Global BROOK90: validation, uncertainties, current progress and future outline.

2021 ◽  
Author(s):  
Ivan Vorobevskii ◽  
Rico Kronenberg
Keyword(s):  
Water Balance ◽  
Model Performance ◽  
Low Flow ◽  
Easy Access ◽  
Climate Projections ◽  
Seasonal Forecasts ◽  
Water Balance Components ◽  
Discharge Data ◽  
Small Catchment ◽  
Wide Range

<p>‘Just drop a catchment and receive reasonable model output’ – still stays as motto and main idea of the ‘Global BROOK90’ project. The open-source R-package is build-up on global land cover, soil, topographical, meteorological datasets and the lumped hydrological model as a core to simulate water balance components on HRU scale all over the world in an automatic mode. First introduced in EGU2020 and followed by GitHub code release including an publication of methodology with few examples we want to continue with the insights on the current state and highlight the future steps of the project.</p><p>A global validation of discharge and evapotranspiration components of the model showed promising results. We used 190 small (median size of 64 km<sup>2</sup>) catchments and FLUXNET data which represent a wide range of relief, vegetation and soil types within various climate zones. The model performance was evaluated with NSE, KGE, KGESS and MAE. In more than 75 % of the cases the framework performed better than the mean of the observed discharge. On a temporal scale the performance is significantly better on a monthly vs daily scale. Cluster analysis revealed that some of the site characteristics have a significant influence on the performance. Additionally, it was found that Global BROOK90 outperforms GloFAS ERA5 discharge reanalysis (for the category with smallest catchments).</p><p>A cross-combination of three different BROOK90 setups and three forcing datasets was set up to reveal uncertainties of the Global BROOK90 package using a small catchment in Germany as a case study. Going from local to regional and finally global scale we compared mixtures of model parameterization schemes (original calibrated BROOK90, EXTRUSO and Global BROOK90) and meteorological datasets (local gauges, RaKlida and ERA5). Besides high model performances for a local dataset plus a calibrated model and weaker results for ERA5 and the Global BROOK90, it was found that the ERA5 dataset is still able to provide good results when combined with a regional and local parameterization. On the other side, the combination of a global parameterization with local and regional forcings gives still adequate, but much worse results. Furthermore, a hydrograph separation revealed that the Global BROOK90 parameterization as well as ERA5 discharge data perform weaker especially within low flow periods.</p><p>Currently, some new features are added to the original package. First, with the recent release of the ERA5 extension, historical simulations with the package now are expanded to 1950-2021 period. Additionally, an alternative climate reanalysis dataset is included in the framework (Merra-2, 0.5x0.625-degree spatial resolution, starting from 1980). A preliminary validation shows insignificant differences between both meteorological datasets with respect to the discharge based model performance.</p><p>Further upgrades of the framework will include the following core milestones: recognition of forecast and climate projections and parameter optimization features. In the nearest future we plan to utilize full power of the Climate Data Store for easy access to seasonal forecasts (i.e. ECMWF, DWD, NCEP) as well as climate projections (CMIP5) to extend the package’s scope to predict near and far future water balance components.</p>

scholarly journals Development of a large-sample watershed-scale hydrometeorological data set for the contiguous USA: data set characteristics and assessment of regional variability in hydrologic model performance

2015 ◽  
Vol 19 (1) ◽  
pp. 209-223 ◽  
Author(s):  
A. J. Newman ◽  
M. P. Clark ◽  
K. Sampson ◽  
A. Wood ◽  
L. E. Hay ◽  
...  
Keyword(s):  
United States ◽  
Seasonal Cycle ◽  
Model Performance ◽  
The United States ◽  
Hydrologic Model ◽  
Low Flow ◽  
Reference Level ◽  
Hydrologic Response ◽  
Data Set ◽  
Wide Range

Abstract. We present a community data set of daily forcing and hydrologic response data for 671 small- to medium-sized basins across the contiguous United States (median basin size of 336 km2) that spans a very wide range of hydroclimatic conditions. Area-averaged forcing data for the period 1980–2010 was generated for three basin spatial configurations – basin mean, hydrologic response units (HRUs) and elevation bands – by mapping daily, gridded meteorological data sets to the subbasin (Daymet) and basin polygons (Daymet, Maurer and NLDAS). Daily streamflow data was compiled from the United States Geological Survey National Water Information System. The focus of this paper is to (1) present the data set for community use and (2) provide a model performance benchmark using the coupled Snow-17 snow model and the Sacramento Soil Moisture Accounting Model, calibrated using the shuffled complex evolution global optimization routine. After optimization minimizing daily root mean squared error, 90% of the basins have Nash–Sutcliffe efficiency scores ≥0.55 for the calibration period and 34% ≥ 0.8. This benchmark provides a reference level of hydrologic model performance for a commonly used model and calibration system, and highlights some regional variations in model performance. For example, basins with a more pronounced seasonal cycle generally have a negative low flow bias, while basins with a smaller seasonal cycle have a positive low flow bias. Finally, we find that data points with extreme error (defined as individual days with a high fraction of total error) are more common in arid basins with limited snow and, for a given aridity, fewer extreme error days are present as the basin snow water equivalent increases.

scholarly journals Development of a large-sample watershed-scale hydrometeorological dataset for the contiguous USA: dataset characteristics and assessment of regional variability in hydrologic model performance

2014 ◽  
Vol 11 (5) ◽  
pp. 5599-5631
Author(s):  
A. J. Newman ◽  
M. P. Clark ◽  
K. Sampson ◽  
A. Wood ◽  
L. E. Hay ◽  
...  
Keyword(s):  
United States ◽  
Seasonal Cycle ◽  
Model Performance ◽  
The United States ◽  
Hydrologic Model ◽  
Low Flow ◽  
Reference Level ◽  
Hydrologic Response ◽  
Daily Streamflow ◽  
Wide Range

Abstract. We present a community dataset of daily forcing and hydrologic response data for 671 small- to medium-sized basins across the contiguous United States (median basin size of 336 km2) that spans a very wide range of hydroclimatic conditions. Areally averaged forcing data for the period 1980–2010 was generated for three basin delineations – basin mean, Hydrologic Response Units (HRUs) and elevation bands – by mapping the daily, 1 km gridded Daymet meteorological dataset to the sub-basin and basin polygons. Daily streamflow data was compiled from the United States Geological Survey National Water Information System. The focus of this paper is to (1) present the dataset for community use; and (2) provide a model performance benchmark using the coupled Snow-17 snow model and the Sacramento Soil Moisture Accounting conceptual hydrologic model, calibrated using the Shuffled Complex Evolution global optimization routine. After optimization minimizing daily root mean squared error, 90% of the basins have Nash–Sutcliffe Efficiency scores > 0.55 for the calibration period. This benchmark provides a reference level of hydrologic model performance for a commonly used model and calibration system, and highlights some regional variations in model performance. For example, basins with a more pronounced seasonal cycle generally have a negative low flow bias, while basins with a smaller seasonal cycle have a positive low flow bias. Finally, we find that data points with extreme error (defined as individual days with a high fraction of total error) are more common in arid basins with limited snow, and, for a given aridity, fewer extreme error days are present as basin snow water equivalent increases.

scholarly journals CHECKS ON THE WATER BALANCE OF A SMALL CATCHMENT

1972 ◽  
Vol 3 (1) ◽  
pp. 44-63 ◽  
Author(s):  
R. C. WARD
Keyword(s):  
Water Balance ◽  
Water Balance Components ◽  
Small Catchment ◽  
Boulder Clay ◽  
Residual Values ◽  
Water Balances

The paper discusses water balance data for a small (16 km2) boulder clay catchment. In order to check the accuracy of the calculations, water balances are cast for different, overlapping periods of time within the same run of data (e.g. three-year, annual, seasonal, monthly, ten-day and storm-period). For each period the residual values are satisfactorily low (cf. 12 mm for the three-year balance and zero for the storm-period balance). A further series of checks is provided by rewriting the water equation in a number of different ways to enable estimated and measured values of certain water balance components to be compared. It is concluded that the measured values seem to be accurate and that the catchment appears to be watertight.

scholarly journals Variability of Hydrological Parameters and Water Balance Components in Small Catchment in Croatia

2016 ◽  
Vol 2016 ◽  
pp. 1-9 ◽  
Author(s):  
Lidija Tadić ◽  
Tamara Dadić ◽  
Marija Leko-Kos
Keyword(s):  
Water Balance ◽  
Potential Evapotranspiration ◽  
Climate Change Impacts ◽  
Partial Sums ◽  
Data Series ◽  
Water Balance Components ◽  
Small Catchment ◽  
Air Temperatures ◽  
Hydrological Hazards ◽  
Great Pressure

Analysis of small catchment area in Croatian lowland with its hydrological characteristics in the period between 1981 and 2014 was carried out in order to define significance of change in hydrological and meteorological parameters (precipitation, air temperatures, and discharges) and water balance components (deep percolation and potential evapotranspiration). There was no significant land use change in the observed period, so all changes in hydrological processes can be considered to be without human impact in the last 35 years. Application of RAPS (Rescaled Adjusted Partial Sums) on all data series distinguished two subperiods with different length but the same behaviour. The first subperiod was a period characterised by the decrease, starting in 1980 and finishing between 1991 and 1995, while the second one was a period characterised by the increase of parameters in all analyses, starting between 1991 and 1995 and finishing in 2001. In comparison to the analysis of climate change impacts per decade, this approach is much more appropriate and gives insight into variations throughout the entire observed period. The most variable but not significant parameters are precipitation and discharges, especially in the second subperiod which has a major impact on occurrence of hydrological hazards such as droughts and floods and makes great pressure and responsibility on water management system.

scholarly journals Evaluation of the use of radar-derived precipitation in water balance simulations: A case study in small-medium catchments in Saxony, Germany

2021 ◽  
Author(s):  
Thanh Thi Luong ◽  
Ivan Vorobevskii ◽  
Judith Pöschmann ◽  
Rico Kronenberg
Keyword(s):  
Water Balance ◽  
Spatial Information ◽  
Regional Scale ◽  
Model Performance ◽  
Radar Data ◽  
Rain Gauge ◽  
Hydrologic Model ◽  
Water Balance Components ◽  
Precipitation Estimation ◽  
Radar Imagery

<p>Water balance estimation/modeling is highly dependent on good-quality precipitation data and often lacks enough spatial information about it. Quantitative precipitation estimation (QPE) using radar data is recognized to have a good potential to significantly enhance the spatial depiction of precipitation compared to conventional rain gauge-based methods. However, precipitation measurements are often underestimated by wind drift or funnel evaporation, so that a correction such as Richter’s method is required before the data can be applied in the model. In this study, the Richter correction is applied for the first time to a radar-based QPE, namely RADKLIM-RW, to model water balance in ten selected catchments in Saxony, Germany. The modelled water balance components for the period 2001-2017 were evaluated by means of comparison of radar- and gauge-based precipitation inputs. The results showed that RADKLIM-RW was able to produce reliable simulations of discharge and water balance (KGE = 0.56 and 0.71 on the daily and monthly scales respectively). Application of the Richter correction improved the model performance by 5.5% and 8.9 % (for rain gauge-based and RADKLIM precipitation respectively). The study concluded that radar data as precipitation input to (pseudo)distributed hydrologic model shows immense potential to improve water balance simulations.</p><p><strong>Hightlights</strong>:</p><ul><li>Comparison of precipitation derived from sensor networks and radar imagery for small catchments</li> <li>Evaluation of potential application of radar precipitation in water balance simulation at regional scale</li> <li>Effect of wind correction (“Richter” correction) on radar precipitation products</li> <li>Evaluating corrected precipitation on water balance processes</li> </ul><p><strong>Keywords</strong>: HRU, radar climatology, RADKLIM RW (RADOLAN), Richter correction, Open sensor network, water balance simulation, BROOK90</p>

Improving continental scale hydrological model performance and stability under variable climate conditions in order to improve the assessment of future water resources

2021 ◽  
Author(s):  
Wendy Sharples ◽  
Andrew Frost ◽  
Ulrike Bende-Michl ◽  
Ashkan Shokri ◽  
Louise Wilson ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Balance ◽  
Hydrological Model ◽  
Model Performance ◽  
Water Balance Components ◽  
Climate Conditions ◽  
Water Balance Component ◽  
Multi Objective ◽  
Model Parameterization ◽  
The Future

<p>Ensuring future water security in a changing climate is becoming a top priority for Australia, which is already dealing with the ongoing socio-economic and environmental impacts from record-breaking bushfires, infrastructure damage from recent flash flooding events, and the prospect of continuing compromised water sources in both regional towns and large cities into the future. In response to these significant impacts the Australian Bureau of Meteorology is providing a hydrological projections service, using their national operational hydrological model (The Australian Water Resources Assessment model: AWRA-L, www.bom.gov.au/water/landscape), to project future hydrological fluxes and states using downscaled meteorological inputs from an ensemble of curated global climate models and emissions scenarios at a resolution of 5km out to the end of this century.</p><p>Continental model calibration using a long record of Australian observational data has been employed across components of the water balance, to tune the model parameters to Australia's varied hydro-climate, thereby reducing uncertainty associated with inputs and hydrological model structure. This approach has been shown to improve the accuracy of simulated hydrological fields, and the skill of short term and seasonal forecasts. However, in order to improve model performance and stability for use in hydrological projections, it is desirable to choose a model parameterization which produces reasonable hydrological responses under conditions of climate variability as well as under historical conditions. To this end we have developed a two-stage approach: Firstly, a variance based sensitivity analysis for water balance components (e.g. ephemeral flow, average to high flow, recharge, soil moisture and evapotranspiration) is performed, to rank the most influential parameters affecting water balance components. Parameters which are insensitive across components are then fixed to a previously optimized value, decreasing the number of calibratable parameters in order to decrease dimensionality and uncertainty in the calibration process. Secondly, a model configured with reduced calibratable parameters is put through a multi-objective evolutionary algorithm (Borg MOEA, www.borgmoea.org), to capture the tradeoffs between the water balance component performance objectives under climate variable conditions (e.g. wet, dry and historical) and across climate regions derived from the natural resource management model (https://nrmregionsaustralia.com.au/).</p><p>The decreased dimensionality is shown to improve the stability and robustness of the existing calibration routine (shuffled complex evolution) as well as the multi-objective routine. Upon examination of the tradeoffs between the water balance component objective functions and in-situ validation data under historical, wet and dry periods and across different Australian climate regions, we show there is no one size fits all parameter set continentally, and thus some concessions need to be made in choosing a suitable model parameterization. However, future work could include developing a set of parameters which suit specific regions or climate conditions in Australia. The approach outlined in this study could be employed to improve confidence in any hydrological model used to simulate the future impacts of climate change. </p>

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

2020 ◽  
Author(s):  
Zana Topalovic ◽  
Andrijana Todorovic ◽  
Jasna Plavsic
Keyword(s):  
Water Balance ◽  
Model Performance ◽  
Subjective Assessment ◽  
Water Balance Components ◽  
Climate Conditions ◽  
Changing Climate ◽  
Statistical Measures ◽  
Water Balance Models ◽  
Model Components ◽  
Monthly Water Balance

<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>

scholarly journals The Elements of Water Balance in the Changing Climate in Poland

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Małgorzata Szwed
Keyword(s):  
Water Balance ◽  
Climate Models ◽  
Control Period ◽  
Thermal Characteristics ◽  
Climate Change Impacts ◽  
Climate Projections ◽  
The European Union ◽  
Water Balance Components ◽  
Considerable Uncertainty ◽  
The Future

Strong global warming has been observed in the last three decades. Central Europe, including Poland, is not an exception. Moreover, climate projections for Poland foresee further warming as well as changes in the spatial and seasonal distribution and quantity of precipitation. However, climate models do not agree on the sign of change of precipitation. In Poland precipitation is projected to decrease in summer (this finding is not robust, being model-dependent) and to increase in winter. Therefore, there is still considerable uncertainty regarding likely climate change impacts on water resources in Poland. However, there is no doubt that changes in the thermal characteristics as well as in precipitation will influence changes in the water balance of the country. In this study, the components of climatic water balance, that is, precipitation, evaporation, and runoff, are calculated for the average conditions in the control period of 1961–1990 and in the future (2071–2100) in Poland. The changes of the water balance components for the present and for the future are compared and analysed. Due to insufficient consistency between climate models a possible range of changes should be presented; hence the multimodel projections from ENSEMBLES Project of the European Union are used in this study.

scholarly journals Assessment of Changes in Water Balance Components under 1.5 °C and 2.0 °C Global Warming in Transitional Climate Basin by Multi-RCPs and Multi-GCMs Approach

Water ◽  
2018 ◽  
Vol 10 (12) ◽  
pp. 1863 ◽  
Author(s):  
Ying Hao ◽  
Jingjin Ma ◽  
Jing Chen ◽  
Dongyong Wang ◽  
Yuan Wang ◽  
...  
Keyword(s):  
Global Warming ◽  
Water Balance ◽  
Surface Runoff ◽  
General Circulation ◽  
Lateral Flow ◽  
Spatial Inhomogeneity ◽  
Climate Projections ◽  
Water Balance Components ◽  
Change Trend ◽  
The Impact

The global warming of 1.5 °C and 2.0 °C proposed in the Paris Agreement has become the iconic threshold of climate change impact research. This study aims to assess the potential impact of 1.5 °C and 2.0 °C global warming on water balance components (WBC) in a transitional climate basin—Chaobai River Basin (CRB)—which is the main water supply source of Beijing. A semi-distributed hydrological model SWAT (Soil and Water Assessment Tool) was driven by climate projections from five General Circulation Models (GCMs) under three Representative Concentration Pathways (RCPs) to simulate the future WBC in CRB under the 1.5 °C and 2.0 °C global warming, respectively. The impacts on annual, monthly WBC were assessed and the uncertainty associated with GCMs and RCPs were analyzed quantitatively, based on the model results. Finally, spatial variation of WBC change trend and its possible cause were discussed. The analysis results indicate that all the annual WBC and water budget are projected to increase under both warming scenarios. Change trend of WBC shows significant seasonal and spatial inhomogeneity. The frequency of flood will increase in flood season, while the probability of drought in autumn and March is expected to rise. The uneven spatial distribution of change trend might be attributed to topography and land use. The comparison between two warming scenarios indicates that the increment of 0.5 °C could lead to the decrease in annual surface runoff, lateral flow, percolation, and the increase in annual precipitation and evapotranspiration (ET). Uncertainties of surface runoff, lateral flow, and percolation projections are greater than those of other components. The additional 0.5 °C global warming will lead to larger uncertainties of future temperature, precipitation, surface runoff, and ET assessment, but slightly smaller uncertainties of lateral flow and percolation assessment. GCMs are proved to be the main factors that are responsible for the impact uncertainty of the majority assessed components.

scholarly journals Extending a Large-Scale Model to Better Represent Water Resources without Increasing the Model’s Complexity

Water ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 3067
Author(s):  
Robyn Horan ◽  
Nathan J. Rickards ◽  
Alexandra Kaelin ◽  
Helen E. Baron ◽  
Thomas Thomas ◽  
...  
Keyword(s):  
Large Scale ◽  
Model Performance ◽  
Data Availability ◽  
Model Complexity ◽  
Low Flow ◽  
Scale Model ◽  
Water Balance Components ◽  
Large Scale Model ◽  
Scale Models ◽  
Availability Assessment

The increasing impact of anthropogenic interference on river basins has facilitated the development of the representation of human influences in large-scale models. The representation of groundwater and large reservoirs have realised significant developments recently. Groundwater and reservoir representation in the Global Water Availability Assessment (GWAVA) model have been improved, critically, with a minimal increase in model complexity and data input requirements, in keeping with the model’s applicability to regions with low-data availability. The increased functionality was assessed in two highly anthropogenically influenced basins. A revised groundwater routine was incorporated into GWAVA, which is fundamentally driven by three input parameters, and improved the simulation of streamflow and baseflow in the headwater catchments such that low-flow model skill increased 33–67% in the Cauvery and 66–100% in the Narmada. The existing reservoir routine was extended and improved the simulation of streamflow in catchments downstream of major reservoirs, using two calibratable parameters. The model performance was improved between 15% and 30% in the Cauvery and 7–30% in the Narmada, with the daily reservoir releases in the Cauvery improving significantly between 26% and 164%. The improvement of the groundwater and reservoir routines in GWAVA proved successful in improving the model performance, and the inclusions allowed for improved traceability of simulated water balance components. This study illustrates that improvement in the representation of human–water interactions in large-scale models is possible, without excessively increasing the model complexity and input data requirements.

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