Stochastic simulation of droughts. Part 2: regional droughts Export

@article{citeulike:1380768, abstract = {In Part 1 we demonstrated the applicability of stochastic models to predicting the characteristics of point drought events within any planning period by means of a case study (Mohan S, Sahoo PK (2007) Hydrological Processes 21: this issue). In addition, studies on regional droughts are important in the context of regional level planning and evolving management strategies. The small number of drought events from a particular streamflow or rainfall series, when subjected to statistical analysis in order to predict future occurrences, produces results that are not very reliable. To overcome this difficulty, we propose using a long sequence of synthetically generated annual rainfall series at various rain-gauge stations of a region, and multiyear regional droughts were derived from both historic and generated series. The key parameters for a successful regional multiyear drought study are the critical area ratio and the critical level, and the area affected by the drought can be ascertained using these parameters. The important regional drought parameters were determined and their suitable probability distributions were arrived at by studying a total of nine possible probability models; these models can be used in predicting the longest regional drought duration and the greatest regional drought severity with a given return period. The effect of change of critical parameters on the regional drought parameters is also studied and reported. Copyright {\copyright} 2007 John Wiley \& Sons, Ltd.}, address = {Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600036, India}, author = {Mohan, S. and Sahoo, P. K.}, citeulike-article-id = {1380768}, citeulike-linkout-0 = {http://dx.doi.org/10.1002/hyp.6653}, citeulike-linkout-1 = {http://www3.interscience.wiley.com/cgi-bin/abstract/114278096/ABSTRACT}, doi = {10.1002/hyp.6653}, journal = {Hydrological Processes}, keywords = {drought, hydrology, to-read}, number = {9999}, pages = {n/a+}, posted-at = {2007-06-12 09:00:15}, priority = {4}, title = {Stochastic simulation of droughts. Part 2: regional droughts}, url = {http://dx.doi.org/10.1002/hyp.6653}, volume = {9999}, year = {2007} }

TY - JOUR ID - citeulike:1380768 L3 - citeulike-article-id:1380768 N2 - In Part 1 we demonstrated the applicability of stochastic models to predicting the characteristics of point drought events within any planning period by means of a case study (Mohan S, Sahoo PK (2007) Hydrological Processes 21: this issue). In addition, studies on regional droughts are important in the context of regional level planning and evolving management strategies. The small number of drought events from a particular streamflow or rainfall series, when subjected to statistical analysis in order to predict future occurrences, produces results that are not very reliable. To overcome this difficulty, we propose using a long sequence of synthetically generated annual rainfall series at various rain-gauge stations of a region, and multiyear regional droughts were derived from both historic and generated series. The key parameters for a successful regional multiyear drought study are the critical area ratio and the critical level, and the area affected by the drought can be ascertained using these parameters. The important regional drought parameters were determined and their suitable probability distributions were arrived at by studying a total of nine possible probability models; these models can be used in predicting the longest regional drought duration and the greatest regional drought severity with a given return period. The effect of change of critical parameters on the regional drought parameters is also studied and reported. Copyright © 2007 John Wiley & Sons, Ltd. IS - 9999 JF - Hydrological Processes AD - Department of Civil Engineering, Indian Institute of Technology Madras, Chennai 600036, India TI - Stochastic simulation of droughts. Part 2: regional droughts VL - 9999 SP - n/a KW - drought KW - hydrology KW - to-read AU - Mohan, S AU - Sahoo, PK PY - 2007/// UR - http://dx.doi.org/10.1002/hyp.6653 ER -