Design of Soil Moisture Monitoring and Drought System of Arid and Semi-arid Regions of Farmland

2013 ◽  
Author(s):  
Pang Dang-Feng ◽  
Lei Yun-Tao ◽  
Yan Hu-Min ◽  
Hao Li-Guo ◽  
Lu Jing
Keyword(s):  
Soil Moisture ◽  
Arid Regions ◽  
Semi Arid ◽  
Soil Moisture Monitoring

scholarly journals Suitability Evaluation of Typical Drought Index in Soil Moisture Retrieval and Monitoring Based on Optical Images

2020 ◽  
Vol 12 (16) ◽  
pp. 2587
Author(s):  
Yan Nie ◽  
Ying Tan ◽  
Yuqin Deng ◽  
Jing Yu
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Arid Regions ◽  
Drought Index ◽  
Dynamic Monitoring ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Rapid Acquisition ◽  
Semi Arid ◽  
Soil Moisture Inversion

As a basic agricultural parameter in the formation, transformation, and consumption of surface water resources, soil moisture has a very important influence on the vegetation growth, agricultural production, and healthy operation of regional ecosystems. The Aksu river basin is a typical semi-arid agricultural area which seasonally suffers from water shortage. Due to the lack of knowledge on soil moisture change, the water management and decision-making processes have been a difficult issue for local government. Therefore, soil moisture monitoring by remote sensing became a reasonable way to schedule crop irrigation and evaluate the irrigation efficiency. Compared to in situ measurements, the use of remote sensing for the monitoring of soil water content is convenient and can be repetitively applied over a large area. To verify the applicability of the typical drought index to the rapid acquisition of soil moisture in arid and semi-arid regions, this study simulated, compared, and validated the effectiveness of soil moisture inversion. GF-1 WFV images, Landsat 8 OLI images, and the measured soil moisture data were used to determine the Perpendicular Drought Index (PDI), the Modified Perpendicular Drought Index (MPDI), and the Vegetation Adjusted Perpendicular Drought Index (VAPDI). First, the determination coefficients of the correlation analyses on the PDI, MPDI, VAPDI, and measured soil moisture in the 0–10, 10–20, and 20–30 cm depth layers based on the GF-1 WFV and Landsat 8 OLI images were good. Notably, in the 0–10 cm depth layers, the average determination coefficient was 0.68; all models met the accuracy requirements of soil moisture inversion. Both indicated that the drought indices based on the Near Infrared (NIR)-Red spectral space derived from the optical remote sensing images are more sensitive to soil moisture near the surface layer; however, the accuracy of retrieving the soil moisture in deep layers was slightly lower in the study area. Second, in areas of vegetation coverage, MPDI and VAPDI had a higher inversion accuracy than PDI. To a certain extent, they overcame the influence of mixed pixels on the soil moisture spectral information. VAPDI modified by Perpendicular Vegetation Index (PVI) was not susceptible to vegetation saturation and, thus, had a higher inversion accuracy, which makes it performs better than MPDI’s in vegetated areas. Third, the spatial heterogeneity of the soil moisture retrieved by the GF-1 WFV and Landsat 8 OLI image were similar. However, the GF-1 WFV images were more sensitive to changes in the soil moisture, which reflected the actual soil moisture level covered by different vegetation. These results provide a practical reference for the dynamic monitoring of surface soil moisture, obtaining agricultural information and agricultural condition parameters in arid and semi-arid regions.

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

scholarly journals Environmental Drivers for Cambial Reactivation of Qilian Junipers (Juniperus przewalskii) in a Semi-Arid Region of Northwestern China

Atmosphere ◽  
2020 ◽  
Vol 11 (3) ◽  
pp. 232
Author(s):  
Qiao Zeng ◽  
Sergio Rossi ◽  
Bao Yang ◽  
Chun Qin ◽  
Gang Li
Keyword(s):  
Soil Moisture ◽  
Water Availability ◽  
Arid Regions ◽  
High Elevation ◽  
Northwestern China ◽  
Environmental Drivers ◽  
Limiting Factor ◽  
Severe Drought ◽  
Cambial Reactivation ◽  
Semi Arid

Although cambial reactivation is considered to be strongly dependent on temperature, the importance of water availability at the onset of xylogenesis in semi-arid regions still lacks sufficient evidences. In order to explore how environmental factors influence the initiation of cambial activity and wood formation, we monitored weekly cambial phenology in Qilian juniper (Juniperus przewalskii) from a semi-arid high-elevation region of northwestern China. We collected microcores from 12 trees at two elevations during the growing seasons in 2013 and 2014, testing the hypothesis that rainfall limits cambial reactivation in spring. Cambium was reactivated from late April to mid-May, and completed cell division from late July to early August, lasting 70–100 days. Both sites suffered from severe drought from January to April 2013, receiving < 1 mm of rain in April. In contrast, rainfall from January to April 2014 was 5–6 times higher than that in 2013. However, cambial reactivation in 2014 was delayed by 10 days. In spring, soil moisture gradually increased with warming temperatures, reaching 0.15 m3/m3 before the onset of xylogenesis, which may have ensured water availability for tree growth during the rainless period. We were unable to confirm the hypothesis that rainfall is a limiting factor of cambial reactivation. Our results highlight the importance of soil moisture in semi-arid regions, which better describe the environmental conditions that are favorable for cambial reactivation in water-limited ecosystems.

scholarly journals An Assessment of the Hydrological Trends Using Synergistic Approaches of Remote Sensing and Model Evaluations over Global Arid and Semi-Arid Regions

2020 ◽  
Vol 12 (23) ◽  
pp. 3973
Author(s):  
Wenzhao Li ◽  
Hesham El-Askary ◽  
Rejoice Thomas ◽  
Surya Prakash Tiwari ◽  
Karuppasamy P. Manikandan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Arid Regions ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Statistical Measures ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
Data Assimilation System ◽  
Semi Arid ◽  
Assimilation System

Drylands cover about 40% of the world’s land area and support two billion people, most of them living in developing countries that are at risk due to land degradation. Over the last few decades, there has been warming, with an escalation of drought and rapid population growth. This will further intensify the risk of desertification, which will seriously affect the local ecological environment, food security and people’s lives. The goal of this research is to analyze the hydrological and land cover characteristics and variability over global arid and semi-arid regions over the last decade (2010–2019) using an integrative approach of remotely sensed and physical process-based numerical modeling (e.g., Global Land Data Assimilation System (GLDAS) and Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) models) data. Interaction between hydrological and ecological indicators including precipitation, evapotranspiration, surface soil moisture and vegetation indices are presented in the global four types of arid and semi-arid areas. The trends followed by precipitation, evapotranspiration and surface soil moisture over the decade are also mapped using harmonic analysis. This study also shows that some hotspots in these global drylands, which exhibit different processes of land cover change, demonstrate strong coherency with noted groundwater variations. Various types of statistical measures are computed using the satellite and model derived values over global arid and semi-arid regions. Comparisons between satellite- (NASA-USDA Surface Soil Moisture and MODIS Evapotranspiration data) and model (FLDAS and GLDAS)-derived values over arid regions (BSh, BSk, BWh and BWk) have shown the over and underestimation with low accuracy. Moreover, general consistency is apparent in most of the regions between GLDAS and FLDAS model, while a strong discrepancy is also observed in some regions, especially appearing in the Nile Basin downstream hyper-arid region. Data-driven modelling approaches are thus used to enhance the models’ performance in this region, which shows improved results in multiple statistical measures ((RMSE), bias (ψ), the mean absolute percentage difference (|ψ|)) and the linear regression coefficients (i.e., slope, intercept, and coefficient of determination (R2)).

scholarly journals Extending the Spatio-Temporal Applicability of DISPATCH Soil Moisture Downscaling Algorithm: A Study Case Using SMAP, MODIS and Sentinel-3 Data

2021 ◽  
Vol 9 ◽  
Author(s):  
Nitu Ojha ◽  
Olivier Merlin ◽  
Christophe Suere ◽  
Maria José Escorihuela
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Arid Regions ◽  
Data Sets ◽  
Sparse Vegetation ◽  
Thermal Data ◽  
Spatio Temporal ◽  
Temporal Coverage ◽  
Semi Arid

DISPATCH is a disaggregation algorithm of the low-resolution soil moisture (SM) estimates derived from passive microwave observations. It provides disaggregated SM data at typically 1 km resolution by using the soil evaporative efficiency (SEE) estimated from optical/thermal data collected around solar noon. DISPATCH is based on the relationship between the evapo-transpiration rate and the surface SM under non-energy-limited conditions and hence is well adapted for semi-arid regions with generally low cloud cover and sparse vegetation. The objective of this paper is to extend the spatio-temporal coverage of DISPATCH data by 1) including more densely vegetated areas and 2) assessing the usefulness of thermal data collected earlier in the morning. Especially, we evaluate the performance of the Temperature Vegetation Dryness Index (TVDI) instead of SEE in the DISPATCH algorithm over vegetated areas (called vegetation-extended DISPATCH) and we quantify the increase in coverage using Sentinel-3 (overpass at around 09:30 am) instead of MODIS (overpass at around 10:30 am and 1:30 pm for Terra and Aqua, respectively) data. In this study, DISPATCH is applied to 36 km resolution Soil Moisture Active and Passive SM data over three 50 km by 50 km areas in Spain and France to assess the effectiveness of the approach over temperate and semi-arid regions. The use of TVDI within DISPATCH increases the coverage of disaggregated images by 9 and 14% over the temperate and semi-arid sites, respectively. Moreover, including the vegetated pixels in the validation areas increases the overall correlation between satellite and in situ SM from 0.36 to 0.43 and from 0.41 to 0.79 for the temperate and semi-arid regions, respectively. The use of Sentinel-3 can increase the spatio-temporal coverage by up to 44% over the considered MODIS tile, while the overlapping disaggregated data sets derived from Sentinel-3 and MODIS land surface temperature data are strongly correlated (around 0.7). Additionally, the correlation between satellite and in situ SM is significantly better for DISPATCH (0.39–0.80) than for the Copernicus Sentinel-1-based (−0.03 to 0.69) and SMAP/S1 (0.37–0.74) product over the three studies (temperate and semi-arid) areas, with an increase in yearly valid retrievals for the vegetation-extended DISPATCH algorithm.

SOIL MOISTURE CONTROLS ON WATER VAPOR AND CARBON FLUXES IN SEMI-ARID REGIONS

2006 ◽  
pp. 67-83 ◽  
Author(s):  
John D. ALBERTSON ◽  
Christopher A. WILLIAMS ◽  
Todd M. SCANLON ◽  
Nicola MONTALDO
Keyword(s):  
Soil Moisture ◽  
Water Vapor ◽  
Arid Regions ◽  
Carbon Fluxes ◽  
Semi Arid

scholarly journals New measures of deep soil water recharge during vegetation restoration process in semi-arid regions of northern China

2020 ◽  
Author(s):  
Yiben Cheng ◽  
Hongbin Zhan ◽  
Wenbin Yang ◽  
Qunou Jiang ◽  
Yunqi Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Sandy Soil ◽  
Arid Regions ◽  
Soil Layer ◽  
Soil Particle ◽  
Sandy Land ◽  
Deep Soil ◽  
Artemisia Sphaerocephala ◽  
The Impact ◽  
Semi Arid

Abstract. Desertification in semi-arid regions is currently a global environmental and societal problem. This research attempts to understand whether a 40-year-old rain-feed Artamisia sphaerocephala Krasch sand-fixing land in Three North Shelterbelt Program (3NSP) of China can be developed sustainably or not, using a newly designed lysimeter to monitor the precipitation-induced deep soil recharge (DSR) at 220 cm depth. Evapotranspiration is calculated through a water balance equation when precipitation and soil moisture data are collected. Comparison of soil particle sizes and soil moisture distributions in artificial sand-fixing land and neighboring bare land is made to assess the impact of sand-fixing reforestation. Results show that such a sand-fixing reforestation results in a root system being mainly developed in the horizontal direction and the changed soil particle distribution. Specifically, the sandy soil with 50.53 % medium sand has been transformed into a sandy soil with 68.53 % fine sand. Within the Artamisia sphaerocephala Krasch sand-fixing experimental area, the DSR values in bare sand plot and Artemisia sphaerocephala Krasch plot are respectively 283.6 mm and 90.6 mm in wet years, reflecting a difference of more than three times. The deep soil layer moisture in semi-arid sandy land is largely replenished by precipitation-induced infiltration. The DSR values of bare sandy land plot and Artemisia sphaerocephala Krasch plot are respectively 51.6 mm and 2 mm in dry years, a difference of more than 25 times. The proportions of DSR reduced by Artemisia sphaerocephala Krasch is 68.06 % and 96.12 % in wet and dry years, respectively. This research shows that Artamisia sphaerocephala Krasch in semi-arid region can continue to grow and has the capacity of fixing sand. It consumes a large amount of precipitated water, and reduces the amount of DSR considerably.

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