Variation of the Relative Soil Moisture of Farmland in a Continental River Basin in China

The reduction of grain production caused by drought is one of the most serious problems caused by natural disasters. The relative soil moisture of farmland is the most important monitoring indicator for agricultural drought. This study investigated the relative soil moisture of farmland data from 38 agrometeorological stations in a continental river basin area in China from 1992 to 2012. Spatial and temporal variations of the relative soil moisture of farmland were studied using geostatistical analysis. The results show that, from 1992 to 2012, the average annual relative soil moisture of farmland in the continental river basin ranged from 62.5 to 86.1%, and the relative soil moisture of farmland was high in the marginal areas of basins and low in the central areas of basins and plateau areas. The relative soil moisture of farmland was high in the Tarim Basin and the Hexi Corridor, which are located in the northern Tianshan Mountains and the southern and northern Qilian Mountains, and was low from the northern Altun Mountains to the south of Lop Nor, the Turpan Depression, and the Tarbagatai Mountains. From 1992 to 2012, the annual average relative soil moisture of farmland in the continental river basins showed an increasing trend, with a growth rate of 0.57% yr−1. The variation tendency of the relative soil moisture of farmland was different in different river basins; the relative soil moisture showed a decreasing trend in the Mongolian Plateau and an increasing trend in other basin areas. The relative soil moisture of farmland increased in summer, spring, and winter, and decreased in autumn. The change in relative soil moisture of farmland was due to a combination of climatic factors, such as precipitation and temperature, as well as topography and glacial meltwater.

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Investigating the Spatio-Temporal Variation of Soil Moisture and Agricultural Drought towards Supporting Water Resources Management in the Red River Basin of Vietnam

Sustainability ◽

10.3390/su13094926 ◽

2021 ◽

Vol 13 (9) ◽

pp. 4926

Author(s):

Nguyen Duc Luong ◽

Nguyen Hoang Hiep ◽

Thi Hieu Bui

Keyword(s):

Soil Moisture ◽

River Basin ◽

Temporal Dynamics ◽

Regional Scale ◽

Dry Season ◽

Red River ◽

Agricultural Drought ◽

Severe Drought ◽

Red River Basin ◽

Spatio Temporal

The increasing serious droughts recently might have significant impacts on socioeconomic development in the Red River basin (RRB). This study applied the variable infiltration capacity (VIC) model to investigate spatio-temporal dynamics of soil moisture in the northeast, northwest, and Red River Delta (RRD) regions of the RRB part belongs to territory of Vietnam. The soil moisture dataset simulated for 10 years (2005–2014) was utilized to establish the soil moisture anomaly percentage index (SMAPI) for assessing intensity of agricultural drought. Soil moisture appeared to co-vary with precipitation, air temperature, evapotranspiration, and various features of land cover, topography, and soil type in three regions of the RRB. SMAPI analysis revealed that more areas in the northeast experienced severe droughts compared to those in other regions, especially in the dry season and transitional months. Meanwhile, the northwest mainly suffered from mild drought and a slightly wet condition during the dry season. Different from that, the RRD mainly had moderately to very wet conditions throughout the year. The areas of both agricultural and forested lands associated with severe drought in the dry season were larger than those in the wet season. Generally, VIC-based soil moisture approach offered a feasible solution for improving soil moisture and agricultural drought monitoring capabilities at the regional scale.

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A novel comprehensive agricultural drought index reflecting time lag of soil moisture to meteorology: A case study in the Yangtze River basin, China

CATENA ◽

10.1016/j.catena.2021.105804 ◽

2022 ◽

Vol 209 ◽

pp. 105804

Author(s):

Qing Tian ◽

Jianzhong Lu ◽

Xiaoling Chen

Keyword(s):

Soil Moisture ◽

River Basin ◽

Yangtze River ◽

Drought Index ◽

Yangtze River Basin ◽

Time Lag ◽

Agricultural Drought ◽

The Yangtze River ◽

The Yangtze River Basin

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Satellite Soil Moisture for Agricultural Drought Monitoring: Assessment of SMAP-Derived Soil Water Deficit Index in Xiang River Basin, China

Remote Sensing ◽

10.3390/rs11030362 ◽

2019 ◽

Vol 11 (3) ◽

pp. 362 ◽

Cited By ~ 10

Author(s):

Qian Zhu ◽

Yulin Luo ◽

Yue-Ping Xu ◽

Ye Tian ◽

Tiantian Yang

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Water Deficit ◽

River Basin ◽

Probability Of Detection ◽

Agricultural Drought ◽

Drought Monitoring ◽

Soil Water Deficit ◽

R Value ◽

Xiang River

Agricultural drought can have long-lasting and harmful impacts on both the ecosystem and economy. Therefore, it is important to monitor and predict agricultural drought accurately. Soil moisture is the key variable to define the agricultural drought index. However, in situ soil moisture observations are inaccessible in many areas of the world. Remote sensing techniques enrich the surface soil moisture observations at different tempo-spatial resolutions. In this study, the Level 2 L-band radiometer soil moisture dataset was used to estimate the Soil Water Deficit Index (SWDI). The Soil Moisture Active Passive (SMAP) dataset was evaluated with the soil moisture dataset obtained from the China Land Soil Moisture Data Assimilation System (CLSMDAS). The SMAP-derived SWDI (SMAP_SWDI) was compared with the atmospheric water deficit (AWD) calculated with precipitation and evapotranspiration from meteorological stations. Drought monitoring and comparison were accomplished at a weekly scale for the growing season (April to November) from 2015 to 2017. The results were as follows: (1) in terms of Pearson correlation coefficients (R-value) between SMAP and CLSMDAS, around 70% performed well and only 10% performed poorly at the grid scale, and the R-value was 0.62 for the whole basin; (2) severe droughts mainly occurred from mid-June to the end of September from 2015 to 2017; (3) severe droughts were detected in the southern and northeastern Xiang River Basin in mid-May of 2015, and in the northern basin in early August of 2016 and end of November 2017; (4) the values of percentage of drought weeks gradually decreased from 2015 to 2017, and increased from the northeast to the southwest of the basin in 2015 and 2016; and (5) the average value of R and probability of detection between SMAP_SWDI and AWD were 0.6 and 0.79, respectively. These results show SMAP has acceptable accuracy and good performance for drought monitoring in the Xiang River Basin.

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Geospatial evaluation of drought resilience in sub-basins of Mahanadi river in India

Water Science & Technology Water Supply ◽

10.2166/ws.2020.178 ◽

2020 ◽

Vol 20 (7) ◽

pp. 2826-2844

Author(s):

Preeti Rajput ◽

Manish Kumar Sinha

Keyword(s):

River Basin ◽

Climatic Factors ◽

Anthropogenic Activities ◽

Central India ◽

River Basins ◽

Drought Vulnerability ◽

High Coverage ◽

Mahanadi River ◽

Geospatial Database ◽

Optimum Utilization

Abstract Development is said to be sustainable in respect of drought if the effect has been absorbed by the existing system. Occurrence of drought depends on physiographical, climatic factors and optimum utilization of available resources of the river basin. This study aims to evaluate the vulnerability and resilience of river basin systems for the identification of priority areas under drought susceptibility for three different river basins, namely Arpa, Kharun and Upper Seonath of Mahanadi river in central India, as a pilot area for this study. The study represents an approach to evaluate the drought susceptibility of river basins based on physiographical factors and anthropogenic activities. A model proposed for vulnerability assessment based on variables of exposure, sensitivity and adaptive capacity, and a geospatial database of basin characteristics contributing to vulnerability, was generated using remote sensing and a geographic information system. Multi-criteria decision analysis was done to evaluate the influence of river basin characteristics, population load and land-use/cover on drought susceptibility for assessing the drought vulnerability of the river basin and suggest the solution for the optimum utilization of natural resources according to the river basin characteristics. The result of this study demarcates the area in four categories of Extremely vulnerable, Moderately vulnerable, Vulnerable and Not vulnerable. On the analysis, only 3.86% of Upper Seonath is Not vulnerable, followed by Kharun basin having 15.59% as Not vulnerable area and 48.23% of the area of Arpa river basin identified as Not vulnerable. Arpa river basin is least affected by drought due to its lower population density and high coverage of forest and agriculture area.

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The 20-y spatio-temporal trends of remotely sensed soil moisture and vegetation and their response to climate change over the Third Pole

Journal of Hydrometeorology ◽

10.1175/jhm-d-21-0077.1 ◽

2021 ◽

Author(s):

Pengfei Shi ◽

Jiangyuan Zeng ◽

Kun-Shan Chen ◽

Hongliang Ma ◽

Haiyun Bi ◽

...

Keyword(s):

Soil Moisture ◽

Climatic Factors ◽

Temporal Trends ◽

Arid Zones ◽

The Tibetan Plateau ◽

Change Rate ◽

Vegetation Growth ◽

The Third ◽

Increasing Trend ◽

Spatio Temporal

AbstractThe Tibetan Plateau (TP), known as the “Third Pole”, is a climate-sensitive and ecology-fragile region. In this study, the spatio-temporal trends of soil moisture (SM) and vegetation were analyzed using satellite-based ESA CCI SM and MODIS LAI data respectively in the growing season during the last 20 years (2000-2019) over the TP covering diverse climate zones. The climatic drivers (precipitation and air temperature) of SM and LAI variations were fully investigated by using both ERA5 reanalysis and observation-based gridded data. The results reveal the TP is generally wetting and significantly greening in the last 20 years. The SM with significant increasing trend accounts for 21.80% (fraction of grid cells) of the TP, and is about twice of the SM with significant decreasing trend (10.19%), while more than half of the TP (58.21%) exhibits significant increasing trend of LAI. Though the responses of SM and LAI to climatic factors are spatially heterogeneous, precipitation is the dominant driver of SM variation with 48.36% (ERA5) and 32.51% (observation-based) precipitation data showing the strongest significant positive partial correlation with SM. Temperature rise largely explains the vegetation greening though precipitation also plays an important role in vegetation growth in arid and semi-arid zones. The combined trend of SM and LAI indicates the TP is mainly composed of wetting and greening areas, followed by drying and greening regions. The change rate of SM is negative at low altitudes and becomes positive as altitude increases, while the LAI value and its change rate decrease as altitude increases.

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Satellite Altimetry over River Basins - Beyond Water Heights

10.5194/egusphere-egu2020-3652 ◽

2020 ◽

Author(s):

Philippa Berry ◽

Jerome Benveniste

Keyword(s):

Soil Moisture ◽

River Basin ◽

Soil Surface ◽

River Basins ◽

Validation Dataset ◽

Altimeter Data ◽

Unique Contribution ◽

Surface Moisture ◽

Satellite Radar ◽

Water Height

The unique contribution of satellite radar altimetry to river monitoring is well understood, with &#8216; altimeter virtual gauge&#8217; heights increasingly ingested into river basin models. However, altimeters gather a wealth of additional information. Waveform shapes reflect underlying topographic variation, surface composition and roughness, and distribution of surface water within the footprint. Backscatter measurements allow soil surface moisture under the satellite track to be determined, using DRy EArth ModelS (DREAMS) crafted from multi-mission altimeter data and ground truth. Initially developed over desert areas, DREAMs are now being built over river basins to extend the scope of altimeter soil moisture measurement.This paper investigates &#160;the potential contribution of these additional data to river basin analysis and modelling.&#160; The following key questions are addressed.&#160; 1) How useful are the data encoded in complex waveform shapes?&#160; 2) Can altimeter soil moisture estimates contribute to modelling in river basins? A series of example river basins were chosen in different topographic and climate situations, including the Amazon, Orinoco, Nile, Niger and Congo basins, and wetlands including the Okavango delta.This paper presents outcomes from analysis of multi-mission altimetry, with ERS-1/2, Envisat, Topex, Jason-1/2, Cryosat-2 and Sentinel-3A/B, plus a database of over 86,000 river and lake timeseries.The analysis outcomes demonstrate the value of altimeter soil surface moisture estimates, both as co-temporal and co-spatial data with inland water height measurements, and as an independent validation dataset to assess soil moisture estimates derived from other remote sensing techniques. The precise backscatter cross-calibration of altimeters on successive missions allows derivation of long soil moisture time series. The ability of nadir-pointing altimeters to penetrate vegetation canopy gives a unique perspective in rainforest areas, with information on underlying water height and extent as well as surface soil moisture. Waveform shape classification allows diverse information to be gleaned, particularly at the higher pulse repetition frequencies of the new generation of SAR Altimeters. In conclusion, satellite radar altimeters collect a wealth of information over river basins; this valuable resource is not yet fully exploited.

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Catchment-scale drought: capturing the whole drought cycle using multiple indicators

Hydrology and Earth System Sciences ◽

10.5194/hess-24-1985-2020 ◽

2020 ◽

Vol 24 (4) ◽

pp. 1985-2002 ◽

Cited By ~ 1

Author(s):

Abraham J. Gibson ◽

Danielle C. Verdon-Kidd ◽

Greg R. Hancock ◽

Garry Willgoose

Keyword(s):

Soil Moisture ◽

Large Scale ◽

Climatic Factors ◽

Southern Oscillation ◽

Meteorological Drought ◽

Southern Annular Mode ◽

Agricultural Drought ◽

Catchment Scale ◽

Climate Resilience ◽

Eastern Australia

Abstract. Global agricultural drought policy has shifted towards promoting drought preparedness and climate resilience in favor of disaster-relief-based strategies. For this approach to be successful, drought predictability and methods for assessing the many aspects of drought need to be improved. Therefore, this study aims to bring together meteorological and hydrological measures of drought as well as vegetation and soil moisture data to assess how droughts begin, propagate and subsequently terminate for a catchment in eastern Australia. For the study area, 13 meteorological drought periods persisting more than 6 months were identified over the last 100 years. During these periods, vegetation health, soil moisture and streamflow declined; however, all of the indicators recovered quickly post-drought, with no evidence of extended impacts on the rainfall–runoff response, as has been observed elsewhere. Furthermore, drought initiation and propagation were found to be tightly coupled to the combined state of large-scale ocean–atmosphere climate drivers (e.g., the El Niño–Southern Oscillation, the Indian Ocean Dipole and the Southern Annular Mode), whereas termination was caused by persistent synoptic systems (e.g., low-pressure troughs). The combination of climatic factors, topography, soils and vegetation are believed to be what makes the study catchments more resilient to drought than others in eastern Australia. This study diversifies traditional approaches to studying droughts by quantifying the catchment response to drought using a range of measures that could also be applied in other catchments globally. This is a key step towards improved drought management.

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Spatiotemporal Variability of Actual Evapotranspiration and the Dominant Climatic Factors in the Pearl River Basin, China

Atmosphere ◽

10.3390/atmos10060340 ◽

2019 ◽

Vol 10 (6) ◽

pp. 340 ◽

Cited By ~ 2

Author(s):

Weizhi Gao ◽

Zhaoli Wang ◽

Guoru Huang

Keyword(s):

Climate Change ◽

River Basin ◽

Climatic Factors ◽

Actual Evapotranspiration ◽

Pearl River ◽

Pearl River Basin ◽

Sunshine Hours ◽

Increasing Trend ◽

The Pearl River ◽

The Pearl River Basin

Evapotranspiration is a vital component of the land surface process, thus, a more accurate estimate of evapotranspiration is of great significance to agricultural production, research on climate change, and other activities. In order to explore the spatiotemporal variation of evapotranspiration under global climate change in the Pearl River Basin (PRB), in China, this study conducted a simulation of actual evapotranspiration (ETa) during 1960–2014 based on the variable infiltration capacity (VIC) model with a high spatial resolution of 0.05°. The nonparametric Mann–Kendall (M–K) test and partial correlation analysis were used to examine the trends of ETa. The dominant climatic factors impacting on ETa were also examined. The results reveal that the annual ETa across the whole basin exhibited a slight but not significant increasing trend during the 1960–2014 period, whereas a significant decreasing trend was found during the 1960–1992 period. At the seasonal scale, the ETa showed a significant upward trend in summer and a significant downward trend in autumn. At the spatial scale, the ETa generally showed a decreasing, but not significant, trend in the middle and upper stream of the PRB, while in the downstream areas, especially in the Pearl River Delta and Dongjiang River Basin, it exhibited a significant increasing trend. The variation of the ETa was mainly associated with sunshine hours and average air pressure. The negative trend of the ETa in the PRB before 1992 may be due to the significant decrease in sunshine hours, while the increasing trend of the ETa after 1992 may be due to the recovery of sunshine hours and the significant decrease of air pressure. Additionally, we found that the “paradox” phenomenon detected by ETa mainly existed in the middle-upper area of the PRB during the period of 1960–1992.

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Downscaling of SMAP Soil Moisture in the Lower Mekong River Basin

Water ◽

10.3390/w12010056 ◽

2019 ◽

Vol 12 (1) ◽

pp. 56 ◽

Cited By ~ 3

Author(s):

Chelsea Dandridge ◽

Bin Fang ◽

Venkat Lakshmi

Keyword(s):

Soil Moisture ◽

Surface Temperature ◽

River Basin ◽

River Basins ◽

Large River ◽

Mekong River ◽

Mekong River Basin ◽

In Situ Data ◽

Large River Basins

In large river basins where in situ data were limited or absent, satellite-based soil moisture estimates can be used to supplement ground measurements for land and water resource management solutions. Consistent soil moisture estimation can aid in monitoring droughts, forecasting floods, monitoring crop productivity, and assisting weather forecasting. Satellite-based soil moisture estimates are readily available at the global scale but are provided at spatial scales that are relatively coarse for many hydrological modeling and decision-making purposes. Soil moisture data are obtained from NASA’s soil moisture active passive (SMAP) mission radiometer as an interpolated product at 9 km gridded resolution. This study implements a soil moisture downscaling algorithm that was developed based on the relationship between daily temperature change and average soil moisture under varying vegetation conditions. It applies a look-up table using global land data assimilation system (GLDAS) soil moisture and surface temperature data, and advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) and land surface temperature (LST). MODIS LST and NDVI are used to obtain downscaled soil moisture estimates. These estimates are then used to enhance the spatial resolution of soil moisture estimates from SMAP 9 km to 1 km. Soil moisture estimates at 1 km resolution are able to provide detailed information on the spatial distribution and pattern over the regions being analyzed. Higher resolution soil moisture data are needed for practical applications and modelling in large watersheds with limited in situ data, like in the Lower Mekong River Basin (LMB) in Southeast Asia. The 1 km soil moisture estimates can be applied directly to improve flood prediction and assessment as well as drought monitoring and agricultural productivity predictions for large river basins.

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COMPARISON OF AGRICULTURAL SITUATION OF INDIA FOR TWO YEARS (2017 AND 2018) USING VARIOUS DROUGHT ASSESSMENT INDICATORS DURING SOUTH WEST MONSOON SEASON IN INDIA

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-3-w6-499-2019 ◽

2019 ◽

Vol XLII-3/W6 ◽

pp. 499-505

Author(s):

S. Saxena ◽

K. Choudhary ◽

R. Saxena ◽

A. Rabha ◽

P. Tahlani ◽

...

Keyword(s):

Remote Sensing ◽

Soil Moisture ◽

Climatic Factors ◽

Monsoon Season ◽

District Level ◽

Agricultural Drought ◽

Drought Assessment ◽

South West Monsoon ◽

Dry Spell ◽

Sown Area

Abstract. Agricultural drought is concerned with the soil moisture deficiency in relation to meteorological droughts and climatic factors and their impacts on agricultural production and economic profitability. Present study is based on two years kharif seasons i.e. 2018 and 2017, comparison of drought assessment using remote sensing, soil moisture indices, rainfall and crop sown area as per the New Drought Manual, December, 2016. The drought assessment was carried out at district and sub-district level under National Agricultural Drought Assessment and Monitoring System (NADAMS) project. Drought trigger-1 is checked with rainfall deviation and dry spell. During 2017, the final drought categories were defined on the basis of Rainfall, Moisture and Vegetation Condition Index. During 2018, the final district level drought categories are defined using 3 indicators, where sown area upto end of August was also considered. Based on the approach defined in the New Drought Manual, analysis was carried out at district level for 17 major agricultural drought prone states of the country. State wise Rainfall deviation, dry spell, NDVI/NDWI situation was compared for both the years. Remote sensing based vegetation and water indices are important impact indicator out of 4 because it gives an idea of crop profile and surface wetness condition respectively. Thus the present study is an attempt to compare the drought situation in kharif season of years 2017 and 2018 on the basis of different impact indicators.

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