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In data scarce basins, such as the Nile River Basin (NRB) in Africa, constraints related to data availability, quality, and access often complicate attempts to estimate runoff sensitivity using conventional methods. In this paper, we show that by integrating the concept of the aridity index (AI) (derived from the Budyko curve) and climate elasticity, we can obtain the first order response of the runoff sensitivity using minimal data input and modeling expertise or experience. The concept of runoff elasticity relies on the fact that the energy available for evapotranspiration plays a major role in determining whether the precipitation received within a drainage basin generates runoff. The approach does not account for human impacts on runoff modification and or diversions. By making use of freely available gauge-corrected satellite data for precipitation, temperature, runoff, and potential evapotranspiration, we derived the sensitivity indicator ( β ) to determine the runoff response to changes in precipitation and temperature for four climatic zones in the NRB, namely, tropical, subtropical, semiarid and arid zones. The proposed sensitivity indicator can be partitioned into different elasticity components i.e: precipitation ( ε p ), potential evapotranspiration ( ε ET p ), temperature ( ε T ) and the total elasticity ( ε tot ) . These elasticities allow robust quantification of the runoff response to the potential changes in precipitation and temperature with a high degree of accuracy. Results indicate that the tropical zone is energy-constrained with low sensitivity, ( β < 1.0 ) , implying that input precipitation exceeds the amounts that can be evaporated given the available energy. The subtropical zone is subdivided into two distinct regions, the lowland (Machar and Sudd marshes), and the highland area (Blue Nile Basin), where each area has a unique sensitivity. The lowland area has high sensitivity, ( β > 1.0 ) . The subtropical-highland zone moves between energy-limited to water-limited conditions during periods of wet and dry spells with varying sensitivity. The semiarid and arid zones are water limited, with high sensitivity, ( β > 1.0 ) . The calculated runoff elasticities show that a 10% decrease in precipitation leads to a decrease in runoff of between 19% in the tropical zone and 30% in the arid zones. On the other hand, a 10% precipitation increase leads to a runoff increase of 14% in the tropical zone and 22% in the arid zone. The estimated runoff changes are consistent with the result obtained using other methods. Thus, the elasticity approach combines data parsimony and analytical simplicity to produce results that are practically useful for most purposes while facilitating communication with stakeholders with different levels of scientific knowledge. More research is needed to extend the application of the method to incorporate the effects of human activities, and land use change. [ABSTRACT FROM AUTHOR]

A new precipitation index-based model, which includes a snow accumulation and melt component, has been developed to simulate hydrology in high latitude catchments. The model couples a point snowmelt model with a current precipitation index ( CPI ) formulation to simulate continuous daily runoff from catchments with seasonal snow cover. A new runoff conversion factor: C T and L f , threshold flow factor Th Q and runoff transformation function Maxbas were introduced into the CPI equation, which converts and transforms the routed daily CPI into daily runoff and maintains the daily base flow in the catchment. The model was developed using twelve sub-arctic boreal catchments located above and below the Arctic Circle in northern Finland, representing a region with considerable seasonal snow cover. The results showed that the model can adequately simulate and produce the dynamics of daily runoff from catchments where the underlying physical conditions are not known. An open-access Excel-based model is provided with this paper for daily runoff simulations. The model can be used to estimate runoff in sub-arctic regions where little data is typically available but significant changes in climate are expected, with considerable shifts in the amount and timing of snowmelt and runoff. [ABSTRACT FROM AUTHOR]

This paper presents a study of the potential for green infrastructure (GI) to restore the predevelopment hydrologic cycle in a semi-arid urban catchment. Simulations of stormwater runoff from a 0.11-km 2 urban catchment in Salt Lake City, Utah, USA for predeveloped (Natural Hydrology, NH), developed (Baseline, BL), and developed with GI (Green Infrastructure, GI) conditions were executed for a one-year period. The study was repeated for a relatively dry year, wet year, and an average year based on precipitation amounts in the year. Bioretention and green roofs were chosen for the GI plan. Results showed that the water budget of the catchment with the GI plan implemented more closely matches the NH water budget compared to the BL scenario, for all three years (dry, wet, average). The BL and GI scenarios showed more significant modifications to the water budget than what has been found by studies in humid climates. Compared to the BL condition, GI annually reduces surface runoff by 35%, 45%, and 43% and restores evapotranspiration by 18%, 19%, and 25% for the dry, average, wet years, respectively. Based on the introduced water budget restoration coefficient (WBRC), the water budget of the study catchment was restored by the GI plan to 90%, 90%, and 82% of the predevelopment state in the dry, average, and wet years, respectively. By comparing the WBRC estimated for other studies, it is further inferred that the water budget is more significantly affected by development and GI restoration in semi-arid than humid climates, but the differences lessen as the precipitation amount increases. [ABSTRACT FROM AUTHOR]

Summary Hydro-climatic data at short time steps are considered essential to model the rainfall–runoff relationship, especially for short-duration hydrological events, typically flash floods. Also, using fine time step information may be beneficial when using or analysing model outputs at larger aggregated time scales. However, the actual gain in prediction efficiency using short time-step data is not well understood or quantified. In this paper, we investigate the extent to which the performance of hydrological modelling is improved by short time-step data, using a large set of 240 French catchments, for which 2400 flood events were selected. Six-minute rain gauge data were available and the GR4 rainfall–runoff model was run with precipitation inputs at eight different time steps ranging from 6 min to 1 day. Then model outputs were aggregated at seven different reference time scales ranging from sub-hourly to daily for a comparative evaluation of simulations at different target time steps. Three classes of model performance behaviour were found for the 240 test catchments: (i) significant improvement of performance with shorter time steps; (ii) performance insensitivity to the modelling time step; (iii) performance degradation as the time step becomes shorter. The differences between these groups were analysed based on a number of catchment and event characteristics. A statistical test highlighted the most influential explanatory variables for model performance evolution at different time steps, including flow auto-correlation, flood and storm duration, flood hydrograph peakedness, rainfall–runoff lag time and precipitation temporal variability. [ABSTRACT FROM AUTHOR]

Summary The climate elasticity of runoff is an important indicator that is used to quantify the relationship between changes in runoff and changes in climate variables. It is a function of both climate and catchment characteristics. Recently, Yang and Yang (2011) proposed an analytical derivation of climate elasticity (YY2011), in which a parameter n was used to represent the impact of the catchment characteristics. In China, both climate and catchment characteristics have large spatial variations. To understand the spatial variation of hydrologic response to climate change, this paper divided China into 210 catchments, further calculated the parameter n , and then estimated the climate elasticity and evaluated the contribution of climate change to runoff for each catchment. The results show that n ranges from 0.4 to 3.8 (with a mean of 1.3 and a standard deviation of 0.6), which has a logarithmic relationship with catchment slope; the precipitation elasticity ranges from 1.1 to 4.8 (with a mean of 1.9 and a standard deviation of 0.6), which shows a large regional variation, smaller values (1.1–2.0) mainly appearing in Southern China, the Songhua River basin and the Northwest, and larger values (2.1–4.8) mainly appearing in the Hai River basin, the Liao River basin and the Yellow River basin. In addition, climate contribution to runoff exhibits a large regional variation, the largest positive values (1.1–3.1%/a) occurring in the Northwest, the largest negative values (−1.0 to −0.5%/a) occurring in the Hai River basin and the middle reach of the Yellow River basin. In theory, the YY2011 method is a first-order approximation. The approximation underestimates the precipitation ( P ) contribution to runoff when P increases and overestimates that when P decreases, and the relative error has a median of ∼3% and a maximum of ∼20% when 10% precipitations change in those catchments of China. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an assessment of the impacts of climate change on a series of indicators of hydrological regimes across the global domain, using a global hydrological model run with climate scenarios constructed using pattern-scaling from 21 CMIP3 (Coupled Model Intercomparison Project Phase 3) climate models. Changes are compared with natural variability, with a significant change being defined as greater than the standard deviation of the hydrological indicator in the absence of climate change. Under an SRES (Special Report on Emissions Scenarios) A1b emissions scenario, substantial proportions of the land surface (excluding Greenland and Antarctica) would experience significant changes in hydrological behaviour by 2050; under one climate model scenario (Hadley Centre HadCM3), average annual runoff increases significantly over 47% of the land surface and decreases over 36%; only 17% therefore sees no significant change. There is considerable variability between regions, depending largely on projected changes in precipitation. Uncertainty in projected river flow regimes is dominated by variation in the spatial patterns of climate change between climate models (hydrological model uncertainty is not included). There is, however, a strong degree of consistency in the overall magnitude and direction of change. More than two-thirds of climate models project a significant increase in average annual runoff across almost a quarter of the land surface, and a significant decrease over 14%, with considerably higher degrees of consistency in some regions. Most climate models project increases in runoff in Canada and high-latitude eastern Europe and Siberia, and decreases in runoff in central Europe, around the Mediterranean, the Mashriq, central America and Brasil. There is some evidence that project change in runoff at the regional scale is not linear with change in global average temperature change. The effects of uncertainty in the rate of future emissions is relatively small. [Copyright &y& Elsevier]

Summary: Modeling the effect of spatial variability of precipitation and basin characteristics on streamflow requires the use of distributed or semi-distributed hydrologic models. This paper addresses a DMIP 2 study that focuses on the advantages of using a semi-distributed modeling structure. We first present a revised semi-distributed structure of the NWS SACramento Soil Moisture Accounting (SAC-SMA) model that separates the routing of fast and slow response runoff components, and thus explicitly accounts for the differences between the two components. We then test four different calibration strategies that take advantage of the strengths of existing optimization algorithms (SCE-UA) and schemes (MACS). These strategies include: (1) lumped parameters and basin averaged precipitation, (2) semi-lumped parameters and distributed precipitation forcing, (3) semi-distributed parameters and distributed precipitation forcing and (4) lumped parameters and basin averaged precipitation, modified using a priori parameters of the SAC-SMA model. Finally, we explore the value of using discharge observations at interior points in model calibration by assessing gains/losses in hydrograph simulations at the basin outlet. Our investigation focuses on two key DMIP 2 science questions. Specifically, we investigate (a) the ability of the semi-distributed model structure to improve stream flow simulations at the basin outlet and (b) to provide reasonably good simulations at interior points. The semi-distributed model is calibrated for the Illinois River Basin at Siloam Springs, Arkansas using streamflow observations at the basin outlet only. The results indicate that lumped to distributed calibration strategies (1 and 4) both improve simulation at the outlet and provide meaningful streamflow predictions at interior points. In addition, the results of the complementary study, which uses interior points during the model calibration, suggest that model performance at the outlet can be further improved by using a semi-distributed structure calibrated at both interior points and the outlet, even when only a few years of historical record are available. [ABSTRACT FROM AUTHOR]

Summary: This paper analyses the observed intra-annual variability of the hydrological response in the Blue River basin (Oklahoma, USA) and explores the underlying process controls with the use of the Tsinghua Representative Elementary Watershed (THREW) model, which is a semi-distributed, physically based model. Analysis of rainfall and runoff data at the event scale revealed a seasonal switching pattern of runoff coefficients. Event runoff coefficients in the moderately wet and wet periods (October–April) are consistently higher than those in the dry period (May–September). The switching pattern can be attributed to the higher potential evaporation in the summer season (relative to precipitation), which contributes to a reduction of soil moisture and thus higher initial losses during storm events. This is partly confirmed by the simulation results with the use of the THREW model. However, the results also show that soil drying alone cannot fully explain the sharp drop of the estimated runoff coefficients between spring and summer. This may be indicative that additional abstraction processes may be operative. Three additional abstraction processes are hypothesized as potential explanations, namely, surface depressions, canopy interception and soil cracking. Each of these processes is introduced into the THREW model sequentially, and evaluated in terms of their ability to reproduce various signatures of intra-annual runoff variability, including the switching behavior of event runoff coefficients. Finally, we present simulation results, where all three abstraction processes are included in the THREW model, and the model are recalibrated against the observed data, resulting in improved reproduction of observed streamflows over the baseline results. [ABSTRACT FROM AUTHOR]

Summary: This paper provides a general overview of changes in flooding caused by climate change in Finland for the periods 2010–2039 and 2070–2099. Changes in flooding were evaluated at 67 sites in Finland with variable sizes of runoff areas using a conceptual hydrological model and 20 climate scenarios from both global and regional climate models with the delta change approach. Floods with a 100-year return period were estimated with frequency analysis using the Gumbel distribution. At four study sites depicting different watershed types and hydrology, the inundation areas of the 100-year floods were simulated with a 2D hydraulic model. The results demonstrate that the impacts of climate change are not uniform within Finland due to regional differences in climatic conditions and watershed properties. In snowmelt-flood dominated areas, annual floods decreased or remained unchanged due to decreasing snow accumulation. On the other hand, increased precipitation resulted in growing floods in major central lakes and their outflow rivers. The changes in flood inundation did not linearly follow the changes in 100-year discharges, due to varying characteristics of river channels and floodplains. The results highlight the importance of comprehensive climatological and hydrological knowledge and the use of several climate scenarios in estimation of climate change impacts on flooding. Generalisations based on only a few case studies, or large scale flood assessments using only a few climate scenarios should be avoided in countries with variable hydrological conditions. [ABSTRACT FROM AUTHOR]

Summary: Proglacial areas are expanding globally as a consequence of sustained glacier retreat, but there are very few studies focusing on their hydrology. This paper examines the surface and atmospheric water fluxes over a complete annual cycle in the proglacial area of the Svalbard glacier Finsterwalderbreen (77N), through a combination of field measurements, physical modelling and statistical estimation. Precipitation in winter (226mm) exceeded that in summer (29mm), and over the course of the annual cycle total precipitation exceeded total evaporation (141mm), although evaporative outputs from the proglacial area exceeded precipitation inputs during the dry summer. Runoff was highly irregular in time, with much of the total annual flow being concentrated into two relatively brief, early-to-mid summer intervals, the greater of which was characterised by the release of subglacially-stored water. Water fluxes were dominated by meltwater supply from the glacier: the total annual glacial runoff (7.38×107 m3) was an order-of-magnitude greater than the precipitation flux delivered directly to the proglacial area, and two orders-of-magnitude greater than evaporative losses from it. Outputs of meltwater from the proglacial area were not significantly different from inputs over the duration of the melt season, so surface water storage does not appear to be important in the studied catchment, despite episodes of flooding over shorter timescales. A synthesised description of the seasonal hydrological cycle in Finsterwalderbreen’s proglacial area is presented, which can be viewed as a set of hydrological boundary conditions for comparable high-latitude locations. Further study of these conditions is required, because the challenging nature of hydrometry in the high-latitudes has the potential to limit progress in understanding environmental change there. [Copyright &y& Elsevier]

Summary: In this paper, progressive methods for assessing drought severity from diverse points of view were conceived. To select a fundamental drought index, the performances of the Effective Drought Index (EDI) and 1-, 3-, 6-, 9-, 12-, and 24-month Standardized Precipitation Indices (SPIs) were compared for drought monitoring data accumulated over 200-year period from 1807 to 2006 for Seoul, Korea. The results confirmed that the EDI was more efficient than the SPIs in assessing both short and long-term droughts. We then proposed the following methods for modifying and supplementing the EDI: (1) CEDI, a corrected EDI that considers the rapid runoff of water resources after heavy rainfall; (2) AEDI, an accumulated EDI that considers the drought severity and duration of individual drought events; and (3) YAEDI, a year-accumulated negative EDI representing annual drought severity. In addition to these indices, to more accurately measure and diagnose droughts, we proposed the utilization of (4) the Available Water Resources Index (AWRI), an existing index that expresses the actual amount of available water. Using the improved methods above, we assessed and summarized important droughts that have occurred in Seoul over the 200years from 1807 to 2006. [Copyright &y& Elsevier]

Summary: The difficulty of predicting rainfall–runoff responses in arid and semi-arid catchments using typically available data sets is well known, hence the need to carefully evaluate the suitability of alternative modelling approaches for a given problem and data set; and to identify causes of uncertainty in order to prioritise research and data. In this paper, we evaluate the distributed model, Kineros2, in application to an arid catchment in Oman, using rainfall–runoff data from 27 storm events. The analysis looks at model sensitivities, uncertainty and performance, based on uniform random sampling of the model parameter space and predictions of features of the observed hydrograph at the catchment outlet. A series of three experiments used different calibration strategies (an 11-parameter calibration, a 5-parameter calibration, and a 3-parameter calibration allowing some spatial variability of the saturated hydraulic conductivity). The parameters most significantly affecting flow peak and volume performance are those controlling infiltration rates on hillslopes. The model output was also generally sensitive to a parameter within the rainfall interpolation model. Relatively little sensitivity to initial catchment wetness was observed. Prediction performance was generally poor, for all events and for all the tested calibration and prediction strategies; and the uncertainty, estimated using model ensembles, was very high. A 2-parameter regression model used in previous work was found to perform better for predicting flow peaks. Literature review shows our results are consistent with experience of other modellers of arid and semi-arid climate hydrology. In order to realise the potential value of distributed, physically based models, for application to arid and semi-arid regions, significant data collection and further research is required, in particular regarding spatial rainfall observation and modelling. [Copyright &y& Elsevier]

Abstract: This paper examines the effect of spatially variable initial soil moisture and spatially variable precipitation on predictive uncertainty of simulated catchment scale runoff response in the presence of threshold processes. The underlying philosophy is to use a physically based hydrological model named CATFLOW as a virtual landscape, assuming perfect knowledge of the processes. The model, which in particular conceptualizes preferential flow as threshold process, was developed based on intensive process and parameter studies and has already been successfully applied to simulate flow and transport at different scales and catchments. Study area is the intensively investigated Weiherbach catchment. Numerous replicas of spatially variable initial soil moisture or spatially variable precipitation with the same geostatistical properties are conditioned to observed soil moisture and precipitation data and serve as initial and boundary conditions for the model during repeated simulations. The effect of spatially soil moisture on modeling catchment runoff response was found to depend strongly on average saturation of the catchment. Different realizations of initial soil moisture yielded strongly different hydrographs for intermediate initial soil moisture as well as in dry catchment conditions; in other states the effect was found to be much lower. This is clearly because of the threshold nature of preferential flow as well as the threshold nature of Hortonian production of overland flow. It was shown furthermore that the spatial pattern of a key parameter (macroporosity) that determined threshold behavior is of vast importance for the model response. The estimation of these patterns, which is mostly done based on sparse observations and expert knowledge, is a major source for predictive model uncertainty. Finally, it was shown that the usage of biased, i.e. spatially homogenized precipitation, input during parameter estimation yields a biased model structure, which gives poor results when used with highly distributed input. If spatially highly resolved precipitation was used during model parameter estimation, the predictive uncertainty of the model was clearly reduced. [Copyright &y& Elsevier]

• Novel approach of rainfall – runoff interpretation with the usage of disdrometer. • Precise estimation of the reduction of runoff basing on droplets structure. • Dominant droplets as a criterion significantly affecting the reduction of infiltration. The objective of this study was the estimation of the effect of droplet structure of diurnal precipitation totals, measured with Thies Clima disdrometer, on the value of surface runoff from three kinds of surface used in urban areas, i.e. a roof surface covered with small-grain roofing paper, a car park surface of openwork concrete slabs, and a tarmac surface, and the resultant reduction of infiltration from atmospheric precipitation. The detailed comparative analysis of diurnal precipitation totals in the aspect of droplet structure, structure of increasing influx of precipitation water to the surface, and changes of air temperature-humidity conditions, allowed preliminary elucidation of the effect of those factors on the values of the runoff indices for the different hardened surfaces. The analysis of reduction of infiltration presents the level of supply losses resulting from the use of surface covering systems with various degrees of permeability to precipitation water. A solution that can minimise the indicated losses can be an approach to precipitation water management assuming interception of possibly the largest amounts of non-productive surface runoff waters, and then using that water. [ABSTRACT FROM AUTHOR]