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Predicting surface runoff from catchment to large region is a fundamental and challenging task in hydrology. This paper presents a comprehensive review for various studies conducted for improving runoff predictions from catchment to large region in the last several decades. This review summarizes the well-established methods and discusses some promising approaches from the following four research fields: (1) modeling catchment, regional and global runoff using lumped conceptual rainfall-runoff models, distributed hydrological models, and land surface models, (2) parameterizing hydrological models in ungauged catchments, (3) improving hydrological model structure, and (4) using new remote sensing precipitation data. [ABSTRACT FROM AUTHOR]

It is now common knowledge that many water resources stresses relate to access to water within a basin. Yi River Basin, a typical river basin characterized by intensive agricultural processes, significant population growth, and water management, has been undergoing grave water problems. In this paper, the long-term trend of precipitation and streamflow in Yi River Basin, from 1964 to 2010, was investigated via Mann-Kendall test. The change point occurred in the year 1965 dividing the long-term series into two periods. Climate elasticity method and linear regression method were implemented to quantify the impact of precipitation and human activities on runoff and presented basically consistent results of the percentage change in an annual runoff for the postchange period. The results reveal that the decline of annual runoff in postchange period is mainly attributed to precipitation variability of 53.66–58.25% and human activities of 46.34–41.74%, as estimated by climate elasticity method and linear regression method, respectively. This study detected the changes in the precipitation-streamflow relationship and investigated the possible causes in the Yi River, which will be helpful for providing a reference for the management of regional water resources. [ABSTRACT FROM AUTHOR]

Precipitation data from 30 stations in the Huaihe River basin (HRB), a climatic transitional zone in east China, were used to investigate the spatiotemporal variability and trends of extreme precipitation on multitimescales for the period 1961–2010. Results indicated that (1) the spatial pattern of the annual precipitation, rainy days, extreme precipitation, and maximum daily precipitations shows a clear transitional change from the south (high) to the north (low) in the HR; it confirmed the conclusion that the HRB is located in the transitional zone of the 800 mm precipitation contour in China, where the 800 mm precipitation contour is considered as the geographical boundary of the south and the north. (2) Higher value of the extreme precipitation intensity mainly occurs in the middle of the east and the central part of the basin; it reveals a relatively distinct west-east spatial disparity, and this is not in line with the spatial pattern of the extreme precipitation total, the sum of the precipitation in 95th precipitation days. (3) Annual precipitation of 22 stations exhibits increasing trend, and these 22 stations are located from the central to the northern part. There is no significant trend detected for the seasonal precipitation. The summer precipitation exhibits a larger change range; this might cause the variation of the flood and drought in the HBR. However, the increasing trend in winter precipitation may be beneficial to the relief of winter agricultural drought. Rainy days in 12 stations, mostly located in and around the central northeastern part, experienced significant decreasing trend. Extreme precipitation days and precipitation intensity have increasing trends, but no station with significant change trend is detected for the maximum precipitation of the basin. (4) The spatiotemporal variability in the HRB is mainly caused by the geographic differences and is largely influenced by the interdecadal variations of East Asian Summer Monsoon in eastern China. The output of this paper could provide references for the practical decision making and integrated basin management of Huaihe River basin. [ABSTRACT FROM AUTHOR]

This study analyzes the variation trends of temperature and precipitation in the Dadu River Basin of China based on observed records from fourteen meteorological stations. The magnitude of trends was estimated using Sen’s linear method while its statistical significance was evaluated using Mann-Kendall’s test. The results of analysis depict increase change from northwest to southeast of annual temperature and precipitation in space. In temporal scale, the annual temperature showed significant increase trend and the annual precipitation showed increase trend. For extreme indices, the trends for temperature are more consistent in the region compared to precipitation. This paper has practical meanings for an effective management of climate risk and provides a foundation for further study of hydrological situation in this river basin. [ABSTRACT FROM AUTHOR]

Downscaling improves considerably the results of General Circulation Models (GCMs). However, little information is available on the performance of downscaling methods in the Andean mountain region. The paper presents the downscaling of monthly precipitation estimates of the NCEP/NCAR reanalysis 1 applying the statistical downscaling model (SDSM), artificial neural networks (ANNs), and the least squares support vector machines (LS-SVM) approach. Downscaled monthly precipitation estimates after bias and variance correction were compared to the median and variance of the 30-year observations of 5 climate stations in the Paute River basin in southern Ecuador, one of Ecuador’s main river basins. A preliminary comparison revealed that both artificial intelligence methods, ANN and LS-SVM, performed equally. Results disclosed that ANN and LS-SVM methods depict, in general, better skills in comparison to SDSM. However, in some months, SDSM estimates matched the median and variance of the observed monthly precipitation depths better. Since synoptic variables do not always present local conditions, particularly in the period going from September to December, it is recommended for future studies to refine estimates of downscaling, for example, by combining dynamic and statistical methods, or to select sets of synoptic predictors for specific months or seasons. [ABSTRACT FROM AUTHOR]

This paper is focused on the probability modeling with a range of distribution models over two inland river basins in China, together with the estimations of return levels on various return periods. Both annual and seasonal maximum precipitations (MP) are investigated based on daily precipitation data at 13 stations from 1960 to 2010 in Heihe River and Shiyang River basins. Results show that GEV, Burr, and Weibull distributions provide the best fit to both annual and seasonal MP. Exponential and Pareto 2 distributions show the worst fit. The estimated return levels for spring MP show decreasing trends from the upper to the middle and then to the lower reaches totally speaking. Summer MP approximates to annual MP both in the quantity and in the spatial distributions. Autumn MP shows a little higher value in the estimated return levels than Spring MP, while keeping consistent with spring MP in the spatial distribution. It is also found that the estimated return levels for annual MP derived from various distributions differ by 22%, 36%, and 53% on average at 20-year, 50-year, and 100-year return periods, respectively. [ABSTRACT FROM AUTHOR]

Data analysis and characterization of precipitation in the Haihe River Basin (HRB) of China are required for management practices for the purpose of flood water control and utilization. In the companion paper, we presented precipitation data in the HRB during 1951-2010 and reported its basic statistics such as temporal trend and spatial variability. In this study, spatiotemporal variability on the precipitation was further investigated comprehensively for the underlying physics and the implication to water resource management. During the summer flood season of the study area, basin-wide precipitation was negatively correlated to average NINO3.4 index. Spatially, summer precipitation was correlated with gridded sea surface temperature (SST) observed in the eastern tropic Pacific Ocean and the western tropic Indian Ocean. SST in two representative areas was identified as potential predictors for precipitation in the HRB. No spatial or temporal correlations were confirmed between precipitation and soil moisture as annual averages in the study area. Copula analysis suggested about 40% possibility in a year with a potential for cross-watershed water diversion within HRB. [ABSTRACT FROM AUTHOR]

Floods and droughts are more closely related to the extreme precipitation over longer periods of time. The spatial and temporal changes and frequency analysis of 5-day and 10-day extreme precipitations (PX5D and PX10D) in the Huai River basin (HRB) are investigated by means of correlation analysis, trend and abrupt change analysis, EOF analysis, and hydrological frequency analysis based on the daily precipitation data from 1960 to 2014. The results indicate (1) PX5D and PX10D indices have a weak upward trend in HRB, and the weak upward trend may be due to the significant downward trend in the 21st century, (2) the multiday (5-day and 10-day) extreme precipitation is closely associated with flood/drought disasters in the HRB, and (3) for stations of nonstationary changes with significant upward trend after the abrupt change, if the whole extreme precipitation series are used for frequency analysis, the risk of future floods will be underestimated, and this effect is more pronounced for longer return periods. [ABSTRACT FROM AUTHOR]

This study analysed the temporal and spatial changes in the water yield coefficient (WYC), which represents the ratio of the gross amount of water resources to precipitation. Factors such as precipitation, rainstorm days, rainless days, vegetation cover change, and land use/cover change were considered to determine the causes of these changes. The results led to the following conclusions: (1) The average annual WYC of the Huang-Huai-Hai River Basin is between 0.03 and 0.58, with an average value of 0.17, which is smaller than the national average WYC of 0.4. (2) Temporally, the WYC varied slightly, with the western part showing a negative trend and the eastern part showing a positive trend. The WYC is positively correlated with precipitation, rainstorm days, and the normalized difference vegetation index (NDVI) and negatively correlated with rainless days. However, a slower change in NDVI produced a faster change in WYC. In areas with land use types exhibiting a large evapotranspiration decrease, the rate of change in the WYC increased. (3) Spatially, the distribution is fairly regular, exhibiting a gradual increase from the northern part of the Yellow River Basin (WYC < 0.1) to the surrounding areas. When the WYC is correlated with precipitation, rainstorm days, rainless days, and NDVI, the R2 values of the linear fitting results are 0.98, 0.91, 0.96, and 0.73, respectively. The WYC is positively correlated with precipitation, rainstorm days, and vegetation coverage and negatively correlated with rainless days, but the correlation coefficient is greatly influenced by the precipitation characteristics and land use types. In areas featuring high proportions of land use types associated with high evapotranspiration, the average WYC is low. [ABSTRACT FROM AUTHOR]