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This study modified the BTOPMC (Block-wise TOPMODEL with the Muskingum-Cunge routing method) distributed hydrological model to make it applicable to semi-arid regions by introducing an adjustment coefficient for infiltration capacity of the soil surface, and then applied it to two catchments above the dams in the Karun River basin, located in semi-arid mountain ranges in Iran. The application results indicated that the introduced modification improved the model performance for simulating flood peaks generated by infiltration excess overland runoff at a daily time scale. The modified BTOPMC was found to fulfil the need to reproduce important signatures of basin hydrology for water resource development, such as annual runoff, seasonal runoff, low flows and flood flows. However, it was also very clear that effective model use was significantly constrained by the scarcity of ground-gauged precipitation data. Considerable efforts to improve the precipitation data acquisition should precede water resource development planning. EditorD. Koutsoyiannis [ABSTRACT FROM AUTHOR]

This article presents a study regarding the hydrological simulation of large basins. It discusses that topography is a significant factor in hillslope hydrology. The TOPMODEL concept has many advantages in this respect and it uses a topographical index derived from a simplified steady state assumption of mass balance and empirical equations of motion over a hillslope. The study aims to introduce Block-wise TOPMODEL as an extension of the TOPMODEL concept in a grid based model for distributed hydrological simulation of large river basins.

This article discusses a study which estimated the evolution of vegetation cover and its hydrological impact in the Mekong River basin in the 21st century. The researchers used climatic predictions, a dynamic global vegetation model, terrestrial biogeochemical model, and the distributed hydrological model. They indicated a significant change in vegetation type mainly on the Tibetan Plateau in China and in mountainous areas, with the degree of change differing for each special report on emissions scenario. They suggested that changes in river discharge will be slowed due to changes in evapotranspiration.

This article discusses a study which investigated the Mekong River basin hydrology for the 1980-2000 period using a grid-based distributed hydrological model called Yamanashi Hydrological Model. The study evaluated the performance of the model using data observed at different locations. It analyzed the seasonal variations of climatic and hydrological characteristics of the basin such as soil moisture, ground water saturation deficit, runoff, precipitation, evapotranspiration, etc. The study found no significant trend in the precipitation, discharge, or soil moisture state of the basin during the simulated period, though there are some seasonal variations which seem to be natural.

The hydrological response to climate change in the Tarim River Basin was investigated by analysing the hydrological, temperature and precipitation data of the past 50 years. The long-term trend of the hydrological time-series, including air temperature, precipitation, and streamflow, was examined by using both parametric and non-parametric techniques and the plausible association between streamflow and climate change by the method of grey correlation analysis. The results show that the study area became warmer in the last few decades. The air temperature experienced a significant monotonic increase by 5%; the precipitation showed a significant decrease in the 1970s and then a major increase in the 1980s and 1990s, with average annual precipitation up by 6-8 mm per decade. A step change occurred in both temperature and precipitation around 1986, with mean temperature and precipitation increasing from 67°C and 146 mm before 1986 to 7.3°C and 180 mm respectively after 1986. The temperature has risen by nearly 1 °C over the past 50 years, possibly resulting from the impact of global climate change. Streamflows in the Aksu River and the Yarkant River have shown a significant (P < 0.05) tendency of increase. This is particularly the case for the Aksu River. The coefficients of streamflow increase in the Aksu and Yarkant Rivers are 0.41 and 0.13 respectively. The results of grey correlation analysis show that in the Aksu River, which is located in the northwest of the basin, the impact of precipitation on streamflow is much greater than that of temperature. However, in the Hotan River, which is located in the southwest of the basin, the impact of temperature on streamflow is much greater than that of precipitation. This is likely to be related to the geographic distribution of the headstreams of the rivers. [ABSTRACT FROM AUTHOR]

The article discusses various reports published within the issue, including one by H. A. P. Hapuarachichi et al. on the hydrology of the Mekong River Basin and another by T. Nobuhiro et al. on the evapotranspiration from a meteorological observation tower in an evergreen broadleaf forest in Kampong Thorn, Central Cambodia.

Summary: In this paper, we present a method to account for modeling uncertainties while regionalising model parameters. Linking model parameters to physical catchment attributes is a popular approach that enables the application of a conceptual model to an ungauged site. The functional relationship can be derived either from the calibrated model parameters (direct calibration method) or by calibrating the functional function (regional calibration method). Both of these approaches are explored through a case study involving TOPMODEL and a number of small- to medium-sized humid basins located in various geographic and climatic regions around the globe. The predictive performance of the functional relationship derived using the direct calibration method (e.g., multiple regression, artificial neural network and partial least square regression) varied among the different schemes. However, the average of the model parameters estimated from regionalisation schemes based on direct calibration is found to be a better surrogate. Even with the use of a parsimonious hydrological model and with posing model calibration as a multi-objective problem, the model parameter uncertainty and its effect on model prediction were observed to be high and varied among the basins. Therefore, to avoid the effect of model parameter uncertainty on regionalization results, a regional calibration method that skips direct calibration of the hydrological model was implemented. This method was improved in order to take into account multiple objective criteria while calibrating regional parameters. The predictive performance of the improved regional calibration method was found to be superior to the direct calibration method, indicating that the identifiability of model parameters has an apparent effect on deriving predictive models for regionalisation. However, the regional calibration method was unable to uniquely identify the regional relationship, and the modeling uncertainties quantified using Pareto optimal regional relationships were considerable. Regionalisation schemes that are based on direct calibration do not explicitly account for the modeling uncertainties. Therefore, to account for these uncertainties in model parameters and regionalisation schemes, methods based on regionalisation of vectors of model parameters (i.e. regionalizing the vectors of equally likely values of model parameters) and posterior probability distribution of model parameters (i.e. estimating the posterior probability distribution of model parameters at ungauged sites by linking the entries of model parameters’ covariance matrix and the posterior mean of model parameter to the catchment attributes) are introduced. The uncertainties in model prediction as quantified from both methods closely followed the prediction uncertainties quantified from calibrated posterior probability distributions of model parameters. Moreover, though the prediction uncertainties associated with the regional calibration method as quantified from the Pareto optimal regional relationship were comparatively higher than those obtained from the direct calibration schemes, they were in close agreement with the prediction uncertainties quantified from the calibrated posterior probability distribution. The ensemble of simulated flows realized from the model parameters sampled from regionalized posterior probability distributions for five ungauged basins are also presented as validation of the proposed methodology. [Copyright &y& Elsevier]

Abstract: This paper focuses on parameter regionalization for the block-wise use of the TOPMODEL with the Muskingum–Cunge routing method (BTOPMC). Pre-determined quantitative relationships with physical basin characteristics are used to reduce uncertainty in parameter estimation and enable prediction in ungauged basins. BTOPMC parameter values, which have previously resulted in efficient model performance, are applied to ten Model Parameter Estimation Experiment (MOPEX) basins without any parameter adjustment to test model performance using ‘blind’ a priori parameter estimates. It is quantitatively shown that parameters can not be satisfactorily estimated a priori without parameter adjustment, either through calibration or transfer functions linking parameters to physical basin features, referred to as ‘improved’ a priori parameter estimation. To compare model performance using different parameter estimation techniques, BTOPMC parameters are re-estimated by automatic optimization. As anticipated, model performance improves significantly when these optimized parameters are used. Good correlation of model performance is also observed between the 19-year validation and 20-year calibration results when optimized parameters are used. This indicates that BTOPMC''s predictive accuracy depends strongly on calibration accuracy, implying that well-optimized parameter values can ensure the accuracy of model predictions. It appears reasonable to use optimized parameter values, selected from successful modelling applications, to make transfer functions which ‘improve’ a priori parameter estimates. The ‘improved’ a priori parameter estimation is achieved through multiple linear regression analysis relating BTOPMC parameters to soil and vegetation types within the basin being modelled. The results suggest that the preliminary parameter transfer functions are encouraging and that ‘improved’ a priori parameter estimation techniques have the potential to reduce parameter uncertainty and enable prediction in ungauged basins. To improve parameter estimation and predictive accuracy of the model, further research to determine more accurate values, and their relationship with physical basin characteristics, is needed. [Copyright &y& Elsevier]

Abstract: Many regional vulnerabilities in Asia are related to freshwater resources, whose major part comes from large rivers, with sources in high mountains. Hence, understanding of observed and projected changes in river discharge is of utmost importance. In the present contribution, results of studies devoted to observations (hydrological networks) and model-based projections of discharge in large rivers in Asia are presented. Even if changes in some observation records can be detected, their attribution is not easy, because the process of river discharge results from multiple factors. Hence, climatic background (observed and modelled changes in precipitation, evapotranspiration, soil moisture, snow cover and glaciers), and non-climatic factors (demography, socio-economy, withdrawals) play a role. Changes in river discharge extremes (high and low flows) are particularly important. Changes in discharges of large Asian rivers are of primary concern to the pursuit of sustainable development in the region. [Copyright &y& Elsevier]