Search

Daily precipitation data from 1951 to 2010 at 33 meteorological stations in five provinces/cities, including Sichuan Province, Yunnan Province, the Guangxi Zhuang Autonomous Region, Guizhou Province and Chongqing City, are used to partition the study area based on precipitation and analyze the spatiotemporal distribution of extreme precipitation. The rotated empirical orthogonal function (REOF) analysis method is used to divide the study area into five parts according to precipitation. The precipitation exhibited greater fluctuations in the last two decades. This finding indicates that extreme precipitation events are increasing. The frequent occurrence of extreme precipitation has made drought and flood disasters more serious. The Mann–Kendall test (M–K test) and moving t test methods are used to analyze the jump and monotonic trends of extreme precipitation indices. It is determined that extreme precipitation indices, including Rx1d, Rx5d, R95p, R99p, CWD and R10 mm, exhibited a weak upward trend during the past 60 years, suggesting that the precipitation amount in the study area decreased slightly, but the maximum daily precipitation amount (Rx1d) and the extremely wet day precipitation (R99p) increased. This finding indicates that precipitation is more concentrated and the extreme precipitation is more serious. The jump for most of the extreme precipitation indices occurred in the 1990s. In terms of spatial scale, extreme precipitation indices, except CDD and CWD, exhibited an increasing trend from the northwest to the southeast. The regions with especially high or low values are easy to identify. Drought risk in northwest Sichuan and the junction of Sichuan and Yunnan is higher. Guangxi Zhuang Autonomous Region and southern part of Yunnan Province have a higher flood risk. The trends of nine extreme precipitation indices also demonstrated the spatial differences. There are more stations exhibiting upward trends than stations showing downward trends for six extreme precipitation indices. The risk of drought/flood may increase in Yunnan and Guangxi, and the storm flood risk in Chongqing exhibited an increasing trend.

In order to analyse the long-term trend of precipitation in the Asian Pacific FRIEND region, records from 30 river basins to represent the large range of climatic and hydrological characteristics in the study area are selected. The long-term trend in precipitation time series and its association with the southern oscillation index (SOI) series are investigated. Application of the nonparametric Mann–Kendall test for 30 precipitation time series has shown that only four of these 30 time series have a long-term trend at the 5% level of significance. Nevertheless, most of the records tend to decrease over the last several decades. The dataset is further divided geographically into northern, middle, and southern zones, with 20°N and 20°S latitude as the dividing lines. The middle zone has the greatest variation and the southern zone the least variation over the past century. Also, the southern zone has greater variation during the past 30 years. The association between precipitation and SOI is investigated by dividing the precipitation records of each station into El Nino, La Nina, and neutral periods. The Wilcoxon rank-sum test showed that differences in precipitation for the three classes were most marked in the southern zone of the study area. The frequencies of below- and above-average precipitation for El Nino, La Nina, and neutral periods are estimated for the 30 precipitation time series as well. The results show that the frequencies of precipitation under each set of conditions, with lower precipitation generally associated with El Nino periods in the southern zone. Copyright © 2005 John Wiley & Sons, Ltd.

Runoff data were analyzed from the semihumid 21.2 km² Goodwin Creek Experimental Watershed (GCEW) in northern Mississippi to examine watershed response over a range of scales. Runoff is monitored at the GCEW outlet and in 13 subcatchments, ranging in area from 0.06 to 17.6 km². Previous data-based studies have shown that simple scaling theory fails to describe scaling of flood quantiles in large watersheds, and there is a fundamental change in scaling behavior in semihumid watersheds at an area of approximately 100 km². It has been found that flood quantiles in nearly all subbasins in the GCEW are self-similar as described by simple scaling theory. It has also been found that expected values of peak flows during single runoff events are described by a power law function of catchment area. The primary reasons why flood quantiles are self-similar on Goodwin Creek are that precipitation is relatively uniform over the basin; peak discharges in smaller catchments are highly correlated with rainfall rates; nearly the entire watershed regularly contributes to runoff and; the groundwater table plays little role in runoff production.

In large river basins, there may be considerable variations in both climate and land use across the region. The evapotranspiration that occurs over a basin may be drastically different from one part of the region to another. The potential influence of these variations in evapotranspiration estimated for the catchment is weakened by using a spatially based distributed hydrological model in such a study. Areal evapotranspiration is estimated by means of approaches requiring only meteorological data: the combination equation (CE) model and the complementary relationship approach—the complementary relationship areal evapotranspiration (CRAE) and advection–aridity (AA) models. The capability of three models to estimate the evapotranspiration of catchments with complex topography and land-use classification is investigated, and the models are applied to two catchments with different characteristics and scales for several representative years. Daily, monthly, and annual evapotranspiration are estimated with different accuracy. The result shows that the modified CE model may underestimate the evapotranspiration in some cases. The CRAE and AA models seem to be two kinds of effective alternatives for estimating catchment evapotranspiration. Copyright © 2003 John Wiley & Sons, Ltd.

The primary objective of this study is to investigate the possibility of including more temporal and spatial information on short-term inflow forecasting, which is not easily attained in the traditional time-series models or conceptual hydrological models. In order to achieve this objective, an artificial neural network (ANN) model for short-term inflow forecasting is developed and several issues associated with the use of an ANN model are examined in this study. The formulated ANN model is used to forecast 1- to 7-h ahead inflows into a hydropower reservoir. The root-mean-squared error (RMSE), the Nash–Sutcliffe coefficient (NSC), the A information criterion (AIC), B information criterion (BIC) of the 1- to 7-h ahead forecasts, and the cross-correlation coefficient between the forecast and observed inflows are estimated. Model performance is analysed and some quantitative analysis is presented. The results obtained are satisfactory. Perceived strengths of the ANN model are the capability for representing complex and non-linear relationships as well as being able to include more information in the model easily. Although the results obtained may not be universal, they are expected to reveal some possible problems in ANN models and provide some helpful insights in the development and application of ANN models in the field of hydrology and water resources. Copyright © 2002 John Wiley & Sons, Ltd.

The water resource issue is one of the most significant problemsthat the Yellow River basin will face this century, and one which has received much attention by public and government for several years. Water authorities will face great challenges in meeting the in-stream flow requirements and providing more water for growing populations, industry and agriculture. In order toevaluate the sustainability of the water resource system inthe study area, an object-oriented system dynamics approachhas been used to develop a model for the water resourcessystem in the Yellow River basin, which is referred to asthe Water Resources System Dynamics (WRSD) model. It hasbeen developed for simulating a water resource system andcapturing the dynamic character of the main elements affectingwater demand and supply in the study area. For thebusiness-as-usual (BaU) scenario, the water demands in theYellow River basin are estimated 50.9, 56.5, and 59.5billion m3 for 2010, 2020, and 2030. The existing andpotential water supplies from surface water, aquifers andtreated waste-water are estimated, and potential waterdemands for domestic, industrial and agricultural uses areprojected. Various water supply and demand scenarios havethen been explored by changing variables and parameters,and the sustainability index of the water supply system isestimated for different sub-regions over various periods.

Based on the stochastic and phenomenological aspects of hydrological processes, a conceptually based stochastic point process (SPP) model for daily stream-flow generation is proposed in this paper. In which, storms are defined by a stochastic point process with marked values. All the random variables defining the process are assumed to be mutually independent, which constitutes a compound Poisson point process. The direct surface runoff is regarded as occurring from storage in a cascade of surface linear reservoirs and is responsible for the short-term variation of the daily stream flows. The baseflow component is considered as coming from subsurface/groundwater storage and is responsible for the long-term persistence of the storm time-series. This type of model is proposed as a more realistic model of daily stream flow than models based on pure stochastic processes. Studies on the instantaneous unit hydrograph and the mechanism of baseflow could thereby provide some parameters for this model. Copyright © 2002 John Wiley & Sons, Ltd.

A decision support system (DSS) for the integration of hydrologic process modeling and risk evaluation of the surface water management alternatives in a river basin is developed. The DSS, named CTIWM, is aimed at supporting the testing and evaluation of water management policies and at facilitating integration of user-selected scenarios into planning strategies of the water resource system in the Chikugo River basin, a multipurpose multireservoir system. CTIWM uses a module library that contains compatible modules for simulating a variety of hydrologic processes. Different numerical models are invoked through a user interface menu, which facilitates communications between users and models in a friendly way. The source code was developed by using object-oriented programming techniques. The result shows that the use of DSSs may effectively improve the speed and quality of water management and give users more flexibility in analyzing different scenarios.

Since the introduction into flood risk analysis, the partial duration series method has gained increasing acceptance as an appealing alternative to the annual maximum series method. However, when the base flow is low, there is clustering in the flood peak or flow volume point process. In this case, the general stochastic point process model is not suitable to risk analysis. Therefore, two types of models for flood risk analysis are derived on the basis of clustering stochastic point process theory in this paper. The most remarkable characteristic of these models is that the flood risk is considered directly within the time domain. The acceptability of different models are also discussed with the combination of the flood peak counted process in twenty years at Yichang station on the Yangtze river. The result shows that the two kinds of models are suitable ones for flood risk analysis, which are more flexible compared with the traditional flood risk models derived on the basis of annual maximum series method or the general stochastic point process theory.

An attempt of using stochastic hydrologic technique to assess the intrinsic risk of reservoir operation is made in this study. A stochastic simulation model for reservoir operation is developed. The model consists of three components: synthetic generation model for streamflow and sediment sequences, one-dimensional delta deposit model for sediment transport processes in reservoirs, and simulation model for reservoir operation. This kind of integrated simulation model can be used to simulate not only the inflow uncertainty of streamflow and sedimentation, but also the variation in operation rules of reservoirs. It is herein used for the risk assessment of a reservoir, and the simulation is performed for different operation scenarios. Simulation for the 100-year period of sediment transport and deposition in the river-reservoir system indicates that the navigation risk is much higher than that of hydropower generation or sediment deposition in the reservoir. The risk of sediment deposition at the river-section near the backwater profile is also high thereby the navigation at the river-segment near this profile takes high risk because of inadequate navigation depth.