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1.
An adequately tested soil and water assessment tool (SWAT) model was applied to the runoff and sediment yield of a small agricultural watershed in eastern India using generated rainfall. The capability of the model for generating rainfall was evaluated for a period of 18 years (1981–1998). The watershed and subwatershed boundaries, drainage networks, slope, soil series and texture maps were generated using a geographical information system (GIS). A supervised classification method was used for land‐use/cover classification from satellite imageries. Model simulated monthly rainfall for the period of 18 years was compared with observations. Simulated monthly rainfall, runoff and sediment yield values for the monsoon season of 8 years (1991–1998) were also compared with their observed values. In general monthly average rainfall predicted by the model was in close agreement with the observed monthly average values. Also, simulated monthly average values of surface runoff and sediment yield using generated rainfall compared well with observed values during the monsoon season of the years 1991–1998. Results of this study revealed that the SWAT model can generate monthly average rainfall satisfactorily and thereby can produce monthly average values of surface runoff and sediment yield close to the observed values. Therefore, it can be concluded that the SWAT model could be used for developing a multiple year management plan for the critical erosion prone areas of a small watershed. Copyright © 2004 John Wiley & Sons, Ltd.  相似文献   

2.
A back‐propagation algorithm neural network (BPNN) was developed to synchronously simulate concentrations of total nitrogen (TN), total phosphorus (TP) and dissolved oxygen (DO) in response to agricultural non‐point source pollution (AGNPS) for any month and location in the Changle River, southeast China. Monthly river flow, water temperature, flow travel time, rainfall and upstream TN, TP and DO concentrations were selected as initial inputs of the BPNN through coupling correlation analysis and quadratic polynomial stepwise regression analysis for the outputs, i.e. downstream TN, TP and DO concentrations. The input variables and number of hidden nodes of the BPNN were then optimized using a combination of growing and pruning methods. The final structure of the BPNN was determined from simulated data based on experimental data for both the training and validation phases. The predicted values obtained using a BPNN consisting of the seven initial input variables (described above), one hidden layer with four nodes and three output variables matched well with observed values. The model indicated that decreasing upstream input concentrations during the dry season and control of NPS along the reach during average and flood seasons may be an effective way to improve Changle River water quality. If the necessary water quality and hydrology data are available, the methodology developed here can easily be applied to other case studies. The BPNN model is an easy‐to‐use modelling tool for managers to obtain rapid preliminary identification of spatiotemporal water quality variations in response to natural and artificial modifications of an agricultural drainage river. Copyright © 2009 John Wiley & Sons, Ltd.  相似文献   

3.
In the present research, possibility of predicting average summer-monsoon rainfall over India has been analyzed through Artificial Neural Network model. In formulating the ANN — based predictive model, three-layer network has been constructed with sigmoid non-linearity. The monthly summer monsoon rainfall totals, tropical rainfall indices and sea surface temperature anomalies have been considered as predictors while generating the input matrix for the ANN. The data pertaining to the years 1950–1995 have been explored to develop the predictive model. Finally, the prediction performance of neural net has been compared with persistence forecast and Multiple Linear Regression forecast and the supremacy of the ANN has been established over the other processes.  相似文献   

4.
Model calibration and validation are necessary before applying it for scenario assessment and watershed management.This study presented the methodology of evaluating Soil and Water Assessment Tool(SWAT) and tested the feasibility of SWAT on runoff and sediment load simulation in the Zhifanggou watershed located in hilly-gullied region of China.Daily runoff and sediment event data from 1998-2008 were used in this study;data from 1998-2003 were used for calibration and 2004-2008 for validation.The evaluation statistics for the daily runoff simulation showed that the model results were acceptable,but the model underestimated the runoff for high-flow events.For sediment load simulation,the SWAT performed well in capturing the trend of sediment load,while the model tended to underestimate sediment load during both the calibration and validation periods. The disparity between observed and simulated data most likely resulted from limitations of the existing SCS-CN and MUSLE methods in the model.This study indicated that the modification of SWAT components is needed to take rainfall intensity and its duration into account to enhance the model performance on peak flow and sediment load simulation during heavy rainfall season.  相似文献   

5.
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. Kundzewicz

ASSOCIATE EDITOR F. Hattermann  相似文献   

6.
ABSTRACT

The suspended sediment rating curves for six stations on four rivers in western and northern Greece are investigated. For each station the suspended sediment load is a power function of the water discharge, which may be distinguished according to wet and dry seasons; the latter yields higher sediment loads for a given discharge than the former. This is due to the higher erosivity of dry season rainfall compared to wet season rainfall producing the same runoff. All rating curve exponents b lie in the range 2.5–3.5 for the wet and 2.0–3.0 for the dry season and are related to the constants a of the curves by empirical equations. The variation in a and b is explained in terms of the annual precipitation and area of the basin, the hypsometric fall, the main channel length, and the average bedslope of the river from the basin divide to the station, through empirical relationships, which also permit the prediction of rating curves for ungauged basins.  相似文献   

7.
《Water Policy》2001,3(1):101-107
An attempt has been made to study the occurrence of floods in the two important river systems of north India, viz. Brahmaputra and Ganga. Both these river systems are located north of Lat. 22°N and lie in the longitudinal belt of north India from Long. 73°E to 97°E. Both these river systems are affected by floods during monsoon months of June–September. It has been seen after examining rainfall and floods of the period 1986–1999 that although variation of monsoon rainfall magnitudes received by these two basins differ considerably in each monsoon season, but by and large, the frequency of floods at their terminal gauge/discharge (G/D) sites at Dhubri and Farakka do not differ very much from each other.  相似文献   

8.
Seasonal and annual trends of changes in rainfall, rainy days, heaviest rain and relative humidity have been studied over the last century for nine different river basins in northwest and central India. The majority of river basins have shown increasing trends both in annual rainfall and relative humidity. The magnitude of increased rainfall for considered river basins varied from 2–19% of mean per 100 years. The maximum increase in rainfall is observed in the Indus (lower) followed by the Tapi river basin. Seasonal analysis shows maximum increase in rainfall in the post‐monsoon season followed by the pre‐monsoon season. There were least variations in the monsoon rainfall during the last century and winter rainfall has shown a decreasing trend. Most of the river basins have experienced decreasing trends in annual rainy days with a maximum decrease in the Mahanadi basin. The heaviest rain of the year has increased from 9–27 mm per 100 years over different river basins with a maximum of 27 mm for the Brahamani and Subaranrekha river basins. A combination of increase in heaviest rainfall and reduction in the number of rainy days suggest the possibility of increasing severity of floods. Such information is useful in the planning, development and management of water resources in the study area. Further, the majority of river basins have also experienced an increasing trend in relative humidity both on seasonal and annual scales. An increase in annual mean relative humidity for six river basins has been found in the range of 1–18% of mean per 100 years, while a decrease for three river basins from ? 1 to ? 13% of mean per 100 years was observed, providing a net increase in the study area by 2·4% of mean per 100 years. It is understood that an increase in areal extent of vegetation cover as well as rainfall over the last century has increased the moisture in the atmosphere through enhanced evapotranspiration, which in turn has increased the relative humidity. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

9.
Sediment transport from mountainous to lowland areas is considered one of the most important geomorphological processes. In the present study, variations in transported sediment loads and dissolved loads have been studied over 3 years (2008–2011) for two forested catchments located in the Lesser Himalayan region of India. Seasonal and annual suspended sediment flux was strongly influenced by amounts of rainfall and streamflow. On average, 93% of annual load was produced during the monsoon, of which 62–78% occurred in only five peak events. Sediment production by the degraded forest catchment (Bansigad) was 1.9-fold (suspended sediment load) to 5.9-fold (bedload) higher than the densely forested catchment (Arnigad). The dissolved organic matter potentially influences total dissolved solids in the stream. Heavy rainfall triggers both stream discharge and landslides, which lead to higher bedload transport. Total denudation rates for Arnigad and Bansigad were estimated at 0.68 and 1.02 mm?year?1, respectively.  相似文献   

10.
A large number of rivers are frozen annually, and the river ice cover has an influence on the geomorphological processes. These processes in cohesive sediment rivers are not fully understood. Therefore, this paper demonstrates the impact of river ice cover on sediment transport, i.e. turbidity, suspended sediment loads and erosion potential, compared with a river with ice‐free flow conditions. The present sediment transportation conditions during the annual cycle are analysed, and the implications of climate change on wintertime geomorphological processes are estimated. A one‐dimensional hydrodynamic model has been applied to the Kokemäenjoki River in Southwest Finland. The shear stress forces directed to the river bed are simulated with present and projected hydroclimatic conditions. The results of shear stress simulations indicate that a thermally formed smooth ice cover diminishes river bed erosion, compared with an ice‐free river with similar discharges. Based on long‐term field data, the river ice cover reduces turbidity statistically significantly. Furthermore, suspended sediment concentrations measured in ice‐free and ice‐covered river water reveal a diminishing effect of ice cover on riverine sediment load. The hydrodynamic simulations suggest that the influence of rippled ice cover on shear stress is varying. Climate change is projected to increase the winter discharges by 27–77% on average by 2070–2099. Thus, the increasing winter discharges and possible diminishing ice cover periods both increase the erosion potential of the river bed. Hence, the wintertime sediment load of the river is expected to become larger in the future. Copyright © 2015 John Wiley & Sons, Ltd.  相似文献   

11.
The HIRHAM regional climate model suggests an increase in temperature in Denmark of about 3 °C and an increase in mean annual precipitation of 6–7%, with a larger increase during winter and a decrease during summer between a control period 1961–1990 and scenario period 2071–2100. This change of climate will affect the suspended sediment transport in rivers, directly through erosion processes and increased river discharges and indirectly through changes in land use and land cover. Climate‐change‐induced changes in suspended sediment transport are modelled for five scenarios on the basis of modelled changes in land use/land cover for two Danish river catchments: the alluvial River Ansager and the non‐alluvial River Odense. Mean annual suspended sediment transport is modelled to increase by 17% in the alluvial river and by 27% in the non‐alluvial for steady‐state scenarios. Increases by about 9% in the alluvial river and 24% in the non‐alluvial river were determined for scenarios incorporating a prolonged growing season for catchment vegetation. Shortening of the growing season is found to have little influence on mean annual sediment transport. Mean monthly changes in suspended sediment transport between ? 26% and + 68% are found for comparable suspended sediment transport scenarios between the control and the scenario periods. The suspended sediment transport increases during winter months as a result of the increase in river discharge caused by the increase in precipitation, and decreases during summer and early autumn months. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

12.
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   

13.
River discharges vary strongly through time and space, and quantifying this variability is fundamental to understanding and modelling river processes. The river basin is increasingly being used as the unit for natural resource planning and management; to facilitate this, basin‐scale models of material supply and transport are being developed. For many basin‐scale planning activities, detailed rainfall‐runoff modelling is neither necessary nor tractable, and models that capture spatial patterns of material supply and transport averaged over decades are sufficient. Nevertheless, the data to describe the spatial variability of river discharge across large basins for use in such models are often limited, and hence models to predict river discharge at the basin scale are required. We describe models for predicting mean annual flow and a non‐dimensional measure of daily flow variability for every river reach within a drainage network. The models use sparse river gauging data, modelled grid surfaces of mean annual rainfall and mean annual potential evapotranspiration, and a network accumulation algorithm. We demonstrate the parameterization and application of the models using data for the Murrumbidgee basin, in southeast Australia, and describe the use of these predictions in modelling sediment transport through the river network. The regionalizations described contain less uncertainty, and are more sensitive to observed spatial variations in runoff, than regionalizations based on catchment area and rainfall alone. Copyright © 2006 John Wiley & Sons, Ltd.  相似文献   

14.
In this paper, a hybrid machine learning ensemble approach namely the Rotation Forest based Radial Basis Function (RFRBF) neural network is proposed for spatial prediction of landslides in part of the Himalayan area (India). The proposed approach is an integration of the Radial Basis Function (RBF) neural network classifier and Rotation Forest ensemble, which are state-of-the art machine learning algorithms for classification problems. For this purpose, a spatial database of the study area was established that consists of 930 landslide locations and fifteen influencing parameters (slope angle, road density, curvature, land use, distance to road, plan curvature, lineament density, distance to lineaments, rainfall, distance to river, profile curvature, elevation, slope aspect, river density, and soil type). Using the database, training and validation datasets were generated for constructing and validating the model. Performance of the model was assessed using the Receiver Operating Characteristic (ROC) curve, area under the ROC curve (AUC), statistical analysis methods, and the Chi square test. In addition, Logistic Regression (LR), Multi-layer Perceptron Neural Networks (MLP Neural Nets), Naïve Bayes (NB), and the hybrid model of Rotation Forest and Decision Trees (RFDT) were selected for comparison. The results show that the proposed RFRBF model has the highest prediction capability in comparison to the other models (LR, MLP Neural Nets, NB, and RFDT); therefore, the proposed RFRBF model is promising and should be used as an alternative technique for landslide susceptibility modeling.  相似文献   

15.
Ashok Mishra  S. Kar  V. P. Singh 《水文研究》2007,21(22):3035-3045
The Hydrologic Simulation Programme‐Fortran (HSPF), a hydrologic and water quality computer model, was employed for simulating runoff and sediment yield during the monsoon months (June–October) from a small watershed situated in a sub‐humid subtropical region of India. The model was calibrated using measured runoff and sediment yield data for the monsoon months of 1996 and was validated for the monsoon months of 2000 and 2001. During the calibration period, daily‐calibrated runoff had a Nash‐Sutcliffe efficiency (ENS) value of 0·68 and during the validation period it ranged from 0·44 to 0·67. For daily sediment yield ENS was 0·71 for the calibration period and it ranged from 0·68 to 0·90 for the validation period. Sensitivity analysis was performed to assess the impact of important watershed characteristics. The model parameters obtained in this study could serve as reference values for model application in similar climatic regions, with practical implications in watershed planning and management and designing best management practices. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

16.
A high-resolution (～1 km horizontal grid and 21 vertical layers) numerical model based on the Princeton Ocean Model (POM) has been used to study the 3D dynamics of the Upper Gulf of Thailand (UGOT). While influenced by tides and rivers like other estuarine systems, the UGOT is unique because it is wide (～100 km?×?100 km), it is shallow (average depth of only ～15 m), it is located in low latitudes (～12.5°N–13.5°N), and it is influenced by the seasonal monsoon. Sensitivity studies were thus conducted to evaluate the impact that surface heat fluxes, monsoonal winds, river runoffs, and the low latitude may have on the dynamics; the latter has been evaluated by modifying the Coriolis parameter and comparing simulations representing low and mid latitudes. The circulation in the UGOT changes seasonally from counter-clockwise during the northeast monsoon (dry season) to clockwise during the southwest monsoon (wet season). River discharges generate coastal jets, whereas river plumes tend to be more symmetric near the river mouth and remain closer to the coast in low latitudes, compared with mid-latitude simulations. River plumes are also dispersed along the coast in different directions during different stages of the monsoonal winds. The model results are compared favorably with a simple wind-driven analytical estuarine model. Comparisons between an El Niño year (1998) and a La Niña year (2000) suggest that water temperatures, warmer by as much as 2 °C in 1998 relative to 2000, are largely driven by decrease cloudiness during the El Niño year. The developed model of the UGOT could be used in the future to address various environmental problems affecting the region.  相似文献   

17.
The event‐ and physics‐based KINEROS2 runoff/erosion model for predicting overland flow generation and sediment production was applied to unpaved mountain roads. Field rainfall simulations conducted in northern Thailand provided independent data for model calibration and validation. Validation shows that KINEROS2 can be parameterized to simulate total discharge, sediment transport and sediment concentration on small‐scale road plots, for a range of slopes, during simulated rainfall events. The KINEROS2 model, however, did not accurately predict time‐dependent changes in sediment output and concentration. In particular, early flush peaks and the temporal decay in sediment output were not predicted, owing to the inability of KINEROS2 to model removal of a surface sediment layer of finite depth. After 15–20 min, sediment transport declines as the supply of loose superficial material becomes depleted. Modelled erosion response was improved by allowing road erodibility to vary during an event. Changing the model values of erosion detachment parameters in response to changes in surface sediment availability improved model accuracy of predicted sediment transport by 30–40%. A predictive relationship between road erodibility ‘states’ and road surface sediment depth is presented. This relationship allows implementation of the dynamic erodibility (DE) method to events where pre‐storm sediment depth can be estimated (e.g., from traffic usage variables). Copyright © 2001 John Wiley & Sons, Ltd.  相似文献   

18.
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.
Time–frequency characterization is useful in understanding the nonlinear and non-stationary signals of the hydro-climatic time series. The traditional Fourier transform, and wavelet transform approaches have certain limitations in analyzing non-linear and non-stationary hydro-climatic series. This paper presents an effective approach based on the Hilbert–Huang transform to investigate time–frequency characteristics, and the changing patterns of sub-divisional rainfall series in India, and explored the possible association of monsoon seasonal rainfall with different global climate oscillations. The proposed approach integrates the complete ensemble empirical mode decomposition with adaptive noise algorithm and normalized Hilbert transform method for analyzing the spectral characteristics of two principal seasonal rainfall series over four meteorological subdivisions namely Assam-Meghalaya, Kerala, Orissa and Telangana subdivisions in India. The Hilbert spectral analysis revealed the dynamic nature of dominant time scales for two principal seasonal rainfall time series. From the trend analysis of instantaneous amplitudes of multiscale components called intrinsic mode functions (IMFs), it is found that both intra and inter decadal modes are responsible for the changes in seasonal rainfall series of different subdivisions and significant changes are noticed in the amplitudes of inter decadal modes of two seasonal rainfalls in the four subdivisions since 1970s. Further, the study investigated the links between monsoon rainfall with the global climate oscillations such as Quasi Bienniel Oscillation (QBO), El Nino Southern Oscillation (ENSO), Sunspot Number (SN), Atlantic Multidecadal Oscillation (AMO) etc. The study noticed that the multiscale components of rainfall series IMF1, IMF2, IMF3, IMF4 and IMF5 have similar periodic structure of QBO, ENSO, SN, tidal forcing and AMO respectively. As per the seasonal rainfall patterns is concerned, the results of the study indicated that for Assam-Meghalaya subdivision, there is a likelihood of extreme rare events at ~0.2 cycles per year, and both monsoon and pre-monsoon rainfall series have decreasing trends; for Kerala subdivision, extreme events can be expected during monsoon season with shorter periodicity (~2.5 years), and monsoon rainfall has statistically significant decreasing trend and post-monsoon rainfall has a statistically significant increasing trend; and for Orissa subdivision, there are chances of extremes rainfall events in monsoon season and a relatively stable rainfall pattern during post-monsoon period, but both monsoon and post-monsoon rainfall series showed an overall decreasing trend; for Telangana subdivision, there is a likelihood of extreme events during monsoon season with a periodicity of ~4 years, but both monsoon and post-monsoon rainfall series showed increasing trends. The results of correlation analysis of IMF components of monsoon rainfall and five climate indices indicated that the association is expressed well only for low frequency modes with similar evolution of trend components.  相似文献   

20.
Regional climate models are important tools to examine the spatial and temporal characteristics of rainfall and temperature at high resolutions. Such information has potential applications in sectors like agriculture and health. In this study, the Regional Climate Model Version 3 (RegCM3) has been integrated in the ensemble mode at 55 km resolution over India for the summer monsoon season during the years 1982–2009. Emphasis has been given on the validation of the model simulation at the regional level. In Central India, both rainfall and temperature show the best correlations with respective observed values. The model gives rise to large wet biases over Northwest and Peninsular India. RegCM3 slightly underestimates the summer monsoon precipitation over the Central and Northeast India. Nevertheless, over these regions, RegCM3 simulated rainfall is closer to the observations when compared to the other regions where rainfall is overestimated. The position of the monsoon trough simulated by the model lies to the north of its original observed position. This is similar to the usual monsoon break conditions leading to less rainfall over Central India. RegCM3 simulated surface maximum temperature shows a large negative bias over the country while the surface minimum temperature is close to the observation. Nevertheless, there is a strong correlation between the all India weighted average surface temperature simulated by RegCM3 and IMD observed values. While examining the extreme weather conditions in Central India, it is found that RegCM3 simulated frequencies of occurrence of very wet days, extremely wet days, warm days and warm nights more often as compared to those in IMD observed values. However, these are systematic biases. The model biases in the frequencies of distribution of rainfall extremes explain the wet and dry biases in different regions in the country. Overall, the inter-annual characteristics of both the rainfall and temperature extremes simulated by RegCM3 in Central India are well in phase with those found in the observed data.  相似文献   

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