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ABSTRACTThere is great potential in Data Assimilation (DA) for the purposes of uncertainty identification, reduction and real-time correction of hydrological models. This paper reviews the latest developments in Kalman filters (KFs), particularly the Extended KF (EKF) and the Ensemble KF (EnKF) in hydrological DA. The hydrological DA targets, methodologies and their applicability are examined. The recent applications of the EKF and EnKF in hydrological DA are summarized and assessed critically. Furthermore, this review highlights the existing challenges in the implementation of the EKF and EnKF, especially error determination and joint parameter estimation. A detailed review of these issues would benefit not only the Kalman-type DA but also provide an important reference to other hydrological DA types.
Editor D. Koutsoyiannis; Associate editor F. Pappenberger 相似文献
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Amadou Angelina Abdouramane Gado Djibo Ibrah Seidou Sanda Ketvara Sittichok 《水文科学杂志》2013,58(10):1709-1723
AbstractA significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). A t-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level. 相似文献
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Mamadou Adama Sarr Philippe Gachon Ousmane Seidou Christopher Robin Bryant Jacques André Ndione Jacques Comby 《水文科学杂志》2013,58(9):1538-1549
AbstractDaily precipitation data from 31 Senegalese stations spanning the period from 1950 to 2007 were used to examine the inter-annual variations of seven rainfall indices: the annual mean precipitation (MEAN); the annual standard deviation of daily precipitation (STD); the frequency of wet days (Prcp1); the maximum number of consecutive dry days (CDD); the maximum 3-day rainfall total (R3D); the wet day precipitation intensity (SDII); and the 90th percentile of rain-day precipitation (Prec90p). The indices were spatially averaged over three agro-climatic regions in Senegal. Trends in the time series of the averaged indices were assessed using both visual examination and a modified version of the Mann-Kendall (MM-K) test. Initially negative significant trends in all seven indices suggest gradually drier conditions over the three agro-climatic regions between 1950 and 1980. In contrast, no significant trends, or even positive significant trends, were observed from the mid-1980s to 2007. The MM-K test was applied to all available data (1950–2007) and the period from 1971 to 2000. While several indices were found to have significant trends towards drier conditions for the 1950–2007 period, only PRCP1 showed a positive significant trend for the 1971–2000 period. The MM-K test did not detect a significant trend for the other indices. It was found that the rainfall deficit and therefore drought is no longer intensifying, and that the region may even become wetter. However, the period covered by the observations is still too short to resolve the question of whether there is now a trend towards wetter conditions.
Editor Z.W. Kundzewicz; Associate editor K. Hamed 相似文献
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Flood quantiles are routinely used in hydrologic engineering to design hydraulic structures, optimize erosion control structure
and map the extent of floodplains. As an increasing number of papers are pointing out cycles and trends in hydrologic time
series, the use of stationary flood distributions leads to the overestimation or underestimation of the hydrologic risk at
a given time. Several authors tried to address this problem by using probability distributions with time-varying parameters.
The parameters of these distributions were assumed to follow a linear or quadratic trend in time, which may be valid for the
short term but may lead to unrealistic long-term projections. On the other hand, deterministic rainfall-runoff models are
able to successfully reproduce trends and cycles in stream flow data but can perform poorly in reproducing daily flows and
flood peaks. Rainfall-runoff models typically have a better performance when simulation results are aggregated at a larger
time scale (e.g. at a monthly time scale vs. at a daily time scale). The strengths of these two approaches are combined in
this paper where the annual maximum of the time-averaged outputs of a hydrologic model are used to modulate the parameters
of a non-stationary GEV model of the daily maximum flow. The method was applied to the Kemptville Creek located in Ontario,
Canada, using the SWAT (Soil and Water Assessment Tool) model as rainfall-runoff model. The parameters of the non-stationary
GEV model are then estimated using Monte Carlo Markov Chain, and the optimal span of the time windows over which the SWAT
outputs were averaged was selected using Bayes factors. Results show that using the non-stationary GEV distribution with a
location parameter linked to the maximum 9-day average flow provides a much better estimation of flood quantiles than applying
a stationary frequency analysis to the simulated peak flows. 相似文献
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The WAMME regional model intercomparison study 总被引：5，自引：3，他引：2
Leonard M. Druyan Jinming Feng Kerry H. Cook Yongkang Xue Matthew Fulakeza Samson M. Hagos Abdourahamane Konaré Wilfran Moufouma-Okia David P. Rowell Edward K. Vizy Seidou Sanda Ibrah 《Climate Dynamics》2010,35(1):175-192
Results from five regional climate models (RCMs) participating in the West African Monsoon Modeling and Evaluation (WAMME) initiative are analyzed. The RCMs were driven by boundary conditions from National Center for Environmental Prediction reanalysis II data sets and observed sea-surface temperatures (SST) over four May–October seasons, (2000 and 2003–2005). In addition, the simulations were repeated with two of the RCMs, except that lateral boundary conditions were derived from a continuous global climate model (GCM) simulation forced with observed SST data. RCM and GCM simulations of precipitation, surface air temperature and circulation are compared to each other and to observational evidence. Results demonstrate a range of RCM skill in representing the mean summer climate and the timing of monsoon onset. Four of the five models generate positive precipitation biases and all simulate negative surface air temperature biases over broad areas. RCM spatial patterns of June–September mean precipitation over the Sahel achieve spatial correlations with observational analyses of about 0.90, but within two areas south of 10°N the correlations average only about 0.44. The mean spatial correlation coefficient between RCM and observed surface air temperature over West Africa is 0.88. RCMs show a range of skill in simulating seasonal mean zonal wind and meridional moisture advection and two RCMs overestimate moisture convergence over West Africa. The 0.5° computing grid enables three RCMs to detect local minima related to high topography in seasonal mean meridional moisture advection. Sensitivity to lateral boundary conditions differs between the two RCMs for which this was assessed. The benefits of dynamic downscaling the GCM seasonal climate prediction are analyzed and discussed. 相似文献
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Alodah Abdullah Seidou Ousmane 《Stochastic Environmental Research and Risk Assessment (SERRA)》2020,34(7):993-1021
Stochastic Environmental Research and Risk Assessment - While Stochastic Weather Generators (SWGs) are used intensively in climate and hydrological applications to simulate hydroclimatic time... 相似文献
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Ketvara Sittichok Ousmane Seidou Abdouramane Gado Djibo Neeranat Kaewprasert Rakangthong 《水文科学杂志》2018,63(4):630-645
Two methods for generating streamflow forecasts in a Sahelian watershed, the Sirba basin, were compared. The direct method used a linear relationship to relate sea-surface temperature to annual streamflow, and then disaggregated on a monthly time scale. The indirect method used a linear relationship to generate annual precipitation forecasts, a temporal disaggregation to generate daily precipitation and the SWAT (Soil and Water Assessment Tool) model to generate monthly streamflow. The accuracy of the forecasts was assessed using the coefficient of determination, the Nash-Sutcliffe coefficient and the Hit score, and their economic value was evaluated using the cost/loss ratio method. The results revealed that the indirect method was slightly more effective than the direct method. However, the direct method achieved higher economic value in the majority of cost/loss situations, allowed for predictions with longer lead times and required less information. 相似文献