scholarly journals Evaluation of Groundwater Simulations in Benin from the ALMIP2 Project

2019 ◽  
Vol 20 (2) ◽  
pp. 339-354
Author(s):  
Mehnaz Rashid ◽  
Rong-You Chien ◽  
Agnès Ducharne ◽  
Hyungjun Kim ◽  
Pat J.-F. Yeh ◽  
...  
Keyword(s):  
Seasonal Variations ◽  
Surface Runoff ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Model ◽  
Substantial Improvement ◽  
Base Flow ◽  
Specific Yield ◽  
Surface Model ◽  
Multidisciplinary Analysis

AbstractA comprehensive estimation of water budget components, particularly groundwater storage (GWS) and fluxes, is crucial. In this study, we evaluate the terrestrial water budget of the Donga basin (Benin, West Africa), as simulated by three land surface models (LSMs) used in the African Monsoon Multidisciplinary Analysis Land Surface Model Intercomparison Project, phase 2 (ALMIP2): CLM4, Catchment LSM (CLSM), and Minimal Advanced Treatments of Surface Interaction and Runoff (MATSIRO). All three models include an unconfined groundwater component and are driven by the same ALMIP2 atmospheric forcing from 2005 to 2008. Results show that all three models simulate substantially shallower water table depth (WTD) with smaller seasonal variations, approximately 1–1.5 m compared to the observed values that range between 4 and 9.6 m, while the seasonal variations of GWS are overestimated by all the models. These seemingly contradictory simulation results can be explained by the overly high specific yield prescribed in all models. All models achieve similar GWS simulations but with different fractions of precipitation partitioning into surface runoff, base flow, and evapotranspiration (ET), suggesting high uncertainty and errors in the terrestrial and groundwater budgets among models. The poor performances of models can be attributed to bias in the hydrological partitioning (base flow vs surface runoff) and sparse subsurface data. This analysis confirms the importance of subsurface hydrological processes in the current generation of LSMs and calls for substantial improvement in both surface water budget (which controls groundwater recharge) and the groundwater system (hydrodynamic parameters, vertical geometry).

scholarly journals Evaluating LSM-Based Water Budgets over a West African Basin Assisted with a River Routing Scheme

2014 ◽  
Vol 15 (6) ◽  
pp. 2331-2346 ◽  
Author(s):  
Augusto C. V. Getirana ◽  
Aaron Boone ◽  
Christophe Peugeot
Keyword(s):  
Deep Water ◽  
Land Surface ◽  
Land Surface Model ◽  
Base Flow ◽  
Water Infiltration ◽  
Surface Model ◽  
Daily Streamflow ◽  
Routing Scheme ◽  
Multidisciplinary Analysis ◽  
River Routing

Abstract Within the framework of the African Monsoon Multidisciplinary Analysis (AMMA) Land Surface Model Intercomparison Project phase 2 (ALMIP-2), this study evaluates the water balance simulated by the Interactions between Soil, Biosphere, and Atmosphere (ISBA) over the upper Ouémé River basin, in Benin, using a mesoscale river routing scheme (RRS). The RRS is based on the nonlinear Muskingum–Cunge method coupled with two linear reservoirs that simulate the time delay of both surface runoff and base flow that are produced by land surface models. On the basis of the evidence of a deep water-table recharge in that region, a reservoir representing the deep-water infiltration (DWI) is introduced. The hydrological processes of the basin are simulated for the 2005–08 AMMA field campaign period during which rainfall and streamflow data were intensively collected over the study area. Optimal RRS parameter sets were determined for three optimization experiments that were performed using daily streamflow at five gauges within the basin. Results demonstrate that the RRS simulates streamflow at all gauges with relative errors varying from −20% to 3% and Nash–Sutcliffe coefficients varying from 0.62 to 0.90. DWI varies from 24% to 67% of the base flow as a function of the subbasin. The relatively simple reservoir DWI approach is quite robust, and further improvements would likely necessitate more complex solutions (e.g., considering seasonality and soil type in ISBA); thus, such modifications are recommended for future studies. Although the evaluation shows that the simulated streamflows are generally satisfactory, further field investigations are necessary to confirm some of the model assumptions.

scholarly journals Introducing Hysteresis in Snow Depletion Curves to Improve the Water Budget of a Land Surface Model in an Alpine Catchment

2014 ◽  
Vol 15 (2) ◽  
pp. 631-649 ◽  
Author(s):  
Claire Magand ◽  
Agnès Ducharne ◽  
Nicolas Le Moine ◽  
Simon Gascoin
Keyword(s):  
Snow Cover ◽  
Land Surface ◽  
Water Budget ◽  
Land Surface Model ◽  
Surface Model ◽  
Depletion Curve ◽  
Physically Based ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Snow Model

Abstract The Durance watershed (14 000 km2), located in the French Alps, generates 10% of French hydropower and provides drinking water to 3 million people. The Catchment land surface model (CLSM), a distributed land surface model (LSM) with a multilayer, physically based snow model, has been applied in the upstream part of this watershed, where snowfall accounts for 50% of the precipitation. The CLSM subdivides the upper Durance watershed, where elevations range from 800 to 4000 m within 3580 km2, into elementary catchments with an average area of 500 km2. The authors first show the difference between the dynamics of the accumulation and ablation of the snow cover using Moderate Resolution Imaging Spectroradiometer (MODIS) images and snow-depth measurements. The extent of snow cover increases faster during accumulation than during ablation because melting occurs at preferential locations. This difference corresponds to the presence of a hysteresis in the snow-cover depletion curve of these catchments, and the CLSM was adapted by implementing such a hysteresis in the snow-cover depletion curve of the model. Different simulations were performed to assess the influence of the parameterizations on the water budget and the evolution of the extent of the snow cover. Using six gauging stations, the authors demonstrate that introducing a hysteresis in the snow-cover depletion curve improves melting dynamics. They conclude that their adaptation of the CLSM contributes to a better representation of snowpack dynamics in an LSM that enables mountainous catchments to be modeled for impact studies such as those of climate change.

scholarly journals Simulating precipitation decline under a Mediterranean deciduous Oak forest: effects on isoprene seasonal emissions and predictions under climatic scenarios

2017 ◽  
Author(s):  
Anne-Cyrielle Genard-Zielinski ◽  
Christophe Boissard ◽  
Elena Ormeño ◽  
Juliette Lathière ◽  
Ilja M. Reiter ◽  
...  
Keyword(s):  
Water Stress ◽  
Seasonal Variations ◽  
Land Surface ◽  
Environmental Changes ◽  
Seasonal Pattern ◽  
Land Surface Model ◽  
Surface Model ◽  
Emission Rates ◽  
Drought Intensity ◽  
Isoprene Emission

Abstract. Seasonal variations of Q. pubescens physiology and isoprene emission rates (ER) were studied from June 2012 to June 2013 at the O3HP site (French Mediterranean) under natural (ND) and amplified (+30 %, AD) drought. While AD significantly reduced the stomatal conductance to water vapour over the season excepting August, it did not significantly limit CO2 net assimilation, which was the lowest in summer. ER followed a significant seasonal pattern, whatever the drought intensity, with mean ER maxima of 78.5 and 104.8 µgC gDM−1 h−1 in July (ND) and August (AD) respectively. Isoprene emission factor increased significantly by a factor of 2 in August and September under AD (137.8 and 74.3 µgC gDM−1 h−1) compared to ND (75.3 and 40.21 µgC gDM−1 h−1), but no changes occurred on ER. An isoprene algorithm (G14) was developed using an optimised artificial neural network trained on our experimental dataset (ER + O3HP climatic and edaphic parameters cumulated over 0 to 21 days before measurements). G14 assessed more than 80 % of the observed ER seasonal variations, whatever the drought intensity. In contrast, ER was poorly assessed under water stress by MEGAN empirical isoprene model, in particular under AD. Soil water (SW) content was the dominant parameter to account for the observed ER variations, regardless the water stress treatment. ER was more sensitive to higher frequency environmental changes under AD (0 to −7 days) compared to ND (7 days). Using IPCC RCP2.6 and RCP8.5 climate scenarios, SW and temperature calculated by the ORCHIDEE land surface model, and G14, an annual 3 fold ER relative increase was found between present (2000–2010) and future (2090–2100) for RCP8.5 scenario compared to a 70 % increase for RCP2.6. Future ER remained mainly sensitive to SW (both scenarios) and became dependent to higher frequency environmental changes under RCP8.5.

GRACE-derived seasonal variations, a key to understanding aquifer sources, recharge and groundwater flow patterns

2020 ◽  
Author(s):  
karem Abdelmohsen ◽  
Mohamed Sultan ◽  
Himanshu Save
Keyword(s):  
Groundwater Flow ◽  
Seasonal Variations ◽  
Spherical Harmonic ◽  
Land Surface ◽  
Land Surface Model ◽  
Buffer Zone ◽  
Forward Modeling ◽  
Surface Model ◽  
Aquifer System ◽  
Lake Nasser

<p>The Nubian Sandstone Aquifer System (NSAS) in northeast Africa is formed of three subbasins, the Dakhla, Kufra, and the Northern Sudan Platform subbasins. The Dakhla subbasin (DSB) receives negligible precipitation (<10 mm/yr), yet displays significant seasonal variations in GRACETWS (average: 50 mm/yr, up to 77 mm/yr) across the entire subbasin. The origin of these variations could be related to one or more of the following factors: (1) leakage out from Lake Nasser, (2) leakage in from surroundings (Kufra basin [west NSAS], Northern Sudan Platform [south NSAS], Mediterranean sea [north NSAS], and Red Sea [east NSAS], and (3) recharge and rapid groundwater flow from Lake Nasser and the northern Sudan Platform. Three approaches were used to investigate the contribution of leakage (factors 1 and 2) to the observed GRACETWS signal over the DSB subbasin: (1) forward modeling (in spherical harmonic domain) of the maximum variations in Lake Nasser levels was applied to test whether the observed seasonal variation in GRACETWS across the DSB can be accounted for by leakage from Lake Nasser alone; (2) estimate (in spherical harmonic domain) the leakage in signal using the simulated TWS from the widely applied Land Surface Model (LSM), GLDAS (Global Land Data Simulation System); and (3) apply iterative forward modeling (iterations: n=30) to reconstruct the true mass variations of GRACETWS over the DSB. Findings suggest: (1) the leakage in signal over the DSB cannot account for the observed seasonal GRACETWS patterns and neither can the leakage out from Lake Nasser; (2) the leakage out signal is centered over Lake Nasser and extends to its immediate surroundings with a maximum radius of 250 km (upper boundary of leakage error); (3) the iterative modeling indicates that the maximum leakage within the 250 km buffer zone around the lake amounted to 22.6 % of the observed GRACETWS signal; (4) minimal leakage (up to 10 mm) from northerly precipitation is observed along the northern sections (~200 km deep) of the NSAS and negligible (< 4 mm) leakage is detected over the remaining sections of the DSB; and (5) the observed seasonal variations in GRACETWS over the DSB is related to an increase in groundwater storage related to seasonal recharge from Lake Nasser and rapid groundwater flow along a network of faults, fractures, and karst topography across the entire DSB.</p>

scholarly journals Improving river flow generation over Great Britain in a land surface model required for coupled land-atmosphere interactions

2018 ◽  
Author(s):  
Alberto Martínez-de la Torre ◽  
Eleanor M. Blyth ◽  
Graham P. Weedon
Keyword(s):  
Great Britain ◽  
Surface Runoff ◽  
Land Surface ◽  
River Flow ◽  
Land Surface Model ◽  
Soil Conditions ◽  
Surface Model ◽  
Climate Modelling ◽  
Operational Systems ◽  
Runoff Production

Abstract. Land surface models (LSMs) represent terrestrial hydrology in weather and climate modelling operational systems and research studies. Using river flow observations from gauge stations, we study the capability of the Joint UK Land Environment Simulator (JULES) LSM to simulate river flow over 13 catchments in Great Britain, each representing different climatic and topographic characteristics at the 1 km2 spatial resolution. A series of tests, carried out to identify where the model results are sensitive to the scheme and parameters chosen for runoff production, suggests that different catchments require different parameters and even different runoff schemes to produce the best results. From these results, we introduce a new topographical parametrization that produces the best daily river flow results (in terms of Nash-Sutcliffe efficiency and mean bias) for all 13 catchments. The new parametrization introduces a dependency on terrain slope, constraining surface runoff production to wet soil conditions over flatter regions (like the Thames catchment; Nash-Sutcliffe efficiency above 0.8), whereas over steeper regions the model produces surface runoff for every rainfall event regardless of the soil wetness state. This new parametrization improves the model capability in regional (Great Britain wide) assessments. The new choice of parameters is reinforced by examining the amplitude and phase of the modelled versus observed river flows, via cross-spectral analysis for time scales longer than daily.

scholarly journals Multisource Estimation of Long-Term Terrestrial Water Budget for Major Global River Basins

2012 ◽  
Vol 25 (9) ◽  
pp. 3191-3206 ◽  
Author(s):  
Ming Pan ◽  
Alok K. Sahoo ◽  
Tara J. Troy ◽  
Raghuveer K. Vinukollu ◽  
Justin Sheffield ◽  
...  
Keyword(s):  
Water Balance ◽  
Error Analysis ◽  
Land Surface ◽  
Water Budget ◽  
Large Scale ◽  
Land Surface Model ◽  
Data Sources ◽  
Surface Model ◽  
Terrestrial Water

A systematic method is proposed to optimally combine estimates of the terrestrial water budget from different data sources and to enforce the water balance constraint using data assimilation techniques. The method is applied to create global long-term records of the terrestrial water budget by merging a number of global datasets including in situ observations, remote sensing retrievals, land surface model simulations, and global reanalyses. The estimation process has three steps. First, a conventional analysis on the errors and biases in different data sources is conducted based on existing validation/error studies and other information such as sensor network density, model physics, and calibration procedures. Then, the data merging process combines different estimates so that biases and errors from different data sources can be compensated to the greatest extent and the merged estimates have the best possible confidence. Finally, water balance errors are resolved using the constrained Kalman filter technique. The procedure is applied to 32 globally distributed major basins for 1984–2006. The authors believe that the resulting global water budget estimates can be used as a baseline dataset for large-scale diagnostic studies, for example, integrated assessment of basin water resources, trend analysis and attribution, and climate change studies. The global scale of the analysis presents significant challenges in carrying out the error analysis for each water budget variable. For some variables (e.g., evapotranspiration) the assumptions underpinning the error analysis lack supporting quantitative analysis and, thus, may not hold for specific locations. Nevertheless, the merging and water balance constraining technique can be applied to many problems.

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