HS2.5.2 | Recent advancement in estimating global, continental and regional scale water balance components
EDI PICO
Recent advancement in estimating global, continental and regional scale water balance components
Convener: Hannes Müller Schmied | Co-conveners: Verena Bessenbacher, Rohini Kumar, Robert Reinecke, Maike Schumacher
PICO
| Wed, 26 Apr, 08:30–10:15 (CEST), 10:45–12:30 (CEST)
 
PICO spot 4
Wed, 08:30
Since early work on the assessment of global, continental and regional-scale water balance components, many studies use different approaches including global models, as well as data-driven approaches that ingest in-situ or remotely sensed observations or combinations of these. They attempted to quantify water fluxes (e.g. evapotranspiration, streamflow, groundwater recharge) and water storage on the terrestrial part of the Earth, either as total estimates (e.g. from GRACE satellites) or in separate compartments (e.g. water bodies, snow, soil, groundwater). In addition, increasing attention is given to uncertainties that stem from forcing datasets, model structure, parameters and combinations of these. Current estimates in literature show that flux and storage estimates differ considerably due to the methodology and datasets used such that a robust assessment of global, continental and regional water balance components remains challenging.

This session is seeking for contributions focusing on:
i. past/future assessment of water balance components (fluxes and storages) such as precipitation, freshwater fluxes to the oceans (and/or inland sinks), evapotranspiration, groundwater recharge, water use, changes in terrestrial water storage or individual components at global, continental and regional scales,
ii. application of innovative explorative approaches undertaking such assessments – through better use of advanced data driven, statistical approaches and approaches to assimilate (or accommodate) remote sensing datasets for improved estimation of terrestrial water storages/fluxes,
iii. analysis of different sources of uncertainties in estimated water balance components,
iv. examination and attribution of systematic differences in storages/flux estimates between different methodologies, and/or
v. applications/consequences of those findings such as sea level rise and water scarcity.

We encourage submissions using different methodological approaches. Contributions could focus on any of the water balance components or in an integrative manner with focus on global, continental or regional scale applications. Assessments of uncertainty in past/future estimates of water balance components and their implications are highly welcome.

PICO: Wed, 26 Apr | PICO spot 4

Chairpersons: Rohini Kumar, Hannes Müller Schmied
08:30–08:35
08:35–08:45
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PICO4.1
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EGU23-2246
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solicited
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On-site presentation
Hylke Beck, Albert van Dijk, Pablo Larraondo, Tim McVicar, Ming Pan, Emanuel Dutra, and Diego Miralles

We present Multi-Source Weather (MSWX), a seamless global gridded near-surface meteorological product featuring a high 3-hourly 0.1° resolution, near-real-time updates (∼3-h latency), and bias-corrected medium-range (up to 10 days) and long-range (up to 7 months) forecast ensembles. The product includes 10 meteorological variables: precipitation, air temperature, daily minimum and maximum air temperature, surface pressure, relative and specific humidity, wind speed, and downward shortwave and longwave radiation. The historical part of the record starts 1 January 1979 and is based on ERA5 data bias corrected and downscaled using high-resolution reference climatologies. The data extension to within ∼3 h of real time is based on analysis data from GDAS. The 30-member medium-range forecast ensemble is based on GEFS and updated daily. Finally, the 51-member long-range forecast ensemble is based on SEAS5 and updated monthly. The near-real-time and forecast data are statistically harmonized using running-mean and cumulative distribution function-matching approaches to obtain a seamless record covering 1 January 1979 to 7 months from now. MSWX presents new and unique opportunities for hydrological modeling, climate analysis, impact studies, and monitoring and forecasting of droughts, floods, and heatwaves (within the bounds of the caveats and limitations discussed herein). The product is available at www.gloh2o.org/mswx.

How to cite: Beck, H., van Dijk, A., Larraondo, P., McVicar, T., Pan, M., Dutra, E., and Miralles, D.: MSWX: Global 3-Hourly 0.1° Bias-Corrected Meteorological Data Including Near-Real-Time Updates and Forecast Ensembles, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2246, https://doi.org/10.5194/egusphere-egu23-2246, 2023.

08:45–08:47
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PICO4.2
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EGU23-2748
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ECS
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On-site presentation
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Zhuoyi Tu and Yuting Yang

Potential evaporation (EP) is an important concept that has been extensively used in hydrology, climate, agriculture and many other relevant fields. However, EP estimates using conventional approaches generally do not conform with the underlying idea of EP, since meteorological forcing variables observed under real conditions are not necessarily equivalent to those over a hypothetical surface with an unlimited water supply. Here, we estimate EP using a recently developed ocean surface evaporation model (i.e., the maximum evaporation model) that explicitly acknowledges the inter-dependence between evaporation, surface temperature (Ts) and radiation such that is able to recover radiation and Ts to a hypothetical wet surface. We first test the maximum evaporation model over land by validating its evaporation estimates with evaporation observations under unstressed conditions at 86 flux sites and found an overall good performance. We then apply the maximum evaporation model to the entire terrestrial surfaces under both wet and dry conditions to estimate EP. The mean annual (1979-2019) global land EP from the maximum evaporation model (EP_max) is 1272 mm yr-1, which is 11.2% higher than that estimated using the widely adopted Priestley-Taylor model (EP_PT). The difference between EP_max and EP_PT is negligible in humid regions or under wet conditions but becomes increasingly larger as the surface moisture availability decreases. This difference is primarily caused by increased net radiation (Rn) when restoring the dry surfaces to hypothetical wet surfaces, despite a lower Ts obtained under hypothetical wet conditions in the maximum evaporation model.

How to cite: Tu, Z. and Yang, Y.: On the estimation of potential evaporation under wet and dry conditions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2748, https://doi.org/10.5194/egusphere-egu23-2748, 2023.

08:47–08:49
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PICO4.3
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EGU23-10850
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ECS
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Virtual presentation
P Kedarnath Reddy, Nishan Bhattarai, and Sumit Sen

Hydrological budgeting of mountainous watersheds like the Indian Himalayan Region (IHR) is critical as they supply water for most of the Indian Sub-continent. Estimating evapotranspiration (ET), a major eco-hydrological process that returns a significant amount of terrestrial precipitation to the atmosphere, however, is a challenge in data-scare regions like IHR. This is further complicated by the geographic extent of the Indian Himalayas, which cover 13 states within the Himalayan range that possess a significant climatic and biotic gradient from east to west. This study aims to compare the applicability of various potential ET (PET) methods for the eastern and western Himalayan regions under different hydro-climatic conditions and suggest the best-fit method using easily accessible hydrometeorological data. The data for this study was obtained from 17 stations covering the IHR extensively during two study periods (1972-1982 and 2003-2009) from the Indian Meteorological Department (IMD). Four temperature-based methods (Thornthwaite, Blaney-Criddle, Kharrufa, and Hargreaves method) were tested against the modified Penman-Monteith (PM) method using reanalysis data (PM-PET). The PET estimates for the stations showed similar variations across three different elevation ranges. Further, it was observed that the Western Himalayas experienced lesser months of drier conditions (i.e., higher PET values during 2-3 months) compared to the Eastern Himalayas, which typically experienced 4-5 months of higher ET demand. It was observed that the PET values from the Hargreaves method were close to PM-PET with NSE (Nash-Sutcliffe Efficiency) values ranging from 0.75-0.92 and r2 values ranging from 0.72-0.92 (except for Jammu; NSE = 0.5, r2 = 0.41) and was found to serve as the best temperature-based method among the four methods for PET estimation in the Western and Central Himalayan region. However, no temperature-based method provided reasonable PET estimates in Eastern Himalayas, as the NSE and r2 values were less than 0.3 for all the methods.  Thus, there is a need to explore why temperature-based PET methods may not be applicable to the Eastern Himalayan region and evaluate other PET methods that are more reliable in this region.

How to cite: Reddy, P. K., Bhattarai, N., and Sen, S.: Understanding Evapotranspiration Variability between the Eastern and Western Himalayas, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10850, https://doi.org/10.5194/egusphere-egu23-10850, 2023.

08:49–08:51
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PICO4.4
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EGU23-1822
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ECS
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On-site presentation
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Changming Li, Hanbo Yang, Wencong Yang, and Ziwei Liu

Evapotranspiration (ET) is one of the key elements linking Earth’s water-carbon system. Accurate estimation of global land evapotranspiration is essential for understanding land-atmosphere interactions under a changing climate. Past decades have witnessed the generation of various ET products. However, due to a lack of observations at the global scale, inherent uncertainties limit the direct use of these data. Here, the aims of our study were as follows: (1) to employ collocation analysis methods, including single and double instrumental variable algorithms (IVS/IVD), triple collocation (TC), quadruple collocation (QC), and extended double instrumental variable algorithms (EIVD) to evaluate five widely used ET products at 0.1° and 0.25° resolutions over daily and 8-day frequencies, including ERA5, FLUXCOM, PMLV2, GLDAS, and GLEAM; (2) to design and validate a collocation-based method for ET merging and generate a long-term (1980-2022) ET product at 0.1°-8Daily and 0.25°-Daily resolutions and evaluate the performance against 68 global flux tower observations. Our results demonstrated that: (1) collocation analysis methods could be reliable tools to serve as alternatives for tower observations at the global scale, which could be helpful for further data assimilation and merging; (2) the merged product performed well over different vegetation types with Correlation of Determination () of 0.65, and 0.61 and root mean square errors () of 0.94 and 1.22 mm/d on average over 0.1° and 0.25°.

How to cite: Li, C., Yang, H., Yang, W., and Liu, Z.: Error Characterization and Multi-source Merging of Global Land Evapotranspiration Products: Collocation-based approach, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1822, https://doi.org/10.5194/egusphere-egu23-1822, 2023.

08:51–08:53
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PICO4.5
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EGU23-4642
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On-site presentation
Daeha Kim and Jong Ahn Chun

The complementary evaporation principle (CEP) could well explain the past changes in global evaporation while avoiding uncertainties in precipitation and soil data. However, it is still difficult to estimate the Priestley-Taylor coefficient (α) for the wet-surface evaporation without actual evaporation data. Here, we proposed an empirical approach that links the CEP and a traditional Budyko equation in order to determine α in locations where no actual evaporation (E) data are available. The CEP–Budyko combined framework enabled us to local climate conditions in α, producing more plausible E estimates in the ungauged locations. We also assessed latitudinal and temporal variations of the E estimates for the past 40 years. This study highlights that the optimal α for CEP is unlikely constant in space, since it needs to be conditioned by local climates.

How to cite: Kim, D. and Chun, J. A.: Changes in global evaporation for the past four decades identified by the complementary evaporation principle and the Budyko framework, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-4642, https://doi.org/10.5194/egusphere-egu23-4642, 2023.

08:53–08:55
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PICO4.6
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EGU23-3326
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ECS
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On-site presentation
Milad Aminzadeh, Noemi Friedrich, Kaveh Madani, and Nima Shokri

The application of agricultural ponds and small engineered impoundments (often < 0.1 km2 area) is growing globally to support livestock, irrigation, and local municipal and industrial demands during dry spells. However, evaporation diminishes the storage efficiency of these popular but often un-inventoried resources. This study provides a reliable framework for estimating global abundance of small reservoirs and associated evaporative hotspots under different climate change scenarios serving as a basis for future water management and planning. To show the applicability of the proposed method and the utility of the insights it provides, we use satellite data to identify spatio-temporal distribution of small reservoirs (~0.001 to 0.1 km2 area) in southern Europe (Italy, Spain, and Portugal) where irrigation heavily depends on water storage in agricultural ponds. While current estimates of evaporative water losses from small reservoirs often rely on pan measurements or Penman-type approaches with locally calibrated heat and mass transfer coefficients, we employ a physically-based model [Aminzadeh et al., 2018] that accounts for inherent reservoir characteristics (e.g., depth and light attenuation), and radiative energy storage within the water body to quantify energy balance and evaporation dynamics from small water reservoirs. Our preliminary results indicate that cumulative area of small reservoirs in the study area has increased from 518 km2 in 2000 to 614 km2 in 2020 (18.5% increase) with cumulative evaporative losses that may exceed 400 Mm3 during warm months (April to September). Although the estimated evaporative water loss looks negligible relative to the annual agricultural water use (< 2%), its significance could be gauged by societal impacts in these regions with chronic water stress problems or the cost of alternate water sources (e.g., desalinated water).

Reference

Aminzadeh, M., Lehmann, P., Or, D. (2018). Evaporation suppression and energy balance of water reservoirs covered with self-assembling floating elements. Hydrol. Earth Syst. Sci., 22, 4015–4032.

How to cite: Aminzadeh, M., Friedrich, N., Madani, K., and Shokri, N.: Insignificant but overlooked: Evaporative losses from small reservoirs in southern Europe, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3326, https://doi.org/10.5194/egusphere-egu23-3326, 2023.

08:55–08:57
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PICO4.7
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EGU23-9951
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ECS
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On-site presentation
Seyed-Mohammad Hosseini-Moghari and Petra Döll

Reservoir operation modeling is challenging since it directly depends on human decision-making that varies from dam to dam. Large-scale reservoir modeling is even more difficult due to the lack of observed operation data. Therefore, generic reservoir operation models are used to model large-scale reservoir operations focusing on a specific purpose, rather than real operations. One of the well-known generic schemes for reservoir operation is Hannsaki et al. (2006) algorithm which is currently used in several global hydrological models including the Water Global Assessment and Prognosis (WaterGAP) model. This algorithm improves hydrological process modeling compared to natural lake methods; however, its performance still needs to be improved, particularly for storage simulations. In this study, a new approach is implemented in the WaterGAP model to improve Hannsaki’s algorithm by using different one-parameter linear operation rules for different reservoir storage levels i.e., above 70 %, between 40 % and 70 %, and below 40 % of reservoir capacity (in total three equations). As a result, we can model each reservoir individually. In addition, we use storage at each time step for estimating the release coefficient instead of the storage at the beginning of the operational year in Hannsaki’s algorithm. The ResOpsUS dataset (historical reservoir inflow, storage, and outflow of major reservoirs across the US) is used to estimate the best parameters for each reservoir and evaluate the results over the US. The results of the new approach show an improvement compared to Hannsaki’s algorithm e.g., when the inflow has a good quality (the Kling-Gupta Efficiency (KGE) greater than 0.50), the median of KEG for storage (outflow) of the new approach reaches 0.23 (0.49) compared to -0.71 (0.25) for Hannsaki’s algorithm.

How to cite: Hosseini-Moghari, S.-M. and Döll, P.: Using observation data to improve simulation of man-made reservoirs in a global hydrological model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-9951, https://doi.org/10.5194/egusphere-egu23-9951, 2023.

08:57–08:59
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PICO4.8
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EGU23-8896
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ECS
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Virtual presentation
Shujie Cheng, Petra Hulsman, Akash Koppa, Lei Cheng, Hylke E. Beck, and Diego G. Miralles

Partitioning runoff accurately into baseflow and quickflow is crucial for our understanding of the water cycle and for the management of droughts and floods. However, global datasets of long-term mean runoff partitioning are rare, even more so datasets relying on physically-based methods. Here, we present a new global 0.25° dataset of runoff, baseflow and quickflow using a hybrid approach of Budyko-based methods and machine learning (ML). The parameters in the Budyko curve and Budyko-based baseflow curve (BFC curve) are estimated with ML (boosted regression trees, BRT) as a function of catchment characteristics. The BRT models are trained and tested in 1226 catchments worldwide, and then applied globally at grid scale. The catchment-trained models show good performance during the testing phase with R2 equal to 0.96 and 0.87 for runoff and baseflow, respectively. The dataset developed in this study shows that 30.3±26.5% (mean ± standard deviation) of the precipitation is partitioned into runoff of which 20.6±22.1% is baseflow and 9.7±10.3% is quickflow. The global long-term mean baseflow in this study (151±181 mm yr–1) is lower than that from the Global Streamflow Characteristics Dataset (GSCD, 241±321 mm yr–1) and higher than that from ERA5-Land (79±145 mm yr–1). This study provides a unique, physically and observationally constrained global dataset of the long-term runoff partitioning. The large differences among different datasets suggest that global runoff partitioning is highly uncertain and requires further investigation.

How to cite: Cheng, S., Hulsman, P., Koppa, A., Cheng, L., Beck, H. E., and Miralles, D. G.: Global runoff partitioning based on Budyko and machine learning, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8896, https://doi.org/10.5194/egusphere-egu23-8896, 2023.

08:59–09:01
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PICO4.9
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EGU23-12752
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ECS
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On-site presentation
Riya Dutta and Yannis Markonis

Changes in the terrestrial hydrologic cycle determine the future availability of water around the world, affecting various aspects of society. Accurate estimation of these changes is essential for effective implementation of water management policies. A major source of uncertainty in such estimates is the data products used for analysis. This study provides a global perspective of changes in water availability in terms of Precipitation minus Evapotranspiration (P-E) using three data sources, namely reanalysis (ERA5-Land), hydrological modelling (TerraClimate), and simulations of eight Global Climate Models (GCMs; CMCC-CM2, CNRM-CM6, EC-Earth3P, ECMWF-IFS, HadGEM3-GC31, IPSL-CM6A, MPI-ESM1, and MRI-AGCM3 ). The period of analysis (1960-2014) is divided into two epochs, and the magnitude of change is analyzed by the percent change in the mean and increasing/decreasing trend over the 55-year period. In general, all three data products successfully capture the climatological mean of P-E with comparatively higher values for the equatorial regions. However, when comparing the intensity of changes the results provided by the three data sources differ significantly, especially for regions at higher latitudes. Projections from various GCMs show significant rise in the precipitation for the higher latitudes, which will also affect the extent of P-E and increase the uncertainty over the changes in water availability. It is critical to find reliable data sources for the historical period to increase confidence in future projections and to successfully implement various bias correction techniques wherever necessary. 

How to cite: Dutta, R. and Markonis, Y.: Global perspective of changes in the terrestrial hydrologic cycle using different data products, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12752, https://doi.org/10.5194/egusphere-egu23-12752, 2023.

09:01–09:03
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PICO4.10
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EGU23-10386
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ECS
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On-site presentation
Nels Bjarke, Ben Livneh, and Joseph Barsugli

Increasing aridity is a growing concern for many regions across the globe, primarily driven by an alteration to the balance of evaporative loss and incoming precipitation. While this is likely to drive declines in the long-term mean of surface water, interannual and decadal variability of precipitation will still produce wet and dry periods. Yet, the potential increase in the occurrence of multiple sequential drought years is of particular concern especially for basins without substantive water shortage infrastructure. In this presentation, we evaluate the enhanced likelihood of multiple consecutive , i.e. years with below 20th percentile annual runoff, occurring within large basins (25,000-150,000 km­2) across the globe that are projected to experience increasing aridity within an ensemble of 16 CMIP6 general circulation models. We use historical simulations (1950-2014) and future projections (2015-2100) from three emission scenarios to demonstrate how aridification, as measured by increases in the long-term ratio of potential evapotranspiration and precipitation, is expected to change. We examine the ways in which changes in aridity paired with projected changes to the interannual variability of precipitation can conspire to enhance the probability, magnitude, and persistence of multi-year drought.

How to cite: Bjarke, N., Livneh, B., and Barsugli, J.: The role of future aridification in multi-year drought persistence for global hydrologic basins, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-10386, https://doi.org/10.5194/egusphere-egu23-10386, 2023.

09:03–09:05
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PICO4.11
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EGU23-3314
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ECS
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On-site presentation
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Ying Hou, Hui Guo, Yuting Yang, and Wenbin Liu

Recent advances in global hydrological modeling yield many global runoff datasets that are extensively used in global hydrological analyses. Here, we provide a comprehensive evaluation of simulated runoff from 21 global models, including 12 climate models from CMIP6, six global hydrological models from the Inter-Sectoral Impact Model Inter-Comparison Project (ISMIP2a) and three land surface models from the Global Land Data Assimilation System (GLDAS), against observed streamflow in 840 unimpaired catchments globally. Our results show that (i) no model performs consistently better in estimating runoff from all aspects, and all models tend to perform better in more humid regions and non-cold areas; (ii) the interannual runoff variability is well represented in ISIMIP2a and GLDAS models, and no model performs satisfactorily in capturing the annual runoff trend; (iii) the runoff intra-annual cycle is reasonably captured by all models yet an overestimation of intra-annual variability and an early bias in peak flow timing are commonly found; and (iv) model uncertainty leads to a larger uncertainty in runoff estimates than that induced by forcing uncertainty in ISIMIP2a, and model uncertainty in GLDAS is larger than that in ISIMIP2a. Finally, we confirm that the multi-model ensemble is an effective way to reduce uncertainty in individual models except for CMIP6 regarding mean annual magnitude and annual runoff trend. Overall, our findings suggest that assessments/projections of runoff changes based on these global outputs contain great uncertainties and should be interpreted with caution, and call for more advanced, observation-guided ensemble techniques for better large-scale hydrological applications.

How to cite: Hou, Y., Guo, H., Yang, Y., and Liu, W.: Global evaluation of runoff simulation from climate, hydrological and land surface models, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3314, https://doi.org/10.5194/egusphere-egu23-3314, 2023.

09:05–09:07
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PICO4.12
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EGU23-14079
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ECS
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Virtual presentation
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Athanasios Tsilimigkras, Douglas Clark, Andrew Hartley, Eleanor Burke, Manolis Grillakis, and Aristeidis Koutroulis

Land Surface Models (LSMs) simulate various biophysical processes of the terrestrial land surface. They have been developed for a variety of applications, including assessing the impact of modifying a particular process on the ecosystem as a whole, e.g., the impact of climate change on hydrology. Due to their great complexity, developing these models is a continuous and laborious process. For example, the JULES (Joint UK Land Environment Simulator) model is developed by a broad community of inter-disciplinary researchers. However, despite the high level of model development, some processes face parsimonious parameterisation. One of these processes is the routing of surface runoff as simulated by the TRIP (Total Runoff Integrating Pathways) scheme [1]. In its current global parameterisation, TRIP uses uniform velocity and meandering characteristics for the entire land surface regardless of the physiography of the actual river system.

Our work aims to improve the surface runoff's routing by optimising the effective velocity and meandering ratio parameters. In a sample of 360 global river basins, these parameters are correlated with physiographic characteristics to derive a method of extrapolation at the global scale. The development and application of the method were based on river discharge from the global GRDC database [2] and basin-scale physiographic attributes from the HydroATLAS database [3]. A factorial experiment was performed from a combination of 20 setups of effective velocity values and 12 meandering ratios, resulting in a total of 198 simulations. Two optimisation methods were developed; in the first method, the optimum routing parameters are defined for the best NSE improvement with the least deviation from the default routing parameters, whereas in the second method a uniform parameter set was assigned based on a categorisation of the basins. Neural Networks were used for regression and classification, respectively for each method, correlating the optimal routing parameters with the physiographic attributes at the river basin scale. The trained neural networks were applied to the HydroATLAS attributes to extrapolate the routing parameters at the global scale. Simulations of the newly developed river routing configuration showed improved skill in simulating river flow at the global scale (NSE increased by 0.13 on average over 360 global river basins), especially regarding the temporal response. Finally, the present work resulted in a publicly available branch of the JULES code, where spatially varying routing parameters can be introduced, contrary to the globally fixed set.

 

[1] Oki, T., & Sud, Y. C. (1998). Design of Total Runoff Integrating Pathways (TRIP) - A Global River Channel Network. Earth Interactions, 2(1), 1–37. https://doi.org/10.1175/1087-3562(1998)002<0001:DOTRIP>2.3.CO;2

[2] GRDC. (n.d.). The Global Runoff Data Centre, 56068 Koblenz, Germany, 56068 Koblenz, Germany. 56068 Koblenz, Germany.

[3] Linke, S., Lehner, B., Ouellet Dallaire, C., Ariwi, J., Grill, G., Anand, M., Beames, P., Burchard-Levine, V., Maxwell, S., Moidu, H., Tan, F., Thieme, M. (2019). Global hydro-environmental sub-basin and river reach characteristics at high spatial resolution. Scientific Data 6: 283. doi: https://doi.org/10.1038/s41597-019-0300-6

 

Acknowledgement: This work is based upon work from COST Action 19139 - PROCLIAS, supported by COST (European Cooperation in Science and Technology).

How to cite: Tsilimigkras, A., Clark, D., Hartley, A., Burke, E., Grillakis, M., and Koutroulis, A.: Using basin-scale physiographic attributes to improve river routing in JULES, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14079, https://doi.org/10.5194/egusphere-egu23-14079, 2023.

09:07–10:15
Chairpersons: Robert Reinecke, Verena Bessenbacher
10:45–10:47
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PICO4.1
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EGU23-11945
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On-site presentation
Oldrich Rakovec, Rohini Kumar, Pallav Kumar Shrestha, and Luis Samaniego

Our study provides a global assessment of water balance components accounting for the uncertainty in globally available precipitation products. This assessment is carried out consistently using a multiscale modelling framework established over more than 6000 GRDC river basins at various spatial resolutions (daily time step, period 1990-2019). The framework is based on the mesoscale Hydrologic Model (mHM; [1,2,3]) equipped with the multiscale parameter regionalization (MPR) scheme. All basins share the same parameterization and are driven with four different state-of-the-art meteorological products: ERA5 reanalysis [4], MSWEP [5], and deterministic EM-Earth v2 [6]. Additionally, the hydrological simulations are benchmarked against E-OBS [7] over Europe and against locally interpolated 1km gridded rain gauge dataset over Germany.

Our results show that EM-Earth clearly exhibits the best streamflow performance across North and South America and Asia with respect to the other products. The MSWEP is the best product in Africa, where the overall model’s performance is rather poor. In Australia, MSWEP and EM-Earth have comparable skills. In Europe, the differences get narrower, although slightly better performance is seen for EM-Earth, with a median performance of 0.5 of daily KGE (N basins=2000), mainly due to correcting the under-catch error of rain gauges which is not considered, e.g. in E-OBS. Furthermore, when we zoom into a subset consisting of medium-sized 200 German basins, the in-house high-resolution meteorologic product clearly overperformed all global products, mainly due to better captured temporal correlation and smaller biases. On the other hand, ERA5 leads to very strong positive biases over German basins using standard parameterization. Finally, our study contributes to discussions on objective quantification of the optimal spatial resolution of hydrological studies.

 

[1] https://doi.org/10.5281/zenodo.5119952

[2] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2008WR007327 

[3] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2012WR012195

[4] https://rmets.onlinelibrary.wiley.com/doi/10.1002/qj.3803

[5] https://hess.copernicus.org/articles/21/589/2017/hess-21-589-2017.html

[6] https://journals.ametsoc.org/view/journals/bams/103/4/BAMS-D-21-0106.1.xml

[7] https://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2017JD028200

 

How to cite: Rakovec, O., Kumar, R., Shrestha, P. K., and Samaniego, L.: Global assessment of hydrological components using a seamless multiscale modelling system, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11945, https://doi.org/10.5194/egusphere-egu23-11945, 2023.

10:47–10:49
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PICO4.2
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EGU23-14505
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ECS
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On-site presentation
Dipesh Singh Chuphal and Vimal Mishra

Streamflow data is highly relevant for flood risk analysis, ecological assessment, and water resources management. However, high-resolution vector-based streamflow data for Indian-Subcontinent river (ISC) basins is critically lacking. The finer-scale streamlines are better represented in a vector-based river network than grid-based network. We generated continuous streamflow data from 1901 to 2100 for ISC river basins. We used observed meteorological data from India Meteorological Department (IMD) for historical and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections for future simulations. We combined the H08 land surface model and the MizuRoute routing scheme to generate the streamflow at 9579 river segments of ISC river basins. We also examined how streamflow variability across the ISC river basins changes under a warming climate. We further investigated the river segments that are more prone to flood and drought in the future. The findings of this study may help in improving local flood and drought awareness and response more effectively than previously possible due to simulations at very fine river segments.

How to cite: Singh Chuphal, D. and Mishra, V.: Streamflow projections for Indian subcontinent river basins, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14505, https://doi.org/10.5194/egusphere-egu23-14505, 2023.

10:49–10:51
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PICO4.3
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EGU23-17281
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ECS
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On-site presentation
Carlos Antonio Fernandez-Palomino, Fred F. Hattermann, Valentina Krysanova, Fiorella Vega-Jácome, Waldo Lavado, and Axel Bronstert

Peru is already facing a number of challenges related to climate change, including retreating glaciers and more severe droughts and floods. Therefore, a countrywide analysis of current and future hydroclimatic conditions is crucial to formulate adaptation strategies in water resource development. This study aims to evaluate the effects of climate change on the distribution of water budget components and streamflow variability across Peru. For that, we bias-adjusted and statistically downscaled CMIP6 climate projections of 10 climate models under two Shared Socioeconomic Pathways (SSP1-2.6 and SSP5-8.5) to obtain a range of possible future regional climatic conditions. These selected scenarios span a range of possible future options from the sustainable pathway (SSP1-2.6, with 2.6 W/m2 by the year 2100) to fossil-fueled development (SSP5-8.5, with 8.5 W/m2 by the year 2100). The adjusted climate data were fed into the hydrological model, Soil and Water Assessment Tool (SWAT), to simulate and analyze future hydroclimatic conditions. SWAT was calibrated and validated at 72 discharge stations against mean, high and low water flows. Climate projections suggest a warmer climate and diverging changes in precipitation, with a drier response over the lowlands of the Upper Amazon related to a substantial reduction in precipitation during June-November and a wetter response over the tropical Andes due to precipitation increases during September-March. Projected changes in hydrological conditions show lower water availability over lowlands and higher water availability along the Andean basins in the future. The projections for hydrological extremes indicate that Peru might face excessive water exposure during floods along the Andean catchments and water scarcity during droughts over the Amazon lowlands in the future, particularly under the fossil-fueled development (SSP5-8.5) scenario. The results of this study provide information to planners and decision-makers for formulating adaptation strategies for sustainable water management under climate change in Peru.

Keywords: water resources, climate change, CMIP6, hydrological extremes, Peru, Andes, Amazon

How to cite: Fernandez-Palomino, C. A., Hattermann, F. F., Krysanova, V., Vega-Jácome, F., Lavado, W., and Bronstert, A.: Climate change impact on water budget and hydrological extremes across Peru, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-17281, https://doi.org/10.5194/egusphere-egu23-17281, 2023.

10:51–10:53
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PICO4.4
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EGU23-2816
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ECS
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On-site presentation
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En Ning Lai, Lan Wang-Erlandsson, Vili Virkki, Miina Porkka, and Ruud van der Ent

Root-zone soil moisture is a key variable representing water cycle dynamics that strongly interacts with ecohydrological, atmospheric, and biogeochemical processes. Recently, it was proposed as the control variable for the green water planetary boundary, suggesting that widespread and considerable deviations from baseline variability now predispose Earth System functions critical to an agriculture-based civilisation to destabilization. However, the global extent and severity of root-zone soil moisture changes under future scenarios remains to be scrutinized. Here, we analyzed root-zone soil moisture departures from the pre-industrial climate variability for a multi-model ensemble of 14 Earth System Models (ESMs) in the Coupled Model Intercomparison Project Phase 6 (CMIP6) in four climate scenarios as defined by the Shared Socioeconomic Pathways (SSP), SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, between 2021 and 2100. The analyses were done for 43 ice-free climate reference regions used by the Intergovernmental Panel on Climate Change (IPCC).We defined ‘permanent departures’ when a region’s soil moisture exits the regional variability envelope of the pre-industrial climate and does not fall back into the range covered by the baseline envelope until 2100. Permanent dry departures (i.e. lower soil moisture than pre-industrial variability) were found to be most pronounced in Central America, southern Africa, the Mediterranean region, and most of South America, whereas permanent wet departures are most pronounced in southeastern South America, northern Africa, and southern Asia. In the Mediterranean region, dry permanent departure may have already happened according to some models. By 2100, there is dry permanent departures in theMediterranean in 70%of the ESMs in SSP1-2.6, the most mitigated situation, and more than 90% in SSP3-7.0 and SSP5-8.5, the medium-high and worst-case scenarios. Northeastern Africa is projected to experience wet permanent departures in 64% of the ESMs under SSP1-2.6, and 93% under SSP5-8.5. The percentage of ice-free land area with departures increases in all SSP scenarios as time goes by. Wet departures are more widespread than dry departures throughout the studied timeframe, except in SSP1-2.6. In most regions, the severity of the departures increases with the severity of global warming. In 2050, permanent departures (ensemble median) occur in about 10% of global ice-free land areas in SSP1-2.6, and in 25% in SSP3-7.0. By the end of the 21st century, the occurrence of permanent departures in SSP1-2.6 increases to 34 %, and in SSP3-7.0, 45 %. Our findings underscore the importance of mitigation to avoid further degrading the Earth System functions upheld by soil moisture. An asscociate paper is available as preprint on EGUsphere: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-971/

How to cite: Lai, E. N., Wang-Erlandsson, L., Virkki, V., Porkka, M., and van der Ent, R.: Root zone soil moisture in over 25 % of global land permanently beyond pre-industrial variability as early as 2050, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2816, https://doi.org/10.5194/egusphere-egu23-2816, 2023.

10:53–10:55
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PICO4.5
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EGU23-8424
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On-site presentation
Andreas Hartmann, Yan Liu, and Mariana Gomez Ospina

Estimating karst water resources at a global scale represents a key step towards enhancing groundwater management. Although recharge estimations at global scale exist, the special karst features leading to different recharge processes, in particular the preferential flow path, have not been adequately accounted for. Representing these special recharge processes is crucial for realistically quantifying recharge in karst regions. In this study, we present a new version of a global karst recharge model and the estimation of its model parameters using multiple observations. The updated model includes a new routine to consider eight land cover types for calculating evapotranspiration, interception and infiltration, as well as a new routine to account for snow and glacier melt. To prepare parameter estimation, six karst landscapes are defined based on the properties of karst grids (spatial resolution of 0.25°). For each of these landscapes, model parameters are found separately using a Monte Carlo uncertainty estimation framework and observations from the international soil moisture network (ISMN) and actual evapotranspiration observations from FLUXNET. With the new calibration, the updated model provides more precise estimates of groundwater recharge in athe karst regions of the world. It will therefore serve as a too  to improve water management in karst regions and identify areas potentially suffering from water shortage.

How to cite: Hartmann, A., Liu, Y., and Gomez Ospina, M.: Global groundwater recharge modeling in karst with explicit consideration of land cover and snow and glacier storage, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8424, https://doi.org/10.5194/egusphere-egu23-8424, 2023.

10:55–10:57
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PICO4.6
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EGU23-7545
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ECS
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On-site presentation
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Pallav Kumar Shrestha, Luis Samaniego, Oldrich Rakovec, and Stephan Thober

Disruptive reservoirs hold back an enormous amount of water, hike evaporation loss and alter the magnitude and timing of streamflow at all scales. Thus, any hydrological model (HM) must correctly represent reservoirs in the simulation. There are two issues while representing reservoirs in the river network of a gridded system. First issue is the error in reservoir catchment area where grids containing a part of the catchment results in under-/overestimation of reservoir inflow. Hence, it is impossible to conserve the catchment area correctly as long as a grid has only one outflow (D8 routing scheme) which is the case for the state-of-the-art gridded HMs. Secondly, when multiple dams are located in the same grid only one dam can be represented to lie on the major stream and be part of the stream network. Currently, gridded HMs either i) classify reservoirs into groups ("global/local","major/minor") simulating them differently in order to conserve the reservoir set, or ii) treat all reservoirs equally but are unable to conserve the reservoir set with smaller reservoirs disappearing at coarser resolutions. So either the set of reservoirs simulated or the reservoir simulation itself gets compromised while modeling across scales. This lack of scalability in space is a prominent source of model uncertainty in HMs (Samaniego et al. 2010, Kumar et al. 2013). We introduce subgrid catchment conservation (SCC), a novel scheme for routing that conserves reservoir catchment at all scales. We hypothesise that the conservation of reservoir catchment paves the way for a scalable hydrological system for reservoir modeling.

To test this hypothesis, we developed a reservoir module in the mesoscale hydrological model (mHM, https://mhm-ufz.org). mHM is tested across seven model resolutions ranging from 1 km to 100 km. The experiment set is the GRanD database, wherein the scalability of the reservoir set is tested for the whole set (7320 reservoirs) and the scalability of reservoir inflow simulation is tested at the headwater reservoirs (approx. 1500 reservoirs). Preliminary results in 70+ headwater reservoirs show that SCC routing preserves the full reservoir set across all scales. In comparison, the classic D8 routing scheme loses 15%, 25% and 50% reservoirs at 0.125 degree, 0.25 degree and 0.50 degree model resolutions, respectively. This indicates the potential of SCC in regulating interscale discrepancies in reservoir states and fluxes, leading to virtually seamless model performance.

The dilemma for modellers using distributed HMs is to compromise in resolution  (i.e., runtime) or to compromise on the number of reservoirs to model. Based on the preliminary results, SCC is poised to solve this long-standing dilemma and complete the quest for scalable hydrological modeling with reservoirs. The findings of this study would contribute to the contemporary effort of hydrological modeling society towards improved global water balance closure, where a good representation of reservoirs and lakes is a crucial element.

How to cite: Shrestha, P. K., Samaniego, L., Rakovec, O., and Thober, S.: The quest for scalable hydrological system for reservoir modeling, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7545, https://doi.org/10.5194/egusphere-egu23-7545, 2023.

10:57–10:59
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PICO4.7
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EGU23-1549
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On-site presentation
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John Worden, Mingjie Shi, and Adriana Bailey

Atmospheric humidity and soil moisture in the Amazon forest are tightly coupled to the region’s water balance, or the difference between two moisture fluxes, evapotranspiration minus precipitation (ET-P). However, large and poorly characterized uncertainties in both fluxes, and in their difference, make it challenging to evaluate spatiotemporal variations of water balance and its dependence on ET or P. Here, we show that satellite observations of the HDO/H 2O ratio of water vapor are sensitive to spatiotemporal variations of ET-P over the Amazon. When calibrated by basin-scale and mass-balance estimates of ET-P derived from terrestrial water storage and river discharge measurements, the isotopic data demonstrate that rainfall controls wet Amazon water balance variability, but ET becomes important in regulating water balance and its variability in the dry Amazon. Changes in the drivers of ET, such as above ground biomass, could therefore have a larger impact on soil moisture and humidity in the dry (southern and eastern) Amazon relative to the wet Amazon. 

How to cite: Worden, J., Shi, M., and Bailey, A.: Amazonian terrestrial water balance inferred from satellite-observed water vapor isotopes, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-1549, https://doi.org/10.5194/egusphere-egu23-1549, 2023.

10:59–11:01
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PICO4.8
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EGU23-14177
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ECS
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On-site presentation
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Ioan Sabin Taranu, David Lawrence, Yoshihide Wada, Ting Tang, Yi Yao, Inne Vanderkelen, Steven De Hertog, and Wim Thiery

Abstract:

Climate change and human water management are the two main drivers of terrestrial water storage change, from regional to global scale. When thinking about the future, our main tools to project upcoming changes in the terrestrial water fluxes and storage are the Earth System Models (ESMs). Through the representation of physical, chemical and biological processes relevant to the climate dynamics, ESMs are the closest we got to represent the real Earth.

Despite important advancements in the development of ESMs, these models are still missing key elements relevant to the representation of the water cycle, notably anthropogenic water management (Nazemi and Howard, 2015). Through the construction of dams and the abstraction of water from surface and groundwater sources, humans can significantly alter the regional and continental water budget, including river discharge and seasonality, groundwater levels and surface evapotranspiration.

The objective of our current project is to reduce this gap, by enhancing the Community Earth System Model to support abstractions for all major water use sectors including domestic, livestock, thermoelectric, manufacturing, mining and irrigation. Some unique features of our development are: full coverage of human water usage for both historical (1971-2010) and future scenarios; a sectoral competition scheme when water availability is limited; application of consumption fluxes on surface soil to accentuate role of human water usage on land-atmosphere interactions; full coupling between routing-land-atmosphere-ocean components. At the moment, all abstractions are performed exclusively from surface water.

For the scope of this conference, we will present for the first time, the global simulation results for the historical period (1971-2010) in land only mode, including a general performance of the model in normal conditions and some case studies for known historical drought events.

 

References:

Nazemi, Ali, and Howard S. Wheater. "On inclusion of water resource management in Earth system models–Part 1: Problem definition and representation of water demand." Hydrology and Earth System Sciences 19.1 (2015): 33-61.

 

How to cite: Taranu, I. S., Lawrence, D., Wada, Y., Tang, T., Yao, Y., Vanderkelen, I., De Hertog, S., and Thiery, W.: Sectoral water usage in the Community Earth System Model (CESM), EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14177, https://doi.org/10.5194/egusphere-egu23-14177, 2023.

11:01–11:03
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PICO4.9
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EGU23-13105
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On-site presentation
Yusuke Satoh, Yadu Pokhrel, Hyungjun Kim, and Tokuta Yokohata

Irrigation is one of the crucial Nature-Human interactions and also an anthropogenic forcing in the Earth system. The literature has shown that artificial water supply to soil for example water exploitation from groundwater for irrigation can alter water and heat budgets at the land surface, resulting in changes in regional climate and hydrological cycles. Due to the expected increase in irrigation to meet growing food demand, the impact of irrigation is likely to increase further in the future. Therefore, it is essential to consider to better understand the irrigation-induced changes in the various components of the Earth system, today and in the future.

Our research aims to advance the quantitative understanding of the impact of irrigation and groundwater exploitation as anthropogenic drivers of regional climate and environmental changes. We developed an earth system modeling framework coupling the updated Earth system model, MIROC-ES2L (Model for Interdisciplinary Research on Climate, Earth System version 2 for Long-term simulations) and newly implemented hydrological human activity modules. This modeling framework enables to simulate a fully coupled Nature-Human system including water cycle dynamics related to irrigation.

Our preliminary results show notable differences between simulations with and without the irrigation process. Here, we show the hydrological variables affected by irrigation and identify the regions and timings of significant impact. Further, we estimate the individual contribution of groundwater and surface water use to such impacts by irrigation.

How to cite: Satoh, Y., Pokhrel, Y., Kim, H., and Yokohata, T.: An evaluation of the impact of irrigation and groundwater pumping on regional climate using an improved Earth-System model, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-13105, https://doi.org/10.5194/egusphere-egu23-13105, 2023.

11:03–11:05
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PICO4.10
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EGU23-14130
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On-site presentation
Assessment of Continental Scale Water Balance for Indian Land Data Assimilation System (ILDAS)
(withdrawn)
Manabendra Saharia, Bhanu Magotra, Ved Prakash, and Augusto Getirana
11:05–11:07
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PICO4.11
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EGU23-8334
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ECS
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On-site presentation
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Máté Chappon and Katalin Bene

In recent years the water levels of Lake Velence - Hungary's third-largest lake - have dropped significantly due to a series of climatic and anthropogenic phenomena. Water managers calculate the lake's water budget based on a methodology established almost 50 years ago. The calculation error is determined as the difference between the computed and observed lake levels. A previous study on the calculation errors of annual water budget computations has found several uncertainties that result in predominantly negative errors; underestimating inflows and, or overestimating outflows.

This study focuses on monthly water budget computations to investigate the possible causes of the calculation errors. The monthly error distribution shows that negative calculation errors accumulate during the year's first five months. Based on this outcome, the methods for determining monthly precipitation, evapotranspiration and surface inflow are explored in more detail for the January – May period. Remote sensing data and numerical modelling were used to fill spatial and temporal data gaps.

The research will result in an improved water budget calculation method, which enhances our understanding of the main processes governing lake water levels. The new approach will give water managers a clearer picture of the effectiveness and necessity of engineering interventions to restore lake water levels.

The research is carried out within the framework of the Széchenyi Plan Plus program with the support of the RRF 2.3.1 21 2022. 00008 project.

 

How to cite: Chappon, M. and Bene, K.: Improving methods to calculate the monthly water budget for Lake Velence, Hungary, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-8334, https://doi.org/10.5194/egusphere-egu23-8334, 2023.

11:07–11:09
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PICO4.12
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EGU23-11481
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Virtual presentation
Jianmei Cheng, Kuiyuan Ding, Yiming Luo, Ying Yu, Yihang Lin, Long He, Xiaowei Zhao, Kun Zheng, and Yanxin Wang

United Nations Educational, Scientific and Cultural Organization (UNESCO) pointed out that about 300 million Africans live in poverty because of water scarcity. However, Africa does not lack natural water resources, but only makes insufficient use of them. We aim to understand the distribution of water storage in Africa and its changes for better management of these water resources. Based on the data from the GRACE gravity satellite and the GLDAS hydrological model, the changes in the total water storage (TWS), the surface water storage (SWS), and the groundwater storage (GWS) of Africa are calculated. On the hydrogeological base service platform OneGroundwater, we comprehensively analyzed the effects of rainfall, land use types, and other human activities on the water reserves. We found that the SWS decreases in the recent 15 years, which suggests that the utilization of surface water in Africa is significant. Meanwhile, the increase in the GWS indicates that the development of groundwater is not enough. Promoting the sustainable extraction of groundwater is helpful to the social development in Arica. Our analysis results show that rainfall is decisive for the changes in the GWS of Africa. The seasonal variation trend of the GWS is consistent with that of rainfall, while there is a certain lag in the yearly variations. The effects of land use types are mainly reflected in recharge and evaporation. The increase in vegetation density strengthens transpiration and reduces the recharge rate of groundwater.

How to cite: Cheng, J., Ding, K., Luo, Y., Yu, Y., Lin, Y., He, L., Zhao, X., Zheng, K., and Wang, Y.: Spatial-temporal characteristics of water storage in Africa based on GRACE and GLDAS data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11481, https://doi.org/10.5194/egusphere-egu23-11481, 2023.

11:09–11:11
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PICO4.13
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EGU23-12207
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ECS
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On-site presentation
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Friedrich Boeing, Thorsten Wagener, Andreas Marx, and Sabine Attinger
Germany experienced exceptional multi-year water storage deficits starting in 2018. Recurring years below average precipitation and above average temperatures lead to water deficits that accumulated primarily in slow-response subsurface water storages such as (deep) soil moisture or groundwater levels. Total water storage (TWS) anomalies estimated by the GRACE satellite mission show a strong decline for Germany since measurements began in 2002, but these time series began with a relatively wet period, ended in an exceptional drought situation, and are still relatively short. Therefore the resulting trends are not representative for long-term TWS dynamics and should not be used to extrapolate the development into the future (Güntner et al, 2022). In addition, the GRACE signal does not allow partitioning of the water storage and flux components. Hydrological simulations provide a suitable tool to analyse the long-term dynamics of water storages. We analyse the long-term monthly TWS anomalies estimated with the hydrological model mHM (Samaniego et al. (2010), Kumar et al. (2013)) from a data reconstruction starting in 1766 (Rakovec et al, 2022). Comparison of the monthly total water storage estimates between the hydrological simulations and two GRACE solutions (JPL RL06M MSCNv02CRI, GFZ COST-G RL01) show good agreement for both anomalies (R²=0.78-0.84) and the residuals after removing the seasonal cycle (R²=0.69-0.72) on the scale of Germany (spatial mean).
We specifically examine the periods of recovery from total water storage deficits from a water balance perspective. Besides precipitation (P) being the main driver of changes in the TWS, the progress of recovery from water storage deficits is controlled by the main water fluxes evapotranspiration (E) and runoff (Q) that are the loss terms in the water balance equation deltaTWS = P - E - Q. Decadal evaluations indicate that the water balance in Germany in recent decades has been increasingly driven by above-average E as a result of the temperature rise. While the cumulative precipitation deficits in the last decade 2011 - 2020 are less exceptional compared to other historical decades, cumulative E residuals account for a much larger part of the water deficits than in other historical decades. The results will contribute to an improved understanding how TWS deficit recovery are affected by long-term changes in the water balance.
 
References:

Güntner, A., Gerdener, H., Boergens, E., Kusche, J., Kollet, S., Dobslaw, H., Hartick, C., Sharifi, E., and Flechtner, F. (2022): Changes of water storage in Germany since 2002 observed with GRACE/GRACE-FO, GRACE/GRACE-FO Science Team Meeting 2022, Potsdam, Germany, 18–20 Oct 2022, GSTM2022-93, https://doi.org/10.5194/gstm2022-93.

Rakovec, O., Samaniego, L., Hari, V., Markonis, Y., Moravec, V., Thober, S., Hanel, M., & Kumar, R. (2022): The 2018–2020 Multi‐Year Drought Sets a New Benchmark in Europe. In Earth’s Future (Vol. 10, Issue 3). American Geophysical Union (AGU). https://doi.org/10.1029/2021ef002394

Samaniego L., R. Kumar, S. Attinger (2010): Multiscale parameter regionalization of a grid-based hydrologic model at the mesoscale. Water Resour. Res., 46,W05523, doi:10.1029/2008WR007327

Kumar, R., L. Samaniego, and S. Attinger (2013): Implications of distributed hydrologic model parameterization on water fluxes at multiple scales and locations, Water Resour. Res., 49, doi:10.1029/2012WR012195

How to cite: Boeing, F., Wagener, T., Marx, A., and Attinger, S.: Long-term dynamics of total water storage deficit recovery in Germany, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12207, https://doi.org/10.5194/egusphere-egu23-12207, 2023.

11:11–11:13
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PICO4.14
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EGU23-12394
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On-site presentation
nooshin mehrnegar, Maike Schumacher, Thomas Jagdhuber, and Ehsan Forootan

The climate change along with anthropogenic water use have been affecting the (re)distribution of water storage and water flux across the Continental United States (CONUS). Understanding these changes requires tools that provide a big picture of the processes that drive these changes. These processes are implemented in this study by combining remote sensing data with available modeling techniques, where the data contains a sample of hydro-climatological signals and models reflect our understanding of these processes. Time series of Terrestrial Water Storage Changes (TWSC) from the Gravity Recovery and Climate Experiment (GRACE, 2003-2017) and its Follow-on (GRACE-FO, 2018-2021) are integrated into the W3RA water balance model within CONUS, where the model is run at 9-km resolution using ERA5 forcing data. The gap in the GRACE and GRACE-FO TWSC products is filled following https://doi.org/10.3390/rs12101639. To achieve the best possible statistical combination, the Markov Chain Monte Carlo-based Data Assimilation (MCMC-DA) approach (https://doi.org/10.1016/j.scitotenv.2020.143579) is applied to use GRACE and GRACE-FO TWSC as a vertical integration constraint to update W3RA's individual water storage estimates. This approach rigorously accounts for the uncertainties of model and observations.

The outputs of MCMC-DA are evaluated using in-situ USGS groundwater level data and the European Space Agency (ESA) Climate Change Initiative (CCI) soil moisture product. The results indicate changes in trend and seasonality of water storage variations, for example, in southwestern (California and Nevada), southeastern (including Florida, South and North Carolina, Virginia, and Georgia), and south-central CONUS (including Texas, New Mexico, Colorado, Kansas, and Oklahoma). MCMC-DA improves the estimation of soil water in regions with high forest intensity, where ESA CCI and models reveal difficulties in capturing the soil-vegetation-atmosphere continuum. The representation of El Nino Southern Oscillation (ENSO)-related variability in water storage are found to be considerably improved after integrating GRACE(-FO) into W3RA. This new hybrid approach is found efficient for understanding the linkage between the climate variability and large-scale hydrological processes.

Keywords: CONU; Data Assimilation; Bayesian Method; MCMC; GRACE(-FO); W3RA; groundwater storage; soil water storage; USGS; ESA CCI.

How to cite: mehrnegar, N., Schumacher, M., Jagdhuber, T., and Forootan, E.: Two decades (2003-2021) of storage changes in the soil water and groundwater of CONUS, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12394, https://doi.org/10.5194/egusphere-egu23-12394, 2023.

11:13–12:30