scholarly journals Simulating the sensitivity of evapotranspiration and streamflow to large-scale groundwater depletion

2019 ◽  
Vol 5 (6) ◽  
pp. eaav4574 ◽  
Author(s):  
Laura E. Condon ◽  
Reed M. Maxwell
Keyword(s):  
Surface Water ◽  
Land Surface ◽  
Large Scale ◽  
Integrated Approach ◽  
Groundwater Depletion ◽  
Past Century ◽  
Groundwater Abstraction ◽  
Aquifer Storage ◽  
Storage Losses ◽  
The Impact

Groundwater pumping has caused marked aquifer storage declines over the past century. In addition to threatening the viability of groundwater-dependent economic activities, storage losses reshape the hydrologic landscape, shifting groundwater surface water exchanges and surface water availability. A more comprehensive understanding of modern groundwater-depleted systems is needed as we strive for improved simulations and more efficient water resources management. Here, we begin to address this gap by evaluating the impact of 100 years of groundwater declines across the continental United States on simulated watershed behavior. Subsurface storage losses reverberate throughout hydrologic systems, decreasing streamflow and evapotranspiration. Evapotranspiration declines are focused in water-limited periods and shallow groundwater regions. Streamflow losses are widespread and intensify along drainage networks, often occurring far from the point of groundwater abstraction. Our integrated approach illustrates the sensitivity of land surface simulations to groundwater storage levels and a path toward evaluating these connections in large-scale models.

scholarly journals Large-scale sensitivities of groundwater and surface water to groundwater withdrawal

2020 ◽  
Author(s):  
Marc F. P. Bierkens ◽  
Edwin H. Sutanudjaja ◽  
Niko Wanders
Keyword(s):  
Surface Water ◽  
Analytical Framework ◽  
Groundwater Withdrawal ◽  
Irrigated Agriculture ◽  
Groundwater Depletion ◽  
Steady Increase ◽  
Groundwater Storage ◽  
Aquifer Storage ◽  
The Impact ◽  
Streamflow Depletion

Abstract. Increasing population, economic growth and changes in diet have dramatically increased the demand for food and water over the last decades. To meet increasing demands, irrigated agriculture has expanded into semi-arid areas with limited precipitation and surface water availability. This has greatly intensified the dependence of irrigated crops on groundwater withdrawal and caused a steady increase of non-renewable groundwater use, i.e. groundwater taken out of aquifer storage that will not be replenished in human time scales. One of the effects of groundwater pumping is the reduction in streamflow through capture of groundwater recharge, with detrimental effects on aquatic ecosystems. The degree to which groundwater withdrawal affects streamflow or groundwater storage depends on the nature of the groundwater-surface water interaction (GWSI). So far, analytical solutions that have been derived to calculate the impact of groundwater on streamflow depletion involve single wells and streams and do not allow the GWSI to shift from connected to disconnected, i.e. from a situation with two-way interaction to one with a one-way interaction between groundwater and surface water. Including this shift and also analyse the effects of many wells, requires numerical groundwater models that are expensive to setup. Here, we introduce a simple conceptual analytical framework that allows to estimate to what extent groundwater withdrawal affects groundwater heads and streamflow. It allows for a shift in GWSI, calculates at which critical withdrawal rate such a shift is expected and when it is likely to occur after withdrawal commences. It also provides estimates of streamflow depletion and which part of the groundwater withdrawal comes out of groundwater storage and which parts from a reduction in streamflow. After a local sensitivity analysis, the framework is used to provide global maps of critical withdrawal rates and timing, the areas where current withdrawal exceeds critical limits, and maps of groundwater depletion and streamflow depletion rates that result from groundwater withdrawal. The resulting global depletion rates are similar to those obtained from global hydrological models and satellites. The analytical framework is particularly useful for performing first-order sensitivity studies and for supporting hydroeconomic models that require simple relationships between groundwater withdrawal rates and the evolution of pumping costs and environmental externalities.

scholarly journals Reservoir-Induced Land Deformation: Case Study from the Grand Ethiopian Renaissance Dam

2021 ◽  
Vol 13 (5) ◽  
pp. 874
Author(s):  
Yu Chen ◽  
Mohamed Ahmed ◽  
Natthachet Tangdamrongsub ◽  
Dorina Murgulet
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Surface Deformation ◽  
Vertical Displacement ◽  
Nile River ◽  
Reservoir Volume ◽  
Novel Approach ◽  
Land Deformation ◽  
Large Scale Land ◽  
The Impact

The Nile River stretches from south to north throughout the Nile River Basin (NRB) in Northeast Africa. Ethiopia, where the Blue Nile originates, has begun the construction of the Grand Ethiopian Renaissance Dam (GERD), which will be used to generate electricity. However, the impact of the GERD on land deformation caused by significant water relocation has not been rigorously considered in the scientific research. In this study, we develop a novel approach for predicting large-scale land deformation induced by the construction of the GERD reservoir. We also investigate the limitations of using the Gravity Recovery and Climate Experiment Follow On (GRACE-FO) mission to detect GERD-induced land deformation. We simulated three land deformation scenarios related to filling the expected reservoir volume, 70 km3, using 5-, 10-, and 15-year filling scenarios. The results indicated: (i) trends in downward vertical displacement estimated at −17.79 ± 0.02, −8.90 ± 0.09, and −5.94 ± 0.05 mm/year, for the 5-, 10-, and 15-year filling scenarios, respectively; (ii) the western (eastern) parts of the GERD reservoir are estimated to move toward the reservoir’s center by +0.98 ± 0.01 (−0.98 ± 0.01), +0.48 ± 0.00 (−0.48 ± 0.00), and +0.33 ± 0.00 (−0.33 ± 0.00) mm/year, under the 5-, 10- and 15-year filling strategies, respectively; (iii) the northern part of the GERD reservoir is moving southward by +1.28 ± 0.02, +0.64 ± 0.01, and +0.43 ± 0.00 mm/year, while the southern part is moving northward by −3.75 ± 0.04, −1.87 ± 0.02, and −1.25 ± 0.01 mm/year, during the three examined scenarios, respectively; and (iv) the GRACE-FO mission can only detect 15% of the large-scale land deformation produced by the GERD reservoir. Methods and results demonstrated in this study provide insights into possible impacts of reservoir impoundment on land surface deformation, which can be adopted into the GERD project or similar future dam construction plans.

scholarly journals Continuous high-resolution midlatitude-belt simulations for July–August 2013 with WRF

2017 ◽  
Vol 10 (5) ◽  
pp. 2031-2055 ◽  
Author(s):  
Thomas Schwitalla ◽  
Hans-Stefan Bauer ◽  
Volker Wulfmeyer ◽  
Kirsten Warrach-Sagi
Keyword(s):  
High Resolution ◽  
Land Surface ◽  
Large Scale ◽  
Temperature Fields ◽  
Surface Model ◽  
Limited Area ◽  
Data Set ◽  
Latitude Belt ◽  
Simulated Precipitation ◽  
The Impact

Abstract. Increasing computational resources and the demands of impact modelers, stake holders, and society envision seasonal and climate simulations with the convection-permitting resolution. So far such a resolution is only achieved with a limited-area model whose results are impacted by zonal and meridional boundaries. Here, we present the setup of a latitude-belt domain that reduces disturbances originating from the western and eastern boundaries and therefore allows for studying the impact of model resolution and physical parameterization. The Weather Research and Forecasting (WRF) model coupled to the NOAH land–surface model was operated during July and August 2013 at two different horizontal resolutions, namely 0.03 (HIRES) and 0.12° (LOWRES). Both simulations were forced by the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis data at the northern and southern domain boundaries, and the high-resolution Operational Sea Surface Temperature and Sea Ice Analysis (OSTIA) data at the sea surface.The simulations are compared to the operational ECMWF analysis for the representation of large-scale features. To analyze the simulated precipitation, the operational ECMWF forecast, the CPC MORPHing (CMORPH), and the ENSEMBLES gridded observation precipitation data set (E-OBS) were used as references.Analyzing pressure, geopotential height, wind, and temperature fields as well as precipitation revealed (1) a benefit from the higher resolution concerning the reduction of monthly biases, root mean square error, and an improved Pearson skill score, and (2) deficiencies in the physical parameterizations leading to notable biases in distinct regions like the polar Atlantic for the LOWRES simulation, the North Pacific, and Inner Mongolia for both resolutions.In summary, the application of a latitude belt on a convection-permitting resolution shows promising results that are beneficial for future seasonal forecasting.

scholarly journals Impact of climate change on groundwater point discharge: backflooding of karstic springs (Loiret, France)

2011 ◽  
Vol 8 (2) ◽  
pp. 2235-2262
Author(s):  
E. Joigneaux ◽  
P. Albéric ◽  
H. Pauwels ◽  
C. Pagé ◽  
L. Terray ◽  
...  
Keyword(s):  
Climate Change ◽  
Surface Water ◽  
Groundwater Quality ◽  
Atmospheric Circulation ◽  
Large Scale ◽  
Weather Type ◽  
Future Climate Change ◽  
Impact Of Climate Change ◽  
The Impact ◽  
Large Scale Atmospheric Circulation

Abstract. Under certain hydrological conditions it is possible for spring flow in karst systems to be reversed. When this occurs, the resulting invasion by surface water, i.e. the backflooding, represents a serious threat to groundwater quality because the surface water could well be contaminated. Here we examine the possible impact of future climate change on the occurrences of backflooding in a specific karst system, having first established the occurrence of such events in the selected study area over the past 40 yr. It would appear that backflooding has been more frequent since the 1980s, and that it is apparently linked to river flow variability on the pluri-annual scale. The avenue that we adopt here for studying recent and future variations of these events is based on a downscaling algorithm relating large-scale atmospheric circulation to local precipitation spatial patterns. The large-scale atmospheric circulation is viewed as a set of quasi-stationary and recurrent states, called weather types, and its variability as the transition between them. Based on a set of climate model projections, simulated changes in weather-type occurrence for the end of the century suggests that backflooding events can be expected to decrease in 2075–2099. If such is the case, then the potential risk for groundwater quality in the area will be greatly reduced compared to the current situation. Finally, our results also show the potential interest of the weather-type based downscaling approach for examining the impact of climate change on hydrological systems.

A Stochastic Parameter Perturbation Method to Represent Uncertainty in a Microphysics Scheme

2021 ◽  
Author(s):  
Gregory Thompson ◽  
Judith Berner ◽  
Maria Frediani ◽  
Jason A. Otkin ◽  
Sarah M. Griffin
Keyword(s):  
Land Surface ◽  
Large Scale ◽  
Random Perturbation ◽  
Longwave Radiation ◽  
Parameter Uncertainties ◽  
Microphysics Scheme ◽  
Convective Systems ◽  
Temporal Correlations ◽  
Precipitation Characteristics ◽  
The Impact

AbstractCurrent state-of-the art regional numerical weather forecasts are run at horizontal grid spacings of a few kilometers, which permits medium to large-scale convective systems to be represented explicitly in the model. With the convection parameterization no longer active, much uncertainty in the formulation of subgrid-scale processes moves to other areas such as the cloud microphysical, turbulence, and land-surface parameterizations. The goal of this study is to investigate experiments with stochastically-perturbed parameters (SPP) within a microphysics parameterization and the model’s horizontal diffusion coefficients. To estimate the “true” uncertainty due to parameter uncertainty, the magnitudes of the perturbations are chosen as realistic as possible and not with purposeful intent of maximal forecast impact as some prior work has done. Spatial inhomogeneities and temporal persistence are represented using a random perturbation pattern with spatial and temporal correlations. The impact on the distributions of various hydrometeors, precipitation characteristics, and solar/longwave radiation are quantified for a winter and summer case. In terms of upscale error growth, the impact is relatively small and consists primarily of triggering atmospheric instabilities in convectively unstable regions. In addition, small in situ changes with potentially large socio-economic impacts are observed in the precipitation characteristics such as maximum hail size. Albeit the impact of introducing physically-based parameter uncertainties within the bounds of aerosol uncertainties is small, their influence on the solar and longwave radiation balances may still have important implications for global model simulations of future climate scenarios.

scholarly journals Object Detection and Image Segmentation with Deep Learning on Earth Observation Data: A Review—Part II: Applications

2020 ◽  
Vol 12 (18) ◽  
pp. 3053 ◽  
Author(s):  
Thorsten Hoeser ◽  
Felix Bachofer ◽  
Claudia Kuenzer
Keyword(s):  
Image Segmentation ◽  
Deep Learning ◽  
Object Detection ◽  
Land Surface ◽  
Large Scale ◽  
Earth Observation ◽  
Observation Data ◽  
Fine Grained ◽  
The Impact ◽  
Object Dynamics

In Earth observation (EO), large-scale land-surface dynamics are traditionally analyzed by investigating aggregated classes. The increase in data with a very high spatial resolution enables investigations on a fine-grained feature level which can help us to better understand the dynamics of land surfaces by taking object dynamics into account. To extract fine-grained features and objects, the most popular deep-learning model for image analysis is commonly used: the convolutional neural network (CNN). In this review, we provide a comprehensive overview of the impact of deep learning on EO applications by reviewing 429 studies on image segmentation and object detection with CNNs. We extensively examine the spatial distribution of study sites, employed sensors, used datasets and CNN architectures, and give a thorough overview of applications in EO which used CNNs. Our main finding is that CNNs are in an advanced transition phase from computer vision to EO. Upon this, we argue that in the near future, investigations which analyze object dynamics with CNNs will have a significant impact on EO research. With a focus on EO applications in this Part II, we complete the methodological review provided in Part I.

Impact of an Exponential Profile of Saturated Hydraulic Conductivity within the ISBA LSM: Simulations over the Rhône Basin

2006 ◽  
Vol 7 (1) ◽  
pp. 61-80 ◽  
Author(s):  
B. Decharme ◽  
H. Douville ◽  
A. Boone ◽  
F. Habets ◽  
J. Noilhan
Keyword(s):  
High Resolution ◽  
Hydraulic Conductivity ◽  
Land Surface ◽  
Large Scale ◽  
Saturated Hydraulic Conductivity ◽  
Rooting Depth ◽  
Surface Model ◽  
Low Resolution ◽  
The Impact ◽  
Hydrological Applications

Abstract This study focuses on the influence of an exponential profile of saturated hydraulic conductivity, ksat, with soil depth on the water budget simulated by the Interaction Soil Biosphere Atmosphere (ISBA) land surface model over the French Rhône River basin. With this exponential profile, the saturated hydraulic conductivity at the surface increases by approximately a factor of 10, and its mean value increases in the root zone and decreases in the deeper region of the soil in comparison with the values given by Clapp and Hornberger. This new version of ISBA is compared to the original version in offline simulations using the Rhône-Aggregation high-resolution database. Low-resolution simulations, where all atmospheric data and surface parameters have been aggregated, are also performed to test the impact of the modified ksat profile at the typical scale of a climate model. The simulated discharges are compared to observations from a dense network consisting of 88 gauging stations. Results of the high-resolution experiments show that the exponential profile of ksat globally improves the simulated discharges and that the assumption of an increase in saturated hydraulic conductivity from the soil surface to a depth close to the rooting depth in comparison with values given by Clapp and Hornberger is reasonable. Results of the scaling experiments indicate that this parameterization is also suitable for large-scale hydrological applications. Nevertheless, low-resolution simulations with both model versions overestimate evapotranspiration (especially from the plant transpiration and the wet fraction of the canopy) to the detriment of total runoff, which emphasizes the need for implementing subgrid distribution of precipitation and land surface properties in large-scale hydrological applications.

Land–Atmosphere Interaction in Tropical Africa

2020 ◽  
Author(s):  
Cathy Hohenegger
Keyword(s):  
Heat Flux ◽  
Soil Moisture ◽  
Latent Heat ◽  
Latent Heat Flux ◽  
Surface State ◽  
Land Surface ◽  
Large Scale ◽  
Moisture Distribution ◽  
Sahel Region ◽  
The Impact

Even though many features of the vegetation and of the soil moisture distribution over Africa reflect its climatic zones, the land surface has the potential to feed back on the atmosphere and on the climate of Africa. The land surface and the atmosphere communicate via the surface energy budget. A particularly important control of the land surface, besides its control on albedo, is on the partitioning between sensible and latent heat flux. In a soil moisture-limited regime, for instance, an increase in soil moisture leads to an increase in latent heat flux at the expanse of the sensible heat flux. The result is a cooling and a moistening of the planetary boundary layer. On the one hand, this thermodynamically affects the atmosphere by altering the stability and the moisture content of the vertical column. Depending on the initial atmospheric profile, convection may be enhanced or suppressed. On the other hand, a confined perturbation of the surface state also has a dynamical imprint on the atmospheric flow by generating horizontal gradients in temperature and pressure. Such gradients spin up shallow circulations that affect the development of convection. Whereas the importance of such circulations for the triggering of convection over the Sahel region is well accepted and well understood, the effect of such circulations on precipitation amounts as well as on mature convective systems remains unclear. Likewise, the magnitude of the impact of large-scale perturbations of the land surface state on the large-scale circulation of the atmosphere, such as the West African monsoon, has long been debated. One key issue is that such interactions have been mainly investigated in general circulation models where the key involved processes have to rely on uncertain parameterizations, making a definite assessment difficult.

scholarly journals An Integrated Approach for Assessing the Impact of Large‐Scale Future Floods on a Highway Transport System

Risk Analysis ◽  
2020 ◽  
Vol 40 (9) ◽  
pp. 1780-1794
Author(s):  
Weiping Wang ◽  
Saini Yang ◽  
Jianxi Gao ◽  
Fuyu Hu ◽  
Wanyi Zhao ◽  
...  
Keyword(s):  
Transport System ◽  
Large Scale ◽  
Integrated Approach ◽  
The Impact

Regional Impacts of Irrigation in Mexico and the Southwestern United States on Hydrometeorological Fields in the North American Monsoon Region

2016 ◽  
Vol 17 (12) ◽  
pp. 2981-2995 ◽  
Author(s):  
Alex Mahalov ◽  
Jialun Li ◽  
Peter Hyde
Keyword(s):  
North American ◽  
Land Surface ◽  
Large Scale ◽  
Rainfall Variability ◽  
Convective Available Potential Energy ◽  
North American Monsoon ◽  
Western Slope ◽  
Surface Model ◽  
Southern Mexico ◽  
The Impact

Abstract In this study, the impacts of Mexican and southwestern U.S. agricultural and urban irrigation on North American monsoon (NAM) rainfall and other hydrometeorological fields are investigated using the Weather Research and Forecasting (WRF) Model by implementing an irrigation scheme into the WRF–land surface model. Taking the 2000–12 monsoon seasons as examples, multiple WRF simulations with irrigation are conducted by designing different crops’ maximum allowable water depletions (SWm). In comparison with gridded rainfall observations in urban and rural area, the WRF simulations with/without irrigation generally capture the observations very well, but with underestimation along the western slope of the Sierra Madre Occidental (SMO) and overestimation over southern Mexico. The simulations of WRF with irrigation are slightly improved over those without irrigation, compared with rainfall and sounding observations. Sensitivity studies reveal that the impact of irrigation on rainfall varies with location and NAM rainfall variability. Irrigation increases rainfall in eastern Arizona–western New Mexico and in northwestern Mexico because of the irrigation-induced increases of convective available potential energy (CAPE) and precipitable water. Overall, irrigation decreases rainfall in western Arizona, along the western slope of the SMO, and in central Mexico because of irrigation-induced increases of convective inhibition (CIN), decreases of CAPE, and/or large-scale water vapor divergence.

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