scholarly journals Application of Improved Remotely Sensed Drought Severity Index Based on Soil Moisture Product in Inner Mongolia

SOLA ◽  
2020 ◽  
Vol 16 (0) ◽  
pp. 259-264
Author(s):  
Lusha Wang ◽  
Ayumi Kotani ◽  
Takafumi Tanaka ◽  
Takeshi Ohta
Water ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 1526 ◽  
Author(s):  
Ye Zhu ◽  
Yi Liu ◽  
Xieyao Ma ◽  
Liliang Ren ◽  
Vijay Singh

Focusing on the shortages of moisture estimation and time scale in the self-calibrating Palmer drought severity index (scPDSI), this study proposed a new Palmer variant by introducing the Variable Infiltration Capacity (VIC) model in hydrologic accounting module, and modifying the standardization process to make the index capable for monitoring droughts at short time scales. The performance of the newly generated index was evaluated over the Yellow River Basin (YRB) during 1961–2012. For time scale verification, the standardized precipitation index (SPI), and standardized precipitation evapotranspiration index (SPEI) at a 3-month time scale were employed. Results show that the new Palmer variant is highly correlated with SPI and SPEI, combined with a more stable behavior in drought frequency than original scPDSI. For drought trend detection, this new index is more inclined to reflect comprehensive moisture conditions and reveals a different spatial pattern from SPI and SPEI in winter. Besides, two remote sensing products of soil moisture and vegetation were also employed for comparison. Given their general consistent behaviors in monitoring the spatiotemporal evolution of the 2000 drought, it is suggested that the new Palmer variant is a good indicator for monitoring soil moisture variation and the dynamics of vegetation growth.


2021 ◽  
Vol 4 (2) ◽  
pp. 14-31
Author(s):  
Polina Lemenkova

Abstract This paper focuses on the environment of Ethiopia, a country highly sensitive to droughts severely affecting vegetation. Vegetation monitoring of Ethiopian Highlands requires visualization of environmental parameters to assess droughts negatively influencing agricultural sustainable management of crops. Therefore, this study presented mapping of several climate and environmental variables including Palmer Drought Severity Index (PDSI). The data were visualized and interpreted alongside the topographic data to evaluate the environmental conditions for vegetation. The datasets included WorldClim and GEBCO and Digital Chart of the World (DCW). Research has threefold objectives: i) environmental mapping; ii) technical cartographic scripting; iii) data processing. Following variables were visualized on seven new maps: 1) topography; 2) soil moisture; 3) T °C minimum; 4) T °C maximum; 5) Wind speed; 6) Precipitation; 7) Palmer Drought Severity Index (PDSI). New high-resolution thematic environmental maps are presented and the utility of GMT for mapping multi-source datasets is described. With varying degrees of soil moisture (mean value of 15.0), min T°C (−1.8°C to 24°C), max T°C (14.4°C to 40.2°C) and wind speed (0.1 to 6.1 m/s), the maps demonstrate the variability of the PDSI fields over the country area (from −11.7 to 2.3) induced by the complex sum of these variables and intensified by the topographic effects notable over the Ethiopian Highlands which can be used for vegetation analysis. The paper presents seven new maps and contributes to the environmental studies of Ethiopia.


2013 ◽  
Vol 94 (1) ◽  
pp. 83-98 ◽  
Author(s):  
Qiaozhen Mu ◽  
Maosheng Zhao ◽  
John S. Kimball ◽  
Nathan G. McDowell ◽  
Steven W. Running

Regional drought and flooding from extreme climatic events are increasing in frequency and severity, with significant adverse ecosocial impacts. Detecting and monitoring drought at regional to global scales remains challenging, despite the availability of various drought indices and widespread availability of potentially synergistic global satellite observational records. The authors have developed a method to generate a near-real-time remotely sensed drought severity index (DSI) to monitor and detect drought globally at 1-km spatial resolution and regular 8-day, monthly, and annual frequencies. The new DSI integrates and exploits information from current operational satellite-based terrestrial evapo-transpiration (ET) and vegetation greenness index [normalized difference vegetation index (NDVI)] products, which are sensitive to vegetation water stress. Specifically, this approach determines the annual DSI departure from its normal (2000–11) using the remotely sensed ratio of ET to potential ET (PET) and NDVI. The DSI results were derived globally and captured documented major regional droughts over the last decade, including severe events in Europe (2003), the Amazon (2005 and 2010), and Russia (2010). The DSI corresponded favorably (correlation coefficient r = 0.43) with the precipitation-based Palmer drought severity index (PDSI), while both indices captured similar wetting and drying patterns. The DSI was also correlated with satellite-based vegetation net primary production (NPP) records, indicating that the combined use of these products may be useful for assessing water supply and ecosystem interactions, including drought impacts on crop yields and forest productivity. The remotely sensed global terrestrial DSI enhances capabilities for nearreal-time drought monitoring to assist decision makers in regional drought assessment and mitigation efforts, and without many of the constraints of more traditional drought monitoring methods.


2006 ◽  
Vol 45 (10) ◽  
pp. 1362-1375 ◽  
Author(s):  
Kingtse C. Mo ◽  
Muthuvel Chelliah

Abstract A 32-km high-resolution modified Palmer drought severity index (MPDSI) based on the National Centers for Environmental Prediction (NCEP) North American Regional Reanalysis (RR) from 1979 to 2004 is presented. The assumptions of Palmer, such as the water balance equation, the difference between observed precipitation and the climatologically expected precipitation over the maximum conditions, and the changes of the index as a function of the current index, are preserved. Many deficiencies of the original PDSI are eliminated by taking fields directly from the RR or by making better estimates. For example, fields such as potential evapotranspiration, evaporation, runoff, total soil moisture, and soil moisture change in a given month are obtained directly from the RR. The potential recharge is defined as the total soil moisture needed to reach the maximum total soil moisture at each grid point for each calendar month. The potential precipitation is defined as the maximum precipitation at each grid point for a given calendar month. The underground volumetric soil moisture includes both frozen and liquid form. Therefore, the contribution of snowmelt is taken into account inexplicitly. The questionable assumptions of two-layer soil model and the available soil moisture capacity are no longer needed. Overall, the MPDSI, when averaged over a large area and long time, often resembles the traditional PDSI based on the Palmer formula and the climate-division data. The MPDSI obeys Gaussian distribution, and so it can also be used to assess the potential for floods. Together with a consistent suite of soil moisture, surface energy, and atmospheric terms from the RR, the MPDSI can be used to monitor and diagnose drought and floods.


Sign in / Sign up

Export Citation Format

Share Document