Journal ArticleDOI
Stochastic renewal model of low-flow streamflow sequences
Hugo A. Loáiciga,Roy B. Leipnik +1 more
- Vol. 10, Iss: 1, pp 65-85
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In this article, it is shown that runs of low-flow annual streamflow in a coastal semi-arid basin of Central California can be adequately modelled by renewal theory.Abstract:
It is shown that runs of low-flow annual streamflow in a coastal semiarid basin of Central California can be adequately modelled by renewal theory. For example, runs of below-median annual streamflows are shown to follow a geometric distribution. The elapsed time between runs of below-median streamflow are geometrically distributed also. The sum of these two independently distributed geometric time variables defines the renewal time elapsing between the initiation of a low-flow run and the next one. The probability distribution of the renewal time is then derived from first principles, ultimately leading to the distribution of the number of low-flow runs in a specified time period, the expected number of low-flow runs, the risk of drought, and other important probabilistic indicators of low-flow. The authors argue that if one identifies drought threat with the occurrence of multiyear low-flow runs, as it is done by water supply managers in the study area, then our renewal model provides a number of interesting results concerning drought threat in areas historically subject to inclement, dry, climate. A 430-year long annual streamflow time series reconstructed by tree-ring analysis serves as the basis for testing our renewal model of low-flow sequences.read more
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Journal ArticleDOI
A review of drought concepts
Ashok K. Mishra,Vijay P. Singh +1 more
TL;DR: In this paper, the authors provide a review of fundamental concepts of drought, classification of droughts, drought indices, historical Droughts using paleoclimatic studies, and the relation between DAs and large scale climate indices.
Journal ArticleDOI
Drought modeling-A review
Ashok K. Mishra,Vijay P. Singh +1 more
TL;DR: In this paper, Mishra et al. reviewed different methodologies used for drought modeling, which include drought forecasting, probability based modeling, spatio-temporal analysis, use of Global Climate Models (GCMs) for drought scenarios, land data assimilation systems for drought modelling, and drought planning.
Journal ArticleDOI
Fitting Drought Duration and Severity with Two-Dimensional Copulas
TL;DR: In this paper, two separate maximum likelihood estimations of univariate marginal distributions are performed first, then followed by a maximization of the bivariate likelihood as a function of the dependence parameters.
Journal ArticleDOI
Drought forecasting using stochastic models
Ashok K. Mishra,V. R. Desai +1 more
TL;DR: In this article, linear stochastic models known as ARIMA and multiplicative Seasonal Autoregressive Integrated Moving Average (SARIMA) models were used to forecast droughts based on the procedure of model development.
Journal ArticleDOI
Performance of conceptual rainfall‐runoff models in low‐yielding ephemeral catchments
TL;DR: In this article, three conceptual rainfall runoff models are assessed in three low-yielding, emphemeral streams over a 10-year period, and the models are a simple conceptual model, Generalized Surface inFiltration Baseflow (GSFB), a hybrid metric/conceptual model, Identification of Hydrographs and Components from Rainfall, Evaporation and Streamflow data (IHACRES), and a complex conceptual model (LASCAM; 22 parameters).
References
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An introduction to probability theory
TL;DR: The authors introduce probability theory for both advanced undergraduate students of statistics and scientists in related fields, drawing on real applications in the physical and biological sciences, and make probability exciting." -Journal of the American Statistical Association