the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 21 Oct 2024
Modeling irrigation and land surface dynamics: comparing AquaCrop and Noah-MP over the Po Valley
Abstract. In this study, irrigation was estimated over the Po Valley (Italy) at a 1-km2 spatial resolution using (i) a crop model, AquaCrop, and (ii) a land surface model, Noah-MP. Both models were run with sprinkler irrigation using a similar setup within NASA's Land Information System. Irrigation estimates were evaluated at the pixel and basin scale, using in situ and satellite-based reference data. In addition, surface soil moisture (SSM), vegetation, and evapotranspiration (ET) estimates were compared with satellite retrievals.
Noah-MP shows on average higher annual irrigation rates (434 mm yr-1) compared to AquaCrop (268 mm yr-1), mainly because more irrigation water losses (not consumed by transpiration) are simulated and compensated for in Noah-MP (runoff, interception, and soil evaporative losses), whereas AquaCrop only accounts for soil evaporative losses. When taking into account representative application water losses for AquaCrop, and conveyance water losses for both models, the irrigation estimates fall within reported ranges of 500–600 mm yr-1. For the field-based evaluation, Noah-MP presents large irrigation events (> 100 mm per event) and less interannual variability compared to AquaCrop. Two-week averaged SSM estimates from both models agree well with downscaled estimates from the Soil Moisture Active Passive (SMAP) mission, with spatially averaged unbiased root mean square differences of 0.05 and 0.04 m3 m-3 for AquaCrop and Noah-MP, respectively. Both models show limitations in terms of vegetation and ET modeling, mainly due to the generalization of vegetation parameters for AquaCrop and a possible sub-optimal vegetation parametrization for Noah-MP. The results of this study highlight the differences between the models which have been created for distinct original purposes and scales, as well as the complexity of irrigation modeling due to its anthropogenic nature, emphasizing the need for observations.
Status: final response (author comments only)
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CC1: 'Comment on egusphere-2024-3205', Nima Zafarmomen, 06 Nov 2024
The paper does an excellent job comparing AquaCrop and Noah-MP, two models with distinct goals and methodologies, to evaluate their performance in estimating irrigation in the Po Valley. This side-by-side analysis provides valuable insights into the advantages and limitations of crop models versus land surface models when applied to complex irrigation systems.
1) How might data assimilation of satellite soil moisture or vegetation index data affect the model's ability to capture interannual variability in irrigation accurately? Would this approach potentially reduce some of the overestimations observed?2) Given the paper's findings on the variability of irrigation rates and timing, do the authors see data assimilation as a viable approach for operational large-scale irrigation modeling, or do they foresee challenges in scalability?
3) Noah-MP includes canopy interception and runoff losses, whereas AquaCrop does not. Could the authors discuss how these differing approaches to irrigation losses might affect their model outputs, especially in the context of large-scale regional studies?
4) I highly recommend the authors consider citing recent work on data assimilation in hydrological modeling for irrigation, specifically studies that integrate satellite-based vegetation indices to improve model accuracy. For example, studies like 'Assimilation of Sentinel‐based Leaf Area Index for Modeling Surface‐Groundwater Interactions in Irrigation Districts'and 'Multivariate Assimilation of Satellite-based Leaf Area Index and Ground-based River Streamflow for Hydrological Modeling of Irrigated Watersheds using SWAT+' showcase how data assimilation can enhance the irrigation districts.
Citation: https://doi.org/10.5194/egusphere-2024-3205-CC1 -
RC1: 'Comment on egusphere-2024-3205', Anonymous Referee #1, 15 Jan 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3205/egusphere-2024-3205-RC1-supplement.pdf
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AC1: 'Reply on RC1', Louise Busschaert, 16 Jan 2025
Dear Referee#1,
We would like to thank you for your time and thoughtful comments on our manuscript. Through this first short response, we would like to take the opportunity to provide clarification on a few important aspects.
First, regarding the study's objective and novelty, we recognize the need for clarification in the manuscript. Both AquaCrop and Noah-MP have been used to estimate irrigation in previous studies. Our goal is not to advance irrigation modeling for the Po Valley specifically but to conduct a comparative analysis of these models as they are. Each model has different original purposes and methodological assumptions, and for the first time, these two types of models are directly compared and analyzed in detail in the context of irrigation modeling at coarse spatial resolution. By confronting their outputs under similar configurations and evaluating them against reference data, we aim to highlight their strengths, weaknesses, and implications for irrigation modeling at large scale. The Po Valley serves as a representative test case due to its intensive irrigation practices.
Regarding the use of a generic crop, this approach is commonly adopted for coarse-resolution studies, including applications with AquaCrop, as it represents a simplified, generalizable crop type suited to large-scale applications, while specific crop types are more appropriate for very high-resolution (field-level) studies. Several parameters, such as the irrigation scheme, were chosen to ensure they are comparable and applicable in both models. In our revised manuscript, we will clarify these parameterization choices to address this point.
We value your feedback and believe the concerns raised can be addressed in a revised version.
Citation: https://doi.org/10.5194/egusphere-2024-3205-AC1 -
AC2: 'Reply on RC1', Louise Busschaert, 15 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3205/egusphere-2024-3205-AC2-supplement.pdf
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AC1: 'Reply on RC1', Louise Busschaert, 16 Jan 2025
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RC2: 'Comment on egusphere-2024-3205', Anonymous Referee #2, 24 Jan 2025
General comment:
This study compares the performance of AquaCrop and Noah-MP models in simulating irrigation and land surface dynamics in the Po Valley, Italy. The methodology is scientifically rigorous, and the data sources are extensive, including field observations, satellite data, and model simulations. The research highlights the differences between the two models under distinct application contexts and reveals the complexity of irrigation modeling. The findings provide valuable insights into improving irrigation modeling and its applications at various scales. However, there remains room for improvement, including deeper discussions on parameterization choices, more comprehensive quantification of uncertainties, and an expanded analysis of the generalizability of the findings.
Specific comments:
- In the introduction, it is recommended to clearly articulate the rationale for choosing AquaCrop and Noah-MP as the focus of the study, with particular emphasis on their respective strengths and limitations in irrigation modeling.
- The description of land surface models (LSMs) and crop models in Section 1 is overly broad. Simplifying the background information and focusing on the aspects most relevant to irrigation modeling would improve clarity.
- Although the paper identifies input data quality and structural assumptions as major sources of uncertainty, it lacks a detailed quantitative analysis. For instance, sensitivity analysis or error decomposition could provide more precise assessments of these uncertainties.
- The potential errors in satellite data and field observations and their impact on the validation results should be further discussed.
- Section 2 mentions critical parameters (e.g., soil moisture thresholds and rootzone depth) that significantly affect simulation outcomes but lacks detailed justification for their selection.
- The differences in vegetation and evapotranspiration modeling between AquaCrop and Noah-MP are crucial. A more thorough analysis of how these differences contribute to discrepancies in the results is recommended.
- Section 4 discusses the limitations of the models but does not adequately explore the applicability of the findings to other regions or climatic conditions. Adding a discussion in this regard or proposing directions for future research could strengthen the study.
- The differing color scales in Figures 2 and 3 may hinder direct comparison. Standardizing the color scales or explaining the differences in the legend is recommended.
- While the temporal changes in irrigation data in Figure 8 are clear, adding a specific discussion on anomalous years (e.g., the 2017 drought) would highlight the models' adaptability to extreme conditions.
Technical corrections
- Replace "AquaCrop relies on a conceptual water balance model (BUDGET)" with "AquaCrop relies on an empirical water balance model (BUDGET)" to more accurately reflect its reliance on empirical formulas.
- The phrase "Temporal aggregation smooths the dynamics but may hide short-term events" would benefit from specific examples of such "short-term events" to enhance clarity.
- The symbols in Equations (1) and (4) should be further clarified when they first appear to avoid potential misunderstanding.
- Ensure consistency in units throughout the paper, such as between mm yr-1 and mm d-1 for outputs like irrigation depth and evapotranspiration.
Citation: https://doi.org/10.5194/egusphere-2024-3205-RC2 -
AC3: 'Reply on RC2', Louise Busschaert, 15 Mar 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2024/egusphere-2024-3205/egusphere-2024-3205-AC3-supplement.pdf
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