Basic Soil Data Requirements for Process-Based Crop Models as a Basis for Crop Diversification

Eranga M Wimalasiri,Tengku Adhwa Syaherah Tengku Mohd Suhairi,Sayed N Azam-Ali,Asha S Karunaratne,Hasika Udayangani,Lal P Vidhanarachchi,Ranjith B Mapa,Ebrahim Jahanshiri

doi:10.3390/su12187781

Eranga M Wimalasiri, Tengku Adhwa Syaherah Tengku Mohd Suhairi + Show 6 more

Open Access

https://doi.org/10.3390/su12187781

Copy DOI

Abstract

Data from global soil databases are increasingly used for crop modelling, but the impact of such data on simulated crop yield has not been not extensively studied. Accurate yield estimation is particularly useful for yield mapping and crop diversification planning. In this article, available soil profile data across Sri Lanka were harmonised and compared with the data from two global soil databases (Soilgrids and Openlandmap). Their impact on simulated crop (rice) yield was studied using a pre-calibrated Agricultural Production Systems Simulator (APSIM) as an exemplar model. To identify the most sensitive soil parameters, a global sensitivity analysis was performed for all parameters across three datasets. Different soil parameters in both global datasets showed significantly (p < 0.05) lower and higher values than observed values. However, simulated rice yields using global data were significantly (p < 0.05) higher than from observed soil. Due to the relatively lower sensitivity to the yield, all parameters except soil texture and bulk density can still be supplied from global databases when observed data are not available. To facilitate the wider application of digital soil data for yield simulations, particularly for neglected and underutilised crops, nation-wide soil maps for 9 parameters up to 100 cm depth were generated and made available online.

Highlights

With the growing concern about climate change and food security, process-based crop models have been used to aid decisions at local, regional and global scales [1,2]
Of all observed soil parameters, the average pH, drainage upper limit (DUL), LL15 and AD of the standard profiles were significantly (p < 0.05) different among climate zones indicating the high variability of soil properties in Sri Lanka (Figures 2 and 3)
Note: BD = bulk density, OC = organic carbon, CEC = cation exchange capacity, SAT = saturation, DUL = drainage upper limit, LL15 = wilting point and AD = soil moisture limit to which soil can dry by evaporation

Summary

Introduction

With the growing concern about climate change and food security, process-based crop models have been used to aid decisions at local, regional and global scales [1,2]. Crop modelling approaches are used in on-farm decision making, studying nutrient dynamics [4], plant breeding [5], sensitivity of crops to changing climates [1] and policy-making [2]. Crop modelling is a useful tool for understanding the likely productivity of crops in different environments. It has been recently suggested that crop modelling can be used to provide evidence for crop diversification in areas that are affected by climate change [6,7]. Simulating the crop yield is cumbersome for these crops as detailed field data are rarely available. Modelling the performance of these crops can benefit from extensive data being available for major crops

Methods

Results

Discussion

Conclusion