Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Shimanga/Effect-of-Rainfall-Variability-on-Maize-Yield-in-Zambia

Domaine:

agricultureclimate

Type de record:

dataset
Créateur:
Shi
Hôte:
Two-dataset analysis of rainfall variability and maize yield across 10 Zambian provinces. Yield panel (1986–2013): correlation, regression, and rainfall efficiency metrics. Rainfall dataset (44 seasons, 1981–2024): October planting window trends, monthly patterns, and provincial vulnerability analysis. Python | SQL | Excel # Rainfall Variability and Its Effect on Maize Yield in Zambia (1986-2013) A hypothesis-driven investigation into climate-agriculture relationships. It demonstrates correlation/regression analysis, monthly pattern detection, efficiency metrics, and translation of null results into policy research agendas. This study evaluates how rainfall variability influences maize yield across ten provinces of Zambia. The analysis tests whether total seasonal rainfall explains yield variation, or whether provincial differences and rainfall patterns provide stronger explanatory value. ## Table of Contents - Research Questions - Data Summary - Dataset Structure - Summary Statistics - Results - Regression Analysis - Trends Over Time - Conclusions & Implications - Repository Structure --- ## Research Questions 1. To what extent does total seasonal rainfall explain variability in maize yield across provinces? 2. How do provincial differences in rainfall patterns relate to maize yield responses? 3. Which provinces are most vulnerable to rainfall variability and drought conditions? --- ## Data Summary - **Time period (yield):** 1986-2013 - **Time period (rainfall):** 1981-2026 - **Provinces analyzed:** 10 (including Muchinga) - **Observations:** 454 records (after filtering zero yields) - **Rainfall range:** 445 mm - 1,537 mm (seasonal total) - **Yield range:** 0.19 - 3.58 t/ha ### Data Constraints | Limitation | Impact | |------------|--------| | Missing yield data (2008-2010) | These years excluded from analysis | | Muchinga province formed in 2011 | Only 3 years available; limited reliability | | Zero yield records removed | Treated as missing data | | Seasonal yield data aggregation | Cannot directly correlate monthly rainfall with yield | ### Data Validation and Revision - Initial dataset contained inconsistencies from query extraction - Dataset was rebuilt and revalidated - All results in this analysis are based on the corrected dataset --- ## Dataset Structure ### …

Visit

github.com

Similaires

Effect of Meteorological Factors on Maize Yield in ComorosImpact of climate change and variability on maize yield in Tropical AfricaEffect of Rainfall Variability on the Maize Varieties Grown in a Changing Climate: A Case of Smallholder Farming in Hwedza, ZimbabweAnthonykennetho/maize-yield-vs-rainfall-regression-josThe Effect of Rainfall, Temperature, and Relative Humidity on the Yield of Cassava, Yam, and Maize in the Ashanti Region of GhanaSpatio‐temporal effects of El Niño events on rainfall and maize yield in Kenya

Effect of Meteorological Factors on Maize Yield in Comoros

Understanding the effects of climatic factors on maize yield will benefit tactical decisions for fut

Impact of climate change and variability on maize yield in Tropical Africa

<p> <span><span>Tropical Africa has been experiencing a lo

Effect of Rainfall Variability on the Maize Varieties Grown in a Changing Climate: A Case of Smallholder Farming in Hwedza, Zimbabwe

Rain-fed maize production has significantly declined in Zimbabwe especially in semi-arid and arid ar

Anthonykennetho/maize-yield-vs-rainfall-regression-jos

A linear regression project exploring the relationship between rainfall and maize yield in Jos, Nige

The Effect of Rainfall, Temperature, and Relative Humidity on the Yield of Cassava, Yam, and Maize in the Ashanti Region of Ghana

This study examined the consequences of changes in minimum temperature, maximum temperature, relativ

Spatio‐temporal effects of El Niño events on rainfall and maize yield in Kenya

Abstract The ability to predict rainfall variability a season in advance could have a major impact