Coupling DSSAT and HYDRUS-1D for simulations of soil water dynamics in the soil-plant-atmosphere system

Abstract Accurate estimation of the soil water balance of the soil-plant-atmosphere system is key to determining the availability of water resources and their optimal management. Evapotranspiration and leaching are the main sinks of water from the system affecting soil water status and hence crop yield. The accuracy of soil water content and evapotranspiration simulations affects crop yield simulations as well. DSSAT is a suite of field-scale, process-based crop models to simulate crop growth and development. A “tipping bucket” water balance approach is currently used in DSSAT for soil hydrologic and water redistribution processes. By comparison, HYDRUS-1D is a hydrological model to simulate water flow in soils using numerical solutions of the Richards equation, but its approach to crop-related process modeling is rather limited. Both DSSAT and HYDRUS-1D have been widely used and tested in their separate areas of use. The objectives of our study were: (1) to couple HYDRUS-1D with DSSAT to simulate soil water dynamics, crop growth and yield, (2) to evaluate the coupled model using field experimental datasets distributed with DSSAT for different environments, and (3) to compare HYDRUS-1D simulations with those of the tipping bucket approach using the same datasets. Modularity in the software design of both DSSAT and HYDRUS-1D made it easy to couple the two models. The pairing provided the DSSAT interface an ability to use both the tipping bucket and HYDRUS-1D simulation approaches. The two approaches were evaluated in terms of their ability to estimate the soil water balance, especially soil water contents and evapotranspiration rates. Values of the d index for volumetric water contents were 0.9 and 0.8 for the original and coupled models, respectively. Comparisons of simulations for the pod mass for four soybean and four peanut treatments showed relatively high d index values for both models (0.94–0.99)

Model Intercomparison of Maize Response to Climate Change in Low-Input Smallholder Cropping Systems

Smallholder farming systems are characterized by poor soil fertility and low agricultural input use; process-based crop growth models can help quantifying the potential impact of climate change on productivity in these systems.With limiting conditions (water and nutrients), crop models need to rigorously account for soil water, nutrient, CO2, and temperature interactions when simulating climate change effects

Simulating forage yields and soil organic carbon under Brachiaria hybrid cv. Cayman in Tanzania with the CROPGRO perennial forage model

Land and soil degradation in cropping systems in sub-Saharan Africa has been exacerbated by inappropriate use of landscapes and poor management practices that result into environmental and subsequential social damages. Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve yields and soil organic carbon (SOC) sequestration. Numerous modelling studies have been conducted on annual cropping systems, however there are no modelling studies on perennial forages. The goal of this study was to adjust and evaluate the ability of DSSAT CROPGRO-Perennial Forage model version 4.7.5.0, which was initially parameterised for Brachiaria cv. Marandu in Brazil, to simulate biomass yields and SOC under Brachiaria cv. hybrid Cayman (BHC) in three districts in the southern highlands of Tanzania. The key adjusted parameters were soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. After model calibration, the root means square error ranged from 638 to 2111 kg/ha for harvested biomass. The d-Statistic for harvested biomass ranged from 0.78 to 0.97. The RMSE for % SOC ranged from 0.26 to 1.01 % and 0.23 to 1.55 % at 0-20 cm and 20-40 cm depth respectively. The d-Statistic for SOC from ranged 0.19 to 0.35 and 0.40 to 0.53 for 0-20 cm and 20-40 cm respectively. The results indicate that the model can be used to simulate the growth of Brachiaria cv. Cayman under different soils and weather conditions with an acceptable adjustment of specific parameters including soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. Also, the model simulated SOC reasonably well despite the wide variability between observed and simulated values, which was attributed to short period for experimentation and other factors not captured by the model including residue return among others. The adapted parameterised model for Brachiaria cv. Marandu performed reasonably well in simulating biomass and SOC in a different region with different soils, climate and management. Hence, the parameterised model for Brachiaria cv. Marandu can also be used for Brachiaria cv. Cayman in a different region with different soils and climate conditions

Adapting the CROPGRO model to simulate biomass production and soil organic carbon of Cayman grass in East Africa

Biophysical models are key to inform management activities that can restore degraded soils and ultimately improve biomass production and soil organic carbon (SOC) sequestration. Within East Africa several studies have been conducted to evaluate models in annual cropping systems, and to quantify the impacts of different agronomic management options on soil organic carbon and yields. However, no modelling studies exist on perennial forage grasses, which are important for mixed-crop livestock systems within the region. We evaluate the CROPGRO-Perennial Forage model (CROPGRO-PFM) using harvested biomass and SOC data from several sites across Kenya and Tanzania. The model version initially parametrized for Brachiaria cv. Marandu and Panicum maximum in Brazil is applied to simulate Brachiaria cv. hybrid Cayman and Panicum maximum in the two countries. We modify model parameters to improve d-statistic and root mean square error (RMSE) for biomass and SOC. Our results show that the CROPRO-PFM model can simulate biomass of Brachiaria cv. Cayman under different soils and weather conditions with an acceptable adjustment of parameters including soil water (lower limit, drained upper limit, saturated water content) and stable soil organic carbon. The d-statistic for harvested biomass across the Tanzania sites ranged between 0.78 to 0.97, while the root means square error ranged between 0.6 to 2 t/ha. Sensitivity simulations with increased manure application rates of 5t/ha show an increase in SOC of up 0.833 t/ha/yr. These results suggest that the CROPGRO-PFM can be used to simulate growth of Brachiaria cv. Cayman adequately under rainfed conditions in the East African highlands

Impacts of 1.5 versus 2.0 °c on cereal yields in the West African Sudan Savanna

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security

Sorghum [Sorghum bicolor (L.) Moench] and cowpea [Vigna unguiculata (L.) Walpers] intercropping improves grain yield, fodder biomass, and nutritive value

Burkina Faso livestock feeding is characterized by a hot dry season fodder deficit, which affects animal performance and causes economic losses. To overcome this challenge, improving quality fodder production through the use of dual-purpose crops is a potential alternative. Hence, this study aimed at testing dual-purpose cultivars of sorghum and cowpea under monoculture and intercropping in the North Sudan zone in Burkina Faso. To do this, a “Mother and Baby trials” approach was adopted. The mother trial was designed as a randomized complete block with eight treatments (combinations of monoculture and intercropping systems for two cowpeas and two sorghum cultivars) and four replications during two cropping seasons (2019 and 2020) at the INERA research station in Saria. The on-farm “baby” trials involved 30 farmers during two cropping seasons (2019 and 2020) in four communes: Koudougou, Poa, Nandiala, and Kokologo. Data were collected on weed biomass and density, fodder biomass and grain yield, intercropping efficiency, and fodder nutritive value. The results of the mother trial showed that intercropping significantly (p ≤ 0.05) reduced weed density and weed biomass. Sorghum cultivar Ponta Negra had the highest fodder biomass yield (10.05 kg DM/ha) while sorghum Sariaso16 had the highest grain yield (4.42 kg/ha). Cowpea cultivar KVx745-11P had greater fodder biomass (4.72 kg DM/ha) than Tiligré (3.28 kg DM/ha) with similar grain yield (2.17 and 2.17 kg/ha). Intercropping was the most efficient land-use cropping system for fodder biomass and grain yield improvement both in mother and baby trials. For fodder nutritive value, cultivars Sariaso16 and Ponta Negra had similar crude protein concentrations (ranging from 4.1 to 5.4%), and cowpea cultivar KVx745-11P haulms had greater crude protein (ranging from 16.9 to 20.3%). The use of Ponta Negra and KVx745-11P and Sariaso16 and KVx745-11P under intercropping is likely to optimize grain and quality fodder production for crop-livestock farmers in the North Sudan zone

Guide for Regional Integrated Assessments: Handbook of Methods and Procedures, Version 5.1

The purpose of this handbook is to describe recommended methods for a trans-disciplinary, systems-based approach for regional-scale (local to national scale) integrated assessment of agricultural systems under future climate, bio-physical and socio-economic conditions. An earlier version of this Handbook was developed and used by several AgMIP Regional Research Teams (RRTs) in Sub-Saharan Africa (SSA) and South Asia (SA)(AgMIP handbook version 4.2, www.agmip.org/regional-integrated-assessments-handbook/). In contrast to the earlier version, which was written specifically to guide a consistent set of integrated assessments across SSA and SA, this version is intended to be more generic such that the methods can be applied to any region globally. These assessments are the regional manifestation of research activities described by AgMIP in its online protocols document (available at www.agmip.org). AgMIP Protocols were created to guide climate, crop modeling, economics, and information technology components of its projects

Do maize crop models catch the impact of future [CO2] on maize yield and water use?

Do maize crop models catch the impact of future [CO2] on maize yield and water use?. iCROPM2016 International Crop Modelling Symposiu