Climate Trend Analysis Research Articles

Spatial-temporal seasonal and annual rainfall trends and variability assessment in the Pangani Basin, East Africa

Although in situ rainfall data remains the most accurate, the gauge network density in East Africa is sparse. It lacks continuity, thus making it inadequate to assess the spatial and long-term rainfall trend and variability accurately. As such, rainfall remote sensing data are normally used instead of ground station data. This study evaluates the capabilities and limitations of remote sensing data compared with ground-based observations in Tanzania's Pangani Basin in assessing the seasonal and annual rainfall trends and variability. Data from the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) and twenty-three ground stations were analyzed, comprising a time series from 1990 to 2022. Trend analysis was conducted using the Mann-Kendall test, while the spatial distribution of precipitation was determined using Sen's slope method. CHIRPS annual rainfall showed good agreement with station rainfall data, with NSE, R2, slope, Pbias, MAE, and RMSE values of 0.84, 0.92, 0.92, 7.55%, 297.4, and 397.1, respectively. The coefficient of variation from station data indicated extreme variability, exceeding 30% for annual rainfall, while CHIRPS data showed moderate variability, ranging from 20% to 30%. Both station data and remote sensing data showed an increasing trend for annual and seasonal rainfall at least 10 stations. However, stations like Maji Moshi, Kiungu Primary School, Segera C. Tank, and Kibong'oto exhibited an increasing trend for vuli rainfall with CHIRPS data, while station data indicated a significant decreasing trend.The study highlights the necessity for calibration and validation to avert misinterpretations in climate trend analyses, especially at the basin level.

A 12-Year Population-Based Analysis of Victimization and Climate Trends in Israeli Arab and Jewish Elementary Schools

ABSTRACT The study aims to examine changes over time in school victimization and climate in Israel, and whether these changes varied between Jewish and Arab schools and schools with different SES. A secondary analysis of the Ministry of Education database of structured student surveys regarding victimization and climate, was conducted during 2008–2019. All students in grades 5–6 were surveyed. The number of schools ranged between 751 and 1,189 (M = 983, SD = 166.3); 73.7% were Jewish schools, and 26.3% were Arab. Peer victimization dropped from 14.95 in 2008 to 7.97 in 2019 (β = -.39). All climate aspects positively increased. The highest improvements were in feeling unsafe (β = -.28). Reductions in victimization and progress in climate were the strongest among students from Arab schools and schools with lower SES. The implications for policy and future research are discussed.

A comparative analysis of temperature trends at Modena Geophysical Observatory and Mount Cimone Observatory, Italy

AbstractGlobal warming has become a critical environmental, social, and economic threat, with increasing frequency and intensity of extreme weather events. This study aims to analyse temperature trends and climate indices in the Po Valley, a significant economic and agricultural region in Italy, by examining data from two historical stations: the urban Modena Observatory and the rural Mount Cimone Observatory. The analysis extends previous studies to 2018, assessing the magnitude of climate changes since the 1950s and isolating the Urban Heat Island (UHI) effect in Modena. Significant warming trends were confirmed at both sites, with in maximum (TX) and minimum (TN) temperatures trends nearly doubling from 1981 to 2018 compared to 1951–2018. For example, TX trends reached 0.84°C·decade−1 in Modena and 0.62°C·decade−1 at Mount Cimone, while TN trends were 0.77 and 0.80°C·decade−1, respectively. Extreme climate indices showed a substantial increase in warm days and nights (TX90p and TN90p, respectively). Particularly we found TX90p of 27.5 days·decade−1 in Modena and 15 days·decade−1 at Mount Cimone while TN90p of 29.5 days·decade−1 in Modena, 22 days·decade−1 at Mount Cimone. The UHI effect significantly impacts Modena's temperature trends. Urbanization contributes up to 65% of the rise in warm nights. Specifically, frost days decreased by 1.88 days·decade−1 (37% of Urban Contribute, UC), tropical nights increased by 5.16 days·decade−1 (57% UC), warm nights increased by 12.7 days·decade−1 (65% UC), and cool nights decreased by 3.19 days·decade−1 (39% UC). Overall, the study underscores the importance of considering both global and local factors in regional climate trend analysis.

Climate change and coastal erosion hotspots in West Africa: The case of Togo

Global warming is a worldwide phenomenon with disastrous implications ranging from ocean warming and glacier melting to sea level rise and coastal damage. This research assesses climate change trends, investigates coastal erosion hotspots and forecasts shoreline dynamics in West Africa. It also includes information on coastal erosion impacts and current coastal defence measures. The data set includes annual mean sea level anomaly, eddy kinetic energy, wave energy data and monthly climate data, such as precipitation, temperature, wind speed, and sunshine, from 1988 to 2023. Additionally, field survey data and Sentinel-2 satellite images were employed from 2015 to 2023 for coastal erosion monitoring. The Mann-Kendall test and Sen's slope test have been employed for climate trend analysis, while the DSAS tools have been used to identify coastal erosion hotspots and forecast future trends. The results revealed a significant increasing trend in annual sea level rise anomaly, annual wave energy, annual eddy kinetic energy, monthly temperature, and monthly sunshine. According to the shoreline dynamics investigation on Togolese coastal area, the Aflao-Port transect had significant accretion rates (up to 15 m/years), whereas the Port-Aneho transect experienced coastal erosion (up to −12 m/years). Climate change may increase wave energy intensity in certain regions, while coastal development can alter littoral transport and shoreline changes. Although there are soft and hard stabilisation solutions to counteract coastal erosion, such as groynes, sandbags, reforestation, and a series of nozzles in Togolese coast, the phenomenon of coastal erosion has evolved in recent years. Future projections in 2033 show that coastal erosion could move from 50 to 250 m inland. It is recommended that climate trend indicators, shoreline dynamics, and coastal stabilisation solutions be incorporated into all coastal and marine policies for sustainable management, with a view to ensuring minimal disruption to the ecosystem services provided by the sea and coast to people.

Changing Tourism Trends and Vulnerability Assessment of Built Environment in Hill Stations of Indian Himalayan Region.

Tourist arrivals in the Indian Himalayan region have led to an increase of 1.6 times the population of the native residents in 2019. The trend of winter tourism among foreign tourists, along with adventure and pilgrimage tourism, has resulted in an average annual growth of 28.78% between 2002 and 2013. This study focuses on the changing tourism and climatic trends in tourist hotspots of the Indian Himalayan Region (IHR) to evaluate the vulnerability of the built environment, which arises from the increasing demand for tourist infrastructure. The approach taken in this research is based on secondary literature available and case studies of emerging tourist centers in and around Shimla region of Himachal Pradesh. According to records from 2019-20, domestic tourism has increased in Himachal Pradesh by 4.57% and in Shimla by 5.51%. However, the changing trends and the tourist demand for fast, unplanned infrastructure growth can lead to over-tourism and disaster vulnerability. Therefore, there is a need to consider the risk and change management in the fragile ecosystem of IHR through analysis of climatic and tourism trends. To achieve this, computerized tools such as Real-Time Systems, Intelligent Transport Systems, and Neural networks projects are suggested for feasibility and assessment of proposed tourism infrastructure projects. The suggested process will strengthen the project vision by benefiting the policymakers, stakeholders, and tourists while maintaining eco-friendly tourism opportunities through project performance management.

Climatic Data Trend Analysis by Mann Kendal Test and Innovative Trend Analysis: A Case Study of Taloqan River at Takhar, Afghanistan.

Climate change is taking place due to increased population and anthropogenic activities. The impacts of climate change have increased the demand for sustainable management of water resources. The semi-arid climatic zone is widely affected by climate change. Afghanistan is vulnerable to climate change because of its climate and variable precipitation. This research has studied the trend analysis of climatic data in the Taloqan River, which is being utilized for drinking and irrigation. The recorded data of the Tangi-Farkhar hydro meteorological station from 2008 to 2021 is used in this work. The non-parametric Mann-Kendall (MK) trend test and the Innovative Trend Analysis (ITA) method are utilized in this investigation. This study has found an increasing trend in the mean value of temperature in May across the period of study but no trend in annual temperature data according to the MK test with a 95 percent confidence level. The ITA shows an increasing trend in the annual temperature data, a decreasing trend in precipitation, and a non-monotonic negative increasing trend in discharge. The MK test has presented no trend in the annual data of precipitation and discharge and showed an increasing trend in the mean discharge value in October and November across the study period.

Statistical Analysis of Climate Trends and Impacts on Groundwater Sustainability in the Lower Indus Basin

Agricultural intensification is increasing global demand for water, with groundwater especially susceptible given its year-round reliability. Climate change impacts on groundwater recharge exacerbate uncertainties for future access and use, especially for large aquifers across alluvial plains such as the Indus Basin of Pakistan. To generate better understanding of climate change impacts on groundwater balances in such contexts, we used MODFLOW 2005 to quantify the groundwater budget of the Northern Rohri Canal Command Area under RCP 4.5 and 8.5 climatic scenarios, while also taking climatic regionalisation into account. Under a baseline scenario, total annual pumping in the northern Rohri command was estimated to be 3.619 billion cubic metres (BCM), and the total net loss in storage over the simulation period from October 2010 to April 2014 was estimated at 1.244 BCM per year. By 2047, net decline in storage is projected to more than double to 2.185 per year under RCP 4.5 scenario and 2.214 under RCP 8.5. Our estimates suggest that a sustainable yield across the command area should be managed at approximately 3 ± 0.3 BCM per year to ensure sufficient adaptive reserves of groundwater for access during times of drought and inadequate surface supply, while also reducing waterlogging impacts from high watertables. This first-time estimate of sustainable yield provides irrigation system managers with an overall guide from which divisional-scale measures to achieve the goal can be identified through stakeholder engagement.

Spatiotemporal dynamics of ecosystem services in response to climate variability in Maze National Park and its environs, southwestern Ethiopia.

Climate variability is one of the major factors affecting the supply of ecosystem services and the well-being of people who rely on them. Despite the substantial effects of climate variability on ecosystem goods and services, empirical researches on these effects are generally lacking. Thus, this study examines the spatiotemporal impacts of climate variability on selected ecosystem services in Maze National Park and its surroundings, in southwestern Ethiopia. We conducted climate trend and variability analysis by using the Mann-Kendall (MK) trend test, Sen's slope estimator, and innovative trend analysis (ITA). Relationships among ecosystem services and climate variables were evaluated using Pearson's correlation coefficient (r), while partial correlation was used to evaluate the relationship among key ecosystem services and potential evapotranspiration (PET). The MK tests show a decreasing trend for both mean annual and main rainy season rainfall, with Sen's slope (β) = -0.721 and β = -0.1.23, respectively. Whereas, the ITA method depicted a significant increase in the second rainy season rainfall (Slope(s) = 1.487), and the mean annual (s = 0.042), maximum (s = 0.024), and minimum (s = 0.060) temperature. Spatial correlations revealed significant positive relationships between ecosystem services and the mean annual rainfall and Normalized Difference Vegetation Index (NDVI), while negative correlations with the mean annual temperature. Additionally, temporal correlations highlighted positive relationships among key ecosystem services and the main rainy season rainfall. The maximum and minimum temperatures and ecosystem services were negatively correlated; whereas, there was strong negative correlations between annual (r = -0.929), main rainy season (r = -0.990), and second rainy season (r = -0.814) PET and food production. Thus, understanding the spatiotemporal variability of climate and the resulting impacts on ecosystem services helps decision-makers design ecosystem conservation and restoration strategies to increase the potential of the ecosystems to adapt to and mitigate the impacts of climate variability.

From Glaciers to Grasslands: Comparative Analysis of Climate Trends in Manang and Mustang, Nepal

This study examines the effects of climate change on Nepal's Manang and Mustang districts by analyzing temperature and precipitation trends, changes in glacial extent, and land cover transformations. Utilizing Landsat imagery from 1992 to 2023 and historical meteorological data, we assess environmental changes in land cover. The results indicate significant decreases in precipitation, particularly during the monsoon season, alongside increases in grassland cover and reductions in barren and forested areas. Manang shows a distinct pattern with rising snowfall, whereas Mustang experiences a notable decline in rainfall, underscoring the necessity for regionspecific adaptation strategies. These findings offer critical insights for shaping climate policies and developing robust strategies to enhance the resilience of high-altitude environments.

Modelled Climate Change Impacts on Spring Canola Production Across British Columbia, Canada

This paper investigates the impact of projected near future climate trends on the production of spring planted canola (Brassica napus, Brassica rapa, and Brassica juncea of canola classification) across British Columbia, Canada. Analysis of historic climate trends from 2001-2020, informed by the Global Historical Climatology Network daily (GHCNd) database, establishes patterns of warming temperatures and increasing precipitation values across the province over the early 21st century. Near future climate trends were modelled using CMIP6 climate models, from 2021-2040 under SSP1-2.6, SSP2-4.5 and SSP5-8.5, with the projections downscaled using ClimateBC. The projected trends mirrored those of the observed historic record, while an observable relationship between rising levels of climate change and increasing projected annual precipitation and temperature is recorded. The subsequent crop modelling using the CSM-CROPGRO-Canola and DNDC models, fed with the modelled climate trends, highlighted the expectation for near future climate change to cause significant decreases in spring canola production across British Columbia.

Impacts of hydroclimate change on climate-resilient agriculture at the river basin management

Abstract This paper focuses on exploring the potential of Climate resilient agriculture (CRA) for river basin-scale management. Our analysis is based on long-term historical and future climate and hydrological datasets within a GIS environment, focusing on the Ajoy River basin in West Bengal, Eastern India. The standardized anomaly index (SAI) and slope of the linear regression (SLR) methods were employed to analyse the spatial pattern of the climate variables (precipitation, Tmax and Tmin) and hydrological variables (actual evapotranspiration (AET), runoff (Q), vapor pressure deficit (VPD), potential evapotranspiration (PET), and climate water deficit (DEF)) using the TerraClimate dataset spanning from 1958 to 2020. Future climate trend analysis spanning 2021 to 2050 was conducted using the CMIP6 based GCMs (MIROC6 and EC-Earth3) dataset under shared socio-economic pathway (SSP2-4.5, SSP5-8.5 and historical). For spatiotemporal water storage analysis, we relied on Gravity Recovery and Climate Experiment (GRACE) from the Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL) data, covering the period from 2002 to 2021. Validation was performed using regional groundwater level data, employing various machine learning classification models. Our findings revealed a negative precipitation trend (approximately −0.04 mm/year) in the southern part, whereas the northern part exhibited a positive trend (approximately 0.10 mm/year).

Sediment deposition within cascade reservoirs: a case study of Baihetan Reservoir in the lower Jinshajiang River, China

Sediment deposition in cascade reservoirs is not only related to the utilization efficiency of the reservoir itself but also to the boundary conditions for the operation of other reservoirs in the same group. The Baihetan Reservoir is the largest hydropower project with the highest unit capacity in the world, and it is necessary to consider sediment deposition within it, as this affects the comprehensive operation of cascade reservoirs in the lower Jinshajiang River. In this study, the input water, sediment, and deposition characteristics were analyzed based on both field hydrological and topographic data of the Baihetan Reservoir during its initial impoundment period. The results showed that water entering Baihetan Reservoir was mainly derived from the upper main stream, and approximately 41% was concentrated in the third quarter. Ten times the amount of sediment derived from the main stream was received from tributaries and uncontrolled areas of the reservoir, and these are the main sediment input sources. The fluctuating backwater area influenced by the upstream Wudongde Reservoir was slightly eroded, and siltation mainly occurred in the dead storage capacity (below 765 m) of the main stream and tributary estuaries in the perennial backwater area; approximately 15.8 times that in the regulating storage capacity (between 765 and 785 m). The differences between the results of this study and those from the reservoir demonstration stage indicate that was a lack of understanding about how climate change, human activities, and uncontrolled areas would affect siltation patterns. In future projects, research focusing on climate trend analyses and the comprehensive consideration of human activities should be combined with extensive sediment production monitoring and model parameter calibration.

Analysis of climatic trends in climate divisions of Oklahoma, USA

Analysis of climatic trends in climate divisions of Oklahoma, USA

Regional climate trend analyses for Aqua MODIS land surface temperatures

ABSTRACT Land surface temperature (LST) is the skin surface temperature of the Earth’s land surface and is an essential climate variable (ECV) that critically characterizes the Earth’s climate and surface energy processes. This is the first regional trend analysis for LST with uncertainties, using a stable LST climate data record suitable for climate trend analyses: the Aqua Moderate Imaging Spectroradiometer (MODIS) dataset (MYDCCI) produced in the European Space Agency (ESA) LST Climate Change Initiative (LST_cci) Project. The quality of the trends is verified here for Western Europe, for which consistent trends per decade of 0.5 K and 0.57 K across daytime and night-time data, respectively. Eight regions representative of a range of biomes and, including the Amazon, Western U.S.A., Greenland, the Sahel, Siberia, China, India, and Australia, have been analysed. Our most significant findings show substantial LST increases for Siberia and the Amazon, as well as evidence of recent increasing trends for the Western U.S.A. Siberia showed the most substantial daytime and night-time changes per decade of +0.87 K and +0.93 K, respectively. Furthermore, the Amazon and Western U.S.A. showed significant daytime LST trend increases of +0.82 K and +0.51 K, respectively. Western Europe and Western U.S.A. show the largest night-time change of +0.57 K and +0.54 K, respectively. India presents an atypical time series with a decreasing daytime and increasing night-time trend per decade of −0.62 K and +0.44 K, respectively, consistent with reported air temperatures. Overall the results show significant positive regional LST trends, against a background of both strong seasonal cycles and intermittent disruptive events, which demonstrate the importance of continued LST observations. The results also incentivize remote sensing science to derive ever more rigorous LST datasets and to continue to investigate emissivity and error correlations to allow improved trend analyses for smaller regions and individual locations.

Analysis of Climate Variability and Trends for Climate-Resilient Maize Farming System in Major Agroecology Zones of Ethiopia

Maize is one of the most important cereal food crops, and it can be grown all year in various agroecological zones. However, its vegetative growth and yield are susceptible to rainfall and temperature variability. As a result, the analysis of rainfall and temperature variability and trend was urgently needed in maize-growing agroecology zones to restructure the production system. The aim of the study was to examine rainfall and temperature variability and trends for developing a climate-resilient maize farming system in major agroecology zones in northwest Ethiopia. The study was implemented in low productive agroecology zones (LPZ), medium productive agroecology zones (MPZ), and high productive agroecology zones (HPZ) of northwest Ethiopia using daily time series climate data during the period 1987–2018. The coefficient of variation (CV), precipitation concentration index (PCI), rainfall anomaly index (RAI), and standardized precipitation (SPI) were applied to examine rainfall variability. Mann–Kendall’s and Sen’s slope estimator trend tests were used to detecting the statistical significance of changes in rainfall and temperature. Statistically significant increasing trends for annual maximum and minimum temperatures were recorded for all maize-producing agroecology zones. The mean annual temperature has exhibited a significant warming trend of 0.12 to 0.54°C per decade. The average annual rainfall has decreased by 38 to 67 mm per decade in all maize agroecology zones. Our research also showed that droughts now happen every one to three years; even consecutive droughts were seen in 2009, 2010, and 2011. For this reason, it could be required to develop a system of climate-resilient maize farming to address the issues of both global warming and the sub-Saharan countries that make up our study area. Climate-resilient maize agronomic activities have been determined by analyzing the onset, length of the growth period (LGP), and cessation date. Accordingly, the lower and upper quartiles of the date of onset of rainfall were in a range of May 9 to June 2, respectively; the length of the growth period (LGP) during the rainy season ranges from 97 to 232 days, and the cessation date of rainfall was November 1. Therefore, the short- to long-maturing maize varieties can be planted from May 9 to June 2 and can begin to be harvested in the first week of November under the current climatic circumstances.

Time series analysis of climatic variability and trends in Shiwalik to Pir Panjal mountain range in the Indian western Himalaya

Time series analysis of climatic variability and trends in Shiwalik to Pir Panjal mountain range in the Indian western Himalaya

Combining multiple geostatistical analyses to assess the past, present, and future of fragile Mediterranean deltaic environments

Littoral plains in general and those of the Mediterranean rivers and ramblas, are highly vulnerable territories. Understanding the past and present conditions of these areas is the best strategy to design efficient land management plans to prevent degradation such as pollutants, soil sealing, erosion, etc. in the near and medium future. In this research, different mapping techniques (land-use changes in twelve different years using manually digitalisation and field observations, from 1956 to 2019, and pattern analysis using ecological landscape indexes), multivariate statistical analyses (Spearman rank coefficient and Principal Component Analysis), and predictive models (Markov chain) are combined to assess the past, current, and future status of the Vélez River delta (Málaga province, Southern Spain), a representative vulnerable territory situated in the popular touristic area of Costa del Sol. We also included a demographic analysis using annual population census data (current inhabitants and projections) and a climate trend analysis (Mann-Kendall test) considering temperatures, precipitations and wind data. Our results demonstrate that the drastic urbanization, including new settlements, roads, and ways, has negatively impacted the delta area, even the alluvial plain, beaches, and natural sand deposits. From 1956 to 2019, >70 ha of deltaic area have been lost. The largest category of land-use, cultivated fields, accounted for up to 72.4 % of the total delta area in 1984. However, this was reduced to 41.1 % by 2019. The alluvial plain and beaches/sand deposits started from 9.3 and 11.8 %, and decreased to 5.2 and 5.9 %, respectively. Also, climate change (especially in temperature) could affect some spatial patterns. Predictive models reveal that it is likely that abandoned spaces, sand deposits, and beaches, will be transformed into new urban areas and, to a lesser extent, into cultivated fields. We concluded that the conservation of the cultivated lands, although decreasing in the area over the studied period, obtained the highest correlation with the delta conservation. Therefore, we affirm that efficient plans, which promote specific changes in land use, would contribute to stopping the degradation of the delta such as pollution of natural areas or soil sealing. Specifically, a plan should be developed to preserve sustainable agriculture and control urban sprawl.

Variation Characteristics of Temperature and Rainfall and Their Relationship with Geographical Factors in the Qinling Mountains

The Qinling Mountains (QMs) are considered to be the division in geology, geochemistry, and physical geography between northern China and southern China. They have crucial effects on regional climate, especially on rainfall and temperature, and have shown great scientific relevance to climate change research in China. Using the observational daily and monthly rainfall and temperature data derived from meteorological and regional automatic stations—as well as the methods of correlation analysis, climate trend analysis, and Mann–Kendal and t tests—we revealed the spatiotemporal change characteristics of temperature and rainfall and their correlation with elevation, longitude, and latitude. The results show that the annual mean temperature (AMT) underwent a significant increasing trend in the QMs. The maximum AMT increase occurred in spring, and the minimum occurred in summer. Positive anomalies of annual mean rainfall amount (AMRA) occurred in the 1960s, 1980s, and 2010s, and negative anomalies occurred in the 1970s, 1990s, and 2000s. In the QMs, the amount of moderate rainfall (MR) occupied the maximum proportion and accounted for 27.9% of the AMRA, whereas the torrential rainfall (TR) occupied the minimum proportion and accounted for 12.8%. The AMRA amount significantly decreased by 130.1 mm from the 1980s to the 1990s and accounted for 13.5% of the measure in the 1980s. The AMT and AMRA showed consistent change trends with increases in elevation and latitude and showed the opposite trend as the longitude increased. The results offer a further understanding of the meteorological background of the QMs, helping us in further investigating the potential physical mechanisms that influence the spatiotemporal distribution characteristics of temperature and rainfall in the QMs. This study will provide a scientific basis for rainfall and temperature forecasts, with relevance to local ecosystems, agriculture, soil erosion, and the prevention and mitigation of floods in the future.

Impact Of Climate Change In Agricultural Production: A Case Of Koshi River Basin, Nepal

The climatic factor has played dominant role on affecting agricultural production in the region. This study focused on analyzing the impact of Climate change in agricultural production in two districts of Nepal. Sunsari district had experienced the highest annual temperature increased (0.0038°C/yr) during 1990 and 2022, whereas the Saptari district had faced sharp decline in rainfall (11.442 mm/yr). Climate change resulted into climate induced disasters such as recurring drought, catastrophic flooding, mass wasting and emergence of pests. The climate data during 1990 and 2022, was used to find climate trend analysis. The inter-annual climatic patterns across time were examined using the trend analysis test and trend line slope. The HH survey concluded with increased in temperature and crop diseases emergence along with increase in the frequency of pests, drought and floods, and decreased in rainfall as perceived by majority of respondents. These parameters were expected to cause negative effect on crop output, human health, animals and vegetation. An increasing tendency in temperature and declining trend in precipitation were the two main climatic trends that were observed in the study area. Climate trends in Barahakshetra of Sunsari district of the KRB showed an increasing rate of precipitation of 7.8021 mm/year. The linear trend analysis of pre-monsoon time showed the precipitation was increasing at the rate of 3.4424 mm/year. The trend of post-monsoon rainfall increased significantly at the rate of 1.7956 mm/year. The Climatic trends as indicated by Barmajhiya Station in the Saptari district of the KRB showed decreasing rate of annual precipitation with 11.442 mm/year. In Saptari district, the annual production of paddy has been observed in decreasing trend of 1092.9 Mt. per year, with the increasing trend of cultivation area with 673.55 ha per year. The decreasing trend of cultivation area was observed with 17.918 ha per year. The HHs survey ascertained that, the majority of respondents perceived the increased temperature and drought with heavy rainfall and flood in the locality. The springs and ponds were at stake resulting into water scarcity with low discharge in rivers.

Understanding Changes in the Hydrometeorological Conditions towards Climate-Resilient Agricultural Interventions in Ethiopia

Climate resilient agriculture (CRA) is very important to achieve long-term improvement in productivity and farm incomes under climate uncertainty. The present study focuses on investigating the plausible changes in the hydrometeorological conditions using big-data analysis techniques in the study of Ethiopia. The original contribution of this work envisages the importance of the CRA system in water-scarce areas for sustainable agriculture planning and management under changing climatic conditions. In the present research, a TerraClimate model was the basis for weather (precipitation and temperature) and hydrological data (runoff, actual evapotranspiration, potential evapotranspiration, vapor pressure deficit and climate water deficit); these data were used to determine the spatial distribution of the standardized anomaly index (SAI) and the slope of the linear regression for long-term (1958–2020) trend analysis. Future climate trend analysis (2021–2100) has been performed through the CMIP6 (EC-Earth3) shared socio-economic pathway (SSP 2) 4.5 dataset. Gravity Recovery and Climate Experiment (GRACE) with CSR and JPL data were utilized for the generation of water storage heat maps from 2002 to 2021. The results show that the average annual rainfall data for over 62 years was found to be 778.42 mm and the standard deviation is 81.53 mm. The results also show that the western part of the study area has the highest temperature trend, which diminishes as one moves eastward; the minimum temperature trend has been found in the western part of the study area. It was found that the equivalent water thickness (EWT) range of both CSR and JPL products was −15 to 40 cm. These results can help local climate-resilient development planning and enhance coordination with other institutions to access and manage climate finance.