Drought Spatiotemporal Characteristics Based on a Vegetation Condition Index in Erbil, Kurdistan Region, Iraq

Drought is a complex phenomenon that has severe impacts on the environment. Vegetation and its conditions are very sensitive to drought effects. This study aimed to monitor and assess the drought severity and its relationships to some ecological variables in ten districts of Erbil Governorate (Kurdistan Region), Iraq, throughout 20 years (1998-2017). The results revealed that droughts frequently hit Erbil throughout the study period. The Landsat time-series- based on Vegetation Condition Index (VCI) significantly correlated with precipitation, Digital Elevation Model (DEM), and latitude. Extreme VCI-based drought area percentages were recorded in 1999, 2000, 2008, and 2011 by 43.4%, 67.9%, 43.3%, and 40.0%, respectively. The highest crop yield reduction in the study area occurred mainly in 2000, 2008, and 2012 due to low precipitation rates. These results reveal the capability of the VCI for drought characteristics and highlighting relationships with some ecological variables, which provide vital information to the decision-makers, environmental, and economic sectors.

Drought assessment for kharif rice using standardized precipitation index (SPI) and vegetation condition index (VCI)

The monthly weather data for 31 years from 1985-2015 was used to analyze the extent of meteorological drought using standardized precipitation index (SPI) over Allahabad, Kanpur and Lucknow. MODIS NDVI data from 2000-2015 was used for monitoring of agricultural drought through NDVI based vegetation condition index (VCI) for all the three districts. The monthly SPI and VCI values from July to October were correlated with productivity index (PI) of kharif rice.Both the indices (SPI and VCI) were positively correlated with PI for all the districts. In Allahabad SPI and VCI during September month showed a significant correlation (0.70**& 0.61*) while in Kanpur VCI during October and SPI of July and August were significantly correlated with PI of kharif Rice. The multiple regression equation developed for predicting kharif rice PI in Allahabad, Kanpur and Lucknow districts explained 69 to 76 per cent variabilityin PI.

Comparison of Multi-Year Reanalysis, Models, and Satellite Remote Sensing Products for Agricultural Drought Monitoring over South Asian Countries

The substantial reliance of South Asia (SA) to rain-based agriculture makes the region susceptible to food scarcity due to droughts. Previously, most research on SA has emphasized the meteorological aspects with little consideration of agrarian drought impressions. The insufficient amount of in situ precipitation data across SA has also hindered thorough investigation in the agriculture sector. In recent times, models, satellite remote sensing, and reanalysis products have increased the amount of data. Hence, soil moisture, precipitation, terrestrial water storage (TWS), and vegetation condition index (VCI) products have been employed to illustrate SA droughts from 1982 to 2019 using a standardized index/anomaly approach. Besides, the relationships of these products towards crop production are evaluated using the annual national production of barley, maize, rice, and wheat by computing the yield anomaly index (YAI). Our findings indicate that MERRA-2, CPC, FLDAS (soil moisture), GPCC, and CHIRPS (precipitation) are alike and constant over the entire four regions of South Asia (northwest, southwest, northeast, and southeast). On the other hand, GLDAS and ERA5 remain poor when compared to other soil moisture products and identified drought conditions in regions one (northwest) and three (northeast). Likewise, TWS products such as MERRA-2 TWS and GRACE TWS (2002–2014) followed the patterns of ERA5 and GLDAS and presented divergent and inconsistent drought patterns. Furthermore, the vegetation condition index (VCI) remained less responsive in regions three (northeast) and four (southeast) only. Based on annual crop production data, MERRA-2, CPC, FLDAS, GPCC, and CHIRPS performed fairly well and indicated stronger and more significant associations (0.80 to 0.96) when compared to others. Thus, the current outcomes are imperative for gauging the deficient amount of data in the SA region, as they provide substitutes for agricultural drought monitoring.

Drought Analysis for the Seyhan Basin with NDVI and VCI Vegetation Indices

Various drought indices have been developed to monitor the drought, which is one of the results of climate change and mitigates its adverse effects on water resources, especially agriculture. Vegetation indices determined by remote sensing have been the subject of many studies in recent years and shed light on drought risk management. This study is examined in the Seyhan River Basin, a basin with Turkey’s considerable population density counts and is situated south of the country. Normalized Difference Vegetation Index (NDVI) and Vegetation Condition Index (VCI) are the most widely used vegetation indices and are very useful because they give results only based on satellite images. This study examined the Seyhan Basin by using satellite data in which the vegetation transformation occurring due to the decline of agricultural and forest areas was also seen. An increase in drought frequency was detected in the Seyhan Basin using NDVI and VCI indices. It was determined that climate change and drought increased with a linear uptrend. It is recommended that decision-makers should take the necessary measures by considering the drought risk maps and that long-term drought management plans should be made and implemented.

Temporal analysis of drought coverage in a watershed area using remote sensing spectral indexes

The development of several time series analysis programs using satellite images has provided many applications based on resources from geostatistics field. Currently, the use of statistical tests applied to vegetation indexes has enabled the analysis of different natural phenomena, such as drought events in watershed areas. The objective of this article is to provide a comparative analysis between NDVI and EVI vegetation index data made available by MOD13Q1 project of MODIS sensor for drought mapping using vegetation condition index (VCI) in the Serra Azul stream sub-basin, MG. The methodology adopted the Cox-Stuart statistical test for seasonality analysis and Pearson's linear correlation to verify the influence of different indexes on delimitation of drought in a watershed. The results indicated the NDVI vegetation index as more efficient than EVI in spatial characterization of studied watershed region, mainly in identification of seasonality. The VCI proved to be highly feasible for monitoring drought in study period between 2013 and 2018, allowing the effective delimitation of drought conditions in the Serra Azul stream sub-basin. In addition, the effectiveness of MODIS sensor data in characterizing drought events that affected the study area was proven.

PEMANTAUAN DAN MITIGASI TINGKAT POTENSI BENCANA KEKERINGAN DI KOTA DUMAI

Kekeringan lahan yang terjadi saat musim kemarau memberikan dampak buruk bagi vegetasi, salah satunya tanah Gambut sangat sensitif terhadap kenaikan suhu menimbulkan kebakaran hutan. Kota Dumai menjadi salah satu daerah yang sering mengalami kebakaran hutan dan lahan, efek terjadi kebakaran ini menjadikan lahan tersebut memiliki kualitas yang menurun meliputi fisika, kimia, dan adanya erosi tanah. Dalam tulisan ini, kami memantau adanya peningkatan dan penuruan dalam beberapa kategori kekeringan lahan. Adapun parameter yang digunakan seperti vegetation health index (VHI), vegetation condition index (VCI), dan temperature condition index (TCI) pada tahun 2013 dan tahun 2018. Hasil penelitian menjelaskan wilayah kekeringan mengalami kenaikan total selama periode pengamatan sebesar 23.119 hektar lahan, dengan kategori tanpa kekeringan terjadi penurunan seluas 23.119 ha, kemudian kategori kekeringan ringan terjadi peningkatan seluas19.510 ha, selanjutnya kategori kekeringan sedang terjadi peningkatan seluas 13.444 ha, lalu kategori kekeringan parah terjadi penurunan seluas 9.163 ha, dan kekeringan ekstrim mengalami penurunan seluas 672 ha. hal ini sejalan dengan terjadinya kenaikan pada suhu tahun 2013 mencapai 38 ºC kemudian mengalami peningkatan menjadi 47,53ºC di tahun 2018 yang sedang mengalami kebakaran hutan dan lahan

Assessing Agricultural Vulnerability to Drought in a Heterogeneous Environment: A Remote Sensing-Based Approach

Agriculture is one of the fundamental economic activities in most countries; however, this sector suffers from various natural hazards including flood and drought. The determination of drought-prone areas is essential to select drought-tolerant crops in climate sensitive vulnerable areas. This study aims to enhance the detection of agricultural areas with vulnerability to drought conditions in a heterogeneous environment, taking Bangladesh as a case study. The normalized difference vegetation index (NDVI) and land cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images have been incorporated to compute the vegetation index. In this study, a modified vegetation condition index (mVCI) is proposed to enhance the estimation of agricultural drought. The NDVI values ranging between 0.44 to 0.66 for croplands are utilized for the mVCI. The outcomes of the mVCI are compared with the traditional vegetation condition index (VCI). Precipitation and crop yield data are used for the evaluation. The mVCI maps from multiple years (2006–2018) have been produced to compute the drought hazard index (DHI) using a weighted sum overlay method. The results show that the proposed mVCI enhances the detection of agricultural drought compared to the traditional VCI in a heterogeneous environment. The “Aus” rice-growing season (sown in mid-March to mid-April and harvested in mid-July to early August) receives the highest average precipitation (>400 mm), and thereby this season is less vulnerable to drought. A comparison of crop yields reveals the lowest productivity in the drought year (2006) compared to the non-drought year (2018), and the DHI map presents that the north-west region of Bangladesh is highly vulnerable to agricultural drought. This study has undertaken a large-scale analysis that is important to prioritize agricultural zones and initiate development projects based on the associated level of vulnerability.

Effects of Droughts on Vegetation Condition and Ecosystem Service Delivery in Data-Poor Areas: A Case of Bobirwa Sub-District, Limpopo Basin and Botswana

Understanding the effects of droughts on vegetation and ecosystem services (ES) is important for climate change adaptation. However, drought occurrence varies across space and time. We examined drought dynamics and impacts on vegetation and ES in the semi-arid Limpopo Basin of Botswana. Weather station precipitation, remotely sensed normalized difference vegetation index (NDVI) and participatory mapping exercises provided data for the analyses. Results show that between 1980 and 2015, rainfall anomaly indices of potential drought years ranged between −4.38 and −0.12. The longest spell of below-average rainfall occurred between 1992 and 1996. On average, drought events lasted for 1.9 years and recurred every 2.3 years. Although the overall drought frequency was 3.7 times in every 5 years, drought prevalence increased to 50%, 60% and 70% between 1981–1990, 1991–2000, and 2001–2010, respectively. The wet season average vegetation condition index between 2000 and 2015 revealed the occurrence of severe-to-extreme droughts in 2002–2003, 2005, 2008–2009 and 2012–2013 and light-to-moderate droughts in 2004, 2006–2007 and 2011, giving a drought prevalence of 73.3%. The increased frequency and severity of droughts is diminishing natural vegetation, crop productivity and several provisioning ES through moisture stress and drought-induced agricultural expansions. There exists an urgent need for smallholder irrigation development in Bobirwa sub-district to improve crop productivity and reduce the drought-induced conversion of woodlands to agriculture.

Assessment of Drought across Kaduna State, Nigeria Using MODIS Dataset

Introduction: Kaduna state in Nigeria is located within the Guinea Savannah of the African Continent. The state is susceptible to desertification and the risks of drought. Aim and Objectives: The aim of the study is to access magnitude and extent drought in Kaduna state Nigeria using MODIS dataset. Study Design: The study examined people’s perception; precipitation data and satellite imageries for assessing and monitoring drought. Descriptive statistics were used to present the some of the data. Methodology: The dataset were analysed using Idrisi remote sensing and Geographical Information (GIS) softwares to determine the aerial coverage of drought and its magnitude. Furthermore, run off were determined, VCI calculated, cross-tabulation were made from classified imageries and the views of respondents were also sought to complement the analysis. Results: The study revealed that there have been several episodes of drought in Kaduna state within the period under review. Runoff decreased from 72.50mm in 2000 to just about 48.00mm in 2009. The study also revealed that there is a positive relationship (0.72) between rainfall and vegetation vigour/biomas in the state. Similarly, vegetation condition index (VCI) revealed a value 10.2% indicating a severe drought in the state based on Kogans drought classification. Conclusion: The study concluded that both rainfall and vegetation/biomas vigour are generally decreasing suggesting a strong positive correlation value of 0.71. While a better high spatial resolution satellite dataset be utilised for further studies in this direction, the study also recommends that individuals and organisations be encouraged to engage in the habit of tree planting in order to curtail the decrease in vegetation biomass in the state. In addition, research and extension services should be strongly promoted in order to develop particular breed of seeds that can survive the drought in this period of food insecurity.