A semi-quantitative approach for modelling crop response to soil fertility: evaluation of the AquaCrop procedure

Abstract

Most crop models make use of a nutrient-balance approach for modelling crop response to soil fertility. To counter the vast input data requirements that are typical of these models, the crop water productivity model AquaCrop adopts a semi-quantitative approach. Instead of providing nutrient levels, users of the model provide the soil fertility level as a model input. This level is expressed in terms of the expected impact on crop biomass production, which can be observed in the field or obtained from statistics of agricultural production. The present study is the first to describe extensively, and to calibrate and evaluate, the semi-quantitative approach of the AquaCrop model, which simulates the effect of soil fertility stress on crop production as a combination of slower canopy expansion, reduced maximum canopy cover, early decline in canopy cover and lower biomass water productivity. AquaCrop's fertility response algorithms are evaluated here against field experiments with tef (Eragrostis tef (Zucc.) Trotter) in Ethiopia, with maize (Zea mays L.) and wheat (Triticum aestivum L.) in Nepal, and with quinoa (Chenopodium quinoa Willd.) in Bolivia. It is demonstrated that AquaCrop is able to simulate the soil water content in the root zone, and the crop's canopy development, dry above-ground biomass development, final biomass and grain yield, under different soil fertility levels, for all four crops. Under combined soil water stress and soil fertility stress, the model predicts final grain yield with a relative root-mean-square error of only 11–13% for maize, wheat and quinoa, and 34% for tef. The present study shows that the semi-quantitative soil fertility approach of the AquaCrop model performs well and that the model can be applied, after case-specific calibration, to the simulation of crop production under different levels of soil fertility stress for various environmental conditions, without requiring detailed field observations on soil nutrient content

Utilizing Process-Based Modeling to Assess the Impact of Climate Change on Crop Yields and Adaptation Options in the Niger River Basin, West Africa

“…To calibrate AquaCrop, we followed the procedure described in detail in [21] and [20]. Briefly, the procedure is as follows:…”

“…This approach produces a ratio (Brel). This is calculated as the total dry above ground biomass at the end of the growing season in a field with soil fertility stress (Bstress) divided by the dry above ground biomass at the end of the growing season in a field without soil fertility stress (Bref) [20]. AquaCrop model has four levels of soil fertility: Poor (P), moderate (M), near optimal (NP) and optimal (OP) levels corresponding to the Nitrogen rate of 0 kg/ha, 60 kg/ha, 90 kg/ha and 120 kg/ha respectively [21].…”

“…In this paper we utilized the Food and Agricultural Organization (FAO)-developed AquaCrop, a process based model, first to quantify crop yield response to climate change in the Niger River Basin (NRB), and second, to investigate the effects of various adaptation measures in mitigating climate change impacts on crop yields. AquaCrop simulates crop yield as a function of water consumption [17,18] and has been shown to satisfactorily model crop yields in various parts of Africa [19,20]. Within the Niger River Basin, [21] (pp.…”

Effects of Management Practices on Quinoa Growth, Seed Yield, and Quality

“…Notably, a small yield decrease was also observed when increasing the nitrogen application up to the highest nitrogen application of 160 kg ha −1 [11]. These disparities can be understood by the large variations in soil fertility, varieties, and crop needs, as affected by water, nutrition supply, plant density, and other environmental constraints [31,32]. Little reported information on the nitrogen application management of quinoa considers nitrogen uptake and soil fertility.…”

Simulation of seed productivity of the rice varieties in the conditions of the South of Ukraine

“…Виявилося, що під впливом зміни клімату спостерігається тенденція до зменшення потреби в зрошувальній воді для рису в досліджуваному районі, а малі схеми зрошення відповідають вимогам (Shrestha, 2014). Дослідження з тефом в Ефіопії, з кукурудзою, пшеницею в Непалі і з квіноа в Болівії показують, що напівкількісна модель родючості ґрунтів AquaCrop може бути застосована за різних рівнів стресу родючості ґрунту для різних умов навколишнього середовища без необхідності проведення детальних польових спостережень за вмістом поживних речовин у ґрунті (Gaelen et al, 2015). У Боснії та Герцеговині програма була застосована в моделюванні майбутніх сценаріїв вирощування з урахуванням різних режимів зрошення та коливань опадів, температури, концентрації СО 2 та термінів сівби.…”