Water dynamics over a Western Patagonian watershed: Land surface changes and human factors

Understanding the soil-gas migration in unsaturated soil is important in a number of problems that include carbon loading to the atmosphere from the bio-geochemical activity and leakage of gases from subsurface sources from carbon storage unconventional energy development. The soil water dynamics in the vadose zone control the soil-gas pathway development and, hence, the gas flux's spatial and temporal distribution at the soil surface. The spatial distribution of soil-water content depends on soil water characteristics. The dynamics are controlled by the water flux at the land surface and water table fluctuations. Physical properties of soil give a better understanding of the soil gas dynamics and migration from greater soil depths. The fundamental process of soil gas migration under dynamic water content was investigated in the laboratory using an intermediate-scale test system under controlled conditions that is not possible in the field. The experiments focus on observing the methane gas migration in relation to the physical properties of soil and the soil moisture patterns. A 2D soil tank with dimensions of 60 cm &#215; 90 cm &#215; 5.6 cm (height &#215; length &#215; width) was used.&#160; The tank was heterogeneously packed with sandy soil along with a distributed network of soil moisture, temperature, and electrical conductivity sensors. The heterogeneous soil configuration was designed using nine uniform silica sands with the effective sieve numbers #16, #70, #8, #40/50, #110, #30/40, #50, and #20/30 (Accusands, Unimin Corp., Ottawa, MN), and a porosity ranging in values from 0.31 to 0.42. Four methane infrared gas sensors and a Flame Ionization detector (HFR400 Fast FID) were used for the soil gas sampling at different depths within the soil profiles and at the land surface.&#160; A complex transient soil moisture distribution and soil gas migration patterns were observed in the 2D tank. These processes were successfully captured by the sensors. These preliminary experiments helped us to understand the mechanism of soil moisture sensor response and methane gas migration into a heterogeneous sandy soil with a view to developing a large-scale test in a 3D tank (4.87 m &#215; 2.44 m &#215; 0.40 m) and finally transition to field deployment.

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Two parameters are required for a Budyko function to describe the land-atmosphere interaction

10.5194/egusphere-egu21-3554 ◽

2021 ◽

Author(s):

Daeha Kim ◽

Jong Ahn Chun

Keyword(s):

Land Surface ◽

River Basins ◽

Control Surface ◽

Primary Control ◽

Evaporative Demand ◽

Atmosphere Interaction ◽

The Mean ◽

Two Parameters ◽

Two Parameter ◽

Surface Changes

While the Budyko framework has been a simple and convenient tool to assess runoff (Q) responses to climatic and surface changes, it has been unclear how parameters of a Budyko function represent the vertical land-atmosphere interactions. Here, we explicitly derived a two-parameter equation by correcting a boundary condition of the Budyko hypothesis. The correction enabled for the Budyko function to reflect the evaporative demand (Ep) that actively responds to soil moisture deficiency. The derived two-parameter function suggests that four physical variables control surface runoff; namely, precipitation (P), potential evaporation (Ep), wet-environment evaporation (Ew), and the catchment properties (n). We linked the derived Budyko function to a definitive complementary evaporation principle, and assessed the relative elasticities of Q to climatic and land surface changes. Results showed that P is the primary control of runoff changes in most of river basins across the world, but its importance declined with climatological aridity. In arid river basins, the catchment properties play a major role in changing runoff, while changes in Ep and Ew seem to exert minor influences on Q changes. It was also found that the two-parameter Budyko function can capture unusual negative correlation between the mean annual Q and Ep. This work suggests that at least two parameters are required for a Budyko function to properly describe the vertical interactions between the land and the atmosphere.

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Thermal and moisture response to land surface changes across different ecosystems over Heilong-Amur River Basin

The Science of The Total Environment ◽

10.1016/j.scitotenv.2021.151799 ◽

2021 ◽

pp. 151799

Author(s):

Tingxiang Liu ◽

Lingxue Yu ◽

Kun Bu ◽

Jiuchun Yang ◽

Fengqin Yan ◽

...

Keyword(s):

River Basin ◽

Land Surface ◽

Amur River Basin ◽

Amur River ◽

Surface Changes

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Improvement of Clustering Methods for Modelling Abrupt Land Surface Changes in Satellite Image Fusions

Remote Sensing ◽

10.3390/rs11151759 ◽

2019 ◽

Vol 11 (15) ◽

pp. 1759 ◽

Cited By ~ 4

Author(s):

Detang Zhong ◽

Fuqun Zhou

Keyword(s):

Land Surface ◽

Satellite Image ◽

Weighted Average ◽

Clustering Methods ◽

Fusion Model ◽

Dynamic Prediction ◽

New Methods ◽

Satellite Sensors ◽

Spectral Mixing ◽

Surface Changes

A key challenge in developing models for the fusion of surface reflectance data across multiple satellite sensors is ensuring that they apply to both gradual vegetation phenological dynamics and abrupt land surface changes. To better model land cover spatial and temporal changes, we proposed previously a Prediction Smooth Reflectance Fusion Model (PSRFM) that combines a dynamic prediction model based on the linear spectral mixing model with a smoothing filter corresponding to the weighted average of forward and backward temporal predictions. One of the significant advantages of PSRFM is that PSRFM can model abrupt land surface changes either through optimized clusters or the residuals of the predicted gradual changes. In this paper, we expanded our approach and developed more efficient methods for clustering. We applied the new methods for dramatic land surface changes caused by a flood and a forest fire. Comparison of the model outputs showed that the new methods can capture the land surface changes more effectively. We also compared the improved PSRFM to two most popular reflectance fusion algorithms: Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and Enhanced version of STARFM (ESTARFM). The results showed that the improved PSRFM is more effective and outperforms STARFM and ESTARFM both visually and quantitatively.

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The influence of land surface changes on regional climate in Northwest China

Advances in Atmospheric Sciences ◽

10.1007/s00376-007-0527-6 ◽

2007 ◽

Vol 24 (3) ◽

pp. 527-537 ◽

Cited By ~ 5

Author(s):

Xingkui Xu ◽

Feng Zhang ◽

Jason K. Levy

Keyword(s):

Land Surface ◽

Regional Climate ◽

Northwest China ◽

Surface Changes

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Detection of open water dynamics with ENVISAT ASAR in support of land surface modelling at high latitudes

Biogeosciences ◽

10.5194/bg-9-703-2012 ◽

2012 ◽

Vol 9 (2) ◽

pp. 703-714 ◽

Cited By ~ 49

Author(s):

A. Bartsch ◽

A. M. Trofaier ◽

G. Hayman ◽

D. Sabel ◽

S. Schlaffer ◽

...

Keyword(s):

Land Surface ◽

Climate Models ◽

Open Water ◽

Data Availability ◽

Water Dynamics ◽

Climate Modelling ◽

Study Region ◽

Water Fraction ◽

Envisat Asar ◽

Statistical Measures

Abstract. Wetlands are generally accepted as being the largest but least well quantified single source of methane (CH4). The extent of wetland or inundation is a key factor controlling methane emissions, both in nature and in the parameterisations used in large-scale land surface and climate models. Satellite-derived datasets of wetland extent are available on the global scale, but the resolution is rather coarse (>25 km). The purpose of the present study is to assess the capability of active microwave sensors to derive inundation dynamics for use in land surface and climate models of the boreal and tundra environments. The focus is on synthetic aperture radar (SAR) operating in C-band since, among microwave systems, it has comparably high spatial resolution and data availability, and long-term continuity is expected. C-band data from ENVISAT ASAR (Advanced SAR) operating in wide swath mode (150 m resolution) were investigated and an automated detection procedure for deriving open water fraction has been developed. More than 4000 samples (single acquisitions tiled onto 0.5° grid cells) have been analysed for July and August in 2007 and 2008 for a study region in Western Siberia. Simple classification algorithms were applied and found to be robust when the water surface was smooth. Modification of input parameters results in differences below 1 % open water fraction. The major issue to address was the frequent occurrence of waves due to wind and precipitation, which reduces the separability of the water class from other land cover classes. Statistical measures of the backscatter distribution were applied in order to retrieve suitable classification data. The Pearson correlation between each sample dataset and a location specific representation of the bimodal distribution was used. On average only 40 % of acquisitions allow a separation of the open water class. Although satellite data are available every 2–3 days over the Western Siberian study region, the irregular acquisition intervals and periods of unsuitable weather suggest that an update interval of 10 days is more realistic for this domain. SAR data availability is currently limited. Future satellite missions, however, which aim for operational services (such as Sentinel-1 with its C-band SAR instrument), may provide the basis for inundation monitoring for land surface and climate modelling applications.

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Impacts of fully coupling land surface and flood models on the simulation of large wetland’s water dynamics: the case of the Inner Niger Delta

Journal of Advances in Modeling Earth Systems ◽

10.1029/2021ms002463 ◽

2021 ◽

Author(s):

Augusto Getirana ◽

Sujay Kumar ◽

Goutam Konapala ◽

Christopher E. Ndehedehe

Keyword(s):

Land Surface ◽

Niger Delta ◽

Water Dynamics

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Blockchain-Aware Distributed Dynamic Monitoring: A Smart Contract for Fog-Based Drone Management in Land Surface Changes

Atmosphere ◽

10.3390/atmos12111525 ◽

2021 ◽

Vol 12 (11) ◽

pp. 1525

Author(s):

Abdullah Ayub Khan ◽

Zaffar Ahmed Shaikh ◽

Asif Ali Laghari ◽

Sami Bourouis ◽

Asif Ali Wagan ◽

...

Keyword(s):

Land Surface ◽

P2p Network ◽

Dynamic Monitoring ◽

Distributed Data ◽

Distributed Monitoring ◽

Distributed Data Management ◽

Smart Contract ◽

Simulation Results ◽

Stored Information ◽

Surface Changes

In this paper, we propose a secure blockchain-aware framework for distributed data management and monitoring. Indeed, images-based data are captured through drones and transmitted to the fog nodes. The main objective here is to enable process and schedule, to investigate individual captured entity (records) and to analyze changes in the blockchain storage with a secure hash-encrypted (SH-256) consortium peer-to-peer (P2P) network. The proposed blockchain mechanism is also investigated for analyzing the fog-cloud-based stored information, which is referred to as smart contracts. These contracts are designed and deployed to automate the overall distributed monitoring system. They include the registration of UAVs (drones), the day-to-day dynamic captured drone-based images, and the update transactions in the immutable storage for future investigations. The simulation results show the merit of our framework. Indeed, through extensive experiments, the developed system provides good performances regarding monitoring and management tasks.

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Upscaling Evapotranspiration with Parsimonious Models in a North Carolina Vineyard

Agronomy ◽

10.3390/agronomy9030152 ◽

2019 ◽

Vol 9 (3) ◽

pp. 152 ◽

Cited By ~ 2

Author(s):

Christian Dold ◽

Joshua Heitman ◽

Gill Giese ◽

Adam Howard ◽

John Havlin ◽

...

Keyword(s):

North Carolina ◽

Water Stress ◽

Water Use ◽

Land Surface ◽

Vegetation Index ◽

Multiple Linear Regression Model ◽

Water Dynamics ◽

Stress Index ◽

Crop Water Stress Index ◽

Water Stress Index

Water stress can positively or negatively impact grape yield and yield quality, and there is a need for wine growers to accurately regulate water use. In a four-year study (2010–2013), energy balance fluxes were measured with an eddy-covariance (EC) system in a North Carolina vineyard (Vitis vinifera cv. Chardonnay), and evapotranspiration (ET) and the Crop Water Stress Index (CWSI) calculated. A multiple linear regression model was developed to upscale ET using air temperature (Ta), vapor pressure deficit (VPD), and Landsat-derived Land Surface Temperature (LST) and Enhanced Vegetation Index (EVI). Daily ET reached values of up to 7.7 mm day−1, and the annual ET was 752 ± 59 mm, as measured with the EC system. The grapevine CWSI was between 0.53–0.85, which indicated moderate water stress levels. Median vineyard EVI was between 0.22 and 0.72, and the EVI range (max–min) within the vineyard was 0.18. The empirical models explained 75%–84% of the variation in ET, and all parameters had a positive linear relationship to ET. The Root Mean Square Error (RMSE) was 0.52–0.62 mm. This study presents easily applicable approaches to analyzing water dynamics and ET. This may help wine growers to cost-effectively quantify water use in vineyards.

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