Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment

Nakabuye, Hope Njuki; Rudnick, Daran R.; DeJonge, Kendall C.; Lo, Tsz Him; Heeren, Derek M.; Qiao, Xin; Franz, Trenton E.; Katimbo, Abia; Duan, Jiaming

doi:10.1016/j.agwat.2022.107957

Cited by 10 publications

(4 citation statements)

References 36 publications

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“…Estimates of daily values for both K cb and K s can be valuable in water balance modeling, but having estimates of K s alone can be good indicators of water stress. When available to use in combination with good estimates of K cb , canopy temperature is an ideal plant-based measurement of water stress to determine K s under full or near-full fc (Kullberg et al, 2017;DeJonge and Zhang, 2021) and trigger irrigation (Wanjura et al, 1992;Nakabuye et al, 2022), and has opportunities for integration into decision support systems for irrigation systems such as center pivots (Andrade et al, 2020;Zhang et al, 2021). Estimation of K s has long been done using canopy temperature, but in the past these techniques were limited to full canopy since viewing of sunlit soil in the background can bias canopy temperature measurements.…”

Section: Discussionmentioning

confidence: 99%

Diurnal Trends of Maize Canopy Cover Under Water Stress

DeJonge,

Zhang,

Cummins

et al. 2024

Journal of Natural Resources and Agricultural Ecosystems

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Highlights RGB trail cams above maize crop collected images every 15 minutes, day and night, to monitor leaf curl. Fractional canopy cover (fc,%) was constant for full irrigation but reduced during the day for limited irrigation. Techniques were developed to estimate reductions in water use (i.e., evapotranspiration) using images of fc. Measurements of fc prior to wilting represent transpiration demand (Kcb ), and reductions of fc represent stress (Ks ). Abstract. By differentiating green and non-green pixels of RGB images of crop canopy, the fractional canopy cover (fc,%) can be estimated and subsequently used to estimate crop transpiration demand (e.g., Kcb, basal crop coefficient, following FAO-56 methodology). While unstressed maize crops maintain consistent fc through the day, leaves of heat or water stressed crops will curl, thereby reducing the instantaneous fc and the associated transpiration. This paper reports the effects of diurnal leaf curl and subsequent fc reduction on full and limited water treatments of irrigated maize through nadir images obtained every 15 minutes. Results suggest that fc images obtained in the early morning (fcNS) are typically representative of a non-stressed condition and can be used to estimate Kcb. Reduction of fc throughout the day (i.e., fc/fcNS) was compared to water stress coefficient Ks obtained from neutron probe and TDR measurement and showed that fc/fcNS from hours 11 a.m. to 2 p.m. had a high correlation (R2 = 0.773), indicating that mid-day fractional canopy cover reduction could be used as a proxy for Ks. This method creates new opportunities for estimating crop water stress during vegetative growth but also highlights potentially unknown challenges regarding lower resolution remote sensing during the same growth stages. Keywords: Basal crop coefficient, Canopy cover, Crop coefficient, Evapotranspiration, Stomatal conductance, Stress crop coefficient, Transpiration, Water stress.

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Section: Discussionmentioning

confidence: 99%

Diurnal Trends of Maize Canopy Cover Under Water Stress

DeJonge,

Zhang,

Cummins

et al. 2024

Journal of Natural Resources and Agricultural Ecosystems

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“…Nitrogen (N) fertilizer in the form of urea-ammonium-nitrate (UAN 32%) was scheduled using active crop canopy sensors. 24 Irrigation was scheduled to meet crop water demand using a locally calibrated soil water balance model 25 (Table S1).…”

Section: ■ Materials and Methodsmentioning

confidence: 99%

Natural Reactive Iron Dynamics in the Agricultural Soil of Semiarid to Arid Systems

Malakar,

Snow,

Rudnick

et al. 2024

ACS Agric. Sci. Technol.

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Quantifying redox-driven changes in iron chemistry in irrigated semiarid to arid soils and their relevance for the availability of nutrients and contaminants is critical for global food security. Data across three growing seasons and two different soil types in semiarid to arid climates indicate site-independent peaks of reactive iron in soil aligned with peaks in irrigation events. The reactive iron formed during irrigation was short-lived, and the concentration was back at baseline during harvest. The significant (p < 0.01) increase of reactive iron ranging from 1589.0 ± 172.3 to 1898.0 ± 201.1 μg g −1 over the growing season triggered by reducing conditions due to transient water infiltration resulted in the mobilization of organic soil carbon and affected the mobility and plant availability of nitrogen, uranium, and arsenic. Porewater samples collected during irrigation events demonstrated increasing iron concentrations over time and positively correlated (p < 0.05) with arsenic and uranium levels. Geogenic arsenic mobilization into soil porewater during peak irrigation events contained significantly (p < 0.01) higher (∼90%) reduced inorganic arsenic species. Crop tissue analysis indicated that roots contained the highest concentrations of trace elements, followed by shoots and grains. Coupled (bio)geochemical redox cycles of iron, nutrients, and contaminants seem to play a critical but so far less recognized role for crop production in irrigated agroecosystems of semiarid to arid systems.

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“…Because of the ignorance of the drainage and leakage, the calculation was not quite in line with the actual situation. Thus, the model was improved by considering the paddy field leakage and the thickness difference in the water layer between the beginning and the end of the growth stage: (7) where P i is the rainfall depth during the rice growth period (mm); W gi is the irrigation water during the time interval (mm); L i is the seepage during the time period, 2 mm/d (Hu et al, 2019); ET i is the field water requirement during each growth stage by using the α-value method (mm) [34]; and λ i are the sensitivity coefficients in various growth stages [35].…”

Section: Jensen Model For Yield Loss Calculationmentioning

confidence: 99%

“…λ i n i=1 (7) where P i is the rainfall depth during the rice growth period (mm); W gi is the irrigation water during the time interval (mm); L i is the seepage during the time period, 2 mm/d (Hu et al, 2019); ET i is the field water requirement during each growth stage by using the α-value method (mm) [34]; and λ i are the sensitivity coefficients in various growth stages [35].…”

Section: Analysis Of Drought Characteristicsmentioning

confidence: 99%

A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss

Liu

Pan

et al. 2023

Sustainability

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China is one of the regions with the most frequent drought disasters and serious social and economic losses. Agricultural drought loss is one the most serious natural disasters. Due to climate change, the regional agricultural drought risk assessment has always been the focus of the academic circle. This study takes Zunyi City as an example, which is the most typical City of karst landform development. The monthly precipitation data set of ground meteorological observation stations in Zunyi City from 1956 to 2020 was selected, and the drought characteristic variables were extracted by the coupled use of the precipitation anomaly percentage (Pa) index and the theory of runs. The Copula function was applied to establish the joint distribution model of characteristic variables, obtaining the drought frequency and drought return periods. Combined with the Jensen model, the agricultural drought loss rate under different drought return periods in the target year (2020) was calculated and evaluated. The results showed that the Gumbel-Hougaard copula function was suitable for the joint distribution of drought joint variables in Zunyi City. From 1956 to 2020, fewer droughts occurred in Zhengan and Wuchuan, and the most droughts took place in Fenggang, Meitan, and Yuqing. The average drought duration in each county was about 1.5 months, and the average drought severity was about 0.35 in spatial distribution. Crop loss rate caused by drought increased and the affected area expanded with the increase of drought return periods (5, 10, 20, 50, and 100 years) in temporal distribution. Meanwhile, the drought disaster was most drastic in the eastern region, followed by the south, north, west, and central area. The results were highly consistent with the historical drought in Zunyi City, which verified the validity of the model. This study could provide scientific knowledge for drought resistance and reasonable mitigation programing for the security of the regional agricultural production and the sustainability of social and economic development.

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Real-time irrigation scheduling of maize using Degrees Above Non-Stressed (DANS) index in semi-arid environment

Cited by 10 publications

References 36 publications

Diurnal Trends of Maize Canopy Cover Under Water Stress

Diurnal Trends of Maize Canopy Cover Under Water Stress

Natural Reactive Iron Dynamics in the Agricultural Soil of Semiarid to Arid Systems

A New Agricultural Drought Disaster Risk Assessment Framework: Coupled a Copula Function to Select Return Periods and the Jensen Model to Calculate Yield Loss

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