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In this paper, a distributed catchment-hydrology model and a physically based lake hydrodynamic model were used to simulate the large-scale and highly dynamic lake catchment system of Poyang Lake, in the middle reach of the Yangtze River basin, China. The simulation of the hydrodynamics of the lake is a significant extension to previous efforts to simulate Poyang Lake's considerable variability in lake extent and flow rates. Further, the combination of the distributed catchment-hydrology model and the lake-hydrodynamic model, applied to a highly dynamic and large-scale system, is a rare attempt to develop a physically based management model of this complexity and scale. Model calibration and validation were undertaken to evaluate the model's performance and to enhance its effectiveness in simulating catchment discharges, lake water levels, lake water surface areas, and lake flow patterns. The results showed a satisfactory agreement with field observations, with Nash-Sutcliffe efficiencies of 0.71-0.84 for catchment discharges, 0.88-0.98 for lake water levels, and 0.80 for lake outflows during the calibration period. The Nash-Sutcliffe efficiency values for the validation period, ranging from 0.62 to 0.97, were largely consistent with the calibration values. Further investigation of the results showed that the modeling approach simulated adequately the lake hydrodynamics in terms of the flow fields within the lake and the seasonal changes in the lake water surface area. The outcomes of this paper will benefit future modeling efforts by providing a tool for predicting the hydrology of Poyang Lake and its catchment under climate variability and land-use changes. [ABSTRACT FROM AUTHOR]

Available water resources are decreasing in river basins around the world. Some reseachers have suggested various indicators and methods that should be used to allocate water resources. This paper attempts an integrated approach to water allocation that accounts for a wide range of factors at the river basin level. Using the Hai, Huai, and Yellow River Basins of Shandong Province in China, 19 indicators were assimilated into a water scarcity index and weighted based on surveys collected from 82 multidisciplinary experts. Fuzzy set probability was then used to quantify water scarcity for each river basin. A water allocation method was also calculated using 13 indicators and objectively weighted using the analytical hierarchy process. Results show that all river basins in Shandong Province have severe water scarcity and highlight that economic factors play the most critical role in water scarcity, followed by water supply factors then water demand. Water allocation indicators were prioritized according to water resource pressure and utilization proportionality among districts in the Huai River Basin. The results should provide direction for future research. [ABSTRACT FROM AUTHOR]

The formation and geomorphic evolution of the Jiuduansha Shoal are investigated over the past 50 years in this paper. The sedimentary processes, formation, and geomorphic evolution of the Jiuduansha Shoal in the Yangtze River Estuary, eastern China, are analyzed based on digitized sea maps from 1945 to 2001, satellite images from 1975 to 2001, and field survey data in the spring-neap tidal cycle in the dry and flood seasons in 2003. The suspended sediment concentration and hydrodynamics of the North Passage and South Passage during the dry and flood seasons in the spring-neap tidal cycle in 2003 were investigated, and relations between the North Passage and South Passage of the Jiuduansha Shoal are analyzed. Results show that seasonal and spring-neap tidal cycle variations in sediment and water discharge from the drainage basin correspond to erosion and deposition on the Jiuduansha Shoal. The results and data can provide useful information for the management of the Yangtze River Estuary and restoration of the estuarine tidal flat ecology. [ABSTRACT FROM AUTHOR]

Base-flow separation has long been an important research topic in hydrology. In the Yellow River Basin in China, base flow is of special concern in the headwater catchments because of its importance for integrated water resources management in the basin as a whole. To quantify base flow in the headwater catchments of the Yellow River Basin for 1956–2000, the two-parameter Kalinin method has been proposed with improved implementation procedures and parametrization techniques. Results show that base flow contributes a larger proportion to streamflow in the headwater catchments than that of surface flow, but with a rather low variation. The results are consistent with that of the other two digital filter methods. Sensitivity analysis of parameter performance in the Kalinin method shows, in detail, that the hydrograph of separated base flow is sensitive to a recession constant, and the other parameter (β) is highly related to the base-flow index and the ratio of base flow against surface flow (δ). [ABSTRACT FROM AUTHOR]

Urban land-use planning is becoming increasingly complex in China because it requires estimating the future urban extent and balancing its various aspects, e.g., provision of enough housing and employment opportunities and preservation of the environment. This paper presents an integrative approach to the problem of sustainable land-use planning. Specifically, an urban growth simulation tool, a cellular automata model, was used to determine the extent of the urban area, and a neural network approach was used to quantitatively predict the land-use structure in the projected year. A multiobjective optimization genetic algorithm was then developed to search for Pareto-optimal urban land-use plans within the urban extent determined by the urban growth model. To search for a sustainable urban land-use plan, social, economic, and environmental objectives were defined that reflect the multiple objectives of the urban system. In addition to these nonspatial goals, objectives concerning the spatial distribution of land usages were proposed. These are classified as local and global spatial objectives. A case study of the Donghu Lake watershed was conducted. Donghu Lake is one of the largest downtown lakes in central China, and the watershed area is undergoing rapid urbanization and suffering from nonpoint source water pollution. The study was carried out to validate the proposed method, and it demonstrated that the models are appropriate for areas undergoing urban expansion. [ABSTRACT FROM AUTHOR]

Growing concerns have been given to parameter uncertainty in hydrological modeling because of the associated effects on water resource management. In this study two uncertainty analysis methods, the sequential uncertainty fitting algorithm (SUFI-2) and the generalized likelihood uncertainty estimation (GLUE), were employed to analyze the uncertainty of surface flow and sediment yield modeling results by the soil and water assessment tool (SWAT) model. The two methods were also compared in terms of the capability in quantifying parameter and prediction uncertainties and the computational efficiency. The results showed that the SUFI-2 method was capable of examining the uncertainty by using the Latin hypercube sampling scheme. It also demonstrated the advantages in analyzing the effects of uncertainties for distributed hydrological models with complex structure and high computational demands. The GLUE method is specialized in reflecting parameter correlations and uncertainties associated with parameters and predictants. [ABSTRACT FROM AUTHOR]

Water scarcity in Huaihe River, the sixth largest river in China, is stressed by the changing climate and intense human activities, especially in the headwater area. Xixian, situated in the upper reaches of the Huai River, is an important agricultural county with a population of more than one million people, and nearly one billion kg of crop yield every year. The projected climate changes and increasing population are expected to further complicate the utilization of already stressed water resources, endangering the agricultural activities in this area. There is pressing need for a watershed model to better understand the interaction between land use activities and hydrologic processes and to support sustainable water use. This study evaluated the performance of the Soil and Water Assessment Tool ( SWAT) for hydrologic modeling in the Xixian basin; three methods of calibration and uncertainty analysis (sequential uncertainty fitting, generalized likelihood uncertainty estimation, and parameter solution) were compared and used to set up the model. The results showed that SWAT performs well in the Xixian River basin, that the hydrological water balance analysis of the basin indicated that base flow is an important aspect of the total discharge within the study area, and that more than 60% of the annual precipitation is lost through evapotranspiration. The calibrated model can be used to further analyze the effects of climate and land use changes and to investigate the effects of different cultivation styles and management scenarios on local water resources. [ABSTRACT FROM AUTHOR]

In this study, the spatial and temporal patterns of trends for reference evapotranspiration (RET) at 34 meteorological stations (between 1957 and 2007) in the Haihe River basin, China, were analyzed using the Mann-Kendall (MK) test and the Sen's method. To reveal the possible causes and main driving forces of the changing patterns of RET, the spatial distribution and temporal patterns of trends for four meteorological variables (i.e., temperature, wind speed, relative humidity, and sunshine duration) were examined for each station. In addition, partial relative analysis between RET and meteorological variables and a sensitivity analysis of RET to meteorological variables were conducted. The results show the following: First, the Haihe River basin is dominated by a significant decreasing MK trend in annual RET at >95% confidence level, which is observed at most stations in the eastern and southern areas of the basin. There are no observed trends or significant increasing MK trends in annual RET in the western plateau. For the intra-annual variability of RET, similar spatial-changing patterns are only observed in summer. Second, there are no obvious trends in RET from the late 1950s to the early 1970s for the whole basin. However, opposite trends of RET in the plateau area are identified after the 1970s in comparison with those in the plain and mountain area of the Haihe River basin. These two trends become significant in the late 1990s. Third, wind speed and sunshine duration are recognized as the two major driving forces for the decreasing trends in RET. Relative humidity is mainly responsible for the increasing trends in the western Haihe River basin during recent decades. [ABSTRACT FROM AUTHOR]

A distributed rainfall-runoff model, Grid-Xinanjiang model based on the topographical information of each grid cell extracted from the digital elevation model (DEM), was developed to simulate the hydrologic processes within watersheds. The water exchange among grids within the watershed and the runoff routing along the river drainage networks are taken into consideration in the model. The Grid-Xinanjiang model was applied to the two watersheds in China for flood simulations. The performance of the developed model was compared with that of the original Xinanjiang model. Initial tests show that the Grid-Xinanjiang model can perform well as the original model in terms of estimates of streamflow and of the model efficiency coefficient. All of the qualified ratios relative to peak flow, runoff, and peak time for the two models applied to the Misai watershed and the Xixian watershed are more than 88%. The Grid-Xinanjiang model outperformed the original model in predicting flood runoff and outlet hydrographs, especially in the larger watershed. The simulation results show the robust capacity of obtaining spatial distributions of hydrologic variables over the original Xinanjiang model, and also revealed that runoff yield has large temporal and spatial variability during storm period and the runoff response is sensitive to the antecedent soil moisture, topography, and spatial distribution of rainfall. [ABSTRACT FROM AUTHOR]

To simulate daily runoff in the middle and lower regions of the Changjiang (Yangtze River) basin, we used an integrated, spatially distributed model consisting of the Hydrological Simulation Program—FORTRAN (HSPF) and two newly developed submodels, the paddy runoff model (PRM), simulating the runoff from paddy fields, and the lake discharge model (LDM), simulating the hydraulic effect of the Changjiang mainstream on the discharge from neighboring lakes. In the PRM, the ratios of the simulated monthly evapotranspiration relative to the observed potential evaporation were close to or exceeded 1.0 in both of the test subcatchments in the full ponding period with plentiful irrigation water, corresponding to many previous observations of evapotranspiraion rates from paddy fields. Whereas the original HSPF could not consider the backwater effect of the water level in the mainstream, the daily discharge from the lakes simulated by the LDM was dependent on the water level in the mainstream and corresponded to the observed data at the hydrologic stations on the channels connecting each lake with the mainstream, as shown by the daily R2 (Nash–Sutcliffe coefficient) values for Dongting Lake (0.89 in the calibration period, 0.90 in the verification period) and for Poyang Lake (0.84 in the calibration period). For the runoff response from the whole basin simulated by the integrated model, the deviations of runoff volume and values of R2 were -4.2% and 0.95 in the calibration and verification periods and 1.6% and 0.93, respectively, at Datong hydrologic station, which shows the good applicability of this model as a tool for management of water resources in the Changjiang basin. [ABSTRACT FROM AUTHOR]

Runoff simulation and prediction in watersheds is an important and essential step in water management systems, safety yield computations, environmental disposal, design of flood control structures, and so on. In this study, the runoff records of Linshan Watershed, Sichuan Province, PRC, during 1984–1993 are presented and used as samples for predictions. The time-delay neural network (TDNN) model combined with a genetic algorithm is proposed and used to predict the nonlinear relationship and to analyze the characteristics of runoff time series in the Linshan Watershed area. Based on analyzing the whole runoff process—for example, the average, maximum, and standard deviation—during said period, the equal length for training and testing is defined. The optimum TDNN structure of August 20, 2001 has been obtained by gradually increasing the time delay to avoid the limitations of the TDNN model. Comparisons between training and testing show that the forecasting model of the runoff level using TDNN combined with genetic algorithms is generally satisfactory and effective, with slight underpredictions at some points. [ABSTRACT FROM AUTHOR]

Investigating the impact of climate change at regional scales is of importance for adaption purposes. In this study, a regional climate model PRECIS is for the first time run for East China on a spatial resolution of 25 km using two global climate models (GCMs) ECHAM5 and HadCM3 as boundary data under A1B emission scenario. The baseline period is 1961-1990. An upgraded quantile mapping method is used to correct the bias of PRECIS outputs for providing reliable future climate change projections (2011-2040). The regional climate model is then coupled with a mesoscale distributed hydrology soil vegetation model (DHSVM), to investigate the impact of climate change on future water resources in the Jinhua River Basin, East China. The hydrological model is calibrated and validated on a daily basis and show reasonable performance. The results show that under both GCMs, statistically, no significant changes in future annual runoff are projected. However, large changes in seasonal and monthly runoff are projected. ECHAM5 projects large decreases in summer () and autumn () and slight increases in spring and winter whereas HadCM3 projects large decreases in autumn () and large increases in spring (28.7%) and winter (60%). The seasonal changes in precipitation in this region are the main driving force for the changes in future runoff. [ABSTRACT FROM AUTHOR]