Annual Time Series Research Articles

Investigating Uncertainty of Future Predictions of Temperature and Precipitation in The Kerman Plain under Climate Change Impacts

Climate change affects hydroclimatic variables, and assessing the uncertainty in future predictions is crucial. This study aims to explore variations in temperature and precipitation in the Kerman Plain under climate change impacts between 2023 and 2054. For this purpose, two climate models, MRI-ESM-2 and BCC-CSM2-MR, were used to simulate precipitation and temperature under two different scenarios. The Mann–Kendall test was employed to analyze the annual time series in the future period. The results indicated an increase in the average temperature of about 1.5 degrees Celsius based on both scenarios in the coming years. Furthermore, an average annual increase of 6.37 mm of precipitation was predicted under the SSP585 scenario. Meanwhile, under the SSP585 scenario, an increase was estimated using the MRI-ESM-2 model, and a decrease was predicted with the BCC-CSM2-MR model. The Mann–Kendall test revealed a downward trend in the BCC-CSM2-MR model under both scenarios and an upward trend in the MRI-ESM-2 model under both scenarios. The bootstrap method and the R-factor index were exploited in this study with a 95% confidence interval to estimate the uncertainty of the predicted data. The results demonstrated that the predicted precipitation is more uncertain than the temperature. Finally, it is postulated that the obtained results provide necessary information for water resource management under a changing climate in the study area.

Foreign direct investment, foreign aid and economic growth nexus in Kenya

The increasing role of foreign capital inflows in reducing the disparity between government revenues and costs as well as impellent economic growth has motivated this study to establish the direction of causality between foreign direct investment (FDI), foreign aid, and economic growth in Kenya. By using annual time series data from 1970 to 2020 within bounds testing approach to cointegration and the error correction model ECM-based Granger-causality, the study found a bidirectional causality between foreign aid and economic growth in the short run and a unidirectional causal flow from foreign aid to economic growth in the long run. The results also support evidences of bidirectional causality between FDI and foreign aid in the short run and a unidirectional causal flow from foreign aid to FDI in the long run. However, the study found no causal relationship between FDI and economic growth, irrespective of whether the causality test is conducted in the short run or in the long run. These empirical findings are encouragement to policy makers in Kenya to carefully channel foreign aid in productive sectors to positively influence economic growth and foreign direct investment, as most relevant targets in achieving Vision 2030 and the Sustainable Development Goals (SDGs).

Finding Causality Between Finance and Growth in Bangladesh

The relationship between financial development and economic growth has gained much attention in the last three decades. It has been primarily believed that financial sector development promotes economic growth. A lot of theoretical and empirical research has been done in this field and the results which came out are a kind of mixed relationship between the two. Bangladesh, a country in the SAARC region has taken different financial reform policies in the same line with other developed and developing countries. The main purpose of this paper is to investigate the relationship between financial development and economic growth in Bangladesh. Annual time series data for the period 1976 to 2020 has been taken and the ARDL technique has been used for this purpose. The ARDL bound testing shows that there is a long-run relationship between financial development variables and economic growth. In the short run, all the proxies of financial development were found to have a significant relation to economic growth. The study has found two bidirectional causality and one unidirectional causality between the variables.

Impact of environmental fiscal reforms on carbon emissions of EURO-4 countries: CS-NARDL approach

This study investigates the effects of the Environmental Fiscal Reforms (EFR) policy on carbon emissions of the top 4 economies of Europe, using annual time series data from 1995 to 2022. The study used a cross-sectional nonlinear autoregressive distributed lag (CS-NARDL) model to examine the relationship. Estimates claim that the variables have an asymmetric long-term and short-term relationship. The negative impacts of carbon taxes on carbon emissions prove that emissions are reduced when polluting activities are taxed. Fiscal policy instrument such as taxation changes the behaviour of the private sector by disincentivizing polluting activities. On the other hand, government expenditure on environmental protection encourages the private sector to embrace and invest in green technologies, decreasing carbon emissions. The ECM term is negative and statistically significant at a 1 percent significance level for CS-NARDL model, implying a stable long-run relationship between variables. It demonstrates that short-run disequilibrium converges to long-run equilibrium at a speed of 47.2 percent. The study also propels new insight into the effectiveness of EFR policy, showing that taxes act as a counter-incentive and expenditure as a positive policy intervention for reducing carbon emissions. EURO-4 countries set an example for policymakers worldwide by rebalancing their energy mix and expanding the use of cleaner alternative energy sources.

CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland

Abstract. We present CAMELS-CH (Catchment Attributes and MEteorology for Large-sample Studies – Switzerland), a large-sample hydro-meteorological data set for hydrologic Switzerland in central Europe. This domain covers 331 basins within Switzerland and neighboring countries. About one-third of the catchments are located in Austria, France, Germany and Italy. As an Alpine country, Switzerland covers a vast diversity of landscapes, including mountainous environments, karstic regions, and several strongly cultivated regions, along with a wide range of hydrological regimes, i.e., catchments that are glacier-, snow- or rain dominated. Similar to existing data sets, CAMELS-CH comprises dynamic hydro-meteorological variables and static catchment attributes. CAMELS-CH (Höge et al., 2023; available at https://doi.org/10.5281/zenodo.7784632) encompasses 40 years of data between 1 January 1981 and 31 December 2020, including daily time series of stream flow and water levels, and of meteorological data such as precipitation and air temperature. It also includes daily snow water equivalent data for each catchment starting from 2 September 1998. Additionally, we provide annual time series of land cover change and glacier evolution per catchment. The static catchment attributes cover location and topography, climate, hydrology, soil, hydrogeology, geology, land use, human impact and glaciers. This Swiss data set complements comparable publicly accessible data sets, providing data from the “water tower of Europe”.

Inter- and intra-year forest change detection and monitoring of aboveground biomass dynamics using Sentinel-2 and Landsat

National aboveground forest biomass products enable monitoring of biomass dynamics in a consistent and repeatable manner to inform carbon accounting and sustainable forest management activities. The availability of images of the Earth's surface from a combination of Landsat and Sentinel-2A and -2B provides an opportunity and capability to track intra-year biomass dynamics availing upon a twice weekly acquisition opportunity. We developed an algorithm that leverages these spatially and spectrally compatible data sources, called Tracking Intra- and Inter-year Change (TIIC), to monitor forest change across Canada's forested ecozones (>650Mha) in near-real time. Combining the stand-replacing change information from TIIC with spatially explicit maps of aboveground biomass (AGB), we demonstrate how intra-annual and inter-annual AGB dynamics, including losses due to stand-replacing disturbances and gains from vegetation growth, can be quantified temporally and spatially. Using independent validation data, our results for the focus year 2019 indicate that TIIC, by analysing images from May 30 to September 1, can accurately detect stand-replacing disturbances across Canada's forested ecozones with an overall accuracy of 99% and correctly attribute the type of change (i.e., wildfire or mechanical removal, the latter of which includes timber harvesting) with an overall accuracy of 99%. From an initial producer's accuracy of 23% for the changed class, accuracy increases incrementally as additional images are added throughout the growing season. attaining a producer's accuracy of 98% by the end of the analysis period. Intra-year change information complements information on long-term trends derived from annual time series monitoring over several decades. Our analysis of AGB dynamics indicated that in every ecozone, widespread small positive AGB increments yielded overall AGB gains that were greater than the sum of the large, punctual AGB losses resulting from stand-replacing disturbances. Overall in 2019, forest AGB increased across Canada's forested ecozones by 2.54%. Temporally, 80% of AGB losses stemming from mechanical removal occurred over the winter and are as such concentrated at the beginning of the growing season. In contrast, AGB losses linked to fires happen more stochastically throughout the growing season and occupy a greater area. By way of disturbance type, 36% of 2019 AGB loss was attributed to mechanical removal, and 64% was attributed to wildfire. Following the approach demonstrated herein, AGB changes can be tracked at a temporal frequency informative of forest management practices and ecological processes on the landscape, thereby refining our understanding of AGB dynamics.

The Effect of Mining, Manufacturing and Agricultural Foreign Direct Investment on Economic Growth of Tanzania

This study assessed the effect of foreign direct investment (FDI) inflow on economic growth in Tanzania. Specifically, the study sought to establish whether FDI from mining, manufacturing and agriculture sectors significantly impact economic growth in Tanzania. The study used annual time series data covering twenty-one (21) years from 2000 through 2020. The data were obtained from the Tanzania Bureau of Statistics, Bank of Tanzania, and World Bank Reports. The study employed an autoregressive distributed lag (ARDL) bounds co-integration test to capture the long-run and the causal links among the variables of interest. Findings from co-integration test indicates a long-run interrelationship among the variables of interest. Furthermore, results from both short-run and long-run estimates show that both FDI inflows from the mining sector had a positive and significant effect on economic growth, while FDI inflows in manufacturing and agricultural sectors had a negative and statistically significant effect on economic growth in the case Tanzania over the period under the study. The results imply that the government should design comprehensive policies that will continue attracting more FDI in the mining sector without compromising the impact of FDI from other sectors

Geo-statistical analysis of climatic variability and trend detection in the Hindu Kush region, North Pakistan.

This paper is an effort of geo-statistical analysis of rainfall variability and trend detection in the eastern Hindu Kush region located in the north-west of Pakistan. The eastern section of the HK region lies in the western part of Pakistan. Exploring rainfall variability and quantifying its trend and magnitude is one of the key indicators among all climatic parameters. In the study area, Pakistan Meteorology Department (PMD) has established seven meteorological stations: Drosh, Chitral, Dir, Timergara, Saidu Sharif, Malam Jabba, and Kalam. Daily, mean monthly, and mean annual rainfall time series data for all the met stations were geo-statistically analyzed in the GIS environment for detecting monthly and annual variability in rainfall, variability, and trend detection. Mann-Kendall (MK) and Theil-Sen's slope (TSS) statistical tests were applied to rainfall data. Initially, the MK test was applied for detection of trends and TSS test was used to quantify the change in magnitude. The results indicate that the rainfall variability in intensity and trend pattern detection. The analysis confirms that an extremely significant rainfall trend in the case of mean annual rainfall was predicted at Dir and Malam Jabba meteorological stations. Opposite to this, at Kalam and Chitral stations, a less significant rainfall trend was noted. In a similar context, no prominent rainfall trend has been found at Drosh, Timergara, and Saidu Sharif meteorological stations. Likewise, using TSS, an extremely negative variation in the magnitude of rainfall was verified at Kalam and Malam Jabba. However, a noteworthy positive change in rainfall magnitude has been noted at Dir and Saidu Sharif meteorological stations. The findings of this research have the potential to assist the decision and policy makers and academicians to think truly and conduct more scientific research studies to mitigate climate change.

Contribution of Indirect Taxes on Goods to Economic Growth of Pakistan (1972-2022)

PURPOSE Economic growth is influenced by the changes in indirect taxes imposed by the government on the production/consumption of goods. This paper aims to identify the empirical relationship between indirect taxes – i.e., federal sales tax, federal excise duty, and customs duty – and the economic growth of Pakistan. METHODOLOGY For this purpose, annual time series data from 1972 to 2018 are used. The objective of the study is to evidence the long-run and short-run relationships of federal sales tax, federal excise duty, and customs duty with economic growth. The Augmented Dickey-Fuller unit root tests are used to check the stationarity of each variable. The Johansen Cointegration Test is performed to identify the cointegration among variables. The Vector Error Correction Model (VECM) is used to estimate the long-run and short-run relationships among these variables. FINDINGS The results of the study show that there are two cointegrating equations among variables. GDP Lag5, GDP Lag6, ST Lag1, ST Lag5, and FE Lag4 possess a positive impact on the economic growth of Pakistan. However, GDP Lag2, FE Lag6, and CD Lag7 have a negative impact on the economic growth of Pakistan. Previous years’ deviations from long-run equilibrium are corrected in the current year at an adjustment speed of 33% and 18% for GDP and ST, respectively. CONTRIBUTION/IMPLICATIONS Since the sales tax has a positive impact on economic growth, whereas federal excise duty and customs duty have a negative relation, it is advisable to form policies that contribute to economic growth instead of restricting it. As of the published statistical records of 2018, sales tax, federal excise duty, and customs duty contribute 65 per cent, 9 per cent, and 26 per cent, respectively, to the total indirect taxes. This collection structure is required to be rationalised to boost economic growth.

Foreign Exchange Market Pressure, Exchange Rate and Trade Balance in Nigeria: Is There Evidence of the J-Curve Effect?

The paper examined the relationship between the pressure in the exchange market, exchange rate, and trade balance in Nigeria to ascertain whether or not the J-Curve effects exist. The investigation was anchored on the Marshal-Lerner and the J-Curve theories using annual time series data from 1986 to 2021. The Structural Vector Autoregressive (SVAR) technique was employed, and the findings revealed that the pressure in the exchange market exerts a strong contemporaneous positive effect on the exchange rate in the country. Also, the findings showed that the exchange rate has a strong contemporaneous negative effect on the trade balance. Furthermore, the long-run results indicated that the exchange rate has a positive but weak effect on the country’s trade balance. Based on these findings, it was concluded that the relationship that exists among foreign exchange market pressure, exchange rate, and balance of trade suggests the potentiality of the J-Curve effects in the economy. The study recommended that local production of goods and services in Nigeria should be strengthened so that the depreciation of the naira would improve the trade balance. In the event of naira depreciation, domestic consumers could redirect their demand to the consumption of locally produced goods and services. Also, local production, especially in manufacturing and agricultural processing, should be encouraged, and the quality of the products be enhanced for competitive exportation to improve the trade balance in the country. The policy implication is that policymakers can leverage naira depreciation as a policy tool to enhance Nigeria’s balance of trade.

Leveraging Islamic Economic To Alleviate Poverty In Indonesia : A Promising Pathway

This empirical study explores the relationship between Islamic banking development, social justice promotion, and poverty reduction in Indonesia, using annual time series data from 1991 to 2021.. Methodology/approach The analysis encompasses unit root tests, Johansen cointegration tests, and Vector Error Correction Models (VECM) to assess short and long-term causality among the variables. The results provide robust evidence that expanding Islamic financial institutions and increasing spending on Islamic philanthropy significantly contribute to reducing national poverty levels over both the short and long-run. Islamic finance, characterized by equity-based principles, facilitates financial access for marginalized groups, while instruments of Islamic philanthropy such as zakat and sadaqah directly assist the disadvantaged, enabling pathways out of poverty. Findings – The findings underscore the potential of Islamic economics to foster equitable, inclusive, and sustainable growth, validating the need for policy support to harness its impact

THE INFLUENCE OF EDUCATION ON COMMUNITY INCOME GAPS:A CASE STUDY IN THE EAST JAVA REGION

Education is one of the main factors that causes income inequality in society.This study aims to investigate the impact of education on income inequality in East Java. The testing method in this study uses a quantitative method by using annual time series data from the education index and Gini ratio in the districts/cities of East Java as the research sample. According to the results of the study, education has a significant correlation with income. A person with a high level of education is more likely to earn a high income. This is due to several factors, including: increased productivity, increased access to employment, and increased social mobility, as education can help someone improve their social status. Therefore, this study is expected to help the government improve access and quality of education in East Java, this is important to reduce income inequality. By understanding the relationship between education and income, the government can design more effective and sustainable policies for the economic development of East Java.

Pengaruh Sistem Pembayaran Elektronik Terhadap Permintaan Uang Di Indonesia Dalam Perspektif Ekonomi Islam

Along with the development of technology and information, the payment system used as a medium of exchange in economic activities continues to change. Current economic transactions do not only use cash but also use electronic non-cash instruments which are more efficient and economical. The purpose of this study was to determine the effect of APMK (debit cards, credit cards) and electronic money on the amount of money demanded. This study uses secondary data sourced from Bank Indonesia and the Central Bureau of Statistics. The data used is annual time series data from 2018 to 2022. The analysis technique used in this study uses multiple linear regression analysis techniques. The results obtained in this study indicate that transactions using debit cards, credit cards and electronic money simultaneously have a significant effect on the amount of money demanded. Viewed partially, debit cards, credit cards and electronic money do not have a significant effect on the amount of money demanded .

Does higher tax rate affect tobacco usage? Unravelling the nexus between tobacco regulatory control and public health concern

ObjectivesBangladesh stands as a prominent global consumer of tobacco, with alarming consequences on public health. The Global Adult Tobacco Survey reported that tobacco consumption claimed over 126 000 lives in 2018, contributing to 13.5% of all deaths in the country. This study aims to explore the effectiveness of higher tax rates and tobacco use regulation as control mechanisms in mitigating tobacco consumption and health care cost burden, with a particular emphasis on its implications for public health. MethodsThis study is based on the annual time series data over the period 2000–2020. The study employs the ordinary least square method to analyze the quantitative confirming the stationarity of data at level. This research uses different models to investigate individual effects and combined effects on both tobacco consumption and tobacco health care cost burden. ResultsThe study finds a negative relationship between tobacco tax rate and tobacco consumption. More specifically, the higher tax rate of tobacco (low (β = −0.3495), medium (β = −0.2319), high (β = −0.9033), premium (β = −0.7322), filtered (β = −0.2114), and non-filtered (β = −0.3452) categories) is significant to reduce tobacco use at 1% level of significance. The study finds similar results when it applied tobacco retail price instead of tobacco tax rate as the independent variable. Finally, the study investigates the impact on health care cost through tobacco consumption, tobacco control law, growth rate, export-import, and tobacco production. The results indicate that tobacco consumption, export-import, and tobacco production increases health care cost burden while tobacco use regulatory decreases it. By reducing tobacco consumption, higher taxes and tobacco use regulation contribute to alleviating the burden on the healthcare system, promoting healthier lifestyles, and aligning with global health objectives. ConclusionsHigher tax rate on tobacco products is necessary to increase the retail price so that tobacco users cannot consume tobacco. Specific tax and uniform tax base are needed so that tobacco users cannot switch to lower priced brands. Tobacco control laws need to revised and proper implementation should be ensured as well, to achieve the goal of tobacco free Bangladesh by 2040. Tobacco-related diseases, responsible for a significant proportion of deaths in the country, could witness a considerable decline with the successful implementation of higher tax rates and tobacco use regulation. This study provides insights that not only contribute to the economic discourse but also accentuate the broader public health benefits arising from effective tobacco taxation policies.

The Effects of Demographic Change on GDP Growth: Research Focus on Russia

There has been a downward trend in economic growth in several economies over the past few decades, with the slowdown trend particularly evident in the case of Russia. These records estimate how much of this growth slowdown can be accounted for by demographic changes. Specifically, this study estimated how a changing age structure of the population (between four groups-ages 0-14, 15-64, and 65+) has affected GDP growth using annual time series data for Russia. The analysis is applied using the Bayesian VAR model. The data for the study are obtained from the World Bank. It was found that demographic changes account for a significant portion of the downward trend in the economic growth of Russia during the past decade. Moreover, the continuation of the demographic shift toward an older population is likely a valuable factor that has increased GDP growth in Russia over the last couple of decades. The research results point out that during the last decade; demographic effects have not had any significant influence on the change of GDP growth levels in Russia. Therefore, the research study contributes in a way indicating that future growth of GDP in Russia will depend much more on the growth of structural productivity, new technologies and worker profitability and much less on demographic changes.

EFFECT OF FORMAL EDUCATION ON POVERTY REDUCTION IN NIGERIA

This study analyzes the impact of formal education on poverty reduction in Nigeria by studying the relationship between government expenditure on education, school enrolment, and labour force participation. It uses 30 years of annual time series data and employs various statistical methods, such as OLS regression, ADF test, Philip Peron unit root test, F-tests, and t-tests. Labour force participation serves as a proxy to understand how these macroeconomic variables affect poverty. The findings reveal that both school enrolment and government expenditure on education significantly affect labour force participation. Specifically, enrolment in secondary and tertiary education positively correlates with increased labour force participation. To enhance poverty reduction in Nigeria, the study proposes improving the effectiveness of government expenditure, enhancing access to quality secondary and tertiary education, fostering collaboration between education and businesses, and emphasizing vocational and technical education aligned with the labour market’s needs.

The Influence of economic growth, exchange rate, and inflation on foreign tourist visits to Indonesia

Tourism is one of the economic sectors that can quickly bring in foreign exchange for the country if managed properly and sustainably. Many economic variable factors influence the demand and supply of the tourism industry, especially the level of foreign tourist visits, such as economic growth, exchange rate, and inflation. This study aimed to determine the influence of economic variable factors, especially economic growth, exchange rate, and inflation, on the number of foreign tourist visits in Indonesia. A quantitative descriptive method is used in this study. To analyze the factors influencing the number of foreign tourist visits in Indonesia, independent variables such as economic growth, exchange rate, and inflation are used in the Multiple Linear Regression equation model. The data used in this study is secondary data on annual time series for the period 2001 – 2020. The research result shows that the number of foreign tourist visits in Indonesia is significantly influenced by economic growth and the exchange rate, while inflation has no significant effect. There are still other factors (non-economic) that influence the decision of tourists to visit. Several factors that need to be considered to increase the interest of foreign tourists visits in Indonesia are tourist attractions, accessibility, amenities, ancillary, attractive promotions, and social, political, and security stabilityJEL Classification A13; B55; D69

Impacts of external factors on Ethiopia's economic growth: Insights on foreign direct investment, remittances, exchange rates, and imports

This study conducts a rigorous examination of relationships that are often assumed but rarely tested within the context of Ethiopia's journey towards sustainable development. An autoregressive distributed lag model is employed using annual time series data from 1982 to 2021 to investigate the short- and long-term impacts of foreign direct investment (FDI), remittances, real exchange rates, and imports on Ethiopia's economic growth. By incorporating additional control variables, this study contributes nuanced insights that were previously lacking in the literature. The findings reveal intriguing patterns that both align with and deviate from existing frameworks. Contrary to some prior studies, foreign investment consistently emerges as a significant driver of economic growth over time. However, remittances demonstrate only transient significance, highlighting the need for cautious policy considerations. The influence of exchange rates on economic growth proves to be unexpectedly complex and nonlinear, challenging conventional assumptions. The empirical validation of these multifaceted realities underscores the importance of this analysis. Furthermore, robustness tests conducted in this study confirm the reliability of the findings while shedding light on additional intricacies. For instance, the relationship between imports and growth is context-dependent and exhibits ambiguities that call for careful consideration. The theoretical and practical implications derived from this research offer valuable insights for researchers and policymakers alike. The recommendations put forth emphasize the promotion of sustained prosperity through evidence-based strategies that prioritize community development.

Variability in Global Climatic Circulation Indices and Its Relationship

Global climatic circulation indices play a major role in determining regional and global climate conditions. These atmospheric circulation patterns exhibit substantial variability, covering a wide geographical area and affecting weather-related events. The primary goal of this study was to examine and characterize various global climatic variability indices during the 1950 to 2020 period (El Niño Southern Oscillation, ENSO; Southern Oscillation Index, SOI; North Atlantic Oscillation, NAO; Atlantic Meridional Mode, AMM; and Indian Ocean Dipole, IOD). Also, this article try to investigating the link between these global climatic indices. Trend analysis showed that the ENSO index exhibits the highest recurrence frequency of correlation relationships with the other yearly global indices with significance at the 95% and 99% levels, while the NAO index exhibits the lowest recurrence frequency. On a seasonal basis, most indices demonstrate more abrupt changes during the winter season than during the summer. An increase occurred in events of abrupt changes in these indices over the last two decades (2000 to 2020), especially annually and in summer. The SOI exhibits the largest number of abrupt changes throughout the entire study period, spanning from positive to negative significant trends, whereas the IOD did not exhibit abrupt changes annually. Increasing and decreasing trends in the global climatic circulation indices may be related to natural and anthropogenic causes of climate change. Regarding both the correlation coefficient (CC) and partial correlation results, there existed a highly negative association between the ENSO and SOI in the annual, winter and summer time series. On the other hand, there is no relationship between ENSO and NAO. Furthermore, on an annual basis, there existed a highly negative association between the NAO and AMM and a less negative but still statistically significant association between these indices during the winter and summer seasons, respectively. Therefore, through the Azore high, the NAO could promote AMM. Moreover, when the NAO, AMM, and SOI are held constant, a positive and robust correlation is reached between the ENSO and IOD in winter season. Therefore, a developing IOD is intensified and sustained during the onset of an El Niño event in winter season.

Assessment of multi-source satellite products using hydrological modelling approach

Multi-source satellite products performance evaluation for varied geographical locations aids in quantification of hydrological variables and is useful in the strategy making and conservation of the hydrological resources available in a basin. The work was focused on assessing utility of multi-source satellite datasets to obtain the estimation of hydrologic variables and provide solution for areas that are poorly gauged. Assessment of the multi-source-satellite products was performed for the poorly gauged river basin with the help of SWAT concerning the Palar River basin, India. We analysed time series at the monthly, seasonal, and annual scales to quantify surface runoff, water yield, ET, & PET at the calibration station and for the entire basin for the period 2003 to 2021. SWAT model estimated highest monthly water yield during November–December, with annual water yield being maximum (220 mm in 2010) and average (99.4 mm), which can be used to understand water resources for irrigation, drinking aspects, and net storage. Average monthly surface runoff patterns were similar for SWAT, TerraClimate, and FLDAS. The FLDAS and SWAT simulated surface runoff show a resemblance in pattern and magnitude for the monthly and annual time series of the average basin scenario. The monthly PET obtained from SWAT and ERA-5 show a similar pattern for the entire basin and at the calibration site. The ET derived from satellite observation has over-predicted the model output at both the calibration site and entire basin.