GIS and RS Based Spatio-Temporal Analysis of Soil Moisture/Water Content Variation in Southern Irrigated Part of Sindh, Pakistan

2018 ◽  
Vol 07 (04) ◽  
Author(s):  
Madiha Zakir
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Temporal Analysis ◽  
Content Variation ◽  
Gis And Rs ◽  
Spatio Temporal

Physical factors of influence in the interactions between rainfall, evapotranspiration and soil moisture driving the spatio-temporal evolution of drought patterns in the Ebro Basin (NE Spain).

2021 ◽  
Author(s):  
Jaime Gaona ◽  
Pere Quintana-Seguí ◽  
Maria José Escorihuela
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Iberian Peninsula ◽  
Land Surface ◽  
Temporal Analysis ◽  
Drought Indices ◽  
Surface Model ◽  
Physical Factors ◽  
Spatio Temporal ◽  
The Impact

<p>Droughts in the Iberian Peninsula are a natural hazard of great relevance due to their recurrence, severity and impact on multiple environmental and socioeconomic aspects. The Ebro Basin, located in the NE of the Iberian Peninsula, is particularly vulnerable to drought with consequences on agriculture, urban water supply and hydropower. This study, performed within the Project HUMID (CGL2017-85687-R), aims at evaluating the influence of the climatic, land cover and soil characteristics on the interactions between rainfall, evapotranspiration and soil moisture anomalies which define the spatio-temporal drought patterns in the basin.</p><p>The onset, propagation and mitigation of droughts in the Iberian Peninsula is driven by anomalies of rainfall, evapotranspiration and soil moisture, which are related by feedback processes. To test the relative importance of such anomalies, we evaluate the contribution of climatic, land-cover and geologic heterogeneity on the definition of the spatio-temporal patterns of drought. We use the Köppen-Geiger climatic classification to assess how the contrasting climatic types within the basin determine differences on drought behavior. Land-cover types that govern the partition between evaporation and transpiration are also of great interest to discern the influence of vegetation and crop types on the anomalies of evapotranspiration across the distinct regions of the basin (e.g. forested mountains vs. crop-dominated areas). The third physical characteristic whose effect on drought we investigate is the impact of soil properties on soil moisture anomalies.</p><p>The maps and time series used for the spatio-temporal analysis are based on drought indices calculated with high-resolution datasets from remote sensing (MOD16A2ET and SMOS1km) and the land-surface model SURFEX-ISBA. The Standardized Precipitation Index (SPI), the EvapoTranspiration Deficit Index (ETDI) and the Soil Moisture Deficit Index (SMDI) are the three indices chosen to characterize the anomalies of the corresponding rainfall (atmospheric), evapotranspiration (atmosphere-land interface) and soil moisture (land) anomalies (components of the water balance). The comparison of the correlations of the indices (with different time lags) between contrasting regions offers insights about the impact of climate, land-cover and soil properties in the dominance, the timing of the response and memory aspects of the interactions. The high spatial and temporal resolution of remote sensing and land-surface model data allows adopting time and spatial scales suitable to investigate the influence of these physical factors with detail beyond comparison with ground-based datasets.</p><p>The spatial and temporal analysis prove useful to investigate the physical factors of influence on the anomalies between rainfall, evapotranspiration and soil moisture. This approach facilitates the physical interpretation of the anomalies of drought indices aiming to improve the characterization of drought in heterogeneous semi-arid areas like the Ebro River Basin.</p>

Détermination de la perméabilité non saturée des matériaux argileux à faible porosité

1995 ◽  
Vol 32 (6) ◽  
pp. 1035-1043 ◽  
Author(s):  
J.C. Robinet ◽  
M. Rhattas
Keyword(s):  
Diffusion Coefficient ◽  
Water Content ◽  
Characteristic Curve ◽  
Local Equilibrium ◽  
Temporal Analysis ◽  
Hydrodynamic Characteristics ◽  
Solution Technique ◽  
Particle Interactions ◽  
Desorption Isotherms ◽  
Spatio Temporal

The presence of impermeable natural or artificial clayey layers plays a fundamental role in protecting ground water from pollution. In the case of low porosity and partially saturated clays, the experimental determination of transfer coefficient is particularly difficult because of a considerable reduction in hydraulic head and of water–particle interactions that reduce the interstitial water mobility. Experimental work was carried out to obtain, in a simple way, the hydrodynamic characteristics of two clayey formations: Boom and Bassin Parisien. The hydraulic profiles were determined by soaking tests on 300 mm high clayey columns and the sorption–desorption isotherms were evaluated by the saline solution technique on several samples of both clays. The spatio-temporal analysis of the hydraulic profiles reveals the variations in isothermal diffusion coefficient according to the water content. In accordance with the hypothesis of local equilibrium, the sorption–desorption isotherms give the characteristic curve of each formation in a potential versus water content relationship. The total diffusivity combined with retention curves allows to calculate the permeability as a function of the saturation. Key words : clay, sorption–desorption isotherms, soaking tests, diffusion coefficient, permeability.

Surface and profile soil moisture spatio-temporal analysis during an excessive rainfall period in the Southern Great Plains, USA

CATENA ◽  
2009 ◽  
Vol 78 (2) ◽  
pp. 159-169 ◽  
Author(s):  
Gary C. Heathman ◽  
Myriam Larose ◽  
Michael H. Cosh ◽  
Rajat Bindlish
Keyword(s):  
Soil Moisture ◽  
Great Plains ◽  
Temporal Analysis ◽  
Southern Great Plains ◽  
Spatio Temporal

Unraveling the time-scale teleconnections between soil moisture and vegetation

2020 ◽  
Author(s):  
Diego Bueso ◽  
Maria Piles ◽  
Gustau Camps-Valls
Keyword(s):  
Soil Moisture ◽  
International Workshop ◽  
Temporal Analysis ◽  
Earth Observation ◽  
Alternative Methods ◽  
Observation Data ◽  
Causal Relations ◽  
Modes Of Variability ◽  
Nonlinear Pca ◽  
Spatio Temporal

<p>Identifying causal relations from observational data is key to understand Earth system interactions. Extensions to spatio-temporal analysis at different scales are of vital importance for better understanding dynamical phenomenon of natural complex systems. Soil moisture-vegetation interactions constitute a central part of ecosystem functioning and health. Here we are interested in uncovering (potentially nonlinear) spatio-temporal causal relations at different time scales between two relevant Earth observation variables: soil moisture (SM) and vegetation optical depth (VOD). To aboard the complexity data problem, we extract relevant and expressive feature components with the nonlinear kernel-based dimensional reduction method ROCK-PCA in [1]. The method yields the main modes of variability of the variables that are then used to study causal relations. To infer causality relations we use the cross-information kernel Granger causality (XKGC) method introduced in [2], which accounts for nonlinear cross-relations between the involved variables and generalizes nonlinear GC methods. Results are succesfully compared to standard correlation analysis, transfer entropy and convergent cross-mapping alternative methods. In general XKGC identifies a sparser connectivity than correlation. Also, well-known wet and dry patterns are identified as reported in the literature, but other interesting unreported connections and spatio-temporal SM<-->VOD emerge.</p><p>REFERENCES<br>[1] D. Bueso, M. Piles and G. Camps-Valls, "Nonlinear PCA for Spatio-Temporal Analysis of<br>Earth Observation Data," in IEEE Transactions on Geoscience and Remote Sensing, accepted (2020).<br>[2] Brajard, J., Charantonis, A., Chen, C., & Runge, J. (Eds.). (2019). Proceedings of the<br>9th International Workshop on Climate Informatics: CI 2019 (No. NCAR/TN-561+PROC).</p>

scholarly journals Flood-initiating catchment conditions: a spatio-temporal analysis of large-scale soil moisture patterns in the Elbe River basin

2013 ◽  
Vol 17 (4) ◽  
pp. 1401-1414 ◽  
Author(s):  
M. Nied ◽  
Y. Hundecha ◽  
B. Merz
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Large Scale ◽  
Principal Component ◽  
Temporal Analysis ◽  
Elbe River ◽  
High Soil Moisture ◽  
Elbe River Basin ◽  
Spatio Temporal ◽  
The Elbe River

Abstract. Floods are the result of a complex interaction between meteorological event characteristics and pre-event catchment conditions. While the large-scale meteorological conditions have been classified and successfully linked to floods, this is lacking for the large-scale pre-event catchment conditions. Therefore, we propose classifying soil moisture as a key variable of pre-event catchment conditions and investigating the link between soil moisture patterns and flood occurrence in the Elbe River basin. Soil moisture is simulated using a semi-distributed conceptual rainfall-runoff model over the period 1951–2003. Principal component analysis (PCA) and cluster analysis are applied successively to identify days of similar soil moisture patterns. The results show that PCA considerably reduced the dimensionality of the soil moisture data. The first principal component (PC) explains 75.71% of the soil moisture variability and represents the large-scale seasonal wetting and drying. The successive PCs express spatially heterogeneous catchment processes. By clustering the leading PCs, we identify large-scale soil moisture patterns which frequently occur before the onset of floods. In winter, floods are initiated by overall high soil moisture content, whereas in summer the flood-initiating soil moisture patterns are diverse and less stable in time.

scholarly journals Evaluation of Spatio-Temporal Soil Moisture Variability in Semi-Arid Rangeland Ecosystem, Maasai Mara National Reserve, Kenya

2021 ◽  
pp. 64-90
Author(s):  
Charles C. Kapkwang ◽  
Japheth O. Onyando ◽  
Peter M. Kundu ◽  
Joost Hoedjes
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Cosmic Ray ◽  
Tourism Industry ◽  
Soil Layers ◽  
Sandy Clay ◽  
Spatially Distributed ◽  
Spatio Temporal ◽  
Semi Arid ◽  
Arid Rangeland

Aim: To evaluate the spatio-temporal soil moisture storage and retention capacities in semi-arid rangeland ecosystem, Maasai Mara National Reserve (MMNR), Kenya Study Design: Randomized complete block design (RCBD) of reference Cosmic Ray Neutron Sensor (CRNS) station, ten-(10) spatially distributed (soil moisture and temperature capacitance) probes (5TM-ECH20) sites. Place and Duration of Study: Kenya, MMNR, the oldest natural semi-arid rangeland ecosystem and globally unique for the great wildebeest migration, between May 2017 and April 2019. Methodology: Soil moisture (SM) variation data was collected using (CRNS) at spatial and point-scale 5TM-ECH2O probes, and gravimetric water content from (10) spatially distributed stations. Both CRNS and 5TM-ECH2O probes were used to monitor near-real time moisture levels at different soil layers ranging between 0-5cm, 5-10cm, 15-20cm, 35-40cm, and 75-80cm. Soil physical and chemical properties were laboratory analyzed. Calibration and validation datasets were obtained from 5TM-ECH2O probe and gravimetric soil samples extracted from respective layers and sites. Results: The pedological characteristics of the investigated ecosystem soil profile indicate decreased bulk density by 2.1% to 11.12% from upper layers (0-5cm) to deeper layers at (75–80 cm). Across the rangeland, 70% of soil textural classes were sandy clay loam (SCL) with higher clay percent and 30% sandy clay (SC) and soil porosity varied between 30.1% and 51% in the ecosystem. Moreover, volumetric 2    water content (VWC) of spatially distributed 5TM-ECH2O probes ranged between 0.11m3m-3 and 0.32m3m-3 during wet season with mean VWC of 0.16m3m-3, however, the VWC ranged between 0.04 m3m-3 and 0.17m3m-3 during the dry season with a mean volume of 0.11m3m-3 across the rangeland ecosystem. Conclusion: In this study, SM exhibited an annual periodicity of seasonal variation of spatial and temporal moisture partitioned as moisture gaining, losing, and a moisture stable period. This probably could be a consequence of increased movement of water to deeper layers caused by high precipitation and less evaporative demand caused by lower temperatures. The calibrated CRNS probe provided good estimates of spatial soil moisture variation when calibrated with 5TM-ECH20 and gravimetric sampling in relation to precipitation events and that deeper soil layers showed higher amount of soil moisture than shallow layers. The findings of the study will provide better formulation of the ecosystem vegetation management policies, conservation and planning for sustainable wildlife tourism industry.

scholarly journals Spatio-temporal soil moisture retrieval at the catchment scale using a dense network of cosmic-ray neutron sensors

2021 ◽  
Vol 25 (9) ◽  
pp. 4807-4824
Author(s):  
Maik Heistermann ◽  
Till Francke ◽  
Martin Schrön ◽  
Sascha E. Oswald
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Root Zone ◽  
Cosmic Ray ◽  
Dense Network ◽  
Constrained Interpolation ◽  
Neutron Count ◽  
Spatio Temporal

Abstract. Cosmic-ray neutron sensing (CRNS) is a powerful technique for retrieving representative estimates of soil water content at a horizontal scale of hectometres (the “field scale”) and depths of tens of centimetres (“the root zone”). This study demonstrates the potential of the CRNS technique to obtain spatio-temporal patterns of soil moisture beyond the integrated volume from isolated CRNS footprints. We use data from an observational campaign carried out between May and July 2019 that featured a dense network of more than 20 neutron detectors with partly overlapping footprints in an area that exhibits pronounced soil moisture gradients within one square kilometre. The present study is the first to combine these observations in order to represent the heterogeneity of soil water content at the sub-footprint scale as well as between the CRNS stations. First, we apply a state-of-the-art procedure to correct the observed neutron count rates for static effects (heterogeneity in space, e.g. soil organic matter) and dynamic effects (heterogeneity in time, e.g. barometric pressure). Based on the homogenized neutron data, we investigate the robustness of a calibration approach that uses a single calibration parameter across all CRNS stations. Finally, we benchmark two different interpolation techniques for obtaining spatio-temporal representations of soil moisture: first, ordinary Kriging with a fixed range; second, spatial interpolation complemented by geophysical inversion (“constrained interpolation”). To that end, we optimize the parameters of a geostatistical interpolation model so that the error in the forward-simulated neutron count rates is minimized, and suggest a heuristic forward operator to make the optimization problem computationally feasible. Comparison with independent measurements from a cluster of soil moisture sensors (SoilNet) shows that the constrained interpolation approach is superior for representing horizontal soil moisture gradients at the hectometre scale. The study demonstrates how a CRNS network can be used to generate coherent, consistent, and continuous soil moisture patterns that could be used to validate hydrological models or remote sensing products.

Sign in / Sign up

Export Citation Format

Share Document