The authors propose a new climatic drought index: the standardized precipitation evapotranspiration index (SPEI). The SPEI is based on precipitation and temperature data, and it has the advantage of combining multiscalar character with the capacity to include the effects of temperature variability on drought assessment. The procedure to calculate the index is detailed and involves a climatic water balance, the accumulation of deficit/surplus at different time scales, and adjustment to a log-logistic probability distribution. Mathematically, the SPEI is similar to the standardized precipitation index (SPI), but it includes the role of temperature. Because the SPEI is based on a water balance, it can be compared to the self-calibrated Palmer drought severity index (sc-PDSI). Time series of the three indices were compared for a set of observatories with different climate characteristics, located in different parts of the world. Under global warming conditions, only the sc-PDSI and SPEI identified an...

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A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index

Cause, conseguenze e strategie di mitigazione Proponiamo il primo di una serie di articoli in cui affronteremo l’attuale problema dei mutamenti climatici. Presentiamo il documento redatto, votato e pubblicato dall’Ipcc - Comitato intergovernativo sui cambiamenti climatici - che illustra la sintesi delle ricerche svolte su questo tema rilevante.

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Climate Change 2007: The Physical Science Basis.

A review of drought concepts

The purpose of this paper is to provide a comprehensive presentation and interpretation of the Ensemble Kalman Filter (EnKF) and its numerical implementation. The EnKF has a large user group, and numerous publications have discussed applications and theoretical aspects of it. This paper reviews the important results from these studies and also presents new ideas and alternative interpretations which further explain the success of the EnKF. In addition to providing the theoretical framework needed for using the EnKF, there is also a focus on the algorithmic formulation and optimal numerical implementation. A program listing is given for some of the key subroutines. The paper also touches upon specific issues such as the use of nonlinear measurements, in situ profiles of temperature and salinity, and data which are available with high frequency in time. An ensemble based optimal interpolation (EnOI) scheme is presented as a cost-effective approach which may serve as an alternative to the EnKF in some applications. A fairly extensive discussion is devoted to the use of time correlated model errors and the estimation of model bias.

The Ensemble Kalman Filter: Theoretical formulation and practical implementation

The topography of a catchment has a major impact on the hydrological, geomorphological. and biological processes active in the landscape. The spatial distribution of topographic attributes can often be used as an indirect measure of the spatial variability of these processes and allows them to be mapped using relatively simple techniques. Many geographic information systems are being developed that store topographic information as the primary data for analysing water resource and biological problems. Furthermore, topography can be used to develop more physically realistic structures for hydrologic and water quality models that directly account for the impact of topography on the hydrology. Digital elevation models are the primary data used in the analysis of catchment topography. We describe elevation data sources, digital elevation model structures, and the analysis of digital elevation data for hydrological, geomorphological, and biological applications. Some hydrologic models that make use of digital representations of topography are also considered.

Digital terrain modelling: A review of hydrological, geomorphological, and biological applications

TWO stochastic modeling approaches for multisite hydrologic forecasting are presented in this work. The models are of ARMAX class expressed in state‐space formulations. The first approach, the adaptive partitioning, models a large catchment by shifting the locations in their time‐lags and modeling the flows of the different subsystems one at a time. The adaptive partitioning approach reintroduces the partitioning proposed by Wood in 1981 in an adaptive and more flexible form. The second approach, the cascading, divides the large catchment into groups of locations and models the groups as subsystems. In both approaches, the models' parameters and noise statistics are updated on‐line in an adaptive manner along with the states. For this purpose, the work proposes an evaluation/ forecasting algorithm based on the three parallel filter theory‐, a state‐space, parameter‐space, and a noise‐space filter. The algorithm is a synthesis and development of two preceding studies by Hebson and Wood, in 1985, and Bergma...

Adaptive Parameter Estimation for Multisite Hydrologic Forecasting

A decision support system for demand management in the Rio Conchos basin, Mexico.

Bayesian theory provides for the explicit accounting of both parameter and model uncertainties. It is used in this work to derive a procedure for discriminating among alternative hydrologic regression models. In particular, the procedure was used to discriminate among alternative exogenous variables in regression models. Controlled experiments with hydrologic models were designed to test the proposed procedure under different assumptions on model prior probabilities, length of sample, and model subset. These examples showed that besides its theoretical advantages, the use of the Bayesian procedure unambiguously selects the correct model in most of the applications.

Choosing among alternative hydrologic regression models

Convective rainfalls of high intensity are largely responsible for most large floods occurring in arid regions. Convective storms are limited in size and rarely cover an entire basin. Therefore flood frequency is affected by the distribution of storm coverage c, which is the fraction of basin area upon which rainfall occurs. Analytical probability density function (pdf) estimates of partial storm coverage are presented as a function of basin area sc and the probability distribution function for storm radius rs Conditional pdfs for the covered area fraction c, given the storm radius f(c/rs), are obtained as a compound distribution with finite probability for maximum coverage and continuous density for smaller values. The conditionality assumption is removed by assuming an exponential storm radius marginal distribution to obtain the catchment coverage pdf. This pdf is compound, with discrete probability for complete catchment coverage P(c=1) and a continuous function for partial overlap. The continuous function combines a Weibull pdf and linear functions of c. Both P(c=1) and f(c)) depend on χ, the average catchment-to-storm radius ratio. The distribution explains the partial coverage data for the Walnut Gulch basin in Arizona. Departures were observed, however, for slightly less than complete coverage, namely, for 0.9 < c < 1. A conceptual event classification and a method were designed to include partial coverage effects on flood frequency distribution.

https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/98WR01246

Partial area coverage distribution for flood frequency analysis in arid regions

The task of real-time streamflow monitoring and forecasting is particularly challenging for ungauged or sparsely gauged river basins, and largely relies upon satellite-based estimates of precipitation. We present the design and implementation of a state-of-the-art real-time streamflow monitoring and forecasting platform that integrates information provided by cutting-edge satellite precipitation products (SPPs), numerical precipitation forecasts, and multiple hydrologic models, to generate probabilistic streamflow forecasts that have an effective lead time of 9 days. The modular design of the platform enables adding/removing any model/product as may be appropriate. The SPPs are bias-corrected in real-time, and the model generated streamflow forecasts are further bias-corrected and merged, to produce probabilistic forecasts that are computed via several model averaging techniques. The platform is currently operational in multiple river basins in Africa, and can also be adapted to any new basin by incorporating some basin-specific changes and recalibration of the hydrologic models.

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Juan B. Valdés

Papers

Adaptive Parameter Estimation for Multisite Hydrologic Forecasting

A decision support system for demand management in the Rio Conchos basin, Mexico.

Choosing among alternative hydrologic regression models

Partial area coverage distribution for flood frequency analysis in arid regions

Design and implementation of an operational multimodel multiproduct real-time probabilistic streamflow forecasting platform