Spatio-Temporal Dynamics and Contributing Factors of Irrigation Water Use in the Loess Plateau

Comments 1: I suggest a detailed review of the methodology, clarifying the data used for the analysis. Do the water use data refer to river inflow and the volume of water in irrigation intakes? In the case of cities, which data is used? Section 2.2 Data Sources indicates the sources from which the data were obtained, but not the details of those data.

Response 1:Thank you for pointing this out. We agree with this comment. Therefore, we have revised Section 2.2 to clarify the nature and source of the irrigation water use data, including distinctions between agricultural and urban contexts.

This revision can be found on Page 3, Lines 125–130.

“The data used in this study include water resource data and land use data. Water resource data from 1965 to 2013, including city-level irrigation water (IRR,1965-2013), quantifying annual agricultural withdrawals including the losses during conveyance and field application (excluding pasture/aquaculture uses), were compiled from national water resource surveys, provincial annual water bulletins covering the Loess Plateau, and FENG’s research data [34]”

Comments 2: Another variable I suggest incorporating into the analysis is precipitation data for the study area, and if available, for each specific location analyzed.

Response 2: Thank you for the insightful comment. We fully acknowledge that irrigation water use is influenced by a range of factors, including climate change—particularly variations in precipitation. However, the objective of our study is not to identify or quantify all possible causal drivers, but rather to decompose the changes in irrigation water use into measurable structural components. Specifically, we use the LMDI model to examine whether increases or decreases in irrigation water use result from changes in total irrigated area, irrigation intensity (i.e., water used per unit area), or adjustments in crop structure and associated technology. Our goal is to provide management-oriented insights that clarify how internal agricultural practices and land-use dynamics contribute to water consumption trends.

We actually agree that external factors such as climate should be integrated into future research, so in response to your concerns, we have added relevant discussion in Section 4.1 (Page 11, Lines 336-339) to acknowledge these broader influences. 

“While irrigation expansion and efficiency improvement are recognized as key drivers, their impacts are shaped by broader socio-economic and climatic dynamics. Precipitation variability and temperature anomalies directly influence irrigation demand and crop growth in arid regions like the Loess Plateau [46].”

Comments 3: I suggest, in the statement made in lines 109-110 be accompanied by a citation confirm it.

Response 3: Thank you for pointing this out. We agree with this comment. Therefore, we have added a citation where in the revised manuscript this change can be found – page 3, line110-112.]

“As shown in Figure 1, the region has a semi-arid to semi-humid climate, with annual precipitation ranging from 50 to 900 mm[28], which exhibits significant temporal and spatial variability[28,29]. ”

Comments  4: I suggest to move lines 200-202 to discussion.

Response 4: Thank you for pointing this out. We have moved it to discussion .This content appears on Page 10, Lines 306-309.

Comments 5: I suggest enriching the discussion by referencing or contrasting it with other studies conducted worldwide.

Response 5: Thank you for pointing this out. We agree with this comment. We have accordingly added international comparisons in the discussion, specifically referencing the North China Plain, where irrigation efficiency improvements have been shown to reduce water use while increasing yields.

This content appears on Page 11, Lines 323-325.

“Similar studies in other arid regions, such as the North China Plain and Middle East and North Africa countries, have reported comparable trends, where irrigation efficiency improvements led to reduced water use despite increasing crop yields [7,41].”

Comments 6: In the Research Limitations and Outlook section, add details of the plant species in the region for future studies, the consumption and the impact of species replacement will be affected differently in function of the type of vegetation.

Response 6: We appreciate this helpful suggestion. We have added a paragraph to Section 4.3 addressing the role of vegetation type and species substitution in irrigation demand.

Please refer to Page 11, Lines 388–396. 

“Different plant species exhibit varying water use characteristics, which may significantly influence irrigation demand. For example, Wei et al. found that native species such as Quercus liaotungensis demonstrated more stable radial growth and lower water use sensitivity to drought compared to introduced species like Robinia pseudoacacia in the Yangjuangou catchment of the Loess Plateau[52]. This suggests that species replacement, often driven by ecological restoration policies, may alter regional water balances. Future research should consider the hydrological impacts of vegetation structure and species composition when evaluating land use transitions and ecosystem recovery in arid and semi-arid regions.”

Comments 1: The pixels of the images in the paper are low and not clear.

Response 1:Thank you for pointing this out. We have re-exported and replaced all figures with high-resolution versions.

Comments 2: There are some inconsistencies in the lengths of data series in the research of the thesis, which need to be explained.

Response 2: Thank you for your suggestion. We have added notes in Section 2.2 to explain that the land use data covers 1985–2020 while irrigation water use data covers 1965–2013 due to data availability differences. The temporal spans of datasets used in this study vary due to differences in data availability. Specifically, the spatiotemporal analysis of cultivated land and irrigated area was based on the available high-resolution land use datasets starting from 1985. In contrast, for the driving force analysis of irrigation water use, we selected the period 1965–2013, as this range contains complete, consistent, and uninterrupted data for irrigation water use, cultivated land area, and planting structure across all study areas.This choice ensures the accuracy and reliability of the LMDI decomposition results. Please see Page 3-4, Line 122–132.

“The data used in this study include water resource and land use data. Water resource data from 1965 to 2013, including city-level irrigation water (IRR,1965-2013), quantifying annual agricultural withdrawals including conveyance and application losses (excluding pasture/aquaculture uses), were compiled from national water resource surveys, provincial annual water bulletins covering the Loess Plateau, and FENG’s research data [34]. Land use data, spanning 1985 to 2020, were derived from the China Land Cover Dataset (CLCD)[35], which classifies land cover into nine categories: farmland, forest, shrubs, grassland, water, ice/snow, bare land, impervious surfaces, and wetlands. The dataset has a spatial resolution of 30 meters and an overall accuracy of 80%. Irrigated area data combined historical records from Feng's research (1965-2013) with governmental agricultural statistics (2000-2019)[34], ensuring temporal continuity.”

Comments 3: The function of Segmented linear regression for agricultural irrigation water in the Loess Plateau should be presented in the paper.

Response 3: Thank you for your comments. We have added a formal explanation of piecewise linear regression and its role in identifying water use trend phases.This can be found in section 2.3.1(Page 4-5, Lines 137–149).

Comments 4: The analysis of driving factors of irrigation water is not comprehensive enough. Irrigation water is affected by local climate change, and at the same time, in the Loess Plateau, the water coming from the upper reaches of the Yellow River and the water diversion policy all affect irrigation water. This paper needs further in-depth analysis and discussion.

Response 4: Agree. Thank you. We have added text in Section 4.1 to emphasize the influence of water diversion policies, precipitation variability, and regional policy heterogeneity.This can be found in Page 11, Lines 336-345.

“ While irrigation expansion and efficiency improvement are recognized as key drivers, their impacts are shaped by broader socio-economic and climatic dynamics. Precipitation variability and temperature anomalies directly influence irrigation demand and crop growth in arid regions like the Loess Plateau [46]. Market-driven cropping shifts, such as from grain to cash crops, can intensify water use when high-value crops are prioritized [47]. Moreover, institutional factors—such as water allocation policies and inter-basin transfer schemes in the Yellow River Basin—substantially affect local water availability [48,49], with marked disparities in irrigation infrastructure and governance across sub-regions [50]. These complex and region-specific drivers warrant further integration into future research and tailored policy recommendations.”

Comments 1: Page 1 Line 30: All keywords are used in the title; it is not preferred to use keywords that are in the title.

Response 1:Thank you. We have revised the keywords to avoid duplication with the title.

See revised keywords on Page 1, Line 30.

“Keywords: Loess Plateau; Water-saving irrigation; LMDI model; Spatio-temporal analysis ”

Comments 2: Page 2 Line 53: “STIRPAT” Authors should add the terms of the abbreviation at the first mention.
Page 2 Line 95: “Logarithmic Mean Divisia Index (LMDI) model”. 

Response 2: Thank you for your suggestion.Agree. We have updated the first occurrence of STIRPAT to include its full form.This change can be found – page 2, line 53-54.

“Similarly, Zhao et al. utilized an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) model to analyze agricultural water use in China, highlighting the roles of population growth, urbanization, and dietary changes as key drivers[10]. “

Comments 3: Page 3 Lines 99-101: “The findings provide crucial insights into the dynamics of …...” The authors should add the findings and conclusions after the results and discussion section.

Response 3: Thank you for pointing this out. We agree with this comment. Therefore, we have added a citation where in the revised manuscript this change can be found – page 3, line102-105.]

“This research could provide crucial insights into the dynamics of irrigation water use, offering practical guidance for optimizing water resource management and fostering sustainable development in the Loess Plateau. ”

Comments 4: Page 4 Line 152: Authors should draw a flowchart to describe the whole working process to facilitate the reader's understanding of the spatiotemporal dynamics of irrigation water use in the Loess Plateau.

Response 4: Thank you for pointing this out.Agree. We have added section2.3.1research framework and a process flowchart titled “Integrated workflow of the study” to help readers understand the methodology.

See Page 4, Line 135-146.

Comments 5:Page 5 Line 170; Figure 2 & Page 5 Line 187; Figure 3b:  It is preferable to add the coordinates of latitude and longitude. Also, the authors should provide a higher quality version of all figures. 
Page 6 Line 222; Figure 5: The authors should provide a higher quality version with visible legend, it's better to cover full page width.

Response 5: Thank you for pointing this out. We have revised these figures to include latitude/longitude coordinates. Figure 5 has been updated with enhanced resolution and a wider layout to improve readability.

See Figure 3, Figure 4b, Figure 6.

Comments 6:Page 7 Line 246: The presented results focus primarily on the role of increased irrigation rates alone, while attributing changes in water use primarily to irrigation expansion and improved efficiency may oversimplify more complex social, economic, or climatic factors. The authors also need to add more literatures review, as the lack of regional differentiation in policy recommendations, as the guidelines presented are general, may not adequately consider local variations across the diverse Loess Plateau regions.

Response 6: Thank you for this valuable suggestion. In response, we have revised the manuscript to better address the complexity and spatial heterogeneity of the driving factors of irrigation water use:

1. In the Results section, we added a new spatial analysis of driving factors across four distinct periods. This is now supported by a newly added figure (Figure 9), which visualizes the spatial distribution of the leading drivers (i.e., irrigated area, crop mix, and water use intensity) across different cities. This can be found in Page 9-10, Lines 267-280.

“Figure 9 reveals clear spatio-temporal heterogeneity in the dominant driving factors of irrigation water use across four stages. From 1965 to 1977, irrigated area expansion dominated most regions, while Ningxia was primarily influenced by increased irrigation intensity, and parts of the Hetao Plain were shaped by changes in crop structure. Between 1977 and 1987, reductions in irrigated area dominated the Hetao region, and declining irrigation intensity was prevalent in several cities in Shanxi and Shaanxi. From 1987 to 2001, irrigated area expansion again became the main driver in the northwest, while irrigation intensity was the dominant factor in the Weihe River Basin and surrounding areas. During 2001–2013, declining irrigation intensity emerged as the most widespread driver, particularly across the Hetao Plain and the northern Mu Us Sandy Land, while other factors showed a more scattered spatial distribution.Land.”

2. In the Discussion section (Section 4.2), we revised the policy recommendations to reflect region-specific management implications. This can be found in Page 11-12, Lines 360-368.

“In addition, the strong regional differentiation in dominant driving factors highlights the need for spatially targeted land and water management strategies. In regions where declining irrigation intensity was the primary driver—such as Ningxia and the northern Mu Us Sandy Land—further promotion of high-efficiency irrigation technologies and crop-water structure optimization is recommended to consolidate existing water-saving outcomes. In contrast, areas where irrigated area expansion persists, such as Ordos and the Hetao irrigation zone, should prioritize stricter irrigation access controls and proactive water use regulation to prevent the accumulation of pressure on regional water resources due to excessive expansion.”

Comments 7: Page 7 Line 229 (Yellow River ranged from -4 to 2 km3 yr-1): Authors should revise the change in agricultural irrigation water use in the middle reaches of the Yellow River.

Page 7 Lines 229-240: “km3 yr-1” Authors should review the units and correct any typos, for example: lines 229, 232, 236 and 240

Response 7:Thank you for pointing this out. We agree with this comment. We have checked and corrected all unit expressions throughout the Results section for consistency.Please see Page 8, Section3.3.

Comments 8: Pages 10-11 Lines 361, 412 and 420; Ref. 6, 30 and 34: Add the name of all authors. The authors should use the MDPI reference style.

Page 12, Line 433: Ref. 39: Revise and check the page number “25-38+204.” and add the reference DOI. Page 12, Line 435: Ref. 40: Delete the repeated dote " Kang, S.Z..". 

Page 12, Line 438: Ref. 41: Add the reference DOI and delete the extra symbol " — —". 

Page 12, Line 443: Ref. 43: Revise and check the page number “1-10+122.” and delete the extra symbol " — —". 

Response 8: Thank you for pointing this out. We have revised all relevant references according to the MDPI reference style, adding author names, fixing punctuation, and including DOIs where available.