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1.
Abstract A hydrological modelling framework was assembled to simulate the daily discharge of the Mandovi River on the Indian west coast. Approximately 90% of the west-coast rainfall, and therefore discharge, occurs during the summer monsoon (June–September), with a peak during July–August. The modelling framework consisted of a digital elevation model (DEM) called GLOBE, a hydrological routing algorithm, the Terrestrial Hydrological Model with Biogeochemistry (THMB), an algorithm to map the rainfall recorded by sparse raingauges to the model grid, and a modified Soil Conservation Service Curve Number (SCS-CN) method. A series of discharge simulations (with and without the SCS method) was carried out. The best simulation was obtained after incorporating spatio-temporal variability in the SCS parameters, which was achieved by an objective division of the season into five regimes: the lean season, monsoon onset, peak monsoon, end-monsoon, and post-monsoon. A novel attempt was made to incorporate objectively the different regimes encountered before, during and after the Indian monsoon, into a hydrological modelling framework. The strength of our method lies in the low demand it makes on hydrological data. Apart from information on the average soil type in a region, the entire parameterization is built on the basis of the rainfall that is used to force the model. That the model does not need to be calibrated separately for each river is important, because most of the Indian west-coast basins are ungauged. Hence, even though the model has been validated only for the Mandovi basin, its potential region of application is considerable. In the context of the Prediction in Ungauged Basins (PUB) framework, the potential of the proposed approach is significant, because the discharge of these (ungauged) rivers into the eastern Arabian Sea is not small, making them an important element of the local climate system. Editor D. Koutsoyiannis; Associate editor S. Grimaldi Citation Suprit, K., Shankar, D., Venugopal, V. and Bhatkar, N.V., 2012. Simulating the daily discharge of the Mandovi River, west coast of India. Hydrological Sciences Journal, 57 (4), 686–704. 相似文献
2.
AbstractThe seasonal variation of land–atmosphere coupling strength has been examined using an extended series of atmospheric general circulation model (AGCM) simulations. In the Western Sahel of Africa, strong coupling strength for precipitation is found in April and May, just prior to and at the beginning of the monsoon season. At this time, heat and water fluxes from the surface are strongly controlled by land conditions, and the unstable conditions in the lower level of the troposphere, as induced by local land state, allow the surface fluxes to influence the variability of convective precipitation—and thus the timing of monsoon onset.Editor Z. W. KundzewiczCitation Yamada, T.J., Kanae, S., Oki, T., and Koster, R.D., 2013. Seasonal variation of land–atmosphere coupling strength over the West African monsoon region in an atmospheric general circulation model. Hydrological Sciences Journal, 58 (6), 1276–1286. 相似文献
3.
《水文科学杂志》2013,58(4)
Abstract Abstract Is it possible to make seasonal and interannual forecasts of hydrological variables if one cannot predict next week’s rainfall? Contrary to common view, some scientists support the hypothesis that variations in mean global temperature and precipitation are controlled more by external forcing (solar variability and volcanic eruptions) than by increasing atmospheric concentration of greenhouse gases. Temperature and precipitation are connected with special phases of the 11-year sunspot cycle, which coincide with significant accumulation of energetic solar eruptions. Because of the possibility of identifying years with many solar eruptions, the attractive prospect emerges of the long-term hydrological forecasting based on cycles of solar activity. Starting from this assumption, an expert system was built based on a fuzzy neural network model for seasonal and interannual forecasting of the Po River discharge. It was found that indices of solar activity and of global circulation are sufficient to yield useful forecasts of hydrological variables. 相似文献
4.
《水文科学杂志》2013,58(5)
Abstract A method is introduced for probabilistic forecasting of hydrological events based on geostatistical analysis. In this method, the predictors of a hydrological variable define a virtual field such that, in this field, the observed dependent variables are considered as measurement points. Variography of the measurement points enables the use of the system of kriging equations to estimate the value of the variable at non-measured locations of the field. Non-measured points are the forecasts associated with specific predictors. Calculation of the estimation variance facilitates probabilistic analysis of the forecast variables. The method is applied to case studies of the Red River in Manitoba, Canada and Karoon River in Khoozestan, Iran. The study analyses the advantages and limitations of the proposed method in comparison with a K-nearest neighbour approach and linear and nonlinear multiple regression. The utility of the proposed method for forecasting hydrological variables with a conditional probability distribution is demonstrated. 相似文献
5.
ABSTRACT This paper attempts to design statistical models to forecast annual precipitation in the Neuquen and Limay river basins in the Comahue region of Argentina. These forecasts are especially useful as they are used to better organize the operation of hydro-electric dams, the agriculture in irrigated valleys and the safety of the population. In this work, multiple linear regression statistical models are built to forecast mean annual rainfall over the two river basins. Since the maximum precipitation occurs in the winter (June–August), forecasting models have been developed for the beginning of March and for the beginning of June, just before the rainy season starts. The results show that the sea-surface temperatures of the Indian and Pacific oceans are good predictors for March models and explain 42.8% of the precipitation index variance. The efficiency of the models increases in June, adding more predictors related to the autumn circulation. 相似文献
6.
ABSTRACTThe aims of this study are to investigate the influence of large-scale atmospheric circulation quantified by indices such as the North Atlantic Oscillation index (NAOI), the Greenland-Balkan Oscillation index (GBOI) and blocking-type indices on the Lower Danube discharge. We separately analysed each season for the 1948–2000 period. In addition to the statistical linear procedure, we applied methods to quantify nonlinear connections between variables, as mutual information between predictors and predictand, using Shannon’s information entropy theory. The nonlinear correlation information between climate indices and discharge is higher than that obtained from the linear measure, providing more insight into real connections. Also, the non-stationarity of the link between variables is highlighted by spectral coherence based on wavelet analysis. For the physical interpretation, we analyse composite maps over the Atlantic-European region. The most significant influence on the discharge of the Lower Danube Basin is given by the GBOI and blocking-type atmospheric circulation over Europe. 相似文献
7.
《水文科学杂志》2013,58(3)
Abstract West African rainfall is characterized by a strong variability, both at decadal and interannual scales. In order to quantify the hydrological impacts of such a variability, analysis of rainfall patterns at fine scales is highly essential. This diagnostic study aims to characterize the Sudanese rainfall regime at hydrological scales, using a raingauge data set collected on the upper Oueme River catchment (Benin) between 1950 and 2002. A long-term drought is observed during the 1970s and 1980s, as in the Sahel. However, the interannual variability remains significant in the Sudanese region. The study of the seasonal cycle, based on the distinction between the oceanic and continental monsoon regimes, shows that the majority of rainfall changes occur in the continental regime. On the one hand, the rainfall peak associated with this regime that has been observed for the last 50 years has occurred increasingly earlier in the season. On the other hand, the annual rainfall deficit is mainly linked to the decrease in the number of large events during the continental part of the season. 相似文献
8.
Identification of best predictors for forecasting seasonal rainfall and runoff in Australia 总被引：2，自引：0，他引：2
The first step towards developing a reliable seasonal runoff forecast is identifying the key predictors that drive rainfall and runoff. This paper investigates the lag relationships between rainfall across Australia and runoff across southeast Australia versus 12 atmospheric‐oceanic predictors, and how the relationships change over time. The analysis of rainfall data indicates that the relationship is greatest in spring and summer in northeast Australia and in spring in southeast Australia. The best predictors for spring rainfall in eastern Australia are NINO4 [sea surface temperature (SST) in western Pacific] and thermocline (20 °C isotherm of the Pacific) and those for summer rainfall in northeast Australia are NINO4 and Southern Oscillation Index (SOI) (pressure difference between Tahiti and Darwin). The relationship in northern Australia is greatest in spring and autumn with NINO4 being the best predictor. In western Australia, the relationship is significant in summer, where SST2 (SST over the Indian Ocean) and II (SST over the Indonesian region) is the best predictor in the southwest and northwest, respectively. The analysis of runoff across southeast Australia indicates that the runoff predictability in the southern parts is greatest in winter and spring, with antecedent runoff being the best predictor. The relationship between spring runoff and NINO4, thermocline and SOI is also relatively high and can be used together with antecedent runoff to forecast spring runoff. In the northern parts of southeast Australia, the atmospheric‐oceanic variables are better predictors of runoff than antecedent runoff, and have significant correlation with winter, spring and summer runoff. For longer lead times, the runoff serial correlation is reduced, especially over the northern parts, and the atmospheric‐oceanic variables are likely to be better predictors for forecasting runoff. The correlations between runoff versus the predictors vary with time, and this has implications for the development of forecast relationship that assumes stationarity in the historical data. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
9.
《水文科学杂志》2013,58(6):1006-1020
AbstractThis paper aims to compare the shift in frequency distribution and skill of seasonal climate forecasting of both streamflow and rainfall in eastern Australia based on the Southern Oscillation Index (SOI) Phase system. Recent advances in seasonal forecasting of climate variables have highlighted opportunities for improving decision making in natural resources management. Forecasting of rainfall probabilities for different regions in Australia is available, but the use of similar forecasts for water resource supply has not been developed. The use of streamflow forecasts may provide better information for decision-making in irrigation supply and flow management for improved ecological outcomes. To examine the relative efficacy of seasonal forecasting of streamflow and rainfall, the shift in probability distributions and the forecast skill were evaluated using the Wilcoxon rank-sum test and the linear error in probability space (LEPS) skill score, respectively, at three river gauging stations in the Border Rivers Catchment of the Murray-Darling Basin in eastern Australia. A comparison of rainfall and streamflow distributions confirms higher statistical significance in the shift of streamflow distribution than that in rainfall distribution. Moreover, streamflow distribution showed greater skill of forecasting with 0–3 month lead time, compared to rainfall distribution. 相似文献
10.
AbstractAn artificial neural network, mid- to long-term runoff forecasting model of the Nenjiang basin was established by deciding predictors using the physical analysis method, combined with long-term hydrological and meteorological information. The forecasting model was gradually improved while considering physical factors, such as the main flood season and non-flood season by stage, runoff sources and hydrological processes. The average relative errors in the simulation tests of the prediction model were 0.33 in the main flood season and 0.26 in the non-flood season, indicating that the prediction accuracy during the non-flood season was greater than that in the main flood season. Based on these standards, forecasting accuracy evaluation was conducted by comparing forecasting results with actual conditions: for 2001 to 2003 data, the pass rate of forecasting in the main flood season was 50%, while it was 93% in the non-flood season; for 2001–2010, the respective values were 45% and 72%. The accuracy of prediction was found to decrease as the length of record increases.Editor D. Koutsoyiannis, Associate editor A. ViglioneCitation Li, H.-Y. Tian, L., Wu, Y., and Xie, M., 2013. Improvement of mid- to long-term runoff forecasting based on physical causes: application in Nenjiang basin, China. Hydrological Sciences Journal, 58 (7), 1414–1422. 相似文献
11.
A seasonal water budget analysis was carried out to quantify various components of the hydrological cycle using the Soil and Water Assessment Tool (SWAT) model for the Betwa River basin (43?500 km2) in central India. The model results were satisfactory in calibration and validation. The seasonal water budget analysis showed that about 90% of annual rainfall and 97% of annual runoff occurred in the monsoon season. A seasonal linear trend analysis was carried out to detect trends in the water balance components of the basin for the period 1973–2001. In the monsoon season, an increasing trend in rainfall and a decreasing trend in ET were observed; this resulted in an increasing trend in groundwater storage and surface runoff. The winter season followed almost the same pattern. A decreasing trend was observed in summer season rainfall. The study evokes the need for conservation structures in the study area to reduce monsoon runoff and conserve it for basin requirements in water-scarce seasons.
EDITOR Z.W. KundzewiczASSOCIATE EDITOR F. Hattermann 相似文献
12.
Abstract One of the world's largest irrigation networks, based on the Indus River system in Pakistan, faces serious scarcity of water in one season and disastrous floods in another. The system is dominated both by monsoon and by snow and glacier dynamics, which confer strong seasonal and inter-annual variability. In this paper two different forecasting methods are utilized to analyse the long-term seasonal behaviour of the Indus River. The study also assesses whether the strong seasonal behaviour is dominated by the presence of low-dimensional nonlinear dynamics, or whether the periodic behaviour is simply immersed in random fluctuations. Forecasts obtained by nonlinear prediction (NLP) and the seasonal autoregressive integrated moving average (SARIMA) methods show that the performance of NLP is relatively better than the SARIMA method. This, along with the low values of the correlation dimension, is indicative of low-dimensional nonlinear behaviour of the hydrological dynamics. A relatively better performance of NLP, using an inverse technique, may also be indicative of the low-dimensional behaviour. Moreover, the embedding dimension of the best NLP forecasts is in good agreement with the estimated correlation dimension. This provides evidence that the nonlinearity inherent in the monthly river flow due to the snowmelt and the monsoon variations dominate over the high-dimensional components and might be exploited for prediction and modelling of the complex hydrological system. Citation Hassan, S. A. & Ansari, M. R. K. (2010) Nonlinear analysis of seasonality and stochasticity of the Indus River. Hydrol. Sci. J. 55(2), 250–265. 相似文献
13.
Abstract This study contributes to the comprehensive assessment of flood hazard and risk for the Phrae flood plain of the Yom River basin in northern Thailand. The study was carried out using a hydrologic–hydrodynamic model in conjunction with a geographic information system (GIS). The model was calibrated and verified using the observed rainfall and river flood data during flood seasons in 1994 and 2001, respectively. Flooding scenarios were evaluated in terms of flooding depth for events of 25-, 50-, 100- and 200-year return periods. An impact-based hazard estimation technique was applied to assess the degree of hazard across the flood plain. The results showed that 78% of the Phrae flood-plain area of 476 km2 in the upper Yom River basin lies in the hazard zone of the 100-year return-period flood. Risk analyses were performed by incorporating flood hazard and the vulnerability of elements at risk. Based on relative magnitude of risk, flood-prone areas were divided into low-, moderate-, high- and severe-risk zones. For the 100-year return-period flood, the risk-free area was found to be 22% of the total flood plain, while areas under low, medium, high and severe risk were 33, 11, 28 and 6%, respectively. The outcomes are consistent with overall property damage recorded in the past. The study identifies risk areas for priority-based flood management, which is crucial when there is a limited budget to protect the entire risk zone simultaneously. Citation Tingsanchali, T. & Karim, F. (2010) Flood-hazard assessment and risk-based zoning of a tropical flood plain: case study of the Yom River, Thailand. Hydrol. Sci. J. 55(2), 145–161. 相似文献
14.
A. K. Mitra L. Stefanova T. S. V. Vijaya Kumar T. N. Krishnamurti 《Pure and Applied Geophysics》2005,162(8-9):1431-1454
Seasonal climate prediction for the Indian summer monsoon season is critical for strategic planning of the region. The mean features of the Indian summer monsoon and its variability, produced by versions of the ‘Florida State University Coupled Ocean-Atmosphere General Circulation Model’ (FSUCGCM) hindcasts, are investigated for the period 1987 to 2002. The coupled system has full global ocean and atmospheric models with coupled assimilation. Four member models were created by choosing different combinations of parameterizations of the physical processes in the atmospheric model component. Lower level wind flow patterns and rainfall associated with the summer monsoon season are examined from this fully coupled model seasonal integrations. By comparing with observations, the mean monsoon condition simulated by this coupled model for the June, July and August periods is seen to be reasonably realistic. The overall spatial low-level wind flow patterns and the precipitation distributions over the Indian continent and adjoining oceanic regions are comparable with the respective analyses. The anomalous below normal large-scale precipitation and the associated anomalous low-level wind circulation pattern for the summer monsoon season of 2002 was predicted by the model three months in advance. For the Indian summer monsoon, the ensemble mean is able to reproduce the mean features better compared to individual member models. 相似文献
15.
Takahiro Sayama Go Ozawa Takahiro Kawakami Seishi Nabesaka Kazuhiko Fukami 《水文科学杂志》2013,58(2):298-312
Abstract Pakistan has suffered a devastating flood disaster in 2010. In the Kabul River basin (92 605 km2), large-scale riverine and flash floods caused destructive damage with more than 1100 casualties. This study analysed rainfall–runoff and inundation in the Kabul River basin with a newly developed model that simulates the processes of rainfall–runoff and inundation simultaneously based on two-dimensional diffusion wave equations. The simulation results showed a good agreement with an inundation map produced based on MODIS for large-scale riverine flooding. In addition, the simulation identified flash flood-affected areas, which were confirmed to be severely damaged based on a housing damage distribution map. Since the model is designed to be used even immediately after a disaster, it can be a useful tool for analysing large-scale flooding and to provide supplemental information to agencies for relief operations. Editor Z.W. Kundzewicz Citation Sayama, T., Ozawa, G., Kawakami, T., Nabesaka, S. and Fukami, K., 2012. Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin. Hydrological Sciences Journal, 57 (2), 298–312. 相似文献
16.
GREGORY J. McCABE JR 《水文科学杂志》2013,58(6):873-887
Abstract Winter mean 700-hectoPascal (hPa) height anomalies, representing the average atmospheric circulation during the snow season, are compared with annual streamflow measured at 140 streamgauges in the western United States. Correlation and anomaly pattern analyses are used to identify relationships between winter mean atmospheric circulation and temporal and spatial variability in annual streamflow. Results indicate that variability in winter mean 700-Hpa height anomalies accounts for a statistically significant portion of the temporal variability in annual streamflow in the western United States. In general, above-average annual streamflow is associated with negative winter mean 700-Hpa height anomalies over the eastern North Pacific Ocean and/or the western United States. The anomalies produce an anomalous flow of moist air from the eastern North Pacific Ocean into the western United States that increases winter precipitation and snowpack accumulations, and subsequently streamflow. Winter mean 700-hPa height anomalies also account for statistically significant differences in spatial distributions of annual streamflow. As part of this study, winter mean atmospheric circulation patterns for the 40 years analysed were classified into five winter mean 700-hPa height anomaly patterns. These patterns are related to statistically significant and physically meaningful differences in spatial distributions of annual streamflow. 相似文献
17.
《水文科学杂志》2013,58(2)
Abstract An updating technique is a tool to update the forecasts of mathematical flood forecasting model based on data observed in real time, and is an important element in a flood forecasting model. An error prediction model based on a fuzzy rule-based method was proposed as the updating technique in this work to improve one- to four-hour-ahead flood forecasts by a model that is composed of the grey rainfall model, the grey rainfall—runoff model and the modified Muskingum flow routing model. The coefficient of efficiency with respect to a benchmark is applied to test the applicability of the proposed fuzzy rule-based method. The analysis reveals that the fuzzy rule-based method can improve flood forecasts one to four hours ahead. The proposed updating technique can mitigate the problem of the phase lag in forecast hydrographs, and especially in forecast hydrographs with longer lead times. 相似文献
18.
Archana Nair Nachiketa Acharya Ankita Singh U. C. Mohanty T. C. Panda 《Pure and Applied Geophysics》2013,170(11):1945-1967
In this study the predictability of northeast monsoon (Oct–Nov–Dec) rainfall over peninsular India by eight general circulation model (GCM) outputs was analyzed. These GCM outputs (forecasts for the whole season issued in September) were compared with high-resolution observed gridded rainfall data obtained from the India Meteorological Department for the period 1982–2010. Rainfall, interannual variability (IAV), correlation coefficients, and index of agreement were examined for the outputs of eight GCMs and compared with observation. It was found that the models are able to reproduce rainfall and IAV to different extents. The predictive power of GCMs was also judged by determining the signal-to-noise ratio and the external error variance; it was noted that the predictive power of the models was usually very low. To examine dominant modes of interannual variability, empirical orthogonal function (EOF) analysis was also conducted. EOF analysis of the models revealed they were capable of representing the observed precipitation variability to some extent. The teleconnection between the sea surface temperature (SST) and northeast monsoon rainfall was also investigated and results suggest that during OND the SST over the equatorial Indian Ocean, the Bay of Bengal, the central Pacific Ocean (over Nino3 region), and the north and south Atlantic Ocean enhances northeast monsoon rainfall. This observed phenomenon is only predicted by the CCM3v6 model. 相似文献
19.
Deepti Joshi Andre St-Hilaire Taha B. M. J. Ouarda Anik Daigle Nathalie Thiemonge 《水文科学杂志》2013,58(11):1996-2010
ABSTRACTThis work explores the ability of two methodologies in downscaling hydrological indices characterizing the low flow regime of three salmon rivers in Eastern Canada: Moisie, Romaine and Ouelle. The selected indices describe four aspects of the low flow regime of these rivers: amplitude, frequency, variability and timing. The first methodology (direct downscaling) ascertains a direct link between large-scale atmospheric variables (the predictors) and low flow indices (the predictands). The second (indirect downscaling) involves downscaling precipitation and air temperature (local climate variables) that are introduced into a hydrological model to simulate flows. Synthetic flow time series are subsequently used to calculate the low flow indices. The statistical models used for downscaling low flow hydrological indices and local climate variables are: Sparse Bayesian Learning and Multiple Linear Regression. The results showed that direct downscaling using Sparse Bayesian Learning surpassed the other approaches with respect to goodness of fit and generalization ability.
Editor D. Koutsoyiannis; Associate editor K. Hamed 相似文献
20.
Stable isotopic compositions (δ18O and d-excess) from 25 rivers in Thailand were analysed monthly during 2013–2015. Results indicated that monsoon precipitation fundamentally influences the river isotopes. The overland flow supplied from monsoon precipitation and human-altered flow regimes produces considerable isotopic variability. Spatial and temporal variations were observed among four principal geographical regions. The seasonality of monsoon precipitation in mountainous Thailand produced large variations in isotopic compositions because most rainfall occurred during the southwest monsoon, and dry conditions prevailed during the northeast monsoon. The northern and northeastern regions are mountainous, highland areas. Low δ18O values were found in these regions, likely because of altitude effects on precipitation. Conversely, monsoonal precipitation continually supplies rivers in southern Thailand all year round, producing higher and more consistent δ18O values than in the other regions. The Chao Phraya plain in the central region experienced enrichment of δ18O river runoff related to evaporation in irrigation systems. Larger catchment areas and longer residence times resulted in more pronounced evaporation effects, producing lower values of d-excess and local river water line slopes compared with precipitation. The isotopic differences between river waters and precipitation were utilized to determine river recharge elevations and water transit time. The methods presented here can be used to explore hydrological interactions in other tropical river basins. 相似文献