Author
David Roncayolo
Bio: David Roncayolo is an academic researcher from University of Arizona. The author has contributed to research in topics: Precipitation & Drainage basin. The author has an hindex of 1, co-authored 1 publications receiving 54 citations.
Papers
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TL;DR: In this paper, the authors analyzed the linkages between large-scale climate patterns and regional precipitation variability, in particular the interannual variation of seasonal precipitation in the Colorado River Basin.
57 citations
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24 Feb 2011TL;DR: The Global River Database as mentioned in this paper is a collection of river data from North and Central America, South America, Europe, Africa, Asia, and Oceania with a focus on flooding and erosion.
Abstract: Foreword 1. Introduction 2. Runoff, erosion and delivery to the coastal ocean 3. Temporal variations 4. Human impacts Appendices. Global River Database: Appendix A: North and Central America Appendix B: South America Appendix C: Europe Appendix D: Africa Appendix E: Eurasia Appendix F: Asia Appendix G: Oceania References Index.
1,046 citations
TL;DR: In this article, a Groundwater Resource Index (GRI) is presented as a reliable tool useful in a multi-analysis approach for monitoring and forecasting drought conditions, which is derived from a simple distributed water balance model, and has been tested in a Mediterranean region, characterized by different geo-lithological conditions mainly affecting the summer hydrologic response of the catchments to winter precipitation.
165 citations
TL;DR: In this article, loglinear models were fitted to drought class transitions derived from Standardized Precipitation Index (SPI) time series computed in a 12-month time scale, and results of three-dimensional loglinear modeling present good results when comparing predicted and observed drought classes with 1 and 2 months lead for those 14 sites.
157 citations
TL;DR: In this paper, the authors used the Standard Precipitation Index (SPI) to track drought and assess the impact of rainfall on shallow groundwater levels in three selected irrigation areas of the Murray-Darling Basin in Australia.
Abstract: The Standard Precipitation Index (SPI) is employed to track drought and assess the impact of rainfall on shallow groundwater levels in three selected irrigation areas of the Murray-Darling Basin in Australia. The continuous SPI method can provide better means of quantifying rainfall variability and correlating it with changes of shallow watertable levels since it is based on continuous statistical functions comparing rainfall variability over the entire rainfall record. Drought analysis in the Australian irrigation areas using SPI indicates that the recent 2000–2006 drought is not the worst drought that has occurred in the recorded history, however if the current low rainfall pattern continues, it would be one of the most prolonged drought. The shallow groundwater fluctuations in the Murrumbidgee Irrigation Area show a very strong correlation with winter rainfall variation. The shallow piezometric levels in the Coleambally Irrigation Area show a weaker degree of correlation with the SPI due to local and regional groundwater dynamics and changes in rice water use. The groundwater levels in the Murray Irrigation Area show least correlation with the SPI, which may be attributed to improved irrigation management practices and complex nature of the groundwater recharge and discharge processes in this area. The overall results however show that the SPI correlates well with fluctuations in shallow ground water table in irrigation areas, and can also capture major drought patterns in Australia. The correlation of SPI with groundwater levels can be adopted for environmental reporting and used as a method of relating climatic impacts on watertables. Differences in piezometric response between years with similar winter and yearly SPI values can be attributed to improvement in irrigators’ management practices.
133 citations
TL;DR: In this paper, a non-stationary gamma distribution with climate indices in its location parameter as a covariate is proposed to incorporate the environmental changes in the present scenario of climate change.
88 citations