Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China

Zhang, Wei; Liu, Chunyan; Zheng, Xunhua; Wang, Kai; Cui, Feng; Wang, Rui; Li, Siqi; Yao, Zhisheng; Zhu, Jiang

doi:https://doi.org/10.5194/bg-16-2905-2019

Articles | Volume 16, issue 14

https://doi.org/10.5194/bg-16-2905-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/bg-16-2905-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 16, issue 14

Research article

|

31 Jul 2019

Research article |

| 31 Jul 2019

Using a modified DNDC biogeochemical model to optimize field management of a multi-crop (cotton, wheat, and maize) system: a site-scale case study in northern China

Wei Zhang, Chunyan Liu, Xunhua Zheng, Kai Wang, Feng Cui, Rui Wang, Siqi Li, Zhisheng Yao, and Jiang Zhu

Download

Final revised paper (published on 31 Jul 2019)
Supplement to the final revised paper
Preprint (discussion started on 25 Sep 2018)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Review-Bg 2018-401-1', Anonymous Referee #1, 05 Dec 2018
- AC1: 'Responses to reviewer', Xunhua Zheng, 16 Jan 2019
RC2: 'Review of "Modeling the biogeochemical effects of rotation pattern and field management practices in a multi-crop (cotton, wheat, maize) rotation system: a case study in northern China"', Anonymous Referee #2, 28 Dec 2018
- AC2: 'Responses to reviewer', Xunhua Zheng, 16 Jan 2019

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

ED: Reconsider after major revisions (17 Jan 2019) by Paul Stoy

AR by Xunhua Zheng on behalf of the Authors (14 Feb 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (25 Feb 2019) by Paul Stoy

RR by Anonymous Referee #1 (28 Mar 2019)

Suggestions for revision or reasons for rejection

Dear Editor,

As stated in the previous review, the manuscript entitled “Modeling the biogeochemical effects of rotation pattern and field management practices in a multi-crop (cotton, wheat, maize) rotation system: a case study in northern China” is within the scope of BG. To ensure reliability, models should be tested and improved as part of their development and application. The manuscript is important in that context but the important part of this manuscript lies with the optimization of different rotation patterns (of three cultivars: cotton, wheat, maize) and management practices which is very complex. The manuscript has been revised and improved. Nonetheless, there are important gaps (see below) which should be seriously considered. The current manuscript is not acceptable for publication in BG as it is poor in terms of validation as well as in novelty. For more details please see my comments below:

GAPS:
- it lacks for a 6 years validation that includes a rotation of all three commodity crops as well as all studied management practices in question

- In the site simulation, NEE is still predicted with lower accuracy by the model; then how this impacted the optimization of mitigation options? Furthermore, decision variables such as NH3 volatilization is not validated by observations.

- There are some vias between modeled annual no3 leaching and assumed observations for no3 leaching. You stated “For the simulations of other nitrogen losses from the cotton field, the NO3−leaching accounted for 9−12% of the applied fertilizer nitrogen for model validation, which was comparable with the field measurements of 16−17%”. This is around 10 Kg N year, rigth? Please, think about what that would means if you scale this value on a regional level (for the whole Northern China) up.

How all this gaps affected your BMP and NIP calculations?

In order to improve the quality of this study (which is poor in terms of validation and novelty), I suggest you to do a Parameter-Induced Uncertainty Quantification for NEE + NH3 + NO + N2O and NO3 Leaching. The Bayesian framework using a Markov Chain Monte Carlo (MCMC) method, will help you to estimate the joint model parameter distribution and you can obtain and pick up the best parameter set combination (using a cost function based on model fitting parameters) that represent your measurements. After this, you can use Monte Carlo in order to derive the best management practice for the studied site.

I still think that a regional inventory for Northern china should be included in the scope of your study (especially because of the importance of the crop rotation cotton, W-M in this region). For this you can pick up the best 50-100 parameters set combinations (derived with the Bayesian framework) together with the BMP (derived with Monte Carlo) and do a Parameter-Induced Uncertainty Quantification of Regional NEE + NH3 + NO + N2O and NO3 Leaching. This can help to policy decision makers to support farmers in Northern China.

Hide

ED: Reconsider after major revisions (03 Apr 2019) by Paul Stoy

AR by Xunhua Zheng on behalf of the Authors (14 Jun 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (14 Jun 2019) by Paul Stoy

RR by Anonymous Referee #3 (03 Jul 2019)

ED: Publish as is (03 Jul 2019) by Paul Stoy

AR by Xunhua Zheng on behalf of the Authors (08 Jul 2019) Manuscript

Download

Article (2746 KB)
Full-text XML

Short summary

A biogeochemical process model-based approach for screening the best management practices (BMPs) of a three-crop system was proposed. The BMPs are the management alternatives with the lowest negative impact potentials that still satisfy all given constraints. Three BMP alternatives with overlapping uncertainties of simulated NIPs were screened from 6000 scenarios using the modified DNDC95 model, which could sustain crop yields, enlarge SOC stock, mitigate GHG, and reduce other nitrogen losses.