Geo-spatial analysis of drought in The Gambia using multiple models

Climate change has made The Gambia vulnerable to drought hazard. Variability and negative trends in rainfall quantity and mid-season dry spells mainly attributed to the impacts of climate change. The inadequacy in hydrometeorological information puts the agricultural sector at a high risk which employs over 70% of the population. The aim of this study was to establish the intensity and spatiotemporal pattern of drought in The Gambia from 2000 to 2020 using multiple drought indices. Rainfall data, satellite images, and government policy documents were analyzed to determine the state of drought in The Gambia. Rainfall data, using Standardized Precipitation Index (SPI) and Precipitation Anomaly Percentage (PAP) were calculated and interpolated, and satellite images were processed using Vegetation Condition Index (VCI) to determine drought intensity and spatial distribution. The findings revealed that drought exists in The Gambia at moderate levels of SPI values (− 1.00 to − 1.49), (35% of PAP), and VCI of no drought intensity of more than 35%. The most drought prone areas in The Gambia are North Bank Region and Eastern parts of country in both north and south of The Gambia River banks. Recommendations of adaptation practice both on-farm and off-farm such as damming and economic diversification was drawn from other parts of the world, to reduce the negative effects of drought hazard in The Gambia.


Introduction
In recent years, a noticeable variability has been observed in global hydro-climate patterns. This is due mainly to unsustainable human activities that has contributed to the unpredictability of climate change pattern (Sharafati et al. 2019;Jarju et al. 2021;Dehghannik et al. 2021). This variability in climatic pattern significantly increased the impact of hydro-climatic hazards such as drought, hurricanes, floods and heat waves hence decision-makers across the globe are concern. Gurain-Sherman (2012) opined that drought is complex; the duration of drought, the time it occurs as per the growth stage of crops, the characteristics of the particular soil affected, the temperature at the time, farmers' choices of crops are all factors that influence the drought intensity/severity and how it may eventually impact food production. Orimoloye et al. (2021) stated that the harshness of drought may comprise reduction in the quantity and quality of potable water, compromise food security, cause an outbreak of hunger-related diseases and in severe cases food scarcity.
The drought moves slowly, its beginning and termination have been noted to be difficult to predict, and drought repercussions can endure for years after the event has ended (Wilhite and Glantz 1985;Komuscu 1999;Dai 2011;Carrão et al. 2016;Achberger 2020). Due to their slow onset, vast spatial extent and prolonged duration, droughts belong to the world's most catastrophic natural calamities, the consequences of which have been observed across Africa (Ahmadalipour and Moradkhani 2018;Winkler et al. 2017). Disasters that are climate-related such as flood, storm, sea-level rise, drought and other extreme weather events accounts for 91% of all disasters worldwide between 1998 and 2017 (CRED and UNISDR 2018). Of this, 4.8% accounts for drought within the ten years period affecting about 1.5 billion people. Although prevalence in terms of occurrence is lower, drought affects large populations than any other disaster. "In years when serious droughts occur in major food-producing regions, crop losses can affect the global food supply and food prices. This occurred in 2008, when Australia, a major global wheat producer, lost substantial production because of severe drought" (Gurian-Sherman 2012). Himanshu et al. (2015) opined that drought is considered to be the most intricate but least understood of all natural hazards, considering the large number of people its impacts affect. Causes of drought is attributed to two main factors (Smith and Petley 2013;Eldho 2014), these are physical and human factors. Typically, physical causes of drought are initiated by atmospheric circulation and weather systems that resulted in lower precipitation and/or higher evaporation than the "normal" of a region and can be directly triggered by human activities (Sierra-Soler et al. 2016;Bi et al. 2021). Teleconnections, which means the "linkages between climate anomalies occurring at long distances apart", sea-surface temperature anomalies (SSTAs), and descending air due to El Nino conditions (ENSO) are all implicated in the causes of drought phenomenon (Smith and Petley 2013). Human factors attributed to causes of drought range from bad agricultural practices, deforestation, excessive irrigation, soil erosion, climate change due to emission of GHGs, urbanization and so on. Major droughts are centred in semiarid regions of the world such as the Great Plains of USA, West African Sahel, East and South Africa, India and Australia (Wilhite 2012;Smith and Petley 2013). In developing countries, (Smith and Petley 2013) drought is best described as a "complex emergency" due to the myriad issues that makes vulnerability to drought impact severe. Climate drivers such as precipitation changes and temperature trends are commonly used at a spatiotemporal scale to observe the effects of climate change (Menzel et al. 2020;Islam et al. 2021). Climate has a significant impact on vegetation dynamics and growth. It has an impact on soil moisture, nutrients, microbial activity, and atmospheric conditions, affecting plant physiology and growth as a result (Islam et al. 2021).

Adaptation strategies
Although drought hazards begin slowly and have severe results, the impacts of drought catastrophes can be mitigated with careful planning and mitigation measures. According to the UNEP's Adaptation Gap Report (2020), the benefits of investing in adaptation outweigh the costs. A $1.8 trillion investment in early warning systems, climate resilient infrastructure, improved dryland agriculture, global mangrove protection, and resilient water resources, according to the Global Commission on Adaptation, could result in $7.1 trillion in avoided costs and non-monetary social and environmental benefits. To achieve disaster mitigation plan components, the following strategies can be used: forecast, monitoring, impact assessment, and reaction (Orimoloye et al. 2021). The monitoring of meteorological droughts is the most important part of drought avoidance. However, it is exceedingly difficult to detect, forecast, and track meteorological droughts and their spatial fluctuation (Dai et al. 2020). According to Javadinejad et al. (2020), a hazardous environment does not imply or correlate with harm and vulnerability. A lack of resilience and mitigation techniques, as well as a lack of knowledge and perception, all contribute to the population's suffering. According to Quraishi (2018), drought adaptation measures include both on-farm and off-farm activities. These programmes are intended to strengthen farmers' resistance to the effects of drought on agricultural products and farmers' livelihoods. On-farm resilience adaption options include, but are not limited to, postponing planting date, modifying cropping system, applying mulch, gap filling where prior crop germination failed, resowing, and crop irrigation/dripping system application. Income diversification, business/trade, migration, non-agricultural labour, and asset sale are examples of off-farm fundamental adaptation techniques. Ngwaru (2021) observed several adaptation practises such as rainwater harvesting in tanks and ponds to be used during dry spells or drought; trainings on soil and water conservation strategies; and the cultivation of drought-tolerant cereals such as pearl millet, sorghum, and finger millet that can be stored for longer periods without spoiling. Another key adaptation method was public awareness campaigns, which educate residents for future natural disasters by developing community-based disaster risk reduction initiatives. According to him, this allows for the identification of local priority levels, which leads to the development of initiatives that help to the mitigation of drought impacts.
Farmers in The Gambia have implemented many drought adaptation tactics, including the use of improved crop varieties such as NERICA (New Rice for Africa) and early maize; crop rotation; water saving techniques; water diversion; and the use of natural and artificial fertilizers. Furthermore, mixed farming is utilized. Poultry farming and animal husbandry have been fostered in various rural communities, particularly in the North Bank Region and Central River Region, where the drought phenomenon is common. This is done to lessen the likelihood of a bad crop in the event of low rainfall or a drought (Har 2019; GoTG/UNCCD 2020). These methods and improved crop types are utilized to attenuate and develop population resilience (Bagagnan et al. 2019;Segnon et al. 2021).
Three rainfall periods were experienced in the Sahel region between 1950 and 2020. The first period (1950)(1951)(1952)(1953)(1954)(1955)(1956)(1957)(1958)(1959)(1960)(1961)(1962)(1963)(1964)(1965)(1966)(1967)(1968)(1969) was characterized by positive rainfall, having abundant rainfall. The second period was between 1970 and 1993 when a negative (anomaly) was experienced. This period witnessed the long and persistent Sahelian drought which causes havoc on humans and livestock. The last period was between 1994 to-date. This period experienced neither persistent heavy rainfall nor continuous drought but variability of heavy rainfall years and dry periods (Segnon et al. 2021). According to GoTG/UNDP (2015) and Carré et al. (2019), historical climate records in The Gambia indicate a shift in the rainfall pattern. From 1950 to 2000, annual rainfall amounts have decreased by about 30%. This decrease has been evident in the reduction in the length of the rainy season and also the quantity of rainfall amounts recorded in the month of August, particularly during the period 1968 to 1985, and in 2002. The erratic rainfall pattern has caused some impacts on the farming system such as reduction in the length of growing season and the additional and frequent mid-season dry-spell also causes drought conditions for farming purposes even during normal rainfall conditions. The Gambia is very sensitive to loss and damage from climate change, notably from climate extreme events such as droughts, as predicted long-term trends in drought and rainfall variability are projected (GoTG 2020).
Many indicators have been developed to detect and monitor meteorological droughts like Standardized Runoff Index (SRI), Standardized Precipitation Index (SPI), standardized precipitation evapotranspiration index (SPEI), Palmer drought severity index (PDSI), effective drought index (EDI) and reconnaissance drought index (RDI) (Anshuka et al. 2019); Normalized Difference Vegetation Index (NDVI), Crop Moisture Index (CMI) Standardized Precipitation Index (SPI) and Surface Water Supply Index (SWSI) are most preferred indices for agricultural drought monitoring, forecasting and water resources management (Himanshu et al 2015); Vegetation Condition Index (VCI), Vegetation Health Index (VHI), Land Surface Temperature (LST), Temperature Condition Index (TCI) are satellite-based assessment indices to assess cumulative moisture, temperature, and vegetation health (Jiang et al. 2021). This paper used SPI, PAP and VCI. The former two indicators are mainly based on precipitation data which is easily accessible and computation is easy. VCI was used to complement the precipitation data in order to highlight the impact of rainfall on vegetation quality. It is said to be more effective in portraying drought impact on vegetation compared to the commonly used NDVI. The main objectives of this study are to determine the state of drought in The Gambia in terms of spatial extent and temporal variation and highlight local adaptation measures against drought hazard in The Gambia.

The study area
The Gambia is the smallest country in mainland Africa having a total land area of 11,300 Km 2 (4388 sq. miles) of this, 1,300 Km 2 is water bodies. Relatively, located on the extreme western-most coast of West Africa and surrounded by Republic of Senegal north, east, and south and the Atlantic Ocean in the West (Fig. 1). Geographically, extends from 13° to 14° North latitude and 13º to 17º West longitude Rivera et al. 2020). The Gambia has a tropical climate with distinct dry and wet season. The dry season is longer starts at mid-October and lasts till mid-June. During this period, the weather is generally warm and dry with average temperature varying from 70°F (21°C) to 80°F (27°C) with a relative humidity varying between 30 and 60%. The rainy season starts in mid-June and lasts till mid-October with August being the wettest month. Temperature is generally hot and can reach as high as 41°C (105°F). Annual rainfall is between 700 and 1000 mm (NEA 2014; MoFEA 2020). It was reported on the World Bank Climate Change Knowledge Portal on The Gambia 1991-2020 that an increased annual mean temperature of 1.0 °C is experienced in The Gambia since 1960s at an average rate of 0.21 °C per decade. October, November and December experienced the most rapid rate of increase at 0.32 °C per decade. Also, linear trends indicate that wet season (July to September) rainfall in The Gambia has decreased significantly between 1960 and 2006 at an average rate of 8.8mm per month per decade. Bah et al. (2019) reported a 27% reduction in annual rainfall since 1951. The length of the rainy season has also reduced with and increasing variability in inter-annual rainfall. In The Gambia, over 70% of the inhabitants are employed in the agricultural field. About 90% of the rural people are directly or indirectly dependent of farming activities for livelihood.

Data acquisition
Since the main objective of this paper work is to assess and analyse the state of drought in The Gambia, the data collected was entirely from secondary sources; research articles, government policy documents formed the review of literature. NASA Power-Data, website: https:// power. larc. nasa. gov/ data-access-viewer which is an open-access web portals was utilized to obtain average monthly precipitation data of 21 years . Precipitation data was acquired from the Department of Fisheries and Water Resources in The Gambia but due to several missing data, satellite data of precipitation from NASA Power-Data Access Viewer was preferred. Nine(9) weather stations from strategic location across the country were selected for collecting precipitation data. These data was utilized to calculate Standardized Precipitation Index (SPI) and Precipitation Anomaly Percentage (PAP).
MODIS (Moderate Resolution Imagery Spectroradiometer) MOD13Q1 V-6 images from United States Geological Survey (USGS) website (https//:www. ladsw eb. modaps. eosdis. nasa. gov) was used to retrieve satellite images of The Gambia (study area) from 2000 to 2020 on a five year interval (2000, 2005, 2010, 2015 and 2020) for the months of June, July, August and September to calculate and obtain Vegetation Condition Index (VCI) values. These months were used as they are relevant in the rainfall period of the country, thus a better time period to assess the impact of rainfall on vegetation health condition. The research process was described in (Fig. 2)

Data processing
Three drought indices were used and rainfall and satellite data were processed with the used of Microsoft Excel and GIS software. First, Standardized Precipitation Index (SPI) was used to process the yearly average rainfall data of June, July, August, and September from 2000 to 2020 using MS Excel. Kamble et al. (2019) establishes the usefulness of using SPI in identifying meteorological and agricultural droughts in India. According to Achberger (2020), the use of SPI is an assumption of the significant influence of precipitation on drought than other variables such as temperature, evapotranspiration, and according to her, these variables are also been proven to influence the intensity of drought. Eq. (1) was used to calculate SPI using Microsoft excel sheet: Where: Xi, is the initial observed data, Xm is the mean or average values of the initially observed values and Sx is the standard deviation. The standard deviation was calculated using Eq. (2): The derived SPI results with negative values indicate drought condition while positive values indicate no drought condition. The results were categorized into five (7)  Precipitation Anomaly Percentage (PAP) was another index used to process rainfall data to determine the drought situation. PAP is a drought monitoring metric developed to displays precipitation as a percentage of the long-term average or normal. PAP might intuitively represent precipitation anomaly. In meteorology, it is often used to assess drought occurrences (Fang et al. 2010). Eqs. (3) and (4) were used to calculate PAP.
(1) Where Pa is PAP, P is the rainfall of a certain period, p' is the long-term average rainfall of the study period, n is 1 to 21, i = 1,2,3…n. The period in this paper is 21 (n=21) i.e., from 2000 to 2020.
Vegetation Condition Index (VCI) was the third index used in processing satellite images. The VCI value is expressed as a percentage range from 1 to 100. A score between 50 and 100% shows no drought (normal vegetation state), a value between 50 and 35% suggests a mild drought situation, and a value less than 35% indicates a severe drought condition (Eyoh et al. 2019). MODIS satellite images (MOD13Q1 from USGS for the months of June, July, August and September from 2000 to 2020 on a five years interval (2000, 2005, 2010, 2015 and 2020) was used to calculate VCI for the Gambia. The MODIS V-6 (MOD13Q1) satellite image is already an NDVI enhanced image. It is used by adjusting the scale factor (0.0001) after which the values are processed using raster calculator. The minimum and maximum NDVI were calculated using raster calculator. Eq.5 and 6 were used to obtain VCI values.

Results, analysis and discussion
Precipitation data and satellite images collected from NASA Power-Data Access Viewer and MODIS V-6 (MOD13Q1) from USGS website respectively. The data were processed using three (3) indices: Standardized Precipitation Index (SPI), Precipitation Anomaly Percentage (PAP), and Vegetation Condition Index (VCI) to establish the state (spatial extent and intensity) of drought condition in the study area. The results are described below.

Results based on standardized precipitation index (SPI) values
According to SPI data, The Gambia has never had a nation-wide extreme drought ( − 2) situation throughout the whole country at any point during the evaluation period . Individual meteorological stations recorded SPI levels that were judged to be severe drought conditions (Fig. 3). For example, based on the aggregate SPI value of these meteorological stations, SPI values of − 2.23 and − 2.04 were recorded in Banjul, the Capital City, and Fatoto in 2018 and 2001, respectively, becoming the driest years. During the research period, the wettest year was 2007, with an overall (4)   (2000-2010) where drought conditions do not prevail in at least one meteorological station. The year 2000 was the most severely affected, with severe drought conditions in the eastern part of the study region. The year 2002 was followed by a mild drought in the eastern part of the study region. The droughts of 2000 and 2002 were important because they damaged areas believed to be the breadbasket of the country (Central River Region and Upper River Region). In 2003, the north-western half of the nation (Kerewan Met Station) was the only section of the study with drought (moderate) conditions. It was only in this year (2003) when drought affected Kerewan meteorological station without affecting any station in the eastern parts of the study area in that decade but low rainfall was recognized throughout the study area.
During the second decade (2011-2020), three meteorological stations stand out as drought prone locations in order of frequency: Kerewan, Fatoto, and Banjul. In comparison to the first decade, the second decade experienced higher rainfall. There were about six to seven years when there was little or no drought in the study region, but not consecutive years, confirming the unpredictability of the drought situation. In terms of total rainfall quantity recorded, the year 2020 was the wettest, followed by 2019, 2017, 2013, and 2014.

Results based on precipitation anomaly percentage (PAP) values
Precipitation data was processed using PAP index and the results were categorized into seven (7) classes to determine the drought condition in terms of intensity and spatial extent on an annual bases during the study period. The year 2002 was the driest with a PAP ≤ 56% considered to be a severe drought condition. This was followed by the years 2001,2000,2011,2016,2007,2019,2004,2006,2013 and 2014 all recording values ranging from severe to moderate drought conditions in decreasing order of intensity. The wettest year based on PAP values was 2020 (PAP ≥ 53%). This was followed by 2008, 2009, 2005, 2017, 2015, 2018, 2010, 2003, and 2012 in descending order of PAP values. Overall, based on the PAP values there were no extremity in both dry and wet conditions but a characteristic variation in inter-annual rainfall pattern exist based on data collected during the study period . Figure 4 shows the annual drought and no-drought conditions based on PAP values below.

Results based on vegetation condition index (VCI) values
The VCI on a five-year interval (2000, 2005, 2010, 2015, and 2020) were categorized into extreme drought, severe drought, moderate drought, no drought, and wet conditions. The driest year in terms of percentage area with extreme and severe drought condition was in 2010 totalling 44% (39% and 15% respectively). The year 2005 also showed a high drought condition of 32% for extreme drought and 7% for severe drought condition. The year 2015 had an extreme drought condition of 30% and a severe drought condition of 6%. The year 2000 had an extreme drought condition of 28% and a severe drought condition of 5%. The year 2020 had only 12% of extreme drought condition and 3% of severe drought condition. Based on vegetation condition index, 2020 had the largest area with healthy vegetation (77%), this was followed by the year 2000 with 55%, then 2015 (45%), 2005 (41%) and 2010 having 27% of wet condition. The year with the highest dry condition was 2010 with an overall drought condition covering 66% (extreme 29%, severe 15%, and moderate 17%) of the total land area of the study area. These values are represented using a histogram (Fig. 5) below.  1 3 In terms of the spatial distribution of drought conditions based on VCI, Kerewan, in the north and majority of the eastern sections of the study area, primarily Fatoto, Basse, Kaur, Kuntaur, and Janjangbureh, were afflicted in 2005, 2010, and 2015). In terms of vegetative conditions, the central areas of the research region, which included the meteorological stations of Kaur, Kuntaur, Janjangbureh, and Basse, were most affected by drought conditions in 2000. 2010 had the most widespread drought conditions over the whole study region, with the exception of a few locations in the north-eastern section of Janjangbureh meteorological station. The vegetation condition in 2020 was exceptional over the whole study region, with just a few patchy areas at the Brikama and Kerewan meteorological stations. In general, the northern parts of the country had poorer vegetative conditions than the southern parts. During the research period, there was no discernible trend in the regional distribution of drought intensity and spatial extent depending on vegetation state. There is heterogeneity in both geographical and temporal aspects.

Analysis of crop production data 2000 to 2018
The crop production data was collected from the Planning Department of the Ministry of Agriculture for the period under review (2000 to 2020). The data for 2018/2019, 2019/2020 seasons were not available. A considerable variation can be observed temporary as well as between the major crops produced. The area cultivated was assessed based on hectares in (000) and the production is assessed in metric tons (000). Form this data, the yield was calculated.

Climate of The Gambia
Based on Koppen's climate classification, the climate of The Gambia can be divided into two classes; the Tropical wet and dry or Savannah Climate (Aw) which covers almost over 90% of the country. Here, precipitation exceeds 1000mm and rains fall only in summer. The average temperature in this climate is greater than 18 degrees centigrade. It has an extended dry season during winter.
The other type is the Dry Semi-arid climate (BSh). This is a grassland climate covering the middle northern tip of the country. This part of the country receives precipitation but potential evaporation and transpiration exceeds precipitation. To understand the climate of this region clearly, refer to the map of Senegambia region below.

Discussion
Rainfall data and satellite images were collected from NASA Power-Data Access Viewer and MODIS V-6 (MOD13Q1) from USGS website respectively. The analyses of drought was based on three (3) drought indices: Standardized Precipitation Index (SPI), Precipitation Anomaly Percentage (PAP), and Vegetation Condition Index (VCI) to establish the state (spatial extent and intensity) of drought condition in the study area. The former two indices are based on rainfall data collected from nine meteorological stations across the country while the later is based on satellite images. Both SPI and PAP indices examine drought condition of the whole study period on a year-to-year basis while VCI is on a five year interval of the study period . The processed rainfall data were categorized in to seven classes and interpolated using Inverse Distance Weighted (IDW) on Arc-GIS. Also, a detailed search of government and non-government reports as well as research articles was done to explore what drought and its impacts are, and what has been done to mitigate these impacts.
The findings from the analysis of rainfall and satellite data revealed that drought existed in The Gambia during the study period. The years with widespread spatial extent of drought conditions were 2000,2002,2010,2012 and 2018 based on results from all the indices used. These results are in conformity with the findings of GoTG/UNCCD (2020) document on historical drought years of 2002 and 2012. Har (2019) also reported the existence of drought in The Gambia in 2018 with severe low rainfall and dry spells affecting many farming communities. Similarly, Precipitation Anomaly Percentage also revealed 2002 as the driest year in The Gambia and 2020 as the wettest year. What clearly stands out in all the indices used to determine drought condition during the study period was the variability in rainfall pattern hence a variability in drought condition during the study period.
Year(s) of drought were followed by year(s) of normal rainfall and generally rainfall of between normal and moderate wet condition. This result was in concurrence with GoTG/ UNCCD (2020) document: National Drought Plan which reported that since 1994, the rainfall pattern shows variability and largely attributed this cause to climate change impacts. It was reported that years before 1970, The Gambia received rainfall in large quantities and regularly. The period between 1970 and 1994 was characterized by severe low rainfall and drought conditions.
The findings revealed that The Gambia is vulnerable to drought conditions. Rainfall is generally moderate with years of low and or severe dry spells during the growing seasons. Due to these factors, climate induced drought remained certain in the future as temperatures continue to increase. The indices used in this research did not reveal years of dry spells but literature (Har 2019; GoTG/UNCCD) reported dry spells in various years within the study period. Dry spells can be very detrimental to crops especially when it happened at the beginning, flowering or seed production stages of the growing season because it severely affects crop yield. This often intensifies the drought condition even though rainfall may not fall far short of the average. This was the situation in The Gambia in both 2012 and 2018 even though rainfall quantities were not as low as 2002, 2001and 2000, Har (2019, reported that drought affected over 700,000 in The Gambia due to low rainfall and dry spells. Rainfall amount was much lower in 2003 and 2005 but the drought intensity was not as bad as in 2002 and 2012. This could be due to less dry spells during the season. The drought intensity in The Gambia in 2000Gambia in , 2012Gambia in , 2014Gambia in and 2018 were mild to moderate droughts. Gurian-Sherman (2012) stated that severe drought attracts more attention but mild and moderate drought are more common and affect crops more especially during mid-season when crops are flowering and producing seeds. This circumstance exacerbated the drought in The Gambia since acute and even severe droughts are uncommon, but midseason dry spells abound. This phenomenon may not change the amount of rainfall in a region, but it can have a significant impact on vegetation, particularly agricultural yields, resulting in low crop production.
The adaptation measures practiced to curb drought in The Gambia as stated in literatures include but not limited to the introduction on drought tolerant crops such as New Rice for Africa (NERICA) and water melon, early maturing cereals, improved farming practices, soil and water conservation techniques, promotion of horticulture and vegetable gardening, and introduction of high yielding crops (Bagagnan et al. 2019). The promotion of animal husbandry was also introduced in drought prone regions of North Bank and Central River Regions to reduce over dependence on crop cultivation (Har 2019). At both national and international stages, the monitoring and forecasting of meteorological drought are one of the most common means to improve the adaptive capacities of local populations.
The Gambia has improved immensely in this aspect. Every year, seasonal rainfall is forecasted where the beginning and ending of the season are forecasted by the Water Resources Department (WDR). Also, July, August, and September (JAS) forecast are given on fortnightly basis so that farmers know what crops to cultivate and what to do during dry spells. The months are very significant especially August which is the month in which The Gambia received highest rainfall. It is the month in which when total rainfall received fall below normal, a drought situation is communicated hence a poor harvest is predictable. Forecasting of rainfall is done to improve the knowledge and perception of the population on the impacts the population could suffer from drought. What needs to be improved on this is the dissemination and simplification of the information for the benefit of the intended groups. Majority of the farming communities cannot read and terminologies used might often be misinterpreted by journalists while reporting hence the need for meteorologists themselves to explain the meaning of the terminologies for proper understanding.
Dam is said to be the most effective method in reducing the impact of drought on locals (Dai et al. 2020). Dams can be multipurpose; irrigation, flood control and supply of water for urban purposes. All these functions are in dare need in The Gambia. Unfortunately, even though the Gambia has a perennial river with various tributaries, the construction of a dam is yet to be realized. The construction of Diama and Manantali Dams on Senegal River were criticized for its lack of integrated approach. The dams were said to have increase productivity especially rice and vegetables (Manikowski and Strapasson (2016). Similarly, the Sameuro Dam in Japan was constructed to control flood as well as stores water for irrigation purposes. It was constructed on the Yoshino River Basin where rainfall is very high in certain areas as well as low in other areas. The dam is also used to supply electricity and maintain the normal function of the river (Wanninayake (2011). Borewells, sometimes with sprinklers or taps attached are also an important source of water for irrigation purposes in The Gambia, but this usage is limited to horticultural gardens usually by women and fruit farmers. This system can be expanded to other farming practices such as cultivation of cereals, groundnut and cotton (Figs 7, 8, 9 and 10).

Conclusion
Drought situation in The Gambia was assessed using three indices: SPI, PAP and VCI. Twenty-one years precipitation data of June, July, August, and September of nine meteorological stations were processed using SPI and PAP. MODIS NDVI (V-6 MOD13Q1) satellite images of June, July, August, and September of 2000, 2005, 2010, 2015 and 2020 from USGS were processed using VCI. The results revealed that drought existed in The Gambia at moderate levels and more common in the farming communities of northern and northeastern parts of the country. The northern and eastern parts of the study area were more drought prone significantly Fatoto, Kerewan, Basse, Kuntaur, and Janjangbureh. The intensity differs based on the indices, SPI revealed the highest intensity based on stations in Banjul (− 2.23) in 2018 and Fatoto (− 2.04) in 2001. 2002 had the highest intensity based on PAP (≤56%), and VCI revealed 2010 having highest intensity (39%). The wettest year was 2020 according to the indices used and Brikama meteorological station was the wettest throughout the study period.
The Gambia is vulnerable to climate hazards especially drought due to variability in hydrometeorological pattern and lowering trend of precipitation and increasing trend in temperature. The findings revealed that SPI, PAP, and VCI can be valuable instruments for drought assessment since there is no specific drought index recognized for used in drought assessment in The Gambia.
It is important to note that monitoring and assessing drought in The Gambia will be of immense important as the impacts of drought can be very devastating not only to the livelihood of those in the farming sector but also the economy of the country in general as over 70% of the population are employed either directly or indirectly in the agricultural sectors. Drought may not only cause food insecurity. It can result to economic hardship,  Research Institute (NARI) helps in crop improvement, National Disaster Management Agency (NDMA) helps in disaster response; at regional and international levels, Inter-State Committee for Fight Against Drought in the Sahel (CILLS) training institute AGRHYMET (Agriculture, Hydrology and Meteorology) trains member country citizens on drought monitoring, agro-meteorology, instruments and computers, crop protection, adaptation and responding to drought impacts. Furthermore, UN agencies such as UNEP, UNCCD, UNFCC, IPCC all work with the government on drought and drought related matters so as to reduce the impact of drought. The most effective mitigation measure to drought impacts in agriculture is the construction of a dam especially that a perennial runs the full-length of The Gambia. This will no doubt curb the intermittent droughts that continue to affects agriculture and threatened food security in The Gambia. Of course, dams have their own negative impacts on humans and the environment as those reported in Senegal. An effective environmental assessment and implementation as in those in Japan and other parts of the world could a learning point for The Gambia.
Author contributions All authors contributed to the study conception and design. Material preparation and data collection were performed by BB, whereas analysis was performed by BB and SM. The first draft of the manuscript was written by BB and SM reviewed and updated the manuscript. All authors read and approved the final manuscript.
Funding The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Data availability
The datasets generated during and analysed during the current study are available from the corresponding author on reasonable request.

Competing Interests
The authors have no relevant financial or non-financial interests to disclose.