This article presents a sensitivity analysis of the main growing factors for wild American ginseng in North Carolina, USA. This study examines the influence and importance of ginseng's natural... Show More

This article presents a sensitivity analysis of the main growing factors for wild American ginseng in North Carolina, USA. This study examines the influence and importance of ginseng's natural growing factors in the predictive models generated through the method of weighted linear combination by conducting a sensitivity analysis over the relative importance of growing factors. By identifying these factors, government agencies can more effectively plan law enforcement activities and streamline their preservation efforts to protect this valuable species. The results of our sensitivity analysis indicate that the shade-related factors and spatial factors play very important roles in predicting suitable areas for wild American ginseng to grow in nature in the context of North Carolina. This finding implies that the proper consideration of these factors substantially enhances model predictability and consistency of predictions with real-world observations.

In eastern Arkansas, the use of surface water for crop irrigation is steadily increasing in response to declining aquifers. Effective conjunctive water management requires accurate and timely... Show More

In eastern Arkansas, the use of surface water for crop irrigation is steadily increasing in response to declining aquifers. Effective conjunctive water management requires accurate and timely information on the locations, sizes, and numbers of on-farm irrigation reservoirs. A method for remotely locating and characterizing on-farm reservoirs was developed using relative elevation and near-infrared imagery. With 62% accuracy, the method automatically identified 429 irrigation reservoirs within a 1.9-Mha area in less than an hour using an off-the-shelf laptop. Reservoirs not accurately identified (i.e., false negatives) were caused by the presence of vegetation or turbidity within the reservoirs. There were no false positive detections. This approach for identifying elevated reservoirs is applicable across the Mississippi Alluvial Plain (MAP) that encompasses over 4-Mha of irrigated cropland and other agricultural areas having low-relief.

Soil erosion is one of the most crucial land degradation problems and is considered the most critical environmental hazard worldwide. The present study uses remote sensing data integrated with the... Show More

Soil erosion is one of the most crucial land degradation problems and is considered the most critical environmental hazard worldwide. The present study uses remote sensing data integrated with the geographical information system (GIS) technique and the revised universal soil loss equation (RUSLE) model for assessing the annual average soil loss of the Digaru watershed of India for 1999 and 2020. The estimated mean gross yearly soil loss from the entire watershed was 102716 t yr-1 in 1999 and 178931.6 t yr-1 in 2020. The overall average soil loss rate increased significantly between 1999 and 2020, rising from 4.73 t—ha-1yr-1 to 8.43 t—ha-1yr-1. The sub-watersheds are prioritized as high (≥ 40 t ha−1yr−1), moderate (20–40 t ha−1yr−1), and low (<20 t ha−1yr−1) based on the spatial distribution of soil erosion. Seven sub-watersheds have been grouped under low priority, followed by seven under moderate priority and one under high priority. This study demands instant attention for soil and water conservation efforts in highly eroded watershed areas.