Abstract
Making precise irrigation decisions several days in advance is of great significance for improving water resource utilization efficiency in arid regions. While crop models such as AquaCrop aid in predicting soil moisture and water requirements, uncertainties arising from soil heterogeneity, management practices, and crop traits can compromise the accuracy of irrigation decisions. Therefore, this study develops a real-time irrigation decision-making (RTID) system and a risk analysis framework based on AquaCrop to evaluate the impacts of uncertainty on a virtual maize field in the Hanyan Irrigation District, an arid region of Northwest China. Results show that uncertainties in weather forecasts, including reference crop evapotranspiration (ET o ) and precipitation, minimally affect net irrigation requirement (NIR) in drought areas. In contrast, sowing date, soil parameters, and crop coefficient (K c ) introduce significant variability. When maximized, these factors cause NIR fluctuations of −15 % to + 13 %, −5 % to + 12 %, and −10 % to + 10 %, respectively. Under the combined influence of these uncertainty factors, the fluctuations in NIR exhibit a saturation effect, meaning that as uncertainty factors continue to accumulate, the magnitude of NIR fluctuations no longer increases obviously. Statistical analysis indicates that when all factors act together, 90 % of NIR predictions remain within ±15 %, while yield losses exceed 1.5 % in ≤ 25 % of cases and 4 % in ≤ 5 % of cases, respectively. Moderately increasing the per-application NIR slightly reduces the risk of yield loss, but the benefits diminish beyond a 10 % increment. These findings provide scientific and practical insights for optimizing precision irrigation in arid regions, highlighting key sources of uncertainty and their impacts on water use efficiency and yield stability. • Developed an AquaCrop-based real-time irrigation decision (RTID) system for farmland. • Sowing date drove major net irrigation requirement (NIR) fluctuations in arid area. • Combined uncertainties showed saturation effect, stabilizing NIR predictions within ±15 % deviation. • Yield loss risk was low, exceeding 1.5 % in ≤ 25 % of cases and 4 % in ≤ 5 % of cases. • Increasing per-application NIR by 10 % reduced yield loss risk effectively, but benefits diminished beyond this increment.
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Claims 9
Claim · model-written summary
Weather forecast uncertainty minimally affected net irrigation requirement in drought areas.
Zea maysNot reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“uncertainties in weather forecasts, including reference crop evapotranspiration (ET o ) and precipitation, minimally affect net irrigation requirement (NIR) in drought areas”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
sowing date uncertainty caused net irrigation requirement fluctuations of −15 % to + 13 %.
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sowing date, soil parameters, and crop coefficient (K c ) introduce significant variability. When maximized, these factors cause NIR fluctuations of −15 % to + 13 %, −5 % to + 12 %, and −10 % to + 10 %, respectively”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
soil parameters uncertainty caused net irrigation requirement fluctuations of −5 % to + 12 %.
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sowing date, soil parameters, and crop coefficient (K c ) introduce significant variability. When maximized, these factors cause NIR fluctuations of −15 % to + 13 %, −5 % to + 12 %, and −10 % to + 10 %, respectively”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
crop coefficient (K c ) uncertainty caused net irrigation requirement fluctuations of −10 % to + 10 %.
Not reportedDirection
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“sowing date, soil parameters, and crop coefficient (K c ) introduce significant variability. When maximized, these factors cause NIR fluctuations of −15 % to + 13 %, −5 % to + 12 %, and −10 % to + 10 %, respectively”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
Combined uncertainty showed saturation in net irrigation requirement fluctuations.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“fluctuations in NIR exhibit a saturation effect, meaning that as uncertainty factors continue to accumulate, the magnitude of NIR fluctuations no longer increases obviously”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
With all factors combined, 90 % of net irrigation requirement predictions remained within ±15 %.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“when all factors act together, 90 % of NIR predictions remain within ±15 %”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
Yield losses exceeded 1.5 % in no more than 25 % of cases.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“yield losses exceed 1.5 % in ≤ 25 % of cases”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
Yield losses exceeded 4 % in no more than 5 % of cases.
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“while yield losses exceed 1.5 % in ≤ 25 % of cases and 4 % in ≤ 5 % of cases”
e1“a virtual maize field in the Hanyan Irrigation District”
Claim · model-written summary
Moderately increasing per-application irrigation requirement slightly reduced yield-loss risk, with diminishing benefit beyond 10 %.
- Treatment
- Moderately increasing the per-application NIRe0
- Outcome
- risk of yield losse0
- Direction
- reducese0
- Qualifier
- beyond a 10 % incremente0
Not reportedComparator
Organisms pictured · Representative pictures of the matched species, not figures from the paper.
Verbatim
e0“Moderately increasing the per-application NIR slightly reduces the risk of yield loss, but the benefits diminish beyond a 10 % increment”
e1“a virtual maize field in the Hanyan Irrigation District”
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