Bahareh Kamali

University of Bonn | Uni Bonn · Institute of Crop Science and Resource Conservation (INRES)

Process-based soil-crop models are becoming increasingly important to estimate the effects of agricultural management practices and climate change impacts on soil organic carbon (C). Although work has been done on the effects of crop type and climate on the root:shoot (biomass) ratio, there is a gap in research on the effects of specific environmen...

Accurate estimation of biomass in grasslands is essential for understanding ecosystem health and productivity. Unmanned Aerial Vehicles (UAVs) have emerged as valuable tools for biomass estimation using canopy height models derived from high-resolution imagery. However, the impact of field disturbances, such as lodging and molehills, on the accurac...

Wet grasslands are crucial components of terrestrial ecosystems, known for their biodiversity and provision of ecosystem services such as flood attenuation and carbon sequestration. Given their ecological significance, monitoring biodiversity within these landscapes is of utmost importance for effective conservation and management strategies. This...

Human activities and climate changes have reduced the inflow to Urmia lake and caused a sharp drop in its water level. This study aimed to identify the breakpoint of rainfall and runoff to evaluate the relative contribution of climate change and human activities in reducing runoff at the Zarrinehroud watershed. The Zarrinehroud basin is the largest...

Large-scale assessments of agricultural productivity necessitate integrated simulations of cropland and grassland ecosystems within their spatiotemporal context. However, simultaneous simulations face limitations due to assumptions of uniform species distribution. Grasslands, particularly those with shallow groundwater tables, are highly sensitive...

Sub-Saharan Africa (SSA) faces significant food security risks, primarily due to low soil fertility leading to low crop yields. Climate change is expected to worsen food security issues in SSA due to a combined negative impact on crop yield and soil fertility. A common omission from climate change impact studies in SSA is the interaction between ch...

This paper addressed one of the main challenges in assimilating remote sensing derived variables into process-based crop model simulations, which is the inconsistent spatial and temporal resolution between information obtained from remote sensing and the outputs of process-based agroecosystem model. We proposed an applied method to reduce the numbe...

Food insecurity in sub-Saharan Africa is partly due to low staple crop yields, resulting from poor soil fertility and low nutrient inputs. Integrated soil fertility management (ISFM), which includes the combined use of mineral and organic fertilizers, can contribute to increasing yields and sustaining soil organic carbon (SOC) in the long term. Soi...

https://www.tropentag.de/2023/abstracts/posters/321.pdf

Crop disease management is crucial for sustainable food production. Although farmers in Nigeria continue to apply broad-spectrum fungicides to potato, potato diseases are still on the rise. Machine-learning methods have recently become more common as part of epidemiological early warning systems. They provide vital information on data–disease relat...

Every grassland has considerable annual vegetation composition dynamics, especially in sites with shallow water levels (Toogood & Joyce, 2009). These wet grasslands, where the vegetation is regularly consuming capillary water, are very sensitive to water availability and respond rapidly by changing their species composition. As different species pr...

To find suitable farming management approaches in the semi-arid climate of Iran, we set up an experiment combining three farm management practices with four crop rotation systems over four growing seasons (two winter and two summer seasons), from 2018 to 2020. The three farm management practices comprised: intensive (IF, with inorganic inputs, remo...

Grasslands are one of the world’s largest ecosystems, accounting for 30% of total terrestrial biomass. Considering that aboveground biomass (AGB) is one of the most essential ecosystem services in grasslands, an accurate and faster method for estimating AGB is critical for managing, protecting, and promoting ecosystem sustainability. Unmanned aeria...

Introduction Soil organic carbon (SOC) dynamic is one of the important factors that directly influence soil properties and quality. In agro-ecosystems, the SOC dynamics are strongly linked to agricultural management practices. Methods In this study, we investigated the response of SOC and its fractions to various combination of agricultural manage...

Grasslands on groundwater level (GL) close to the surface where the vegetation is regularly consuming capillary water are called wet grasslands. Their biomass production should linearly respond to water availability in the capillary fringe of the soils. However, different species produce different biomass, the biomass yield is constantly altering a...

Crop model intercomparison studies have mostly focused on the assessment of predictive capabilities for crop development using weather and basic soil data from the same location. Still challenging is the model performance when considering complex interrelations between soil and crop dynamics under a changing climate. The objective of this study was...

This study investigates the main drivers of uncertainties in simulated irrigated maize yield under historical conditions as well as scenarios of increased temperatures and altered irrigation water availability. Using APSIM, MONICA, and SIMPLACE crop models, we quantified the relative contributions of three irrigation water allocation strategies, th...

The dynamics of grassland ecosystems are highly complex due to multifaceted interactions among their soil, water, and vegetation components. Precise simulations of grassland productivity therefore rely on accurately estimating a variety of parameters that characterize different processes of these systems. This study applied three calibration scheme...

Assessing the risk of yield loss in African drought-affected regions is key to identify feasible solutions for stable crop production. Recent studies have demonstrated that Copula-based probabilistic methods are well suited for such assessment owing to reasonably inferring important properties in terms of exceedance probability and joint dependence...

Reliable crop type maps from satellite data are an essential prerequisite for quantifying crop growth, health, and yields. However, such maps do not exist for most parts of Africa, where smallholder farming is the dominant system. Prevalent cloud cover, small farm sizes, and mixed cropping systems pose substantial challenges when creating crop type...

The uncertainties associated with crop model inputs can affect the spatio-temporal variance of simulated yields, particularly under suboptimal irrigation. The aim of this study was to determine and quantify the main drivers of irrigated potato yield variance; as influenced by crop management practices as well as climate and soil factors. Using a lo...

Crop models were originally developed for application at the field scale but are increasingly used to assess the impact of climate and/or agronomic practices on crop growth and yield and water dynamics at larger scales. This raises the question of how data aggregation approaches affect outputs when using crop models at large spatial scales. This st...

Crop model inter-comparisons have mostly been carried out to test the predictive ability under the past range of climatic conditions and for soils of the same site. Unknown is, however, the ability of individual crop models to predict effects of changes in climatic conditions on soil ecosystems beyond the range of site-specific variability. The obj...

Agroecosystem models need to reliably simulate all biophysical processes that control crop growth, particularly the soil water fluxes and nutrient dynamics. As a result of the erosion history, truncated and colluvial soil profiles coexist in arable fields. The erosion‐affected field‐scale soil spatial heterogeneity may limit agroecosystem model pre...

Smallholder farmers in sub‐Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multi‐model assessment of simulation accuracy and uncertainty i...

Agro-ecosystem models have been developed to study effects of agricultural management on crop production, mostly from an agronomic point of view. Based on a biophysical process representation, their most prominent advantage is the coupled modelling of crop development and yield formation, as well as water and nutrients fluxes in the plant-soil syst...

Input data aggregation affects crop model estimates at the regional level. Previous studies have focused on the impact of aggregating climate data used to compute crop yields. However, little is known about the combined data aggregation effect of climate (DAEc) and soil (DAEs) on irrigation water requirement (IWR) in cool-temperate and spatially he...

Input data aggregation influences crop model estimates at the regional level. Previous studies have focused on the impact of aggregating the climate data used to compute crop yields. Little is known about the combined data aggregation effect of climate (DAEc) and soil (DAEs) model inputs. This study explores the implications of using coarse resolut...

Drought events have significant impacts on agricultural production in Sub-Saharan Africa (SSA), as agricultural production in most of the countries relies on precipitation. Socio-economic factors have a tremendous influence on whether a farmer or a nation can adapt to these climate stressors. This study aims to examine the extent to which these fac...

Robust calibration of hydrologic models is critical for simulating water resource components; however, the time-consuming process of calibration sometimes impedes the accurate parameters’ estimation. The present study compares the performance of two approaches applied to overcome the computational costs of automatic calibration of the HEC-HMS (Hydr...

Crop yields exhibit known responses to droughts. However, quantifying crop drought vulnerability is often not straightforward, because components of vulnerability are not defined in a standardized and spatially comparable quantity in most cases and it must be defined on a fine spatial resolution. This study aims to develop a physical crop drought v...

Process-based crop models are increasingly used to assess the effects of different agricultural management practices on crop yield. However, calibration of historic crop yield is a challenging and time-consuming task due to data limitation and lack of adaptive auto-calibration tools compatible with the model to be calibrated on different spatial an...

Drought as a slow-onset phenomenon inflicts important losses to agriculture where the degree of vulnerability depends not only on physical variables such as precipitation and temperature, but also on societal preparedness. While the scopes of physical and social vulnerability are very different in nature, studies distinguishing these two aspects ha...

This study contributes to a better understanding of climate change adaptation by investigating different farming systems and by including cognitive factors as explanatory variables. We compared a food crop and a horticultural farming system, regarding applied adaptation measures and factors influencing adaptation. The data were based on a field sur...

A large number of local and global databases for soil, land use, crops, and climate are now available from different sources, which often differ, even when addressing the same spatial and temporal resolutions. As the correct database is unknown, their impact on estimating water resource components (WRC) has mostly been ignored. Here, we study the u...

Studies using Drought Hazard Indices (DHIs) have been performed at various scales, but few studies associated DHIs of different drought types with climate change scenarios. To highlight the regional differences in droughts at meteorological, hydrological, and agricultural levels, we utilized historic and future DHIs derived from the Standardized Pr...

We present the model results and their uncertainties of an inter-sectoral impact model inter-comparison initiative (ISI-MIP) for climate change impacts in Africa. The study includes results on hydrological, crop and health aspects. The impact models used ensemble inputs consisting of 20 time series of daily rainfall and temperature data obtained fr...

Soil erosion threatens both soil and water resources and has increased globally due to the removal of natural vegetation and the intensification of existing agriculture. Brazil is privileged by a large proportion of natural vegetation and abundant freshwater. Recently, modifications of the Brazilian Forest Act (BFA) have been approved that offer la...

Soil erosion threatens both soil and water resources and has increases globally due to changes in land use, mainly the substitution of natural vegetation by agricultural crops and pasture, or the intensification of existing agriculture. Brazil is privileged by a large proportion of natural vegetation and abundant freshwater. Recently, a new Brazili...

This study aims at identifying historical patterns of meteorological, hydrological, and agricultural (inclusively biophysical) droughts in the Karkheh River Basin (KRB), one of the nine benchmark watersheds of the CGIAR Challenge Program on Water and Food. Standardized precipitation index (SPI), standardized runoff index (SRI), and soil moisture de...

Estimation of parameters of a hydrologic model is undertaken using a procedure called “calibration” in order to obtain predictions as close as possible to observed values. This study aimed to use the particle swarm optimization (PSO) algorithm for automatic calibration of the HEC-HMS hydrologic model, which includes a library of different event-bas...

This study presents single-objective and multi-objective particle swarm optimization (PSO) algorithms for automatic calibration of Hydrologic Engineering Center- Hydrologic Modeling Systems rainfall-runoff model of Tamar Sub-basin of Gorganroud River Basin in north of Iran. Three flood events were used for calibration and one for verification. Four...

This study presents the application of an uncertainty-based technique for automatic calibration of the well-known Hydrologic Engineering Center-Hydrologic Modelling System (HEC-HMS) model. Sequential uncertainty fitting (SUFI2) approach has been used in calibration of the HEC-HMS model built for Tamar basin located in north of Iran. The basin was d...