Hydrologic Estimation Methods And Analysis In Un-gauged Basins

Across the globe, water resource and the water environment are under threat as never before, which restricts the development of economy, and the major difficulty we are facing is that the hydrologic data what we need is scarce or even inexistent. Research in un-gauged basins has become more and more popular all over the world. According to the IAHS PUB (Prediction in Un-gauged Basins) Programme, the main works and conclusions in this paper were summarized as follows:(1) The different research methods used in un-gauged basins were reviewed and discussed. For predicting runoff in un-gauged basins, observation and experiment are often used in traditional hydrology; while the new theories and methods, such as RS, GIS, DEM, artificial neural networks, wavelets analysis, are widely used in modern hydrology.(2) The IHACRES model, the Xinanjiang model and the SCS model were introduced. The applicabilities of those models for runoff simulation in un-gauged basins were compared and discussed. It is shown that the more complex models may not absolutely perform better than the simpler models. When the parameters were transplanted to simulate runoff in un-gauged basins, similarity factors between the reference basin and the target basin, such as basin area and the distance between basins, should be considered seriously.(3) The uncertainty of parameters in these hydrological models was discussed. Strong equifinality exists in model calibration period. If the objective function R2 is the only criterion used to optimize the model parametrs, it may face with the large uncertainty.(4) Regional regression analysis method was used to estimate annual runoff in un-gauged basins. Since it considered almost all the factors, which influenced the runoff synthetically, the accuracy of simulation was higher than the traditional method of isograph.