41846
2018
2018
eng
16
postprint
1
2018-11-12
2018-11-12
--
Seasonal drought prediction for semiarid northeastern Brazil
A set of seasonal drought forecast models was assessed and verified for the Jaguaribe River in semiarid northeastern Brazil. Meteorological seasonal forecasts were provided by the operational forecasting system used at FUNCEME (Ceará’s research foundation for meteorology)and by the European Centre for Medium-Range Weather Forecasts (ECMWF). Three downscaling approaches (empirical quantile mapping, extended downscaling and weather pattern classification) were tested and combined with the models in hindcast mode for the period 1981 to 2014. The forecast issue time was January and the forecast period was January to June. Hydrological drought indices were obtained by fitting a multivariate linear regression to observations. In short, it was possible to obtain forecasts for (a) monthly precipitation,(b) meteorological drought indices, and (c) hydrological drought indices. The skill of the forecasting systems was evaluated with regard to root mean square error (RMSE), the Brier skill score (BSS) and the relative operating characteristic skill score (ROCSS). The tested forecasting products showed similar performance in the analyzed metrics. Forecasts of monthly precipitation had little or no skill considering RMSE and mostly no skill with BSS. A similar picture was seen when forecasting meteorological drought indices: low skill regarding RMSE and BSS and significant skill when discriminating hit rate and false alarm rate given by the ROCSS (forecasting drought events of, e.g., SPEI1 showed a ROCSS of around 0.5). Regarding the temporal variation of the forecast skill of the meteorological indices, it was greatest for April, when compared to the remaining months of the rainy season, while the skill of reservoir volume forecasts decreased with lead time. This work showed that a multi-model ensemble can forecast drought events of timescales relevant to water managers in northeastern Brazil with skill. But no or little skill could be found in the forecasts of monthly precipitation or drought indices of lower scales, like SPI1. Both this work and those here revisited showed that major steps forward are needed in forecasting the rainy season in northeastern Brazil.
Hydrology and Earth System Sciences
verification of six hydro-meteorological forecast products
urn:nbn:de:kobv:517-opus4-418461
online registration
Hydrology and earth system sciences 22 (2018) Nr.9, S.5041-5056 DOI:10.5194/hess-22-5041-2018
<a href="http://publishup.uni-potsdam.de/opus4-ubp/frontdoor/index/index/docId/41845">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
CC-BY - Namensnennung 4.0 International
José Miguel Martins Delgado
Sebastian Voss
Gerd Bürger
Klaus Josef Vormoor
Aline Murawski
José Marcelo Rodrigues Pereira
Eduardo Martins
Francisco Vasconcelos Júnior
Till Francke
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
476
eng
uncontrolled
Hydrological drought
eng
uncontrolled
River-Basin
eng
uncontrolled
Model
eng
uncontrolled
Patterns
eng
uncontrolled
Precipitation
eng
uncontrolled
Variability
eng
uncontrolled
Nordeste
Geowissenschaften
open_access
Mathematisch-Naturwissenschaftliche Fakultät
Referiert
Open Access
Universität Potsdam
https://publishup.uni-potsdam.de/files/41846/pmnr476.online.pdf
42795
2019
2019
eng
21
702
postprint
1
2019-04-26
2019-04-26
--
Seasonal drought prediction for semiarid northeast Brazil
The semiarid northeast of Brazil is one of the most densely populated dryland regions in the world and recurrently affected by severe droughts. Thus, reliable seasonal forecasts of streamflow and reservoir storage are of high value for water managers. Such forecasts can be generated by applying either hydrological models representing underlying processes or statistical relationships exploiting correlations among meteorological and hydrological variables. This work evaluates and compares the performances of seasonal reservoir storage forecasts derived by a process-based hydrological model and a statistical approach.
Driven by observations, both models achieve similar simulation accuracies. In a hindcast experiment, however, the accuracy of estimating regional reservoir storages was considerably lower using the process-based hydrological model, whereas the resolution and reliability of drought event predictions were similar by both approaches. Further investigations regarding the deficiencies of the process-based model revealed a significant influence of antecedent wetness conditions and a higher sensitivity of model prediction performance to rainfall forecast quality.
Within the scope of this study, the statistical model proved to be the more straightforward approach for predictions of reservoir level and drought events at regionally and monthly aggregated scales. However, for forecasts at finer scales of space and time or for the investigation of underlying processes, the costly initialisation and application of a process-based model can be worthwhile. Furthermore, the application of innovative data products, such as remote sensing data, and operational model correction methods, like data assimilation, may allow for an enhanced exploitation of the advanced capabilities of process-based hydrological models.
Postprints der Universität Potsdam Mathematisch-Naturwissenschaftliche Reihe
what is the added value of a process-based hydrological model?
10.25932/publishup-42795
urn:nbn:de:kobv:517-opus4-427950
1866-8372
Hydrology and Earth System Sciences 23 (2019), pp. 1951–1971 DOI: 10.5194/hess-23-1951-2019
<a href="http://publishup.uni-potsdam.de/opus4-ubp/frontdoor/index/index/docId/42794">Bibliographieeintrag der Originalveröffentlichung/Quelle</a>
false
true
CC-BY - Namensnennung 4.0 International
Tobias Pilz
José Miguel Martins Delgado
Sebastian Voss
Klaus Josef Vormoor
Till Francke
Alexandre Cunha Costa
Eduardo Martins
Axel Bronstert
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
702
eng
uncontrolled
Water Availability
eng
uncontrolled
Uncertainty Processor
eng
uncontrolled
Forecasting Framework
eng
uncontrolled
Sediment Transport
eng
uncontrolled
Reservoir Networks
eng
uncontrolled
Jaguaribe Basin
eng
uncontrolled
Climate
eng
uncontrolled
Precipitation
por
uncontrolled
Nordeste
eng
uncontrolled
Connectivity
Geowissenschaften
open_access
Institut für Geowissenschaften
Referiert
Open Access
Institut für Erd- und Umweltwissenschaften
Universität Potsdam
https://publishup.uni-potsdam.de/files/42795/pmnr702.pdf
4309
2009
eng
postprint
1
2010-07-19
--
--
Cellulose/gold nanocrystal hybrids via an ionic liquid/aqueous precipitation route
Injection of a mixture of HAuCl4 and cellulose dissolved in the ionic liquid (IL) 1-butyl-3-methylimidazolium chloride [Bmim]Cl into aqueous NaBH4 leads to colloidal gold nanoparticle/cellulose hybrid precipitates. This process is a model example for a very simple and generic approach towards (noble) metal/cellulose hybrids, which could find applications in sensing, sterile filtration, or as biomaterials.
urn:nbn:de:kobv:517-opus-45046
4504
Molecules 14 (2009), 11, S. 4682 - 4688, DOI: 10.3390/molecules14114682
<hr>The article was originally published by MDPI:
<br><a href="http://www.mdpi.com/journal/molecules">
Molecules</a>. - 14 (2009), 11, S. 4682-4688<br>
ISSN 1420-3049<br>
DOI <a href="http://dx.doi.org/10.3390/molecules14114682"> 10.3390/molecules14114682</a>
Zhonghao Li
Andreas Taubert
Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
paper 135
eng
uncontrolled
Cellulose
eng
uncontrolled
Gold nanoparticles
eng
uncontrolled
Ionic liquid
eng
uncontrolled
Precipitation
eng
uncontrolled
Hybrid material
Chemie und zugeordnete Wissenschaften
open_access
Institut für Chemie
Universität Potsdam
https://publishup.uni-potsdam.de/files/4309/pmnf135.pdf