Navaratnam Leelaruban (Leelan) is a Ph.D. student in the Department of Civil and Environmental Engineering at North Dakota State University. He received a MS degree in Civil Engineering with water resources emphasis at North Dakota State University (2011), and a BS degree in Civil Engineering in University of Peradeniya, Sri Lanka (2007). His current research focuses on modeling droughts and its impact.
A Study of the Spatial and Temporal Characteristics of Drought and its Impact in North Dakota
Fellow: Navaratnam Leelaruban
Advisor: G. Padmanabhan, Ph.D., Professor, Department of Civil and Environmental Engineering, North Dakota State University
Co-Advisor: Adnan Akuz. Ph.D., Assistant Professor, Department of Soil Science and State Climatologist, North Dakota State University
Degree Progress: Ph.D. in Civil and Environmental Engineering expected graduation in Fall 2015.
Drought is a complex phenomenon, and difficult to accurately describe because of its complex characteristics. It is well known that drought is a spatially and temporally varying natural hazard. Understanding drought severity, frequency, duration, and spatial extent is critical in drought mitigation and planning. It is crucial to understand how drought propagates in space and time for effective management and mitigating measures. Also, it is well known that drought significantly impacts agriculture, environment, and society. A clear understanding of drought impact on these sectors will help address planning for future droughts. Quantifying drought impact is difficult because of the complex characteristics of drought and also the impacted sectors.
Various drought indices are used to identify and monitor drought situations, and to decide the timing and level of drought responses. The most commonly used indices include (i) Palmer Drought Severity Index (PDSI) (ii) Standardized Precipitation Index (SPI) (iii) Crop Moisture Index (CMI) and (iv) U.S Drought Monitor Index. All except the last one are severity indicators and do not reflect the spatial extent of droughts. Each index has its own advantages and disadvantages from the users’ perspectives. A composite index which will reflect the severity and spatial coverage corresponding to that severity together, particularly at the county level will be useful for resource allocation for drought mitigation purposes.
It is estimated that drought costs the United States $6–8 billion annually. Drought creates stress on water sources (i.e., surface water, groundwater), and on soil moisture. This will impact water-dependent industries including agriculture, water supply, and recreation. Researchers have developed several techniques to understand the drought impact.
There is still a need for comprehensive drought study to understand the drought and its impact in North Dakota. Especially, the recent development and availability of computational tools can help develop better understanding of drought. The recent drought events in this region emphasize the need for a rigorous drought study.
A refined county-level drought Severity and Coverage index is developed for drought management based on U.S Drought Monitor (USDM) drought severity and coverage values. The spatial variation of drought severity and frequency within North Dakota are analyzed and mapped. Based on the relationship between crop yield and USDM severity coverage values a crop specific county-wide drought Index is proposed. Transition probabilities are derived for crop yield categories from state of less severe drought year to more severe drought year using Markovian process. Impact of drought on barley yield is studied using Multiple Linear Regression and Artificial Neural Network. Responses of groundwater level to drought are being investigated based on drought severity and duration.
North Dakota has experienced several drought events in the past. The impact of drought in this region has significant influence on the economy, social, and environmental sector of North Dakota. This study will analyze the characteristics and impact of drought in this region. The results of this study will be useful for state agencies, and water dependent industries to plan and manage the future drought events. In addition, this study will propose potential actions to be taken in order to improve the drought monitoring and mitigation in the state of North Dakota. Though this study focuses on the state of North Dakota, the methodologies used in this study can be adopted for other places. In general, this research will contribute to understand the propagation mechanism of drought, and assess the impact of drought on agriculture and groundwater resources using novel approaches.
Presentations:Leelaruban. N., Odabas. M., Halis Simsek, and G. Padmanabhan , 2014. Application of Artificial Neural Network to study the Barley yield under different Drought Conditions. North Central ASABE/CSBE Intersectional Meeting, March 28-29, 2014 , Brookings, SD [Podium Presentation]
Advisor: G. Padmanabhan, Ph.D., PE
Co-Advisor: Adnan Akuz. Ph.D