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Agricultural water supply (AWS) estimation is one of the first and fundamental steps of developing agricultural management plans, and its accuracy must have substantial impacts on the following decision-making processes. In modeling the AWS for paddy fields, it is still common to determine parameter values, such as infiltration rates and irrigation efficiency, solely based on literature and rough assumptions due to data limitations; however, the impact of parameter uncertainty on the estimation has not been fully discussed. In this context, a relative sensitivity index and the generalized likelihood uncertainty estimation (GLUE) method were applied to quantify the parameter sensitivity and uncertainty in an AWS simulation. A general continuity equation was employed to mathematically represent the paddy water balance, and its six parameters were investigated. The results show that the AWS estimates are sensitive to the irrigation efficiency, drainage outlet height, minimum ponding depth, and infiltration, with the irrigation efficiency appearing to be the most important parameter; thus, they should be carefully selected. Multiple combinations of parameter values were observed to provide similarly good predictions, and such equifinality produced the substantial amount of uncertainty in AWS estimates regardless of the modeling approaches, indicating that the uncertainty should be counted when developing water management plans. We also found that agricultural system simulations using only literature-based parameter values provided poor accuracy, which can lead to flawed decisions in the water resources planning processes, and then the inefficient use of public investment and resources. The results indicate that modelers’ careful parameter selection is required to improve the accuracy of modeling results and estimates from using not only information from the past studies but also modeling practices enhanced with local knowledge and experience.

Abstract:Simulink, an extension of MATLAB, is a graphics-based model development environment for system modeling and simulation. Simulink's user-friendly features, including block (data process) and arrow (data transfer) objects, a large number of existing blocks, no need to write codes, and a drag and drop interface, provide modelers with an easy development environment. In this study, a Tank model was developed using Simulink and applied to a rainfall-runoff simulation for a study watershed to demonstrate the potential of Simulink as a tool for hydrological analysis. In the example given here, the Tank model was extended by two sub-modules representing evapotranspiration and storage-runoff distribution. In addition, model pre-and post-processing, such as input data preparation and results plotting, was carried out in MATLAB. Moreover, model parameters were calibrated using MATLAB optimization tools without any additional programming for linking the calibration algorithms and the model. The graphical representation utilized in the Simulink version of the Tank model helped us to understand the hydrological interactions described in the model, and the modular structure of the program facilitated the addition of new modules and the modification of existing modules as needed. From the study, we found that Simulink could be a useful and convenient environment for hydrological analysis and model development.

Regionalized lumped rainfall-runoff (RR) models have been widely employed as a means of predicting the streamflow of an ungauged watershed because of their simple yet effective simulation strategies. Parameter regionalization techniques relate the parameter values of a model calibrated to the observations of gauged watersheds to the geohydrological characteristics of the watersheds. Thus, the accuracy of regionalized models is dependent on the calibration processes, as well as the structure of the model used and the quality of the measurements. In this study, we have discussed the potentials and limitations of hydrological model parameter regionalization to provide practical guidance for hydrological modeling of ungauged watersheds. This study used a Tank model as an example model and calibrated its parameters to streamflow observed at the outlets of 39 gauged watersheds. Multiple regression analysis identified the statistical relationships between calibrated parameter values and nine watershed characteristics. The newly developed regional models provided acceptable accuracy in predicting streamflow, demonstrating the potential of the parameter regionalization method. However, uncertainty associated with parameter calibration processes was found to be large enough to affect the accuracy of regionalization. This study demonstrated the importance of objective function selection of the RR model regionalization.

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Estuarine reservoirs are available for use in various water resource systems. In agriculture, supplying irrigation water that meets water quality standards is essential for food safety. This study focused on the Ganwol estuarine reservoir in the midwestern region of South Korea, which suffers from water quality deterioration problems. To explore the water quality improvement in an estuarine reservoir, it is essential to understand the characteristics of water quality changes in the reservoir following water pollution control management. Therefore, the purpose of this study is to evaluate the effects of water quality management on the estuarine reservoir, which is separated by levees, using the soil and water assessment tool (SWAT)-environmental fluid dynamics code (EFDC) linkage model. In this study, soil remediation by dredging the reservoir’s bottom soil and effluent control from public sewage treatment works were considered as the water management plans. The results of this study indicate that reducing the internal load of the reservoir increases internal resilience and reducing the external inflow load decreases the impact on the system. Hence, comprehensive measures are effective in improving water quality.

Salinity is one of the most common and critical environmental factors that limit plant growth and reduce crop yield. The aquifers, the primary sources of irrigation water, of south Florida are shallow and highly permeable, which makes agriculture vulnerable to projected sea level rise and saltwater intrusion. This study evaluated the growth responses of two ornamental nursery crops to the different salinity levels of irrigation water to help develop saltwater intrusion mitigation plans for the improved sustainability of the horticultural industry in south Florida. Two nursery crops, Hibiscus rosa-sinensis and Mandevilla splendens, were treated with irrigation water that had seven different salinity levels from 0.5 (control) to 10.0 dS/m in the experiment. Crop height was measured weekly, and growth was monitored daily using the normalized difference vegetation index (NDVI) values derived from multispectral images collected using affordable sensors. The results show that the growth of H. rosa-sinensis and M.splendens was significantly inhibited when the salinity concentrations of irrigation water increased to 7.0 and 4.0 dS/m, for each crop, respectively. No significant differences were found between the NDVI values and plant growth variables of both H. rosa-sinensis and M.splendens treated with the different irrigation water salinity levels less than 2.0 dS/m. This study identified the salinity levels that could reduce the growth of the two nursery crops and demonstrated that the current level of irrigation water salinity (0.5 dS/m) would not have significant adverse effects on the growth of these crops in south Florida.

Heavy metals, including arsenic from abandoned mines, are easily transported with sediment and deposited in waterbodies such as reservoirs and lakes, creating critical water quality issues when they are released. Understanding the leaching of heavy metals is necessary for developing efficient water quality improvement plans. This study investigated how arsenic leaches from different soil and sediment types and responds to hydrologic conditions to identify areas susceptible to arsenic contamination. In this study, batch- and column-leaching tests and sequential extraction procedures were used to examine arsenic leaching processes in detail. The results showed that most arsenic-loaded sediments accumulated in the vicinity of a reservoir inlet, and arsenic in reservoir beds have a higher leaching potential than those from agricultural land and stream beds. Arsenic deposited at the bottom of reservoirs had higher mobility than that in the other soils and sediments, and arsenic leaching was closely associated with the acidity of water. In addition, arsenic leaching was found to be responsive to seasons (wet or dry) as its mobilization is controlled by organic compounds that vary over time. The results suggested that temporal variations in the hydrochemical composition of reservoir water should be considered when defining a management plan for reservoir water quality.