Hydrological models must be carefully calibrated to ensure that predictions are scientifically sound and reliable. As a goodness-of-fit measure, an ideal threshold of the Nash-Sutcliffe efficiency coefficient ($E_{ns}$ ) has been reported to be 0.65, based on yearly and monthly simulation results with the soil and water assessment tool (SWAT). To further explore the use of $E_{ns}$ as a goodness-of-fit measure for daily runoff simulation with SWAT, the authors ran the model with five different parameter values, using Jinjiang River Basin on the southeast coast of China as the study area. In addition, to find how the model versions varied in predicting changes in flood and drought with changes in land use, each of the five model versions were run two times separately: once for the land use condition in 1985, and then again for the land use condition in 2006. The authors investigated the relationships between $E_{ns}$ variation and model accuracy and discussed the differences in predicted runoff due to land use change as caused by the five model versions. The results show that the coefficient of determination ($R^2$ ) was highly associated with $E_{ns}$ , with a high $R^2$ corresponding to a high $E_{ns}$ ; the $E_{ns}$ value was quite sensitive to simulation results of the maximum one-day (1d) runoff; 0.75; the $E_{ns}$ value was not sensitive to simulation results of the minimum 1d and seven-day (7d) runoff, and unlike the flood runoff, the errors in drought flow increased adversely with increased $E_{ns}$ , indicating the poor performance of the SWAT model regarding drought flows; and the variations in runoff simulations, due to the land use change, were sensitive to model version switching and were fundamentally similar to the changes in the error indicators said above. The five SWAT versions varied in performance ($E_{ns}$ ) in daily runoff simulation and had different measures of goodness-of-fit for various characteristics of the flood and drought processes. As a result, an $E_{ns}$ of 0.75 is suggested as a threshold for satisfactory simulation of maximum 1d discharge in the study watershed.

Based on monthly streamflow and precipitation data from 1960 to 2010 in the Jinjiang River Basin of China, Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were used to represent meteorological and hydrological drought, respectively. The response of hydrological drought to meteorological drought under the influence of Shanmei reservoir was investigated. The results indicate that SPI and SSI have a decreasing trend during recent several decades. Monthly scales of SSI series have a significant decreasing trend from November to the following February and a significant increasing trend from May to July at Shilong hydrological station. There are three significant periodic variations with a cycle of 6-7 years, 11-12 years, and 20-21 years for annual scales of SSI series. SPI series have the same periodic variations before the 1980s, but they have not been synchronous with SSI since the 1980s at Shilong due to influences of Shanmei reservoir, especially at the periodic variations of 20-21 years. The variation of the lag time of hydrological drought in response to meteorological drought is significant at the seasonal scale. The lag time of hydrological drought to meteorological drought extends one month on average in spring, summer, and autumn but about three months in winter.

This study presents a scaling analysis of the time development of clear-water scour depth at bridge piers. It shows that the widely-used exponential formula can be theoretically derived with scaling arguments. The derivation provides connections between the physical pier-scouring process and two empirical constants used in the formula. The dependence of the two constants on sediment coarseness is calibrated using published laboratory data with scour duration ranging from 49 to 1094 h. The analysis presented is restricted to conditions, including steady flow, clear-water scour, narrow circular cylindrical pier, and uniform sediment with low coarseness.

Hydrological models often perform poorly in simulating dry years in regions with large inter-annual variability in rainfall. We calibrated the Soil and Water Assessment Tool (SWAT) model to dry and wet years separately, using the semi-arid Barrett watershed on the west coast of USA as an example. We used hydrological and meteorological data from 1980–2010 to calibrate the SWAT model parameters, compared the monthly runoff results simulated by SWAT using a traditional calibration for the entire runoff series with results using a calibration with the wet and dry year series, and analyzed differences in the most sensitive parameters between the wet and dry year series. The results showed that (1) the SWAT model calibrated to the entire runoff series produced significant differences in simulation efficiency between the wet years and dry years, with lower efficiency during the dry years; (2) the calibration with separate wet and dry years greatly enhanced the SWAT model’s simulation efficiency for both wet and dry years; (3) differences in hydrological conditions between wet and dry years were represented by changes in the values of the six most sensitive parameters, including baseflow recession rates, channel infiltration rates, Soil Conservation Service (SCS) curve number, soil evaporation, shallow aquifer flow, and soil water holding capacity. Future work can attempt to determine the physical processes that underlie these parameter changes and their impact on the hydrological response of the semi-arid watersheds.