A distributed monthly water balance model: formulation and application on Black Volta Basin

Abdollahi, Khodayar; Bashir, Imtiaz; Verbeiren, Boud; Harouna, Mahamane R.; Griensven, Ann van; Huysmans, Marijke; Batelaan, Okke

doi:10.1007/s12665-017-6512-1

Cited by 71 publications

(82 citation statements)

References 44 publications

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“…In these maps, every pixel represents the magnitude of the water budget component (in mm). A WetSpass-M model calculates the total actual evapotranspiration per pixel as a sum of evaporations from open water, impervious surface area, bare soil, interception of vegetated area, and the transpiration of the vegetative cover [13,32]. This research is the first study to assess spatial and temporal distribution of groundwater recharge in the Drava flood plain.…”

Section: Resultsmentioning

confidence: 99%

“…This clearly reveals that the soil map is strongly affected on the spatial distribution of surface runoff. The used WetSpass-M model calculates monthly surface runoff in (mm/month) using a rationale method through an actual surface runoff and soil moisture coefficient [13]. The monthly, seasonal, and annual WetSpass simulated runoffs in the basin are presented in (Table 1).…”

Section: Resultsmentioning

confidence: 99%

“…The WetSpass-M model requires a set of basic input data, including meteorological data (precipitation, air temperature, wind speed, and potential evapotranspiration), distributed groundwater depth, LAI, soil types, topography (DEM and slope), and land use/land cover of the investigated area [13,26,27].…”

Section: Input Datamentioning

confidence: 99%

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Assessment of Groundwater Recharge, Evaporation, and Runoff in the Drava Basin in Hungary with the WetSpass Model

2019

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The assessment of spatial and temporal distribution of groundwater recharge is required as an input to develop the regional groundwater model in the Drava flood plain for more accurate simulations of different management scenarios. WetSpass-M, a GIS-based spatially-distributed water balance model, was implemented to assess monthly, seasonal, and the annual averages of groundwater recharge, surface runoff and actual evapotranspiration in the Drava basin, Hungary for the period between 2000–2018. The basic relevant input-data for the Wetspass-M model is prepared in grid-maps using the tool ARCGIS tool. It comprises monthly climatological recordings (e.g., rainfall, temperature, wind speed), distributed land cover, soil map, groundwater depth, topography, and slope. The long-term temporal and spatial average monthly precipitation (58 mm) is distributed as 29% (17 mm) surface runoff, 27% (16 mm) actual evapotranspiration, and 44% (25 mm) groundwater recharge. The mean annual groundwater recharge, actual evapotranspiration, and surface runoff were 307, 190, and 199 mm, respectively. The findings of the WetSpass-M model are intended to support integrated groundwater modeling. The analysis of simulation results shows that WetSpass-M model works properly to simulate hydrological water budget components in the Drava basin. Moreover, a better understanding of the simulated long-term average spatial distribution about water balance components is useful for managing and planning the available water resources in the Drava basin.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Assessment of Groundwater Recharge, Evaporation, and Runoff in the Drava Basin in Hungary with the WetSpass Model

2019

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“…Spatially distributed monthly groundwater recharge was simulated using the WetSpass‐M model (Abdollahi et al, ; Batelaan & De Smedt, ) on the same grid as the grid for the groundwater flow (MODFLOW) model. This groundwater recharge output from the WetSpass‐M model was used as an input for the MODFLOW model.…”

Section: Methodsmentioning

confidence: 99%

“…Simulation of spatially distributed monthly groundwater recharge: Spatially distributed monthly groundwater recharge was simulated using the WetSpass‐M model (Abdollahi et al, ; Batelaan & De Smedt, ) as explained in section 2.4.1. Spatial variability is taken into account during the groundwater recharge simulation, and spatial variability is well captured but that its magnitude may have considerable uncertainty as there is no direct calibration of the WetSpass‐M model. A single recharge multiplier is assigned to the groundwater recharge corresponding with each time step (1 month):

{rch}_{i} = r \overset{{italicch}_{normali}}{true} * θi,

where rch i is the corrected spatial distributed recharge of ith time step, θ is the recharge multiplier for the corresponding time step, and

r \overset{{italicch}_{i}}{true}

is the simulated groundwater recharge obtained from the WetSpass model for the ith time step.…”

Section: Methodsmentioning

confidence: 99%

Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model

Mustafa

Nossent

Ghysels

et al. 2018

Water Resources Research

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We present a general and flexible Bayesian approach using uncertainty multipliers to simultaneously analyze the input and parameter uncertainty of a groundwater flow model with consideration of the heteroscedasticity of the groundwater level error. Groundwater recharge and groundwater abstraction multipliers are introduced to quantify the uncertainty of the spatially distributed input data of the groundwater model in addition to parameter uncertainty. The heteroscedasticity of the groundwater level error is also considered in our Bayesian approach by incorporating a new heteroscedastic error model. The proposed methodology is applied in an overexploited aquifer in Bangladesh where groundwater abstraction and recharge data are highly uncertain. The results of the study confirm that consideration of recharge and abstraction uncertainty through the use of recharge and abstraction multipliers is feasible even in a fully distributed physically based groundwater flow model. Heteroscedasticity is present in the groundwater level error and has an effect on the model predictions and parameter distributions. The input uncertainty affects the model predictions and parameter distributions and it is the dominant source of uncertainty in the groundwater flow prediction. Additionally, the approach described also provides a new way to optimize the spatially distributed recharge and abstraction data along with the parameter values under uncertain input conditions. We conclude that considering model input uncertainty along with parameter uncertainty and heteroscedasticity of the groundwater level error is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.

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Groundwater recharge over the past 100 years: Regional spatiotemporal assessment and climate change impact over the Saguenay‐Lac‐Saint‐Jean region, Canada

Boumaiza

Walter

Chesnaux

et al. 2022

Hydrological Processes

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Proper knowledge of potential groundwater recharge (PGR) and its spatiotemporal distribution are essential for sustainable groundwater management, especially within the context of climate change. Here, a robust GIS‐based water budget framework was developed to estimate PGR at a regional scale and map its spatial distribution. This framework is demonstrated over the Saguenay‐Lac‐Saint‐Jean region (13 200 km2) of Quebec (Canada). The PGR mapping process was based on a model incorporating water budget components. The vertical inflows (VI) include water amounts from rainfall and snowmelt, whereby the latter was assessed using HYDROTEL model. VI were combined with the maximum and minimum temperatures to estimate actual evapotranspiration (AET), while the surface runoff (RuS) was assessed using the curve number method. Field observations of annual variation in temperatures and the water budget components, over a period of 100 years (1910–2009), were used to provide a comprehensive overview of the effects of climate change on PGR. The last 10 years of the observation period (i.e., 2000–2009) indicate that 6% of the study area has PGR rates of 35%–50%. PGR rates of 20%–35% occur in 58% of the study area, while 36% have PGR of 5%–20%. The trend analysis of temperature time series reveals an average of 1.1 ± 0.6°C increase over 100 years. Also, an increase in the water budget components is observed. Despite the increasing trends of RuS and AET, PGR still showed an increasing trend with an average increase of 0.7 ± 0.4 mm/year over the past 100 years. This observation indicates that the increase in VI was enough to compensate for the increases in AET and RuS. This finding of an increasing PGR in the study area provides useful information for future studies focusing on predicting long‐term PGR evolution and for the development of efficient long‐term groundwater management strategies.

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A distributed monthly water balance model: formulation and application on Black Volta Basin

Cited by 71 publications

References 44 publications

Assessment of Groundwater Recharge, Evaporation, and Runoff in the Drava Basin in Hungary with the WetSpass Model

Assessment of Groundwater Recharge, Evaporation, and Runoff in the Drava Basin in Hungary with the WetSpass Model

Estimation and Impact Assessment of Input and Parameter Uncertainty in Predicting Groundwater Flow With a Fully Distributed Model

Groundwater recharge over the past 100 years: Regional spatiotemporal assessment and climate change impact over the Saguenay‐Lac‐Saint‐Jean region, Canada

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