Abstract: In the Volta River Basin, flooding has been one of the most damaging natural hazards during the last few decades. Therefore, flood frequency estimates are important for disaster risk management. This study aims at improving knowledge of flood frequencies in the Volta River Basin using regional frequency analysis based on L-moments. Hence, three homogeneous groups have been identified based on cluster analysis and a homogeneity test. By using L-moment diagrams and goodness of fit tests, the generalized extreme value and the generalized Pareto distributions are found suitable to yield accurate flood quantiles in the Volta River Basin. Finally, regression models of the mean annual flood with the size of the drainage area, mean basin slope and mean annual rainfall are proposed to enable flood frequency estimation of ungauged sites within the study area.
Abstract: Accurate representation of the spatial distribution of snow water equivalent (SWE) in mountainous basins is critical for furthering the understanding of snow as a water resource, especially in the Western United States. To estimate the spatial distribution and total volume of SWE over mountainous basins, previous work has either assumed uniform snow density or used simple approaches to estimate density. This study uses over 1000 direct measurements of SWE and snow depth (from which density was calculated) in sampling areas that were physiographically proportional to a large (207 km2) mountainous basin in southwest Montana. Using these data, modeled spatial distributions of density and depth were developed and combined to obtain estimates of total basin SWE. Six estimates of SWE were obtained using varying combinations of the distributed depth and density models and were compared to the average of three different models that utilized direct measurements of SWE. Models utilizing direct SWE measurements varied by approximately 1% around their mean, while SWE estimates derived from combined depth and density models varied by over 14% around the same mean. This study highlights the need to carefully consider the spatial variability of density when estimating SWE based on snow depth in these environments.
Abstract: Trends in high, moderate, and low streamflow conditions from United States Geological Survey (USGS) gauging stations were evaluated for a period of 1951–2013 for 18 selected watersheds in South Dakota (SD) using a modified Mann-Kendall test. Rainfall trends from 21 rainfall observation stations located within 20-km of the streamflow gauging stations were also evaluated for the same study period. The concept of elasticity was used to examine sensitivity of streamflow to variation in rainfall and land cover (i.e., grassland) in the study watersheds. Results indicated significant increasing trends in seven of the studied streams (of which five are in the east and two are located in the west), nine with slight increasing trends, and two with decreasing trends for annual streamflow. About half of the streams exhibited significant increasing trends in low and moderate flow conditions compared to high flow conditions. Ten rainfall stations showed slight increasing trends and seven showed decreasing trends for annual rainfall. Streamflow elasticity analysis revealed that streamflow was highly influenced by rainfall across the state (five of eastern streams and seven of western streams). Based on this analysis, a 10% increase in annual rainfall would result in 11%–30% increase in annual streamflow in more than 60% of SD streams. While streamflow appears to be more sensitive to rainfall across the state, high sensitivity of streamflow to rapid decrease in grassland area was detected in two western watersheds. This study provides valuable insight into of the relationship between streamflow, climate, and grassland cover in SD and would support further research and stakeholder decision making about water resources.
Abstract: In this paper, the water level fluctuations of eight Ethiopian Rift Valley lakes were analyzed for their hydrological stability in terms of water level dynamics and their controlling factors. Long-term water balances and morphological nature of the lakes were used as bases for the analyses. Pettit’s homogeneity test and Mann–Kendall trend analysis were applied to test temporal variations of the lake levels. It is found that the hydrological stability of most of the Ethiopian Rift Valley lakes is sensitive to climate variability. In terms of monotonic trends, Lake Ziway, Hawassa, Abaya and Beseka experienced significant increasing trend, while Ziway, Langano and Chamo do not. In addition, homogeneity test revealed that Lake Hawassa and Abaya showed significant upward shift around 1991/1992, which was likely caused by climate anomalies such as the El Niño / Southern Oscillation (ENSO) phenomena. Lake Abiyata is depicted by its significant decreasing monotonic trend and downward regime shift around 1984/1985, which is likely related to the extended water abstraction for industrial consumption.
Abstract: An analysis of hydrological response to a multi-model approach based on an ensemble of seven snow models (SM; degree-day and mixed degree-day/energy balance models) coupled with three hydrological models (HM) is presented for a snowmelt-dominated basin in Canada. The present study aims to compare the performance and the reliability of different types of SM-HM combinations at simulating snowmelt flows over the 1961–2000 historical period. The multi-model approach also allows evaluating the uncertainties associated with the structure of the SM-HM ensemble to better predict river flows in Nordic environments. The 20-year calibration shows a satisfactory performance of the ensemble of 21 SM-HM combinations at simulating daily discharges and snow water equivalents (SWEs), with low streamflow volume biases. The validation of the ensemble of 21 SM-HM combinations is conducted over a 20-year period. Performances are similar to the calibration in simulating the daily discharges and SWEs, again with low model biases for streamflow. The spring-snowmelt-generated peak flow is captured only in timing by the ensemble of 21 SM-HM combinations. The results of specific hydrologic indicators show that the uncertainty related to the choice of the given HM in the SM-HM combinations cannot be neglected in a more quantitative manner in simulating snowmelt flows. The selection of the SM plays a larger role than the choice of the SM approach (degree-day versus mixed degree-day/energy balance) in simulating spring flows. Overall, the snow models provide a low degree of uncertainty to the total uncertainty in hydrological modeling for snow hydrology studies.