A5045657508- Climate variability and models
- Climate change impacts on agriculture
- Hydrology and Drought Analysis
- Agriculture Sustainability and Environmental Impact
- Plant Water Relations and Carbon Dynamics
- Agricultural risk and resilience
- Rangeland Management and Livestock Ecology
- Meteorological Phenomena and Simulations
- Soil and Water Nutrient Dynamics
- Agricultural Economics and Practices
- Atmospheric and Environmental Gas Dynamics
- Plant responses to elevated CO2
- Effects of Environmental Stressors on Livestock
- Soil Carbon and Nitrogen Dynamics
- Wheat and Barley Genetics and Pathology
- Cassava research and cyanide
- Hydrology and Watershed Management Studies
- Energy and Environment Impacts
- Science and Climate Studies
- Climate Change and Health Impacts
- Greenhouse Technology and Climate Control
- Crop Yield and Soil Fertility
- Animal Diversity and Health Studies
- Transboundary Water Resource Management
- Soil erosion and sediment transport
Karlsruhe Institute of Technology
2020-2025
Aarhus University
2024
University of Bonn
2023
University of Tehran
2012-2021
Crop yield forecasting depends on many interactive factors, including crop genotype, weather, soil, and management practices. This study analyzes the performance of machine learning deep methods for winter wheat prediction using an extensive dataset phenology variables in 271 counties across Germany from 1999 to 2019. We proposed a Convolutional Neural Network (CNN) model, which uses 1-dimensional convolution operation capture time dependencies environmental variables. used eight supervised...
Abstract A multivariate bias correction based on N‐dimensional probability density function transform (MBCn) technique is applied to four different high‐resolution regional climate change simulations and key meteorological variables, namely precipitation, mean near‐surface air temperature, maximum minimum surface downwelling solar radiation, relative humidity, wind speed. The impact of bias‐correction the historical (1980–2005) period, inter‐variable relationships, measures spatio‐temporal...
Climate change is increasingly putting milk production from cattle-based dairy systems in north sub-Saharan Africa (NSSA) under stress, threatening livelihoods and food security. Here we combine livestock heat stress frequency, dry matter feed water accessibility data to understand where environmental changes NSSA's drylands are jeopardizing cattle production. We show that conditions worsened for ∼17% of the study area. Increasing goat camel populations by ∼14% (∼7.7 million) ∼10% (∼1.2...
Abstract A major societal challenge is to produce sufficient food for a growing global population while simultaneously reducing agricultural nitrogen pollution within safe environmental boundaries. Here we use spatially-resolved, process-based simulations of cereal cropping systems (at 0.5° resolution) show how redistribution fertiliser usage could meet this on scale. Focusing cereals (maize, wheat and rice), find that current production be (i) maintained with 32% reduction in total use, or...
Sub-Saharan Africa (SSA) is home to approximately ¼ of the global livestock population, which in last 60 years has increased by factors 2.5-4 times for cattle, goats and sheep. An important resource pastoralists, most live semi-arid arid environments, where they roam during day are kept enclosures (or bomas) night. Manure, although rich nitrogen, rarely used, therefore accumulates bomas over time. Here we present in-situ measurements N2O fluxes from 46 Kenya show that even after 40 following...
<title>Abstract</title> Pastoralism is a major way of life in the Sahelian and Sudanian (SaSu) zone Africa, playing an important social-environmental role through food production use suitable land for seasonal migrations (transhumance). Using Earth Observation (EO) data, we systematically analyze environmental factors—water access, soil properties, topography, vegetation cover, tree road biomass availability— to assess SaSu’s suitability transhumance as well permanent farming systems,...
Process-based agricultural system models (PBMs) are pivotal tools for evaluating the environmental impacts of practices. However, their large-scale application is constrained by significant computational demands, extensive time requirements, and data availability. These challenges hinder policymakers land managers in implementing sustainable practices at scales meaningful decision-making. Recent advancements machine learning (ML) offer a promising solution providing computationally efficient...
Abstract Crop residue management plays an important role in determining agricultural greenhouse gas emissions and related changes soil carbon stocks. However, no publicly-available global dataset currently exists for how crop residues are managed. Here we present such a dataset, covering the period 1997–2021, on 0.5° resolution grid. For each grid cell estimate total production of from cereal crops, determine fraction (i) used livestock feed/bedding, (ii) burnt field, (iii) other off-field...
Introduction Cassava production is essential for food security in sub-Saharan Africa and serves as a major calorie-intake source Nigeria. Estimating the yield gap Nigeria to indicate most important limiting factors production, identify hotspot areas. Secondly, these assessments may help set agendas policy development research prioritization where current information scarce. Materials methods Here, Wwe used crop model, LINTUL5, calibrated five different cassava varieties based on field...
Abstract Climate change is known as one of the key challenges 21st century for sustainable agricultural development over Southwest Asia. However, not much about way that climate changes might affect precipitation, temperature, and zones their consequence Here we have analysed probable in modified Thornthwaite by using monthly temperature precipitation data from 320 meteorological stations during historical period 1971–2015, well future projections 17 GCMs (General Circulation Models) outputs...
Abstract This study focuses on heat stress conditions for dairy cattle production in West Africa under current and future climatic conditions. After testing the accuracy of dynamically downscaled climate datasets simulating historical daily maximum temperature (Tmax) relative humidity (RH) 50 meteorological stations, we used dataset calculating temperature-humidity index (THI), i.e., an indicating a scale. Calculations were made period (1981–2010) using ERA-Interim reanalysis dataset, two...
Abstract A complete understanding of the nexus between productivity and sustainability agricultural production systems calls for a comprehensive assessment nitrogen budget (NB). In our study, data from well-monitored Danish Agricultural Watershed Monitoring Program (LOOP-program; 2013–2019) is used quantitative inter-comparison three different approaches to drive process-based model LandscapeDNDC on regional scale. The aim assess how assumptions simplifications about farm management...
Drought is a natural disaster that has always had severe impact on agriculture, especially rain-fed agriculture. Many studies have indicated different indices, for example the standardized precipitation index (SPI), do not show acceptable efficiency in quantifying agricultural drought. In current study, an was utilized so-called effective (SEPI). The SEPI employs during wheat-growing season using two-layer soil-water balance model. order to assess of representing and capturing fluctuations...