최근 강우 발생빈도의 불규칙한 변화로 홍수 및 가뭄 피해가 증가함에 따라 불규칙한 자연현상의 특 성을 예측하는 확률론적 방안들이 관심을 받고 있다. 본 연구에서는 자연계 현상을 확률론적으로 예측 하는 기법인 플랙탈이론의 허스트지수(Hurst exponent)를 이용한 자기유사성 평가를 전국 64개 기상관 측소의 월강수량 자료를 대상으로 실시하였다. 1986년부터 2015년까지 총 30년 동안의 월강수량을 평 가한 결과 허스트지수는 H=0.97~0.99의 범위로 나타났다. 이는 H>1/2의 양의 상관관계를 보이며, 자 기유사성을 가지는 것으로 평가될 수 있어 기존의 축척된 자료를 통해 향후의 이상강우에 대한 예측이 가능하다는 사실을 보여주는 것으로 나타났다.

본 연구에서는 농촌 소하천의 적정 환경유지용수 산정을 위한 기초조사로 경상남도 고성군 하이면 와룡 리에 위치한 봉현저수지를 수원으로 하는 봉현천과 하이저수지를 수원으로 하는 석지천을 대상으로 시기 적 우기이면서 농번기인 2010년 5월에서 10월까지 총 6회에 걸쳐 18개 지점을 선정하여 하천조사 및 유 량 모니터링을 실시하였다. 그 결과 선행 강수량이 많을 경우 하천의 전 구간에 유량이 증가하였고, 선행 강수량이 적거나 없는 경우에는 계측이 불가능할 정도로 하천이 메말라 있었다. 각 하천의 상류부의 경우 에는 항시 일정량의 유량을 확인 할 수 있었는데 이는 댐 침윤에 기인한 것으로 추정되었다. 유량 프로파 일을 작성한 결과 봉현천 하류부 2,000 m 지점과 3,500 m 지점, 석지천 하류부 1,200 m 지점에서 주변 참다래 과수원의 관개용수 양수, 참다래 보관 및 선별공장에서의 취수 및 관측지점 상류부의 연속적인 보 의 영향으로 유량이 감소하는 것을 확인할 수 있었고, 봉현천 하류부 4,200 m 지점에서는 유량이 증가하 였는데 이는 배수로를 통한 유출수의 유입에 의한 것으로 추정되었다. 향후 지속적이고 장기적인 현장 모 니터링을 통하여 농어촌환경용수 공급을 위한 적정 유지유량을 산정하는데 기초자료로 활용할 수 있을 것 으로 사료된다.

본 연구의 목적은 남강 하류의 중장기 물이용 계획을 위하여 기초적인 용수 수요와 공급가능성을 검토하는 것 이다. 중장기 물이용 계획을 담고 있는 수자원장기종합계획이나 낙동강유역조사보고서를 바탕으로 수자원단위지 도의 표준유역별 자료를 생성하여 목적별 용수 수요와 수자원 부존량을 추정하였다. 수자원 부존량은 단순 3단 TANK모형을 이용하고 표준유역별 용수 수요는 농업용수, 공업용수, 생활용수, 기타 용수 등으로 나누고 원단위 기법으로 계산하였다. 남강 하류 10개 표준유역에서의 총유출량은 925,414천 ㎥/년이고, 총 용수 수요량은 연 462,988천 ㎥인데 이중 농업용수와 생활용수가 각각 243,194천 ㎥, 105,493천 ㎥이고 공업용수가 32,686천 ㎥, 기타 81,615천 ㎥이었다. 남가람 진주혁신도시 건설을 영향을 고려한 경우는 수자원 부존량의 변화는 미미하나 신규 인구의 유입에 의한 생활용 수 수요로 17,156천 ㎥의 추가 용수가 필요할 것으로 분석되었다.

As the impacts of climate change have been emerged all the way through society, the potential risks specifically on agricultural water and facilities are recently getting concerned. Evaluating vulnerability of agriculture to climate change on is a time-tested strategy. While a number of researches on the adaption and mitigation of climate change were performed in various aspects for sustainable agricultural production, the vulnerability of management system for agricultural water and infrastructure has not been investigated yet. This study is aimed to clarify the definition of vulnerability to climate change, find the major indicators able to presume the vulnerability, and finally determine the relative importance of the indicators based on the specialist questionnaire survey and its analyses. The lists of indicators for major parts of agricultural water management such as, water use, flood control, reservoir related issues, and pumping and drainage systems are initialized referring to the related precedent studies. The primary survey was conducted in the form of Delphi to complement the list and methods and the main survey was then conducted using AHP(Analytic Hierarchy Process) technique to quantitatively prioritize the indicators. The results derived in this study would be directly adopted in weighting importance of indicators to investigate the indicator-based vulnerability analysis to climate change in agricultural water and infrastructure management.

Recently the use of smart phones and mobile devices is increasing rapidly, data search and retrieval in the mobile environments are generalized. There are only few mobile applications available in the area of agriculture while huge amount of new applications are developed and uploaded. The purpose of this study was to develop the android based mobile application for providing agricultural infrastructure and disaster information. The mobile application was designed through the database establishment and management system, server management system, and mobile application development. The database is composed of weather data, agricultural infrastructure data, and agricultural disaster data. By developing the mobile application which provides agricultural infrastructure information, it is expected to improve the accessibility to agricultural information and mitigate the agricultural disaster damages.

Smartphones change the picture of data and information sharing and make it possible to share various real-time flooding data and information. The vulnerability indicators of farmland inundation is needed to calculate the risk of farmland flood based on changeable hydro-meteorological data over time with morphologic characteristics of flood-damaged areas. To find related variables show the vulnerability of farmland inundation using the binary-logit model and correlation analysis and to provide vulnerability indicators were estimated by fuzzy set method. The outputs of vulnerability indicators were compared with the results of Monte Carlo simulation (MCS) for verification. From the result vulnerability indicators are applicable to mobile_based information system of farmland inundation.

Climate change is the most direct threatening factors in sustaining agricultural productivity. It is necessary to reduce the damages from the natural hazards such as flood, drought, typhoons, and snowstorms caused by climate change. Through the vulnerability assessment to adapt the climate change, it is possible to analyze the priority, feasibility, effect of the reduction policy. For the vulnerability assessment, broad amount of weather data for each meterological station are required. Making the database management system for the meteorologic data could troubleshoot of the difficulties lie in handling and processing the weather data. In this study, we generated the meteorologic data retrieval system (MetSystem) for climate change vulnerability assessment. The user interface of MetSystem was implemented in the web-browser so as to access to a database server at any time and place, and it provides different query executions according to the criteria of meteorologic stations, temporal range, meteorologic items, statistics, and range of values, as well as the function of exporting to Excel format (*.xls). The developed system is expected that it will make it easier to try different analyses of vulnerability to natural hazards by the simple access to meteorologic database and the extensive search functions.

The objective of this study was to make a map of farmland vulnerability to flood inundation based on morphologic characteristics from the flood-damaged areas. Vulnerability mapping based on the records of flood damages has been conducted in four successive steps; data preparation and preprocessing, identification of morphologic criteria, calculation of inundation vulnerability index using a fuzzy membership function, and evaluation of inundation vulnerability. At the first step, three primary digital data at 30-m resolution were produced as follows: digital elevation model, hill slopes map, and distance from water body map. Secondly zonal statistics were conducted from such three raster data to identify geomorphic features in common. Thirdly inundation vulnerability index was defined as the value of 0 to 1 by applying a fuzzy linear membership function to the accumulation of raster data reclassified as 1 for cells satisfying each geomorphic condition. Lastly inundation vulnerability was suggested to be divided into five stages by 0.25 interval i.e. extremely vulnerable, highly vulnerable, normally vulnerable, less vulnerable, and resilient. For a case study of the Jinju, farmlands of 138.6km2, about 18% of the whole area of Jinju, were classified as vulnerable to inundation, and about 6.6km2 of farmlands with elevation of below 19 m at sea water level, slope of below 3.5 degrees, and within 115 m distance from water body were exposed to extremely vulnerable to inundation. Comparatively Geumsan-myeon and Sabong-myeon were revealed as the most vulnerable to farmland inundation in the Jinju.

Climate change has increased the number of floods and inundation on farmland. Recently various mobile applications through inundation mapping, flood forecasts and evacuation routes have been developed for the prevention and reduction of flood damages. However, most of current prevention systems for farmland flooding are still web-based systems relying on the field survey which needs a lot of human and time resources although mobile devices has been rapidly improved and widely used. The purpose of this study is to design a mobile application for preventing and reducing farmland flood and inundation damages and collecting damage information in real time. We put advanced mobile device functions such as GPS, network communications, cameras into our system design. This system implement 2way communication and intuitive application that will increase information efficiency and decrease flood damage. Our design has been tested through previous flooding data of Jinju city in 2010.

The aim of this paper is to investigate the applicability of high spatial resolution remote sensing images for conducting the rural amenity resources survey. There are a large number of rural amenity resources and field reconnaissance without a sufficient preliminary survey involves a big amount of cost and time even if the data quality cannot always be satisfied with the advanced study. Therefore, a new approach should be considered like the state-of-the-art remote sensing technology to support field survey of rural amenity resources as well as to identify the spatial attributes including the geographical location, pathway, area, and shape. Generally high-resolution satellite or aerial photo images are too expensive to cover a large area and not free of meteorological conditions, but recently rapidly-advanced internet-based image services, such as Google Earth, Microsoft Bing maps, Bluebirds, Daum maps, and so on, are expected to overcome the handicaps. The review of the different services shows that Google Earth would be the most feasible alternative for the survey of rural amenity resources in that it provides powerful tools to build spatial features and the attributes and the data format is completely compatible with other GIS(Geographic information system) software. Hence, this study tried to apply the Google Earth service to interpret the amenity resources and proposed the reformed work process conjugating the internet-based high-resolution images like satellite and aerial photo data.

Many urban people are attracted to the recreational opportunities and attractions of rural areas, such as beautiful scenery, lakes, mountains, forests, and resorts. Furthermore, rural development planning increasingly emphasizes the integration of resource extractive industries with non-market-based recreational and amenity values. This article outlines a method to estimate an amenity level of rural areas such as natural amenities index and shows the relation of the natural amenity and population growth. The results revealed that natural amenity classifying each region can be explained with geographical characteristics, temperature-humidity, and sunshine duration time. In analysis with population, natural amenity does not exactly explain that but can be one of the important factor of population change.

수문 인자, 특히 강우량의 공간 분포 해석은 수자원 분야에서 중요한 관심사 중 하나이다. 기존의 티센법(Thiessen), 역거리법, 등우선법이 공간적 연속성과 지형 특성을 고려하지 못하는 한계를 가지고 있는데, 본 연구에서는 일강우량에 대한 강우 공간분포 해석의 정확도 향상을 위해 월평균 자료와 평년 강우량 자료를 산출하여, 이들과 수집한 일강우량 자료간의 상관성 분석하였으며 이를 근거로 지구통계학적 분석방법인 코크리깅(Co-kriging) 기법의 이

The objectives of this study were to develop an evaluation method of regional vulnerability to agricultural drought and to classify the vulnerability patterns. In order to test the method, 24 city or county areas of Gyeonggi-do were chose. First, statistic data and digital maps referred for agricultural drought were defined, and the input data of 31 items were set up from 5 categories: land use factor, water resource factor, climate factor, topographic and soil factor, and agricultural production foundation factor. Second, for simplification of the factors, principal component analysis was carried out, and eventually 4 principal components which explain about 80.8% of total variance were extracted. Each of the principal components was explained into the vulnerability components of scale factor, geographical factor, weather factor and agricultural production foundation factor. Next, DVIP (Drought Vulnerability Index for Paddy), was calculated using factor scores from principal components. Last, by means of statistical cluster analysis on the DVIP, the study area was classified as 5 patterns from A to E. The cluster A corresponds to the area where the agricultural industry is insignificant and the agricultural foundation is little equipped, and the cluster B includes typical agricultural areas where the cultivation areas are large but irrigation facilities are still insufficient. As for the cluster C, the corresponding areas are vulnerable to the climate change, and the D cluster applies to the area with extensive forests and high elevation farmlands. The last cluster I indicates the areas where the farmlands are small but most of them are irrigated as much.

The objectives of this study are to develop an agricultural drought evaluation model based on administrative boundaries and to assist the effective drought-related decision-making of local governments. The model which was named ADEM(Administrative Drought Evaluation Model for Paddies) is designed to simulate daily water balance between available water quantities from various agricultural water facilities such as reservoirs, wells, pump stations, etc. and water requirements in paddies. And in order to numerically describe the agricultural drought severity, two indices were defined; One is ADFP(Agricultural Drought Frequency for Paddies) which is calculated with a frequency analysis of monthly water deficit, and the other is ADIP(Agricultural Drought Index for Paddies) with a scale of -4.2~+4.2. The developed model was applied to Yeoju district and showed good correspondence with the historical records of drought.