Flood water infiltrates ephemeral channels, recharging local and regional aquifers, and it is the main water source in hyperarid regions. Quantitative estimations of these resources are limited by the scarcity of data from such regions. The floods of the Kuiseb River in the Namib Desert have been monitored for 46 years, providing a unique data set of flow hydrographs from one of the world's hyperarid regions. The study objectives were to: (1) subject the records to quality control; (2) model flood routing and transmission losses; and (3) study the relationships between flood characteristics, river characteristics and recharge into the aquifers. After rigorous quality-testing of the original gauge-station data, a flood-routing model based on kinematic flow with components accounting for channel-bed infiltration was constructed and applied to the data. A simplified module added to this routing model estimates aquifer recharge from the infiltrating flood water. Most of the model parameters were obtained from field surveys and GIS analyses. Two of the model parameters-Manning's roughness coefficient and the constant infiltration rate-were calibrated based on the high-quality measured flow data set, providing values of 0.025 and 8.5 mm/h, respectively. This infiltration rate is in agreement with that estimated from extensive direct TDR-based moisture measurements in the vadose zone under the Kuiseb River channel, and is low relative to those reported for other sites. The model was later verified with additional flood data and observed groundwater levels in boreholes. Sensitivity analysis showed the important role of large and medium floods in aquifer recharge. To generalize from the studied river to other streams with diverse conditions, we demonstrate that with increasing in infiltration rate, channel length or active channel width, the relative contribution of high-magnitude floods to recharge also increases, whereas medium and small floods contribute less, often not reaching the downstream parts of the arid ephemeral river at all. For example, more than three-quarters of the floods reaching the downstream Kuiseb River (with an infiltration rate of 8.5 mm/h) would not have reached similar distances in rivers with all other properties similar but with infiltration rates of 50 mm/h. The recharge volume in the downstream segment in the case of higher infiltration is mainly contributed by floods with magnitude ???93rd percentile, compared to floods in the 63rd percentile at an infiltration rate of 8.5 mm/h. ?? 2009 Elsevier B.V. All rights reserved.

Detailed hydrologic models require high-resolution spatial and temporal data. This study aims at improving the spatial interpolation of daily precipitation for hydrologic models. Different parameterizations of (1) inverse distance weighted (IDW) interpolation and (2) A local weighted regression (LWR) method in which elevation is the explanatory variable and distance, elevation difference and aspect difference are weighting factors, were tested at a hilly setting in the eastern Mediterranean, using 16 years of daily data. The preferred IDW interpolation was better than the preferred LWR scheme in 27 out of 31 validation gauges (VGs) according to a criteria aimed at minimizing the absolute bias and the mean absolute error (MAE) of estimations. The choice of the IDW exponent was found to be more important than the choice of whether or not to use elevation as explanatory data in most cases. The rank of preferred interpolators in a specific VG was found to be a stable local characteristic if a sufficient number of rainy days are averaged. A spatial pattern of the preferred IDW exponents was revealed. Large exponents (3) were more effective closer to the coast line whereas small exponents (1) were more effective closer to the mountain crest. This spatial variability is consistent with previous studies that showed smaller correlation distances of daily precipitation closer to the Mediterranean coast than at the hills, attributed mainly to relatively warm sea-surface temperature resulting in more cellular convection coastward. These results suggest that spatially variable, physically based parameterization of the distance weighting function can improve the spatial interpolation of daily precipitation

Quantitatively estimating rainfall-runoff relations in extremely arid regions is a challenging task, mainly because of lack of in situ data. For the past 40 years, rain and floods have been monitored in the Nahal Yael catchment (0.5 km2) in southern Israel, providing a unique data set of runoff hydrographs and rainfall in a hyper-arid region. Here we present an exploratory study focusing on rainfall-runoff modeling issues for a small (0.05 km2) sub-catchment of Nahal Yael. The event-based model includes the computation of rainfall excess, hillslope and channel routing. Two model parameters of the infiltration process were found by calibration. A resampling methodology of calibration group composition is suggested to derive optimal model parameters and their uncertainty range. Log-based objective functions were found to be more robust and less sensitive than non-log functions to calibration group composition. The fit achieved between observed and computed runoff hydrographs for the calibration and validation events is considered good relative to other modeling studies in arid and semi-arid regions. The study indicates that, under the calibration scheme used, a lumped model performs better than a model representing the catchment division into three sub-catchments. In addition, the use of rain data from several gauges improves runoff prediction as compared to input from a single gauge. It was found that rainfall uncertainty dominates uncertainties in runoff prediction while parameter uncertainties have only a minor effect. ?? 2009 Elsevier B.V. All rights reserved.

Flash-flood warning models can save lives and protect various kinds of infrastructure. In dry climate regions, rainfall is highly variable and can be of high-intensity. Since rain gauge networks in such areas are sparse, rainfall information derived from weather radar systems can provide useful input for flash- flood models. This paper presents a flash-flood warning model which utilizes radar rainfall data and applies it to two catchments that drain into the dry Dead Sea region. Radar-based quantitative precipita- tion estimates (QPEs) were derived using a rain gauge adjustment approach, either on a daily basis (allowing the adjustment factor to change over time, assuming available real-time gauge data) or using a constant factor value (derived from rain gauge data) over the entire period of the analysis. The QPEs served as input for a continuous hydrological model that represents the main hydrological processes in the region, namely infiltration, flow routing and transmission losses. The infiltration function is applied in a distributed mode while the routing and transmission loss functions are applied in a lumped mode. Model parameters were found by calibration based on the 5 years of data for one of the catchments. Val- idation was performed for a subsequent 5-year period for the same catchment and then for an entire 10- year record for the second catchment. The probability of detection and false alarm rates for the validation cases were reasonable. Probabilistic flash-flood prediction is presented applying Monte Carlo simulations with an uncertainty range for the QPEs and model parameters. With low probability thresholds, one can maintain more than 70% detection with no more than 30% false alarms. The study demonstrates that a flash-flood warning model is feasible for catchments in the area studied.