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Citation Kundzewicz, Z. W. & Stakhiv, E. Z. (2010) Are climate models 'ready for prime time' in water resources management applications, or is more research needed? Editorial. Hydrol. Sci. J. 55(7), 1085-1089. [ABSTRACT FROM AUTHOR]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The state of Paraná is one of the largest corn producers in Brazil, cultivating in two growing seasons. This study evaluated bivariate correlations between precipitation and the second-crop corn yield between the first 10 days of April and the first 10 days of October using spatial statistics. The spatial analysis of yield was evaluated using geostatistical models and validated by cross-validation. Spatial analysis was performed using the local indicator of spatial association and a cross-semivariogram, and the co-dispersion coefficient was used to validate the correlation between variables. Cross-validation identified the exponential model as the best fit, indicating a spatial dependence of 317.26 km. Spatial associations between municipalities were significant throughout the state of Paraná, Brazil. The cross-semivariogram allowed fitting the wave, spherical, Gaussian, and exponential models, with a spatial correlation of 37.04 to 570.38 km between the precipitations and yield. Moreover, the co-dispersion coefficient validated the correlation between the two variables for all 10-day periods. [ABSTRACT FROM AUTHOR]

Regional flood frequency analyses are highly affected by the number of gauged catchments and lengths of observation periods at the individual gauges. Therefore, information is unevenly distributed in the region of interest. In particular, the occurrence of single extreme floods that are observed or not observed at some gauges, depending on the observation period, may have a large impact on the regionalization. We evaluated the impact of the sample length on the regionalization of a type-specific statistical mixture-model. In a case study it is shown how the regionalization error can be reduced by more than 50% if the sample sizes increase. We compare three approaches to handling this stochastic uncertainty in regionalization. The alignment of the statistical distribution parameters to consider the impact of extreme floods proved to be most beneficial when aiming to obtain homogeneous regionalized flood quantiles for hydrologically similar regions in a region with heterogeneous observation periods. [ABSTRACT FROM AUTHOR]

Accurate estimators of streamflow statistics are critical to the design, planning, and management of water resources. Given increasing evidence of trends in low-streamflow, new approaches to estimating low-streamflow statistics are needed. Here we investigate simple approaches to select a recent subset of the low-flow record to update the commonly used statistic of 7Q10, the annual minimum 7-day streamflow exceeded in 9 out of 10 years on average. Informed by low-streamflow records at 174 US Geological Survey streamgages, Monte Carlo simulation experiments evaluate competing approaches. We find that a strategy which estimates 7Q10 using the most recent 30 years of record when a trend is detected, reduces error and bias in 7Q10 estimators compared to use of the full record. This simple rule-based approach has potential as the basis for a framework for updating frequency-based statistics in the context of possible trends. [ABSTRACT FROM AUTHOR]

This study evaluates the thematic representation of drinking water quality of 211 habitations along the Dwarka River Basin (DRB), West Bengal, India. The dominant water type is Ca-Mg-HCO3. Statistical analysis of the spatial dataset indicates a clustering pattern (with a nearest-neighbour ratio of 0.368 and Z score of 29.774). Two different techniques, spatial interpolation of water quality index (WQI) and composite water quality index (WQIC) of physico-chemical constituents, were implemented to compare their performance. The WQIC indicates approximately 11.68% of the total study area is at non-permissible levels, whereas the normal WQI technique predicts about 1.64% of the area is in non-permissible zones. Spatial water quality zonation by means of the overlay technique was superior to the conventional WQI technique in precisely distinguishing the characteristics of the permissible area with respect to even a single WHO recommended water quality parameter. [ABSTRACT FROM AUTHOR]

Nowadays, mathematical models are widely used to predict climate processes, but little has been done to compare the models. In this study, multiple linear regression (MLR), multi-layer perceptron (MLP) network and adaptive neuro-fuzzy inference system (ANFIS) models were compared for precipitation forecasting. The large-scale climate signals were considered as inputs to the applied models. After selecting the most effective climate indices, the effects of large-scale climate signals on the seasonal standardized precipitation index (SPI) of the Maharlu-Bakhtaran catchment, Iran, simultaneously and with a delay, was analysed using a cross-correlation function. Hence, the SPI time series was forecasted up to four time intervals using MLR, MLP and ANFIS. The results showed that most of the indices were significant with SPI of different lag times. Comparison of the SPI forecast results by MLR, MLP and ANFIS models showed better performance for the MLP network than the other two models (RMSE = 0.86, MAE = 0.74 for the first step ahead of SPI forecasting).Editor D. Koutsoyiannis; Associate editor F. Pappenberger [ABSTRACT FROM PUBLISHER]

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Hydrological Sciences Journal/Journal des Sciences Hydrologiques is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)