The objectives of this study were to monitor and analyse water quality and soil property in paddy fields where untreated wastewater is irrigated. Three paddy fields where streamflow mixed with untreated wastewater has been irrigated (untreated wastewater district, UWD) were selected for monitoring, and five paddy fields in Yongin area (Yongin district, YID) where water from Idong agricultural reservoir (well-managed) has been irrigated were selected for comparative evaluation. Electronic conductivity (EC), suspended solids (SS), total nitrogen (T-N), total phosphorous (T-P), NO3-N, Ca 2+ , Mg 2+ , Na + , total coliform (TC), fecal coliform (FC), and E. coli of the irrigation water in the UWD were significantly higher than those in the YID. Relatively high concentrations of EC, T-N, T-P, TC, FC, E. coli, copper (Cu), lead (Pb), zinc (Zn), and aluminium (Al) were shown in the irrigation water of the UWD especially during May to June. In general, the paddy soil in the UWD contained more Pb, Zn, and Cu than in the YID although the soil heavy metal contents in the UWD still meet the Korean soil contamination warning standards. No temporal trends in the heavy metal concentrations were found in paddy soils of the UWD. This study showed that the use of untreated wastewater to paddy fields has the possibility of negative impacts on water quality and soil, although long-term monitoring is needed to fully evaluate its effects.

The objective of this study was to evaluate simulation of agricultural water supply considering yearly variation of irrigation efficiency. The water supply data of the Idong reservoir from 2001 through 2009 was collected and used for this study. Total 6 parameters including irrigation efficiency (), drainage outlet height, and infiltration, were used for sensitivity analysis, calibration, and validation. Among the parameters, the  appeared to be the most sensitivity parameter. The  was calibrated on a yearly basis considering sensitivity and time-varying characteristic, while other parameters were set to fixed values. The statistics of percent bias (), Nash-Sutcliffe efficiency (), and root means square error to the standard deviation of measured data () for a monthly step were 2.7%, 0.93, and 0.26 for the calibration, and 3.9%, 0.89, and 0.32 for the validation, correspondently. The results showed a good agreement with the observations. This implies that the modeling only with appropriate parameter values, apart from modeling approaches, can simulate the real supply operation reasonably well. However, the simulations with uncalibrated parameters from previous studies produced poor results. Thus, it is important to use calibrated values, and especially, we suggest the 's yearly calibration for simulating agricultural water supply.

The TANK model has been widely used in rainfall-runoff modeling due to its simplicity of concept and computation while achieving forecast accuracy. A major barrier to the model application is to determine parameter values for ungauged watersheds, leading to the need of a method for the parameter estimation. The objective of this study was to develop regression equations for estimating the 3th TANK model parameters considering their variations for the ungauged watersheds. Thirty watersheds of dam sites and stream stations were selected for this study. A genetic algorithm was used to optimize TANK model parameters. Watershed characteristics used in this study include land use percent, watershed area, watershed length, and watershed average slope. Generalized equations were derived by correlating to the optimized parameters and the watershed characteristics. The results showed that the TANK model, with the parameters determined by the developed regression equations, performed reasonably with 0.60 to 0.85 of Nash-Sutcliffe efficiency for daily runoff. The developed regression equations for the TANK model can be applied for the runoff simulation particularly for the ungauged watersheds, which is common for upstream of agricultural reservoirs in Korea.

The objective of this study was to investigate characteristics of irrigation return flow from paddy block in a reservoir irrigated district during growing seasons. The irrigation return flow was divided into three parts, quick return flow from irrigation canal (RFI), quick return flow from drainage canal (RFD), and delayed return flow (DRF). The RFI was calculated from water level and stage-discharge relationships at the ends of the irrigation canals. The DRF was estimated using measured infiltration amount from paddy fields of the irrigated district. A combined monitoring and modeling method was used to estimate the RFD by subtracting surface runoff from surface drainage. The paddy block irrigated from the Idong reservoir was selected to study the irrigation return flow components. The results showed that daily agricultural water supply (AWS), the RFI, and the RFD were 27.4 mm day , respectively in May, which were greater than other months (p<0.05). The return flow ratio of the RFI and the RFD were the greatest in July (34.6%) and May (72.3%), respectively. The daily AWS was closely correlated with the RFD (correlation coefficients of 0.76~0.86) in except for July with, while correlation coefficient with the RFI were 0.56 and 0.42 in June and July, respectively (p<0.01). The total irrigation return flow was 1,965 mm in 2011, and 1,588 mm in 2012, resulting in total return flow ratio of 84.6% and 79.1%, respectively. This results indicate that substantial amounts of agricultural water were returned to streams as irrigation return flow. Thus, irrigation return flow should be fully considered into the agricultural water resources planning in Korea.

Along with global warming, ever intensifying weather events have increased damages to agricultural farms and facilities. The objective of this study was to investigate the spatial distribution and regional characteristics of agricultural damages by extreme weather events. Agricultural disaster statistics provided by the National Emergency Management Agency were summed over for a 13-year period from 1998 to 2010 and used for the spatial analysis. Two indices of damage area ration and property damage per unit area were introduced to quantify regional agricultural damages. As the results, farm inundation accounted for the largest area primarily damaged by typhoons with heavy rainfalls. Most property damages to farm lands originated from farm erosion in the alpine regions by localized guerrilla rains. The two major causes of damages to greenhouse and livestock facilities were typhoon with strong wind and winter blizzards. Gangwon was the province of the largest property loss mostly from farm land erosion losses, followed by Gyeongnam, Jeonnam, and Chungnam where losses to greenhouse and livestock facilities were relatively greater. Property loss per unit area was also the greatest for the Gangwon province (4.91 M￦/ha), followed by Gyongnam and Chungnam of 2.20 and 1.50 M￦/ha, respectively. Unit loss for greenhouse and livestock facilities was 13.3 M￦/ha, approximately 13 times greater than that for farm land (1.06 M￦/ha). The study findings indicated the importance of reducing highland farm erosion and reinforcing farming facilities structures for agricultural disaster management.