scholarly journals Impact of precipitation and increasing temperatures on drought trends in eastern Africa

2021 ◽  
Vol 12 (1) ◽  
pp. 17-35
Author(s):  
Sarah F. Kew ◽  
Sjoukje Y. Philip ◽  
Mathias Hauser ◽  
Mike Hobbins ◽  
Niko Wanders ◽  
...  
Keyword(s):  
Soil Moisture ◽  
A Priori ◽  
Agricultural Drought ◽  
Eastern Africa ◽  
Precipitation Trend ◽  
Crop Failure ◽  
Evaporative Demand ◽  
Clear Trend ◽  
Moisture Analysis ◽  
The Impact

Abstract. In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe. However, the link between droughts and climate change is not sufficiently understood. Here we investigate trends in long-term agricultural drought and the influence of increasing temperatures and precipitation deficits. Using a combination of models and observational datasets, we studied trends, spanning the period from 1900 (to approximate pre-industrial conditions) to 2018, for six regions in eastern Africa in four drought-related annually averaged variables: soil moisture, precipitation, temperature, and evaporative demand (E0). In standardized soil moisture data, we found no discernible trends. The strongest influence on soil moisture variability was from precipitation, especially in the drier or water-limited study regions; temperature and E0 did not demonstrate strong relations to soil moisture. However, the error margins on precipitation trend estimates are large and no clear trend is evident, whereas significant positive trends were observed in local temperatures. The trends in E0 are predominantly positive, but we do not find strong relations between E0 and soil moisture trends. Nevertheless, the E0 trend results can still be of interest for irrigation purposes because it is E0 that determines the maximum evaporation rate. We conclude that until now the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and we recommend that any soil moisture analysis be supplemented by an analysis of precipitation deficit.

scholarly journals Impact of precipitation and increasing temperatures on drought in eastern Africa

2019 ◽  
Author(s):  
Sarah F. Kew ◽  
Sjoukje Y. Philip ◽  
Mathias Hauser ◽  
Mike Hobbins ◽  
Niko Wanders ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Potential Evapotranspiration ◽  
A Priori ◽  
Agricultural Drought ◽  
Eastern Africa ◽  
Precipitation Trend ◽  
Crop Failure ◽  
Evaporative Demand ◽  
Clear Trend ◽  
The Impact

Abstract. In eastern Africa droughts can cause crop failure and lead to food insecurity. With increasing temperatures, there is an a priori assumption that droughts are becoming more severe, however, the link between droughts and climate change is not sufficiently understood. In the current study we focus on agricultural drought and the influence of high temperatures and precipitation deficits on this. Using a combination of models and observational datasets, we studied trends in six regions in eastern Africa in four drought-related annually averaged variables – soil moisture, precipitation, temperature and, as a measure of evaporative demand, potential evapotranspiration (PET). In standardized soil moisture data, we find no discernible trends. Precipitation was found to have a stronger influence on soil moisture variability than temperature or PET, especially in the drier, or water-limited, study regions. The error margins on precipitation-trend estimates are however large and no clear trend is evident. We find significant positive trends in local temperatures. However, the influence of these on soil moisture annual trends appears limited as evaporation is water limited. The trends in PET are predominantly positive, but we do not find strong relations between PET and soil moisture trends. Nevertheless, the PET-trend results can still be of interest for irrigation purposes as it is PET that determines the maximum evaporation rate. We conclude that, until now, the impact of increasing local temperatures on agricultural drought in eastern Africa is limited and recommend that any soil moisture analysis be supplemented by analysis of precipitation deficit.

scholarly journals Spatio–temporal Assessment of Drought in Ethiopia and the Impact of Recent Intense Droughts

2019 ◽  
Vol 11 (15) ◽  
pp. 1828 ◽  
Author(s):  
Yuei-An Liou ◽  
Getachew Mehabie Mulualem
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Pearson Correlation ◽  
Early Warning Systems ◽  
Heat Index ◽  
Trend Test ◽  
Northwestern Part ◽  
Precipitation Trend ◽  
Spatio Temporal ◽  
The Impact

The recent droughts that have occurred in different parts of Ethiopia are generally linked to fluctuations in atmospheric and ocean circulations. Understanding these large-scale phenomena that play a crucial role in vegetation productivity in Ethiopia is important. In view of this, several techniques and datasets were analyzed to study the spatio–temporal variability of vegetation in response to a changing climate. In this study, 18 years (2001–2018) of Moderate Resolution Imaging Spectroscopy (MODIS) Terra/Aqua, normalized difference vegetation index (NDVI), land surface temperature (LST), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) daily precipitation, and the Famine Early Warning Systems Network (FEWS NET) Land Data Assimilation System (FLDAS) soil moisture datasets were processed. Pixel-based Mann–Kendall trend analysis and the Vegetation Condition Index (VCI) were used to assess the drought patterns during the cropping season. Results indicate that the central highlands and northwestern part of Ethiopia, which have land cover dominated by cropland, had experienced decreasing precipitation and NDVI trends. About 52.8% of the pixels showed a decreasing precipitation trend, of which the significant decreasing trends focused on the central and low land areas. Also, 41.67% of the pixels showed a decreasing NDVI trend, especially in major parts of the northwestern region of Ethiopia. Based on the trend test and VCI analysis, significant countrywide droughts occurred during the El Niño 2009 and 2015 years. Furthermore, the Pearson correlation coefficient analysis assures that the low NDVI was mainly attributed to the low precipitation and water availability in the soils. This study provides valuable information in identifying the locations with the potential concern of drought and planning for immediate action of relief measures. Furthermore, this paper presents the results of the first attempt to apply a recently developed index, the Normalized Difference Latent Heat Index (NDLI), to monitor drought conditions. The results show that the NDLI has a high correlation with NDVI (r = 0.96), precipitation (r = 0.81), soil moisture (r = 0.73), and LST (r = −0.67). NDLI successfully captures the historical droughts and shows a notable correlation with the climatic variables. The analysis shows that using the radiances of green, red, and short wave infrared (SWIR), a simplified crop monitoring model with satisfactory accuracy and easiness can be developed.

scholarly journals LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the CONtiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables

2018 ◽  
Author(s):  
Clément Albergel ◽  
Simon Munier ◽  
Aymeric Bocher ◽  
Bertrand Bonan ◽  
Yongjun Zheng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Initial Conditions ◽  
The United States ◽  
Agricultural Drought ◽  
Reference Network ◽  
Surface Model ◽  
Area Index ◽  
Medium Range Weather Forecast ◽  
The Impact

LDAS-Monde, an offline land data assimilation system with global capacity, is applied over the CONtiguous US (CONUS) domain to enhance monitoring accuracy for water and energy states and fluxes. LDAS-Monde ingests satellite-derived Surface Soil Moisture (SSM) and Leaf Area Index (LAI) estimates to constrain the Interactions between Soil, Biosphere, and Atmosphere (ISBA) Land Surface Model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the Total Runoff Integrating Pathways (CTRIP) continental hydrological system (ISBA-CTRIP). LDAS-Monde is forced by the ERA-5 atmospheric reanalysis from the European Center For Medium Range Weather Forecast (ECMWF) from 2010 to 2016 leading to a 7-yr, quarter degree spatial resolution offline reanalysis of Land Surface Variables (LSVs) over CONUS. The impact of assimilating LAI and SSM into LDAS-Monde is assessed over North America, by comparison to satellite-driven model estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project, and upscaled ground-based observations of gross primary productivity from the FLUXCOM project. Also, taking advantage of the relatively dense data networks over CONUS, we also evaluate the impact of the assimilation against in-situ measurements of soil moisture from the USCRN network (US Climate Reference Network) are used in the evaluation, together with river discharges from the United States Geophysical Survey (USGS) and the Global Runoff Data Centre (GRDC). Those data sets highlight the added value of assimilating satellite derived observations compared to an open-loop simulation (i.e. no assimilation). It is shown that LDAS-Monde has the ability not only to monitor land surface variables but also to forecast them, by providing improved initial conditions which impacts persist through time. LDAS-Monde reanalysis has a potential to be used to monitor extreme events like agricultural drought, also. Finally, limitations related to LDAS-Monde and current satellite-derived observations are exposed as well as several insights on how to use alternative datasets to analyze soil moisture and vegetation state.

Analysis of Soil Moisture Characteristics with the Application of Soil in Civil Engineering in 2011 in Gaoyao

2012 ◽  
Vol 568 ◽  
pp. 31-34 ◽  
Author(s):  
Ling Li Fan
Keyword(s):  
Regression Analysis ◽  
Soil Moisture ◽  
Civil Engineering ◽  
Dominant Role ◽  
Soil Humidity ◽  
Moisture Analysis ◽  
Sunshine Hours ◽  
Moisture Variation ◽  
The Impact ◽  
Soil Moisture Variation

The data of soil moisture in layer of 0-50cm, precipitation, temperature, sunshine hours and cloudiness in 2011 in Gaoyao were analyzed. The results showed that the soil moisture was vertical uniformly distributed in Gaoyao. The soil humidity was larger in an overcast day than in the others. It was relatively smaller in a sunny day than in the others, because of the impact of solar radiation and temperature on soil moisture. Three layer soil moisture variations were almost synchronous, but the variation amplitude of soil moisture in 0-10cm layer was biggest, and 30-50cm soil moisture variation was least. Regression analysis showed that, precipitation and cloudiness played a dominant role on soil moisture variation, while temperature and sunshine had little effect on the soil moisture. Analysis of soil moisture characteristics with the application of soil was useful to civil engineering in Gaoyao.

scholarly journals AGRICULTURAL DROUGHT AND SOIL MOISTURE ANALYSIS USING SATELLITE IMAGE BASED INDICES

2019 ◽  
Vol XLII-3/W6 ◽  
pp. 507-514
Author(s):  
S. Sreekesh ◽  
N. Kaur ◽  
S. R. Sreerama Naik
Keyword(s):  
Soil Moisture ◽  
Satellite Image ◽  
Condition Index ◽  
Agricultural Drought ◽  
Drought Severity ◽  
Severe Drought ◽  
Landsat Images ◽  
Moisture Conditions ◽  
The Impact ◽  
Meteorological Droughts

<p><strong>Abstract.</strong> The deficiency in rainfall leads to meteorological droughts. Its manifestations are visible both in the vegetation cover and soil moisture. The present study assessed the characteristics of agricultural drought following meteorological droughts. The study also assessed the severity of meteorological droughts and their manifestation on the agriculture and soil moisture in a semi-arid area. The study has been carried out for the Malaprabha sub-basin which partly covers three districts of North Interior Karnataka, India. India Meteorological Department’s (IMD) criteria have been used to identify the drought years, and its severity has been assessed through the Standard Precipitation Index (SPI). The IMD’s monthly rainfall data were used to identify the drought years and periods for the region. Among the drought years, the mild, moderate, and severe drought along with deficit and excess rainfall years were considered to assess and characterize the soil moisture conditions and the agricultural drought. The satellite image based indices for these selected years were constructed to determine the soil moisture conditions and the agricultural drought severity. The Temperature-Vegetation Dryness Index (TVDI) was used to determine the soil moisture conditions. The indices employed to determine the agriculture drought are NDVI, Thermal Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI). These satellite-based indices were calculated using the Landsat images of the selected drought and non-drought years. The results showed that the seasonal and annual drought are frequent in the study area. There are spatial and temporal variations in the drought years and their severity. The satellite-based indices clearly indicate the spatial variation in the agriculture droughts and its intensity. It has been found that the impact of drought on agriculture has significantly reduced due to the development of well-irrigation in the sub-basin. VHI is more appropriate in determining the agricultural drought and its characteristics.</p>

scholarly journals Anatomy of the 2018 agricultural drought in The Netherlands using in situ soil moisture and satellite vegetation indices

2020 ◽  
Author(s):  
Joost Buitink ◽  
Anne M. Swank ◽  
Martine van der Ploeg ◽  
Naomi E. Smith ◽  
Harm-Jan F. Benninga ◽  
...  
Keyword(s):  
Soil Moisture ◽  
The Netherlands ◽  
Moisture Content ◽  
Land Surface ◽  
Soil Moisture Content ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Summer Drought ◽  
The Impact

Abstract. The soil moisture status near the land surface is a key determinant of vegetation productivity. The critical soil moisture content determines the transition from an energy-limited to a water-limited evapotranspiration regime. This study quantifies the critical soil moisture content by comparison of in situ soil moisture profile measurements of the Raam and Twenthe networks in the Netherlands, with two satellite derived vegetation indices (NIRv and VOD) during the 2018 summer drought. The critical soil moisture content is obtained through a piece-wise linear correlation of the NIRv and VOD anomalies with soil moisture on different depths of the profile. This nonlinear relation reflects the observation that negative soil moisture anomalies develop weeks before the first reduction in vegetation indices. Furthermore, the inferred critical soil moisture content was found to increase with observation depth and this relationship is shown to be linear and distinctive per area, reflecting the tendency of roots to take up water from deeper layers when drought progresses. The relations of non-stressed towards water-stressed vegetation conditions on distinct depths are derived using Remote Sensing, enabling the parameterization of reduced evapotranspiration and its effect on GPP in models to study the impact of a drought on the carbon cycle.

scholarly journals Anatomy of the 2018 agricultural drought in the Netherlands using in situ soil moisture and satellite vegetation indices

2020 ◽  
Vol 24 (12) ◽  
pp. 6021-6031
Author(s):  
Joost Buitink ◽  
Anne M. Swank ◽  
Martine van der Ploeg ◽  
Naomi E. Smith ◽  
Harm-Jan F. Benninga ◽  
...  
Keyword(s):  
Soil Moisture ◽  
The Netherlands ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Vegetation Indices ◽  
Agricultural Drought ◽  
Summer Drought ◽  
Near Infrared Reflectance ◽  
The Impact

Abstract. The soil moisture status near the land surface is a key determinant of vegetation productivity. The critical soil moisture content determines the transition from an energy-limited to a water-limited evapotranspiration regime. This study quantifies the critical soil moisture content by comparison of in situ soil moisture profile measurements of the Raam and Twente networks in the Netherlands, with two satellite-derived vegetation indices (near-infrared reflectance of terrestrial vegetation, NIRv, and vegetation optical depth, VOD) during the 2018 summer drought. The critical soil moisture content is obtained through a piece-wise linear correlation of the NIRv and VOD anomalies with soil moisture on different depths of the profile. This non-linear relation reflects the observation that negative soil moisture anomalies develop weeks before the first reduction in vegetation indices: 2–3 weeks in this case. Furthermore, the inferred critical soil moisture content was found to increase with observation depth, and this relationship is shown to be linear and distinctive per area, reflecting the tendency of roots to take up water from deeper layers when drought progresses. The relations of non-stressed towards water-stressed vegetation conditions on distinct depths are derived using remote sensing, enabling the parameterization of reduced evapotranspiration and its effect on gross primary productivity in models to study the impact of a drought on the carbon cycle.

scholarly journals A new agricultural drought index considering the irrigation water demand and water supply availability

2020 ◽  
Vol 104 (3) ◽  
pp. 2409-2429
Author(s):  
Zikang Xing ◽  
Miaomiao Ma ◽  
Yongqiang Wei ◽  
Xuejun Zhang ◽  
Zhongbo Yu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Irrigation Water ◽  
Water Demand ◽  
Drought Index ◽  
Agricultural Drought ◽  
Drought Event ◽  
Moisture Condition ◽  
Irrigation Water Demand ◽  
Moisture Variation ◽  
The Impact

Abstract Agricultural drought has a tremendous impact on crop yields and economic development under the context of global climate change. As an essential component of water balance in irrigated areas, artificial irrigation, which is not widely incorporated into agricultural drought indices in previous studies. Therefore, an irrigation water deficit index (IWDI) based on the estimation of irrigation water demand and supply is proposed. The performance of the new index was compared with the Soil Moisture Anomaly Percentage Index (SMAPI) over the upstream of the Zi River basin (UZRB). The results indicated the IWDI is highly correlated with precipitation, runoff, and potential evapotranspiration, combined with a more comprehensive moisture condition than the previous agricultural drought index. Due to the consideration of crop growth process and farmland spatial distribution, the proposed index showed a significant advantage in stressing drought conditions of agricultural concentration area and eliminating the impact of invalid soil moisture drought of non-growing seasons. Furthermore, the drought condition identified by the new index presented a good agreement with the historical drought event that occurred in 2013.7–8, which accurately reproduced the soil moisture variation and vegetation growth dynamics.

Model computations on the impact of changing climate on natural regeneration of Scots pine in Finland

1995 ◽  
Vol 25 (6) ◽  
pp. 929-942 ◽  
Author(s):  
Seppo Kellomäki ◽  
Hannu Väisänen
Keyword(s):  
Soil Moisture ◽  
Scots Pine ◽  
Natural Regeneration ◽  
Diameter Growth ◽  
Temperature Elevation ◽  
Evaporative Demand ◽  
Seed Crop ◽  
Wide Spacing ◽  
The Impact ◽  
Growth Of Seedlings

Based on model computations, the regeneration of Scots pine (Pinussylvestris L.) in southern (60°N) and northern (66°N) Finland was studied in relation to an elevating temperature. The temperature elevation increased flowering and the subsequent seed crop, particularly in northern Finland, with a decrease in the frequency of zero crops. In southern Finland, the number of seedlings produced by each seed crop increased when applying wide spacing, but decreased when applying narrow spacing of parent trees. This was due to a decrease in soil moisture induced by the increasing evaporative demand and transpiration of the parent trees. In northern Finland, temperature elevation substantially increased the success of regeneration in terms of seedlings produced by each seed crop regardless of the spacing of parent trees. In terms of the density of seedling stands and the height and diameter growth of seedlings, the establishment of a seedling stand within a given period of time was substantially improved under the improved temperature conditions in both southern and northern Finland.

scholarly journals LDAS-Monde Sequential Assimilation of Satellite Derived Observations Applied to the Contiguous US: An ERA-5 Driven Reanalysis of the Land Surface Variables

2018 ◽  
Vol 10 (10) ◽  
pp. 1627 ◽  
Author(s):  
Clement Albergel ◽  
Simon Munier ◽  
Aymeric Bocher ◽  
Bertrand Bonan ◽  
Yongjun Zheng ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Land Surface ◽  
The United States ◽  
Agricultural Drought ◽  
Land Data Assimilation ◽  
Land Data Assimilation System ◽  
The Impact ◽  
Data Assimilation System ◽  
Assimilation System

Land data assimilation system (LDAS)-Monde, an offline land data assimilation system with global capacity, is applied over the CONtiguous US (CONUS) domain to enhance monitoring accuracy for water and energy states and fluxes. LDAS-Monde ingests satellite-derived surface soil moisture (SSM) and leaf area index (LAI) estimates to constrain the interactions between soil, biosphere, and atmosphere (ISBA) land surface model (LSM) coupled with the CNRM (Centre National de Recherches Météorologiques) version of the total runoff integrating pathways (CTRIP) continental hydrological system (ISBA-CTRIP). LDAS-Monde is forced by the ERA-5 atmospheric reanalysis from the European Center for Medium Range Weather Forecast (ECMWF) from 2010 to 2016 leading to a seven-year, quarter degree spatial resolution offline reanalysis of land surface variables (LSVs) over CONUS. The impact of assimilating LAI and SSM into LDAS-Monde is assessed over North America, by comparison to satellite-driven model estimates of land evapotranspiration from the Global Land Evaporation Amsterdam Model (GLEAM) project, and upscaled ground-based observations of gross primary productivity from the FLUXCOM project. Taking advantage of the relatively dense data networks over CONUS, we have also evaluated the impact of the assimilation against in situ measurements of soil moisture from the USCRN (US Climate Reference Network), together with river discharges from the United States Geological Survey (USGS) and the Global Runoff Data Centre (GRDC). Those data sets highlight the added value of assimilating satellite derived observations compared with an open-loop simulation (i.e., no assimilation). It is shown that LDAS-Monde has the ability not only to monitor land surface variables but also to forecast them, by providing improved initial conditions, which impacts persist through time. LDAS-Monde reanalysis also has the potential to be used to monitor extreme events like agricultural drought. Finally, limitations related to LDAS-Monde and current satellite-derived observations are exposed as well as several insights on how to use alternative datasets to analyze soil moisture and vegetation state.

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