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Modelling the effects of climate change on water availability in the semi-arid of North-East Brazil
(2001)
Advances in Flood Research
(2002)
As a consequence of increasing winter rainfall totals and intensities over the second half of the 20th century, signs of increased flooding probability in many areas of the Rhine and Meuse basins have been documented. These changes affecting rainfall characteristics are most evidently due to an increase in westerly atmospheric circulation types. Land use changes, particularly urbanization, can have significant local effects in small basins (headwaters) with respect to flooding, especially during heavy local rainstorms, but no evidence exists that land use change has had significant effects on peak flows in the rivers Rhine and Meuse. For the 21st century, most global circulation models suggest higher winter rainfall totals. Most hydrological simulations of the Rhine-Meuse river basins suggest an increased flooding probability, with a progressive shift of the Rhine from a 'rain-fed/meltwater' river into a mainly 'rain-fed' river. A very limited effect of changes in land use on the discharge regime seems to exist for the main branches of the Meuse and Rhine rivers. For mesoscale basins, future changes in peak flows depend on the changes in the variability of extreme precipitations in combination with land use changes. Copyright (C) 2004 John Wiley Sons, Ltd
Approximation of Groundwater - Surface Water - Interactions in a Mesoscale Lowland River Catchment
(2004)
The spatial variability of landscape features such as topography, soils and vegetation defines the spatial pattern of hydrological state variables like soil moisture. Spatial variability thereby controls the functional behaviour of the landscape in terms of its runoff response. A consequence of spatial variability is that exchange processes between landscape patches can occur at various spatial scales ranging from the plot to the basin scale. In semi-arid areas, the lateral redistribution of surface runoff between adjacent landscape patches is an important process. For applications to large river basins of 10(4)-10(5) km(2) in size, a multi-scale landscape discretization scheme is presented in this paper. The landscape is sub-divided into modelling units within a hierarchy of spatial scale levels. By delineating areas characterized by a typical toposequence, organised and random variability of landscape characteristics is captured in the model. Using runoff-runon relationships with transition frequencies based on areal fractions of modelling units, lateral surface and subsurface water fluxes between modelling units at the hillslope scale are represented. Thus, the new approach allows for a manageable description of interactions between fine-scale landscape features for inclusion in coarse-scale models. Model applications for the State of Ceara (148,000 km(2)) in the north- east of Brazil demonstrate the importance of taking into account landscape variability and interactions between landscape patches in a semi-arid environment. Using mean landscape characteristics leads to a considerable underestimation of infiltration-excess surface runoff and total simulated runoff. Re-infiltration of surface runoff and lateral redistribution processes between landscape patches cause a reduction of runoff volumes at the basin scale and contribute to the amplification of variations in runoff volumes relative to variations in rainfall volumes for semi-arid areas. (C) 2004 Elsevier B.V. All rights reserved
Simple water balance modelling of surface reservoir systems in a large data-scarce semiarid region
(2004)
Water resources in dryland areas are often provided by numerous surface reservoirs. As a basis for securing future water supply, the dynamics of reservoir systems need to be simulated for large river basins, accounting for environmental change and an increasing water demand. For the State of Ceara in semiarid Northeast Brazil, with several thousands of reservoirs, a simple deterministic water balance model is presented. Within a cascade-type approach, the reservoirs are grouped into six classes according to storage capacity, rules for flow routing between reservoirs of different size are defined, and water withdrawal and return flow due to human water use is accounted for. While large uncertainties in model applications exist, particularly in terms of reservoir operation rules, model validation against observed reservoir storage volumes shows that the approach is a reasonable simplification to assess surface water availability in large river basins. The results demonstrate the large impact of reservoir storage on downstream flow and stress the need for a coupled simulation of runoff generation, network redistribution and water use
A methodology is presented to assess the impact of reservoir silting oil water availability for semiarid environments, applied to seven representative watersheds in the state of Ceara, Brazil. Water yield is computed using stochastic modelling for several reliability levels and water yield reduction is quantified for the focus areas. The yield-volume elasticity concept, which indicates the relative yield reduction in terms of relative storage capacity of the reservoirs, is presented and applied. Results chow that storage capacity was reduced by 0.2% year(-1) due to silting, that the risk of water shortage almost doubled in less than 50 years for the most critical reservoir, and that reduction of storage capacity had three times more impact oil yield reduction than the increase in evaporation. Average 90% reliable yield-volume elasticity was 0.8, which means that the global water yield (Q(90)) in Ceara is expected to diminish yearly by 388 L s(-1) due to reservoir silting
This study presents an application of an innovative sampling strategy to assess soil moisture dynamics in a headwater of the Weißeritz in the German eastern Ore Mountains. A grassland site and a forested site were instrumented with two Spatial TDR clusters (STDR) that consist of 39 and 32 coated TDR probes of 60 cm length. Distributed time series of vertically averaged soil moisture data from both sites/ensembles were analyzed by statistical and geostatistical methods. Spatial variability and the spatial mean at the forested site were larger than at the grassland site. Furthermore, clustering of TDR probes in combination with long-term monitoring allowed identification of average spatial covariance structures at the small field scale for different wetness states. The correlation length of soil water content as well as the sill to nugget ratio at the grassland site increased with increasing average wetness and but, in contrast, were constant at the forested site. As soil properties at both the forested and grassland sites are extremely variable, this suggests that the correlation structure at the forested site is dominated by the pattern of throughfall and interception. We also found a strong correlation between average soil moisture dynamics and runoff coefficients of rainfall-runoff events observed at gauge Rehefeld, which explains almost as much variability in the runoff coefficients as pre-event discharge. By combining these results with a recession analysis we derived a first conceptual model of the dominant runoff mechanisms operating in this catchment. Finally, long term simulations with a physically based hydrological model were in good/acceptable accordance with the time series of spatial average soil water content observed at the forested site and the grassland site, respectively. Both simulations used a homogeneous soil setup that closely reproduces observed average soil conditions observed at the field sites. This corroborates the proposed sampling strategy of clustering TDR probes in typical functional units is a promising technique to explore the soil moisture control on runoff generation. Long term monitoring of such sites could maybe yield valuable information for flood warning. The sampling strategy helps furthermore to unravel different types of soil moisture variability.
Spatial patterns as well as temporal dynamics of soil moisture have a major influence on runoff generation. The investigation of these dynamics and patterns can thus yield valuable information on hydrological processes, especially in data scarce or previously ungauged catchments. The combination of spatially scarce but temporally high resolution soil moisture profiles with episodic and thus temporally scarce moisture profiles at additional locations provides information on spatial as well as temporal patterns of soil moisture at the hillslope transect scale. This approach is better suited to difficult terrain (dense forest, steep slopes) than geophysical techniques and at the same time less cost-intensive than a high resolution grid of continuously measuring sensors. Rainfall simulation experiments with dye tracers while continuously monitoring soil moisture response allows for visualization of flow processes in the unsaturated zone at these locations. Data was analyzed at different spacio-temporal scales using various graphical methods, such as space-time colour maps (for the event and plot scale) and binary indicator maps (for the long-term and hillslope scale). Annual dynamics of soil moisture and decimeterscale variability were also investigated. The proposed approach proved to be successful in the investigation of flow processes in the unsaturated zone and showed the importance of preferential flow in the Malalcahuello Catchment, a datascarce catchment in the Andes of Southern Chile. Fast response times of stream flow indicate that preferential flow observed at the plot scale might also be of importance at the hillslope or catchment scale. Flow patterns were highly variable in space but persistent in time. The most likely explanation for preferential flow in this catchment is a combination of hydrophobicity, small scale heterogeneity in rainfall due to redistribution in the canopy and strong gradients in unsaturated conductivities leading to self-reinforcing flow paths.
The intention of the presented study is to gain a better understanding of the mechanisms that caused the bimodal rainfall-runoff responses which occurred up to the mid-1970s regularly in the Schafertal catchment and vanished after the onset of mining activities. Understanding, this process is a first step to understanding the ongoing hydrological change in this area. It is hypothesized that either subsurface stormflow, or fast displacement of groundwater, could cause the second delayed peak. A top-down analysis of rainfall-runoff data, field observations as well as process modelling are combined within a rejectionistic framework. A statistical analysis is used to test whether different predictors. which characterize the forcing. near surface water content and deeper subsurface store, allow the prediction of the type of rainfall-runoff response. Regression analysis is used with generalized linear models Lis they can deal with non-Gaussian error distributions Lis well its a non-stationary variance. The analysis reveals that the dominant predictors are the pre-event discharge (proxy of state of the groundwater store) and the precipitation amount, In the field campaign, the subsurface at a representative hillslope was investigated by means of electrical resistivity tomography in order to identify possible strata as flow paths for subsurface stormflow. A low resistivity in approximately 4 in depth-either due to a less permeable layer or the groundwater surface-was detected. The former Could serve as a flow path for subsurface stormflow. Finally, the physical-based hydrological model CATFLOW and the groundwater model FEFLOW are compared with respect to their ability to reproduce the bimodal runoff responses. The groundwater model is able to reproduce the observations, although it uses only an abstract representation of the hillslopes. Process model analysis as well Lis statistical analysis strongly suggest that fast displacement of groundwater is the dominant process underlying the bimodal runoff reactions.
Detention areas provide a means to lower peak discharges in rivers by temporarily storing excess water. In the case of extreme flood events, the storage effect reduces the risk of dike failures or extensive inundations for downstream reaches and near the site of abstraction. Due to the large amount of organic matter contained in the river water and the inundation of terrestrial vegetation in the detention area, a deterioration of water quality may occur. In particular, decay processes can cause a severe depletion of dissolved oxygen (DO) in the temporary water body. In this paper, we studied the potential of a water quality model to simulate the DO dynamics in a large but shallow detention area to be built at the Elbe River (Germany). Our focus was on examining the impact of spatial discretization on the model's performance and usability. Therefore, we used a zero-dimensional (OD) and a two-dimensional (2D) modeling approach in parallel. The two approaches solely differ in their spatial discretization, while conversion processes, parameters, and boundary conditions were kept identical. The dynamics of DO simulated by the two models are similar in the initial flooding period but diverge when the system starts to drain. The deviation can be attributed to the different spatial discretization of the two models, leading to different estimates of flow velocities and water depths. Only the 2D model can account for the impact of spatial variability on the evolution of state variables. However, its application requires high efforts for pre- and post-processing and significantly longer computation times. The 2D model is, therefore, not suitable for investigating various flood scenarios or for analyzing the impact of parameter uncertainty. For practical applications, we recommend to firstly set up a fast-running model of reduced spatial discretization, e.g. a OD model. Using this tool, the reliability of the simulation results should be checked by analyzing the parameter uncertainty of the water quality model. A particular focus may be on those parameters that are spatially variable and, therefore, believed to be better represented in a 2D approach. The benefit from the application of the more costly 2D model should be assessed, based on the analyses carried out with the OD model. A 2D model appears to be preferable only if the simulated detention area has a complex topography, flow velocities are highly variable in space, and the parameters of the water quality model are well known.
An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.
Channel transmission losses in drylands take place normally in extensive alluvial channels or streambeds underlain by fractured rocks. They can play an important role in streamflow rates, groundwater recharge, freshwater supply and channel-associated ecosystems. We aim to develop a process-oriented, semi-distributed channel transmission losses model, using process formulations which are suitable for data-scarce dryland environments and applicable to both hydraulically disconnected losing streams and hydraulically connected losing(/gaining) streams. This approach should be able to cover a large variation in climate and hydro-geologic controls, which are typically found in dryland regions of the Earth. Our model was first evaluated for a losing/gaining, hydraulically connected 30 km reach of the Middle Jaguaribe River (MJR), Ceara, Brazil, which drains a catchment area of 20 000 km(2). Secondly, we applied it to a small losing, hydraulically disconnected 1.5 km channel reach in the Walnut Gulch Experimental Watershed (WGEW), Arizona, USA. The model was able to predict reliably the streamflow volume and peak for both case studies without using any parameter calibration procedure. We have shown that the evaluation of the hypotheses on the dominant hydrological processes was fundamental for reducing structural model uncertainties and improving the streamflow prediction. For instance, in the case of the large river reach (MJR), it was shown that both lateral stream-aquifer water fluxes and groundwater flow in the underlying alluvium parallel to the river course are necessary to predict streamflow volume and channel transmission losses, the former process being more relevant than the latter. Regarding model uncertainty, it was shown that the approaches, which were applied for the unsaturated zone processes (highly nonlinear with elaborate numerical solutions), are much more sensitive to parameter variability than those approaches which were used for the saturated zone (mathematically simple water budgeting in aquifer columns, including backwater effects). In case of the MJR-application, we have seen that structural uncertainties due to the limited knowledge of the subsurface saturated system interactions (i.e. groundwater coupling with channel water; possible groundwater flow parallel to the river) were more relevant than those related to the subsurface parameter variability. In case of the WEGW application we have seen that the non-linearity involved in the unsaturated flow processes in disconnected dryland river systems (controlled by the unsaturated zone) generally contain far more model uncertainties than do connected systems controlled by the saturated flow. Therefore, the degree of aridity of a dryland river may be an indicator of potential model uncertainty and subsequent attainable predictability of the system.
We generated medium-range forecasts of runoff for a 50 km(2) headwater catchment upstream of a reservoir using numerical weather predictions (NWPs) of the past as input to an operational hydrological model. NWP data originating from different sources were tested. For a period of 8.5 years, we computed daily forecasts with a lead time of +120 h based on an empirically downscaled version of the ECMWF's ensemble prediction system. For the last 3.5 years of the test period, we also tried the deterministic COSMO-EU forecast disseminated by the German Weather Service for lead times of up to +72 h. Common measures of skill indicate superiority of the ensemble runoff forecast over single-value forecasts for longer lead times. However, regardless of which NWP data were being used, the probability of event detection (POD) was found to be generally lower than 50%. In many cases, values in the range of 20-30% were obtained. At the same time, the false alarms ratio (FAR) was often found to be considerably high. The observed uncertainties in the hydrological forecasts were shown to originate from both the insufficient quality of precipitation forecasts as well as deficiencies in hydrological modeling and quantitative precipitation estimation. With respect to the anticipatory control of reservoirs in the studied catchment, the value of the tested runoff forecasts appears to be limited. This is due to the unfavorably low POD/FAR ratio in conjunction with a high cost-loss ratio. However, our results indicate that, in many cases, major runoff events related to snow melt can be successfully predicted as early as 4-5 days in advance.
From 6 to 9 August 2012, intense rainfall hit the northern Philippines, causing massive floods in Metropolitan Manila and nearby regions. Local rain gauges recorded almost 1000mm within this period. However, the recently installed Philippine network of weather radars suggests that Metropolitan Manila might have escaped a potentially bigger flood just by a whisker, since the centre of mass of accumulated rainfall was located over Manila Bay. A shift of this centre by no more than 20 km could have resulted in a flood disaster far worse than what occurred during Typhoon Ketsana in September 2009.
Floods and debris flows in small Alpine torrent catchments (<10km(2)) arise from a combination of critical antecedent system state conditions and mostly convective precipitation events with high precipitation intensities. Thus, climate change may influence the magnitude-frequency relationship of extreme events twofold: by a modification of the occurrence probabilities of critical hydrological system conditions and by a change of event precipitation characteristics. Three small Alpine catchments in different altitudes in Western Austria (Ruggbach, Brixenbach and Langentalbach catchment) were investigated by both field experiments and process-based simulation. Rainfall-runoff model (HQsim) runs driven by localized climate scenarios (CNRM-RM4.5/ARPEGE, MPI-REMO/ECHAM5 and ICTP-RegCM3/ECHAM5) were used in order to estimate future frequencies of stormflow triggering system state conditions. According to the differing altitudes of the study catchments, two effects of climate change on the hydrological systems can be observed. On one hand, the seasonal system state conditions of medium altitude catchments are most strongly affected by air temperature-controlled processes such as the development of the winter snow cover as well as evapotranspiration. On the other hand, the unglaciated high-altitude catchment is less sensitive to climate change-induced shifts regarding days with critical antecedent soil moisture and desiccated litter layer due to its elevation-related small proportion of sensitive areas. For the period 2071-2100, the number of days with critical antecedent soil moisture content will be significantly reduced to about 60% or even less in summer in all catchments. In contrast, the number of days with dried-out litter layers causing hydrophobic effects will increase by up to 8%-11% of the days in the two lower altitude catchments. The intensity analyses of heavy precipitation events indicate a clear increase in rain intensities of up to 10%.
Due to the environmental and socio-economic importance of mountainous regions, it is crucial to understand causes and consequences of climatic changes in those sensitive landscapes. Daily resolution alpine climate data from Switzerland covering an elevation range of over 3,000m between 1981 and 2017 have been analysed using highly resolved trends in order to gain a better understanding of features, forcings and feedbacks related to temperature changes in mountainous regions. Particular focus is put on processes related to changes in weather types, incoming solar radiation, cloud cover, air humidity, snow/ice and elevation dependency of temperature trends. Temperature trends in Switzerland differ depending on the time of the year, day and elevation. Warming is strongest during spring and early summer with enhanced warming of daytime maximum temperatures. Elevation-based differences in temperature trends occur during autumn and winter with stronger warming at lower elevations. We attribute this elevation-dependent temperature signal mainly to elevation-based differences in trends of incoming solar radiation and elevation-sensitive responses to changes in frequencies of weather types. In general, effects of varying frequencies of weather types overlap with trends caused by transmission changes in short- and long-wave radiation. Temperature signals arising from snow/ice albedo feedback mechanisms are probably small and might be hidden by other effects.
Study region: Tisza and Prut catchments, originating on the slopes of the Carpathian mountains. Study focus: The study reported here investigates (i) climate change impacts on flood risk in the region, and (ii) uncertainty related to hydrological modelling, downscaling techniques and climate projections. The climate projections used in the study were derived from five GCMs, downscaled either dynamically with RCMs or with the statistical downscaling model XDS. The resulting climate change scenarios were applied to drive the eco-hydrological model SWIM, which was calibrated and validated for the catchments in advance using observed climate and hydrological data. The changes in the 30-year flood hazards and 98 and 95 percentiles of discharge were evaluated for the far future period (2071-2100) in comparison with the reference period (1981-2010). New hydrological insights for the region: The majority of model outputs under RCP 4.5 show a small to strong increase of the 30-year flood level in the Tisza ranging from 4.5% to 62%, and moderate increase in the Prut ranging from 11% to 22%. The impact results under RCP 8.5 are more uncertain with changes in both directions due to high uncertainties in GCM-RCM climate projections, downscaling methods and the low density of available climate stations.
The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021-2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced.
Recent climatic changes have the potential to severely alter river runoff, particularly in snow-dominated river basins. Effects of changing snow covers superimpose with changes in precipitation and anthropogenic modifications of the watershed and river network. In the attempt to identify and disentangle long-term effects of different mechanisms, we employ a set of analytical tools to extract long-term changes in river runoff at high resolution. We combine quantile sampling with moving average trend statistics and empirical mode decomposition and apply these tools to discharge data recorded along rivers with nival, pluvial and mixed flow regimes as well as temperature and precipitation data covering the time frame 1869-2016. With a focus on central Europe, we analyse the long-term impact of snow cover and precipitation changes along with their interaction with reservoir constructions.
Our results show that runoff seasonality of snow-dominated rivers decreases. Runoff increases in winter and spring, while discharge decreases in summer and at the beginning of autumn. We attribute this redistribution of annual flow mainly to reservoir constructions in the Alpine ridge. During the course of the last century, large fractions of the Alpine rivers were dammed to produce hydropower. In recent decades, runoff changes induced by reservoir constructions seem to overlap with changes in snow cover. We suggest that Alpine signals propagate downstream and affect runoff far outside the Alpine area in river segments with mixed flow regimes. Furthermore, our results hint at more (intense) rain-fall in recent decades. Detected increases in high discharge can be traced back to corresponding changes in precipitation.