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Results suggest that increased temperature could change the rate of evapotranspiration and the form of precipitation, subsequently influencing monthly streamflow patterns.
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Figure 5 Observed and simulated monthly streamflow depth of the Wujiang River watershed at four sub-basin outlets during 1960 2000.
The historical monthly streamflow data for Pahang River, which is a major river system in Malaysia that characterized by highly stochastic hydrological patterns, is used in the study.
Moreover, the monthly water temperature is predicted with more accuracy than monthly streamflow.
Thomas-Fiering model (based on Markov autoregressive model) has been adopted for generation of synthetic scenario (monthly streamflow series) and subsequently downscaling of modeled monthly streamflow to daily values was carried out.
The results indicate that the estimated monthly streamflow data compares favorably well with the observed data and this generated monthly streamflow data has been used to generate corresponding daily flow data.
Regionalization using mean annual and mean monthly streamflow values was used to delineate hydrologic regimes with distinct temporal flow variations.
BJP ensemble forecasts of monthly streamflow volumes are generally reliable in ensemble spread.
The NSCE value for monthly streamflow over a period of 22 years was 0.79.
Monthly streamflow forecasts with long lead time are being sought by water managers in Australia.
Finally, cloud forest conversion to pasture does not promote significant monthly streamflow change.
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