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

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.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/).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.&#160;

Download Full-text

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

10.5194/egusphere-egu2020-8552 ◽

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

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&#8217; 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.&#160;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.&#160;&#160;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.&#160;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.

Download Full-text

Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use

Hydrology and Earth System Sciences ◽

10.5194/hess-20-2877-2016 ◽

2016 ◽

Vol 20 (7) ◽

pp. 2877-2898 ◽

Cited By ~ 73

Author(s):

Hannes Müller Schmied ◽

Linda Adam ◽

Stephanie Eisner ◽

Gabriel Fink ◽

Martina Flörke ◽

...

Keyword(s):

Water Resources ◽

Water Balance ◽

Water Use ◽

Climate Forcing ◽

Land Area ◽

Water Balance Components ◽

Climate Forcings ◽

The Impact ◽

Global Water

Abstract. When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.

Download Full-text

On the selection of precipitation products for the regionalisation of hydrological model parameters

Hydrology and Earth System Sciences ◽

10.5194/hess-25-5805-2021 ◽

2021 ◽

Vol 25 (11) ◽

pp. 5805-5837

Author(s):

Oscar M. Baez-Villanueva ◽

Mauricio Zambrano-Bigiarini ◽

Pablo A. Mendoza ◽

Ian McNamara ◽

Hylke E. Beck ◽

...

Keyword(s):

Hydrological Model ◽

Model Performance ◽

Temporal Distribution ◽

Hydrological Regime ◽

Hydrologic Model ◽

Spatial Proximity ◽

Model Parameters ◽

Ungauged Catchments ◽

Water Balance Components ◽

Feature Similarity

Abstract. Over the past decades, novel parameter regionalisation techniques have been developed to predict streamflow in data-scarce regions. In this paper, we examined how the choice of gridded daily precipitation (P) products affects the relative performance of three well-known parameter regionalisation techniques (spatial proximity, feature similarity, and parameter regression) over 100 near-natural catchments with diverse hydrological regimes across Chile. We set up and calibrated a conceptual semi-distributed HBV-like hydrological model (TUWmodel) for each catchment, using four P products (CR2MET, RF-MEP, ERA5, and MSWEPv2.8). We assessed the ability of these regionalisation techniques to transfer the parameters of a rainfall-runoff model, implementing a leave-one-out cross-validation procedure for each P product. Despite differences in the spatio-temporal distribution of P, all products provided good performance during calibration (median Kling–Gupta efficiencies (KGE′s) > 0.77), two independent verification periods (median KGE′s >0.70 and 0.61, for near-normal and dry conditions, respectively), and regionalisation (median KGE′s for the best method ranging from 0.56 to 0.63). We show how model calibration is able to compensate, to some extent, differences between P forcings by adjusting model parameters and thus the water balance components. Overall, feature similarity provided the best results, followed by spatial proximity, while parameter regression resulted in the worst performance, reinforcing the importance of transferring complete model parameter sets to ungauged catchments. Our results suggest that (i) merging P products and ground-based measurements does not necessarily translate into an improved hydrologic model performance; (ii) the spatial resolution of P products does not substantially affect the regionalisation performance; (iii) a P product that provides the best individual model performance during calibration and verification does not necessarily yield the best performance in terms of parameter regionalisation; and (iv) the model parameters and the performance of regionalisation methods are affected by the hydrological regime, with the best results for spatial proximity and feature similarity obtained for rain-dominated catchments with a minor snowmelt component.

Download Full-text

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

10.5194/egusphere-egu21-742 ◽

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

&#8216;Just drop a catchment and receive reasonable model output&#8217; &#8211; still stays as motto and main idea of the &#8216;Global BROOK90&#8217; 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.A global validation of discharge and evapotranspiration components of the model showed promising results. We used 190 small (median size of 64 km2) 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).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.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.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&#8217;s scope to predict near and far future water balance components.

Download Full-text

Landscape-scale water balance monitoring with an iGrav superconducting gravimeter in a field enclosure

Hydrology and Earth System Sciences ◽

10.5194/hess-21-3167-2017 ◽

2017 ◽

Vol 21 (6) ◽

pp. 3167-3182 ◽

Cited By ~ 12

Author(s):

Andreas Güntner ◽

Marvin Reich ◽

Michal Mikolaj ◽

Benjamin Creutzfeldt ◽

Stephan Schroeder ◽

...

Keyword(s):

Time Series ◽

Water Balance ◽

Water Storage ◽

Superconducting Gravimeter ◽

Landscape Scale ◽

Temperate Climate ◽

Water Balance Components ◽

Climate Conditions ◽

The Road ◽

Field Deployment

Abstract. In spite of the fundamental role of the landscape water balance for the Earth's water and energy cycles, monitoring the water balance and its components beyond the point scale is notoriously difficult due to the multitude of flow and storage processes and their spatial heterogeneity. Here, we present the first field deployment of an iGrav superconducting gravimeter (SG) in a minimized enclosure for long-term integrative monitoring of water storage changes. Results of the field SG on a grassland site under wet–temperate climate conditions were compared to data provided by a nearby SG located in the controlled environment of an observatory building. The field system proves to provide gravity time series that are similarly precise as those of the observatory SG. At the same time, the field SG is more sensitive to hydrological variations than the observatory SG. We demonstrate that the gravity variations observed by the field setup are almost independent of the depth below the terrain surface where water storage changes occur (contrary to SGs in buildings), and thus the field SG system directly observes the total water storage change, i.e., the water balance, in its surroundings in an integrative way. We provide a framework to single out the water balance components actual evapotranspiration and lateral subsurface discharge from the gravity time series on annual to daily timescales. With about 99 and 85 % of the gravity signal due to local water storage changes originating within a radius of 4000 and 200 m around the instrument, respectively, this setup paves the road towards gravimetry as a continuous hydrological field-monitoring technique at the landscape scale.

Download Full-text

Applications of Hydrological Model Simulated Long Term Water Balance Components for India

10.22541/au.159423230.01524040 ◽

2020 ◽

Author(s):

Saksham Joshi ◽

Venkat Raju Pokkuluri ◽

Annie Issac ◽

Venkateshwar Rao ◽

Pamaraju Venkata Rao ◽

...

Keyword(s):

Water Balance ◽

Hydrological Model ◽

Water Balance Components

Download Full-text

Future climate changes under different scenarios and their effects on runoff in the upper Taohe River Basin

10.22541/au.161223416.66421339/v1 ◽

2021 ◽

Author(s):

zhen wang ◽

Meixue Yang ◽

xuejia wang ◽

lizhen cheng ◽

guoning wan ◽

...

Keyword(s):

Climate Change ◽

Water Resources ◽

River Basin ◽

Average Method ◽

Climate Changes ◽

Hydrological Model ◽

Moving Average ◽

Future Climate ◽

Annual Average ◽

The Future

Climate changes may pose challenges to water management. Simulation and projection of climate-runoff processes through hydrological models are essential means to assess the impact of global climate change on runoff variations. This study focuses on the upper Taohe River Basin which is an important water sources for arid and semi-arid regions in Northwest China. In order to assess the impacts of environmental changes, outputs from a regional climate model and the SWAT hydrological model were used to analyze the future climate change scenarios to water resources quantitatively. The examined climate changes scenarios results showed that average annual temperature from 2020 to 2099 in this area exhibits a consistent warming trend with different warming rates, at rates of 0.10°C/10a, 0.20°C /10a and 0.54°C /10a under RCP2.6, RCP4.5 and RCP8.5(Representative Concentration Pathways, RCPs), The value of precipitation experiences different trends under different emission scenarios. Under the RCP2.6, average precipitation would decrease at a rate of 3.69 mm/10a, while under the RCP4.5 and RCP8.5, it would increase at rates of 4.97 mm/10a and 12.28 mm/10a, respectively. The calibration and validation results in three in-site observations (Luqu, Xiabagou and Minxian) in the upper Taohe River Basin showed that SWAT hydrological model is able to produce an acceptable simulation of runoff at monthly time-step. In response to future climate changes, projected runoff change would present different decreasing trends. Under RCP2.6, annual average runoff would experience a progress of fluctuating trend, with a rate of-0.6×108m3 by 5-year moving average method; Under the RCP4.5 and RCP8.5, annual average runoff would show steadily increasing trends, with rates of 0.23×108m3 and 0.16×108m3 by 5-year moving average method. The total runoff in the future would prone to drought and flood disasters. Overall, this research results would provide a scientific reference for reginal water resources management on the long term.

Download Full-text

Impact Assessment of Climate Change on the Near and the Far Future Streamflow in the Bocheongcheon Basin of Geumgang River, South Korea

Water ◽

10.3390/w13182516 ◽

2021 ◽

Vol 13 (18) ◽

pp. 2516

Author(s):

Yoonji Kim ◽

Jieun Yu ◽

Kyungil Lee ◽

Hye In Chung ◽

Hyun Chan Sung ◽

...

Keyword(s):

Climate Change ◽

Water Resources ◽

Water Resources Management ◽

Model Performance ◽

Hydrologic Model ◽

Management Policy ◽

Resources Management ◽

The Future ◽

Management Plans ◽

The Impact

Highly concentrated precipitation during the rainy season poses challenges to the South Korean water resources management in efficiently storing and redistributing water resources. Under the new climate regime, water resources management is likely to become more challenging with regards to water-related disaster risk and deterioration of water quality. To alleviate such issues by adjusting management plans, this study examined the impact of climate change on the streamflow in the Bocheongcheon basin of the Geumgang river. A globally accepted hydrologic model, the HEC-HMS model, was chosen for the simulation. By the calibration and the validation processes, the model performance was evaluated to range between “satisfactory” and “very good”. The calibrated model was then used to simulate the future streamflow over six decades from 2041 to 2100 under RCP4.5 and RCP8.5. The results indicated significant increase in the future streamflow of the study site in all months and seasons over the simulation period. Intensification of seasonal differences and fluctuations was projected under RCP 8.5, implying a challenge for water resources managers to secure stable sources of clean water and to prevent water-related disasters. The analysis of the simulation results was applied to suggest possible local adaptive water resources management policy.

Download Full-text

Extending a Large-scale Model to Better Represent Water Resources without Increasing the Model Complexity

10.20944/preprints202109.0195.v1 ◽

2021 ◽

Author(s):

Robyn Horan ◽

Nathan J. Rickards ◽

Alexandra Kaelin ◽

Helen E. Baron ◽

Thomas Thomas ◽

...

Keyword(s):

Water Resources ◽

Input Data ◽

Large Scale ◽

Model Performance ◽

Model Complexity ◽

Scale Model ◽

Groundwater Abstraction ◽

Water Balance Components ◽

Groundwater Levels ◽

Hydrological System

A robust hydrological assessment is challenging in regions where human interference, within all aspects of the hydrological system, significantly alters the flow regime of rivers. The challenge was to extend a large-scale water resources model, GWAVA, to better represent water resources without increasing the model complexity. A groundwater and a regulated reservoir routine were incorporated into GWAVA using modifications of the existing AMBHAS-1D and Hanasaki methodologies, respectively. The groundwater routine can be varied in complexity when sufficient input data is available but fundamentally is driven by three input parameters. The reservoir routine was extended to account for the presence of large, regulated reservoirs using two calibratable parameters. The additional groundwater processes and reservoir regulation was tested in two highly anthropogenically influenced basins in India: the Cauvery and Narmada. The inclusion of the revised groundwater routine improved the simulation of streamflow in the headwater catchments and was successful in improving the representation of the baseflow component. In addition, the model was able to produce a time series of daily groundwater levels, recharge to groundwater and groundwater abstraction. The regulated reservoir routine improved the simulation of streamflow in catchments downstream of major reservoirs, where the streamflow was largely reflective of reservoir releases, when calibrated using downstream observed streamflow records. The model was able to provide a more robust representation of the annual volume and daily outflow released from the major reservoirs and simulate the major reservoir storages adequately. The addition of one-dimensional groundwater processes and a regulated reservoir routine proved successful in improving the model performance and traceability of water balance components, without excessively increasing the model complexity and input data requirements.

Download Full-text

Testing the Robustness of a Physically-Based Hydrological Model in Two Data Limited Inland Valley Catchments in Dano, Burkina Faso

Hydrology ◽

10.3390/hydrology7030043 ◽

2020 ◽

Vol 7 (3) ◽

pp. 43

Author(s):

Mouhamed Idrissou ◽

Bernd Diekkrüger ◽

Bernhard Tischbein ◽

Boubacar Ibrahim ◽

Yacouba Yira ◽

...

Keyword(s):

Soil Moisture ◽

Water Balance ◽

Burkina Faso ◽

Hydrological Model ◽

Model Performance ◽

Surface Flow ◽

Small Scale ◽

Model Parameters ◽

Inland Valley ◽

Physically Based

This study investigates the robustness of the physically-based hydrological model WaSiM (water balance and flow simulation model) for simulating hydrological processes in two data sparse small-scale inland valley catchments (Bankandi-Loffing and Mebar) in Burkina Faso. An intensive instrumentation with two weather stations, three rain recorders, 43 piezometers, and one soil moisture station was part of the general effort to reduce the scarcity of hydrological data in West Africa. The data allowed us to successfully parameterize, calibrate (2014–2015), and validate (2016) WaSiM for the Bankandi-Loffing catchment. Good model performance concerning discharge in the calibration period (R2 = 0.91, NSE = 0.88, and KGE = 0.82) and validation period (R2 = 0.82, NSE = 0.77, and KGE = 0.57) was obtained. The soil moisture (R2 = 0.7, NSE = 0.7, and KGE = 0.8) and the groundwater table (R2 = 0.3, NSE = 0.2, and KGE = 0.5) were well simulated, although not explicitly calibrated. The spatial transposability of the model parameters from the Bankandi-Loffing model was investigated by applying the best parameter-set to the Mebar catchment without any recalibration. This resulted in good model performance in 2014–2015 (R2 = 0.93, NSE = 0.92, and KGE = 0.84) and in 2016 (R2 = 0.65, NSE = 0.64, and KGE = 0.59). This suggests that the parameter-set achieved in this study can be useful for modeling ungauged inland valley catchments in the region. The water balance shows that evaporation is more important than transpiration (76% and 24%, respectively, of evapotranspiration losses) and the surface flow is very sensitive to the observed high interannual variability of rainfall. Interflow dominates the uplands, but base flow is the major component of stream flow in inland valleys. This study provides useful information for the better management of soil and scarce water resources for smallholder farming in the area.

Download Full-text