scholarly journals Characteristic of Soil Moisture in Indonesia Using ESA CCI Satellites Products

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Fatkhuroyan Fatkhuroyan ◽  
Trinah Wati ◽  
Roni Kurniawan
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Temporal Variability ◽  
Land Surface ◽  
Water Exchange ◽  
Spatial And Temporal Variability

Soil moisture (SM) is one of the energy and water exchange main drivers between the atmosphere and land surface. The study aims to analyze the soil moisture characteristics in Indonesia on monthly and seasonal time scales. The analysis uses mapping of monthly and seasonal ESA CCI SM satellite products of mean daily from 1979 to 2016. The results showed the spatial and temporal variability of SM in Indonesia. Sumatera has SM values > 0.3 m3/m3 almost throughout the year. Besides, Java has SM values > 0.3 m3/m3 from January to April and October to December while 0.2-0.3 m3/m3 from May to September. In Borneo, the SM value > 0.3 m3/m3 from February to June and November to December, while from July to September are 0.2-0.3 m3/m3. Sulawesi has SM values > 0.3 m3/m3 from January to July, on December, and 0.2-0.3 m3/m3 from august to November. Bali to Nusa Tenggara have SM values between 0.2-0.3 m3/m3 throughout the year, except <0.2 m3/m3 in Sumba, Timor Island, and Central Lombok from June to November. Maluku has SM values between 0.2-0.3 m3/m3 throughout the year, while Papua has SM values >0.3 m3/m3 throughout the year, except in Jayawijaya Mountain and South Papua. The ESA CCI SM product is essential for monitoring SM in Indonesia.

scholarly journals Confronting Weather and Climate Models with Observational Data from Soil Moisture Networks over the United States

2016 ◽  
Vol 17 (4) ◽  
pp. 1049-1067 ◽  
Author(s):  
Paul A. Dirmeyer ◽  
Jiexia Wu ◽  
Holly E. Norton ◽  
Wouter A. Dorigo ◽  
Steven M. Quiring ◽  
...  
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Observational Data ◽  
Temporal Variability ◽  
Land Surface ◽  
Large Scale ◽  
Heat Dissipation ◽  
Measurement Techniques ◽  
The United States ◽  
Spatial And Temporal Variability

Abstract Four land surface models in uncoupled and coupled configurations are compared to observations of daily soil moisture from 19 networks in the conterminous United States to determine the viability of such comparisons and explore the characteristics of model and observational data. First, observations are analyzed for error characteristics and representation of spatial and temporal variability. Some networks have multiple stations within an area comparable to model grid boxes; for those it is found that aggregation of stations before calculation of statistics has little effect on estimates of variance, but soil moisture memory is sensitive to aggregation. Statistics for some networks stand out as unlike those of their neighbors, likely because of differences in instrumentation, calibration, and maintenance. Buried sensors appear to have less random error than near-field remote sensing techniques, and heat-dissipation sensors show less temporal variability than other types. Model soil moistures are evaluated using three metrics: standard deviation in time, temporal correlation (memory), and spatial correlation (length scale). Models do relatively well in capturing large-scale variability of metrics across climate regimes, but they poorly reproduce observed patterns at scales of hundreds of kilometers and smaller. Uncoupled land models do no better than coupled model configurations, nor do reanalyses outperform free-running models. Spatial decorrelation scales are found to be difficult to diagnose. Using data for model validation, calibration, or data assimilation from multiple soil moisture networks with different types of sensors and measurement techniques requires great caution. Data from models and observations should be put on the same spatial and temporal scales before comparison.

scholarly journals Verification and Intercomparison of Multimodel Simulated Land Surface Hydrological Datasets over the United States

2011 ◽  
Vol 12 (4) ◽  
pp. 531-555 ◽  
Author(s):  
Yun Fan ◽  
Huug M. van den Dool ◽  
Wanru Wu
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Surface Water ◽  
Water Balance ◽  
Time Scales ◽  
Land Surface ◽  
The United States ◽  
Surface Model ◽  
Spatial And Temporal Variability ◽  
Water Balance Components

Abstract Several land surface datasets, such as the observed Illinois soil moisture dataset; three retrospective offline run datasets from the Noah land surface model (LSM), Variable Infiltration Capacity (VIC) LSM, and Climate Prediction Center leaky bucket soil model; and three reanalysis datasets (North American Regional Reanalysis, NCEP/Department of Energy Global Reanalysis, and 40-yr ECMWF Re-Analysis), are used to study the spatial and temporal variability of soil moisture and its response to the major components of land surface hydrologic cycles: precipitation, evaporation, and runoff. Detailed analysis was performed on the evolution of the soil moisture vertical profile. Over Illinois, model simulations are compared to observations, but for the United States as a whole some impressions can be gained by comparing the multiple soil moisture–precipitation–evaporation–runoff datasets to one another. The magnitudes and partitioning of major land surface water balance components on seasonal–interannual time scales have been explored. It appears that evaporation has the most prominent annual cycle but its interannual variability is relatively small. For other water balance components, such as precipitation, runoff, and surface water storage change, the amplitudes of their annual cycles and interannual variations are comparable. This study indicates that all models have a certain capability to reproduce observed soil moisture variability on seasonal–interannual time scales, but offline runs are decidedly better than reanalyses (in terms of validation against observations) and more highly correlated to one another (in terms of intercomparison) in general. However, noticeable differences are also observed, such as the degree of simulated drought severity and the locations affected—this is due to the uncertainty in model physics, input forcing, and mode of running (interactive or offline), which continue to be major issues for land surface modeling.

Regional scale spatial and temporal variability of soil moisture in a prairie region

2016 ◽  
Vol 30 (20) ◽  
pp. 3639-3649 ◽  
Author(s):  
Travis T. Burns ◽  
Aaron A. Berg ◽  
Jaclyn Cockburn ◽  
Erica Tetlock
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Regional Scale ◽  
Spatial And Temporal Variability

Spatial and temporal variability of soil moisture over India using IRS P4 MSMR data

2005 ◽  
Vol 26 (10) ◽  
pp. 2241-2247 ◽  
Author(s):  
R. P. Singh ◽  
D. R. Mishra ◽  
A. K. Sahoo † ◽  
S. Dey
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Spatial And Temporal Variability

Soil Moisture Drought in China, 1950–2006

2011 ◽  
Vol 24 (13) ◽  
pp. 3257-3271 ◽  
Author(s):  
Aihui Wang ◽  
Dennis P. Lettenmaier ◽  
Justin Sheffield
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Agricultural Drought ◽  
Central China ◽  
Spatial Extent ◽  
Drought Severity ◽  
Spatial And Temporal Variability ◽  
The Tibetan Plateau ◽  
Small Areas ◽  
Physically Based

Abstract Four physically based land surface hydrology models driven by a common observation-based 3-hourly meteorological dataset were used to simulate soil moisture over China for the period 1950–2006. Monthly values of total column soil moisture from the simulations were converted to percentiles and an ensemble method was applied to combine all model simulations into a multimodel ensemble from which agricultural drought severities and durations were estimated. A cluster analysis method and severity–area–duration (SAD) algorithm were applied to the soil moisture data to characterize drought spatial and temporal variability. For drought areas greater than 150 000 km2 and durations longer than 3 months, a total of 76 droughts were identified during the 1950–2006 period. The duration of 50 of these droughts was less than 6 months. The five most prominent droughts, in terms of spatial extent and then duration, were identified. Of these, the drought of 1997–2003 was the most severe, accounting for the majority of the severity–area–duration envelope of events with areas smaller than 5 million km2. The 1997–2003 drought was also pervasive in terms of both severity and spatial extent. It was also found that soil moisture in north central and northeastern China had significant downward trends, whereas most of Xinjiang, the Tibetan Plateau, and small areas of Yunnan province had significant upward trends. Regions with downward trends were larger than those with upward trends (37% versus 26% of the land area), implying that over the period of analysis, the country has become slightly drier in terms of soil moisture. Trends in drought severity, duration, and frequency suggest that soil moisture droughts have become more severe, prolonged, and frequent during the past 57 yr, especially for northeastern and central China, suggesting an increasing susceptibility to agricultural drought.

scholarly journals Controls and characteristics of variability in soil moisture and groundwater in a headwater catchment

2014 ◽  
Vol 11 (8) ◽  
pp. 9475-9517
Author(s):  
H. K. McMillan ◽  
M. S. Srinivasan
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Water Table ◽  
Temporal Variability ◽  
Extreme Values ◽  
Stream Water ◽  
Spatial And Temporal Variability ◽  
Multiple Time ◽  
Strong Impact ◽  
Strong Control

Abstract. This paper presents experimental results from a new headwater research catchment in New Zealand. We made distributed measurements of streamflow, soil moisture and groundwater levels, sampling across a range of aspects, hillslope positions, distances from stream and depths. Our aim was to assess the controls, types and implications of spatial and temporal variability in surface and groundwaters. We found that temporal variability is strongly controlled by the seasonal cycle, for both soil moisture and water table, and for both the mean and extremes of the distributions. The standard deviation of both soil moisture and groundwater values calculated per timestep is larger in winter than in summer, and standard deviations typically peak during rainfall events due to partial saturation of the catchment. Controls on the spatial variability differed between the water stores. Aspect had a strong control on groundwater but not on soil moisture, distance from stream controlled both soil moisture and groundwater. The depth of the soil moisture sensor had little impact in terms of mean water content, but a strong impact on the extreme values, i.e. saturation. Co-measurement of soil moisture and water table level variability allowed us to identify variability components that differed between these water stores e.g. patterns of strong response in soil water content were not the same for groundwater level, and those that were consistent e.g. vertical infiltration of summer rainfall through upper and lower soil depths, or rising near-stream water tables through shallow wells to lower soil depths. Signatures of variability were observed in the streamflow series, showing that understanding variability is important for hydrological prediction. Total catchment variability is composed of multiple variability sources. The dominant variability type changes with catchment wetness conditions according to which water stores are active, and in particular those which are close to a threshold such as field capacity or saturation. Our results suggest that the integrative processes that create emergent catchment behaviour should be understood as the sum of these multiple, time varying components.

Time Scales of Land Surface Hydrology

2006 ◽  
Vol 7 (5) ◽  
pp. 868-879 ◽  
Author(s):  
Aihui Wang ◽  
Xubin Zeng ◽  
Samuel S. P. Shen ◽  
Qing-Cun Zeng ◽  
Robert E. Dickinson
Keyword(s):  
Soil Moisture ◽  
Time Scales ◽  
Time Scale ◽  
Land Surface ◽  
Vertical Structure ◽  
Root Zone ◽  
Layer Model ◽  
Surface Hydrology ◽  
Soil System ◽  
Land Surface Hydrology

Abstract This paper intends to investigate the time scales of land surface hydrology and enhance the understanding of the hydrological cycle between the atmosphere, vegetation, and soil. A three-layer model for land surface hydrology is developed to study the temporal variation and vertical structure of water reservoirs in the vegetation–soil system in response to precipitation forcing. The model is an extension of the existing one-layer bucket model. A new time scale is derived, and it better represents the response time scale of soil moisture in the root zone than the previously derived inherent time scale (i.e., the ratio of the field capacity to the potential evaporation). It is found that different water reservoirs of the vegetation–soil system have different time scales. Precipitation forcing is mainly concentrated on short time scales with small low-frequency components, but it can cause long time-scale disturbances in the soil moisture of root zone. This time scale increases with soil depth, but it can be reduced significantly under wetter conditions. Although the time scale of total water content in the vertical column in the three-layer model is similar to that of the one-layer bucket model, the time scale of evapotranspiration is very different. This suggests the need to consider the vertical structure in land surface hydrology reservoirs and in climate study.

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