Review Reports - Research on Water and Fertilizer Use Strategies for Silage Corn Under Different Irrigation Methods to Mitigate Abiotic Stress

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

.I have reviewed the manuscript (plants-4054951) "Research on water and fertilizer utilization strategies for silage maize under different irrigation methods to cope with combined water, fertilizer and heat stress".
When I searched the Web of Science (WoS) using the terms “silage maize”, “drip irrigation”, and “fertilizer” in the topic, I learned that some similar studies had been published previously. In the study, three irrigations, three fertilizations, and two mulches (as mulched and unmulched) with the use of maize cultivar DK808 were combined with three replications.
Demerits of the study are given below:
1. The “Introduction” section seems to be written for the regional readers.
2. Although experiments depended on irrigation and fertilization applications, irrigation amounts were selected according to local amounts. “The irrigation amount was divided into low water (50%), medium water (75%) and high water (100%) according to the local irrigation amount”. What are local amounts? Lesser than 50% or higher than 50%?
3. Similarly, fertilization applications depended on local rates. “The fertilization rate was divided into low fertilizer (bottom fertilizer 300kg˖hm-2 , top dressing 72kg˖hm-2 ), medium fertilizer (bottom fertilizer 375kg˖hm-2 , top dressing 90kg˖hm-2 ), high fertilizer (bottom fertilizer 450kg˖hm-2 , top dressing 108kg˖hm-2 ) according to the local fertilization rate”. What are local rates? What are NPK rates and micronutrients?
4. The common metric data should be used for unit measurements instead of mu, hm etc… This article will be read all over the world after being published. Regional consepts will confuse the minds of readers.
5. I read M&M two times, but I have not learned whether the experiment was carried out in a single year (2023) or two years (2023-2024).
6. The most important point is that an experiment should be conducted with a maximum of two topics (two combinations) for explaining interactions. Four topics (irrigation amounts, fertilization rates, mulches and years) cannot be explained to readers.

Author Response

Point1：The “Introduction” section seems to be written for the regional readers.

Response 1:

We sincerely appreciate the reviewer’s critical feedback. We recognize that the previous version relied too heavily on local context, which may have limited the manuscript’s appeal to a broader international audience. In the revised manuscript, we have thoroughly restructured the Introduction to establish a global and national scientific perspective. The key revisions are as follows:

As the world 's second most populous country with more than 1.4 billion people, China is facing a growing contradiction between limited water resources and growing food security needs. Although China 's total freshwater resources are among the highest in the world, its per capita share is only about 2,100 m3 - only a quarter of the world average - making it one of the world 's most water-stressed countries [1-2]. Agriculture consumes more than 60 % of China 's total water intake, and this pressure is particularly prominent in the Yellow River Basin ( YRB ). The rigid water quota in this area often has a significant conflict with the expansion of high-water-consuming crops [3-4]. At the same time, China 's animal husbandry is undergoing a rapid transformation to high-quality and large-scale production. Silage corn has become the cornerstone of this transformation because of its high biomass yield and high energy density [5].

As a key agro-pastoral ecotone, the Yellow River irrigation area in Inner Mongolia has contributed greatly to this supply chain [6-7]. However, the region generally faces a rigid gap in water resources, high bulk density in the topsoil of some plots, and large differences in water and fertilizer conservation capacity, which seriously restricts the release of agricultural production potential. The problem of excessive irrigation and unbalanced fertilization caused by traditional water and fertilizer management depends on experience, which further causes low water use efficiency and serious fertilizer loss. It is also easy to cause ecological problems such as soil nutrient imbalance and threaten the sustainable development of agriculture. More importantly, there is a significant multiple stress dilemma in the region - water restriction causes water stress, resulting in insufficient water supply for maize growth ; the temperature of well water is low, and direct irrigation causes the soil temperature to drop sharply to form temperature stress, which inhibits the absorption capacity of roots to water and fertilizer; the imbalance of fertilization brings about fertilizer stress, resulting in the imbalance of soil nutrient ratio and the decrease of fertilizer utilization rate. At present, the effect of water and fertilizer under the combined action of these three stresses is not clear, and the optimization strategy of water and fertilizer for different hydrological years is lack of in-depth study, which makes it difficult for farmers to implement scientific water and fertilizer management, and can not fully tap the production potential of silage corn [8-10]. Therefore, under the goal of water-saving agriculture and ' double carbon ', it is urgent to optimize the water and fertilizer system of silage maize by combining quantitative simulation with field experiment [11-13].

Crop growth model is an effective tool to quantify the interaction between water and fertilizer-crop-environment [14-16]. Compared with more complex models such as DSSAT [17-18] or WOFOST [19-20], AquaCrop has attracted much academic attention due to its ' water-driven ' core engine and the balance between model ease of use and simulation accuracy [21-22]. The model is widely used in the analysis of deficit irrigation scenarios in water shortage areas, the effect of nutrient stress on crop growth, and the optimization of farmland water and fertilizer [23-24]. However, there are still significant research gaps : the existing simulation studies rarely consider the interaction of ' water-fertilizer-heat ' compound stress of silage maize under different drip irrigation modes in sandy soil environment. In addition, the parameter calibration and verification data in this area are insufficient, and further calibration is needed in combination with field measured data.

In this study, a comprehensive quantitative study on the correlation of ' water-fertilizer-heat ' triple stress was carried out in the long-term simulation framework for silage maize in the Yellow River Basin. Different from previous studies that focused on single factor stress or general soil types [25-26], our work introduced temperature stress into the AquaCrop model to evaluate the growth dynamics of silage maize. The key is that this study constructs a decision matrix suitable for different hydrological years ( wet years, normal years, and dry years ) by using a 35-year meteorological data set, which transcends the limitations of short-term field trials. This provides a mechanistic understanding of how film-mediated heat preservation and irrigation depth interact to alleviate abiotic stress.

Based on the above research gaps, the objectives of this study include : The AquaCrop model of silage maize was calibrated and validated under different drip irrigation modes ( DIM and SBDI ) in the Yellow River irrigation area ; Quantitative analysis of the characteristics and evolution of water, fertilizer and temperature stress under different hydrological scenarios ; Determine the optimal water and fertilizer threshold that can minimize abiotic stress while maximizing yield and water use efficiency. This study can provide a scientific basis for the precise management of silage maize in arid and semi-arid areas.

Framing within a Global Context: We have repositioned the study within the global challenge of water-food security. By comparing China’s per capita water resources (2,100 m³) with the global average and highlighting its status as a major food producer, we underscore that the water scarcity in the Yellow River Basin is a representative case of a global crisis, making the findings relevant to other water-stressed regions worldwide.
Scientific Generalization of Regional Issues: We have re-defined the study area as a "pivotal agro-pastoral ecotone" rather than just a local irrigation district. The specific challenge of cold-well-water irrigation has been generalized into the "hydro-thermal-nutrient stress nexus"—a complex abiotic stress dilemma that is common in groundwater-irrigated arid lands globally.
Methodological Advancement: We have emphasized that our study "transcends the limitations of short-term field trials" by employing a 35-year long-term simulation framework. This methodology provides a transferable decision-making matrix for climate-adaptive management, which is a significant concern for the international scientific community.
Identifying Universal Knowledge Gaps: The revised gap analysis now focuses on the performance of crop models in "sandy soil environments" under multi-factorial stress. Given that sandy soils are globally prevalent in arid zones, this ensures that the research addresses a widespread scientific gap.

We believe these revisions have significantly enhanced the manuscript's international relevance.

Point2：

Although experiments depended on irrigation and fertilization applications, irrigation amounts were selected according to local amounts. “The irrigation amount was divided into low water (50%), medium water (75%) and high water (100%) according to the local irrigation amount”. What are local amounts? Lesser than 50% or higher than 50%?

Response 2:

Thank you very much for the reviewer's opinion. We deeply apologize for the unclear statement of irrigation benchmarks in the text. 'Local irrigation amount ' refers to the regional full irrigation quota ( 180 mm ) of silage maize in the Inner Mongolia irrigation area of the Yellow River, which is the standard irrigation depth required to achieve potential yield under local climatic conditions.

In this study, 180 mm was defined as 100 % baseline ( high water ). The other two levels, 135 mm and 90 mm, represent 75 % and 50 % of the local standard, respectively. Therefore, all experimental treatments represented deficit irrigation strategies ( equal to or below local standards ). This definition has been explicitly added to the ' Materials and Methods ' section. As follows :

The irrigation amount was determined according to the local irrigation quota (180mm) and set as a 100 % benchmark. Three irrigation levels were set: low water (50 % of the local amount, i.e., 90mm), medium water (75 %, 135mm) and high water (100 %, 180mm).

Point3：

Similarly, fertilization applications depended on local rates. “The fertilization rate was divided into low fertilizer (bottom fertilizer 300kg˖hm^-2, top dressing 72kg˖hm^-2), medium fertilizer (bottom fertilizer 375kg˖hm^-2, top dressing 90kg˖hm^-2), high fertilizer (bottom fertilizer 450kg˖hm^-2, top dressing 108kg˖hm^-2) according to the local fertilization rate”. What are local rates? What are NPK rates and micronutrients?

Response 3:

We thank the review experts for their professional insights. The so-called ' local fertilization rate ' (total amount of 1125 kg ha^-1) represents the traditional high input fertilization habits of local farmers in the study area. In this regard, we have explained the specific composition of nutrients in detail. The base fertilizer was N-P2O5-K2O ratio of 18-22-5 compound fertilizer, and the topdressing was urea with 46.8 % nitrogen content. Taking the control group (CK, local standar) as an example, the total amount of pure nitrogen applied was 310.5 kg ha^-1 N (135 kg ha^-1 from base fertilizer and 175.5 kg ha^-1 from topdressing). Regarding trace elements, no additional trace elements were applied in this study. Related has been added to the ' materials and methods ' section. As follows:

Similarly, the fertilization level was designed according to the gradient of local traditional fertilization (total 1125 kg ha^-1). The treatments included: low fertilizer (300 kg ha^-1 base fertilizer, 72 kg ha^-1 topdressing), medium fertilizer (375 kg ha^-1 base fertilizer, 90 kg ha^-1 topdressing) and high fertilizer (450 kg ha^-1 base fertilizer, 108 kg ha^-1 topdressing). The base fertilizer compound fertilizer contains 18 % N, 22 % P2O5 and 5 % K2O, and the topdressing urea contains 46.8 % N. The control group (CK) followed a complete local standard (irrigation 180mm, fertilization 1125 kg ha^-1).

Point4：

The common metric data should be used for unit measurements instead of mu, hm etc… This article will be read all over the world after being published. Regional consepts will confuse the minds of readers.

Response 4:

We apologize for the confusion caused by the use of regional and non-standard units. We fully agree with the reviewers that standard units of measurement are essential for the clarity and global transferability of scientific research.

In the revised manuscript, we have systematically updated all measurement units to conform to the International System of Units (SI). The specific modifications are as follows:

1.All regional units ' mu ' have been converted to ' ha '.

The non-standard abbreviation ' hm ' has been replaced by the international standard abbreviation ' ha '.

3.We carefully checked and standardized the entire manuscript, including text, tables and pictures, to ensure consistency and clarity of understanding for international readers.

Point5：

I read M&M two times, but I have not learned whether the experiment was carried out in a single year (2023) or two years (2023-2024).

Response 5:

We sincerely apologize for the unclear expression and the trouble. The field experiment was indeed carried out across two consecutive growing seasons: 2023 and 2024.

In order to clarify the experimental design and the use of data in the revision, we have made the following changes :

Field trial period: We have explicitly added a note at the beginning of the ' Materials and Methods ' section (Section 2.2), pointing out that field trials are conducted from May to September in 2023 and 2024, respectively.

Data utilization: The data collected in 2023 is used for the calibration of the AquaCrop model, while the independent data in 2024 is used for model validation.

Long-term simulation: In addition to these two years of field experiments, we also used a total of 35 years of meteorological data from 1990 to 2024 for scenario simulation, as detailed in Section 2.4.

We have modified the text to ensure that the timeline of the experiment is now very eye-catching and easy for readers to find.

Point6：

The most important point is that an experiment should be conducted with a maximum of two topics (two combinations) for explaining interactions. Four topics (irrigation amounts, fertilization rates, mulches and years) cannot be explained to readers.

Response 6:

We sincerely thank the reviewers for their professional insights into the complexity of research. We are aware that the previous description may have caused misunderstanding. We hope to clarify that this study is not a simple four-factor randomized experiment, but a systematic comparison of two irrigation modes (DIM and SBDI) for the ' water-fertilizer-heat stress bond ':

Clarify patterns and variables :

Canopy coverage (CC) is an output indicator for model validation, not an experimental factor.

DIM (mulched drip irrigation) and SBDI (shallow subsurface drip irrigation) are two main irrigation modes (systems) for comparison. They are not independent random variables, but two different management strategies for regulating crop heat and water environment.

2.Using accumulated temperature (GDD) to quantify temperature stress :

We use the effective accumulated temperature (GDD) as a mechanism index to express temperature stress. In this region, low-temperature groundwater irrigation can induce significant thermal shocks.

DIM represents a heat preservation mode, and film mulching accelerates the accumulation of accumulated temperature (GDD), thereby alleviating temperature stress.
SBDI represents a membrane-free sustainable model, and the lack of plastic film leads to ' accumulated temperature deficit ', which directly quantifies the impact of temperature stress on crop development.

3.Simplify complexity by layering:

To address the concerns about ' interpretability ', we used a hierarchical logic rather than a four-factor interaction analysis:

System layer: We first compare how DIM and SBDI create different thermal environments (the test results are expressed by accumulated temperature, the temperature stress formula substituted in the system).

Optimization layer : In each specific mode, we focused on the water × fertilizer interaction (only 2 factors) to determine the optimal coupling threshold.

Scenario layer: We tested these water and fertilizer optimization schemes for specific systems under three hydrological scenarios (wet, flat, and dry years) to ensure that the recommendations have climate adaptability.

Amend the description:

We reconstructed the manuscript to follow the logic of ' two systems → model calibration and verification → test result analysis → water and fertilizer optimization → scenario test ' to ensure that the interaction was intuitive and scientific.

Author Response File: Author Response.docx

Reviewer 2 Report

Comments and Suggestions for Authors

Comments on plants-4054951

Research on water and fertilizer utilization strategies for silage maize under different irrigation methods to cope with combined water, fertilizer, and heat stress

Most of this paper emphasizes the maize-crop management for improving irrigation and fertilizer in the specific area of the north based on the AquaCrop model. By the ways, for Plants, the primary data for plant reflection (i.e., growth and physiology) in 2023 and 2024 are recommended to be shown, and minor points are in the comment below.

In line 38, please be specific in terms of yield, i.e., aboveground biomass yield or crop production yield.
Provide a full name of each abbreviation that is found in all figures in their caption.
Add a specific year number and detail (wet, normal, or dry year) for the Figure 7 caption note, including Figures 11 and 12.
According to lines 243-244 and 2. 4.3 Typical hydrological year temperature data: please elaborate on a reason in lines 265-270. Why are 1993, 2000, and 2012 shown for the hydrological years?
In line 473, refer to Table 1 about soil particle size; however, Table 1 is not this one.
According to lines 463-465, please add mean data of key primarily of results such as aboveground biomass yield (every 15-day measurement) in the main text or in the supplementary section.
In Fig. 8, add detail of the membrana tectoria type and blue dots in the figure caption.

……………………………………………………….

Comments for author File: Comments.pdf

Author Response

Point1：In line 38, please be specific in terms of yield, i.e., aboveground biomass yield or crop production yield.

Response 1:

We sincerely thank the reviewer for this insightful suggestion regarding the precision of our terminology. We agree that the term "yield" should be clearly defined to avoid ambiguity.

In the context of silage maize, the entire aboveground portion of the plant is harvested for forage. Therefore, the "yield" reported in this study refers specifically to the Aboveground biomass yield. As follows :

To reconcile the intensifying trade-off between chronic water scarcity and escalating forage demand in the Yellow River Basin, this study optimized integrated irrigation and fertilization regimes for silage maize. Leveraging the AquaCrop model, validated by 2023–2024 field experiments and a 35-year (1990–2024) meteorological dataset, we systematically quantified the impacts of multi-factorial water-fertilizer-heat stress under drip irrigation with mulch (DIM) and shallow-buried drip irrigation (SBDI). Model performance was robust, yielding high simulation accuracy for soil moisture (RMSE < 3.3%), canopy cover (RMSE < 3.95%), and aboveground biomass (RMSE < 4.5 t·ha⁻¹), with EF > 0.7 and R2≥0.85. Results revealed distinct stress dynamics across hydrological scenarios: mild temperature stress predominated in wet years, whereas severe water and fertilizer stresses emerged as the primary constraints during dry years. To mitigate these stresses, a medium fertilizer rate (555 kg·ha⁻¹) was identified as the stable optimum, while dynamic irrigation requirements were determined as 90, 135, and 180 mm for wet, normal, and dry years, respectively. Comparative evaluation indicated that DIM achieved maximum productivity in wet years (Aboveground biomass yield 70.4 t·ha⁻¹), whereas SBDI exhibited superior "stable yield-water saving" performance in normal and dry years. The established "hydrological year-irrigation method-threshold" framework provides a robust decision-making tool for precision management, offering critical scientific support for the sustainable, high-quality development of livestock farming in arid regions.

Point2：

Provide a full name of each abbreviation that is found in all figures in their caption.

Response 2:

We sincerely thank the reviewer for this helpful suggestion. To ensure that each figure is self-explanatory and accessible to the readers, we have meticulously reviewed all figures in the manuscript and added the full names of all abbreviations to their respective captions.

For example, abbreviations such as DIM (Drip irrigation under mulch), SBDI (Shallow-buried drip irrigation), WUE (Water use efficiency), AGDB (Aboveground dry biomass), and CC (Canopy cover) are now explicitly defined at the end of each relevant figure caption.

Point3：

Add a specific year number and detail (wet, normal, or dry year) for the Figure 7 caption note, including Figures 11 and 12.

Response 3:

Thank you very much for the valuable comments made by the reviewers, we have carefully adopted and completed the changes. Because there are no Figure 7, Figure 11 and Figure 12 in this paper, it is speculated that this is a pen error, which should be Table 7, Table 11 and Table 12. We have supplemented the detailed information of specific year values and year hydrological types ( wet year / normal year / dry year ) for the title annotations of these three tables as required. Because the table has been adjusted, the current table 6 is the previous table 7. As shown below :

Table 6. Effects of water-fertilizer coupling on silage maize yield, water use efficiency and fertilizer partial productivity in different hydrological years.

Planting methods	Different hydrological years	Treatment	Yield（ton ha^-¹）	Water use efficiency（kg ha^-¹ mm^-1）	Fertilizer partial productivity（kg˖kg^-1）
Drip irrigation under film	Wet year （2012）	P1	66.7	128.00	150.23
		P2	70.4	135.10	126.85
		P3	68.9	132.22	103.45
	Normal year （1993）	P4	64.2	145.58	144.59
		P5	67.1	152.15	120.90
		P6	66.3	150.34	99.55
	Dry year （2000）	P7	46.8	127.94	105.41
		P8	48.9	133.68	88.11
		P9	47.6	130.13	71.47
Shallow buried drip irrigation	Wet year （2012）	Z1	65.7	126.08	147.97
		Z2	68.5	131.45	123.42
		Z3	67.4	129.34	101.2
	Normal year （1993）	Z4	60.9	138.10	137.16
		Z5	65.8	149.21	118.56
		Z6	63.7	144.44	95.65
	Dry year （2000）	Z7	45.1	123.29	101.58
		Z8	46.8	127.94	84.32
		Z9	45.7	124.93	68.62

Table 11. Subsurface drip irrigation fertigation system simulation scenario plan.

Hydrological years	Treatment	Irrigation quota /mm						Fertilization amount /（kg˖ha^-1）
Hydrological years	Treatment	Seedling	Jointing	Large bell mouth	heading and flowering	heading and flowering	pustulation	Bottom fertilizer	Jointing	Large bell mouth
Wet year (2012)	P1	10	16	16	16	16	16	300	72	72
	P2	10	16	16	16	16	16	375	90	90
	P3	10	16	16	16	16	16	450	108	108
Normal year (1993)	P4	15	24	24	24	24	24	300	72	72
	P5	15	24	24	24	24	24	375	90	90
	P6	15	24	24	24	24	24	450	108	108
Dry year (2000)	P7	20	32	32	32	32	32	300	72	72
	P8	20	32	32	32	32	32	375	90	90
	P9	20	32	32	32	32	32	450	108	108

Table 12. Shallow drip irrigation water and fertilizer simulation scenario scheme.

Hydrological years	Treatment	Irrigation quota /mm							Fertilization amount /（kg˖ha^-1）
Hydrological years	Treatment	Seedling	Jointing	Large bell mouth	heading and flowering	heading and flowering		pustulation	Bottom fertilizer	Jointing	Large bell mouth
Wet year (2012)	Z1	10	16	16	16		16	16	300	72	72
	Z2	10	16	16	16		16	16	375	90	90
	Z3	10	16	16	16		16	16	450	108	108
Normal year (1993)	Z4	15	24	24	24		24	24	300	72	72
	Z5	15	24	24	24		24	24	375	90	90
	Z6	15	24	24	24		24	24	450	108	108
Dry year (2000)	Z7	20	32	32	32		32	32	300	72	72
	Z8	20	32	32	32		32	32	375	90	90
	Z9	20	32	32	32		32	32	450	108	108

Point4：

According to lines 243-244 and 2. 4.3 Typical hydrological year temperature data: please elaborate on a reason in lines 265-270. Why are 1993, 2000, and 2012 shown for the hydrological years?

Response 4:

Heartfelt thanks to the reviewer for this profound and valuable opinion. Based on the temperature data of typical hydrological years in lines 243-244 and section 2.4.3 of the original text, we have added the specific reasons for selecting 1993,2000 and 2012 as typical hydrological years in 2.3.1. Specifically, 1993,2000 and 2012 are the representative dry / normal / wet years selected according to the classification criteria of typical hydrological years in the study area and the characteristics of annual precipitation. The relevant detailed content has been supplemented to the corresponding text position as required. The contents are as follows :

The changes in rainfall during the whole growth period of typical forage crops in Tumut Zuoqi from 1990 to 2024 are shown in Fig. 4, and the rainfall of silage maize in the growth and development stage showed certain fluctuations, and the difference between the minimum and maximum values was obvious. Silage maize has a large water demand in the growth and development stage, and rainfall has a great impact on its growth and development and the formation of biomass. The average rainfall during the multi-year growth period of silage maize (May-September) was 307.5mm, the rainfall peaked in 1998 at 534.7mm, and in 2011 it was underestimated at 129.8mm, with a maximum value of 4.12 times the minimum. The average rainfall of silage maize in dry year, normal year and wet year was 193mm, 315mm and 433mm, respectively.

Since the rainfall in 1993,2000 and 2012 is close to the average rainfall of the corresponding hydrological year, 1993 is selected as the typical year of the normal year, 2000 as the typical year of the dry year, and 2012 as the typical year of the wet year. Figure 5 shows the temperature data maps for 1993, 2000 and 2012. The temperature variation range was -25.7 ~ 34.1°C in 1993, -26.4 ~ 35.8°C in 2000, and -27.2 ~ 35.1°C in 2012. The average temperatures in 1993, 2000 and 2012 were 6.96, 7.96°C and 7.07°C, respectively. The average temperatures in the growing seasons in 1993, 2000 and 2012 were 19.86, 21.80°C and 20.34°C, respectively, and the average daily maximum temperatures were 34.1, 35.8 and 35.1°C in June, July and June, respectively.

Point5：

In line 473, refer to Table 1 about soil particle size; however, Table 1 is not this one.

Response 5:

Heartfelt thanks to the reviewer for rigorously pointing out the citation error. We have corrected the 473 lines of false references. In this paper, the soil particle size parameters are wrongly labeled as Table 1, and now corrected to the correct table number (such as Table 9). The contents are as follows:

The model is calibrated by the measured values in 2023 and verified by the measured data in 2024. The soil moisture content, canopy coverage and aboveground biomass (yield) of the model were calibrated and verified by trial and error method.The soil moisture and canopy coverage were sampled and tested using a five-point sampling method, with each point repeated three times and measured once every 7 days. Similarly, the aboveground biomass (yield) was also sampled and tested using a five-point sampling method, with each point repeated three times and measured once every 15 days. Among them, for aboveground biomass (yield), 5 plants that could represent the average growth were taken from each plot, the aboveground parts were cut off, blanched at 105℃ for 0.5h, dried at 75℃ to constant weight, and the dry weight was measured. The aboveground biomass (yield) was obtained by multiplying the dry weight by the planting density. Soil moisture content was determined by the drying method. Crop height was measured with a tape measure. Canopy coverage was calculated using the leaf area index, with an extinction coefficient of 0.7 [43]. Before the experiment, soil texture at each monitoring point was determined using the Wilkes soil particle size distribution method (Table 9). Sampling depths were 0-10cm, 10-20cm, 20-40cm, 40-60cm, and 60-80cm. One groundwater level monitoring well was located within the experimental field (monitored every 7 days, Figure 2). Daily meteorological data for rainfall, radiation, air temperature, wind speed, and humidity were obtained from the automatic weather station in the experimental area (HOBO-U30, Onset Computer Corp., Bourne, MA, USA2).

Point6：

According to lines 463-465, please add mean data of key primarily of results such as aboveground biomass yield (every 15-day measurement) in the main text or in the supplementary section.

Response 6:

Heartfelt thanks to the reviewers for the constructive and valuable suggestions put forward in this paper. According to the reviewer 's suggestion, we uploaded the mean data of the above-ground biomass (measured every 15 days) and soil moisture content (measured every 7 days) results in the supplementary data, and the canopy coverage (measured every 7 days) is reflected in 2.2.1 in the text. The supplementary mean data are consistent with the measured values of the original test, which is accurate and reliable, and further improves the integrity and persuasiveness of the research results.

Point7：

In Fig. 8, add detail of the membrana tectoria type and blue dots in the figure caption.

Response 6:

Heartfelt thanks to the reviewers for their valuable comments. In accordance with the recommendations, we have added a detailed description of the type of film and blue dots in the title of the revised Figure 8. All modifications have been completed and are fully consistent with the contents of the map.

Figure 8. Experimental layout diagram. Coating type, PBAT-based biodegradable mulch; Blue dot, drip irrigation pipe

Point1：In line 38, please be specific in terms of yield, i.e., aboveground biomass yield or crop production yield.

Response 1:

We sincerely thank the reviewer for this insightful suggestion regarding the precision of our terminology. We agree that the term "yield" should be clearly defined to avoid ambiguity.

Point2：

Provide a full name of each abbreviation that is found in all figures in their caption.

Response 2:

Point3：

Add a specific year number and detail (wet, normal, or dry year) for the Figure 7 caption note, including Figures 11 and 12.

Response 3:

Table 6. Effects of water-fertilizer coupling on silage maize yield, water use efficiency and fertilizer partial productivity in different hydrological years.

Planting methods	Different hydrological years	Treatment	Yield（ton ha^-¹）	Water use efficiency（kg ha^-¹ mm^-1）	Fertilizer partial productivity（kg˖kg^-1）
Drip irrigation under film	Wet year （2012）	P1	66.7	128.00	150.23
		P2	70.4	135.10	126.85
		P3	68.9	132.22	103.45
	Normal year （1993）	P4	64.2	145.58	144.59
		P5	67.1	152.15	120.90
		P6	66.3	150.34	99.55
	Dry year （2000）	P7	46.8	127.94	105.41
		P8	48.9	133.68	88.11
		P9	47.6	130.13	71.47
Shallow buried drip irrigation	Wet year （2012）	Z1	65.7	126.08	147.97
		Z2	68.5	131.45	123.42
		Z3	67.4	129.34	101.2
	Normal year （1993）	Z4	60.9	138.10	137.16
		Z5	65.8	149.21	118.56
		Z6	63.7	144.44	95.65
	Dry year （2000）	Z7	45.1	123.29	101.58
		Z8	46.8	127.94	84.32
		Z9	45.7	124.93	68.62

Table 11. Subsurface drip irrigation fertigation system simulation scenario plan.

Hydrological years	Treatment	Irrigation quota /mm						Fertilization amount /（kg˖ha^-1）
Hydrological years	Treatment	Seedling	Jointing	Large bell mouth	heading and flowering	heading and flowering	pustulation	Bottom fertilizer	Jointing	Large bell mouth
Wet year (2012)	P1	10	16	16	16	16	16	300	72	72
	P2	10	16	16	16	16	16	375	90	90
	P3	10	16	16	16	16	16	450	108	108
Normal year (1993)	P4	15	24	24	24	24	24	300	72	72
	P5	15	24	24	24	24	24	375	90	90
	P6	15	24	24	24	24	24	450	108	108
Dry year (2000)	P7	20	32	32	32	32	32	300	72	72
	P8	20	32	32	32	32	32	375	90	90
	P9	20	32	32	32	32	32	450	108	108

Table 12. Shallow drip irrigation water and fertilizer simulation scenario scheme.

Hydrological years	Treatment	Irrigation quota /mm							Fertilization amount /（kg˖ha^-1）
Hydrological years	Treatment	Seedling	Jointing	Large bell mouth	heading and flowering	heading and flowering		pustulation	Bottom fertilizer	Jointing	Large bell mouth
Wet year (2012)	Z1	10	16	16	16		16	16	300	72	72
	Z2	10	16	16	16		16	16	375	90	90
	Z3	10	16	16	16		16	16	450	108	108
Normal year (1993)	Z4	15	24	24	24		24	24	300	72	72
	Z5	15	24	24	24		24	24	375	90	90
	Z6	15	24	24	24		24	24	450	108	108
Dry year (2000)	Z7	20	32	32	32		32	32	300	72	72
	Z8	20	32	32	32		32	32	375	90	90
	Z9	20	32	32	32		32	32	450	108	108

Point4：

According to lines 243-244 and 2. 4.3 Typical hydrological year temperature data: please elaborate on a reason in lines 265-270. Why are 1993, 2000, and 2012 shown for the hydrological years?

Response 4:

Point5：

In line 473, refer to Table 1 about soil particle size; however, Table 1 is not this one.

Response 5:

Point6：

According to lines 463-465, please add mean data of key primarily of results such as aboveground biomass yield (every 15-day measurement) in the main text or in the supplementary section.

Response 6:

Point7：

In Fig. 8, add detail of the membrana tectoria type and blue dots in the figure caption.

Response 6:

Figure 8. Experimental layout diagram. Coating type, PBAT-based biodegradable mulch; Blue dot, drip irrigation pipe

Author Response File: Author Response.docx

Reviewer 3 Report

Comments and Suggestions for Authors

Suggestions:

Title: Summarize and remove duplicate words. I suggest the following: Research on water and fertilizer use strategies for silage corn under different irrigation methods to mitigate abiotic stress.

Abstract: Summarize to a maximum of 200 words according to the journal's guidelines and make the objective clearer in the Abstract.

Keywords: Do not use keywords that already exist in the title.

Introduction: Suggestion to include information on the percentage of freshwater available in China, which has the second largest population in the world, to reinforce the severity of water scarcity in the country. Discuss the importance of corn silage for animal feed in China. Report which animal species are most fed and their quantity in the country to give weight to the choice of plant. At the end of the introduction, make your objective clearer and with fewer elements of the methodology.

Materials and Methods: What is the water quality in the region? Does it present risks of soil salinization? If so, how is this mitigated? In irrigation equipment, does water quality pose a risk of emitter clogging? If so, how is this risk mitigated? Do the soils in the region present a risk of salinization and sodification?

Author Response

Point1：Title: Summarize and remove duplicate words. I suggest the following: Research on water and fertilizer use strategies for silage corn under different irrigation methods to mitigate abiotic stress.

Response 1:

Heartfelt thanks to the reviewers for their professional and constructive suggestions on the title of the paper. We fully adopted and used the title suggested by the reviewer : Research on water and fertilizer use strategies for inducing corn under different irrigation methods to abiotic stress. At the same time, we have combed and condensed the original title according to the requirements, deleted the repeated words, and the optimized title has been updated in the revised draft.

Point2：

Abstract: Summarize to a maximum of 200 words according to the journal's guidelines and make the objective clearer in the Abstract.

Response 2:

Heartfelt thanks to the reviewer for this important and professional proposal. In accordance with the requirements, we carefully revised the abstract in strict accordance with the journal submission guidelines : the content of the abstract was condensed to less than 200 words, and the purpose of this study was further clarified in the revised abstract, so that the content of the abstract was clearer and more accurate. As shown below :

Point3：

Keywords: Do not use keywords that already exist in the title.

Response 3:

Heartfelt thanks to the reviewers for their rigorous and valuable comments. In compliance with the recommendation, we have carefully revised the keyword section : deleted all keywords that were repeated in the revised title, and added representative new keywords related to the core content of this study to ensure the rationality and uniqueness of keywords. As shown below :

Keywords: Water-fertilizer-thermal coupling; water and fertilizer system; drip irrigation under mulch film; shallow buried drip irrigation; AquaCrop model

Point4：

Response 4:

I sincerely thank the reviewers for their comprehensive and constructive comments, which greatly enhance the integrity and argumentation of the introduction. In accordance with the recommendations, we have made detailed modifications and additions to the introduction : ( 1 ) Supplemented the specific data on the proportion of available freshwater resources in China ( the world 's second most populous country ), further highlighting the seriousness of China 's water shortage and the urgency of agricultural water conservation research ; ( 2 ) The important position of silage corn as the main livestock and poultry feed in China was elaborated in detail, which clearly demonstrated the practical significance of selecting silage corn as the research object in this study. ( 3 ) Re-combing and optimizing the end of the introduction, further clarifying the core research purpose of this study, and deleting redundant research methods to make the research purpose more focused and concise. All the revisions are closely combined with the background of this study and fully meet the requirements of the reviewers. As shown below :

Point5：

Response 5:

We sincerely appreciate the reviewer for this rigorous and valuable suggestion. As advised, we have supplemented detailed information regarding water quality, soil salinization/sodification risks and emitter clogging risk in the Materials and Methods sectio. Specifically, the groundwater quality in the study area was tested to be up to the irrigation water quality standard, and the irrigation water posed no risk of soil salinization. In terms of irrigation equipment, the drip irrigation pipes were replaced annually in this study with a limited frequency of irrigation; the groundwater contained few microorganisms, and water-soluble fertilizers were exclusively applied in the experiment, which completely avoided the risk of emitter clogging. Additionally, the soil in the study area had no potential risks of salinization and sodification. All the supplemented contents are consistent with the actual experimental conditions of the study area. As shown below :

The irrigation water source in this study area is local groundwater, which will not cause the risk of soil salinization. The drip irrigation pipe used in the experiment was replaced once a year, and the frequency of field irrigation was low. At the same time, the microbial content of groundwater in the study area is very low, and all fertilization treatments are applied with water-soluble fertilizer, which effectively eliminates the risk of emitter blockage. In addition, under the experimental conditions, there was no potential risk of salinization and alkalization in the soil of the study area.

Author Response File: Author Response.docx

Reviewer 4 Report

Comments and Suggestions for Authors

The study is devoted to the study of an urgent environmental problem and is of interest. The study was conducted on an actual agricultural plant in the field conditions. The work has not only scientific, but also practical significance, which increases the value of the research. The figures and tables are informative. The scope of the study is sufficient. The comments to the authors are given below.

Please complete the introduction: in a separate paragraph, describe the novelty of your research, give a description of the problem - what has already been studied and what is fundamentally new in your work. Add more links to scientific articles in the Introduction.
During the discussion, we ask you to highlight a separate section on corn adaptation to drought and excess water in order to understand the mechanisms of plant adaptation. This section, no matter how small, will enhance the scientific value of the manuscript.
In conclusion, please provide more specific recommendations on the use of your model in agriculture: the pros and cons of the model for today, as well as further prospects for the development of research.

Overall, the study makes a good impression.

Author Response

Point1：Please complete the introduction: in a separate paragraph, describe the novelty of your research, give a description of the problem - what has already been studied and what is fundamentally new in your work. Add more links to scientific articles in the Introduction.

Response 1:

We sincerely thank the reviewers for this insightful and constructive suggestion, which further improves the academic depth and integrity of the introduction. According to the suggestion, we have carefully revised and supplemented the introduction : ( 1 ) A separate paragraph has been added to illustrate the novelty of this study ; ( 2 ) By systematically summarizing the existing research progress and shortcomings in related research fields, the research gaps are clarified, and the fundamental new contents and innovations of this research compared with previous research are further elaborated. ( 3 ) In order to strengthen the academic foundation and logical rigor of the research background and novelty statement, we add more relevant high-quality scientific paper citations in the introduction part. All the supplementary contents are closely integrated with the core research content of this study, which is consistent with the research status in this field. As shown below :

Point2：

During the discussion, we ask you to highlight a separate section on corn adaptation to drought and excess water in order to understand the mechanisms of plant adaptation. This section, no matter how small, will enhance the scientific value of the manuscript.

Response 2:

We sincerely thank the reviewers for this insightful and valuable suggestion, which is crucial to improve the scientific depth and academic value of this study. According to the suggestion, we added a separate paragraph in the discussion section to emphasize and elaborate the adaptation mechanism of silage maize to drought and excessive water stress. This supplement effectively enhances the scientific value of the proposed manuscript. As shown below :

Silage maize shows significant physiological plasticity to extreme water conditions : under drought conditions, it maintains cell turgor pressure through stomatal regulation and root architecture adjustment [41] ; in the case of excess water, hypoxia and nutrient leaching are alleviated by regulating root zone aeration [42]. The dynamic irrigation threshold ( from 90 mm in wet years to 180 mm in dry years ) simulated in this study utilized these biological mechanisms : in dry years, 180 mm supplemental irrigation supported the osmotic regulation of crops and prevented leaf senescence ; in wet years, the irrigation amount reduced to 90 mm optimized the fertilizer-water-air ratio of high-permeability sand and avoided the ' physiological drought ' caused by hypoxia and nutrient leaching in the root zone. By combining with the inherent adaptation strategy of crops, the ' hydrological year-based ' management scheme proposed in this study effectively balances the relationship between crop survival mechanism and yield maximization under multiple abiotic stresses.

Point3：

In conclusion, please provide more specific recommendations on the use of your model in agriculture: the pros and cons of the model for today, as well as further prospects for the development of research.

Response 3:

We sincerely thank the reviewers for their constructive comments. We modified the conclusion section to provide clearer agricultural advice and key evaluations of the model.

Specifically, we have :

Practical suggestions : It is clear that the established framework is applicable to both pre-growth planning and mid-growth scheduling.

Advantages and disadvantages : The advantages of the model ( efficiency in water-driven growth simulation and low parameter requirements for region scaling ) are highlighted, and the disadvantages of the model ( limitations of static management ) are affirmed.

Future prospects : The potential of the AquaCrop framework to integrate with real-time IoT sensors and remote sensing is outlined to achieve precise management from static to dynamic and consistent with sustainable agricultural policies.

We believe that these increases provide a more comprehensive perspective to look at the utility and future trajectory of the model. In the conclusion is as follows :

The ' drip irrigation mode-water and fertilizer level-hydrological year type ' adaptation system constructed in this study provides a robust quantitative basis for water and fertilizer management for pre-growth period planning and mid-growth period scheduling of silage maize in arid and semi-arid irrigation areas. Although the AquaCrop model shows extremely high efficiency in formulating water-saving strategies due to its water-driven engine and low parameter requirements, it is limited to static water and fertilizer system optimization and lacks refined dynamic judgment and system optimization. According to the needs of relevant policies, this experiment will improve the optimization of water and fertilizer system in dynamic changes by combining the model with the Internet of Things (IoT) and remote sensing in the future, and provide a basis for the implementation of relevant policies.