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Recently, with changing rainfall patterns worldwide due to climate change, the effects and damages of upland crops are increasing. A water supply system from irrigation facilities such as agricultural reservoirs and pumping stations has been established in paddy fields, whereas irrigation uplands equipped with water supply facilities account for only 18.5% of the upland area. Therefore, it is necessary to analyze vulnerable areas of upland droughts because they depend on natural rainfall and lack the ability to respond to drought damage. Currently, there is limited drought information to respond to an upland drought because the characteristics of crops and actual cultivation period are not analyzed. Soil moisture directly resulting from rainfall shortage is highly related to drought, especially for upland crops and vegetation. Therefore, upland crops drought can be evaluated using soil moisture and weather data. In this study, an upland drought vulnerability index based on runs theory and entropy method was developed using effective soil moisture, soil moisture drought index, and groundwater level. Soil moisture and meteorological data were obtained from the soil moisture observation network (Rural Development Administration), and weather observation network (Korea Meteorological Administration). The results showed that Upland Drought Vulnerability Index (UDVI) can be an effective tool for quantitatively evaluating upland drought vulnerability.

Due to the recent spring drought, it has been difficult to supply agricultural water owing to an insufficient water supply before irrigation, thereby illuminating the importance of efficient water management for allocating optimal agricultural water amounts. Thus, improved management plans for irrigation facilities are required as well as an optimal water management plan for agricultural water supplies and equitable distribution. In this study, we applied modulated controls to the EPA-SWMM and analyzed the agricultural water supply and demand. The EPA-SWMM simulates the hydrological water supply and can be applied to a water supply network. Modulated controls can simulate continuous, intermittent, and rotational irrigation methods by setting the supply time series, and adjusting the water supply and drainage based on ponding depth conditions in the paddy field. We applied the EPA-SWMM with modulated controls to Gosam reservoir in Anseong to analyze the agricultural water supply and irrigation efficiency. The water supply via canals and irrigated areas was analyzed to identify areas of water shortages or oversupply. According to the results of a quantitative water supply analysis, we determined that it is necessary to control the water supply using gate opening rate controls. The results obtained herein can contribute to efficient water management by evaluating the efficiency of irrigation organizations during a drought when insufficient agricultural water is available via preliminary analysis of agricultural water supply methods.

A flash drought is a drought that occurs rapidly within a short period of time, owing to changes in weather and environmental factors that occur rapidly due to extreme weather caused by climate change. Drought damage occurs within a relatively short period of time, and extreme vegetation stress can damage crops due to reduced water supply. Thus, different monitoring methods are required for different drought types. In this study, ESI (Evaporative Stress Index) and EDDI (Evaporative Demand Drought Index) were calculated to evaluate the short-term drought and determine the mechanism that causes flash droughts. The ESI and EDDI both indicates faster responses to the 2017 spring drought event than the SPI (Standardized Precipitation Index), confirming their sensitive drought assessment abilities. A flash drought detection standard was established based on the drought category used in USDM (United States Drought Monitor), and seven flash drought events were detected in South Korea over 5 years (2014-2018). A correlation analysis indicates that, among the hydrometeorological factors, the correlation coefficients between soil moisture/maximum temperature and flash drought occurrence exhibited strong positive (negative) correlations (0.9 and -0.9, respectively). The carbon change pattern obtained using GPP (Gross Primary Productivity) differed, exhibiting a -60% average GPP reduction rate compared to three other regions (JB, CN, and CB) where flash droughts occurred in 2018. We focus our discussion on opportunities to extend flash drought detection and mechanism determination using two drought indices that must be addressed to improve flash drought monitoring in South Korea.

Due to global climate change and weather fluctuations, weather phenomena such as global warming and increasing carbon dioxide concentration are intensifying. Climate change increases the frequency of natural disasters and has been affecting the occurrence of drought. In recent years, severe drought has been occurring all over the world. California in the United States experienced a mega drought from 2006 to 2016, Australia experienced a millennium drought from 2001 to 2009, and the Central and Northern African continent suffered a mega drought from 2005 to 2018. With regard to extreme drought events, depletion of water resources has continued for a long time, causing enormous damage that is difficult to restore socially and economically. Drought response strategy for South Korea has focused on drought recovery and emergency measures for drought damage. To respond to severe drought events, it is necessary to evaluate regional drought response capacity and drought preparedness. In this study, long-term water resource comprehensive plan, water management yearbook, and water statistics were used to evaluate drought response capabilities according to region, including resilience analysis such as local economy, drought preparation system, and drought training. The water resource shortage of each local government was calculated based on water demand and supply data, and drought response capability of the local government was analyzed by combining it with resilience analysis for drought. The results of this study can be used for long-term drought preparedness and establishment of countermeasures in the future through the evaluation of drought response capacity according to region.

Recently, various factors such as climate change, watershed environment change, and, socio-economic change, have been shown to have a major impact on the hydrological water cycle and on available water resources in agricultural watersheds. Therefore, it is necessary to identify the water cycle elements of watersheds accurately and to quantify them objectively. Agricultural watersheds can be divided into the basin, irrigation facilities such as reservoir and pumping stations, irrigation areas, and water cycle elements such as rainfall and evapotranspiration water supply and demand. A systematic management system of agricultural water cycle should be established through element analysis, module development, and modeling techniques for comprehensive interpretation of agricultural watersheds. This study involved the monitoring and modeling of inlet, outlet, and reservoir to analyze and quantify water cycle elements in the Madun reservoir (located in Anseong, Gyeonggi-do) and Heungeop reservoir (located in Wonju, Gangwon-do). The watershed runoff, water supply and drainage of irrigation canal, and return flow were estimated using the Storm Water Management Model (SWMM) based on analysis of canal networks and hydraulic calculations. These results can be utilized to ensure stable supply of agricultural water resources and to inform water management policies.

Climate change has altered the frequency, intensity, and timing of mean and extreme precipitation events. Extreme precipitation has caused tremendous socio-economic losses and displays strong regional variability. Although many previous studies have addressed daily extreme precipitation, hourly extreme rainfall still needs to be thoroughly investigated. In this study, we investigated the trends, spatio-temporal variability, and long-term variations in mean and extreme precipitation over South Korea using daily and hourly observational data. During the past 50 years (1973–2022), there has been a notable escalation in maximum hourly precipitation, although the boreal summer mean precipitation has increased only marginally. Regionally, an increase in mean and extreme rainfall occurred in the northern part of the central region. Moreover, increased intensity and frequency of extreme precipitation have contributed more to the total summer precipitation in recent years. Our findings provide scientific insights into the progression of extreme summer precipitation events in South Korea.

The global expansion of cyanobacterial blooms poses a major risk to the safety of freshwater resources. As a result, many explorations have been performed at a regional scale to determine the underlying impact mechanism of cyanobacterial blooms for one or several waterbodies. However, two questions still need to be answered quantitatively at a global scale to assist the water management. One is to specify which factors were often selected as the driving forces of cyanobacterial blooms, and the other is to estimate their quantitative relationships. For that, this paper applied a systematic literature review for 41 peer-reviewed studies published before May 2021 and a statistical meta-analysis based on the Pearson's or Spearman's correlation coefficients from 27 studies. These results showed that the water quality, hydraulic conditions, meteorological conditions and nutrient levels were often considered the driving forces of cyanobacterial blooms in global freshwater systems. Among these, meteorological conditions and nutrient level had the highest probability of being chosen as the driving force. In addition, knowledge of the quantitative relationships between these driving forces and cyanobacterial blooms was newly synthesized based on the correlation coefficients. The results indicated that, at a global scale, meteorological conditions were negatively related to cyanobacterial blooms, and other driving forces, such as water quality, hydraulic conditions and nutrient levels, were positively related to cyanobacterial blooms. In addition, the measurement indicators of these driving forces had diverse forms. For example, the nutrient level can be measured by the concentration of different forms of nitrogen or phosphorus, which may lead to different results in correlation analysis. Thus, a subgroup meta-analysis was necessary for the subdivided driving forces and cyanobacterial blooms, which had a better accuracy. Overall, the synthesized knowledge can help guide advanced cyanobacteria-centered water management, especially when the necessary cyanobacterial data of targeting waterbodies are inaccessible.

Agricultural drought can have long-lasting and harmful impacts on both the agricultural ecosystem and economy. Recently, as climate change has increased global warming, the frequency and intensity of droughts are increasing as weather and environmental factors that directly affect agriculture are rapidly changing. In South Korea, severe droughts have occurred every year for the past seven years. Compared to paddies supplied with water from agricultural reservoirs, upland crops are highly vulnerable to drought due to a lack of irrigation facilities. The consumption requirements for upland crops cannot be satisfied by rainfall alone and require supplementation through irrigation. The amount of upland crop consumption and irrigation water should be calculated not only by the amount of evaporation but also by taking into account the soil moisture movement. Soil moisture is a key variable for defining the agricultural drought index; however, in situ soil moisture observations are unavailable for many areas. Remote sensing techniques can allow surface soil moisture observations at different tempo-spatial resolutions. Soil available water content is an important factor used in evaluating upland drought impacts. It is recognized as a major factor in water resource circulation. This study proposes a practical method to perform drought risk assessments for upland crops based on evaporation and soil moisture by utilizing Famine Early Warning Systems Network evaporation acidity satellite images provided by the United States Geological Survey.

Weather and hydrological phenomena have been changing due to climate change as evidenced by localized torrential rainfall and precipitation falling by more than 30% compared to the annual average. From 2013 to 2017 the ninety-nine reservoirs reached a water storage rate of 0%, making a secure stable water supply for agriculture uncertain. There is an increased need for information regarding agricultural water management to respond to the changes in the agricultural environment and climate. Therefore, automatic water level measurement facilities have been introduced to determine the real-time reservoir storage capacity and agricultural water supply. According to the Ministry of Agriculture, Food and Rural Affairs' guidelines for the installation and operation of water level measurement instruments, automatic water level facilities are currently installed at 1,734 reservoirs and 1,880 irrigation canals, with water level data generated at 10-minute intervals. The official recognition of hydrological water level data for agricultural reservoirs increased from six in 2016 to forty-nine in 2019. Anomaly detection algorithm methods for data regarding the agricultural reservoir level as well as quality control measures based on agricultural reservoir characteristics are required to minimize data quality degradation and generate reliable hydrological data over time. Though it was practically impossible to analyze the correlation between the water level or run-off and influential factors such as weather and terrain, recently a non-linear hydrological analysis has been possible using models such as Artificial Neural Networks (ANNs). This study aims to present an anomaly detection algorithm for reservoir level data using deep learning based LSTM (Long Short-Term Memory) models, in combination with other neural networks for managing quantitative information of agricultural water supply.

Surface soil moisture (SSM) has considerable impact in land-atmosphere exchanges of water and energy. However, due to the inherent deficiencies of remotely sensed data (e.g., cloud contamination), neither of current algorithms alone can provide daily and seamless SSM at field scale (i.e., 30 m). To explore this research gap, we proposed a novel SSM fusion framework of Generating high Resolution, Accurate, Seamless data using Point-Surface fusion (GRASPS) based on multiple remotely sensed, reanalysis, and in-situ datasets. First, 30 m seamless continuous SSM correlated variables (land surface temperature, NDVI, Albedo) were generated by enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). Then, downscaled auxiliary variables and other background variables were input into a deep learning model to produce 30 m daily and seamless SSM. To further improve the downscaling accuracy, a pixel classification based bias correction method was developed. This proposed GRASPS method was validated over a densely distributed in-situ soil moisture sensor network (HOAL) in Austria. The average Pearson correlation coefficient (PCC), root mean squared error (RMSE), unbiased RMSE (ubRMSE), Bias, and mean absolute error (MAE) over all validation sites for the downscaled SSM achieved 0.78, 0.048 m^3 m^(-3), 0.033 m^3 m^(-3), -0.001 m^3 m^(-3), and 0.041 m^3 m^(-3), respectively. After bias correction, the RMSE, ubRMSE, Bias, and MAE at validation sites further decreased by 13%, 7%, 22%, and 18%, respectively. The proposed method maximizes the potential of data fusion and deep learning in generating field scale seamless SSM, which is promising for fine-scale studies and applications in agricultural, hydrological, and environmental domains. Currently, the manuscript is under review. More information and results will be released soon.

Droughts are a frequent natural phenomenon that has amplified globally in the 21st century and are projected to become more common and extreme in the future. Consequently, this affects the progress of drought indices and frameworks to categorize drought conditions. Several drought-related indices and variables are required to capture different features of complex drought conditions. Therefore, we explained the signs of progress of ecological drought that were ecologically expressive to promote the integration between the research on and identification of water scarcity situations and analyzed different frameworks to synthesize the drought effects on species and ecosystems. Notably, we present an inclusive review of an integrated framework for an ecological drought. The ecological drought framework affords the advantage of improved methodologies for assessing ecological drought. This is supported by research on water-limited ecosystems that incorporated several drought-related elements and indicators to produce an integrated drought framework. In this framework, we combined multiple studies on drought recovery, early warning signs, and the effects of land management interferences, along with a schematic representation of a new extension of the framework into ecological systems, to contribute to the success and long-term sustainability of ecological drought adaptation, as well as on-the-ground examples of climate-informed ecological drought management in action for an integrated framework for ecological drought. This study provides an integrated approach to the understanding of ecological drought in line with accelerated scientific advancement to promote persistence and plan for a future that irretrievably exceeds the ecosystem thresholds and new multivariate drought indices.

Technological and socioeconomic interventions accompanied by climate warming strongly dictate farming practices, lending a direct impact over future irrigation water demand and supply. In this article, two pivotal factors of farming practices and climate change were included to assess their role in the future paddy water management of Korea. Field surveys were conducted across irrigated areas of twelve agricultural reservoirs to distinguish traditional and current paddy farming practices. Projected climate for two future time slices the 2060s (2020 to 2059) and the 2100s (2060 to 2100) under two representative concentration pathway scenarios (4.5 and 8.5) were used for climate change impact assessment. Crop evapotranspiration (ETc), effective rainfall, gross duty of water (GDW) and annual inflow were simulated from 1987 to 2100 under both farming practices. Future climate projections suggested a continuous warming trend accompanied by distinctively negative/positive shifts in central/southern region annual rainfall by the end of the twenty-first century. Annual inflow in the central (southern) region reservoirs exhibited downward (upward) trends during the 2060s and only upward trends during the 2100s, respectively, whereas rice ETc showed upward tendencies regardless of the farming practices. Rice season effective rainfall varied for different reservoirs mostly showing increasing tendencies. The GDW increased implying that projected positive rainfall shifts might not withhold the driving impacts of temperature rise over regional irrigation water demands. Following the traditional farming practices in future would intensify the anticipated rise in irrigation demand and may lead to water shortages given the present storage capacities of agricultural reservoirs.

Damage due to climate change is increasing worldwide; in South Korea, the increase in temperature is greater than the average global temperature increase. These changes in temperature have increased the frequency of and damage caused by droughts. To reduce drought damage, the importance of efficient water management policies and evapotranspiration, an index used for water management policies, is increasing. Analyzing the variation in evapotranspiration is relevant to understanding climate change and agricultural water management. Owing to the lack of evapotranspiration data collected using a Lysimeter, evapotranspiration has been estimated using the FAO-56 Penman–Monteith (PM) equation on meteorological datasets as recommended by the United Nations Food and Agriculture Organization. Long-term meteorological data with a maximum of 100 years were collected from 12 sites to estimate evapotranspiration. The objectives of this study were the following: (1) estimate evapotranspiration based on the PM equation, (2) analyze the trends in temperature and evapotranspiration, and (3) evaluate the relationship between temperature and evapotranspiration through correlational analysis. The results improve our understanding of climate change and provide a valuable reference for regional water resource management. We estimated evapotranspiration and analyzed the tendency of temperature and evapotranspiration. As a result, analysis of seasonal ET0 at all stations represented generally increasing trends in spring, summer, and autumn with generally decreasing trends in winter. Results of the seasonal Mann–Kendall test between temperature metrics (maximum, average, minimum) and ET0 showed that the maximum temperature exhibited a distinct increase in spring and winter in some areas. In this study, we determined the strength of the relationship between temperature and ET0 using the Pearson correlation coefficient. The results of evaluating the relationship between each temperature metric and evapotranspiration showed that the maximum temperature had the strongest relationship compared to the average and minimum temperatures.

For agricultural water management to be successfully achieved, flow analysis of irrigation canal network flows is essential to determine the proper distribution of crop water requirements and to contribute to an optimized irrigation operation and water allocation. This study developed a hydraulic analysis model for irrigation canal flow by using the Storm Water Management Model (SWMM) module by adding the network modelling and paddy water balance model. This model was applied to a rice paddy field rehabilitation project area in the Daesan District located in the western part of South Korea. Results obtained from the calibrated simulation model were compared with the actual measurement data from water-level gauges at the irrigation canals. The irrigation hydraulic analysis model for canal network flow indicates the significance of using irrigation management tools in improving the analysis for accurate irrigation scheduling based on its simulation results, such as flow travel time, water level and flow amount. Copyright © 2016 John Wiley & Sons, Ltd.

Egypt is a country that is vulnerable to many of the sustainability challenges and climate change effects to which all countries around the world are struggling to respond, and the United Nations is warning that Egypt could run out of the water by the year 2025. Reference evapotranspiration is the first step in estimating crop water requirements and irrigation water management. A better understanding of trends in reference evapotranspiration is crucial for scientific management of water resources in arid and semi-arid regions. The aim of this study is to identify the spatiotemporal of annual and monthly reference evapotranspiration changes in Egypt, as evidenced by spatial distribution and temporal trends. The results showed that significant changes in spatial distribution of reference evapotranspiration have occurred in the last 35 years beginning in the 1980s. The southeastern regions, the older agricultural lands in the Nile Delta and valley, as well as the northwestern regions were most affected regions. However, the western desert showed the lowest impact from climate change. The winter season from November to February showed the lowest impact from climate change, while during the summer season, the highest significant differences occurred, especially from June to October. The last five years (2013–2017) showed a significant decrease from the previous 5 years (2008–2012) but still show a significant increase from previous periods of time (1983–2007). Hence, the western desert is more suitable for agricultural expansion. Furthermore, agricultural and irrigation activities during the summer season have to change respond to the impact of climate change on water resources management.

An increase in abnormal climate change patterns and unsustainable irrigation in uplands cause drought and affect agricultural water security, crop productivity, and price fluctuations. In this study, we developed a soil moisture model to project irrigation requirements (IR) for upland crops under climate change using estimated effective rainfall (ER), crop evapotranspiration (ET c ) and the IR of 29 major upland crops in South Korea. The temperature and precipitation will increase, but the ER is projected to decrease under climate change. ET c and the net irrigation requirement (NIR) are expected to increase under climate change. Vegetable crops have less ER and more NIR than cereal crops with a similar amount of ET c , which means they are more sensitive to water scarcity and IR than cereal crops. In addition, we found that barley has the smallest daily ET c and IR but the highest increase rate in NIR under climate change, especially in the central part of South Korea. The NIR of Chinese cabbage-fall is the lowest in the northern region and increases moving southwards. The NIR of spinach is projected to increase gradually from the southern and eastern coastlines to the northern inland area. Onions have the largest ET c and NIR of the 29 upland crops, but they show small changes compared to other crops under climate change. Water scarcity is a major limiting factor for sustainable agricultural production. The variation of IR and ET c values for each crop under different climate change scenarios depends on the crop, soil, space, and meteorological characteristics. The results of this study can be used as a guideline for irrigation and soil water management for upland crops under climate change.

Agricultural water is delivered by open irrigation canals in system of reservoirs with a widespread distribution in South Korea. Traditional irrigation management problems include water distribution systems with less capacity than the peak demand, irregular delivery rates, and low irrigation efficiency and uniformity. It is necessary to strategically compare the estimated irrigation demands with the actual water supplies for decision making in order to maintain the water supply according to the demand. Accurate measurement and monitoring of water distribution systems is essential in order to solve the problems of water efficiency and availability. Auto water level gauges installed at the head and tail sections of each irrigation canal in the Dongjin River were used to measure the discharge during irrigation periods. In this study, we introduced an approach to assess the water delivery performance indicators of the open irrigation canals, which is essential for identifying the key issues for water management improvement. The irrigation efficiencies according to the water delivery performance indicators were measured with an automatic water gauge in the irrigation canals and were calculated from the spatial and temporal distribution of the water supply for the lack of planning in water delivery. The calculated performance indicators are useful to understand the irrigator behavior and general irrigation trends. Analysis of the results yielded insights into possible improvement methods in order to develop water management policies that enable irrigation planners to improve the temporal uniformity and equity in the water distribution.

Drought has had large impacts on economies, societies and the environment, and could become even more disruptive given the context of climate change characterized by increasing temperature and more variable and extreme precipitation. Changes in the frequency, duration, and severity of droughts will have enormous impacts on the hydrological cycle, water management and agricultural production. Therefore, one major concern arising from climate change is its potential effects on water resources. Although South Korea has been experiencing serious drought and water scarcity issues in recent years, preparedness for potential changes in the frequency, severity and duration of drought disasters due to climate change effects has received only limited attention. It is important to detect changes in temporal trends of drought at the regional scale. This information will aid understanding the impacts of climate change and its subsequent effects on hydrology and agriculture. In this paper, we have addressed the question of how climate change might influence the impact of drought hazard by estimating the potential changes in temporal trends of drought in South Korea. We have assessed the temporal trends of future drought with drought indices (Standardized Precipitation Index [SPI], Standardized Precipitation Evapotranspiration Index [SPEI], and Self-Calibrating Palmer Drought Severity Index [SC-PDSI]) using past observed data (1981–2010) from 54 meteorological stations maintained by the Korea Meteorological Administration (KMA) and projected climate change scenarios (2011–2100) as depicted by the Representative Concentration Pathways models (RCPs). The drought hazard assessment was quantitatively evaluated by analyzing drought frequency, duration, severity and magnitude using the run theory method based on different timescales of the drought indices. The results demonstrated a significant increase of potential drought impacts in the future. Additionally, significant increases in the drought magnitude and severity were found at different time scales for each drought indicator. The results indicated that the temporal pattern of potential drought progression and recession across South Korea can be used for the development of proactive drought risk management and mitigation strategies.

Detecting changes in the spatio-temporal patterns of temperature and precipitation is a prerequisite for developing effective adaptation options and strategies for the future. An effective method for assessing climate change and for providing information to decision makers and stakeholders is needed to implement appropriate adaptation strategies. The objective of this study was to determine whether climate change has caused spatio-temporal changes in meteorological elements in North Korea. We delineated the spatio-temporal patterns of temperature and precipitation caused by climate change in specific time periods based on statistically significant differences using a statistically robust method. Historical weather data from 27 meteorological stations over a 30-year period (1981–2010) were used. The results demonstrated that statistically significant changes occurred over the 30 years. The temporal trends in the maximum and minimum temperatures were highly significantly different in the western agricultural regions and central/southwest urban regions during 1996–2010 compared with 1981–1995. The precipitation amounts were significantly different in the southeast regions (around the coast). The numbers of precipitation events were significantly different for portions of the northern and northeast areas near the mountains. Additionally, statistically significant differences in the spatial structures of the temperature and precipitation were found at different time scales. The significant differences were not uniform in each season/month. Therefore, significant differences occurred in the meteorological elements, and particular locations and urbanized areas were affected by global warming. However, the temporal trends and spatial structures of each meteorological element were not equally modified; the meteorological changes occurred locally as a result of the changing climate.

Climate change influences various environmental aspects, including those specifically related to agricultural water resources such as runoff, evapotranspiration, droughts and floods. Understanding the impact of climate change on reservoirs in relation to the passage of time is an important component of water resource management and the maintenance of a stable water supply. In different regions, changes in rainfall and hydrologic patterns due to climate change can increase the occurrences of reservoir water shortages and affect the future availability of agricultural water resources differently. It is a main concern for sustainable development in agricultural water resources management to evaluate the adaptive capability of a water supply under future climate conditions. Studies on climate change impacts and vulnerability assessments have been an essential process for preparing adaptive measures. This paper proposes a practical method to assess water supply vulnerability and sustainability in terms of climate change for the adaptive capability of agricultural reservoirs in South Korea based on a concept of probability theory and reliability analysis using time-dependent change analysis of water supply and demand. The objectives of this study were to investigate if there is evidence of climate change occurrences with respect to potential water supply capacity and irrigation water requirements; and to apply an irrigation vulnerability assessment model to assess the potential effects and predict the impacts of agricultural water demand and supply on reservoir operation to govern local water management decisions under climate variability and change. The irrigation vulnerability was estimated to evaluate the performance of water supplies in agricultural reservoirs; it is a recommended preparatory adaptive measure for developing a future water supply strategy in terms of using climate change scenarios reflecting different future conditions.

Understanding the changes in reference evapotranspiration under climate change is an important component to improve crop management because it is projected to cause potential effects of crop production. Therefore, detecting the changes in the spatial distribution and temporal trends of reference evapotranspiration at the regional and local scale aids in understanding the impacts of climate change and its subsequent effect on hydrology and agriculture. The objective of this study is to determine whether climate change has caused changes in the spatial distribution and temporal trends of reference evapotranspiration in South Korea, and to quantify any abrupt changes and periods of the spatial distribution and temporal trends to compare the statistical significant differences at annual and monthly timescales. The reference evapotranspiration values were determined based on the United Nations Food and Agriculture Organization (FAO) Penman-Monteith equation, using historical weather data for 54 meteorological stations over a 40-year period (1973-2012). Our results showed that statistically significant annual reference evapotranspiration change has occurred in midwest regions with agricultural areas during 1973-1977. Almost agricultural areas in midwest and southwest regions occurred in statistically significant changes of the monthly reference evapotranspiration during February, March and November during the previous two decades (1973-1982 and 1983-1992). These results appear that climate change that have aided significant reference evapotranspiration change in South Korea since the 1970s. Knowledge of long-term spatial distribution and temporal trends of reference evapotranspiration related to climate change would be useful to water resources and agricultural planning.

Reservoirs are principal water resources that supply irrigation water to paddy fields and play an important role in water resources management in South Korea. For optimal irrigation reservoir operation and management, it is necessary to determine the duration of irrigation water shortages. Management of reservoir operation and irrigation scheduling should take into consideration essential variables that include the water supply in a reservoir and the water demand in the associated irrigation district. The agricultural water supply and demand show different patterns based on the variability and uncertainty of meteorological and hydrological phenomena. The duration of excessive water supply can be quantitatively determined through analysis of deviations and changes in the timing of agricultural water supply and demand. In this study, we introduce an approach to assess the vulnerable seasons of paddy irrigation to enable more effective operation and management of reservoirs. The vulnerable seasons were evaluated through comparison of the potential water supply capacity and irrigation water requirements based on water budget analysis via a time series change analysis. We have assessed the changing in the total duration and duration shifts of the vulnerable irrigation seasons for four agricultural reservoirs using past observed data (1981–2010) from meteorological stations maintained by the Korea Meteorological Administration (KMA) and projected climate change scenarios (2011–2100) as depicted by the Representative Concentration Pathways (RCPs) emission scenarios. For irrigation vulnerable seasons under both the RCP 4.5 and RCP 8.5 scenarios, the results showed periods of significant increases in which total vulnerable seasons compared to the historical period; the longest duration of vulnerability occurred during the 2071–2100 period under the RCP 8.5. Identification of the vulnerable seasons for paddy irrigation can be applied in agricultural water management to more effectively manage reservoir operation during irrigation periods with climate changes.

Plastic greenhouse cultivation is expanding in Korea due to increasing demand for value-added agricultural products. Potential pollutant accumulate in the root zone and may leach downward by irrigation water, causing soil and groundwater contamination. A nutrient management plan is needed to reduce the nutrient load from plastic greenhouse cultivation, although few studies have examined nutrient leaching and accumulation in the soil layers. In this study, soil, soil water, irrigation water, and weather conditions were monitored in the twice-a-year cultivation of cucumber and tomato in a plastic greenhouse for 2 years. Soil and soil water samples were analyzed every two weeks to investigate the level of nutrient accumulation and the nutrient leaching characteristics. Excessive fertilization caused nutrient accumulation in the root zone and the leaching of nutrients into the lower soil profile. The amount of phosphorus that accumulated on the soil particles of the root zone, however, did not significantly leach out with soil water movement. The electrical conductivity (EC) and NO3–N of the soil water gradually increased from the root zone to the lower zone and the NO3–N average concentration in the 150 cm soil layer was nearly equal to the maximum concentration of the fertigation water. The amount of percolation was 476.3 mm (56% of the irrigation water) in the cropping period for first cucumber cultivation (CP-C#1), 241.8 mm (53% of the irrigation water) in the cropping period for second cucumber cultivation (CP-C#2), 346.6 mm (42% of the irrigation water) in the cropping period for first tomato cultivation (CP-T#1), and 348.1 mm (51% of the irrigation water) which in the cropping period for second tomato cultivation (CP-T#2). The total NO3–N losses through leaching from the lower zone (60 to 150 cm soil layer) to deeper soil were 137.4 kg N ha−1 in the CP-C#1, 195.9 kg N ha−1 in the CP-C#2, 758.6 kg N ha−1 in the CP-T#1, and 54.7 N ha−1 in the CP-T#2. A significant amount of nutrients were not utilized for crop growth but instead leached in accordance with the movement of the soil water. The results of this study can serve as a baseline for the long-term monitoring of greenhouse nutrient loads and can be used in the design of new guidelines to reduce nutrient loads from plastic greenhouse cultivation.