Anomaly Index Research Articles

Climate change impacts on staple crops: Assessment of smallholder farmers’ adaptation methods and barriers

Crops in Sub-Saharan African countries are generally more vulnerable to climate change with considerable impacts on yields. In this study, the impacts of climate change on selected root crops, cereals and vegetables were examined with the practice of adaptation as well as barriers hindering the adoption of selected adaptation options in selected farming communities in Ogun state, Nigeria. The climate dataset ranging from 1982 to 2020 and crop yield data ranging from 1996 to 2020 were used in this study. The social data was collected through a structured questionnaire administered among a total of 120 rural farmers purposively selected for the study. The data collected were analysed and presented using descriptive statistics, bivariate correlations and regression statistics. The results showed a high variation in climatic variables together with an obvious anomaly index with severity. The correlation results indicate a strong relationship between rainfall minimum/maximum temperatures and most crops, with R > 0.60, at p > 0.05. The results of multiple regression showed R2 ≤ 0.64 values for all crops at p < 0.05. This result implies that climate parameters accounted for significant percentage of the changes in yields. The results also showed low practice of adaptation among rural farmers and the major barrier hindering the practice of adaptation is lack of capital, including financial, physical, and human capital, which was responsible for 70% of the hurdles to climate change adaptation measures implementation. The key findings here are that the cropping system has been impacted by climate change and that the adaptive capacity of rural farmers in the study area is generally low. The study concludes that although climate change is obvious, there is generally a need to enhance the adaptation options available to smallholder farmers in the region.

Characterisation of Meteorological Drought in Northern Nigeria Using Comparative Rainfall-Based Drought Metrics

Meteorological droughts occur when there is deficiency in rainfall; i.e. rainfall availability is below some acclaimed normal values. Hence, the greater challenge is to be able to obtain suitable methods for assessing drought occurrence, its onset or initiation and termination. Thus, an attempt was made in this paper to evaluate the performance of Standardised Precipitation Index (SPI) and Standardised Precipitation Anomaly Index (SPAI) to characterise drought in Northern Nigeria for purposes of comparison and eventual adoption of probable candidate index for the development of an Early Warning System. The findings indicated that despite the fact that the annual timescale may be long, it can be employed to obtain information on the temporal evolution of drought especially, regional behaviour. However, monthly timescale can be more appropriate if emphasis is on evaluating the effects of drought in situations relating to water supply, agriculture and groundwater abstractions. The SPAI can be employed for periodic rainfall time series though; it accentuates drought signatures and may not necessarily dampen high fluctuations due to implications of high climatic variability considering the stochastic nature and state transition of drought phenomena. On the other hand, the temporal evolution of SPI and SPAI were not coherent at different temporal accumulations with differences in fluctuations. However, despite the differences between the SPI and SPAI, generally at some timescales, for instance, 6-month accumulation, both spatial and temporal distributions of drought characteristics were seemingly consistent. In view of the observed shortcomings of both indices, especially the SPI, the Standardised Nonstationary Precipitation Index (SnsPI) should be looked into and too, other indexes that take into consideration the implications of global warming by incorporating potential evapotranspiration may be deemed more suitable for drought studies in Northern Nigeria.

Fluvial connectivity in the Brazilian semi-arid, Araripe sedimentary plateau

This article aims at identifying and describing short-term connectivity scenarios in a semi-arid watershed in northeastern Brazil. The emergence of different decadal connectivity patterns is discussed, addressing the role of recent climatic inputs in triggering cut-and-fill erosive-depositional patterns within a valley bottom. A confluence stretch between a tributary and the stem channel was selected in order to analyze changes in connectivity and dysconnectivity patterns in response to climatic inputs from 2004 to 2014. The climatic behavior was assessed using the Rainfall Anomaly Index, which established dry and wet years, hence highlighting the relationship between connected and unconnected channel phases and a decennial precipitation dynamic. The years of 2004, 2008 and 2011 stand out as the rainiest and with the highest RAI values, in contrast to 2012, with a total rainfall of less than 600 mm and a RAI value below -2. The discrepancy between the 2012 rainfall total and the 2013/2014 biennium points to the relevance of this period for the reworking of alluvial deposits and connectivity resumption in the watershed. In the ephemeral drainages, connectivity is dramatically interrupted every dry season, creating fluvial disconnection. Dysconnectivity is characteristic of tropical semi-arid fluvial environments, but at landscape scale it may attest to the longevity of dry conditions, hence shall be addressed at time intervals ranging from a few days to thousands and tens of thousands of years.

Assessing the Impact of Long-Term ENSO, SST, and IOD Dynamics on Extreme Hydrological Events (EHEs) in the Kelani River Basin (KRB), Sri Lanka

Hydrological extremes are common throughout the world and can be considered a globally significant phenomenon with severe environmental and social consequences. In recent decades, especially in the second half of the 20th century, Extreme Hydrological Events (EHEs) have attracted extensive attention. Physiological and anthropogenic factors have increased the frequency and severity of hydrological extremes worldwide in the last few decades. Recently, it has become a significant environmental issue in Sri Lanka. Both floods and droughts are widespread throughout the country, and the influence of floods is becoming more common every year. Currently, the frequency and severity of EHEs in the Kelani River Basin (KRB), Sri Lanka, are very common and have increased due to climate variations. Therefore, this study focused mainly on evaluating the EHEs and the impact of long-term El Niño Southern Oscillation (ENSO), Sea Surface Temperature (SST), and Indian Ocean Dipole (IOD) dynamics on extreme events. Rainfall Anomaly Index (RAI) and Extreme Precipitation Indices (EPIs) were calculated to examine the EHEs and their spatial variability. In addition, the relationships between EHEs and ENSO were investigated using several climate indices based on SST anomalies. Both observed and satellite-derived daily precipitation from 1951 to 2019 were used to assess the EHEs in the KRB. The trend of EHEs and the change points were evaluated using the Pettitt test, and teleconnection with global indices was examined using the correlation coefficient in the R application. The result of the study revealed that the pattern of EHEs varied spatially from 1951 to 2019. The strong La Niña years showed a high degree of teleconnection with EHEs in April (r = 0.622 at 0.05 significance level) and August (r = −0.732 at 0.05 significance level). NINO3.4 and the Southern Oscillation Index (SOI) have shown a significant positive impact on EHEs in the Northeast Monsoon (NEM) period. This research on KRB will be a popular scientific measure that can provide scientific results and solutions for the comprehensive decision-making process in the future. Investigating the global physical changes that influence EHEs is critical to taking the necessary steps to reduce the severity of hydrological extremes in Sri Lanka.

Effects of dry spells on soil moisture and yield anomalies at a montane managed grassland site: A lysimeter climate experiment

AbstractThe frequency and severity of droughts in the Alps are expected to increase due to rising air temperatures and changes in precipitation regimes. Although biomass production in humid mountain areas tends to be energy limited rather than water limited, an increase in droughts may have negative impacts on the water availability and thus agricultural yields. This study aimed to analyse the impacts of dry spells on soil moisture and yield anomalies at a montane permanent grassland site in Austria. Dry spells in the time period from 2018 to 2020 were identified using the Standardized Precipitation Index, Palmer Drought Severity Index and the Soil Moisture Anomaly Index. Data from a lysimeter climate experiment were used to evaluate drought impacts on soil water storage and grassland yield under ambient and manipulated conditions. The results indicated the occurrence of three extreme droughts between 2018 and 2020. Although the studied grassland is generally considered a nonwater‐limited ecosystem, the most extreme drought in summer 2019 caused severe and extreme yield anomalies under ambient and heated conditions. Only mild yield anomalies were observed on plots with elevated atmospheric carbon dioxide concentration. This drought‐mitigating effect was attributed to the water savings enabled by partial stomatal closure under elevated CO2. The shorter dry spells in spring and late summer 2018 led to more diverse effects; mildly to moderately negative yield anomalies were found on the heated plots, whereas the anomalies tended to be less negative or even positive on plots under ambient temperature. In contrast, some time periods without water stress showed positive effects of heating on yield. These findings suggest that drought impacts on a humid montane grassland depend on both water availability and air temperature. Higher air temperature can have positive effects on yield if the ecosystem is energy limited. However, global warming suggests a tendency from energy to water limitation, in which the increased evaporative demand of the atmosphere aggravates soil moisture droughts and thus has potentially negative effects on yield.

INDICES DE SEVERIDADE DA SECA NO SEMIÁRIDO, PARAÍBA

The occurrence of annual and multiannual droughts in the Brazilian semiarid is a recurrent phenomenon that triggers a series of consequences, impacting the environment and the quality of life of the population inhabiting this region. Due to its location in the drought polygon, the Immediate Geographical Region of Monteiro – PB (REGIM does not diverge from this reality. Given the above, this research aims to correlate the DM, PNI, and RAI Severity Indices of Drought Events in the REGIM, through the historical rainfall series data, to classify the quantitative data on a monthly and annual scale and identify these cycles' Severity of Events (SDE) and consequently evaluate the variation of precipitation over time, identifying the dry and rainy periods. The research sourced monthly rainfall data from the Northeast Development Superintendence (SUDENE), National Institute of Meteorology (INMET), and Executive Agency of Water Management of Paraíba (AESA) to compose the spatial and temporal precipitation variability, which was calculated through the Normal Percentage Index – NPI (CUNHA, 2008), Decision Method – DM (GIBBS; MAHER, 1967) and Rainfall Anomaly Index – RAI (ROOY, 1965). Keywords: Rainfall Standardization Indices – Ipp; Severity of Events – SDE; Water Resources.

An assessment methodology for drought severity and vulnerability using precipitation-based indices for the arid, semi-arid and humid districts of Tamil Nadu, India

Abstract As the short- and long-term impacts of climate change are becoming more visible at smaller regional scales, frequent occurrence (absence) of erratic precipitation as well as water scarcity issues can be identified as reliable indicators for predicting meteorological droughts. A supervised declaration of meteorological drought based on available precipitation data requires an understanding of reliability and consistency of drought indices for appropriate severity classification. An attempt has been made in this study to critically evaluate the performance of six popular drought indices namely, Standardized Precipitation Index (SPI), China Z Index (CZI), Modified China Z Index (MCZI), Deciles Index (DI), Rainfall Anomaly Index (RAI), and Z-Score Index (ZSI) for four districts in Tamil Nadu falling under arid (Karur), semi-arid (Cuddalore), dry sub-humid (Kanyakumari) and moist sub-humid (Coimbatore) conditions based on 120 years of precipitation records. Results showed that the SPI and CZI provided similar quantification of drought events (about 18% of the total months) irrespective of their climatic considerations while ZSI and RAI resulted in overestimation of drought severity (about 30–47%). Based on the classification strategy adopted for the selected indices, a framework for drought vulnerability assessment is proposed in conjunction with the estimated drought severity classifications.

Historical and projected spatial and temporal rainfall status of Dar es Salaam, Tanzania, from 1982 to 2050

Dar es Salaam, like other cities in Africa, experiences flash floods during the rainfall season that destroy infrastructure due to the overflow of rivers and blocked sewage. This study investigates the historical and future variability and changes in spatial and temporal rainfall over Dar es Salaam. Station data and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) gridded data crossing 38 years (1982–2019) were used as a baseline and the Coordinated Regional Climate Downscaling Experiment (CORDEX) dataset from 2021 to 2050 was used for projection under Representative Concentration Pathway (RCP 4.5) forcing scenarios. A trend analysis of historical data was conducted at monthly, seasonal, and annual timescales. Mann–Kendall statistical tests and Sen’s slope estimator were applied to identify the current trend direction and magnitude of changes in rainfall patterns over time. A standardized anomaly index (SAI) was also employed to detect the region’s trends in wetness and dryness. The spatial distribution of rainfall in the city was investigated using an inverse distance weighted (IDW) interpolation technique. The statistical results reveal that a non-significant trend in rainfall was observed on monthly, seasonal, and annual timescales. Generally, in the future (2021–2050), the annual cycle of rainfall shows a slight decrease in monthly rainfall, especially from January to August, and an increase from September to December compared to historical (1982–2019) rainfall, for most of studied locations. Spatially, the distribution of projected rainfall shows that the southern part of the city will experience higher rainfall than other parts. The most significant findings were a decrease in annual projected rainfall by 20%, the MAM projected rainfall season increased by 42%, and an increase of 38% of the OND-projected rainfall season. The findings of this study will be useful for the improved management and planning of the city.

Spatio-temporal variability and trends of hydroclimatic variables at Zarima Sub-Basin North Western Ethiopia

Globally, hydroclimatic variables have been changed due to human activities and have an impact on agricultural production and water resource management. This study investigated the spatio-temporal variability of hydroclimatic variables in Zarima subbasin using rainfall and temperature data from 1984 to 2018 and stream flow data from 1990 to 2014. The data were analyzed using the coefficient of variation, standardized anomaly index, Mann–Kendall trend and Sen’s slope estimator test. The results showed that rainfall, maximum and minimum temperatures of the Zarima subbasin varied spatially and temporally. The annual and Kiremit season rainfall and stream flow showed low to moderate variability (CV < 30%) whereas Bega and Belg season rain fall and stream flow showed high degree of variability (CV < 40%). The annual and Kiremit season rainfall showed relatively higher variability along the northern border of the subbasin. However, maximum temperature showed less degree of variability (CV < 10%) over the subbasin, whereas the annual and seasonal minimum temperatures showed less to moderate variability (CV = 2–28%). The minimum temperature showed moderate variability around the south east lower border of the subbasin on the annual time scale and the north east part of the subbasin during the Kiremit season. The Bega and Belg seasons mean minimum temperatures showed less to high degree of variability (CV = 0–40%). The south east lower part of the subbasin showed moderate to high variability during the Bega and Belg seasons. Results of a standardized anomaly index of the rainfall, temperature and stream flow confirmed that the sub basin experienced fluctuations between dry, wet, cool and warm years. The spatial representation of annual rainfall showed a statically significant increasing trend in some parts of the subbasin and an insignificant increasing trend in the majority of the subbasin up to 300 mm per decade, while the Bega and Belg seasons showed statistically insignificant increasing and decreasing trends. Kiremit season rainfall showed heterogenous results in both statistics and trend direction. The mean annual maximum showed an increasing trend from 0.35 to 0.9 °C. The Bega, Belg and Kiremit seasons' maximum temperatures increased by a range of 0.35 to 0.95 °C; 0.4 from 1.2 °C and 0.1 to 0.55 °C pre decade respectively. While the annual minimum temperature increased by 0.05 to 0.5 °C and decreasing trend by 0.1 to 0.3 °C around the south eastern part of the subbasin. The Bega and Belg season minimum temperatures increased up to 0.5 °C and 1 °C and temperatures decreased in the range of 0.1 to 0.5 oC per decade. The Kiremit season minimum temperature increased by a range of 0.05 to 0.5 °C. The annual, Bega, Belg and Kiremit season stream flow increased insignificantly by 0.32, 0.31, 0.02 and 0.68 mm3/s respectively. In general, the subbasin experienced hydroclimatic variability which affects the life of the people, agricultural production and the economy of the area. This needs further investigation for planning and management of water resource management for the success of future water resources projects.

Monitoring gas flaring in Texas using time-series sentinel-2 MSI and landsat-8 OLI images

• A high-resolution inventory of gas flaring in Texas is constructed. • Spatial-temporal characteristics of gas flaring over Texas are analyzed. • The greenhouse gas emissions hotspots from the gas flaring regions are explored. Since the shale Oil/Gas revolution, gas flaring and venting in the United States has garnered increasing attention. There is a pressing need to understand the spatial–temporal characteristics of gas flaring and track the associated greenhouse gas emissions. In this context, we use a thermal anomaly index (TAI) incorporating the Google Earth Engine (GEE) cloud computation and local batch processing for monitoring gas flaring and characterizing its spatial–temporal dynamics. We then apply a quantitative analysis of satellite-based carbon dioxide (CO 2 ) and methane (CH 4 ) in the gas flaring region. Here, we generate a gas flaring sites inventory in Texas from 2013 to 2022 based on > 83,500 multi-source moderate-resolution images (including 74,627 Sentinel-2 Multispectral Instrument [MSI] images and 8,969 Landsat-8 Operational Land Imager [ OLI] images). Validations and comparisons demonstrate that our method is reliable for MSI and OLI images, with an overall accuracy of > 95 % and a low commission rate and omission rate. We detected 217,034 gas flares from 9,296 flaring sites in Texas, and the majority (>92 %) were found in the central and western regions of the Permian Basin and the Eagle Ford Shale. The number of detected gas flaring sites vastly outnumbered the existing Visible Infrared Imaging Radiometer Suite (VIIRS) fire products, with an upward trend from 2013 to 2019 and a downward trend from 2020 to 2022. Notably, the gas flaring sites dropped significantly at the beginning of the COVID-19 pandemic (from December 2019 to May 2020), with the lowest average monthly growth rate of −14.38 %, and fell to the level of mid-2017. Application of gas flaring data identifies the localized greenhouse gas (GHG) emission hotspots in Texas and demonstrates that the increased effect of CH4 released from gas flaring regions was significantly stronger than that of CO 2 . These findings can provide references for monitoring similar small industrial sources in the future, can be used as an essential supplement to low-resolution fire products, and improve our understanding of CO 2 and CH 4 emissions from gas flaring at fine spatial scales.

Decadal Assessment and Distribution of Rainfall Anomaly Index (1991 – 2020) for Benin City, Edo State, Nigeria

This study was designed to provide valuable insight into the temporal patterns of rainfall in Benin City, Edo State, Nigeria using rainfall data from 1991 – 2020 (30 years) collected from Nigerian Meteorological Agency (NIMET), airport station, Benin City. The data were assessed based on 10 years interval (decade) identified as decadal A (1991-2000), decadal B (2001-2010) and decadal C (2011-2020). The data was analysed descriptively using charts and graphs. Also, Rainfall Anomaly Index (RAI) was determined for each decadal. Findings from the study reveal that rainfall pattern changes significantly based on statistics for each decadal. In decadal A, rainfall usually began in the month of July to October, June to September in decadal B while May to September in decadal C with rainfall going above the annual precipitation (2679 mm) for the City. The rainfall anomaly over the city revealed that there was a composite nature in which some dry years were mixed with wet years and vice versa and this occurred in all decades. RAI revealed that decadal C recorded the highest number of years (7) of intense rainfall compared to decadal A and B. The trend for the average annual rainfall showed a significant trend based on the decade. The average annual rainfall increased with time (decade) as the trend rose from 1886.9 mm in decade A to 1890.0mm in decade B and 2078.8 mm in decade C. The year of greatest positive value was 2016 (decadal C), with an average RAI of 6.53 classified as extremely humid. Based on these findings, the study concludes that the climate in Benin City has significantly changed.

Assessment of Hydrological Extremes for Arid Catchments: A Case Study in Wadi Al Jizzi, North-West Oman

The objective of this research was to analyse hydrological variability by conducting an intensive analysis of extreme events, under dry and wet conditions. Drought conditions were assessed using the Standard Precipitation Index (SPI) and Rainfall Anomaly Index (RAI), while the Soil Conservation Service (SCS) method was used to simulate flooding at four stations. The SPI results indicated that the amount of rainfall within the catchment area is near to normal, ranging from 64% to 75%, with some extremely wet exceptions which may cause flash floods. The RAI results also indicated that the amount of rainfall within the catchment area is near to normal, but the extremely wet category obtained the largest percentage (ranging from 36% to 50%) and the very wet category had the lowest percentage (ranging from 9% to 36%). The simulated flooding, using SCS, tended to slightly underestimate the observed streamflow, while the performance showed some weaknesses when the observed flooding was less than 1 m3/s. The Nash–Sutcliffe Efficiency showed higher performance at closer rainfall stations to the outlet, with values of 0.92 and 0.94. Distant stations simulated floods that showed a lower level of efficiency, with values of 0.77 and 0.81. Given the fact that hydrological extremes (dry and wet conditions) are connected, the findings of the two indices and the SCS method are consistent and suitable for monitoring drought and flood events under climate change.

Spatio-temporal drought assessment of the Subarnarekha River basin, India, using CHIRPS-derived hydrometeorological indices.

Precipitation studies have a crucial role in deciphering climate change and monitoring natural disasters such as droughts. Such studies lead to better assessment of rainfall amounts and spatial variabilities; and have a vital role in impact assessment, mitigation, and prediction of occurrence. Thus, this study has been undertaken in the Subarnarekha River basin using Climate Hazards group Infrared Precipitation with Stations (CHIRPS) dataset. Precipitation datasets helped in deriving hydrometeorological indices such as the Rainfall Anomaly Index (RAI) and Standardized Precipitation Index (SPI) for the identification of drought occurrences. The core objective was to infer spatio-temporal drought scenarios and their trend characterization covering four decades over the years 1981 to 2020. Quantitative drought assessment was done using run theory for identifying the Drought Duration (DD), Drought Severity (DS), Drought Intensity (DI), and Drought Frequency (DF). Mann-Kendall (MK) test was performed to understand the precipitation and drought trends at annual and seasonal scales. Eight severe drought events were identified in the Subarnarekha River basin for the past 40years and the average DI value of 0.8 was recorded. MK test results for the precipitation showed a significant positive trend (95% confidence level) for pre-monsoon periods. However, for SPI, a significant positive trend was observed over the intervals of 3 (SPI3), 6 (SPI6), and 12 (SPI12) months respectively at an annual timescale, suggesting wetter conditions within the study area. Moreover, there had been insignificant negative trends for SPI1 and SPI3 during winter. It indicates that during the short-term SPI scale, i.e., 1month (SPI1) and 3months (SPI3), the instances of negative SPI values inferred were high, which point to the increasing incidences of meteorological drought possibly due to deficient soil moisture. Thus, the results indicated that the CHIRPS precipitation product-derived hydrometeorological indices could act as a valuable tool for assessing the past spatio-temporal drought conditions of the Subarnarekha River basin. This may further be helpful in planning for sustainable water resource management of such river basins.

Spatio-Temporal Rainfall Variability and Concentration over Sri Lanka

Changes in precipitation patterns significantly affect flood and drought hazard management and water resources at local to regional scales. Therefore, the main motivation behind this paper is to examine the spatial and temporal rainfall variability over Sri Lanka by Standardized Rainfall Anomaly Index (SRAI) and Precipitation Concentration Index (PCI) from 1990 to 2019. The Mann–Kendall (MK) trend test and Sen’s slope (SS) were utilized to assess the trend in the precipitation concentration based on PCI. The Inverse Distance Weighting (IDW) interpolation method was incorporated to measure spatial distribution. Precipitation variability analysis showed that seasonal variations are more than those of annual variations. In addition, wet, normal, and dry years were identified over Sri Lanka using SRAI. The maximum SRAI (2.27) was observed for the year 2014 for the last 30 years (1990–2019), which shows the extremely wet year of Sri Lanka. The annual and seasonal PCI analysis showed moderate to irregular rainfall distribution except for the Jaffna and Ratnapura areas (annual scale-positive changes in Katugastota for 21.39% and Wellawaya for 17.6%; seasonal scale-Vavuniya for 33.64%, Trincomalee for 31.26%, and Batticaloa for 18.79% in SWMS). The MK test, SS-test, and percent change analyses reveal that rainfall distribution and concentration change do not show a significant positive or negative change in rainfall pattern in Sri Lanka, despite a few areas which experienced significant positive changes. Therefore, this study suggests that the rainfall in Sri Lanka follows the normal trend of precipitation with variations observed both annually and seasonally.

Evaluation of Rainfall Extreme Characteristics in Dodoma Urban, A Central Part of Tanzania

The occurrence of low rainfall in semi-arid areas including Dodoma urban leads to a shortage of water. This paper addresses the evaluation of rainfall extreme characteristics by analyzing the variability indices, probability distribution, and return periods. The daily rainfall index shown the magnitude of rainfall varied unpredictably within annual wetted days. The study area experienced a period of one to two months per year with extreme seasonality as evaluated using the rainfall seasonality index. The standardized anomaly index indicated the equivalent of 60% of 20 years experienced the dried years with unpredicted occurrence. The Weibull distribution was selected out of Fifteen probability functions when ranked using Kolmogorov–Smirnov and Anderson-Darling tests. The return periods of rainfall had an average rainfall of 576 mm and were predicted using seventeen plotting position methods and Weibull distribution. Therefore, the magnitude of rainfall in the semi-arid areas would not easily be estimated but using more than one technique would improve the evaluation of rainfall characteristics.

Temporal Rainfall Anomaly and Its Association with Crop Yield: In the Case of Afar Region, Ethiopia

Ethiopian economy is predominantly agrarian and the majority of the population in the country engaged in agricultural activities which is considerably affected by rainfall variability. The majority of the nation's crops are rain-fed, making them particularly vulnerable to the fluctuation that can cause severe food insecurity, which can result in famine and poverty over the whole nation. The impact of rainfall variability was very serious in the pastoral areas that are largely inhabited by the pastoralist whose livelihood depend primarily on livestock farming. For this study, rainfall data were taken from Ethiopian Meteorology Institute (EMI) for 1981-2020 period and yield data were taken from Central Statistical Agency (CSA) of Ethiopia for 1994-2019 period. This study was briefly evaluated rainfall variability and its impact on yield and computed Rainfall Anomaly Index (RAI) for Kiremt cropping season in a pastoral area of Afar region, Ethiopia. Regression analysis for the Kiremt cropping season based on observed rainfall dataset was used in the study to further analyze the relationship between rainfall variability and yield. The temporal analysis of RAI clearly indicated that there were more dry years than wet years with varies magnitude. The year of 1984 and 2009 were found extremely dry with magnitude of -4.95 and -4.13, respectively whereas 1987, 2015, 2002, 2004 and 1997 were identified as very dry with magnitude of -3.92, -3.39, -3.16, -2.88 and -2.41, respectively. The year of 1988 and 1998 found extremely humid with magnitude of 5.87 and 5.33 whereas 2020, 1994, 2010 and 1992 were very humid with magnitude of 3.47, 3.20, 2.98 and 2.34 respectively. The outcome of the regression analysis showed a positive link between rainfall anomaly and crop production for the Kiremt cropping season, with yield increasing with a positive rainfall anomaly and rainfall anomaly accounting for 29.4% of crop yield. Keywords: Kiremt Cropping Season, Rainfall Anomaly Index, Pastoral Area, Regression, Yield DOI: 10.7176/JEES/12-9-03 Publication date: September 30 th 2022

ANALYSIS OF RAINFALL AND TEMPERATURE TRENDS IN DUSTIN MA TOWN, DUTSIN-MA LOCAL GOVERNMENT AREA, KATSINA STATE, NIGERIA

The study examined the trend detection of rainfall and temperature in Dutsin-Ma, Dutsin-Ma Local Government Area, Katsina State. The study was aimed at determining the significance of rainfall and temperature trends in the area if it is in accordance with the global climate change scenarios. Secondary data (rainfall and temperature) for thirty-one (31) years from 1984-2014was used, the data was source from NOAA/NCEP and were subjected to the following analysis; Descriptive statistics, Mann Kendall, Sen’s Slope Model Estimator, Standardized Anomaly Index (SAI), and Rainfall Anomaly Index (RAI). The results revealed a significant decrease of rainfall at (p-value = - 0.0108mm), the values of Kendall Tau, Z- Statistics and Sen’s Slope forrainfall were (-0.3247mm, -2.5495mm and -26.11mm) respectively. There is a significant increase of temperature at (p-value = 0.0037 oC), the values Kendall Tau, Z- Statistics and Sen’s Slope for temperature were (0.3699 oC, 2.9068 oC and 0.0410 oC). The rainfall decrease at the rate of -0.0594-1 (mm) while temperature increase at the rate of 0.0597-1 (oC). There is (52%)of positive anomaly and (48%) of negative anomalies of rainfall while the temperature has (48%) of positive anomaly and (52%) of negative anomalies during the study period. The RAI is (- 3.51mm), which indicates very dry condition and the rainfall pattern changes every decade. The study concluded that there is significant increase in temperature and decrease in rainfall,anomalies of the climatic variable influences, climate variability in the area and Dutsin-Ma is classified as very dry climate and the rainfall pattern changes every decade. The study recommended that human activities which influence increase in temperature should be reduced.

Study on the water-richness law and zoning assessment of mine water-bearing aquifers based on sedimentary characteristics

To study and prevent the water hazards of deep coal mines roof in the Inner Mongolia–Shaanxi (IM–S) mining area, it is essential to correctly evaluate the water-richness distributions of water-bearing aquifers in roof. This paper puts forward a sediment control method for water-richness law and zoning in the roof aquifers of deep Jurassic coals. To determine the vertical distance of direct water-bearing aquifers, the height of fractured water-conducting zone was detected by an underground network parallel electrical method. The plane and lateral spatial distribution patterns of the water-bearing aquifers and the control of the water-richness distribution was analyzed with the sediment control method. An evaluation system that consisted of four indicators, i.e., sedimentary environmental impact index, interlayer ratio of sandstone and mudstone, sandstone thickness, geophysical water-richness anomaly index was constructed. Furthermore, an Analytic Hierarchy Process (AHP) was introduced to establish the comprehensive zoning map. Finally, through the example analysis of Muduchaideng coal mine, the zoning evaluation results of water-richness were verified by the mine inflow. The findings of this study provide scientific guidance for prevention and control of mine water hazards in the IM–S mining area.

Landsat NDVI-based vegetation degradation dynamics and its response to rainfall variability and anthropogenic stressors in Southern Bui Plateau, Cameroon

• Long-term vegetation degradation is assessed by means of time-series Landsat NDVI. • Mean annual NDVI and rainfall anomaly index (RAI) were compared. • Anthropogenic stressors are primarily responsible for vegetation degradation. • Vegetation degradation leads to declining land productivity and ecosystem services. Land degradation is a serious problem affecting the livelihoods of people leaving in marginal lands. Its assessment has been made easy by a plethora of remote sensing techniques. This study seeks to establish the spatiotemporal trends in vegetation degradation and its response to climate change and anthropogenic stressors in Southern Bui Plateau, Cameroon. The study used mean annual Landsat-derived NDVI of cloud-free months to model vegetation degradation dynamics over 37 years (1984–2021) based on Ordinary Least Square (OLS) Regression and Pearson's Product Correlation of NDVI with Rainfall Anomaly Index (RAI) on a pixel-by-pixel basis. Areas undergoing significant degradation are estimated at 10.81% (1469.08 km 2 ) and slight degradation, 23.57% (3202.39 km 2 ). Total degraded lands accounted for 34.38% (either 4671.47 km 2 ). Areas with slight improvement in vegetation cover accounted for 24.88%, while 9.69% area showed significant improvement. NDVI-Rainfall relationship revealed that areas significantly impacted by human activities and pressures ( r ≤ -0.50) driving vegetation changes covered 24.67% (either 3352.03 km 2 ), while those under climatic variability and change influence ( r ≥ 0.50 ≥ 0.90) accounted for 55.84% (either 7587.26 km 2 ), under both climatic and human stressors ( r ≥ 0.50 < 0.70), 13.09% (either 1779.01 km 2 ) and areas not significantly impacted, i.e., somewhat stable nature over the years accounted for 6.40% (869.04 km 2 ). Areas under human vegetation pressures occupy the heavily grazed landscapes, the transhumance paths, and forested areas of the Kilum-Ijim forest. The practice of sustainable land management and landscape restoration initiatives are key to achieving land degradation neutrality at watershed scale.

Drought Assessment of Eastern Satara District of Maharashtra using Rainfall Anomaly Index

Drought is widely recognized as a phenomenon associated with scarcity of water. Proper evaluation and management of rainfall is a crucial need to reduce the severity of drought. Present work aims to study the spatial and temporal fluctuation in the rainfall of the eastern part of the Satara district of Maharashtra using the Rainfall Anomaly Index (RAI). Monthly and annual rainfall data of sixteen metrological stations were used for the period between 1979 and 2013. RAI was computed and prepared spatial distribution maps. The present study reveals that the eastern and southern part of the study area are prone to drought condition. The present investigation is useful to delineate potential sites of drought and through this study, risk of future drought conditions can be curtailed.