Drought is a water related natural hazard. It is difficult to characterize drought because of its diffused nature and spatiotemporal variability. However, understanding the variability of drought characteristics such as severity, frequency, duration, and spatial extent is critical in drought mitigation and planning. Impact of drought on agriculture, water supply, and energy sectors has been long-recognized. The current understanding of drought and its impact is limited due to its complex characteristics and ways in which it impacts various sectors. This study focuses on two important aspects of drought: variability of drought characteristics across different spatial scales, and impact of droughts on crop yield and groundwater. Two drought indices, one integrating severity and spatial coverage, and also taking into account the type of specific crops, were investigated for county level use. The developed indices were used in studying drought at the county level, and its impact on crop yields. These indices can be used for resource allocation at the county level for drought management. Drought is reported in the United States (U.S.) for different administrative units at different spatial scales. The variation of drought characteristics across different spatial scales and scale dependence was investigated, demonstrating the importance of considering spatial scales in drought management. A methodology is proposed to quantify the uncertainty in reported values of drought indices using geostatistical tools. The uncertainty was found to increase with increasing spatial scale size. Artificial Neural Network and regression methods were used to model the impact of drought on crop yield and groundwater resources. Relationships of crop yields and groundwater levels with drought indices were obtained. Overall, this study contributes towards understanding of the spatial variation of drought characteristics across different spatial scales, and the impact of drought on crop yields and groundwater levels.