An open-source tool for improving on-farm yield forecasting systems

IntroductionThe increased frequency of extreme climate events, many of them of rapid onset, observed in many world regions, demands the development of a crop forecasting system for hazard preparedness based on both intraseasonal and extended climate prediction. This paper presents a Fortran version of the Crop Productivity Model AquaCrop that assesses climate and soil fertility effects on yield gap, which is crucial in crop forecasting systemsMethodsFirstly, the Fortran version model - AQF outputs were compared to the latest version of AquaCrop v 6.1. The computational performance of both versions was then compared using a 100-year hypothetical experiment. Then, field experiments combining fertility and water stress on productivity were used to assess AQF model simulation. Finally, we demonstrated the applicability of this software in a crop operational forecast system.ResultsResults revealed that the Fortran version showed statistically similar results to the original version (r2 > 0.93 and RMSEn < 11%, except in one experiment) and better computational efficiency. Field data indicated that AQF simulations are in close agreement with observation.ConclusionAQF offers a version of the AquaCrop developed for time-consuming applications, such as crop forecast systems and climate change simulations over large areas and explores mitigation and adaptation actions in the face of adverse effects of future climate change

Impact of climate change on water resources and crop production in Western Nepal: Implications and adaptation strategies

Irrigation-led farming system intensification and efficient use of ground and surface water resources are currently being championed as a crucial ingredient for achieving food security and reducing poverty in Nepal. The potential scope and sustainability of irrigation interventions under current and future climates however remains poorly understood. Potential adaptation options in Western Nepal were analyzed using bias-corrected Regional Climate Model (RCM) data and the Soil and Water Assessment Tool (SWAT) model. The RCM climate change scenario suggested that average annual rainfall will increase by about 4% with occurrence of increased number and intensity of rainfall events in the winter. RCM outputs also suggested that average annual maximum temperature could decrease by 1.4 °C, and average annual minimum temperature may increase by 0.3 °C from 2021 to 2050. Similarly, average monthly streamflow volume could increase by about 65% from March–April, although it could decrease by about 10% in June. Our results highlight the tight hydrological coupling of surface and groundwater. Farmers making use of surface water for irrigation in upstream subbasins may inadvertently cause a decrease in average water availability in downstream subbasins at approximately 14%, which may result in increased need to abstract groundwater to compensate for deficits. Well-designed irrigated crop rotations that fully utilize both surface and groundwater conversely may increase groundwater levels by an average of 45 mm from 2022 to 2050, suggesting that in particular subbasins the cultivation of two crops a year may not cause long-term groundwater depletion. Modeled crop yield for the winter and spring seasons were however lower under future climate change scenarios, even with sufficient irrigation application. Lower yields were associated with shortened growing periods and high temperature stress. Irrigation intensification appears to be feasible if both surface and groundwater resources are appropriately targeted and rationally used. Conjunctive irrigation planning is required for equitable and year-round irrigation supply as neither the streamflow nor groundwater can provide full and year-round irrigation for intensified cropping systems without causing the degradation of natural resources

Improving Cereal Production in the Terai Region of Nepal: Assessment of Field Management Strategies through a Model Based Approach

Rice (Oryza sativa L.), maize (Zea mays L.) and wheat (Triticum aestivum L.) are the major cereal crops in Nepal accounting for more than 95% of cereal production in Nepal. The focus of the research are these three cereal crops grown in the Terai region of Nepal, which contributes to more than 70% of national cereal production. However, yield is reported generally low as result of low rainfall and/or fertilizer applications. For improving the cereal production in Terai, a sound and balanced management of fertilizer and water application encompassing the local limitations and needs of farmers is required. The major objective of this research is to understand the impact of inorganic fertilizer and irrigation application on the yield of the cereal crops in Terai region of Nepal. To study the crop response, the AquaCrop model was selected and fine tuned for rice, maize and wheat. The calibrated and validated AquaCrop model was used to formulate a realistic water and fertility management for the grain crops to improve and stabilize the yield. The possibility to forecast the yield with the fine-tuned and validated AquaCrop model was also investigated as an objective. Field experiments were set up in Rampur (Chitwan), taken as a representative area of Terai, for two years (2009-2011) to investigate crop response of rice, wheat and maize for different fertilizer and water treatments and to collect data for calibration and validation of AquaCrop. From field experiments, it was observed that there was a significant increase in yield of all crops with higher fertilizer application. In the dry season, the water regime played a significant role in the increase of the above ground biomass and consequently final grain yields. However, the small sample size makes such conclusion speculative; the data collected from field experiments were used for fine-tuning the non-conservative crop parameters of rice, wheat and maize in AquaCrop to the local conditions in Terai (Chitwan). The calibrated model was able to simulate accurate soil water content, canopy development, dry aboveground biomass and grain yield in fertility stressed and non-stressed fields. The fine-tuned crop parameters were used to validate AquaCrop for different water and fertilizer treatments. The AquaCrop model was able to simulate accurately the effect of the different soil fertility levels on biomass production and ultimately crop yield for different water management (rainfed and irrigated) and various climatic conditions. The statistical analysis of the comparison between the observed and simulated final grain yields yielded very good Coefficients of Variation of Root Mean Squared Deviation (CV(RMSD)), Coefficients of Determination (R²) and Nash-Sutcliffe Efficiencies (EF) of respectively 0.05, 0.89 and 0.84 for rice, 0.10, 0.75 and 0.72 for wheat and 0.08, 0.97 and 0.96 for maize.A regional farmer household survey was performed to understand the local regional crop management. Analysis of the farmer household survey showed very low application of fertilizers for the grain crops. The amount of fertilizer used depended on the availability of the water. However, chemical fertilizer use was always below the National Recommended Fertilizer Dose (NRFD). The major cause of the lower use of chemical fertilizer was mainly due to an assumed negative effect (because of unbalanced use) and high costs. The amount of irrigation applied decreases as the dry season progresses. Irrigating in the dry seasons depended on the availability of groundwater.A regional soil survey was performed to determine the variation of the regional soil characteristics. Analysis of textural class, bulk density and soil organic matter (SOM) content were performed on the soil samples collected. Comparison among three pedo transfer functions showed that pedo transfer function developed by Saxton and Rawls (2006) has the lowest CV(RMSD) of 27%, and hence was chosen to determine the representative soil physical characteristics required by AquaCrop.The fine-tuned and validated AquaCrop model was used to simulate and develop different management scenarios for the Chitwan region. To reduce the simulation time, the soil was categorized into five soil classes based on the soil characteristics (total available water), which was most influential to crop yield. The analysis of the spatial variability of the rainfall and evapotranspiration in the region showed minimal variability. The climatic data from Rampur meteorological station was used to represent the Chitwan region. AquaCrop was run on the five soil classes to obtain realistic irrigation and soil fertility strategies for the region by considering the existing water availability and soil fertility constraints of the farmers. Results of the management strategies indicated that the monsoon rice yield was mainly constrained by soil fertility and can be increased with improved soil fertility management. For the crops in the dry seasons, yields were mainly constrained by water stress. The yields in the dry season can be stabilized and increased with deficit irrigation strategies. The amount of irrigation to be applied depended on the fertilizer application, so they should be managed accordingly to maximize the yield.Analysis of the ability of AquaCrop to perform simulations with 10-daily data showed that the average soil water content was well simulated and can be used to simulate the stress affecting the canopy cover and crop transpiration. However, in simulations where soil water content induced early crop senescence, the use of 10-daily rainfall data showed some discrepancy and underestimated the lower yields. Hence, 10-daily data was not considered for use in yield forecast. The simulations with historical daily data to predict the yield of maize within the season showed some promising results. The update of the climatic data as the season progresses allowed AquaCrop to predict the possibility of crop failure already by the mid of season. The process for yield prediction can be used for crops with similar drought sensitive stages. This willallow the farmer to react and the government to prepare for yield failure.status: publishe

Strategies to improve cereal production in the Terai region (Nepal) during dry season: simulations with aquacrop

Strategies to improve cereal yield in Terai (Nepal) were developed with AquaCrop by simulating different scenarios of irrigation and fertilizer management for three dominant soil types with 30 years historical climatic data. Farmers yield increased from 25 to 115% depending on soil type, fertility and irrigation level. Considering the low availability of irrigation water and fertilizers, use of deficit irrigation with 1/4 of the net irrigation requirement (Inet) and fertilizer application below 50% of national recommended fertilizer dose (NRFD) was regarded as the most suitable strategy. For fertilizer applications above 50% of NRFD, deficit irrigation with 1/3 Inet is recommended.status: publishe

Cereal yield stabilization in Terai (Nepal) by water and soil fertility management modeling

Rice (Oryza sativa L.), maize (Zea mays L.) and wheat (Triticum aestivum L.) are the major cereals cultivated in the Terai region of Nepal. In the region, agriculture is mainly rainfed and fertilizer applications are low. In this study, water and soil fertility management was modeled with the FAO AquaCrop model. For the model calibration and validation, field trials were set up during two years in Rampur, a representative area of Terai at Chitwan. The statistical comparison between the simulated and observed yield of the validation fields resulted in an average RRMSE (relative root mean squared error), R2 (coefficient of determination) and EF (Nash–Sutcliffe efficiency) of 0.05, 0.94 and 0.90 for rice, 0.08, 0.90 and 0.87 for wheat and 0.08, 0.97 and 0.96 for maize, respectively. The validated model was subsequently used to simulate different scenarios with 30 years of historical climatic data to determine realistic soil fertility and water management strategies for increasing crop yields. For the monsoon crops (rice and maize) that benefit from abundant rainfall, only an improved fertility management could increase crop yields by up to 65% and 58%, for rice and maize, respectively. During the winter and spring, seasons with lesser rainfall, crops were severely under-watered in absence of irrigation. For winter wheat, application of deficit irrigation increased yield by up to 67–197% compared to the rainfed crop yield for different fertility levels. For spring maize, full irrigation with increased fertilizer application was recommended to increase the yield. However, by considering the water scarcity in the region, application of deficit irrigation resulted in good and stable yields under low to moderate fertility and always resulted in a better water productivity than fully irrigated crops. It was demonstrated that increasing soil fertility of the winter and spring crops without considering irrigation could sometimes result in crop failure, instead of a yield increase. For fertilizer applications above 50% of the national recommended fertilizer applications, full irrigations are recommended for best yield results for winter and spring crops.status: publishe

Reinvigorating food production in Nepal: Strengthening the irrigation–agriculture nexus

Nepal is increasingly dependent on food imports, which rose by about 60% between 2015 and 2020, according to foreign trade statistics. This trend threatens Nepal’s agricultural future and undermines food security – an undesirable outcome for a country already classified as having a ‘moderate level of hunger’ in the 2022 Global Hunger Index

Tapping irrigation potential: Exploring challenges and solutions in Western Nepal

Irrigating farmland in Nepal increases crop yields, helping to reduce the country’s trade gap for agricultural commodities, and build a more food-secure economy. But despite having plenty of water available – 225 billion cubic meters each year – Nepal has a long way to go in tapping its resources to the full

Yield response of sugar beets to water stress under Western European conditions

The average yield of sugar beet has almost doubled within the last 30 years. With the raise in average yields and the increase in sensitivity to water stress of sugar beets, the yield response factor (Ky) derived by Doorenbos and Kassam (1979) needs an update. In this article, the soil water balance model BUDGET (Raes et al., 2006) was calibrated and validated to obtain correct estimations of the evapotranspiration deficit (1-ETa/ETc, where ETa=actual crop evapotranspiration and ETc=maximum crop evapotranspiration under standard conditions) of sugar beets in two locations in France. Datasets of observed soil water contents of several years and different irrigation treatments were used. The simulated evapotranspiration deficits and observed yields were used to derive a seasonal Ky. The obtained linear and polynomial yield response relation between observed yield decline and evapotranspiration deficit showed a high goodness-of-fit. The coefficient of determination (R2)=0.83, the Nash-Sutcliffe efficiency (EF)=0.79, the relative root mean squared error (RRMSE)=0.26 for linear; the coefficient of determination (R2)=0.85, the Nash-Sutcliffe efficiency (EF)=0.79, the relative root mean squared error (RRMSE)=0.25 for polynomial). The results suggested a more pronounced response of sugar beet to water stress in Europe as compared to the values previously reported by Doorenbos and Kassam (1979). The comparison between the observed and simulated yields (with the updated Ky) for another site in France confirmed the findings.Ky Drought stress Crop water productivity BUDGET Soil water balance Model