576 research outputs found

    Reference crop evapotranspiration derived from geo-stationary satellite imagery: a case study for the Fogera flood plain, NW-Ethiopia and the Jordan Valley, Jordan

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    First results are shown of a project aiming to estimate daily values of reference crop evapotranspiration ET0 from geo-stationary satellite imagery. In particular, for Woreta, a site in the Ethiopian highland at an elevation of about 1800 m, we tested a radiation-temperature based approximate formula proposed by Makkink (MAK), adopting ET0 evaluated with the version of the Penman-Monteith equation described in the FAO Irrigation and Drainage paper 56 as the most accurate estimate. More precisely we used the latter with measured daily solar radiation as input (denoted by PMFAO-Rs). Our data set for Woreta concerns a period where the surface was fully covered with short green non-stressed vegetation. Our project was carried out in the context of the Satellite Application Facility on Land Surface Analysis (LANDSAF) facility. Among others, the scope of LANDSAF is to increase benefit from the EUMETSAT Satellite Meteosat Second Generation (MSG). In this study we applied daily values of downward solar radiation at the surface obtained from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) radiometer. In addition, air temperature at 2m was obtained from 3-hourly forecasts provided by the European Centre for Medium-Range Weather Forecasts (ECMWF). Both MAK and PMFAO-Rs contain the psychrometric "constant", which is proportional to air pressure, which, in turn, decreases with elevation. In order to test elevation effects we tested MAK and its LANDSAF input data for 2 sites in the Jordan Valley located about 250 m b.s.l. Except for a small underestimation of air temperature at the Ethiopian site at 1800 m, the first results of our LANDSAF-ET0 project are promising. If our approach to derive ET0 proves successfully, then the LANDSAF will be able to initiate nearly real time free distribution of ET0 for the full MSG disk

    Remote sensing of energy and water fluxes over Volta Savannah catchments in West Africa

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    The deterioration of the West African savannah in the last three decades is believed to be closely linked with about 0.5 C rise in temperature leading to evaporation losses and declining levels of the Volta Lake in Ghana. Although hydrological models can be used to predict climate change impacts on the regional hydrology, spatially-observed ground data needed for this purpose are largely unavailable. This thesis seeks to address this problem by developing improved methods for estimating energy and water fluxes (e.g. latent heat [ET]) from remotely sensed data and to demonstrate how these may be used to parameterize hydrological models. The first part of the thesis examines the potential of the Penman-Monteith method to estimate local-scale ET using groundbased hydrometeorological observations, vegetation coefficients and environmental data. The model results were compared with pan observations, scintillometer (eddy correlation) measurements and the Thomthwaite empirical method. The Penman- Monteith model produced better evaporation estimates (~3.90 mm day(^-1) for the Tamale district) than its counterpart methods. The Thomthwaite, for example, overestimated predictions by 5.0-11.0 mm day(^-1). Up-scaling on a monthly time scale and parameterization of the Grindley soil moisture balance model with the Thomthwaite and Penman-Monteith data, however, produced similar estimates of actual evaporation and soil moisture, which correlated strongly (R(^2) = 0.95) with water balance estimates. To improve ET estimation at the regional-scale, the second part of the thesis develops spatial models through energy balance modelling and data up-scaling methods, driven by radiometric measurements from recent satellite sensors such as the Landsat ETM+, MODIS and ENVISAT-AATSR. The results were validated using estimates from the Penman-Monteith method, field observations, detailed satellite measurements and published data. It was realised that the MODIS sensor is a more useful source of energy and water balance parameters than AA TSR. For example, stronger correlations were found between MODIS estimates of ET and other energy balance variables such as NDVI, surface temperature and net radiation (R(^2) = 0.67-0.73) compared with AATSR estimates (R(^2) = 0.31-0.40). There was also a good spatial correlation between MODIS and Landsat ETM+ results (R(^2) = 0.71), but poor correlations were found between AATSR and Landsat data (R(^2) = 0.0-0.13), which may be explained by differences in instrument calibration. The results further showed that ET may be underestimated with deviations of ~2.0 mm day 1 when MODIS/AATSR measurements are validated against point observations because of spatial mismatch. The final part of the thesis demonstrates the application of the ET model for predicting runoff (Q) using a simplified version of the regional water balance equation. This is followed byanalysis of flow sensitivity to declining scenarios of biomass volume. The results showed the absence of Q for >90% of the study area during the dry season due largely to crude model approximation and lack of rainfall data, which makes model testing during the wet season important. Runoff prediction may be improved if spatial estimates of rainfall, ET and geographical data (e.g. land-use/cover maps, soil & geology maps and DEM) could be routinely derived from satellite imagery

    Agroclimatic analysis for mainland East Asia by a GIS approach

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    Climate has been long recognised as an important constraint to crop production. Many agroclimatic analyses have been developed in Mainland East Asian countries to assist their agricultural development and resource management. These analyses were all restricted to using a limited number of data points and static summations of climatic variables. The complex climatic patterns and the non-linear responses of crops to climate cannot be captured by such agroclimatic analyses. This thesis addressed the agroclimatic environment and its impact on crop production using a different philosophy and methodology in order to overcome these shortcomings. There are four related components in this study. They are: 1). regular grid climatic data sets; 2). crop responses to the environmental elements in Mainland East Asia; 3). agroclimatic classification; and 4). crop modeling at selected representative stations from various agroclimatic zones. The regular grid climatic data sets consist of climatic surfaces and a digital elevation model (DEM). In this study they were developed at a resolution of l/20th degree. While this study focused on agroclimatic analysis these data sets can be applied to any other fields that relate to climate such as forestry, ecology and conservation. These climatic surfaces express climatic variables as functions of multi-dimensional thin plate smoothing splines in term of longitude, latitude and elevation. They were developed using the ANUSPLIN package, and are based on a network of up to 3800 stations across Mainland East Asia. Estimates for climatic variables at any location in the Mainland East Asian countries can be calculated from these surfaces with input of the appropriate independent variables. A DEM at a resolution of l/20th degree, calculated using the ANUDEM package and based on terrain data digitised from topographic maps, was used to construct data sets in this study. These data sets consist of 434,484 grid cells across the studying area. Based on such data sets, crop responses to the climatic environment were simulated using a general plant growth model GROWEST. This model transforms the non-linear responses of key plant groups to linear dimensionless scalars. These include a light index (LI), a thermal index (Tl), a moisture index (MI) and an integrated multi-factor growth index (GI). The spatial and seasonal variations of these indices were analysed for each of the 434,484 grid cells across Mainland East Asia. With 39 selected GROWEST attributes, Mainland East Asia was classified into 66 groups and further aggregated to 14 agroclimatic zones using the ALOC and FUSE modules of a numerical taxonomic package PATN. These agroclimatic zones have been given descriptive labels, thus; 1.Cold high plateau zone 2.Hot dry desert 3.Grassland zone 4.Single-crop 5.Double crop/wheat and 6.Double crop/rice 7.Warm hills 8.Warm highlands 9.Tropical mountain tops 10.Tropical forest 11.Triple-crop 12.Humid tropical lowlands 13.Perhumid tropical highlands 14.Perhumid tropical lowlands Finally, 14 representative stations were selected from the major cropping zones of Mainland East Asia for more detailed crop modeling using the DSSAT v3 package. The Seasonal Analysis module was used to model wheat, maize and rice production for for a period of 15 years, and has further demonstrated the major climatic constraints on crop production for various agroclimatic zones

    The use of erosion models to predict the influence of land use changes on urban impoundments

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    The impact of soil loss from urban erosion processes is a major problem confronting decision makers on a national and local level. One such resource is the Boksburg Lake in the Eastern Service Delivery Region of the Ekurhuleni Metropolitan Municipality of the Gauteng Province, South Africa. The purpose of the study was to quantify what impact soil erosion, as a result of changes in land-use, had on the urban impoundment. There is a close relationship between how land is managed and the impact erosion may have on in-stream health. Increased erosion as a result of catchment changes increases the loads of phosphorus introduced into streams (Croke, 2002) and subsequently increases the occurrence of eutrophication. The management of sediment levels combined with reduced catchment phosphorus load is viewed as the most viable option in eutrophication abatement. Available soil erosion models and methods were compared and the most suited selected for the study. The study used a modified approach of the Universal Soil Loss Equation and the Soil Loss Estimation Model for Southern Africa. These were adjusted for urban conditions. Various simulation models were run and the results presented. Results from five of the models yielded results within 15%, or 85% confidence, of the measured results. Four of these models are however not generally accepted methods and can only be used as indication. The USLE method utilizing the Vanoni SDR equation is the preferred method and was applied in subsequent modelling. The simulation results of the phosphorus loading, although not within a 10% accuracy, relates to the observed loadings of 2008. By observing a similar trend as the sediment loadings, as a result of the development, it was concluded that the phosphorus loadings relate to the soil loss models which was related to changes in the catchments as a result of changes in land usage (imperviousness as indicator)

    Final Report of the DAUFIN project

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    DAUFIN = Data Assimulation within Unifying Framework for Improved river basiN modeling (EC 5th framework Project

    Assessment of potential rooftop solar PV electricity at a suburban scale, and a comparative analysis based on topographical obstruction and seasonality

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    Long-term climate change mitigation calls for a switch from the current global non-renewable energy system to low greenhouse gas (GHG) emission energy solutions. Many nations have started adopting energy-efficient technology as part of their climate change programs and the built environment has been identified as a key lever for reducing emissions linked to energy efficiency. Building rooftop photovoltaic (PV) system is an effective technology to reduce emissions through the use of solar energy. In recent years, rooftop PV systems have become the main source of solar-generated energy, and forecasting their output is critical when assessing a site\u27s PV energy potential. However, integrating topographical features with seasonal considerations to estimate solar PV energy is challenging. There are some studies available that estimate solar PV energy on rooftops using geospatial tool modeling, but these have limitations in functionality, accuracy, and calculation speed. This study uses a geospatial tool to assess the solar PV potential of suitable rooftops in the suburbs of Wollongong, Australia, namely, Wombarra and Cringila. The model used in this study compares the energy potential of these two suburbs based on the topographical feature (escarpment), seasonality, rooftop slope, and aspect. The digital surface model (DSM) is created using LiDAR data, and then the DSM, building footprints, and suburb boundaries data are used to calculate the solar PV energy potential. A total of 1594 buildings from two suburbs were considered. Subsequently, solar radiation modeling for four common seasons in a year and a comparison of solar radiation output, suitable rooftop area, and electricity output are being done for both suburbs. Wombarra\u27s building rooftops are shadowed by the escarpment, whereas Cringila\u27s aren\u27t. Even though the weather in both suburbs is similar, the escarpment\u27s shadow affects solar PV energy output. Wombarra has 178 kWh/m2/building lesser yearly solar radiation than Cringila. Hence, Cringila offers more solar rooftop installation potential per building. The average annual potential electricity generation per dwelling in Wombarra is 20.6 kWh/m2/day, and the same for Cringila is 27.6 kWh/m2/day. The outcome reveals that 1352 building rooftops, with a usable area of 75481 m2, are the best locations for installing solar panels. According to the Australian Government\u27s Energy Made Easy statistics, the annual electricity consumption per household in Wollongong is 5707.6 kWh (Australian Energy Regulator 2022). The estimated yearly electricity production is 12705 Mwh (Wombarra: 2778.3 Mwh, Cringila: 9926.7 Mwh), which would be sufficient to meet local electricity consumption. An excess of 17% from Wombarra and 48% from Cringila can be exported back to the grid, which can be used by 3 neighbouring areas. Tiseo (2021) reported that Australia\u27s power sector released 656.4 grams/kWh of CO2 in 2020. Therefore, solar PV panels on all suitable rooftops of both suburbs could prevent 8339.5 tonnes of CO2 emissions. To achieve the goal of clean energy, future development can use the study\u27s findings as a guide. The proposed approach can assist in influencing policies and subsidies to boost deployment. This research can be made more in-depth by taking into account social and economic factors like consumer choices and return on investment, and physically inspecting specific building rooftop impediments

    Sustainable Use of Soils and Water: The Role of Environmental Land Use Conflicts

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    This book on the sustainable use of soils and water addressed a variety of issues related to the utopian desire for environmental sustainability and the deviations from this scene observed in the real world. Competing interests for land are frequently a factor in land degradation, especially where the adopted land uses do not conform with the land capability (the natural use of soil). The concerns of researchers about these matters are presented in the articles comprising this Special Issue book. Various approaches were used to assess the (im)balance between economic profit and environmental conservation in various regions, in addition to potential routes to bring landscapes back to a sustainable status being disclosed

    Weather and crop dynamics in a complex terrain, the Gamo Highlands – Ethiopia : Towards a high-resolution and model-observation based approach

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    Motivation: Ethiopia is one of the Sub-Saharan countries that are strongly influenced by climate fluctuations. These meteorological changes directly affect agriculture and consequently cause disturbances on the regional and local economy. To pinpoint a few crucial issues: (1) the agricultural sector in Ethiopia accounts for 80% of the employment and contributes 45% of the GDP. A relevant factor in relation to this PhD thesis is that the country’s agriculture is by 95% rainfed agronomy. (2) The Ethiopian landscape is composed of complex terrains of the East African mountain system – the Ethiopian Highlands (40% of the Ethiopia’s landmass is elevated more than 1500 m above sea level). This complex orography modulates weather and climate at scales ranging from local to regional. In the region, weather dynamics are mainly driven by both synoptic (e.g. Intertropical Convergence Zone – ITCZ) and mesoscale flows (e.g. lake and mountain breezes). These weather scales ultimately influence the way crops grow. The aim of this study was to evaluate how weather and crop growth vary in a complex terrain and heterogeneous landscape. I focus on the Gamo Highlands, south-west Ethiopia, a mountainous region with two large Rift-Valley lakes in Ethiopia. The crop of interest was potato – a crop that has become popular in Ethiopia, significantly contributing to food security and income, but sensitive to climatic variations. As a research method, I deployed a high-resolution weather and crop modelling approach to describe how the growth and yield of the potato crop depend on the variations in weather. For observation-based studies and for testing the models’ performance, six automatic weather stations were installed and field crop experiments were conducted near the stations. More specifically, this thesis addresses the role of meteorological crop drivers (e.g. the incoming shortwave radiation (SW↓), maximum temperature (Tmax), minimum temperature (Tmin) and precipitation (PPT)) and edaphic variables (soil moisture and soil temperature) on the yield and growth of the Ethiopian potato cultivars. Research methods and findings: In Chapter 1, I reviewed the contemporary global environmental challenge, the Anthropocene geologic era, in relation to the food system in perspective. In this chapter, I cascaded the problem from the global to the local scale. The chapter argued that the global weather models need to be downscaled to the local scales in order to study weather and climate impacts on crop dynamics in complex topographic landscapes such as Ethiopia. In Chapters 2 and 3, I presented the model-observation combined research strategy implemented in this thesis. The temporal and spatial variations in weather and crop dynamics are analysed using data from 2001 to 2010. To this end, the Weather Research and Forecasting (WRF) model is used to simulate weather at coarse (54 × 54 km2) and fine (2 × 2 km2) resolutions during the 10-years. The model is validated with in situ data. The meteorological crop growth drivers (SW↓, Tmax, Tmin, PPT, vapour pressure deficit and wind speed) and soil data from the ISRIC soil database are supplied as inputs to a process-based crop model called GECROS. The 10-year belg seasons WRF model analysis is showed large temporal and spatial variabilities in SW↓, Tmax, Tmin and PPT in the Gamo Highlands. For example, Tmax ranged from 10 °C on the summit of mount Guge to 30 °C in the valley around Lake Abaya and Lake Chamo. Temporally, the belg season of 2006 is identified as climatologically normal whilst the 2008 (driest) and 2010 (wettest) belg seasons are categorized as anomalous years. The temporal variations in simulated attainable potato yield showed a high yield (~20 to 30 t ha-1) during the normal belg season whereas the yield was lower (5 to 10 t ha-1 less than in the normal year) for the anomalous belg seasons (Chapter 2). As compared to the coarse resolution domain, the fine resolution domain is better represented topography and weather variations. Because of the improved representation of topography and weather in the fine resolution domain, the leaf area index (LAI) and the length of the growing season (LGS) simulated by the GECROS model were in the recommended range for potato (LAI of 3 m2 m-2 and LGS of 120 days are simulated). For comparison, modelled values were unacceptably low in the coarse resolution domain (LAI of 1.0 m2 m-2 and LGS of 60 days). It is also interesting to see that temperature and precipitation played opposing roles in the modelled yield, a phenomenon I called a compensating effect. To explain the term, moving up the mountains, the temperature decreases – with a positive effect on yield, and precipitation increases with a negative effect on yield. The lower temperature at higher elevation increases the LGS; as a result, more carbon is allocated to the tubers than in a shorter growing season. The higher precipitation at higher elevation may give rise to soil nutrient loss caused by leaching. Aloft the highlands, temperature and PPT are showed opposite trends, but their effects are balanced out in the ultimate yield (Chapter 3). Chapter 4 presented the Gamo Highlands Meteorological Stations (GEMS) – a network of six automatic weather stations, which were operational since April 2016 in two transects of the highlands. Near to the GEMS network, potato field trials are conducted. I used the GEMS data to study both the mesoscale and synoptic weather scales influencing the Gamo Highlands. Furthermore, I deployed the in situ data to the GECROS crop model. The GEMS data are analysed for belg-2017 showed major differences between the start (February) and the end (May) of the belg season. February and May are more mesoscale and synoptic scale weather system dominated months, respectively. During February, the day-night wind sources showed strong variation. Strong south to south-easterly lake breezes are observed during daytime; whereas, weak and more localised mountain winds are identified during the night-time. In May, the day-night flow contrast was small and the dominant flows were southerly. The location of ITCZ calculated by the NOAA (National Oceanic and Atmospheric Administration) and the GEMS observed sea-level-pressure (SLP) data showed strong correlation. My analysis showed that the low-pressure system (ITCZ) and the rainbelt are not coincided in the Gamo Highlands. The maximum PPT is received in May where the ITCZ is located on average nearly 6° (north) away from Gamo Highlands. During the maximum PPT in May 2017, the southerly moist air masses from the moisture sources (e.g. Indian Ocean) may move to the low-pressure system located to the north of the study area. During the daytime, PPT is less probable as cloud formation was less likely due to the enhanced solar radiation. However, during night-time, the southerly moisture can be trapped in the highlands and orographic PPT can be triggered. This PPT is locally modulated due to the presence of the Gamo Highlands and presence of the lakes. The moisture is crucial for potato agronomy during the belg season. The GECROS model sensitivity analysis, using the GEMS data, showed that model input of constant PPT (belg-averaged) gave the highest crop yield due to improved soil moisture throughout the growing season. Chapter 5 dealt with investigating the role of environmental factors on potato yield and growth in the Gamo Highlands. Here, the GEMS weather and edaphic data are correlated with crop growth variables such as plant height, canopy cover, yield and yield traits. The GEMS and crop observation datasets showed that plant height and canopy cover are strongly correlated with temperature sum (Tsum) with an r2 > 0.95 during the canopy buildup phase (P1). Tsum (d °C) is defined as the sum of the daily average temperatures during the growing season. The crop growth - Tsum correlation is further explained in terms of SW↓ and soil moisture, in which an improved (Gudene) and a local (Suthalo) cultivar showed different responses to SW↓ and soil moisture regimes. Data also showed that tuber yield is poorly explained by meteorological and edaphic data, suggesting further research activity in this regard. When the number of days to crop maturity was between 100-110 days, an optimal tuber yield is obtained. Chapter 6 presented the main findings of the thesis in perspective. Finally, Chapter 7 discussed the key findings in-line with the research questions stated in Chapter 1. Conclusions and perspectives: In complex terrain, weather/climate varies over short distances affecting crop growth. To describe crop growth and yield in the region, a high-resolution weather model, coupled to a crop model is needed. The weather model outputs can be used as input to the crop model. A dense station network installed in a complex topographic region can give us insights on mesoscale flows (e.g. lake-mountain flows), synoptic systems (e.g. south-north movement of the ITCZ) and crop growth (e.g. LGS and LAI). Additional weather stations (e.g. on the lee-side of the Gamo Highlands and east of the Lakes Abaya and Chamo) can give us improved understanding of weather scales and crop growth. Tsum during the P1 is found to be a good predictor of plant height and canopy cover for the Ethiopian potato cultivars. The poor correlation between environmental variables and yield and yield traits suggests more dedicated field experiments should be designed. One of the suggested field experiments is continuous monitoring of the partitioning of dry matter to the tubers to study how crop yield varies as a function of elevation and meteorology.</p

    Contribution of informal shallow groundwater irrigation to livelihoods security and poverty reduction in the White Volta Basin (WVB): Current status and future sustainability

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    Shallow groundwater irrigation (SGI) using hand-dug shallow wells and dugouts is expanding, in the WVB, and is becoming attractive to farmers throughout. SGI is farmer-driven and has developed without any government or donor involvement. The production of vegetables and cash crops during the dry season utilizing SGI has provided farmers with a supplemental source of income and an alternative to seasonal urban migration. Although SGI has been increasing substantially, the extent of this practice is not documented.This project has help assess, the impacts of intensive SGI on sub-basin hydrology, net groundwater recharge farmers' livelihoods and on rural poverty reduction in the Atankuidi catchment a tributary of the WVB with the highest per capita groundwater use
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