Search Results (20)

Chinese cabbage (Brassica rapa) is one of the most important fall vegetables in South Korea. Recently, cabbage yields fluctuated due to climate change, leading to an unstable supply and increased prices. Additionally, raised temperatures led to increased beet armyworm (Spodoptera exigua) populations, resulting in greater plant damage. In this study, the Agricultural Policy/Environmental Extender (APEX) model was employed to develop the cabbage growth model. To enhance model accuracy, 4 years of field data collected from multiple locations in South Korea were utilized for model validation and calibration. The model goodness of fit tests revealed R² values between 0.9485 and 0.9873. Two different cabbage models, representing the physiological characteristics of common varieties cultivated in Korea, were applied to assess growth patterns under two distinct climate change scenarios, SSP245 and SSP585. A larval duration prediction model was formulated using previous field data. Under future climate conditions, simulation results indicate that as temperatures rise, Chinese cabbage yields will likely decrease continually, with increasing plant damage from insects. The modeling results can help farmers to control and manage crop insect pests under varying environmental conditions. Full article

Irrigation plays a vital role in many agricultural crop production regions. Drainage water recycling (DWR) is a popular irrigation water management system that collects excess water drained from cropland fields and stores it in on-site reservoirs for reuse. The efficacy of these systems varies by location, climate, irrigation frequency, and crop demands. Simulating this system would be beneficial for assessing the impact of water and land management practices on agriculture and natural resources. This study presents the development of computational algorithms for DWR simulation with the Agricultural Policy Environmental eXtender (APEX) model, along with the results for 39 testing sites where both reservoir and drainage systems are adopted. Simulating a DWR system with the revised reservoir module, the APEX model simulates irrigation water reuse ranging between 29% and 93%; sediment reduction of around 66%; nitrogen loss reduction of 23% and 73% for the mineral and organic forms, respectively; and phosphorus loss reduction of 22% and 79% for the soluble and sediment-transported forms, respectively. In conclusion, the results provided by the APEX model for sediment loss reduction align with field data, but discrepancies for nitrogen and phosphorus losses emerged from this test. Full article

Wheat offers winter forage for cattle grazing and is one of the most valuable cash crops in Texas. In this study, we evaluate the impacts of climate change projections on winter wheat grain yields in five major wheat producing counties in Texas (Deaf Smith, Ochiltree, Hansford, Moore, and Parmer). For this purpose, extant soil and climate data were utilized in conjunction with Agricultural Policy Environmental eXtender (APEX) and Coupled Model Intercomparison Project—Phase 5 (CMIP 5) climate projections to determine the most reasonable future trajectory of Texas winter wheat yields. The results indicate that Deaf Smith and Parmer counties are projected to experience the greatest yield decrease, 33.33%, about 696 kg/ha under the CMIP5 RCP4.5 (Texas projected temperature increase between 2.2 and 3.3 °C) 2046–2070 scenario compared to a 1981–2017 baseline. The maximum percentage yield increase was noticed in Ochiltree County under the CMIP5 RCP8.5 2071–2095 scenario, with an 84.2% (about 1857 kg/ha) yield increase compared to the 1981–2017 baseline. Parmer County is projected to experience the greatest yield decrease of 20%, about 348 kg/ha, under the RCP4.5 2046–2070 scenario when compared to the 1981–2005 baseline. The maximum percentage yield increase is projected for Ochiltree County—a 105.9% increase, about 2089 kg/ha—under the RCP8.5 2071–2095 scenario when compared to the 1981–2005 baseline. In general, with few exceptions, winter wheat yields are projected to rise under the projected climate scenarios. Full article

While the ecological benefits of no-till are largely indisputable, the economic impacts are less certain, and the latter may be partly to blame for lower-than-expected adoption of no-till. In this study, we contribute to a better understanding of the ecosystem and farm-level economic impacts of no-till, with Buchanan County in the northeastern region of the U.S. State of Iowa as the backdrop due to previously established data and model validation efforts in that region. Using the Agricultural Policy Environmental eXtender (APEX) and Farm Economic Model (FEM), we simulated two tillage scenarios—a conservation tillage baseline and no-till—for continuous corn and corn–soybean rotations in Buchanan County using gridded historical climate data. We find that no-till provides clear ecosystem benefits, except that soluble nutrient losses might actually rise. We also find that under current commodity prices for corn and soybeans, no-till is not as profitable as the conservation tillage baseline. For no-till to be at least as profitable as the baseline under current commodity prices, the yield penalty associated with no-till cannot be higher than 1.5% for corn and 0.8% for soybeans, or similar combinations that entail a revenue penalty of about $24,000 for an 809-hectare continuous corn or corn–soybean operation. Given the simulated yield penalties associated with no-till, corn and soybean prices would have to be substantially lower in order for no-till to break even. Consequently, incentives for conservation practice implementation may need to be tied to commodity prices and yield penalties in order to elicit greater adoption rates. Full article

The Agricultural Policy Environmental eXtender (APEX) model is used to study how different agricultural practices, such as fertilizing, irrigation, and tillage, would affect water quality and runoff in the Lake Karla watershed (Central Greece). The model was calibrated for the potential evapotranspiration with satisfactory results for the period 1980–2008 and for the yields of the main crops grown in the region (cotton, maize, and wheat) from 1980–2015. Full article

Nonpoint source pollution from cultivated croplands has often been associated with downstream water quality impairment in various watersheds. Given projected changes in global climate patterns, this study contributes to the existing literature by elucidating the impacts of climate projections on edge-of-field surface runoff and sediment and nutrient losses. We apply a well-tested ecohydrological model, Agricultural Policy Environmental eXtender (APEX), to continuous corn and corn–soybean fields in Buchanan County, Iowa, using climate scenarios developed from three well-known representative concentration pathway (RCP) climate projections: RCP 2.6, RCP 4.5, and RCP 8.5. Our results indicate that there will be a moderate to substantial increase in surface runoff, sediment, and nutrient losses depending upon the reference point of comparison (baseline scenario) and upon which climate scenario actually materializes. However, regardless of which climate scenario materializes and regardless of the baseline for comparison, soluble nitrogen losses are bound to increase, the magnitude depending upon the climate scenario. We find also that nutrient losses will be higher from continuous corn fields than from corn–soybean fields, given the tillage practices implemented on corn versus soybeans in the study area. Similarly, we find that nutrient losses may be higher from fields that receive manure than fields that receive only inorganic fertilizer, though this latter finding may be predicated upon the specific nutrient application rates utilized. Full article

Droughts reduce crop yields, which translates to reduced nutrient uptake or removal from the soil. Under such conditions, residual plant nutrients such as nitrogen (N) and phosphorus (P) can be carried over for subsequent crops. We applied the Agricultural Policy Environmental eXtender (APEX) model to simulate continuous corn (Zea mays L.)/soybean (Glycine max [L.] Merr.) rotations on 3703 farm fields within the Upper Mississippi River Basin (UMRB) over a 47-year timescale: 1960 to 2006. We used the Standardized Precipitation Index (PSI) to identify the drought years between 1960 to 2006, following which we evaluated potential drought-induced carryover N and P nutrients in corn/soybean rotations relative to near normal and very to extremely wet years. Overall, drought reduced N uptake, total N losses, N mineralization and N fixation, the main driver of the soybean carryover N. Given the high cost of fertilizers and concerns over nutrient loss impacts on offsite water quality, farmers are compelled to account for every plant nutrient that is already in the soil. Information from this study could be applied to develop optimal N and P recommendations after droughts, while identification of region-wide potential reductions in N and P applications has implications for conservation efforts aimed at minimizing environmental loading and associated water quality concerns. Full article

The Agricultural Policy/Environmental eXtender (APEX) model has been used for farm/small watershed management, and the ArcAPEX interface was developed using the ArcGIS extension. However, the interface requires a paid license and limits dynamic applications that reflect various agricultural farming practices. In this study, a novel APEX model interface using Quantum GIS, the QAPEX analysis system, was developed by incorporating open-source-based GIS software for the simulation of water quality impacts of various best management practices reflecting local farming activities. The watershed delineation process running on the QAPEX interface is more flexible than that on the ArcAPEX interface, which renders simulations on hydrology and water quality with considerable precision. The newly developed system can be used to visually interpret simulation results (e.g., flow and load duration curve functions). Therefore, the open-source-based model can be used to derive data for sustainable agricultural policies, with a focus on the field-level application of management practices. Full article

With population growth and resource depletion, maximizing the efficiency of soybean (Glycine max [L.] Merr.) and rice (Oryza sativa L.) cropping systems is urgently needed. The goal of this study was to shed light on precise irrigation amounts and optimal agronomic practices via simulating rice–rice and soybean–rice crop rotations in the Agricultural Policy/Environmental eXtender (APEX) model. The APEX model was calibrated using observations from five fields under soybean–rice rotation in Arkansas from 2017 to 2019 and remote sensing leaf area index (LAI) values to assess modeled vegetation growth. Different irrigation practices were assessed, including conventional flooding (CVF), known as cascade, multiple inlet rice irrigation with polypipe (MIRI), and furrow irrigation (FIR). The amount of water used differed between fields, following each field’s measured or estimated input. Moreover, fields were managed with either continuous flooding (CF) or alternate wetting and drying (AWD) irrigation. Two 20-year scenarios were simulated to test yield changes: (1) between rice–rice and soybean–rice rotation and (2) under reduced irrigation amounts. After calibration with crop yield and LAI, the modeled LAI correlated to the observations with R² values greater than 0.66, and the percent bias (PBIAS) values were within 32%. The PBIAS and percent difference for modeled versus observed yield were within 2.5% for rice and 15% for soybean. Contrary to expectation, the rice–rice and soybean–rice rotation yields were not statistically significant. The results of the reduced irrigation scenario differed by field, but reducing irrigation beyond 20% from the original amount input by the farmers significantly reduced yields in all fields, except for one field that was over-irrigated. Full article

This research aims to assess the impact of climate change on water balance components in irrigated paddy cultivation. The APEX-Paddy model, which is the modified version of the APEX (Agricultural Policy/Environmental eXtender) model for paddy ecosystems, was used to evaluate the paddy water balance components considering future climate scenarios. The bias-corrected future projections of climate data from 29 GCMs (General Circulation Models) were applied to the APEX-Paddy model simulation. The study area (Jeonju station) forecasts generally show increasing patterns in rainfall, maximum temperature, and minimum temperature with a rate of up to 23%, 27%, and 45%, respectively. The hydrological simulations suggest over-proportional runoff–rainfall and under-proportional percolation and deep-percolation–rainfall relationships for the modeled climate scenarios. Climate change scenarios showed that the evapotranspiration amount was estimated to decrease compared to the baseline period (1976–2005). The evaporation was likely to increase by 0.12%, 2.21%, and 7.81% during the 2010s, 2040s, and 2070s, respectively under Representative Concentration Pathway (RCP)8.5, due to the increase in temperature. The change in evaporation was more pronounced in RCP8.5 than the RCP4.5 scenario. The transpiration is expected to reduce by 2.30% and 12.62% by the end of the century (the 2070s) under RCP4.5 and RCP8.5, respectively, due to increased CO₂ concentration. The irrigation water demand is generally expected to increase over time in the future under both climate scenarios. Compared to the baseline, the most significant change is expected to increase in the 2040s by 3.21% under RCP8.5, while the lowest increase was found by 0.36% in 2010s under RCP4.5. The increment of irrigation does not show a significant difference; the rate of increase in the irrigation was found to be greater RCP8.5 than RCP4.5 except in the 2070s. The findings of this study can play a significant role as the basis for evaluating the vulnerability of rice production concerning water management against climate change. Full article

Intensive agriculture causes nutrient leaching and accelerates erosion processes, which threatens the good quality status of surface waters, as proposed by the European Union (EU) Water Framework Directive. The purpose of this study was to define the impact of two alternative agricultural land-use change scenarios defined in a Municipal Spatial Plan on surface water quality by using the Agricultural Policy/Environmental eXtender (APEX) model. As experimental area, we chose a small Kožbanjšček stream catchment (1464 ha) situated in the Goriška Brda region in Slovenia. The area, due to favorable conditions for vineyards, is facing increasing deforestation. The change of 66.3 ha of forests to vineyards would increase the sediment, nitrate, and phosphorus loads in the stream by 24.8%, 17.1%, and 10.7%, respectively. With the implementation of vegetative buffer strips as a mitigation measure of the current situation, we could reduce the sediment, nitrate, and phosphorus loads by 17.9%, 11.1%, and 3.1%, respectively, while a combination of the two land-use change scenarios would result in a slight increase of the above-mentioned loads, corresponding to 0.61%, 2.1%, and 6.6%, respectively, compared to the baseline situation. The results confirm that, as we can increase pollution levels with deforestation, we can also reduce water pollution by choosing proper types of land management measures. Full article

Cultivation of highly salt-tolerant plants (i.e., halophytes), may provide a viable alternative to increase productivity compared to conventional salt-sensitive crops, increasing the economic potential of salt-affected lands that comprise ~20% of irrigated lands worldwide. In this study the Agricultural Policy/Environmental eXtender (APEX) model was adapted to simulate growth of the halophyte quinoa, along with salt dynamics in the plant-soil-water system. Model modifications included salt uptake and salt stress functions formulated using greenhouse data. Data from a field site were used to further parameterize and calibrate the model. Initial simulation results were promising, but differences between simulated and observed soil salinity and plant salt values during the growing season in the calibration suggest that additional improvements to salt uptake and soil salinity algorithms are needed. To demonstrate utility of the modified APEX model, six scenarios were run to estimate quinoa biomass production and soil salinity with different irrigation managements and salinities. Simulated annual biomass was sensitive to soil moisture, and root zone salinity increased in all scenarios. Further experiments are needed to improve understanding of crop salt uptake dynamics and stress sensitivities so that future model updates and simulations better represent salt dynamics in plants and soils in agricultural settings. Full article

The conservation agriculture production system (CAPS) approach with drip irrigation has proven to have the potential to improve water management and food production in Ethiopia. A method of scaling-up crop yield under CAPS with drip irrigation is developed by integrating a biophysical model: APEX (agricultural policy environmental eXtender), and a Geographic Information System (GIS)-based multi-criteria evaluation (MCE) technique. Topography, land use, proximity to road networks, and population density were considered in identifying potentially irrigable land. Weather and soil texture data were used to delineate unique climate zones with similar soil properties for crop yield simulation using well-calibrated crop model parameters. Crops water demand for the cropping periods was used to determine groundwater potential for irrigation. The calibrated APEX crop model was then used to predict crop yield across the different climatic and soil zones. The MCE technique identified about 18.7 Mha of land (16.7% of the total landmass) as irrigable land in Ethiopia. Oromia has the highest irrigable land in the nation (35.4% of the irrigable land) when compared to other regional states. Groundwater could supply a significant amount of the irrigable land for dry season production under CAPS with drip irrigation for the various vegetables tested at the experimental sites with about 2.3 Mha, 3.5 Mha, 1.6 Mha, and 1.4 Mha of the irrigable land available to produce garlic, onion, cabbage, and tomato, respectively. When comparing regional states, Oromia had the highest groundwater potential (40.9% of total potential) followed by Amhara (20%) and Southern Nations, Nationalities, and Peoples (16%). CAPS with drip irrigation significantly increased groundwater potential for irrigation when compared to CTPS (conventional tillage production system) with traditional irrigation practice (i.e., 0.6 Mha under CTPS versus 2.2 Mha under CAPS on average). Similarly, CAPS with drip irrigation depicted significant improvement in crop productivity when compared to CTPS. APEX simulation of the average fresh vegetable yield on the irrigable land under CAPS with drip irrigation ranged from 1.8–2.8 t/ha, 1.4–2.2 t/ha, 5.5–15.7 t/ha, and 8.3–12.9 t/ha for garlic, onion, tomato, and cabbage, respectively. CAPS with drip irrigation technology could improve groundwater potential for irrigation up to five folds and intensify crop productivity by up to three to four folds across the nation. Full article

Spring peanut is a valuable alternative crop to mitigate water scarcity caused by excessive water use in conventional cropping systems in the North China Plain (NCP). In the present study, we evaluated the capability of the Agricultural Policy Environmental eXtender (APEX) model to predict spring peanut response to sowing dates and seeding rates in order to optimize sowing dates, seeding rates, and irrigation regimes. Data used for calibration and validation of the model included leaf area index (LAI), aboveground biomass (ABIOM), and pod yield data collected from a field experiment of nine sowing dates and seeding rate combinations conducted from 2017 to 2018. The calibrated model was then used to simulate peanut yield responses to extended sowing dates (5 April to 4 June with a 5-day interval) and seeding rates (15 plants m⁻² to 50 plants m⁻² with a 5 plants m⁻² interval) using 38 years of weather data as well as yield, evapotranspiration (ET), and water stress days under different irrigation regimes (rainfed, one irrigation before planting (60 mm) or at flowering (60 mm), and two irrigation with one time before planting and one time at flowering (60 mm each time) or at pod set (60 mm each time)). Results show that the model satisfactorily simulates pod yield of peanut based on R² = 0.70, index of agreement (d value) being 0.80 and percent bias (PBIAS) values ≤4%. Moreover, the model performed reasonably well in predicting the emergence, LAI and ABIOM, with a R² = 0.86, d = 0.95 and PBIAS = 8% for LAI and R² = 0.90, d = 0.97 and PBIAS = 1% for ABIOM, respectively. Simulation results indicate that the best combination of sowing dates and seeding rates is a density of 35–40 plants m⁻² and dates during early-May to mid-May due to the influence of local climate and canopy structure to the growth and yield of peanut. Under the optimal sowing date and plant density, an irrigation depth of 60 mm during flowering gave a pod yield (5.6 t ha⁻¹) and ET (464 mm), which resulted in the highest water use efficiency (12.1 kg ha⁻¹ mm⁻¹). The APEX model is capable of assessing the effects of management practices on the growth and yield of peanut. Sowing 35–40 plants m⁻² during early-May to mid-May with 60 mm irrigation depth is the recommended agronomic practice for peanut production in the water-constrained NCP. Full article

The Agricultural Policy/Environmental eXtender (APEX) model has been widely used to assess changes in agrochemical loadings in response to conservation and management led by US Department of Agriculture (USDA). However, the existing APEX model is limited in quantification of wetland water quality functions. This study improved the current model capacity to represent wetland water quality functions by addition of a new biogeochemical module into the APEX model. The performance of an enhanced APEX model was tested against five observed outgoing water quality variables (e.g., sediment, organic N, NO₃, NH₄ and PO₄) from a wetland within the Eastern Shore of Maryland. Generalized Likelihood Uncertainty Estimation (GLUE) was implemented to assess model uncertainty. The enhanced APEX model demonstrated that it could effectively represent N and P cycling within the study wetland. Although improvement of model performance was limited, the additions of wetland biogeochemical routines to the APEX model improved our understanding of inner mass exchanges within N and P cycling for the study wetland. Overall, the updated APEX model can provide policymakers and managers with improved means for assessment of benefits delivered by wetland conservation. Full article