Effects of climate change and human interactions on water balance dynamics in the River Vistula basin

<div> <p>Water balance modelling is often applied in studies of climate and human impacts on water resources. Annual water balance is usually derived based on precipitation, discharge and temperature observations under an assumption of negligible changes in annual water storage in a catchment. However, that assumption might be violated during very dry or very wet years. In this study we apply groundwater level measurements to improve water balance modelling in nine sub-catchments of the River Vistula basin starting from the river sources downstream. Annual and inter-annual water balance is studied using a Budyko framework to assess actual evapotranspiration and total water supply. We apply the concept of effective precipitation to account for possible losses due to water interception by vegetation. Generalised Likelihood Uncertainty Estimation GLUE is used to account for parameter and structural model uncertainty, together with the application of eight Budyko-type equations. Seasonal water balance models show large errors for winter seasons while summer and annual water balance models follow the Budyko framework. The dryness index is much smaller in winter than in summer for all sub-catchments. The spatial variability of water balance modelling errors indicate an increasing uncertainty of model predictions with an increase in catchment size. The results show that the added information on storage changes in the catchments provided by groundwater level observations largely improves model accuracy. The results also indicate the need to model groundwater level variability depending on external factors such as precipitation and evapotranspiration and human interventions. The modelling tools developed will be used to assess future water balance in the River Vistula basin under different water management scenarios and climate variability.</p> </div>

The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: description and case study

The Ensemble Framework For Flash Flood Forecasting (EF5) was developed specifically for improving hydrologic predictions to aid in the issuance of flash flood warnings by the US National Weather Service. EF5 features multiple water balance models and two routing schemes which can be used to generate ensemble forecasts of streamflow, streamflow normalized by upstream basin area (i.e., unit streamflow), and soil saturation. EF5 is designed to utilize high-resolution precipitation forcing datasets now available in real time. A study on flash-flood-scale basins was conducted over the conterminous United States using gauged basins with catchment areas less than 1000 km2. The results of the study show that the three uncalibrated water balance models linked to kinematic wave routing are skillful in simulating streamflow.

Soil Water Balance and Vegetation Dynamics in a Semi-arid Mediterranean Ecosystem

Under arid conditions, where water availability is the limiting factor for plant survival, water balance models can be used to explain vegetation dynamics. [...]

The Ensemble Framework For Flash Flood Forecasting (EF5) v1.2: Description and Case Study

The Ensemble Framework For Flash Flood Forecasting (EF5) was developed specifically for improving hydrologic predictions to aid in the issuance of flash flood warnings by the U.S. National Weather Service. EF5 features multiple water balance models and two routing schemes which can be used to generate ensemble forecasts of streamflow, streamflow normalized by upstream basin area (i.e., unit streamflow), and soil saturation. EF5 is designed to utilize high resolution precipitation forcing datasets now available in near real time. A study on flash flood scale basins was conducted over the conterminous United States using gauged basins with catchment areas less than 1,000 km2. The results of the study show that the three uncalibrated water balance models linked to kinematic wave routing are skillful in streamflow prediction.

Transferability of monthly water balance models under changing climate conditions in an arid catchment

<p>Assessment of climate change impact on water resources is often based on hydrologic projections developed using monthly water balance models (MWBMs) forced by climate projections. These models are calibrated against historical data but are expected to provide accurate flow simulations under changing climate conditions. However, an evaluation of these models’ performance is needed to explore their applicability under changing climate conditions, assess uncertainties and eventually indicate model components that should be improved. This should be done in a comprehensive evaluation framework specifically tailored to evaluate applicability of MWBMs in changing climatic conditions.</p><p> </p><p>In this study, we evaluated performance of four MWBMs (abcd, Budyko, GR2M and WASMOD) used for hydrologic simulations in the arid Wimmera River catchment in Australia. This catchment is selected as a challenge for model application because it was affected by the Millennium drought, characterised by a decrease in precipitation and a dramatic drop in runoff. The model evaluation within the proposed framework starts with dividing the complete record period into five non-overlapping sub-periods, calibration and cross-validation (i.e., transfers) of the models. The Kling-Gupta efficiency coefficient is used for the calibration in each sub-period. Consistency in model performance, parameter estimates and simulated water balance components across the sub-periods is analysed. Model performance is quantified with statistical performance measures and errors in hydrological signatures. Because the relatively short monthly hydrologic series can lead to biased numerical performance indicators, the framework also includes subjective assessment of model performance and transferability. </p><p> </p><p>The results show that model transfer between climatically contrasted sub-periods affect all statistical measures of model performance and some hydrologic signatures: standard deviation of flows, high flow percentile and percentage of zero flows. While some signatures are reproduced well in all transfers (baseflow index, lag 1 and lag 12 autocorrelations), suggesting their low informativeness about MWBM performance, many signatures are consistently poorly reproduced, even in the calibrations (seasonal distribution, most flow percentiles, streamflow elasticity). This means that good model performance in terms of statistical measures does not imply good performance in terms of hydrologic signatures, probably because the models are not conditioned to reproduce them. Generally, the greatest drop in performance of all the models is obtained in transfers to the driest period, although abcd and Budyko slightly outperformed GR2M and WASMOD. Subjective assessment of model performance largely corresponds to the numerical indicators.</p><p> </p><p>Simulated water balance components, especially soil and groundwater storages and baseflow, significantly vary across the simulation periods. These results suggest that the model components and the parameters that control them are sensitive to the calibration period. Therefore, improved model conceptualisations (particularly partitioning of fast and slow runoff components) and enhanced calibration strategies that put more emphasis on parameters related to slow runoff are needed. More robust MWBM structures or calibration strategies should advance transferability of MWBMs, which is a prerequisite for effective water resources management under changing climate conditions.</p>

Characteristics and influencing factors of flash floods in Bavaria (Germany) – an analysis using a hydrological-hydraulic model ensemble

<p>In recent years, heavy precipitation and flash flood events frequently occurred in Germany. The project HiOS (reference map for surface runoff and flash floods) focusses on the analysis of these events using conceptual lumped precipitation runoff models, distributed raster-based water balance models (LARSIM and WaSiM), as well as a hydrodynamic model internally coupled with infiltration routines (TELEMAC-2D). The objective of our research is to analyze which factors and processes foster flash floods, and how they may be represented in models. We show a comprehensive methodological comparison using simulation results of some events in Bavaria. These do not include erosion and log jam scenarios.</p><p>The catchments distributed across whole Bavaria considering a variety of catchment characteristics and varying in size between 1.2 and 164km². All models are driven by 5 minute pseudo-calibrated radar precipitation data of the German Weather Service (YW product), which are available for entire Germany in a 1km² raster. The distributed water balance models are available using high-resolution cell grids. WaSiM uses a regular grid size of 50m, whereas LARSIM is run using 100m cells and an embedded hydrological response unit scheme. All TELEMAC-2D meshes are built with a standard mesh size of 5m in the catchment and 2m in the settled area of interest, while important hydrodynamic structures are resolved more in detail.</p><p>We want to highlight the variety of applied hydrological and hydrodynamic model approaches of runoff generation and concentration, whereby both, simple conceptual and complex physical methods are included. Runoff generation processes are represented using the SCS-CN method, a modified Lutz-Südbayern approach, a Xinjiang-bucket model combined with a Green&Ampt infiltration routine, as well as a layer-resolving Richards model. Beyond that, some of these consider silting up and soil crack formation. Runoff concentration processes are assessed by constant translation, Strickler flow time index method, a combination of Williams and Kalinin-Miljukov method, as well as finally with two-dimensionally resolved shallow water equations.</p><p>As expected, runoff generation is influenced by land use and soil parametrization. However, the amount of created runoff differs a lot changing the method of simulation. Furthermore, the runoff volume reacts quite sensitive to small changes in the preceding saturation conditions. Runoff concentration is influenced by slope, retention capacity of the flood plain, the network of drainages, as well as the formation of polders by water-crossing structures such as traffic infrastructure. Our results therefore clearly show the individual characteristics of extreme events depending on the catchment properties, which are reflected by the demands concerning the modelling techniques. The findings of this study illustrate the importance of improved radar-derived precipitation observations as well as the need for a spatially distributed and layered soil moisture product to enhance flash flood modelling using hydrological models.</p>