Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea

Hong, Eunmi; Nam, Won‐Ho; Choi, Jin‐Yong; Pachepsky, Yakov

doi:10.1016/j.agwat.2015.12.003

Cited by 38 publications

(11 citation statements)

References 62 publications

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“…It has to be noted that when we collected 20 random samples over four consecutive years for simulations, we did not distinguish between days of rainfall, antecedent rainfall, rainfall recessions, or baseflow. The irrigation water requirement can be different for these hydrological situations and also differ between crop species, rooting depth and crop growth stage and water availability (Hong et al, 2016). The methodology of this study can be applied for specific crops and hydrological situations when the crop module in SWAT is developed and tuned to this crop and can be applied for irrigation strategy of a specific agricultural water management.…”

Section: Discussionmentioning

confidence: 99%

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream

Hong

Shelton

Pachepsky

et al. 2017

Journal of Environmental Management

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Knowledge of the microbial quality of irrigation waters is extremely limited. For this reason, the US FDA has promulgated the Produce Rule, mandating the testing of irrigation water sources for many farms. The rule requires the collection and analysis of at least 20 water samples over two to four years to adequately evaluate the quality of water intended for produce irrigation. The objective of this work was to evaluate the effect of interannual weather variability on surface water microbial quality. We used the Soil and Water Assessment Tool model to simulate E. coli concentrations in the Little Cove Creek; this is a perennial creek located in an agricultural watershed in south-eastern Pennsylvania. The model performance was evaluated using the US FDA regulatory microbial water quality metrics of geometric mean (GM) and the statistical threshold value (STV). Using the 90-year time series of weather observations, we simulated and randomly sampled the time series of E. coli concentrations. We found that weather conditions of a specific year may strongly affect the evaluation of microbial quality and that the long-term assessment of microbial water quality may be quite different from the evaluation based on short-term observations. The variations in microbial concentrations and water quality metrics were affected by location, wetness of the hydrological years, and seasonality, with 15.7-70.1% of samples exceeding the regulatory threshold. The results of this work demonstrate the value of using modeling to design and evaluate monitoring protocols to assess the microbial quality of water used for produce irrigation.

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Section: Discussionmentioning

confidence: 99%

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream

Hong

Shelton

Pachepsky

et al. 2017

Journal of Environmental Management

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“…토양 유효수분율 산정 공식은 Eqs. (2)~(4)와 같다 (Hong et al, 2016). (Hunt et al, 2009;Nam et al, 2012;Nam et al, 2015)…”

Section: 실측기반 토양유효수분율 산정unclassified

Drought Risk Assessment for Upland Crops using Satellite-derived Evapotranspiration and Soil Available Water Capacity

Jeon¹,

Nam²,

Lee³

et al. 2021

J. Korean Soc. Hazard Mitig

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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.

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“…For example, the CGMR model predicts a reduction in IRR during most of the cropping seasons of all crops except winter wheat ( Figure 5) in the 2090s under the A1B (moderate) emission scenario. In this study, we estimated irrigation water requirement based on projected climate data (i.e., changes in temperature and precipitation) similar to other studies [23][24][25]. However, we did not consider the direct effects of increased CO 2 concentrations on the joint physiological and structural effect on plant growth and related water savings during the growing period of crops.…”

Section: Crop Irrigation Requirement Uncertainties Between General CImentioning

confidence: 99%

Assessing Potential Climate Change Impacts on Irrigation Requirements of Major Crops in the Brazos Headwaters Basin, Texas

Awal

Fares

Bayabil

2018

Water

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In order for the agricultural sector to be sustainable, farming practices and management strategies need to be informed by site-specific information regarding potential climate change impacts on irrigation requirements and water budget components of different crops. Such information would allow managers and producers to select cropping systems that ensure efficient use of water resources and crop productivity. The major challenge in understanding the link between cropping systems and climate change is the uncertainty of how the climate would change in the future and lack of understanding how different crops would respond to those changes. This study analyzed the potential impact of climate change on irrigation requirements of four major crops (cotton, corn, sorghum, and winter wheat) in the Brazos Headwaters Basin, Texas. The irrigation requirement of crops was calculated for the baseline period and three projected periods: 2020s (2011-2030), 2055s (2046-2065), and 2090s (2080-2099). Daily climate predictions from 15 general circulation models (GCMs) under three greenhouse gas (GHG) emission scenarios (B1, A1B, and A2) were generated for three future periods using the Long Ashton Research Station-Weather Generator (LARS-WG) statistical downscaling model. Grid-based (55 grids at~38 km resolution) irrigation water requirements (IRRs) and other water budget components of each crop were calculated using the Irrigation Management System (IManSys) model. Future period projection results show that evapotranspiration (ET) and IRR will increase for all crops, while precipitation is projected to decrease compared with the baseline period. On average, precipitation meets only 25-32% of the ET demand, depending on crop type. In general, projections from almost all GCMs show an increase in IRR for all crops for the three future periods under the three GHG emission scenarios. Irrigation requirement prediction uncertainty between GCMs was consistently greater in July and August for corn, cotton, and sorghum regardless of period and emission scenario. However, for winter wheat, greater uncertainties between GCMs were observed during April and May. Irrigation requirements show significant variations across spatial locations. There was no consistent spatial trend in changes of IRR for the four crops. A unit change in precipitation is projected to affect IRR differently depending on the crop type.

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Projected irrigation requirements for upland crops using soil moisture model under climate change in South Korea

Cited by 38 publications

References 62 publications

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream

Modeling the interannual variability of microbial quality metrics of irrigation water in a Pennsylvania stream

Drought Risk Assessment for Upland Crops using Satellite-derived Evapotranspiration and Soil Available Water Capacity

Assessing Potential Climate Change Impacts on Irrigation Requirements of Major Crops in the Brazos Headwaters Basin, Texas

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