scholarly journals Temporal and Spatial Comparison of Agricultural Drought Indices from Moderate Resolution Satellite Soil Moisture Data over Northwest Spain

2017 ◽  
Vol 9 (11) ◽  
pp. 1168 ◽  
Author(s):  
Miriam Pablos ◽  
José Martínez-Fernández ◽  
Nilda Sánchez ◽  
Ángel González-Zamora
2020 ◽  
Author(s):  
Maria Jose Escorihuela ◽  
Pere Quintana Quintana-Seguí ◽  
Vivien Stefan ◽  
Jaime Gaona

<p>Drought is a major climatic risk resulting from complex interactions between the atmosphere, the continental surface and water resources management. Droughts have large socioeconomic impacts and recent studies show that drought is increasing in frequency and severity due to the changing climate.</p><p>Drought is a complex phenomenon and there is not a common understanding about drought definition. In fact, there is a range of definitions for drought. In increasing order of severity, we can talk about: meteorological drought is associated to a lack of precipitation, agricultural drought, hydrological drought and socio-economic drought is when some supply of some goods and services such as energy, food and drinking water are reduced or threatened by changes in meteorological and hydrological conditions. 
</p><p>A number of different indices have been developed to quantify drought, each with its own strengths and weaknesses. The most commonly used are based on precipitation such as the precipitation standardized precipitation index (SPI; McKee et al., 1993, 1995), on precipitation and temperature like the Palmer drought severity index (PDSI; Palmer 1965), others rely on vegetation status like the crop moisture index (CMI; Palmer, 1968) or the vegetation condition index (VCI; Liu and Kogan, 1996). Drought indices can also be derived from climate prediction models outputs. Drought indices base on remote sensing based have traditionally been limited to vegetation indices, notably due to the difficulty in accurately quantifying precipitation from remote sensing data. The main drawback in assessing drought through vegetation indices is that the drought is monitored when effects are already causing vegetation damage. In order to address drought in their early stages, we need to monitor it from the moment the lack of precipitation occurs.</p><p>Thanks to recent technological advances, L-band (21 cm, 1.4 GHz) radiometers are providing soil moisture fields among other key variables such as sea surface salinity or thin sea ice thickness. Three missions have been launched: the ESA’s SMOS was the first in 2009 followed by Aquarius in 2011 and SMAP in 2015.</p><p>A wealth of applications and science topics have emerged from those missions, many being of operational value (Kerr et al. 2016, Muñoz-Sabater et al. 2016, Mecklenburg et al. 2016). Those applications have been shown to be key to monitor the water and carbon cycles. Over land, soil moisture measurements have enabled to get access to root zone soil moisture, yield forecasts, fire and flood risks, drought monitoring, improvement of rainfall estimates, etc.</p><p>The advent of soil moisture dedicated missions (SMOS, SMAP) paves the way for drought monitoring based on soil moisture data. Initial assessment of a drought index based on SMOS soil moisture data has shown to be able to precede drought indices based on vegetation by 1 month (Albitar et al. 2013).</p><p>In this presentation we will be analysing different drought episodes in the Ebro basin using both soil moisture and vegetation based indices to compare their different performances and test the hypothesis that soil moisture based indices are earlier indicators of drought than vegetation ones.</p>


Geography ◽  
2020 ◽  
Author(s):  
Woonsup Choi

Drought is a natural disaster that has plagued human society throughout history. However, the meaning of drought varies by perspective and academic discipline, and the cause of drought is difficult to pinpoint. Despite the variation in its meaning, drought generally refers to the condition of an abnormally low amount of water for a given climate. Here the water can be precipitation, streamflow, soil moisture, groundwater, reservoir storage, and the like, but the lack of precipitation is a precursor for other types of drought. The lack of precipitation is often associated with anomalous atmospheric conditions such as atmospheric-circulation anomalies, higher-than-normal temperatures, and lower-than-normal relative humidity. Sea surface temperature anomalies may lead to sustained atmospheric-circulation anomalies. Drought defined as a lack of precipitation is often called meteorological or climatological drought. Other drought types can be classified within the context of the affected sectors, such as agricultural, hydrological, and socioeconomic drought. Agricultural drought generally refers to a lack of soil moisture, and hydrological drought refers to a lack of surface and subsurface water (e.g., streamflow and groundwater). Socioeconomic drought hampers human activities such as industry or water supply. As meteorological drought persists, other types of drought can follow. Such definitions of drought are regarded as conceptual definitions, but operational definitions are also necessary for quantitative understanding and management of drought events. Operational definitions use quantitative indices to identify the occurrence and characteristics of drought events such as onset, duration, termination, and deficit volume of drought. Much of existing drought research concerns developing, revising, and applying drought indices to investigate spatial and temporal patterns of drought at various geographical scales. Drought research has progressed along several directions, such as causes of drought, characteristics of drought events, impacts, and mitigation. Each of these directions is represented by the works cited in this article.


2015 ◽  
Vol 16 (3) ◽  
pp. 1397-1408 ◽  
Author(s):  
Hongshuo Wang ◽  
Jeffrey C. Rogers ◽  
Darla K. Munroe

Abstract Soil moisture shortages adversely affecting agriculture are significantly associated with meteorological drought. Because of limited soil moisture observations with which to monitor agricultural drought, characterizing soil moisture using drought indices is of great significance. The relationship between commonly used drought indices and soil moisture is examined here using Chinese surface weather data and calculated station-based drought indices. Outside of northeastern China, surface soil moisture is more affected by drought indices having shorter time scales while deep-layer soil moisture is more related on longer index time scales. Multiscalar drought indices work better than drought indices from two-layer bucket models. The standardized precipitation evapotranspiration index (SPEI) works similarly or better than the standardized precipitation index (SPI) in characterizing soil moisture at different soil layers. In most stations in China, the Z index has a higher correlation with soil moisture at 0–5 cm than the Palmer drought severity index (PDSI), which in turn has a higher correlation with soil moisture at 90–100-cm depth than the Z index. Soil bulk density and soil organic carbon density are the two main soil properties affecting the spatial variations of the soil moisture–drought indices relationship. The study may facilitate agriculture drought monitoring with commonly used drought indices calculated from weather station data.


2018 ◽  
Vol 10 (8) ◽  
pp. 1265 ◽  
Author(s):  
Nazmus Sazib ◽  
Iliana Mladenova ◽  
John Bolten

Soil moisture is considered to be a key variable to assess crop and drought conditions. However, readily available soil moisture datasets developed for monitoring agricultural drought conditions are uncommon. The aim of this work is to examine two global soil moisture datasets and a set of soil moisture web-based processing tools developed to demonstrate the value of the soil moisture data for drought monitoring and crop forecasting using the Google Earth Engine (GEE). The two global soil moisture datasets discussed in the paper are generated by integrating the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) missions’ satellite-derived observations into a modified two-layer Palmer model using a one-dimensional (1D) ensemble Kalman filter (EnKF) data assimilation approach. The web-based tools are designed to explore soil moisture variability as a function of land cover change and to easily estimate drought characteristics such as drought duration and intensity using soil moisture anomalies and to intercompare them against alternative drought indicators. To demonstrate the utility of these tools for agricultural drought monitoring, the soil moisture products and vegetation- and precipitation-based products were assessed over drought-prone regions in South Africa and Ethiopia. Overall, the 3-month scale Standardized Precipitation Index (SPI) and Normalized Difference Vegetation Index (NDVI) showed higher agreement with the root zone soil moisture anomalies. Soil moisture anomalies exhibited lower drought duration, but higher intensity compared with SPIs. Inclusion of the global soil moisture data into the GEE data catalog and the development of the web-based tools described in the paper enable a vast diversity of users to quickly and easily assess the impact of drought and improve planning related to drought risk assessment and early warning. The GEE also improves the accessibility and usability of the earth observation data and related tools by making them available to a wide range of researchers and the public. In particular, the cloud-based nature of the GEE is useful for providing access to the soil moisture data and scripts to users in developing countries that lack adequate observational soil moisture data or the necessary computational resources required to develop them.


Water ◽  
2021 ◽  
Vol 13 (19) ◽  
pp. 2777
Author(s):  
Tao Cheng ◽  
Siyang Hong ◽  
Bensheng Huang ◽  
Jing Qiu ◽  
Bikui Zhao ◽  
...  

Drought is the costliest disaster around the world and in China as well. Northeastern China is one of China’s most important major grain producing areas. Frequent droughts have harmed the agriculture of this region and further threatened national food security. Therefore, the timely and effective monitoring of drought is extremely important. In this study, the passive microwave remote sensing soil moisture data, i.e., the SMOS soil moisture (SMOS-SM) product, was compared to several in situ meteorological indices through Pearson correlation analysis to assess the performance of SMOS-SM in monitoring drought in northeastern China. Then, maps based on SMOS-SM and in situ indices were created for July from 2010 to 2015 to identify the spatial pattern of drought distributions. Our results showed that the SMOS-SM product had relatively high correlation with in situ indices, especially SPI and SPEI values of a nine-month scale for the growing season. The drought patterns shown on maps generated from SPI-9, SPEI-9 and sc-PDSI were also successfully captured using the SMOS-SM product. We found that the SMOS-SM product effectively monitored drought patterns in northeastern China, and this capacity would be enhanced when field capacity information became available.


2013 ◽  
Vol 781-784 ◽  
pp. 2353-2356
Author(s):  
Jing Wen Xu ◽  
Shuang Liu ◽  
Jun Fang Zhao ◽  
Jin Lun Han ◽  
Peng Wang

Soil moisture plays an important role in agricultural drought monitoring. However, the traditional observed soil moisture data from meteorological stations has not been able to meet the demands for large-scale drought monitoring temporally and spatially. The microwave remote sensing is a new effective way for obtaining near surface soil moisture. The temporal and spatial variation in soil moisture in arid regions in northern China is examined based on the soil moisture data retrieved from AMSR-E (Advanced Microwave Scanning Radiometer-EOS), with which the observed soil moisture data at 10 cm depth from meteorological stations are compared. The results show that there is a small change in soil moisture with seasons for the central and west areas, while a large change for the east areas of the study region and the soil moisture in summer and autumn is greater than that in spring and winter. And that it decreases from southeast to northwest spatially, as is agree with the spatial distribution of precipitation in the study area. Moreover, there is a great difference in spatial distribution between the soil moisture retrieved from AMSR-E and the observed soil moisture data from meteorological stations for the central and west areas, while a small difference for the east areas of the study region.


Water ◽  
2019 ◽  
Vol 11 (7) ◽  
pp. 1375 ◽  
Author(s):  
Ali Ajaz ◽  
Saleh Taghvaeian ◽  
Kul Khand ◽  
Prasanna H. Gowda ◽  
Jerry E. Moorhead

A new agricultural drought index was developed for monitoring drought impacts on agriculture in Oklahoma. This new index, called the Soil Moisture Evapotranspiration Index (SMEI), estimates the departure of aggregated root zone moisture from reference evapotranspiration. The SMEI was estimated at five locations across Oklahoma representing different climates. The results showed good agreement with existing soil moisture-based (SM) and meteorological drought indices. In addition, the SMEI had improved performance compared to other indices in capturing the effects of temporal and spatial variations in drought. The relationship with crop production is a key characteristic of any agricultural drought index. The correlations between winter wheat production and studied drought indices estimated during the growing period were investigated. The correlation coefficients were largest for SMEI (r > 0.9) during the critical crop growth stages when compared to other drought indices, and r decreased by moving from semi-arid to more humid regions across Oklahoma. Overall, the results suggest that the SMEI can be used effectively for monitoring the effects of drought on agriculture in Oklahoma.


2020 ◽  
Vol 22 (4) ◽  
pp. 937-956
Author(s):  
Odai Al Balasmeh ◽  
Richa Babbar ◽  
Tapas Karmaker

Abstract Wadi Shueib catchment in Jordan is a water stress area and climate change is creating a further deficiency in precipitation, streamflow, and soil moisture; which are a deterrent to agriculture production in the area. In order to analyze the drought-like situation in the area, a hybrid drought index (HDI) has been developed considering the combined effect of these three variables. Fuzzy analytical hierarchy process (F-AHP) and entropy weight methods were carried out to develop a hybrid drought index (HDI) which combines meteorological, hydrological, and agricultural drought indices based on precipitation, streamflow, and soil moisture data in the area. The wavelet transform (WT) with cross wavelet (XCT) and wavelet coherence (WTC) were applied to investigate the interaction and the relations between the HDI index, drought indices, and large-scale sunspot activity Niño3.4 index. The results show that HDI can easily capture the trend of the drought-like conditions in the area based on the available data. The trend analysis of HDI revealed an increasing trend in the drought incidences in the near future. The study can be used as an early alarm for drought in the area, which can be helpful in the decision-making process towards water resources planning and management in the future.


2020 ◽  
Vol 12 (7) ◽  
pp. 2801
Author(s):  
Yuan Li ◽  
Yi Dong ◽  
Dongqin Yin ◽  
Diyou Liu ◽  
Pengxin Wang ◽  
...  

Monitoring agricultural drought is important to food security and the sustainable development of human society. In order to improve the accuracy of soil moisture and winter wheat yield estimation, drought monitoring effects of optical drought index data, meteorological drought data, and passive microwave soil moisture data were explored during individual and whole growth periods of winter wheat in 2003–2011, taking Henan Province of China as the research area. The model of drought indices and relative meteorological yield of winter wheat in individual and whole growth periods was constructed based on multiple linear regression. Results showed a higher correlation between Moderate-Resolution Imaging Spectroradiometer (MODIS) drought indices and 10 cm relative soil moisture (RSM10) than 20 cm (RSM20) and 50 cm (RSM50). In the whole growth period, the correlation coefficient (R) between vegetation supply water index (VSWI) and RSM10 had the highest correlation (R = −0.206), while in individual growth periods, the vegetation temperature condition index (VTCI) was superior to the vegetation health index (VHI) and VSWI. Among the meteorological drought indices, the 10-day, 20-day, and 30-day standard precipitation evapotranspiration indices (SPEI1, SPEI2, and SPEI3) were all most relevant to RSM10 during individual and whole growth periods. RSM50 and SPEI3 had a higher correlation, indicating that deep soil moisture was more related to drought on a long time scale. The relationship between Advanced Microwave Scanning Radiometer for EOS soil moisture (AMSR-E SM) and VTCI was stable and significantly positive in individual and whole growth periods, which was better compared to VHI and VSWI. Compared with the drought indices and the relative meteorological yield in the city, VHI had the best monitoring effect during individual and whole growth periods. Results also showed that drought occurring at the jointing–heading stage can reduce winter wheat yield, while a certain degree of drought occurring at the heading–milk ripening stage can increase the yield. In the whole growth period, the combination of SPEI1, SPEI2, and VHI had the best performance, with a coefficient of determination (R2) of 0.282 with the combination of drought indices as the independent variables and relative meteorological yield as the dependent variable. In the individual growth period, the model in the later growth period of winter wheat performed well, especially in the returning green–jointing stage (R2 = 0.212). Results show that the combination of multiple linear drought indices in the whole growth period and the model in the returning green–jointing period could improve the accuracy of winter wheat yield estimation. This study is helpful for effective agricultural drought monitoring of winter wheat in Henan Province.


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