Simulation Study of Yield and Soil Water Balance Responses of a Maize Crop to Farmers? Irrigation Scheduling Practices in Tanzania

Igbadun, HE; Salim, BA

doi:10.4172/2168-9768.1000119

Cited by 4 publications

(9 citation statements)

References 19 publications

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“…Across the three characteristic seasons, seasonal ET for the different schedules ranged from 305 to 415 mm for T1, 295 to 393 mm for T2, 275 to 361 mm for T3 and 275 to 341 mm for T4. These simulated values fall within the range of seasonal consumptive water use reported in other simulation studies for maize [12,14] and some deficit studies observed through field experimentation [26]. However, the lower values appear to be outside (below) the range of other field studies [27,28].…”

Section: Soil Water Dynamics and Irrigationsupporting

confidence: 81%

“…High deep percolation loss (up to 1133 mm) at short irrigation intervals and high water application have been reported in other simulation studies evaluating interval scheduling [12,14]. Besides the obvious negative impact on the efficiency of agricultural water use, Igbadun and Salim [14] highlight that some of the consequences of high percolation losses include rapid build-up of the water table, the increase in soil salinity and water logging, which leads to poor yield due to low soil temperatures and poor aeration of plant roots. Figure 4 shows the simulated seasonal evapotranspiration (ET) for the different water application depths for the depletion irrigation scheduling.…”

Section: Soil Water Dynamics and Irrigationmentioning

confidence: 61%

“…Additionally, it can be observed ( Figure 1c,d) that the lower the application depth (for the same depletion level), the greater the frequency of water application. These observations have important implications, as crop productivity depends not only on the timing and severity of water deficits, but is also influenced by the duration of the drying cycle between water application [7,14,25].…”

Section: Soil Water Dynamics and Irrigationmentioning

confidence: 99%

“…The ANOVA test indicated highly significant differences (p < 0.01) in seasonal water applied among the five schedules, which can be attributed to the frequencies of irrigation. In general, a typical range of crop water requirement for maize crop is about 500-800 mm [14]. The simulated irrigation water supplied under the interval irrigation management is depicted in Figure 2d.…”

Section: Soil Water Dynamics and Irrigationmentioning

confidence: 99%

“…The effect of irrigation regimes on crop yield and WUE varies with crops and is acknowledged to be location and climate specific [14], highlighting the need to investigate the suitability of different scenarios in localized environments rather than extrapolating results from other regions. The objective of this study was to identify potential strategies for improving WUE in maize production in southern Taiwan through the use of simulation modelling.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Identifying Irrigation Strategies for Improved Agricultural Water Productivity in Irrigated Maize Production through Crop Simulation Modelling

Greaves

Wang

2017

Sustainability

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Abstract:Identifying irrigation strategies that improve agricultural water use efficiency (WUE) have a pivotal role to play in sustainable water development. In this study, the AquaCrop model was used to examine the impact of different irrigation scheduling options on yields to identify viable strategies to enhance WUE for irrigated maize. Two scheduling scenarios at water application depths ranging from 20 to 50 mm were investigated: schedules based on allowable depletion of total available water (TAW) in the root zone and interval schedules based on irrigating at predefined daily intervals. For both scenarios, simulated yields, seasonal water applied and percent percolation loss were within the range of 9.16 to 10.22 ton/ha, 180 to 950 mm and 0-61%, respectively. The WUE in terms of water applied (WUE Irr ) and crop evapotranspiration (WUE ET ) ranged from 1.07 to 5.48 kg/m 3 and 2.42 to 4.42 kg/m 3 , respectively. The results revealed that depletion levels of 40-50% TAW at water depths of 20-40 mm could be used to obtain high WUE without significant yield penalty. Moreover, a good balance between yield, improved WUE ET and percolation reduction was observed at water depths of 30-40 mm for daily intervals with water applied during the vegetative-reproductive stage of 7-5, 10-5 and 10-7. The identified strategies can contribute to the development of best management practices for water conservation.

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Section: Soil Water Dynamics and Irrigationsupporting

confidence: 81%

Section: Soil Water Dynamics and Irrigationmentioning

confidence: 61%

Section: Soil Water Dynamics and Irrigationmentioning

confidence: 99%

Section: Soil Water Dynamics and Irrigationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Identifying Irrigation Strategies for Improved Agricultural Water Productivity in Irrigated Maize Production through Crop Simulation Modelling

Greaves

Wang

2017

Sustainability

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Modeling deficit irrigation water demand of maize and potato in Eastern Germany using ERA5-Land reanalysis climate time series

Ogunsola,

Bankole,

Soboyejo

et al. 2024

Irrig Sci

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ERA5-Land reanalysis (ELR) climate time series has proven useful in (hydro)meteorological studies, however, its adoption for local studies is limited due to accuracies constraints. Meanwhile, local agricultural use of ELR could help data-scarce countries by addressing gaps in (hydro)meteorological variables. This study aimed to evaluate the first applicability of the ELR climate time series for modeling maize and potato irrigation water demand (IWD) at field scale and examined the performance of ELR precipitation with bias correction (DBC) and without bias correction (WBC). Yield, actual evapotranspiration (ETa), irrigation, water balance, and crop water productivity (CWP) were evaluated using the deficit irrigation toolbox. The study found that maize (13.98-14.49 ton/ha) and potato (6.84-8.20 tons/ha) had similar mean seasonal yield under different irrigation management strategies (IMS). The Global Evolutionary Technique for OPTimal Irrigation Scheduling (GET-OPTIS_WS) IMS had the highest mean seasonal yields under DBC and WBC, while rainfall and constant IMS had the most crop failures. DBC had a higher mean seasonal ETa than WBC, except for the potato FIT and rainfall IMS. Global Evolutionary Technique for OPTimal Irrigation Scheduling: one common schedule per crop season (GET-OPTIS_OS) and GET-OPTIS_WS IMS outperformed conventional IMS in IWD by 44%. Overall, GET-OPTIS_OS and GET-OPTIS_WS performed best for maize and potato CWP in terms of IWD, scheduling, and timing. Therefore, adoption of ELR climate time series and advanced irrigation optimization strategies such as GET-OPTIS_OS and GET-OPTIS_WS can be beneficial for effective and efficient management of limited water resources, where agricultural water allocation/resource is limited.

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Modeling Deficit Irrigation Water Demand of Maize and Potato in Eastern Germany using ERA5-Land Reanalysis Climate Time Series

Ogunsola,

Bankole,

Soboyejo

et al. 2024

Preprint

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ERA5-Land reanalysis (ELR) climate time series has proven useful in (hydro)meteorological studies, however, its adoption for local studies is limited due to accuracies constraints. Meanwhile, local agricultural use of ELR could help data-scarce countries by addressing gaps in (hydro)meteorological variables. This study aimed to evaluate the first applicability of the ELR climate time series for modeling maize and potato irrigation water demand (IWD) at field scale and examined the performance of ELR precipitation with bias correction (DBC) and without bias correction (WBC). Yield, actual evapotranspiration (ETa), irrigation, water balance, and crop water productivity (CWP) were evaluated using the deficit irrigation toolbox. The study found that maize (13.98–14.49 ton/ha) and potato (6.84–8.20 tons/ha) had similar mean seasonal yield under different irrigation management strategies (IMS). The Global Evolutionary Technique for OPTimal Irrigation Scheduling (GET-OPTIS_WS) IMS had the highest mean seasonal yields under DBC and WBC, while rainfall and constant IMS had the most crop failures. DBC had a higher mean seasonal ETa than WBC, except for the potato FIT and rainfall IMS. Global Evolutionary Technique for OPTimal Irrigation Scheduling: one common schedule per crop season (GET-OPTIS_OS) and GET-OPTIS_WS IMS outperformed conventional IMS in IWD by 44%. Overall, GET-OPTIS_OS and GET-OPTIS_WS performed best for maize and potato CWP in terms of IWD, scheduling, and timing. Therefore, adoption of ELR climate time series and advanced irrigation optimization strategies such as GET-OPTIS_OS and GET-OPTIS_WS can be beneficial for effective and efficient management of limited water resources, where agricultural water allocation/resource is limited.

show abstract

Simulation Study of Yield and Soil Water Balance Responses of a Maize Crop to Farmers? Irrigation Scheduling Practices in Tanzania

Cited by 4 publications

References 19 publications

Identifying Irrigation Strategies for Improved Agricultural Water Productivity in Irrigated Maize Production through Crop Simulation Modelling

Identifying Irrigation Strategies for Improved Agricultural Water Productivity in Irrigated Maize Production through Crop Simulation Modelling

Modeling deficit irrigation water demand of maize and potato in Eastern Germany using ERA5-Land reanalysis climate time series

Modeling Deficit Irrigation Water Demand of Maize and Potato in Eastern Germany using ERA5-Land Reanalysis Climate Time Series

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