 ].stability For EVCA [27]. classification,For EVCA classification, a value of a 1.0 isvalue used forof 1.0 grade is used 3, which for grade is the 3, wh areaich that is the has area the that highest has the class highest within class the within target the area, target 0.7 area, is used 0.7 for gradeis used 4, 0.3for forgrade grade 4, 0.3 5, for and grade 0.0 for 5, and no data,0.0 for as no shown data, as in shown Figure in5. Figure Medium-resolution 5. Medium-resolution land coverage land fromcoverage the Korea from Ministrythe Korea of Ministry Environment of Environmen was usedt towas determine used to determine existing land existing use andland coverage use and as ofcoverage 2007. Gawond-do as of 2007. [28Gawond-do] and Kang [28] et al.and [29 Kang] suggested et al. [29] land suggested cover standards land cover for standards wildlife habitat for suitability.wildlife habitat Land cover suitability. was indexed Land cover according was indexed to these according studies: naturalto these forest studies: was natural given aforest value was of 1.0, naturalgiven grasslanda value of and1.0, natural coppice grassland were 0.8, and pastures coppice and were orchards 0.8, pastures were 0.6, and rice orchards paddy were farms 0.6, or rice arable landpaddy were farms 0.4, otheror arable cultivated land were areas 0.4, were other 0.2, cultivated and urbanization areas were promotion 0.2, and urbanization and residential promotion areas were approximatelyand residential 0.0. areas were approximately 0.0.

1 0.9 0.8 0.7 0.6 0.5 0.4

Classification 0.3 0.2 0.1 0 Grade 1 Grade 2 Grade 3 No data

Ecological quality index

1 0.9 0.8 0.7 0.6 0.5 0.4

Classification 0.3 0.2 0.1 0 Grade 3 Grade 4 Grade 5 No data Environmental conservation value assessment

1 0.9 0.8 0.7 0.6 0.5 0.4 Classification 0.3 0.2 0.1 0 Forest Grassland Pasture, orchard Farmland Protected Urban area cultivation Land cover

FigureFigure 5. 5.Classification Classification of ofecological ecological variablesvariables in the the Hantan Hantan River River Dam Dam reservoir reservoir area: area: (a) ( aEcological) Ecological qualityquality index; index; (b ()b Environmental) Environmental conservationconservation value assessment; assessment; and and (c ()c )Land Land cover. cover. Sustainability 2016, 8, 1117 8 of 16

2.4. Verification of the HS Model The ecological monitoring data were based on the environmental impact assessment of the Hantan River Dam and the wildlife survey data collected after the environmental impact assessment. Data were extracted from each dataset and used in an analysis with ArcGIS 10.0 (ESRI Inc., Redlands, CA, USA). The target area was divided into a 10 m × 10 m grid. The monitoring data were assigned to each cell of the converted map. The national ecosystem survey of the Ministry of Environment has been performed at ten-year intervals to establish systematic nationwide natural conservation measures based on the ‘Natural Conservation Law into Natural Environment Conservation Act’, and the third survey was the latest to be completed. The second and third national ecosystem surveys were performed between 1997 and 2005 and between 2006 and 2012, respectively. Territories were divided by water systems and forests, and the survey was conducted on a representative mountain within the territory. A map-sheet-based survey was performed, where a single sheet of a topographic map with a 1:25,000 scale was selected as the survey unit and was divided into a nine by nine grid (203000 along the latitude and longitude), with each cell surveyed [30,31]. The national ecosystem survey in Korea contains data uncertainty because wildlife habitats are indirectly presumed from traces and excrement. However, this study adapted the national ecosystem survey data because wild animal species data are very limited in Korea. Although all species cannot be evaluated with the same criteria because each species has its own characteristics, the evaluation process in this study is suggested for general evaluations, such as the selection of dam reservoir sites. Therefore, this evaluation method will be useful for overall HS but cannot show the HS for specific wildlife. In addition, this study does not consider the uncertainty of observed wildlife habitat data because the survey period was long (1997–2013), and we assumed all environmental changes from dam construction were greater than the uncertainty within surveys. The order of wildlife migration is adapted from habitat monitoring analysis based on land cover in the . Based on these studies, the indices were unequally assigned considering the degree of their effects on wildlife migration, resulting in the following order: urbanized area and residential area > greenhouse cultivation > rice paddy and field farmland > pasture and orchard > natural grassland and shrub forest > natural forest along the Han River, South Korea [28,29].

3. Results

3.1. Spatial Assessment of Geomorphic Variables Figure6 and Table1 show the results of the geomorphic variable classification based on Figure3. Classification areas of 0.5 and 1.0 were relatively close and the dominant classification area is slightly more than 50% of the total area in Table1. Figure6 shows the spatial distribution of geomorphic variable classification indices. The geomorphic variables of altitude, slope steepness, and slope aspect have high indices at the reservoir borders and in upstream areas of the reservoir.

Table 1. Classification area of the Hantan River Dam reservoir in geomorphological variables.

Variables Classifications Grading Standard Area (103 m2) Percent (%) Recessive area (others) 0.5 367,020 48.6 Altitude Dominant area (100–170 m) 1.0 388,165 51.4 Recessive area (others) 0.5 303,584 40.2 Slope steepness Dominant area (0◦–15◦) 1.0 451,601 59.8 Recessive area (others) 0.5 316,423 41.9 Slope aspect Dominant area (Flat, 22.5◦–157.5◦) 1.0 438,762 58.1 Sustainability 2016, 8, 1117 9 of 16 Sustainability 2016, 8, 1117 9 of 15

FigureFigure 6.6. Spatial classification classification of of geomorphic geomorphic variables: variables: (a ()a )Altitude; Altitude; (b ()b Slope) Slope steepness; steepness; and and (c) (cSlope) Slope aspect. aspect.

3.2.3.2. SpatialSpatial AssessmentAssessment ofof VegetationVegetation Variables Variables TheThe resultsresults ofof thethe spatialspatial classificationclassification ofof vegetationvegetation variablesvariables areare representedrepresented inin FigureFigure7 7and and TableTable2 .2. Generally, Generally, all all three three vegetation vegetation variables variables show show similar similar results. results. The The vegetation vegetation variables variables of of forestforest physiognomy, physiognomy, vegetation vegetation type, type, and and tree tree age age show show high high scores scores in the in the downstream downstream area area and and to the to westthe west of the of midstream the midstream reservoir, reservoir, while while geomorphological geomorphological variables variables show highshow scores high upstreamscores upstream of the reservoir.of the reservoir. In particular, In forestparticular, physiognomy forest phys showsiognomy high scores shows both high upstream scores and both downstream upstream of theand reservoirdownstream (Figure of the7a). reservoir Table2 shows (Figure that 7a). natural Table forest2 shows for that forest natural physiognomy, forest for unforestedforest physiognomy, area for forestunforested type, andarea 21–30 for forest years fortype, tree and age 21–30 were theyears dominant for tree classifications, age were the respectively. dominant classifications, respectively. SustainabilitySustainability2016 2016, 8,, 1117 8, 1117 1010 of of15 16

FigureFigure 7. Spatial7. Spatial classification classification of of vegetation vegetationvariables: variables: (a) Forest physiognomy; physiognomy; (b (b) )Vegetation Vegetation type; type; andand (c) ( Treec) Tree age. age.

TableTable 2. Classification2. Classification area area of of the the Hantan Hantan River River damdam reservoirreservoir in vegetation variables. variables. Variables Classifications Grading Standard Area (103 m2) Percentage 3 2 Variables ClassificationsUnforested Grading Standard0.0 Area258,531 (10 m ) Percentage34.2 Forest physiognomy UnforestedPlantation 0.00.5 258,531181,311 24.0 34.2 Forest physiognomy NaturalPlantation forest 0.51.0 181,311315,343 41.8 24.0 NaturalNon-forest forest 1.00.0 315,343258,531 34.2 41.8 Coniferous forest 0.3 234,790 31.1 Vegetation type Non-forest 0.0 258,531 34.2 Deciduous forest 0.7 175,655 23.3 Coniferous forest 0.3 234,790 31.1 Vegetation type DeciduousMixed forest forest 0.7 1.0 175,655 86,209 11.4 23.3 MixedNon-forest forest 1.00.0 258,531 86,209 34.2 11.4 1~10 0.2 0 0.0 Non-forest11~20 0.00.4 258,53160,795 8.1 34.2 Tree age 1~10 0.2 0 0.0 21~30 0.6 173,131 22.9 11~20 0.4 60,795 8.1 Tree age 31~40 0.8 254,994 33.8 21~30 0.6 173,131 22.9 Over 40 1.0 7734 1.0 31~40 0.8 254,994 33.8 Over 40 1.0 7734 1.0 3.3. Spatial Assessment of Ecological Variables

3.3. SpatialFigure Assessment 8 and Table of Ecological 3 show Variables the results of the spatial assessment of ecological variables. Dominant classes in ecological variables are grade 2, no data, and forest for EQI, ECVA, and land cover,Figure respectively,8 and Table as3 shown show in the Table results 3. EQI of an thed land spatial cover assessment indices showed of ecological very similar variables. spatial DominantHSI distributions classes in and ecological were high variables predominantly are grade from 2, no the data, midstream and forest to the for downstream EQI, ECVA, reservoir and land cover,areas respectively, and to the asnorthwest shown in of Table upstream3. EQI areas. and land The coverECVA indices only had showed high indexes very similar in patches spatial that HSI distributions and were high predominantly from the midstream to the downstream reservoir areas and Sustainability 2016, 8, 1117 11 of 16

Sustainability 2016, 8, 1117 11 of 15 to the northwest of upstream areas. The ECVA only had high indexes in patches that coincided with highcoincided scores forwith EQI high and scores land for cover EQI variablesand land ascover well. variables Landcover as well. indices Land werecover highindices predominantly were high in thepredominantly downstream in reservoirthe downstream area (Figure reservoir8c), andarea each(Figure of the8c), vegetation and each of variables the vegetation had high variables indices had high indices primarily in the downstream area (Figure 7), which implies that the downstream primarily in the downstream area (Figure7), which implies that the downstream area should have area should have high overall ecological indices. As shown in Figure 8, the areas with high high overall ecological indices. As shown in Figure8, the areas with high vegetation variable indices vegetation variable indices also have high ecological nature status indices, and tend to be also have high ecological nature status indices, and tend to be vegetation preservation areas. vegetation preservation areas.

FigureFigure 8. Spatial8. Spatial classification classification of of ecological ecological variables:variables: (a) Ecological Ecological quality quality index; index; (b (b) Environmental) Environmental conservationconservation value value assessment; assessment; and and ( c()c) Land Land cover. cover.

TableTable 3. 3.Classification Classification area area of of the the Hantan Hantan RiverRiver Dam reservoir in in ec ecologicalological variables. variables.

Variables Classifications Grading Standard Area (103 m2)Percent (%) Variables Classifications Grading Standard Area (103 m2) Percent (%) No data 0.0 280,316 37.1 Ecological quality Grade 3 No data 0.3 0.0 51,209 280,316 37.1 6.8 index Grade 2 Grade 3 0.7 0.3 416,944 51,209 55.2 6.8 Ecological quality index Grade 1 Grade 2 1.0 0.7 6716 416,944 55.2 0.9 No data Grade 1 0.0 1.0 595,280 6716 78.8 0.9 Environmental Grade 5 No data 0.3 0.0 6716 595,280 78.8 0.9 conservationEnvironmental value Grade 4 Grade 5 0.7 0.3 153,189 6716 20.3 0.9 assessmentconservation Grade 3 Grade 4 1.0 0.7 0 153,189 20.3 0.0 value assessment Urban areaGrade 3 0.0 1.0 0 0 0.0 Protected cultivation 0.2 33,969 4.5 Urban area 0.0 0 0.0 Farmland 0.4 26,278 3.5 Land cover Protected cultivation 0.2 33,969 4.5 Pasture, orchard 0.6 184,085 24.4 Farmland 0.4 26,278 3.5 Land cover Grassland 0.8 22,942 3.0 Pasture, orchard 0.6 184,085 24.4 Forest 1.0 487,911 64.6 Grassland 0.8 22,942 3.0 Forest 1.0 487,911 64.6 Sustainability 2016, 8, 1117 12 of 16 Sustainability 2016, 8, 1117 12 of 15

3.4.3.4. Spatial Spatial Assessment Assessment of of Combined Combined Overall Overall Variables Variables TheThe map map generated generated using using the the overlay overlay method method is is shown shown in in Figure Figure 99.. AfterAfter damdam construction,construction, thethe 3 2 3 2 totaltotal study study area changedchanged fromfrom 906,457906,457× × 103 m2 toto 755,185 755,185 × 10103 mm2 (83.3%(83.3% of of the the pre-dam pre-dam area) area) owing owing toto the the rise rise in in water water levels. levels. The The total total area area of each of each evaluation evaluation index index value value (0–1) (0–1) is shown is shown in Table in Table 4. The4. areaThe areawith withan index an index value value of 0.64–0.73 of 0.64–0.73 was the was largest, the largest, at 20.0% at 20.0% of the of total the study total study area. area.The area The with area anwith evaluation an evaluation index index of less of than less 0.27 than was 0.27 only was only6.8% 6.8%of the of total the totalarea. area.Ecologically Ecologically healthy healthy areas, areas, i.e., thosei.e., those with withcumulative cumulative evaluation evaluation indexes indexes >6.5, acco >6.5,unted accounted for 20.3% for 20.3%of the oftotal the area total (0.73–0.82, area (0.73–0.82, 9.6%; 0.82–0.91,9.6%; 0.82–0.91, 9.7%; 0.91–1, 9.7%; 0.91–1, 1.0%). 1.0%).

FigureFigure 9. 9. HSIHSI values values and and wildlife wildlife locations locations in in the the Hantan Hantan River River Dam Dam reservoir reservoir area. area.

Figure 9 overlays the ecological quality map with observed wildlife locations from national Figure9 overlays the ecological quality map with observed wildlife locations from national ecosystem survey data from the Ministry of Environment [29]. This study assumed that superior ecosystem survey data from the Ministry of Environment [29]. This study assumed that superior wildlife habitats and ecologically healthy areas have an HSI between 0.73 and 1 in Table 4. Areas wildlife habitats and ecologically healthy areas have an HSI between 0.73 and 1 in Table4. Areas with with an HSI between 0.73 and 1 contain 72% of observed wildlife locations, as shown in Figure 9. an HSI between 0.73 and 1 contain 72% of observed wildlife locations, as shown in Figure9. The ecologically healthy areas are concentrated into six large areas (A–F in Figure 9). The wildlife The ecologically healthy areas are concentrated into six large areas (A–F in Figure9). The wildlife appearances are low in A and B, at 7% and 8%, respectively, and on the eastern side of the upper appearances are low in A and B, at 7% and 8%, respectively, and on the eastern side of the upper stream, where wildlife was not observed. Land use in this area is mostly fields and paddies, as stream, where wildlife was not observed. Land use in this area is mostly fields and paddies, as shown shown in Figure 8c, which explains the low ecological indices in this area; a forest patch on the in Figure8c, which explains the low ecological indices in this area; a forest patch on the western side western side of the reservoir also had a low ecological index. The areas labeled C and D have of the reservoir also had a low ecological index. The areas labeled C and D have relatively high HSIs relatively high HSIs and wildlife appeared frequently, at 24% and 11%, respectively, demonstrating and wildlife appeared frequently, at 24% and 11%, respectively, demonstrating that the results of this that the results of this study are reliable. However, for the areas labeled E and F, no wildlife study are reliable. However, for the areas labeled E and F, no wildlife appearances were noted, despite appearances were noted, despite the high HSIs. Although E and F represent relatively high classifications in terms of vegetation and ecological variables (Figures 7 and 8), wildlife appearances Sustainability 2016, 8, 1117 13 of 16 the high HSIs. Although E and F represent relatively high classifications in terms of vegetation and ecological variables (Figures7 and8), wildlife appearances were rare, at 6% and 3%, respectively. This may be a problem of accessibility, linked to the presence of fences and other restrictions. To confirm the reliability of our results, comparison with more site data will be needed. However, as our study was conducted with all available data, the results are assumed to be reliable because estimated high HSI areas (0.73–1.00) in this study matched with 72% of observed wildlife habitats locations.

Table 4. Evaluation results for ecological areas of the Hantan River Dam. HSI: Habitat Suitability Index.

Overall HSI Area (103 m2) Percent (%) 0.04–0.09 37 0.0 0.09–0.18 1275 0.1 0.18–0.27 60,764 6.7 0.27–0.36 169,932 18.7 0.36–0.45 23,647 2.6 0.45–0.55 20,593 2.3 0.55–0.64 113,426 12.5 0.64–0.73 181,640 20.0 0.73–0.82 87,199 9.6 0.82–0.91 87,740 9.7 0.91–1.00 8932 1.0 Dam reservoir 151,272 16.7 Total 906,457 100

4. Conclusions This study presented the impacts of geomorphic, vegetation, and ecological variables to an ecologically healthy area in the Hantan River Dam reservoir, South Korea, because dam construction affects those variables. We applied a standardized HSI score for each variable to quantify the nine selected variables in geomorphic, vegetation, and ecological categories. Our method can be applied to other cases, where the standardized HS index can be used to assess ecologically healthy areas near dam reservoirs. Indices such as these can also be used to plan individual ecological restoration strategies for other dam reservoir areas. The assessment model developed in this study evaluates ecologically healthy areas around dam reservoirs and can be used to make ecological restoration plans in the future. By analyzing the area and determining the ecologically healthy area, which means the area suitable for wildlife habitat, using various variables, locations of restoration points can be selected, and habitat restoration plans can be made for specific taxa by analyzing observed wildlife locations. Although this study focused on the dam reservoir area based on terrestrial animals, a similar model could, and should, be created for the effects on rivers and reservoir environments. To do so, hydraulic and water quality effects, riverbed structure, and other variables should be included as evaluation variables. Application of this HSI-based evaluation model to dam reservoirs, as well as qualification of the ecological value of the surrounding areas must be carried out through a long-term survey, and subsequent improvement to the model should follow in the future.

Acknowledgments: This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government. Author Contributions: Hyeongsik Kang designed the research and analyzed data; Myoung-Jin Um wrote and revised the manuscript; Daeryong Park wrote and revised manuscript and made a substantial contribution to the interpretation of the results. All authors read and approved the final manuscript. Conflicts of Interest: The authors declare no conflict of interest. Sustainability 2016, 8, 1117 14 of 16

References

1. Petts, G.E. Impounded Rivers; John Wiley & Sons Ltd. Publishers: Chichester, UK, 1984. 2. World Commission on Dams (WCD). Dams, Ecosystem Functions and Environmental Restoration; WCD Thematic Review Environmental Issues II.1; World Commission on Dams (WCD): London, UK, 2000. 3. Korea Environment Institute. Case Studies for Management of Environment—Friendly Dams; Korea Environment Institute: Seoul, Korea, 2003. (In Korean) 4. Chen, S.; Chen, B.; Su, M. The cumulative effects of dam project on river ecosystem based on multi-scale ecological network analysis. Procedia Environ. Sci. 2011, 5, 12–17. [CrossRef] 5. Kim, D.G.; Shin, H.K.; Kim, J.G.; Kim, H.S.; Yoo, B.K.; Ahn, K.S.; Jang, S.W. Functional Assessment of Yongdam Dam-wetland by HGM. J. Wetl. Res. 2011, 13, 665–675. (In Korean) 6. Lim, H.J.; Lee, M.W. Prior Eco-preserve Zoning through Stream Ecosystem Evaluation on Dam Basin—A Case of Yongdam-dam Watershed, Jeollabukdo Province. J. Korean Inst. Landsc. Archit. 2011, 39, 103–112. (In Korean) [CrossRef] 7. Harada, J. Conservation and Improvement of the Natural Environment in Reservoir Watersheds in Japan. Water Resour. Dev. 2002, 18, 595–610. [CrossRef] 8. Harada, J.; Nario, Y. Conservation and Improvement of the Environment in Dam Reservoirs. Water Resour. Dev. 2004, 20, 77–96. [CrossRef] 9. Korea Water Resources Corporation. A Guideline on Environment-Friendly Design; Korea Water Resources Corporation: Daejeon, Korea, 1997. (In Korean) 10. Koo, B. Ecological Conservation and Restoration Strategies on Construction and Management Projects—Focused on Dam Projects. J. Korean Soc. Restor. Reveg. Technol. 2004, 7, 1–13. (In Korean) 11. Kliskey, A.; Lofroth, E.; Thompson, W.; Brown, S.; Schreier, H. Simulating and evaluating alternative resource-use strategies using GIS-based habitat suitability indices. Landsc. Urban Plan. 1999, 45, 163–175. [CrossRef] 12. Pereira, J.; Itami, R. GIS-based habitat modeling using logistic multiple regression—A study of the Mt. Graham red squirrel. Photogramm. Eng. Remote Sens. 1991, 57, 1475–1486. 13. Vincenzi, S.; Caramori, G.; Rossi, R.; De Leo, G.A. A GIS-based habitat suitability model for commercial yield estimation of Tapes philippinarum in a Mediterranean coastal lagoon (Sacca di Goro, Italy). Ecol. Model. 2006, 193, 90–104. [CrossRef] 14. Ortigosa, G.R.; De Leo, G.A.; Gatto, M. VVF: Integrating modelling and GIS in a software tool for habitat suitability assessment. Environ. Model. Softw. 2000, 15, 1–12. [CrossRef] 15. Hirzel, A.H.; Arlettaz, R. Modeling habitat suitability for complex species distributions by environmental-distance geometric mean. Environ. Manag. 2003, 32, 614–623. [CrossRef][PubMed] 16. Yi, Y.; Wang, Z.; Yang, Z. Impact of the Gezhouba and Three Gorges Dams on habitat suitability of carps in the Yangtze River. J. Hydrol. 2010, 387, 283–291. [CrossRef] 17. Yi, Y.; Tang, C.; Yang, Z.; Chen, X. Influence of Manwan Reservoir on fish habitat in the middle reach of the Lancang River. Ecol. Eng. 2014, 69, 106–117. [CrossRef] 18. Som, N.A.; Goodman, D.H.; Perry, R.W.; Hardy, T.B. Habitat Suitability Criteria via Parametric Distributions: Estimation, Model Selection and Uncertainty. River Res. Appl. 2016, 32, 1128–1137. [CrossRef] 19. Korea Water Resources Corporation. Hantangang-Dam Environmental Impact Statements; Korea Water Resources Corporation: Daejeon, Korea, 2001. 20. Korea Ministry of Environment. The Implementation of the Riparian Buffer Zone in the Nakdong River (Notification No. 2002–140); Ministry of Environment: Sejong, Korea, 2002. (In Korean) 21. United States Fish and Wildlife Service. Standards for the Development of Habitat Suitability Index Models, Ecological Service Manual 103; Division of Ecological Service: Washington, DC, USA, 1981. 22. McHarg, I.L. Design with Nature; Natural History Press: New York, NY, USA, 1969. 23. Jang, R.I. Ecological Landscape Evaluation Compared by Visual Aspect through GIS Overlaying—A Case Study on ChonbukBuan-dam Watershed. Master’s Dissertation, Chonbuk University, Jeonju, Korea, 2008. (In Korean) 24. Instream Flow and Aquatic System Group. Development and Evaluation of Habitat Suitability Criteria for Use in the Instream Flow Incremental Methodology: Biologic Report; Instream Flow Information Paper No. 21; National Institute of Ecology: Seochun, Korea, 1986. Sustainability 2016, 8, 1117 15 of 16

25. Korea Ministry of Environment. Environment Geographic Information System; Ministry of Environment: Sejong, Korea, 2016. (In Korean) 26. Korea Ministry of Environment. The Southern R.O.K. (Republic of Korea) ECVAM(Environmental Conservation Value Assessment Map) Report; Korea Ministry of Environment: Sejong, Korea, 2005; pp. 1–11. (In Korean) 27. Kang, S.; Kim, J.-O. Morphological analysis of green infrastructure in the Seoul metropolitan area. South Korea. Landsc. Ecol. Eng. 2015, 11, 259–268. [CrossRef] 28. Gangwon-do. A Study on Ways of Restoring Riverine in Hangang Watershed; Ganwon-do: Chuncheon, Korea, 2011. (In Korean) 29. Kang, H.S.; Lee, Y.S.; Jeon, S.H. A Study on the Evaluation Method of Ecologically Fragmented Section for Restoration of the Riverine Ecobelt. J. Korean Soc. Civ. Eng. 2016, 31, 383–391. (In Korean) 30. Ministry of Environment, National Institute of Environmental Research (MOE and NIER). The Guideline of 2nd Korean Nationwide Survey on Natural Environments; Ministry of Environment and National Institute of Environmental Research: Seoul, Korea, 2006. (In Korean) 31. Ministry of Environment, National Institute of Environmental Research (MOE and NIER). The Guideline of 3rd Korean Nationwide Survey on Natural Environments; Ministry of Environment and National Institute of Environmental Research: Sejong, Korea, 2016. (In Korean)

© 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).