Scinovex

Research article · 2026 · Full text

International Journal of Geography Geology and Environment

Geographical Study of the Impact of Climate Uncertainty on Agricultural Productivity in Latur District (2015-2026)

Arjun Keshav KatkeProf. Dr. Satish D. Gavit

Volume 8(8) · Pages 79–82 · DOI: 10.22271/27067483.2026.v8.i8a.852 ↗

Research areasClimate change impacts on agricultureAgricultural Economics and PracticesAgricultural risk and resilience

↓ Read full-text PDF0 citations

Abstract

Author-written

Latur district, located in the Marathwada region of Maharashtra, is one of the most drought-prone districts in the state. Agriculture in the district is predominantly rainfed; therefore, climatic uncertainty—manifested through fluctuations in rainfall, recurring droughts, and rising temperatures—has a direct impact on agricultural productivity. This study examines the nature of climate uncertainty and its geographical impact on agricultural productivity during the period from 2015 to 2026.The study is based on secondary data collected from District Socio-Economic Reviews, rainfall records, and Agricultural Production Index (API) statistics. Statistical analysis reveals a strong positive correlation (r = 0.84) between annual rainfall and the Agricultural Production Index. During severe drought years such as 2015 and 2021, the API declined by approximately 20-30 percent. Major crops, including soybean, pigeon pea (tur), and sugarcane, were the most adversely affected. Furthermore, the farmer suicide rate exhibited a strong negative correlation with rainfall (r = -0.95), indicating increased socio-economic distress during drought years.The study highlights the urgent need to promote drought-resilient crops, strengthen watershed management practices, and formulate climate-resilient agricultural policies to ensure sustainable agricultural development in Latur district.

Summary

Source-checked

Plain-language reading of the full paper, prepared with AI and checked against the text. Each point links to the authors' own words.

  1. Why it matters

    • Latur district in Maharashtra's Marathwada region is highly susceptible to drought. View evidence ↗

      Why it matters

      Latur district in Maharashtra's Marathwada region is highly susceptible to drought.

      In the paper's own words

      “Latur district, located in the Marathwada region of Maharashtra, is one of the most drought-prone districts in the state.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Over 70% of the district's agriculture depends on rainfall, making it vulnerable to climatic fluctuations. View evidence ↗

      Why it matters

      Over 70% of the district's agriculture depends on rainfall, making it vulnerable to climatic fluctuations.

      In the paper's own words

      “More than 70 percent of agriculture in the district is rainfed.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
    • Studying climate uncertainty is critical because it directly affects the rural economy and the livelihoods of farmers. View evidence ↗

      Why it matters

      Studying climate uncertainty is critical because it directly affects the rural economy and the livelihoods of farmers.

      In the paper's own words

      “The significance of this study lies in its close association with farmers' livelihoods and the rural economy.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  2. The question

    • The study aims to analyze how climate uncertainty impacted agricultural productivity in Latur district between 2015 and 2026. View evidence ↗

      The question

      The study aims to analyze how climate uncertainty impacted agricultural productivity in Latur district between 2015 and 2026.

      In the paper's own words

      “This study examines the nature of climate uncertainty and its geographical impact on agricultural productivity during the period from 2015 to 2026.”

      Page 1

      Found in: Introduction

      Read it in the full textOpen PDF at page 1 ↗
  3. What they did

    • The research used secondary data from government reviews, economic surveys, and agricultural reports. View evidence ↗

      What they did

      The research used secondary data from government reviews, economic surveys, and agricultural reports.

      In the paper's own words

      “The present study is based entirely on secondary data. Data were collected from the District Socio-Economic Review (2010-11 to 2024-25), the Economic Survey of Maharashtra, reports of the Department of Agriculture, and published research papers.”

      Page 2

      Found in: Introduction

      Read it in the full textOpen PDF at page 2 ↗
    • Pearson's Correlation Coefficient was used to determine the relationship between annual rainfall and agricultural productivity. View evidence ↗

      What they did

      Pearson's Correlation Coefficient was used to determine the relationship between annual rainfall and agricultural productivity.

      In the paper's own words

      “The Pearson's Correlation Coefficient (r) was employed to examine the relationship between rainfall and agricultural productivity.”

      Page 2

      Found in: Impact on Agricultural Productivity

      Read it in the full textOpen PDF at page 2 ↗
    • The analysis focused on three primary metrics: annual rainfall, the farmer suicide rate, and the Agricultural Production Index (API) with a 2010 base year of 100. View evidence ↗

      What they did

      The analysis focused on three primary metrics: annual rainfall, the farmer suicide rate, and the Agricultural Production Index (API) with a 2010 base year of 100.

      In the paper's own words

      “Information on annual rainfall, the Agricultural Production Index (API, base year 2010 = 100), and the farmer suicide rate was used for analysis.”

      Page 2

      Found in: Introduction

      Read it in the full textOpen PDF at page 2 ↗
  4. What they found

    • There is a strong positive correlation (r = 0.84) between annual rainfall and the Agricultural Production Index, meaning higher rainfall generally increases productivity. View evidence ↗

      What they found

      There is a strong positive correlation (r = 0.84) between annual rainfall and the Agricultural Production Index, meaning higher rainfall generally increases productivity.

      In the paper's own words

      “The statistical analysis reveals a strong positive correlation (r = 0.84) between annual rainfall and the Agricultural Production Index (API) in Latur district.”

      Page 3

      Found in: Impact on Agricultural Productivity

      Read it in the full textOpen PDF at page 3 ↗
    • In years of severe drought, the Agricultural Production Index dropped by roughly 20-30%. View evidence ↗

      What they found

      In years of severe drought, the Agricultural Production Index dropped by roughly 20-30%.

      In the paper's own words

      “During severe drought years, the Agricultural Production Index declined by approximately 20-30 percent.”

      Page 3

      Found in: Impact on Agricultural Productivity

      Read it in the full textOpen PDF at page 3 ↗
    • Water-intensive crops, specifically sugarcane, soybean, and pigeon pea (tur), suffered the most severe productivity losses. View evidence ↗

      What they found

      Water-intensive crops, specifically sugarcane, soybean, and pigeon pea (tur), suffered the most severe productivity losses.

      In the paper's own words

      “Water-intensive crops such as soybean, pigeon pea (tur), and sugarcane were the most severely affected.”

      Page 3

      Found in: Impact on Agricultural Productivity

      Read it in the full textOpen PDF at page 3 ↗
    • A strong negative correlation (r = -0.95) exists between rainfall and farmer suicide rates, indicating that lower rainfall is associated with higher suicide rates. View evidence ↗

      What they found

      A strong negative correlation (r = -0.95) exists between rainfall and farmer suicide rates, indicating that lower rainfall is associated with higher suicide rates.

      In the paper's own words

      “The study found a strong negative correlation (r = -0.95) between annual rainfall and the farmer suicide rate.”

      Page 3

      Found in: Socio-Economic Impacts

      Read it in the full textOpen PDF at page 3 ↗
    • The number of hot days (above 32°C) increased from 147 days in 1960 to 188 days by 2019. View evidence ↗

      What they found

      The number of hot days (above 32°C) increased from 147 days in 1960 to 188 days by 2019.

      In the paper's own words

      “In 1960, the district experienced 147 days with temperatures above 32°C, whereas this number increased to 188 days by 2019.”

      Page 3

      Found in: Temperature and Other Climatic Factors

      Read it in the full textOpen PDF at page 3 ↗
    • Groundwater levels have dropped significantly, with some wells now exceeding 600 meters in depth. View evidence ↗

      What they found

      Groundwater levels have dropped significantly, with some wells now exceeding 600 meters in depth.

      In the paper's own words

      “groundwater levels have declined considerably, and the depth of several wells has exceeded 600 metres”

      Page 3

      Found in: Temperature and Other Climatic Factors

      Read it in the full textOpen PDF at page 3 ↗
  5. What it means

    • The authors conclude that climate uncertainty significantly reduced agricultural productivity in Latur district from 2015 to 2026. View evidence ↗

      What it means

      The authors conclude that climate uncertainty significantly reduced agricultural productivity in Latur district from 2015 to 2026.

      In the paper's own words

      “The present study concludes that climate uncertainty had a significant negative impact on agricultural productivity in Latur district during the period 2015-2026.”

      Page 4

      Found in: Conclusion and Recommendations Conclusion

      Read it in the full textOpen PDF at page 4 ↗
    • The authors recommend promoting drought-resistant crops like pearl millet (bajra), sorghum (jowar), and indigenous pulses. View evidence ↗

      What it means

      The authors recommend promoting drought-resistant crops like pearl millet (bajra), sorghum (jowar), and indigenous pulses.

      In the paper's own words

      “Promote the cultivation of drought-resistant crops, such as sorghum (jowar), pearl millet (bajra), and indigenous pulse crops.”

      Page 4

      Found in: Introduction

      Read it in the full textOpen PDF at page 4 ↗
    • The authors suggest that future research should use GIS, remote sensing, and climate modeling to improve the accuracy of impact assessments. View evidence ↗

      What it means

      The authors suggest that future research should use GIS, remote sensing, and climate modeling to improve the accuracy of impact assessments.

      In the paper's own words

      “Future studies may utilize remote sensing, Geographic Information Systems (GIS), and climate modelling techniques to improve the accuracy of climate impact assessments.”

      Page 4

      Found in: Temperature and Other Climatic Factors

      Read it in the full textOpen PDF at page 4 ↗

Visual summary

3 visuals

Illustrations explain the paper; charts are replotted from the paper's own table values.

AI-generated illustration
AI-generated conceptual illustration (Sorghum and soybean crops in the Latur District landscape). It explains the idea and does not show study data.↗ Enlarge
Climate-Productivity-Social Linkage
AI-generated conceptual illustration (Sorghum and soybean crops in the Latur District landscape). It explains the idea and does not show study data.

AI-generated conceptual illustration (Sorghum and soybean crops in the Latur District landscape). It explains the idea and does not show study data.

Open full-size image ↗

Climate-Productivity-Social Linkage

AI-generated conceptual illustration (Sorghum and soybean crops in the Latur District landscape). It explains the idea and does not show study data.

View source evidence ↗
Replotted from source data
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Rainfall (mm) and API (Base Year 2010 = 100): 2015 vs 2016 vs 2017 vs 2018 vs 2019
Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Rainfall (mm) and API (Base Year 2010 = 100): 2015 vs 2016 vs 2017 vs 2018 vs 2019

Replotted from Table 1 (page 2) of the original paper. Every bar is the paper's own table value.

View source evidence ↗
Replotted from source data
Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.↗ Enlarge
Farmer Suicide Rate: 2015 vs 2016 vs 2017 vs 2018 vs 2019
Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

Open full-size image ↗

Farmer Suicide Rate: 2015 vs 2016 vs 2017 vs 2018 vs 2019

Replotted from Table 2 (page 3) of the original paper. Every bar is the paper's own table value.

View source evidence ↗

Figures & tables

From the original paper
Latur District - Annual Rainfall, Agricultural Production Index (API), and Drought Status (2015-2026)Table 1Page 2Farmer Suicide Rate in Latur District (Per 100,000 Population)Table 2Page 3
FULL TEXT Original article · reflowed for reading

Introduction

Climate change and the resulting climate uncertainty have emerged as major global challenges for the agricultural sector. As India is predominantly an agrarian country, agriculture largely depends on the monsoon. The Marathwada region of Maharashtra is particularly drought-prone, and Latur district is one of the most vulnerable districts in this region. More than 70 percent of agriculture in the district is rainfed. Consequently, irregular rainfall, frequent droughts, and rising temperatures have led to significant fluctuations in agricultural productivity. During the period from 2015 to 2026, Latur district experienced several drought years. Among these, 2015 and 2021 were the most severe drought years, with rainfall considerably below the long-term average. As a result, the Agricultural Production Index (API) declined sharply. The productivity of major crops such as soybean, sorghum (jowar), pigeon pea (tur), and chickpea (gram) decreased substantially. This led to increased economic stress on farmers and a rise in the number of farmer suicides. From a geographical perspective, these impacts need to be studied because agricultural productivity is influenced by the combined effects of soil type, topography, irrigation facilities, and local climatic conditions. The significance of this study lies in its close association with farmers' livelihoods and the rural economy. The findings will contribute to the formulation of climate-resilient agricultural policies. The study is entirely based on secondary data and employs appropriate statistical methods for analysis.

Study Area

Latur district is situated between 17 °52′ and 18 °50′ North latitude and 76 °18′ and 77 °18′ East longitude in the Marathwada region of Maharashtra, India. The district covers a geographical area of approximately 7,157 square kilometres (7.15 lakh hectares), of which about 6.65 lakh hectares are under cultivation. Administratively, the district comprises ten tehsils: Latur, Ausa, Nilanga, Udgir, Ahmedpur, Renapur, Chakur, Deoni, Jalkot, and Shirur Anantpal. The soils of the district are predominantly black cotton soils, ranging from shallow to deep in depth. The climate is hot semi-arid, with an average annual rainfall ranging between 680 and 734 mm. The Manjara River and its tributaries constitute the principal sources of irrigation; however, the irrigated area remains limited. Being located in the rainshadow region of the Western Ghats, the district experiences highly erratic rainfall. According to the 2011 Census, nearly 71.4 percent of the population is directly dependent on agriculture for their livelihood. The analysis indicates that the average annual rainfall of the district is 680 mm, with a standard deviation of 98 mm and a coefficient of variation of 14.42%, reflecting moderate

Objectives of the

Objectives of the

Temperature and Other Climatic Factors

The number of hot days has increased significantly over time. In 1960, the district experienced 147 days with temperatures above 32°C, whereas this number increased to 188 days by 2019. This trend is expected to continue under future climate change scenarios. In addition, groundwater levels have declined considerably, and the depth of several wells has exceeded 600 metres, indicating increasing pressure on groundwater resources due to prolonged droughts and rising water demand. These environmental changes have intensified water scarcity and further reduced the resilience of the agricultural sector in Latur district.

Impact on Agricultural Productivity

The statistical analysis reveals a strong positive correlation (r = 0.84) between annual rainfall and the Agricultural Production Index (API) in Latur district. This indicates that higher rainfall generally leads to improved agricultural productivity, whereas drought conditions significantly reduce crop production.

During severe drought years, the Agricultural Production Index declined by approximately 20-30 percent. Waterintensive crops such as soybean, pigeon pea (tur), and sugarcane were the most severely affected. In contrast, drought-tolerant crops such as sorghum (jowar) showed comparatively better resilience; however, their overall productivity also declined under prolonged drought conditions.

In the Kharif season, crops such as soybean and pigeon pea experienced substantial yield reductions due to erratic rainfall. Similarly, in the Rabi season, the productivity of chickpea and wheat was adversely affected by inadequate soil moisture. The years 2015 and 2021 witnessed extensive crop failures because of severe drought. Since only a limited area in the district is irrigated, agriculture remains highly dependent on monsoon rainfall, making crop production extremely vulnerable to climatic uncertainty.

Socio-Economic Impacts

Climate uncertainty has imposed considerable economic and social stress on farming households in Latur district.

Frequent droughts have resulted in increasing indebtedness, migration, school dropouts, and health-related problems, thereby affecting the overall well-being of rural communities.

The study found a strong negative correlation (r = -0.95) between annual rainfall and the farmer suicide rate. Lower rainfall and prolonged drought conditions were associated with a higher incidence of farmer suicides, reflecting the severe socio-economic consequences of climate variability The analysis of socio-economic impacts indicates that migration accounted for 30%, indebtedness for 25%, school dropouts for 20%, health-related problems for 15%, and mental health issues for 10% of the major consequences associated with climate uncertainty in the district.

Discussion

The findings of the study indicate that climate uncertainty in Latur district is closely associated with its geographical characteristics. The district is located in the rain-shadow region of the Western Ghats, resulting in highly irregular rainfall. Although the predominance of black cotton soils enables greater moisture retention, prolonged droughts eventually dry out even these soils, thereby reducing their capacity to support crop growth. The limited extent of irrigation infrastructure has further increased the dependence of agriculture on monsoon rainfall. Consequently, climatic variability has a direct and substantial impact on agricultural productivity. The increasing cultivation of crops such as soybean, which require relatively higher water availability, has further heightened the vulnerability of the agricultural sector to drought conditions. Prolonged droughts lead to reduced agricultural production, declining farm income and increasing indebtedness among farmers. These economic hardships often contribute to higher incidences of farmer suicides. The study also reveals geographical disparities within the district, with comparatively lower adverse impacts observed in areas having better irrigation facilities than in predominantly rainfed regions.

Conclusion and Recommendations Conclusion

The present study concludes that climate uncertainty had a significant negative impact on agricultural productivity in Latur district during the period 2015-2026. A strong positive relationship exists between annual rainfall and the Agricultural Production Index (API), indicating that rainfall remains the most critical determinant of agricultural performance in the district. During extreme drought years, agricultural production declined by approximately 20-30 percent, accompanied by severe socio-economic consequences, including increased indebtedness, migration, and farmer suicides.

Figures and tables from the paper

Table 1. Latur District - Annual Rainfall, Agricultural Production Index (API), and Drought Status (2015-2026)
YearRainfall (mm)API (Base Year 2010 = 100)Drought Status
201555076Extreme
201682095Normal
201777093Mild
201865085Severe
201961080Severe
202059078Severe
202154073Extreme
202268089Moderate
202373092Mild
202461098Normal
202564090Mild-Moderate

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Latur District - Annual Rainfall, Agricultural Production Index (API), and Drought Status (2015-2026)↗ Enlarge
Table 1
Latur District - Annual Rainfall, Agricultural Production Index (API), and Drought Status (2015-2026)

Latur District - Annual Rainfall, Agricultural Production Index (API), and Drought Status (2015-2026)

Open full-size image ↗
Original paper tableSource PDF · page 2 ↗
Table 2. Farmer Suicide Rate in Latur District (Per 100,000 Population)
YearFarmer Suicide Rate
201530
201617
201719
201826
201928
202032
202135
202222
202320
202429
202527

Table text extracted from the original PDF; superscript letters are shown inline. The original table image is below.

View original table image
Farmer Suicide Rate in Latur District (Per 100,000 Population)↗ Enlarge
Table 2
Farmer Suicide Rate in Latur District (Per 100,000 Population)

Farmer Suicide Rate in Latur District (Per 100,000 Population)

Open full-size image ↗
Original paper tableSource PDF · page 3 ↗

References

6 in the original paper
  1. Jadhav VS. Statistical Analysis of Drought Impact on Agricultural Sector in Latur District, Maharashtra. Int J Stat Appl Math. 2025;10(7A):39-45.
  2. Department of Agriculture, Government of Maharashtra. District-wise APY Estimates. 2025. http://krishi.maharashtra.gov.in/
  3. Indian Districts. Agriculture -Latur. 2025. https://indiandistricts.in/statistics/maharashtra/latur/agri culture/
  4. Katke AK. A Geographical Study of Change in Fruit Cultivation Area in Latur District. Int J Geogr Geol Environ. 2024;6(1).
  5. Kelkar SM, Kulkarni A, Rao KK. Impact of Climate Variability and Change on Crop Production in Maharashtra, India. Curr Sci. 2020;118(8).
  6. Zilla Parishad Latur. Agriculture Department. 2026. https://zplatur.gov.in/en/agriculture-department/