Search Results (5)

Recently, the Agricultural Policy Extender (APEX) model was enhanced with a grazing module, and the modified grazing database, APEXgraze, recommends sustainable livestock farming practices. This study developed a combinatorial deterministic approach to calibrate runoff-related parameters, assuming a normal probability distribution for each parameter. Using the calibrated APEXgraze model, the impact of grazing operations on native prairie and cropland planted with winter wheat and oats in central Oklahoma was assessed. The existing performance criteria produced four solutions with very close values for calibrating runoff at the farm outlet, exhibiting equifinality. The calibrated results showed that runoff representations had coefficients of determination and Nash–Sutcliffe efficiencies >0.6 in both watersheds, irrespective of grazing operations. Because of non-unique solutions, the key parameter settings revealed different metrics yielding different response variables. Based on the least objective function value, the behavior of watersheds under different management and grazing intensities was compared. Model simulations indicated significantly reduced water yield, deep percolation, sediment yield, phosphorus and nitrogen loadings, and plant temperature stress after imposing grazing, particularly in native prairies, as compared to croplands. Differences in response variables were attributed to the intensity of tillage and grazing activities. As expected, grazing reduced forage yields in native prairies and increased crop grain yields in cropland. The use of a combinatorial deterministic approach to calibrating parameters offers several new research benefits when developing farm management models and quantifying sensitive parameters and uncertainties that recommend optimal farm management strategies under different climate and management conditions. Full article

Frequent and prolonged droughts challenge groundwater sustainability in California but managing aquifer recharge can help to partially offset groundwater overdraft. Here, we use managed aquifer recharge (MAR) to examine potential benefits of adding an artificial recharge facility downstream from California’s Lower American River Basin, in part to prepare for drought. We use a statewide hydroeconomic model, CALVIN, which integrates hydrology, the economics of water scarcity cost and operations, environmental flow requirements, and other operational constraints, and allocates water monthly to minimize total scarcity and operating costs. This study considers a recharge facility with unconstrained and constrained flows. The results show that adding a recharge facility increases groundwater storage, reduces groundwater overdraft, and increases hydropower without substantially impacting environmental flows. Further, artificial recharge adds economic benefits by (1) reducing the combined costs of water shortage and surface water storage and (2) by increasing hydropower revenue. This study provides a benchmark tool to evaluate the economic feasibility and water supply reliability impacts of artificial recharge in California. Full article

Strawberry is a high value and labor-intensive specialty crop in California. The three major fruit production areas on the Central Coast complement each other in producing fruits almost throughout the year. Forecasting strawberry yield with some lead time can help growers plan for required and often limited human resources and aid in making strategic business decisions. The objectives of this paper were to investigate the correlation among various weather parameters related with strawberry yield at the field level and to evaluate yield forecasts using the predictive principal component regression (PPCR) and two machine-learning techniques: (a) a single layer neural network (NN) and (b) generic random forest (RF). The meteorological parameters were a combination of the sensor data measured in the strawberry field, meteorological data obtained from the nearest weather station, and calculated agroclimatic indices such as chill hours. The correlation analysis showed that all of the parameters were significantly correlated with strawberry yield and provided the potential to develop weekly yield forecast models. In general, the machine learning technique showed better skills in predicting strawberry yields when compared to the principal component regression. More specifically, the NN provided the most skills in forecasting strawberry yield. While observations of one growing season are capable of forecasting crop yield with reasonable skills, more efforts are needed to validate this approach in various fields in the region. Full article

In California, a significant percentage of the pistachio acreage is in the San Joaquin Valley on saline and saline-sodic soils. However, irrigation management practices in commercial pistachio production are based on water-use information developed nearly two decades ago from experiments conducted in non-saline orchards sprinkler-irrigated with good quality water. No information is currently available that quantify the effect of salinity or combined salinity and sodicity on water use of micro-irrigated pistachio orchards, even though such information would help growers schedule irrigations and control soil salinity through leaching. To fill this gap, a field research study was conducted in 2016 and 2017 to measure the actual evapotranspiration (ETa) from commercial pistachio orchards grown on non-saline and saline-sodic soils in the southern portion of the San Joaquin Valley of California. The study aimed at investigating the functional relations between soil salinity/sodicity and tree performance, and understanding the mechanisms regulating water-use reduction under saline and saline-sodic conditions. Pistachio ETa was measured with the residual of energy balance method using a combination of surface renewal and eddy covariance equipment. Saline and saline-sodic conditions in the soil adversely affected tree performance with different intensity. The analysis of field data showed that ETa, light interception by the tree canopy, and nut yield were highly and linearly related (r² > 0.9). Moving from non-saline to saline and saline-sodic conditions, the canopy light interception decreased from 75% (non-saline) to around 50% (saline) and 30% (saline-sodic), and ETa decreased by 32% to 46% relative to the non-saline orchard. In saline-sodic soils, the nut yield resulted around 50% lower than that of non-saline orchard. A statistical analysis performed on the correlations between soil physical-chemical parameters and selected tree performance indicators (ETa, light interception, and nut yield) revealed that the sodium adsorption ratio (SAR) adversely affected tree performance more than the soil electrical conductivity (ECe). Results suggest that secondary effects of sodicity (i.e., degradation of soil structure, possibly leading to poor soil aeration and root hypoxia) might have had a stronger impact on pistachio performance than did salinity in the long term. The information presented in this paper can help pistachio growers and farm managers better tailor irrigation water allocation and management to site-specific orchard conditions (e.g., canopy features and soil-water salinity/sodicity), and potentially lead to water and energy savings through improved irrigation management practices. Full article

California is a global leader in the agricultural sector and produces more than 400 types of commodities. The state produces over a third of the country’s vegetables and two-thirds of its fruits and nuts. Despite being highly productive, current and future climate change poses many challenges to the agricultural sector. This paper provides a summary of the current state of knowledge on historical and future trends in climate and their impacts on California agriculture. We present a synthesis of climate change impacts on California agriculture in the context of: (1) historic trends and projected changes in temperature, precipitation, snowpack, heat waves, drought, and flood events; and (2) consequent impacts on crop yields, chill hours, pests and diseases, and agricultural vulnerability to climate risks. Finally, we highlight important findings and directions for future research and implementation. The detailed review presented in this paper provides sufficient evidence that the climate in California has changed significantly and is expected to continue changing in the future, and justifies the urgency and importance of enhancing the adaptive capacity of agriculture and reducing vulnerability to climate change. Since agriculture in California is very diverse and each crop responds to climate differently, climate adaptation research should be locally focused along with effective stakeholder engagement and systematic outreach efforts for effective adoption and implementation. The expected readership of this paper includes local stakeholders, researchers, state and national agencies, and international communities interested in learning about climate change and California’s agriculture. Full article